Schizotypy and Schizophrenia: The View from Experimental Psychopathology

Schizotypy and Schizophrenia

Schizotypy and Schizophrenia The View from Experimental Psychopathology Mark F. Lenzenweger

THE GUILFORD PRESS New York   London

© 2010 Mark F. Lenzenweger Published by The Guilford Press A Division of Guilford Publications, Inc. 72 Spring Street, New York, NY 10012 www.guilford.com All rights reserved No part of this book may be reproduced, translated, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise, without written permission from the Publisher and author. Printed in the United States of America This book is printed on acid-free paper. Last digit is print number:  9  8  7  6  5  4  3  2  1 Library of Congress Cataloging-in-Publication Data Lenzenweger, Mark F.   Schizotypy and schizophrenia : the view from experimental psychopathology / by Mark F. Lenzenweger.    p. ; cm.   Includes bibliographical references and index.   ISBN 978-1-60623-865-3 (hard cover: alk. paper)   1.  Schizotypal personality disorder.  2.  Schizophrenics—Psychology. 3.  Psychology, Experimental.  I.  Title.   [DNLM:  1.  Schizophrenia—pathology.  2.  Schizophrenic Psychology. 3.  Psychopathology—methods. WM 203 L575s 2010]  RC569.5.S36L46 2010   616.85′81—dc22 2010018676

To Lauren and to the memory of Paul —M. F. L.

About the Author

Mark F. Lenzenweger, PhD, is Distinguished Professor of Psychology at the State University of New York at Binghamton and Adjunct Professor of Psychology in Psychiatry at Weill Cornell Medical College in New York. Dr. Lenzenweger held a professorial post at Cornell University for 11 years, where he was a member of the tenured faculty. He moved on to Harvard University, where he chaired the Quantitative Methods Committee in the Department of Psychology, as well as helped to relaunch the clinical science program there. He left Cambridge, Massachusetts, to return to upstate New York to accept an interarea professorship in clinical science, cognitive science, and behavioral neuroscience in the Department of Psychology at the State University of New York at Binghamton and was promoted to Distinguished Professor in 2007. Dr. Lenzenweger has been recognized as a Distinguished Investigator by NARSAD: The Brain and Behavior Research Fund and is a Fellow of the American Psychological Society and the American Psychopathological Association. The author of numerous original empirical and theoretical scientific papers and editor or coeditor of six scholarly volumes, he maintains active research programs in three areas: schizotypy and schizophrenia, longitudinal study of personality disorders, and quantitative methods. He also continues to see patients in long-term psychotherapy in private practice. Dr. Lenzenweger lives in Ithaca, New York, with his wife, three children, and three cats.

vii

Preface

Schizotypy and Schizophrenia: The View from Experimental Pschyopathology explores lessons I learned in the psychological science laboratory while studying schizotypy and schizophrenia. It raises questions about schizotypy and details my efforts to find answers using the methods of the experimental psychopathology laboratory and related statistical procedures. I examine a host of related conceptual issues, data analytic strategies, and methodological viewpoints that I have found helpful. In framing the book in the form of questions and answers, of discussions of methodological approaches born of necessity, and of clinical anecdotes and research recollections, as well as “stories of discovery,” I hope that the reader will develop an appreciation for those substantive issues that have been and are currently pressing (and interesting) in schizotypy research. Perhaps more important, I hope to convey some sense of how to pursue the answers to the questions and issues posed herein. In short, the theme of this book is “how to think about doing research on schizotypy and schizophrenia.” The book you are holding in your hands grew out of a psychopathology seminar that I have offered over the years at Harvard, the State University of New York at Binghamton, and Cornell. My seminar has consisted of talks given to and discussions with advanced undergraduate students and graduate students in psychological science and has focused on the experimental psychopathology of schizophrenia, schizotypy, and, on occasion,

ix

x

Preface

the personality disorders. My aim here has been to take what seemed most profitable from those seminars—both in form and content—and present it on the page in a manner similar to what I have done in the classroom. The suggestion to present the substantive content of my typically (fairly informal) seminar talks in this form came from Lauren Korfine, PhD. Any conceptual bloopers (which I hope I have avoided) herein are, however, solely my responsibility. I do not try to cover all of the issues, challenges, or problems in contemporary schizotypy or schizophrenia research; rather, those I have sought to explore are relatively small in number but fundamental. For the most part, this monograph is targeted to advanced undergraduate students in psychological science, as well as beginning graduate students in clinical psychological science and experimental psychopathology, particularly those with an interest in schizotypy, schizotypic psychopathology, and schizophrenia. However, many of the conceptual and methodological problems I speak to are relevant to depression, anxiety, the personality disorders, and other forms of psychopathology. As such, this book may serve as a general introduction to “research thinking” in psychopathology. I suspect it may also be useful to psychiatrists-in-training who are in search of an introduction to research methods and the experimental psychopathology perspective. The possibility that my coverage of certain topics or the manner in which I examine them might appear somewhat unorthodox to some readers would be congenial to me. In fact, if one were to see this effort as a little idiosyncratic, that would reflect an assessment with which I would cheerfully agree! Readers are encouraged to make use of whatever they find helpful in these pages. What this book is not is probably just as important as what it is. This book is not a systematic review of all issues relevant to schizotypy and schizophrenia. This book is also not intended to be an exhaustive current literature review of the empirical research in schizotypy. Comprehensive reviews are best reserved for journals catering to such reviews—for example, Psychological Bulletin—and, optimally, would take the form of meta-analyses (as opposed to traditional qualitative literature reviews).

How I Got Here Students frequently inquire of me, “How did you get into psychopathology research?” or “Was there some important event that got you interested in schizophrenia?” or “How can you be a clinician and a researcher in psychopathology at the same time?” Some students often simply ask me, “How did



Preface

xi

you get here?” In my college application essay, I held forth earnestly on my intention to become a mammalian zoologist when I “grew up.” I was drawn to the complexities of animal behavior as I had watched (really marveled at) the behavior of any number of creatures in the wooded areas around my home in then quasi-rural (not-quite-yet-suburban) Maryland. How did the gray squirrel communicate through tail movements? How many sunflower seeds could a chipmunk carry in its cheek pouches? How was it that our Labrador retriever was drawn to the water, even on cold February days? Was it not terribly cold for her to swim in the Chesapeake Bay with ice forming on her ears? The questions always popped into my head, and the field of zoology intuitively felt like the intellectual place where I wanted to spend my time. To make a long, and somewhat strange, story short, I trekked to Upstate New York for college, and I ended up studying psychology at Cornell University in Ithaca. I was drawn to the study of individual differences, taking many courses in personality, psychopathology, and related biopsychology, as well as neurobiology (it was not called “neuroscience” then). I had the good fortune to be guided in my studies by my advisor, Richard B. Darlington (a University of Minnesota PhD), and inspired to probe experimental psychopathology by Robert H. Dworkin (a Harvard PhD). In short, Bob introduced me to the experimental psychopathology enterprise and the excitement therein, whereas Dick showed me the wonderful world of probabilistic and statistical thinking. They provided the foundation and framework for “how to think” about psychopathology. I was drawn early to schizophrenia, in part due to academic interests, as well as clinical experiences in a clerkship placement at the local state psychiatric hospital. My undergraduate academic interests ranged widely in the realm of personality and psychopathology writing, for example, on schizophrenia as a manifestation of a Jungian kingship archetype, the evidence for diazepam (Valium) addiction, and, believe it or not, attentional dysfunction in schizophrenia. (I actually still have those term papers in the basement.) My undergraduate psychiatric fieldwork clerkship experience was indeed a “turning point,” as the developmental psychopathologist Sir Michael Rutter says.1 I had been spending time on a weekly basis visiting 1 Developmentalists (e.g., Rutter & Rutter, 1993) often speak of “turning points” or critical junctures in the developmental pathway and, to my mind, there are particularly rich encounters with mentors and colleagues that can serve this function in one’s professional development. For the beginning experimental psychopathologist, it may seem daunting or anxiety provoking to reach out to senior investigators and theoreticians; however, my advice is to do so. The potential rewards in doing so can be immense.

xii

Preface

with a chronically ill elderly woman at the Willard State Psychiatric Hospital2 as part of our psychopathology fieldwork course on “helping relationships.” This woman was essentially mute, disconnected from any interpersonal connections, and seemingly absorbed deeply in some sort of inner preoccupation. Was she really thinking of anything? Was she showing a form of a negative symptom known as “alogia,” or the absence of thought? Who knows? All I knew was that she was deeply ill with schizophrenia, had been ill for decades (really since she was a young woman), and never sought to make contact with the outer world. After weeks of sitting with her, making small talk about the weather, about the beauty of the fall foliage and the stunning view of Seneca Lake (one of the larger Finger Lakes) from the hospital grounds or, more mundanely, about the new paint in the day room, I was convinced that I would never make contact with her as a human being. Then, one day, she looked at me, smiled a very warm smile (heretofore, she had had a wooden, expressionless face), and handed me a candy, a Goetze’s caramel cream. She said, “Would you like a candy?” I was dumbstruck! I had broken through. There was a person in there, her brain was still working, she could relate after all. My goodness, what a terrible intrapsychic prison in which to live. Was this really happening? (I had been told, “Don’t bother, she’ll never talk to you, she is an old chronic schizophrenic.”) The supervising clinical psychologist who witnessed this interaction nearly fell off his seat, and he asked me, “What did you do?” I had no idea what I had done, other than be a human being. I did know that I was completely taken with this experience, this disease, the inhumanity of it, and the challenge it represented. For me this was the very beginning of allowing clinical experience and observation to guide a scientific pursuit. (And, by the way, I still have that caramel cream candy in my desk.) I finished college at Cornell and went to graduate school at Yeshiva University in New York City. In moving to New York, I sought to have the rich clinical experiences that are so typically found in a large metropolitan area and to be immersed in clinical psychodynamic thinking. What! Hold the phone, psychodynamic thinking? What about the experimental psychopa2 Willard State Psychiatric Center—known initially as the Willard State Hospital near Geneva, New York—once housed numerous long-term, chronic psychiatric patients, many of whom suffered from schizophrenia and other psychotic illnesses. Many of these patients, like the one I describe here, lived out their lives, spanning decades, in the hospital after they were admitted initially, typically as young people. A fascinating account of a number of these patients at Willard can be found in the rich and poignant book by Penney and Stastny (2008).



Preface

xiii

thology of schizophrenia?3 Well, I held an abiding interest in psychodynamic thinking, and, frankly, I was told there was no better place in the world to study it than in New York City. (Indeed, this turned out to be true, and remains true, in my opinion.) My research interests in schizophrenia remained strong, nonetheless, and blossomed alongside my clinical interests. I had the good fortune to reconnect with Bob Dworkin (who had relocated to Columbia University, as well as holding an adjunct position at Yeshiva University). Bob, once again, became an intellectual force in my education as my PhD advisor/chairman. My research interests in schizophrenia found fertile ground in the laboratory of Nikki Erlenmeyer-Kimling and Barbara Cornblatt at the New York State Psychiatric Institute. The long rides on the subway train to “P.I.,” as we called the Institute, provided ample opportunity to read the many books and papers to which I was drawn at this time: the Chapmans’ classic Disordered Thought in Schizophrenia (Chapman & ­Chapman, 1973), Gottesman’s newly released Schizophrenia: The Epigenetic Puzzle (Gottesman & Shields, 1982), and Meehl’s (1973) Psychodiagnosis: Selected Papers. 3 Most

students no longer encounter a course in psychodynamic theory in their undergraduate psychology experience. Often, the only mention of the approach occurs when it is dismissed (or worse, disparaged) as nonscientific by the professor. Unfortunately, many critics of psychodynamic thinking have no genuine training in the approach, nor have they cared for patients (e.g., some of the loudest “critics” have been comparative literature, philosophy and/or English professors). Thus, lacking clinical training and/or experience, their criticisms are frequently misdirected at metapsychological aspects of psychoanalytic theory (see Klein, 1976, for a rigorous intellectual discussion of clinical theory vs. metapsychology), which are aspects of the dynamic corpus long abandoned by most informed dynamically oriented clinicians and theoreticians. The dropping jaw of the humanist who is informed that modern psychodynamic thinking has little to no interest in metapsychology is rather striking to observe. Modern dynamic thinking is concerned with clinical theory. Many of the clinical insights gleaned from the psychodynamic treatment (e.g., behavior has meaning; transference and resistance; anxiety leading to defensive psychological maneuvers; the reality of unconscious psychological processes) are used in varying forms across a wide range of psychological interventions, either implicitly or explicitly. Moreover, contemporary psychological science maintains a strong interest in many constructs and processes rooted in psychodynamic observation (see Westen, 1998). So when one of my patients unknowingly removes the wedding band from his finger while telling me his marriage is “just fine” during a psychotherapy session, I seize the clinical opportunity to probe the meaning of this behavior (in this instance, the patient burst into tears about his dysfunctional marriage). Psychologists open to dynamic clinical concepts are in good company with this interest. Those who visited the office of the late Regents Professor Paul E. Meehl, the leading intellectual light in psychological science in the last 100 years (and a University of Minnesota “dust-bowl” empiricist PhD!), would see a psychoanalytic couch in his office and a picture of Freud on the wall. The real scientific question involved here is simple—“Does psychodynamically oriented treatment work for certain patients?”—and the answer, based on empirical data, is yes (see Clarkin, Levy, Lenzenweger, & Kernberg, 2007; Leischenring & Rabung, 2008). Clearly, an interpretive psychodynamic approach is not indicated for psychotic illness (e.g., schizophrenia), although empathy, understanding, and an awareness of the impact of the illness on the self are surely appropriate.

xiv

Preface

My Intellectual and Professional Pathway to Paul E. Meehl A second “turning point” of critical importance for my intellectual development came (literally) in the form of an oversized envelope, stuffed with reprints, from Professor Paul E. Meehl (University of Minnesota). Colleagues have often asked “How did you come to know Paul Meehl?” or “Were you a student of Meehl’s?” I never studied at Minnesota; rather, my connection with Meehl developed organically through reading his work and, later, through my research in schizotypy and taxometrics. Nearly 30 years ago, as a graduate student, I became interested in ­Meehl’s writings and essentially pursued a self-directed study of his work. His 1962 classic article “Schizotaxia, Schizotypy, Schizophrenia” (Meehl, 1962) captured my imagination, and I had the good fortune to have come upon a copy of the unpublished, magnificently rich, 127-page-long manuscript “Memo to Lykken on Schizophrenia Research Strategy” (Meehl, 1966). In reading his papers on schizophrenia, genetics, and methodological issues, I saw numerous references to the Manual for Use with Checklist of Schizotypic Signs (Meehl, 1964); however, I had never seen the document itself. So, convinced this Manual must contain immense clinical wisdom (which I was told was the case by those who had read it), I wrote to Meehl to request a copy and hoped that it and other reprints were still available. I was also having difficulty locating his 1970 paper “Nuisance Variables and the Ex Post Facto Design” (Meehl, 1970). What happened next, quite honestly, changed my career. Namely, Paul sent me the Manual and a stack of reprints that was thicker than the Manhattan White Pages (which at that time was nearly 5 inches thick!) and suggested I read all of them after I finished the Manual. The Manual did include immense clinical wisdom but, more important, opened the door to a connection with the scholar and his ideas. There was something magically transformative about those papers (yes, I know, scientists are not supposed to talk about things such as magic), in addition to the brilliance that emanated from nearly every line of prose. Simply put, my fascination with schizotypy was born of these papers. This “schizotypy” notion pulled me in and struck me as a potential gold mine of ideas, as well as a major lever with respect to the elusive nature of schizophrenia proper. Some years later, when I was an assistant professor at Cornell University in 1989, after the appearance of my report in the Archives of General Psychiatry, which documented the relationship between the Perceptual Aberration Scale (Chapman, Chapman, & Raulin, 1978) and unexpressed schizophrenia liability (Lenzenweger & Loranger, 1989a), I received



Preface

xv

a delightfully spirited letter from Paul encouraging this line of work. What a reinforcing pellet that was for a beginning assistant professor! However, what really opened up channels of communication came about through a moment of confusion in working through one of Meehl’s equations in a taxometric paper and the text associated with the equation.4In short, my then collaborator (Lauren Korfine) read the taxometric material to mean one thing, and I gleaned yet another meaning from the same text—clearly, as we were not engaged in a deconstructionist exercise, one of us was wrong. What to do? Telephone Professor Meehl directly, naturally! Somewhat nervously, I called Meehl and stated that we needed help deciphering some taxometric material. He was intrigued and asked me to read the “offending text,” which I did. After a pause, which seemed to last a long time, Paul exclaimed, “Damn, that is bad prose, isn’t it! I can see how you guys come away with two different meanings!” We sorted out the prose and the math (Lauren was right, by the way) and so began a rich and rewarding professional association and friendship with Paul. This long-distance connection (via postal correspondence, e-mails, and phone calls, as I was in Ithaca or Cambridge and Paul was in Minneapolis) provided me with intellectual sustenance for years. I cannot begin to describe the total intellectual impact Paul had on my scientific approach, but I know this relationship deeply affected the manner in which I regard psychopathology and research methods (and it continues to do so). One might wonder, What is the point in sharing all of this auto­ biographical experience? Is Lenzenweger having a “TMI (too-much­information)” lapse here? The point is simple: The road to discovery in science is rarely linear; it is filled with interesting twists and turns. Moreover, serendipity plays a role (which many scientists will only acknowledge in private) in the origin of ideas and their intellectual development. Importantly, in the case of psychopathology research, clinical observation serves as a vast well of hypotheses and possible avenues for exploration. I have shared 4 At

the time we were doing this work (unlike now), there were no readily available computer programs to do the necessary calculations. In order to conduct a taxometric analysis, one needed to write the equations in computer code and conduct the analyses step by step. Needless to say, this approach took more time; however, to my mind, it represented an excellent way to learn the underlying logic and computations involved in taxometric analysis. I recommend strongly that any student interested in taxometric analysis work through an entire computation by hand to gain an appreciation for the numerous considerations that play into an analysis. Of course, it goes without saying that this handson equations-level understanding of nearly any statistical technique is preferable (at least at the beginning) to the “point-and-click” approach in which the statistical procedures occur in something of a “black box” for most users.

xvi

Preface

a glimpse into my own journey for pedagogical purposes. The path is not linear, despite what one might hear or be told, and one must be open to that nonlinearity, as it can lead to important hypotheses. I have had the good fortune to have had many other individuals serve as teachers, mentors, and/or guides for me in one capacity or another. Barbara A. Cornblatt and Nikki Erlenmeyer-Kimling, also members of my graduate doctoral committee, provided an outstanding early intellectual laboratory environment at the New York State Psychiatric Institute/ Columbia University while I was in graduate school. Armand W. Loranger served as my postdoctoral preceptor at the Weill Cornell Medical College (formerly Cornell University Medical College) and has remained a valued colleague, collaborator, and friend over the decades. Armand’s affection for descriptive phenomenology, classification, and diagnosis provided me with a peerless foundation in descriptive psychopathology and appreciation for exacting standards in diagnosis and research. I am extremely fortunate, as well, to have been the recipient of transformative intellectual generosity from Brendan A. Maher and Irving I. Gottesman, two of the undisputed pillars of experimental psychopathology and psychiatric/behavioral genetics, respectively, and both true professors. Sadly, Brendan A. Maher passed away shortly before this book was completed. Others have given generously as well to my education through productive scientific collaborations, consultations, and, importantly, scholarly discussion: Loren J. Chapman, Jean P. Chapman, Dante Cicchetti, John F. Clarkin, Richard A. Depue, William M. Grove, Philip S. Holzman, Jill M. Hooley, Jerome Kagan, Lauren Korfine, Stephen M. Kosslyn, Steven Matthysse, Ken Nakayama, Gillian A. O’Driscoll, Deborah L. Levy, Sohee Park, Richard E. Pastore, Robert R. Rosenthal, Donald B. Rubin, Sir Michael Rutter, David A. Silbersweig, Niels G. Waller, Jerry S. Wiggins, John B. Willett, and Leslie J. Yonce. These individuals have collectively taught me “how to think” about psychopathology and research methodology. I have often felt over the years that if I could do the same for my students, then I would be doing them a real service. Here a disclaimer about mentioning names—my intention is twofold: (1)  give credit where credit is due and (2) make this story more human and place the ideas within an intellectual history. The reader of this volume will quickly come to appreciate the high esteem with which I regard clinical observation, insight, and experience. I have been most fortunate here as well, having had the wonderful and massively enriching experience to work with a number of master clinicians over the years, including Jay S. Kwawer (William Alanson White Institute), L.  Mark Russakoff (formerly of Weill Cornell Medical College), Otto F.



Preface

xvii

Kernberg (Weill Cornell Medical College), and Robert D. Stolorow (Yeshiva University). Finally, I am grateful to the late Morton Bortner, who “took a chance on me” in supporting my admission to graduate study in clinical psychology at Yeshiva University. My professorial appointments have spanned Cornell, Harvard, and the State University of New York at Binghamton. Throughout my career, I have also maintained a fruitful and invigorating connection with the Department of Psychiatry at Weill Cornell Medical College. Jack D. Barchas, head of the Cornell psychiatry department, has been a generous sponsor and steady advisor over these many years. The late Jeremy R. Knowles, former Dean of the Faculty of Arts and Sciences at Harvard, was steadfastly supportive. Jean-Pierre (Peter) Mileur, former Dean of Arts and Sciences at the State University of New York at Binghamton, created and maintained a first-rate academic environment for me at Binghamton, for which I am grateful. In this context I also thank NARSAD: The Brain and Behavior Research Fund and the National Institute of Mental Health for their support, in part, of my research studies. I have met some colleagues over the years who have (to my mind, at least) done all they could to limit, reduce, and even eliminate their time in the classroom. This attitude toward teaching is one that I simply cannot comprehend. Certainly administration of RO-1s and the slog of Kuhnian “normal science” pales in comparison to the intellectual excitement of the seminar room, I should think. Let’s face it—virtually none of us in psychology or psychiatry is going to Stockholm to collect a Nobel Prize. Teaching is, arguably, the most important thing we will ever do, and it is a rare privilege indeed. Thus, I give special thanks for the honor I have had to actively and continuously teach over the past nearly 25 years at Harvard, Cornell, and the State University of New York at Binghamton. In short, my students have taught me many things, and, to be sure, they are in no small measure responsible for this book. For me, writing this book has been a genuine adventure, one that consistently brought me into contact with numerous wonderful colleagues who gave freely of their time and input. Many people provided helpful insights, observations, anecdotes, and, importantly, encouragement as this book has taken shape, and I thank them for their interest and energetic support. I am particularly grateful to Irving I. Gottesman, the late Brendan A. Maher, Deborah L. Levy, and Niels G. Waller for fielding many queries regarding one matter or another as they came to my mind during the writing process. A number of other thank-yous are also in order. I am especially grateful to Seymour Weingarten at The Guilford Press for both his consistent sup-

xviii

Preface

port of and interest in this project as well as a near endless level of patience (waiting for it to get done!). I could not have asked for a better editor. I would also like to thank the library staff members and express my gratitude for the library resources at the State University of New York at Binghamton, Cornell University, and Weill Cornell Medical College. A gracious thank-you is also due my community of friends in Ithaca—most of whom are not psychologists and have no sense of what “schizotypy” is, but who were unflagging in their support of this project. “How’s that book coming along?” was something I heard from these friends many times at Gimme Coffee, a café in Ithaca that served as my ersatz academic office while I prepared much of the manuscript. Finally, portions of this book were written in Monteverde and Montezuma, Costa Rica, during my sabbatical year (2007–2008), and I am grateful to the many “Ticos” and ex-pats who spoke encouraging words, raised thoughtful layman’s questions about my topic, and provided a wonderful work environment that helped to move this project forward. Finally, of course, my deepest love and gratitude to Lauren, my life partner and wife, for encouraging me to follow my own path for this book, as well as to our children Julian, Anya, and Sage Phoenix, who kept asking me if I was working on my book (and allowed me to do so) and waited patiently for its completion. To the reader, again, take what you find helpful in this book and put it to use in your work. In the immortal words and spirit of Woody Guthrie, “Take it easy, but take it.” Mark F. Lenzenweger Ithaca, New York

Contents

Part I.  Schizotypes and Schizotypy   1. “Welcome to the Machine”

3

Part II.  The Experimental Psychopathologist’s Toolbox   2. Reliability, Validity, and How We Collect Data

23

  3. Practical Tools and Pragmatic Issues

57

  4. Analytic Heuristics, Caveats, and Soapbox Moments

88

Part III.  Schizotypy Viewed from the Laboratory   5. Recognizing the Schizotype

117

  6. Begin with a Model

141

  7. Genetics, Genomics, Phenotypes, and Endophenotypes: The Challenge of Complex Disease

177



xix

xx

Contents

  8. Probing Critical Neurocognitive Endophenotypes: Attentional Dysfunction, Executive and Working Memory Functioning, Eye-­Movement Dysfunction, and Thought Disorder

236

  9. Motion and Touch: Simpler May Be Better

267

10. The Schizotype through Time . . .

298

11. Now, Just What about This “Type” Business in “Schizotype”?

330

Part IV.  Reactions, Reflections, and Projections 12. Thoughts on Impediments, Imaging, Environment, Intervention, and Innovation

363

Appendix A.  Summary Rating Sheet from Manual for Use with Checklist of Schizotypic Signs

387

Appendix B.  Selected Quantitative Measures of Schizotypy

390

Appendix C.  Getting Started: A Provisional Reading List

391

References

393

Index

435

Part I

Schizotypes and Schizotypy

Chapter 1

“Welcome to the Machine”

My research interest in schizotypy and schizotypic psychopathology crystallized in a critical clinical moment during my clinical training at The New York Hospital–­Cornell Medical Center/Westchester Division. I had the good fortune to be there when trainees (both PhDs and MDs) were still taught to “talk to their patients”,1 that is, to try to understand the experience of a patient and to attend to his or her intrapsychic and interpersonal processes (in addition, of course, to learning all about modern classification, diagnosis, and psychopharmacology). There, we were asked to conduct psychiatric interviews with patients in a weekly case conference. The patients for the conference were selected from the case panels of one’s peers, and the goal of the exercise was to gain a diagnostic impression and understanding of the patient by interview. One’s interviewing style was, of course, subject to considerable scrutiny and critique by both one’s supervisors and peers. One day, I was to be the interviewer, and I met the patient selected for interview outside the conference room. He seemed rather emotionally flattened (but not depressed), dressed somewhat oddly (with an oversized jacket on 1 By

the late 1980s the impact of a managed care approach to health care in the United States was being reflected in the reorganization of psychiatric and clinical psychology training programs. At the time, most emphasis was placed on selecting the right medication for a patient and lesser emphasis was placed on the development of finely tuned empathic psychotherapeutic skills. Although this probably seems rather odd, given what one often thinks of when considering what many clinical psychologists and psychiatrists are supposed to do, it was largely true nonetheless. A result has been the emergence of a new cohort of clinicians who actually have relatively weak clinical skills.



3

4

SCHIZOTYPES AND SCHIZOTYPY

a warm day), and he was wearing dark sunglasses (indoors). I introduced myself, shook his hand, and began to describe what would happen in the next 45 minutes or so. He interrupted me to ask, “Are you taking me into a star chamber? Is this the machine? Is this ‘Welcome to the Machine’?” I reassured him that the conference room was neither, nor was it the Camera stellata from English history. I asked him what he had in mind. He told me that he frequently saw the shape of things change before his eyes and that he often felt that he saw colorful objects sail through his field of vision. “Do you really see these things?” I asked. He responded with, “Sort of yes, sort of no; I don’t really believe anything is there and I know things don’t really change their shape.” “Are you super anxious when this sort of thing happens?” I followed. “Nope, not really, not at all,” he said. “Are you really anxious now?” I asked, expecting him to say something in the affirmative (most patients do get anxious before a case conference experience). He responded without any real emotion, “No, I am not particularly anxious, but, can you tell me, is this a star chamber? Is this the machine?” “No, it is not,” I replied, though I was perplexed by what he had in mind. I was fascinated by what this young man described as perceptual aberrations. We entered the conference room. He surveyed the trainees seated about the room and asked if he could leave. I responded with an old Harry Stack Sullivan interviewing technique, namely, we sat with our backs to the group in chairs set at an angle to one another. He immediately seemed more at ease. In the interview that followed, it became very clear to me that this fellow did not like being around people (he felt odd, out of place, “different”). He found social contact to be a stressful and aversive experience. His lack of connections to other people in the world was offset by an intense immersion in the inner world of fantasy and unusual perceptual experiences. What was especially clinically interesting was that he was clearly not psychotic (i.e., he was not suffering from schizophrenia or some other psychotic illness). Quite simply, so began my interest in the schizotype, the experience of the schizotype, schizotypy as a theoretical construct, perceptual aberrations, and the potential connections between schizotypy and both schizotypic psychopathology and schizophrenia.

Getting Oriented The focus of this book is lessons I learned in the experimental psychopathology laboratory while doing empirical research on schizotypy and schizo-

Welcome to the Machine

5

typic psychopathology. The place to start is phenomenology and description.2 I have always found it useful to review several cases that convey the essence of what is meant by schizotypic psychopathology. In our observation of these cases, we consider both the signs and symptoms of schizotypic psychopathology in the form of vignettes. For our purposes, a sign is some behavior, feature, or other characteristic that we can observe with our own eyes, whereas a symptom refers to a thought, feeling, or other aspect of psychological life that an individual reports to us (sometimes in response to a question or via spontaneous expression). Let us consider the following individuals. None of these individuals has schizophrenia, nor could all of them be diagnosed with a DSM-IV schizophrenia-­related personality disorder, yet they are all schizotypes. •• Case 1: Dennis is a 24-year-old single male graduate student who is studying physics at a research university. He leads a socially isolated life and has but one “friend,” with whom he has esoteric “talklets.” Occasionally, he speaks briefly to his peers in the graduate program; they refer to him among themselves as “the loner.” The word talklet is one that he uses, and he assumes that a listener will understand its meaning. For him, a talklet refers to a relatively brief conversation with another person. Most of these conversations are short in duration, often rather one-sided, with Dennis simply “speaking at someone.” Dennis is rather unaware that others experience his “talklets” in this manner. He claims to feel no strong emotions, feeling neither joy nor sadness ever. The only emotion he seems to feel is anxiety, typically when he is in the presence of other people. He is not so much concerned that he will do something foolish or embarrass himself in front of other people; rather, he simply finds social encounters to be aversive, unpleasant, and unsettling. The anxiety he feels is ever present in all his social interactions, except with his elderly parents. His speech can difficult to understand due to odd word usage. For example, he speaks of “technicalizing” with his friends, assuming, again, that a listener will know what this word means. According to Dennis, technicalizing means talking about anything that “implies a mathematical basis.” He frequently thinks neutral events have “special relevance” for him, for example, he thinks (but does not believe) that shopkeepers set up their window displays with him in mind. Dennis often seems to misperceive aspects of his body, such as think2 Many

psychiatric and clinical psychology trainees jump straight into the intricacies and puzzles of an individual’s life in an effort to understand a patient. Moral: Start simply; start with phenomenology.

6

SCHIZOTYPES AND SCHIZOTYPY

ing that his hands momentarily seem misshapen or larger (although, again, he does not believe anything has really happened to his hand). •• Case 2: Stephen is a 51-year-old, single male who works for the U.S. Postal Service, typically during the midnight shift. He rarely speaks to his coworkers beyond relatively superficial greetings. Instead, he focuses on “sorting the mail in his cage,” as he terms it, and he normally hums musical tunes quietly while he works. Stephen usually sleeps on the couch in his work clothes after returning home from his job, often leaving the lights on in his apartment. He uses the couch even though he has a comfortable bed. He lives alone, shares his apartment with a small dog, and rarely ventures out except to do errands or go to work. Stephen never speaks to his neighbors, frequently passing them in the hallway without making any kind of eye contact or showing any sort of recognition that another human being is nearby. His face is essentially expressionless most of the time. In conversations at work, his statements are brief, consisting of few words, and at times his expressions are difficult to understand. For example, he said the following to his supervisor when describing how hard it was to open some boxes: “The outer exterior of the box seemed to be expressed outward, which hardens the work with such cardboard structures.” He describes seeing trails of yellow, red, and blue light following behind stars in the evening sky, and he feels these colors have special significance for him, namely suggesting that his inner nature is “astral.” Just what astral means is not particularly clear; he is distinctly not New Age in outlook. Stephen is reluctant to go into banks because he feels he might be observed closely, and he is worried that bank tellers might try to “cheat me a little.” When some U.S. currency changed its design, Stephen reported that he didn’t like using the newly formatted currency. In fact, after receiving some “new” 20-dollar bills from the ATM, he entered the bank, uneasily, to request that the bank teller exchange his money, changing the “new 20s” for “old 20s.” When asked why he wanted to do this, Stephen said to the teller, “I’m not sure about the new money.” He often seems awkward (e.g., holding his arms in odd postures) and nervous, frequently rocking back and forth from one foot to another. •• Case 3: Alice is a 33-year-old single woman with a BA in English, and, despite her educational attainment, she works at a low-level clerical position at a local bed-and-­breakfast inn. Throughout the day she spends a great deal of time daydreaming, typically envisioning herself as a magazine writer, and she rarely speaks to others unless spoken to first. She reports

Welcome to the Machine

7

having a consistently “uneasy” feeling when around others and on occasion says, “interacting with others is painful for me, it is associated with the same pain you feel when your knuckles hit and run across a carrot grater.” She has experienced herself as “different from others” for as long as she can remember and sometimes feels as though she gets “all mixed up or confused” when doing mundane things, such as shopping or taking a walk. Her parents report that she was somewhat awkward and clumsy as a child and had trouble manipulating small objects such as puzzle pieces or small toys. She often feels that numbers, symbols, and certain images are imbued with a magical power of sorts, and she will alter her behavior depending on the numerals appearing in the date. When walking down the street, she is especially attentive to the expressions on the faces of those who pass her. To her, a smile on the face of a stranger is often taken to mean that the stranger knows something about her (usually something undesirable). She has never dated and reports having no sensual feelings or sexual desires. Her relatives tell her that her speech is hard to follow. She often stays up late into the night reading philosophy and religious texts. •• Case 4: Claire, a 27-year-old married woman, works as a code writer for a large software company in a Northern California city. Claire tends to dress in an unusual manner, often wearing clothing that often seems too heavy for the warm climate in which she lives. Throughout childhood she had only one friend, whom she continues to talk to on the phone on a weekly basis. She has no other close friends to speak of beyond her husband. In college, she pursued a double major in German literature and computer science. She met the man she would later marry in a college computer science class. He told her that he was drawn to her because she was “quirky” and “eccentric.” Claire has described an “unusual ability to sense what will happen in the world,” something akin to a “sixth sense,” and she maintains that it goes beyond simply intuition. She also feels that she can influence events with her mind; for example, she thinks that she can make a red light turn green (though she denies that she really “believes” she can do so). She collects small figurines and amulets that she feels help her to “find her way through the world.” Claire’s coworkers do not know her very well, but they find her “pleasant enough, although sort of flaky.” When speaking to most people she appears ill at ease and seems relieved when the conversation ends. On occasion her grimaces or giggles in response to some aspect of a conversation are regarded by other people in the conversation as odd or “weird.” Her face, otherwise, displays little in the way of emotion.

8

SCHIZOTYPES AND SCHIZOTYPY

A First Pass at Terminology and Organizing Our Concepts Clearly, each of these people seems very interesting in certain ways. In some instances they reveal unusual beliefs or behaviors. Some descriptors tend to be relevant to virtually all of them, such as odd or eccentric. The emotional characteristics of these individuals seem a bit “off” as well; the central theme in the phenomenological picture is that they show minimal displays of emotion but have a fair amount of anxiety floating about in their inner experience. It is also interesting to observe that some of the behaviors, beliefs, and experiences seem quite distinct from normative psychological functioning (e.g., magical thinking, i.e., belief in forms of causality that are clearly at odds with conventionally accepted forms of causation or perceptual aberrations, disturbances in the perception of the shape or configuration things), whereas others might be construed as more extreme versions of commonly occurring dimensions of experience (e.g., sociality, or degree of engagement with the social world). This is a fascinating issue that raises deep conceptual issues and calls for complex research approaches; we return to this issue more fully later on. For the purposes of our discussion, this person whom we seek to understand will be known to us as a schizotype, revealing what we term schizotypic psychopathology. None of these individuals has clinical schizophrenia. Some, but not all, of these individuals might be diagnosed with schizotypal personality disorder in the Diagnostic and Statistical Manual of Mental Disorders (4th ed, text rev.; DSM-IV-TR; American Psychiatric Association, 2000). Schizotype, schizotypy, and schizotypic psychopathology, as concepts, are developed throughout this book. Not all schizotypes present clinically in a similar fashion; in short, they do not necessarily share the same features. Moreover, the features that do exist within this class of psychopathology vary in intensity, as well as in their impact on social or occupational functioning. The cases described here could be considered to contain dilute components that are suggestive of schizophrenia, the profound psychotic illness characterized by massive disorganization of thought, perception, behavior, and emotion, as well as gross impairments in occupational and social functioning. However, none of those patients described is psychotic. Individuals with schizophrenia display hallucinations, delusions, thought disorder, lack of social relations, diminished motivation to function, and, at times, highly bizarre behavior. A primary assumption in this discussion is that schizotypy is an underlying (invisible to the naked eye) liability for schizophrenia. By implication, all people with schizophrenia harbor schizotypy. However, one may harbor schizotypy that reveals itself at the cognitive, interpersonal, and

Welcome to the Machine

9

emotional levels in ways other than full-blown psychosis, and this is precisely the sort of manifestation depicted in the four preceding cases.

The Breadth of the Schizophrenia Phenotype: Implications for Defining the Nonpsychotic Schizotype The definition of schizophrenia proper has had a complex history (Lenzenweger, 1999b). When first described by Kraepelin (1919/1971) and Bleuler (1911/1950), the working breadth of the disease phenotype was rather narrow, which meant that a distinctive and severe set of features constituted the illness and the diagnosis was not given frequently. This traditional, narrow definition seemed to stay largely in place among European psychiatrists and psychologists. From the 1920s through the 1960s, however, the definition of schizophrenia in the United States was broadened excessively. Indeed, during my training days at the New York State Psychiatric Institute, some long-term observers of the definition of schizophrenia would often quip that, “in the 1950s, everything that walked west on 168th in Manhattan had a schizophrenic core” (one walked west on 168th Street to go to the Psychiatric Institute from the New York City subway). The 1950s represented the period in which, arguably, the breadth of the definition of schizophrenia was really at its greatest. During that time, “everyone could develop schizophrenia,” in the minds of some clinicians. It was the heyday of the “psychotic core” concept, which meant that if one pushed hard enough (with stress) and dug deeply enough (clinically), one would find psychosis in every person. According to this view, we all possessed the capacity to develop schizophrenia (not merely a psychotic phenomenology that most of us would show with enough sleep deprivation or with a dose of LSD, but rather true blue schizophrenia). This vision of schizophrenia owed much to the overzealous overextension of the psychodynamic model to schizophrenia. Interestingly, this development would likely have been to the chagrin of both Sigmund Freud, the Viennese neurologist who founded psychoanalysis and who thought the origins of schizophrenia would be revealed as genetic, and Carl G. Jung, the Swiss psychiatrist and psychoanalyst who founded analytical psychology and who early in his career studied word associations in schizophrenia, and who thought a “toxin X” would eventually be revealed as the cause of schizophrenia. During the late 1970s and early 1980s, the breadth of the schizophrenia concept in the United States returned to a narrower, more “European-like” width because of (1) concerns about diagnostic reliability, (2) excessive variation in the rates of the schizophrenia diagnosis in the United States as compared with

10

SCHIZOTYPES AND SCHIZOTYPY

the United Kingdom, and (3) reemergence of interest in clinical diagnosis as reflected in explicitly defined criteria and the development of structured interviews (see Lenzenweger, 1999b; Gottesman, 1991). Interestingly, as the definition of schizophrenia returned to a breadth that seemed more consistent with that of the original observers (Kraepelin, Bleuler) during the past 35 years or so, there has been an enhanced level of interest in those individuals who bear some dilute phenomenological resemblance to schizophrenia and who might harbor a schizophrenia liability—­ namely, the schizotype. This modern increased interest in the schizotype has been guided by both rigorous theoretical models and careful empirical research. The interest is fueled by the reality that schizotypes do not have clinical schizophrenia yet harbor the liability for the illness. The connections between schizotypy on the one hand and schizotypic psychopathology and schizophrenia on the other have been established by years of research in the laboratory, including mine, and the logic and methods of such work are emphasized here.

What Are the Clinical Features of the Schizotype? One could sift through the four cases described previously and discern many of the cardinal features of the schizotype. The model schizotype is someone who has relatively impoverished interpersonal relations, often having few friends aside from family members. The manner in which the schizotype speaks and uses language can be rather unusual. Words may be used in an unconventional manner that other people do not readily understand or find confusing. The schizotype may have momentary oddities in perception, for example, seeing objects or body parts briefly change their shape or size, and may think relatively neutral events have special significance for him or her (e.g., thinking that a professor directs a lecture specifically to him or her or thinking that others frequently comment on his or her behavior or appearance). He or she may think that he or she can make things happen, as if by a magical ability, such as “causing” a person to call on the phone just by thinking about that person. Emotions and affect expression are rather atypical in the schizotype as well. A schizotype may display little, if any, affect on the face, often appearing rather blunted or expressionless. He or she may claim to feel little to no emotion. What is particularly interesting is that many schizotypes report feeling highly anxious around people, so much so that many carve out lives that minimize contact with other people. Suspiciousness is also a characteristic of many schizotypes. This suspiciousness

Welcome to the Machine

11

can take many forms, such as frequent concerns about being cheated or conspired against, but it falls short of the psychotic level of delusional beliefs (they do not believe that they are being cheated or persecuted). Many master clinicians and researchers have suggested other important schizotypic signs and/or symptoms (see Chapter 5).

How Does “Schizotypy” as a Construct Connect to Schizophrenia? The signs and symptoms of schizophrenia reflect a psychotic illness in an individual, and understanding the nature of those features is essential for understanding schizotypy and schizotypic psychopathology. In this context, the intended meaning of the term psychotic is critical. It should be understood to have two primary meanings, implying a mental state reflective of illness that (1) is very severe (quantitative meaning) and (2) evidences a break with reality constraints in the realm of perception (hallucinations), thought organization (formal thought disorder), and beliefs (delusions) (qualitative meaning). As noted previously, the early observers of schizophrenia, such as Emil Kraepelin (1919/1971) and Eugen Bleuler (1911/1950), provided the classic descriptions of the illness. Any serious student of schizophrenia should take the time to read these masterworks. However, both of these observers also took careful notice of what we would now term schizotypic psychopathology. How did Kraepelin and Bleuler learn so much about the phenomenology of schizophrenia and schizotypic psychopathology? Although it may seem implausible today, given that most psychiatric patients currently spend less than 3 days in the hospital, the patients in those days lived their lives out, for the most part, in psychiatric hospitals. There, efforts were made to provide humane care as well as refuge for the deeply psychotic person, who typically suffered from schizophrenia or related illnesses, but most never returned home. As a consequence, Kraepelin, Bleuler, and other attending clinicians came to know not only the patients in great detail but also their biological family members. The family members visited their relatives at the hospitals and in doing so they themselves could be observed. It is through these observations, in part, that some of the earliest insights into schizotypic psychopathology were gained. Consider Kraepelin’s and Bleuler’s observations made after years of seeing the biological relatives of people affected with schizophrenia (Box 1.1). It should be clear from these observations that both Kraepelin and Bleuler thought there was some connection between the clinical illness schizophrenia, or really the underlying

12

SCHIZOTYPES AND SCHIZOTYPY

BOX 1.1. Early Observations from Masters of Phenomenology In the families attacked there comes under observation with relative frequency besides dementia praecox a series of other anomalies, especially manic–depressive insanity and eccentric personalities [emphasis added]. . . . The latter are probably for the most part to be regarded as “latent schizophrenias” and therefore essentially the same as the principal malady. —K raepelin (1919/1971) There is also a latent schizophrenia, and I am convinced that this is the most frequent form, although admittedly these people hardly ever come for treatment. . . . In this form we see in nuce all the symptoms and all combinations of symptoms which are present in the manifest types of the disease. —Bleuler (1911/1950)

liability for the illness, and these unusual features observed in the relatives of schizophrenia patients. Kraepelin was struck by the high rate of eccentric personalities among the biological relatives of his schizophrenia patients. Bleuler thought there was a form of the illness characterized by dilute forms of symptomatology suggestive of schizophrenia proper. The implication of these seminal conjectures was really quite profound for the history of schizophrenia research—­namely, that schizophrenia could manifest itself in an alternative form; it need not always appear as the well-known clinical phenotype. These clinical observations laid the foundation stones for the schizotypic psychopathology and schizophrenia connection. However, at the time, the early 1900s, this notion represented a hypothesis.

What Is the Impact of Schizophrenia on Society and Why Do We Study It? Schizophrenia is a profound mental disorder, perhaps the most severe form of psychopathology known to humankind.3 It affects roughly 1 in every 100 individuals and appears across all cultures, countries, and continents. The illness is not a “myth,” not “a sane reaction to an insane world,” nor the result 3 Interestingly,

the case has been made that schizophrenia is a relatively modern illness and has not been among human beings for nearly as long as other illnesses. Gottesman (1991) argues this perspective, and Evans, McGrath, and Milns (2003), in a review of Greek and Roman literature, find no compelling evidence of the illness in classical times.

Welcome to the Machine

13

of “labeling” or a “double bind,” all ideas now considered defunct and recognized as devoid of intellectual merit (although popular during the 1960s and the heyday of the so-­called antipsychiatry movement). Rather, schizophrenia is now widely considered to be a brain-based disorder that involves a substantial genetic component, dysfunctional neurobiology, and as yet unspecified environmental inputs (e.g., birth complications, in utero exposure to maternal influenza, noisome work conditions) that come together to generate the illness. Schizophrenia strikes early in life (late teens, early 20s), can be severely disabling across the life span, and results in rather tremendous economic costs such as those related to direct care, aftercare and support (and rehabilitation), and forgone earnings (due to being lost to the workforce). It is important to emphasize that, with the newer medications available for the treatment of the illness, the typical person so affected does not spend his or her entire life in a psychiatric hospital (as in the days of Kraepelin and Bleuler). Today, many people with schizophrenia pursue fuller lives, with the help of medication and aggressive psychosocial treatment. This is true of contemporary schizophrenia sufferers when compared with those so affected but 20 years ago. However, even today, many schizophrenia patients do not return to the level of psychological and social functioning they had before the illness struck, and they are faced with the challenges of a chronic illness, which reappears from time to time, in their daily living. Clearly, schizophrenia is a major form of psychopathology that is massively disabling; thus we want to try to understand its causes and development, with an eye toward (eventually) prevention. We are motivated in this goal by many factors, not the least of which concerns the cost of this illness to the individual and society. The monetary cost of schizophrenia has been the focus of some careful economic modeling, and the numbers generated by these exercises are staggering. According to estimations (Wu et al., 2005) done using 2002 dollars and prevalence data from the well-known National Comorbidity Survey—­Replication, a large-scale, national epidemiological study of psychiatric disorders, the overall cost was estimated at $62.7 billion. This figure can be further broken down into direct health care cost ($22.7 billion), direct nonhealth excess costs (e.g., living costs; $7.6 billion), and total indirect excess costs (e.g., unemployment; $32.4 billion; Wu et al., 2005). These figures reflect the total economic impact of schizophrenia on society (i.e., the cost posed by the illness in people with the illness vs. the cost had they never been affected by schizophrenia). In England, based on 2004–2005 estimations, the total societal cost of schizophrenia was £6.7 billion (or $22.1 billion; Mangalore & Knapp, 2007). Costs in the United

14

SCHIZOTYPES AND SCHIZOTYPY

States and in England are somewhat difficult to compare because of massive differences in health care costs resulting from large differences in care and support systems. Finally, Knapp, Mangalore, and Simon (2004) estimated the worldwide societal cost of schizophrenia, and, although there is considerable variation across countries, the economic impact of schizophrenia is really quite astounding. Knapp et al. (2004) estimate that between 1.5 and 3% of total national health care expenditures are due to schizophrenia and that “sizeable portions of total inpatient budgets are accounted for by people with schizophrenia” (p.  290). The monetary estimates, of course, do not even gauge the “pain cost” of schizophrenia—by this we mean the psychological pain and anxiety suffered by patients themselves, and by their partners, children, parents, and so on. For example, how can one estimate the cost of the psychological fear and anxiety felt by parents when they receive a 4:00 A.M. phone call from the police indicating that their son was picked up while walking down the interstate highway in the nude claiming that the Central Intelligence Agency was inserting microchips under his fingernails? Or the despair felt by a young woman who had been a talented mathematics major in college when, on emergence of the illness, she could no longer even subtract 3s in a sequence beginning at 100 due to cognitive disorganization from her schizophrenia? One, of course, could argue that the study of schizophrenia is interesting in its own right given the profound deviations in normal human psychological functioning seen in the illness. It is a fascinating and perplexing problem beckoning to be understood. Study of such deviation provides useful information on the nature of normative functioning whereby illuminating the pathological informs the normal (a fundamental tenet of developmental psychopathology; Cicchetti & Cohen, 2006). The challenge to understand the causes of schizophrenia receives most of its urgency and sense of purpose, however, from the pain and cost components associated with it.

What Leverage Does Study of Schizotypy and the Schizotype Offer for Uncovering the Causes of Schizophrenia? Schizophrenia has long frustrated generations of research workers (e.g., it has even been thought of as “graveyard” for psychopathology geneticists, notwithstanding some gains that have been made in recent years), and its specific etiology (Meehl, 1972b, 1977) remains elusive. How best to gain

Welcome to the Machine

15

leverage on this disorder? I argue that this is done best through the study of the schizotype and full incorporation of a schizotypy model in schizophrenia research. The primary thesis of this book, therefore, concerns a conceptual and empirical approach that is intended to provide leverage in our understanding of the fundamental nature of schizophrenia. Moreover, it is argued that a coherent model that stresses several components at different levels of analysis will optimally provide that leverage. The primary working assumption of this argument (as well as the program of research on which it is built) is that schizophrenia is a manifestation of an underlying construct (more about constructs to follow) known as schizotypy and schizotypic psychopathology is to be thought of as an alternative manifestation of schizotypy and, by implication, a variant of schizophrenia liability. The primary utility of schizotypic psychopathology as a unit of analysis (in relation to schizophrenia) is that it potentially represents a clearer window on the underlying liability for schizophrenia per se. How can this be so? The reason for this assertion can be best found in an analogy. Imagine that a house mysteriously burns to the ground, and the fire investigators need to determine what happened. How did this fire start? It is all rather difficult to probe through the ashes and burnt debris to find a valid cause for the fire. Imagine further that the fire actually began in the breaker box that contains the crossroads of the major electrical circuitry for the house. The fire investigator might be able to find the breaker box and the remnants of charred breakers, melted and twisted plastic components, burnt wiring, and so on. However, in this mess of twisted and charred debris, it would be particularly hard to figure out just which specific wire or poor connection was the cause of the sparking that ignited the fire. One could guess, or limit potential explanations, based on what is known about typical breaker boxes; however, the precise unfolding of events cannot be known with certainty after the fact. Imagine further that we had been electrical inspectors and had been able to examine and record the condition and status of the various wiring and connections in the breaker box prior to the fire. If we had been in this position as inspectors, then we could probably say with greater confidence that the two wires without insulation and nearly touching one another could represent a genuine fire hazard. If we had known what was wrong ahead of time (prior to the onset of the fire), then, perhaps, we (1) could understand more fully what gave rise to the fire and (2) could have engaged in preventive intervention (i.e., we could have fixed the wires that lacked insulation). By extension to schizophrenia, imagine that the clinical illness of schizophrenia represents the fire that has already begun. As time goes by,

16

SCHIZOTYPES AND SCHIZOTYPY

particularly during, say, the first 5 years of the illness, the brain begins to manifest illness-­related changes. Thus, in a very real sense, the study of the schizophrenia-­affected brain represents an endeavor that is, by definition, clouded by the illness per se and all its various impacts. To discover the precise site(s) (or nature) of the etiological dysfunction responsible for schizophrenia after the illness has expressed itself is not unlike trying to discover the nature of the wiring problems in the breaker box that caused our hypothetical house fire. This is so because the transition to a psychotic state, along with various associated processes (e.g., medication, institutionalization, deterioration in functioning, stigma associated with a major mental disorder, impact of comorbid conditions, e.g., substance abuse) inevitably color the neurobiological, neurological, cognitive, personality, and social functioning of an individual. Depending on one’s point of view, the clinical illness can merely be seen as “clouding” the picture, and therefore it hampers the search for important clues as to the nature of schizophrenia (though this problem can be overcome with sufficiently clever research designs), whereas another point of view would hold that the causal picture (etiology and fundamental pathologies) becomes opaque with the onset of clinical illness. How, then, should the psychopathologist proceed? The answer to this question, more or less, depends on how one defines the beginning of the illness, as well as how one defines the boundaries of the illness (i.e., Does schizophrenia always look like schizophrenia?). The present discussion is based, therefore, on a second critical assumption, namely that schizophrenia begins long before the emergence of the well-known clinical symptoms of the disorder. Alternative manifestations of liability and early developing pathology are not necessarily easily accepted or easily defined assumptions. For example, simply defining the beginning of the illness can be challenging. One could conceivably take the position that the illness began long before the manifestation of the clinical signs and symptoms of schizophrenia. For example, one could restrict oneself to emerging preschizophrenia, or prodromal, symptoms and behaviors that appear during the buildup to clinical schizophrenia. One would maintain that the “fire” began then. Alternatively, one could hypothesize that the illness begins earlier in childhood and, therefore, examine dysfunctions that are known to be associated with later schizophrenia, such as motoric abnormalities, in the late teens or early 20s. It may actually be the case that schizophrenia or, perhaps more accurately, the pathological processes that reveal themselves in clinical schizophrenia, begin at biological conception. The blueprint for the illness might be laid down nearly immediately and slowly begin to reveal itself through

Welcome to the Machine

17

subtle deviations in neural development, disruption in neurobiological systems, abnormalities in behavioral development, and, later, impaired psychological functioning. The assumption that schizophrenia liability can reveal itself in alternate forms represents a theoretical bridge that both expands what one typically thinks of as the phenotypic boundaries for schizophrenia and, importantly, provides powerful conceptual and statistical tools for illuminating the nature of schizophrenia (Meehl, 1962; Lenzenweger, 1998; Kendler, Neale, & Walsh, 1995). It should be evident that one of these alternate expressions of schizophrenia liability is schizotypic psychopathology. It should be understood, therefore, that schizotypic psychopathology is not merely an analog of schizophrenia; rather, it represents a valid, albeit nonpsychotic, expression of the same liability that underpins schizophrenia. An analog in psychopathology research approaches means utilizing an artificially created—­ typically in the laboratory—­deviation in psychological state or functioning that shares presumably some aspects with a genuine form of psychopathology. For example, analog depression represents a transient emotional state induced in a laboratory for the purposes of trying to understand some aspect of clinical (major) depression.4 In short, schizotypic psychopathology is not an analog for schizophrenia; rather, it is a valid alternate expression of schizophrenia liability. It is the real thing.

A Thumbnail Sketch of the Benefits of the Schizotypy Model Approach In summary, what are the benefits of the schizotypy model approach in our search for the causes of schizophrenia? First and foremost, the study of schizotypic psychopathology provides a “cleaner” window on underlying schizophrenia liability. By cleaner I mean an opportunity to study in the laboratory genetically influenced, neurobiologically based processes (neurocognitive, affective, personality) that are uncontaminated by “third variable” confounds, such as medication, deterioration, and institutional4 Creating

analog depression might involve something like making normal undergraduate students believe that they have done poorly on some sort of psychological task or test and then studying a specific aspect of their cognitive functioning, such as attributional style. One might hypothesize that one could induce a pattern of thinking characterized by seeing the causes for failure as internal to the self, stable over time, and global in its impact, thus bringing about “depression” in the students. The assumption of an analog research approach is that it provides leverage on genuine depression. But to what extent does such analog depression really mimic clinical depression?

18

SCHIZOTYPES AND SCHIZOTYPY

ization. Schizotypic psychopathology represents the breaker box before the fire. Second, the schizotypy model approach to schizophrenia also provides a rich opportunity to discover endophenotypes for schizophrenia liability. Endophenotypes (Gottesman & Gould, 2003; Shields & Gottesman, 1973) represent genetically influenced manifestations of the underlying liability for an illness that are invisible to the unassisted or “naked” eye (Chapter 7). Third, incorporation of valid schizotypy indicators (e.g., schizotypic psychopathology) into genomic investigations directed at etiology and development of schizophrenia will enhance the power of such studies (Lenzenweger, 1994; Brzustowicz, 2007; Brzustowicz & Bassett, 2008). Fourth, via longitudinal investigations, the study of schizotypic psychopathology can elucidate epigenetic factors that might relate to the differences in outcome of schizotypes (i.e., stable schizotypal personality disorder vs, conversion to schizophrenia).

A Word about “Experimental Psychopathology” Finally, it is it is important to define what is meant by experimental psychopathology. Many students in psychological science are familiar with the more traditional subdivisions of the field, such as experimental, cognitive, developmental, clinical, social, industrial/organizational, and so on. Psychological science is beginning to mature, and, as a result, the complexity of the problems that the contemporary discipline focuses on has required the field to realize that many traditionally compartmentalized approaches to human behavior are insufficient for tackling the problems of greatest interest. For example, personality psychology has begun to move away from strictly questionnaire research to incorporate neurobehavioral systems models, affective and emotional science perspectives, and genetic vantage points. The scientific study of psychopathology has also matured and grown beyond the simple psychological testing and descriptive approaches of clinical psychology. For example, one cannot really ponder a complex topic such as schizophrenia without bringing in elements of experimental psychology, psychometrics, behavioral genetics, cognitive science, and all manner of neuroscience. Experimental psychopathology emerged over the past 30 years as a powerful approach to the study of psychopathology. The classic definition of experimental psychopathology centers on the use of the experimental methods and the rigors of the experimental psychology laboratory in the study of psychopathology. This definition and the resulting research subdiscipline owes much to Brendan A. Maher’s semi-

Welcome to the Machine

19

BOX 1.2. On the Nature of Experimental Psychopathology: Lenzenweger’s View Experimental psychopathology is the psychological science discipline that uses the methods of the experimental psychology laboratory in conjunction with quantitative analytic approaches to gain leverage on etiology and pathogenesis of psychopathology, within a brain-based (genomic, endophenotype, neurobiological) diathesis–stressor matrix.

nal volume titled Principles of Psychopathology: An Experimental Approach (Maher, 1966). Maher’s vision for an effective approach to the study of psychopathology has yielded considerable fruit and continues to grow and develop (see Lenzenweger & Hooley, 2003). Incorporating the neuroscience perspective and embracing the technology of neuroimaging, as well as modern genomics, modern experimental psychopathology continues to provide an essential vantage point for seeking to better understand the nature of psychopathology. I would, therefore, offer my own definition of contemporary experimental psychopathology5 (Box 1.2). We unpack this definition, explicitly and implicitly, as we progress through this book. However, at this juncture, we must take a necessary conceptual and methodological detour. This detour is intended to convey some basic notions regarding an effective way to think about doing experimental psychopathology research. The issues covered in Chapters 2, 3, and 4 will be the “balls that one will need to keep in the air” when attempting to unravel complex problems such as schizophrenia and schizotypic psychopathology.

5 Although

most experimental psychopathologists have training as psychologists in the methods of the experimental psychology laboratory, it is important to note that the “experimental psychopathology” perspective is really just that, a perspective. It represents an approach or vantage point. It is not a professional guild; there are no membership cards. Rather, it represents an approach that is founded on shared values embodied in the merits of laboratory-based science. Whereas many experimental psychopathologists began their careers with formal training in clinical psychology, there are many experimental psychopathologists who do not hold that credential. Many psychiatrists (MDs) who have come to laboratory research on mental illness are considered experimental psychopathologists.

Part II

The Experimental Psychopathologist’s Toolbox

Chapter 2

Reliability, Validity, and How We Collect Data

Nothing is so difficult as not deceiving oneself. —Ludwig Wittgenstein, Culture and Value (1984)

The first impulse of many students who ponder the schizotype is to consider how this form of personality organization develops in the first place. Some wonder how the schizotype moved to fully symptomatic schizophrenia in some cases. The urge is to try to answer the “etiological” question. However, in order to bring clarity to any discussion of schizotypy, as well as to extract as much meaning as possible from the research corpus, it makes sense to take a detour through research methods and general principles of experimental psychopathology. Over the next three chapters I discuss what I call the experimental psychopathologist’s toolbox. This toolbox contains a variety of things. I distinguish between what I term conceptual tools versus practical tools. By conceptual tools I mean those ideas and concepts that I have found useful in my own research on schizotypy. The conceptual tools have a bit more to do with providing a “way of thinking” about method problems, data, analysis, and so on. The practical tools are just that—­little tools, tips, and methods

23

24

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

(statistical and otherwise) that enable one to extract meaning and direction from data. Finally, I deliver up a collection of heuristics, caveats, and “soapbox moments” relevant to the conduct of psychopathology research. This list is by no means exhaustive, and if I have left out someone’s favorite tool or methodological issue, I want to emphasize that such an omission does not suggest that I see other topics unfavorably or of little value.

On the Importance of Clinical Observation in Psychopathology Research It is safe to say that very nearly all of the research vectors that I have pursued in the laboratory have begun as clinical observations. Moreover, the clinical observations have taken me to these research areas in a nonlinear fashion, which I would never have predicted. Moral: Allow clinical observation to guide you; to make use of clinical observation, you must learn your phenomenology. In psychopathology research, especially in some of the more research-­focused PhD clinical science training programs, one has the impression that students know a good deal about research but that they would not know a patient if they fell over one. Alternatively, lest anyone feel left out, there are plenty of trainees (and practicing PhD, PsyD, and MD clinicians) who have virtually no clue about research despite what they may have learned in graduate school or medical school. In short, you want to know both realms and for good reason. Excellent clinical observation not only yields better treatment but can also, importantly, be an amazingly rich domain for research hypotheses. Likewise, excellent training in research and the methods of science inevitably makes one a better clinician (even if one is principally a “consumer” of research as a practicing clinician). With respect to the origin of research ideas, the scope and process of clinical observation is ideally suited to the “context of discovery.” My research foci on perceptual aberrations, exteroceptive somatosensory processing, proprioceptive somatosensory processing, and psychomotor performance all represent research directions whose origins could be traced, in part, to clinical observations. The potential richness of clinical observation as a source of research ideas is conveyed in an anecdote related by Brendan A. Maher, “The Hallucinating Man” (Box 2.1). One of the things that people can do very well is recognize patterns in behavior or other psychological phenomena. In clinical observation, the human being as observer can exercise real input, particularly when he or

Reliability, Validity, and How We Collect Data

25

BOX 2.1. The Hallucinating Man: Clinical Observation, Hypothesis Generation, and Insights Gained Brendan A. Maher, PhD A man came to see me in my office at Harvard, having been referred to me by the departmental secretary, who heard him mention that he had a diagnosis of schizophrenia. He had come seeking help, and I explained to him that I could do nothing in the way of treatment, etc., but that he could help me. He, I pointed out, knew schizophrenia from the inside—while I knew it, at best, from the outside. Perhaps he would be willing to tell me about it. He accepted, and we set up a weekly meeting. The topic of hallucinations came up at one meeting mainly because his flow of conversation was repeatedly interrupted by his “voices,” which appeared to emanate from a point in one corner of the ceiling of my office. He would shout at them, saying “Shut up. Can’t you see that I am trying to talk to somebody.” I asked him if he could point to the source of the voice and if he could recognize the voice, and he replied that it was that of a woman friend of the family and that she was continually “correcting” him about his appearance and behavior. At that point I asked him to turn half-right (90 degrees) and, when had done so, to point to the source of the voice. He did so and said that the source had also moved. At the next meeting he came in a state of mild excitement at the discovery that he had made. “Those voices aren’t outside me—when I moved my head the voice moved. The voice must really be in my own head. It must be something about the way I am thinking about things.” I felt that this discovery of his might well be a therapeutic beginning of insight and responded supportively to his new insight. My intentions had not been therapeutic but rather to get a better understanding of what the experience of hallucinations in schizophrenia might be like. We met a few more times, and I think that he had begun to look at his own language and behavior in the spirit of an observer, but he moved from the Boston area and I never heard from him again. Reprinted with permission from Brendan A. Maher (December 4, 2007).

she knows what to look for. Remaining open to the rich heuristic potential of clinical observation is a prerequisite for fruitful research; one can gain only a small number of insights for research from reading the theories or research products of others. Thus, before we ponder the more technical matters of reliability and validity, I take this opportunity to emphasize that clinical observation remains both essential and peerless as a new research idea source.

26

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

Reflections on Reliability and Validity for the Psychopathologist Two of the most important concepts that must be under one’s proverbial belt before one enters the experimental psychopathology laboratory are reliability and validity. The classic treatise on reliability and validity is that of Cronbach and Meehl (1955).1 Reliability refers, in essence, to the repeatability of measurements. If one measures a phenomenon on one occasion with a given device or instrument, will the same measurement values obtain when the device or process is used to measure the same phenomenon again? In more technical terms, reliability refers to the amount of true score variance that can be consistently assessed with a measurement device or instrument as opposed to error variance (which is not readily reproducible due to its randomness). This notion reflects the basic classical assumption that all test scores or measurement values are potentially fallible, and, therefore, all observed scores represent a composite of true score variance and error variance. The various specific forms of reliability (internal consistency, test–­retest, alternate form, interrater, split-half) need not concern us here in detail, as they are described in entry-level methodology and psychological testing textbooks. The important notion is that measurement should be consistent and reproducible if it is to have any real scientific utility. Validity concerns the extent to which a test or measurement device actually measures what it claims to measure. This is a deceptively simple statement that should be unpacked a little to gain an appreciation of its importance. First, this basic definition assumes that there is some objective criterion of validity against which we could compare measurements taken with a device or measure. A paper-and-­pencil test of swimming ability (the test) should be predictive of the actual ability to swim (the criterion). One could correlate scores on the swimming ability inventory with the observed ability to swim as the test takers are tossed into a pool. This seems rather straightforward. However, unfortunately, most of the concepts in which we are interested in psychopathology (even when measured experimentally) and in psychological science generally do not readily present such objective criteria against which to compare measurements (like the swimming example). Concepts such as anxiety, depression, hostility, thought disorder, intelligence, and interpersonal aversiveness are not readily linked to an accepted objective criterion. Concepts such as anxiety or thought disorder cannot be defined 1 See

Maher and Gottesman (2005) for detailed consideration of the impact of this landmark paper.

Reliability, Validity, and How We Collect Data

27

flawlessly in terms of observable criteria, nor can they be readily reduced to entirely observable phenomena. They are unobservable as ideas, concepts, theoretical notions, or latent entities but indispensable for the work of the psychologist. Psychologists’ concern with latent entities or concepts was a necessity, though it rather challenged the prevalent assumptions of 1930s–1940s regarding “observables.” This rather annoying and murky state of affairs was initially tackled by MacCorquodale and Meehl (1948) and extended in a critically important manner by Cronbach and Meehl (1955), the latter work yielding the essential notion of construct validity. Before the notion of a construct—a hypothetical entity, concept, or idea—could be introduced to psychological science, the field itself had to become comfortable with, or at least introduced to, the notion that not all phenomena of interest to psychologists would be reducible to observables. In their groundbreaking 1948 paper, MacCorquodale and Meehl2 explicated the distinction between “intervening variables” and “hypothetical constructs.” The former implied linking concepts that described the relations between observable phenomena. For example, the term habit strength could be used to describe the mathematical relations between two variables, such as an observable independent variable and an observable behavior. Habit strength was therefore just a communication device or conceptual name to describe the relations between observable phenomena—a so-­called intervening variable. In contrast, MacCorquodale and Meehl (1948) suggested that psychologists allow themselves to also use the notion of a “hypothetical construct.” The hypothetical construct was not thought to be directly observable, nor could it be defined as a direct function of observables (not unlike the concept “atom” for physicists). The “hypothetical construct” viewpoint caused a certain amount of anxiety among those deeply committed to the behavioral paradigm that held sway in psychology at the time. The simple truth of the matter was that most of what psychological science was interested in studying were, for the most part, hypothetical constructs. Once the field came to recognize the essential nature of hypothetical constructs, the scene was set for a formal exploration of construct validity. How 2 The

contemporary student of psychological science might be somewhat puzzled by references to some literature that is nearly 60 years old (or older). The timeless ideas in such papers represent the pure gold of scientific psychology. This brings to mind an experience I had some time ago. I asked a student if he had read MacCorquodale and Meehl (1948), and the student responded by saying, “no, it isn’t available in PDF format.” I found this response confusing as the journal, Psychological Review, was held in the world-class library of the institution where I was at the time, and I understood that copying machines were readily available. This classic paper, as well as many other old gems, have now become available in electronic format (e.g., PDF) and are easily accessed.

28

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

best to establish that one was measuring a hypothetical construct in a valid fashion? Prior to Cronbach and Meehl’s (1955) examination of validity in psychological tests, psychologists more or less expected that any sort of measurement taken should be readily identified or linked to some objective and observable criterion. Thus, if one measured some trait (e.g., dominance) that varied across people, then these measurements would need to be connected to observable dominant behavior. How could genuinely dominant behavior be observed? Could dominant behavior be manipulated by the investigator? The difficulty posed by this assumption for those psychologists working with subjects other than the ubiquitous white laboratory rat was acutely felt in many quarters. For example, during World War II the United States government set up the Office of Strategic Services (OSS), which was the forerunner of the Central Intelligence Agency, to recruit and assess individuals for potential intelligence-­related assignments in the various World War II theaters. The OSS employed many psychologists in this effort, and the hope was to devise an assessment procedure by which viable candidates could be identified and retained for intelligence work. However, a major obstacle in this effort was the selection of a criterion of validity for their assessment procedures. To make a long story short, the psychologists that ran the OSS assessment procedure (OSS Assessment Staff, 1948) realized that they were really concerned with hypothetical constructs for the most part in their evaluations. They realized that they could not hope to identify external, observable criteria of validity against which to compare their evaluations of the candidates. They implicitly understood that they needed some form of construct validity approach, although they did not have this notion on hand at the time. Such a concept arrived with Cronbach and Meehl (1955), who described construct validity, as distinct from face, content, and criterion validity (i.e., other forms of validity), as a property possessed by a psychological test such that the test actually measures the hypothetical construct it purports to measure. This form of validity was derived from the overall corpus of empirical relations that associated scores on a test (or other measurement device) with other variables that putatively tapped the construct of interest. Thus the pattern of data (or relations) could be relied on as a method by which one could determine whether a test was worth its salt, whether it was measuring the unobservable (latent) hypothetical construct of interest. For the most part, nearly all concepts of interest in psychopathology represent “hypothetical constructs,” and good measurement processes are thought to index these unobservable entities, thereby suggest-

Reliability, Validity, and How We Collect Data

29

ing the presence of construct validity. Finally, another seminal aspect of the Cronbach and Meehl (1955) exposition on construct validity was the notion of the nomological net, which refers to a network of nomologicals (scientific law-like statements) that linked together latent constructs via either causal relations or probabilistic (stochastological) relations. The linkages in this network could be direct (i.e., causal) or indirect (i.e., shared causes, or ties to common observables postulated by the nomologicals and influenced by latent constructs). Reliability and validity, therefore, represent two critical tools in the experimental psychopathologist’s toolbox. Indeed, it is difficult to conceive of psychopathology research moving forward without these notions. Even descriptive psychopathology—the enumeration of signs and symptoms of putative disease entities—­implicitly entails construct validity. However, the situation in psychopathology research creates some unique instances involving reliability and validity that occur not infrequently (to be discussed shortly). Reliability and validity are intimately related to one another in ways that are worth committing to memory. First, reliability of measurement does not ensure validity. One can generate highly repeatable measurements, although that is no guarantee that the measurements possess validity. Second, when measurements are made validly, they will be, by definition, reliable. Third, one can impact the validity of measurement through alterations in the reliability of measurement. Fourth, reliability sets an upper bound on validity (i.e., the square root of the reliability sets an upper bound on the validity of a measure). Fifth, excessively high reliability can be a telltale sign that one is dealing with an interesting state of affairs in terms of latent structures that underlie one’s study population. Although psychologists had long been concerned with the issues of reliability and validity, particularly in clinical psychology with its assessment focus, the same cannot necessarily be said for psychiatry. The watershed paper for an interest in validity in psychiatry was the brief paper by Eli Robins and Samuel Guze (1970) in which they laid out their approach for establishing the “validity” of schizophrenia. Their approach consisted of looking at what essentially amounted to criterion validity (à la Cronbach & Meehl, 1955) relations in several domains: (1) clinical description/phenomenology; (2) laboratory studies; (3) delimitation from other disorders; (4) follow-up study; and (5) family study. These authors argued that the pattern of results across this set of domains could be taken to be supportive of the validity of a psychiatric illness. In short, Robins and Guze (1970) really

30

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

applied the model criterion and construct validity advanced by Cronbach and Meehl (1955) nearly 15 years earlier.3 A fascinating development then occurred during the period after psychiatry “rediscovered” descriptive psychiatry (1970s and 1980s) and, arguably, first discovered the value of reliability, especially as embodied in the DSM-III (American Psychiatric Assocation, 1980) diagnostic system. Although nearly all researchers (psychologists and psychiatrists alike) saw the value of enhanced reliability in diagnostic assessments, symptom ratings, and any other measurement enterprise, it was not entirely obvious to all that one could go “too far” in the quest for reliability. In short, if one pushed a measure as far as possible in terms of reliability (i.e., attempting to maximally enhance the reliability of a measure or scoring system), then an unusual thing could happen. That is, although the measure or scoring system that one had been working with might possess some appreciable level of validity at a given (lower) reliability, it was found that when the reliability of the measure or scoring system was increased, the validity of the approach actually decreased! The classic tutorial on this issue was provided by Gregory Carey and Irving Gottesman, two Minnesota PhDs, in a 1978 paper in the Archives of General Psychiatry titled “Reliability and validity in binary ratings: Areas of common misunderstanding in diagnosis and symptom ratings.” As noted by Carey and Gottesman (1978), “It is frequently assumed, however, that because one instrument (or one definition of a symptom or diagnosis) has more reliability than another, it has a greater potential for having more validity” (p. 1454), but they demonstrate that such an assumption is simply not true. What is going on here? Is it not the case that high reliability is a good thing? Jane Loevinger, the Washington University of St. Louis psychologist, provided the classic treatment of this issue, or what is known as the “attenuation paradox,” which had been described in relation to psychometric measurement previously (1954; see also Loevinger, 19574). This notion refers to a situation in which further increases in the reliability 3 Each

of these papers has had an enormous impact on its respective field. For example, as of 2008, the Cronbach and Meehl (1955) paper had been cited more than 2,000 times by other scientists, and the Robins and Guze (1970) paper had been cited more than 700 times (primarily within psychiatry). These figures must be put into perspective by the fact that most scientific papers go uncited. A paper cited more than 25 times has done reasonably well in “being noticed.” From the standpoint of sociology of science, it is interesting to note, however, that Robins and Guze (1970) actually do not cite Cronbach and Meehl (1955) despite the implicit adoption of the construct validity model by the former parties. This attests to a certain parochial nature in citation practices across professions.

4 The

Loevinger (1957) monograph, truly her magnum opus, on rational test construction represents one of the richest documents in psychological science. It is highly recommend (but not necessarily easy) reading. A useful companion to the original text can be found in Clark and Watson (1995).

Reliability, Validity, and How We Collect Data

31

of a measure may actually, though not always, diminish the validity of measurements. In short, one can work so hard to make a measurement process or instrument reliable that the end result is an inadvertent narrowing of the domain covered by the instrument, so that the resulting measurement values have considerably less validity. Loevinger (1954) defined the attenuation paradox in test theory as follows: A paradoxical property of a test is a property such that the validity of the test is not a monotonic function of that property. . . . Is it not intuitively valid, however, to demand that the most basic concept of psychometrics shall be a non-­paradoxical property of tests? Reliability is paradoxical. (pp. 500–501)

Returning to psychopathology and the reliability of binary ratings (e.g., presence or absence of a symptom), we must always remember that one can work so hard at making a measurement or rating system reliable, that the validity of the output is compromised. Does this sort of thing actually happen? Yes, it does. Two examples of this are worthy of consideration. One concerns altering an illness definition to ensure high levels of reliability, and the other concerns training subjects to make ratings reliably on a task that is typically time-­consuming and expensive.

Don’t Squeeze the Validity Right Out of the Thing!: Two Cautionary Tales As psychiatry rediscovered its descriptive roots in the 1970s and began to discover empirical research (typically with the aid of psychologists trained in measurement, design, and statistics), the architects of the “modern” diagnostic nomenclature (e.g., DSM-III; American Psychiatric Association, 1980) began to be concerned with the validity of the system. However, in the quest to advance research on the validity of various forms of psychopathology, definitions of illnesses were reframed in terms of explicit criteria and were transformed into a collection of easily rated signs or symptoms in the DSM-III. The goal of this revision was to attain relatively high levels of reliability for the assessment of psychopathology. For example, with respect to schizophrenia, the DSM-III definition of the disorder, introduced in 1980 (American Psychiatric Association, 1980), was nearly exclusively focused on the so-­called positive (or productive) symptoms of schizophrenia. This was so because symptoms such as hallucinations, delusions, and disorganized behavior were usually easily detected and because their presence could be

32

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

agreed on more readily by independent raters. This shift to explicit criteria was a major change from the earlier DSM-II (American Psychiatric Association, 1968) definitions of schizophrenia, which tended to be prosy narratives lacking in explicit detail or guidance for establishing a diagnosis. On balance, it would seem that a move in the direction of a more reliable system with explicit diagnostic criteria would fundamentally be a good thing, quite sensible, in fact. However, did this revision of the diagnostic criteria for schizophrenia go too far? Did it diminish the validity of the illness identified years before by the founding observers, Kraepelin and Bleuler? Was reliability increased so much that the validity of the diagnostic concept was diminished? Two studies that examined the familial transmission of schizophrenia using the “new and improved” DSM-III definition of schizophrenia speak directly to this point (although the respective authors did not view their results from this perspective). First, Pope and colleagues (Pope, Jonas, Cohen, & Lipinski, 1982) reported on a chart-based study of schizophrenia among the first-­degree biological relatives of 39 probands (i.e., index cases, diagnosed patients) diagnosed with DSM-III schizophrenia. A rater, blind to the diagnosis of the probands, carefully reviewed information provided in the psychiatric charts of these patients looking for evidence of schizophrenia in the biological relatives of the patients. Pope et al. (1982) reported that no case of schizophrenia was found among these relatives. Even though this study relied on a family-­history approach to the assessment of psychopathology, an approach known to have somewhat diminished ability to detect all cases of illness in relatives under consideration, the data were nonetheless highly provocative. In the second study, Abrams and Taylor (1983) examined the first-­degree biological relatives of 30 adult patients diagnosed with schizophrenia according to the DSM-III criteria for the illness. They found a 1.6% morbidity risk rate for schizophrenia among the relatives, and this figure did not differ significantly from a comparison group, nor did it suggest evidence, to the authors, of noteworthy familial aggregation. These papers delivered up results clearly at odds with decades’ worth of data on the familial transmission, which typically showed considerably higher morbid risk rates for schizophrenia in the first-­degree biological relatives of patients, as well as providing relatively strong evidence for familial aggregation of the illness. Even as of the early 1980s, it was well known that an important criterion of validity for the schizophrenia phenotype over the years was the familial transmission of the illness (Gottesman & Shields, 1982). But this criterion of validity was suddenly not found for those cases diagnosed with DSM-III schizophrenia by Pope et al. (1982) or Abrams and Taylor (1983), who suggested that the evidence for “the familial transmission of narrowly

Reliability, Validity, and How We Collect Data

33

defined schizophrenia is weak” (p. 171). The diagnoses were done by highly trained psychiatrists, and in the Abrams and Taylor (1983) study many of the patients’ relatives were interviewed directly, thus avoiding the limitations of the family-­history method. So what happened here? Was it not the case that this new definition of schizophrenia, which was highly reliable, should have generated a highly valid phenotype? The results of these studies serve to illustrate the concern over the quest for reliability, with the implicit assumption that such a quest will necessarily enhance validity. Clearly, schizophrenia did not suddenly become an illness with little to no pattern of familial aggregation, and to infer as much from these studies was wrong, especially in light of more modern evidence (e.g., Gottesman, 1991; Harrison & Owen, 2003). What most likely happened was that these studies revealed that in making the DSM-III definition of schizophrenia so highly reliable, the authors may have so squeezed the definition such that an aspect of validity was lost, in this case the important criterion of validity of familial aggregation of the illness. Close inspection of the DSM-III definitional criteria for schizophrenia revealed a clue to this mystery. These criteria were, by and large, limited to the positive symptoms of schizophrenia, whereas the negative features of the illness, noted by Kraepelin and Bleuler, were largely absent (Dworkin & Lenzenweger, 1983, 1984). At the time the DSM-III was being assembled, negative symptoms were thought to be so difficult to rate reliably that it was thought best to omit them from the definition of the illness in the DSM-III. However, this omission may have inadvertently removed an important piece of the valid definition of schizophrenia, namely the familial/genetic aspect (see Dworkin & Lenzenweger, 1984). When research staff is trained to make ratings of one sort or another, they are typically “trained up” to a high level of reliability. In the minds of most researchers, the higher the reliability achieved by the raters during training, the better. The assumption behind this preference is that a high level of reliability will come with a high level of validity (a common misconception not widely appreciated by many researchers). An interesting example of this sort of thing comes from the study of expressed emotion (EE), which is a family emotional climate construct, and its relation to relapse in schizophrenia. A very well-­established finding in the schizophrenia treatment literature is that when schizophrenia patients return to their homes after being stabilized (i.e., symptoms, mainly the positive features, are reduced) in the hospital, typically with medication, they will frequently return to a psychotic state more rapidly if the emotional climate in the home to which they have returned is characterized by high levels of EE (i.e., criticality, hos-

34

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

tility, and emotional overinvolvement; Butzlaff & Hooley, 1999). Although the mechanism for this relationship is not understood, the empirical finding relating EE levels to relapse rates is robust. Simply put, if your parents or partner direct hostility, criticality, and overinvolvement your way, then you are more likely to relapse into another schizophrenia episode (typically after discontinuing medication) than someone in a “low-EE” climate. Coding emotional climate in the form of EE from interview assessments is a cumbersome and lengthy research task. The actual interview with family members itself can take upward of 2 hours, and the dreary coding task of the taped interview material can take up to 4 hours of staff time. Is this the best way for a PhD-level researcher to spend his or her time? Hooley and Richters (1991) explored the possibility of developing an alternative approach to coding the interview data from the EE interview tapes. They sought to train undergraduate university students to code the same constructs (criticality, hostility, and emotional overinvolvement) from materials gathered and coded in a valid fashion by highly trained EE professionals. The logic of this methodological work was straightforward: Develop a method by which others could code EE information, thereby freeing up more senior workers from the task. Clearly, a necessary component of the work would require that the undergraduate raters be trained to be highly reliable with raters known to generate valid ratings of EE. Hooley and Richters (1991) set about this task, trained their undergraduate assistants to high levels of reliability with expert raters, and then examined the ability of the student-­assessed EE ratings to predict relapse in a sample of patients. (The investigators already knew that the ratings made by the experts predicted relapse quite well in the sample to be studied.) The six raters (Harvard College undergraduates) in this study achieved an average reliability of .83 to .89 with an expert’s ratings of the components of EE during the training phase of the study. Clearly, they were highly reliable. With respect to the actual target cases rated after the raters had achieved reliability training, the students’ ratings correlated reasonably highly with expert assessments of EE components on the target patients. However, and this is the important part, although the EE ratings made by the students correlated highly with EE ratings made by experts, the students’ ratings did not predict relapse in these patients! In fact, none of the EE ratings made by the students predicted relapse, no matter how the investigators configured their measurement approach (e.g., Q-sort vs. Likert ratings). Somehow the students, who were bright and capable, missed essential information in their ratings of the tapes that served to diminish the validity of their assessments despite their reliability. The authors concluded, “Developing a good EE analogue

Reliability, Validity, and How We Collect Data

35

is neither as easy, nor arguably as desirable, as it appears at first glance, and indeed may be more self-­limiting than most researchers believe” (Hooley & Richters, 1991, p. 97).5 The implication of these studies is clear: Do not assume that achieving high levels of reliability (e.g., high interrater reliability, highly reliable definition of presumed construct) confers high levels of validity. Moreover, recognize the fact that increasing the reliability of a measurement or definition may actually undermine the validity of the concept, construct, or illness being measured. This peculiar reality is known as the “attenuation paradox” in psychometrics.

Psychopathologists Beware! Latent Mixtures May Bias Your Reliability Analysis At research meetings, colloquia, and so on, it is not uncommon to hear psychopathologists discuss the reliability of the measures in their study. Often this means reporting on the internal-­consistency reliability—or degree of homogeneity—­present in a self-­report or other instrument that may have been used. Typically, the Cronbach’s coefficient alpha (a) or Kuder–­Richardson-20 value is presented as demonstrating the high level of reliability shown by the instrument in the study population. This statistical approach to reliability assessment, of course, assumes that the subjects have been sampled from a single population and that the items on the measure of choice are tapping into a single underlying dimension. In the case of psychopathology research, the assumption regarding the single population deserves special attention and urges caution in interpretation. The Minnesota psychometrician Niels G. Waller (2008) has discussed the potential bias that may creep into a reliability analysis if the study sample under investigation has not been drawn from a single population. Waller’s point is nontrivial given that many forms of psychopathology cohere (hang together) rather well and may set themselves apart from the normal population in identifiable ways, thereby representing a distinct subgroup or class within a study sample (see Meehl, 1992, 2004). Samples consisting of identifiable subsamples of subjects set the stage for the emergence of an unusual reliability picture. Consider the topic of this book, namely schizotypy. It is 5 It

remains challenging to come up with a shortcut method for the assessment of expressed emotion (EE). Indeed, Hooley and Parker (2006) argue for the continued utility of the more labor-­intensive but data-rich approach to the assessment of EE embodied in the Camberwell Family Interview method.

36

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

argued that the schizotype harbors the latent liability for schizophrenia, and, no matter what genetic model of the illness is espoused, one is either at risk for the illness or one is not (see Lenzenweger, 1998). Therefore, when one combines schizotypes and nonschizotypes into an overall subject sample, one has created a mixture of latent groups or types of individuals. This mixture at the latent level will affect the coefficient alpha values that will be obtained from an analysis of the item-level data for a study measure in question, typically inflating the estimate of reliability. Let us consider this issue in greater detail. It makes sense to visualize what we mean by “latent mixture.” Normally one conceives of a distribution of scores as being drawn from a single population and centered, in some fashion, about a central tendency (most being unimodal in shape; Figure 2.1). In the case of mixture, we are speaking of a situation in which an observed distribution of scores harbors two or more distributions, potentially reflective of having been drawn from two or more qualitatively dif200

Frequency

150

100

50

0 40.00

60.00

80.00

100.00

120.00

140.00

Femininity

FIGURE 2.1.  Classic unimodal normal. The distribution of scores for a psychometric measure of femininity among 1,600 first-year college students is depicted here. The dark curve represents a theoretically perfect unimodal normal (curve) distribution. The vertical bars indicate case counts for a given score on the femininity scale. As data go in psychopathology and personality, the real data depicted in this graph are reasonably normally distributed and unimodal in shape.

Reliability, Validity, and How We Collect Data

37

ferent populations. Such distributions frequently reveal their mixed nature at the latent level via some clue in the shape of the observed distribution (see Figure 2.2), though not necessarily so (see Figure 2.3). For example, a bimodal distribution has two discernible modes, that is, that are visible to the naked, unassisted eye (see Beauchaine, 2003, for an excellent review). What happens if one analyzes internal-­consistency reliability from a population that really consists of commingled samples? Waller (2008) demonstrates that coefficient alpha and related indexes can be severely biased and that “in most cases the bias inflates a; in other cases a is attenuated” (p. 211). What this means in practical terms is that when someone reports very high alpha values (typically with some amount of self-­assurance that the scale used is up to par in terms of reliability) from what could very well

3.00

Complement Taxon

2.50

Value

2.00

1.50

1.00

0.50

0.00 25.00 24.00 23.00 22.00 21.00 20.00 19.00 18.00 17.00 16.00 15.00 14.00 13.00 12.00 11.00 10.00 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 value

FIGURE 2.2.  Classic bimodality. This figure depicts what would be thought of as classic bimodality. There are two modes within this overall distribution of scores, and the theoretical reason for the bimodality is the presence of two qualitatively different groups of people harbored within the overall sample. In this depiction there are two clearly discernible modes, and the overall distribution is clearly recognizable as non-normal. This sort of data array rarely happens in practice.

38

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX 300 250 200

N

150 100 50 0

FIGURE 2.3.  Unimodal distribution harboring two normal components. Admixture of two discrete normal distributions of n = 1,000, each indicated by hatched bars and dashed lines. The effect size separating the distributions is 2 standard deviation units. Note that despite this large effect, there is no evidence of bimodality in the combined distribution, indicated by solid bars. Note also that the combined distribution is near normal, as indicated by the solid line. Reprinted with permission from Beauchaine (2003, p. 505).

be a mixed sample, then it is quite likely that the reliability represents an inflated, biased value that speaks more to the impact of mixture than to the actual internal consistency of the measure. In a powerful demonstration, Waller (2008) shows that one can obtain relatively high a values for an overall sample of subjects even when the internal-­consistency values of the items under consideration are zero within the subsamples that constitute the mixture within the overall sample.

How about Latent Mixture and Validity Relations? In this context it is worth considering the additional impact of latent mixtures on obtained correlational relationships among data for validity.6 Waller (2008) clearly demonstrated the impact of latent mixing specifically on reli6 Reliability

places an upper bound on validity, and this relationship is technically as follows: the square root of reliability provides the upper boundary on validity coefficients. Thus, if the reliability of a measure is .81, then validity coefficients (i.e., correlations between test scores and some other criterion measure) cannot exceed .90. The observant student will realize that validity can, therefore, exceed reliability in magnitude (although a rarity).

Reliability, Validity, and How We Collect Data

39

ability analysis, as discussed earlier. However, we can extend this concern to validity relationships as well. To begin, one merely needs to recall the impact that various sample characteristics can have on the correlation coefficient (e.g., Pearson product–­moment correlation coefficient, or our friend r) to appreciate the impact of mixture per se. Recall that the restriction of range or truncation of the range of values on variables under consideration in a correlational analysis will often serve to diminish the absolute value of the obtained r between variables. For example, imagine that we were interested in the correlation between reading ability and grade level in schoolchildren. However, if we limit our analysis to second and third graders (restricted range), we might find that level of schooling and reading level correlate positively but with a relatively low magnitude r. When we examine this same relationship (grade level x reading ability) in first through ninth graders, we see that the correlation is again positive but much higher in magnitude. One can inflate the value of an obtained correlation between X and Y by selecting a sample of subjects from the lower and higher ends of a range of values on some index, variable Z. Imagine that one has rather intentionally set up a study whereby the subjects in one of two study groups were selected for deviance on a psychometric measure (e.g., anxiety). Let’s say the “normal group” was from the lower 50% of the anxiety distribution, whereas the “anxious group” came from the top 10% of the anxiety distribution (variable Z). We then correlate the individual difference scores on the personality trait of neuroticism (X) with the level of heart palpitations (Y) assessed in the subjects. We find the r between the neuroticism scores and heart palpitation rate is .50 in the combined sample. Is this the true relationship between neuroticism and heart palpitation rate? Probably not, as the obtained r is likely to be inflated. The inflation of r here really represents an artifact of the “extreme groups” selection strategy that was employed in assembling the samples at the start. The astute reader will readily wonder, What would the r between these two variables be if a sample of subjects representing the entire range on the anxiety screening measure had been selected? The answer is (1) that midrange of omitted subjects would indeed be important and (2) the r between neuroticism and heart palpitation rate would likely be lower. What implications does this sort of thing have for validity issues? How could such a scenario play itself out in some analogous fashion in psychopathology research? We can now extend this consideration to the possibility of a mixed sample, whereby a correlational relationship between an X and a Y variable is examined in an overall study sample that actually represents a mixture of different subpopulations (reflective of type Z). In short, the obtained r

40

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

between the X and Y variables of interest may indeed be inflated due to the underlying mixture. Not unlike the reliability scenario explored by Waller (2008), the mixture will play out its effects among other relationships as well. Thus, to the extent that the relationship between X and Y (or neuroticism and heart palpitation rate) is used as evidence of criterion validity (e.g., perhaps for the anxiety screening measure used to assemble the sample), the relationship between X and Y may be inflated or biased upward due to the latent composition of the sample. What is particularly important to note about this situation is that the latent mixture that derives from variable Z may not necessarily be visible from an examination of, for example, a scatterplot of the observed variables in the analysis (e.g., X and Y). For example, one may not readily see two distinct clouds of data points arrayed in the X and Y indicator space. The graphs in Figure 2.4 are used to show how latent mixtures can affect data; the reality of the latent mixing may be indiscernible to the naked eye. In the hypothetical data displayed, we can see that the identical correlational relationship between symptom X and symptom Y can be obtained in two very different ways. In panel A we can see how the mixing of two distinct populations (the “c”s and “t”s in the graphic, reflective of some typological variable Z) at the latent level can create the appearance of a strong correlation (the solid line) between symptom X and symptom Y even though these variables are uncorrelated (the dashed lines) within the different subpopulations (i.e., the t’s and c’s). Whereas in panel B, we see how the observed correlation arises from quantitative variation along the symptom X and symptom Y dimensions across the study subjects (which have all been drawn from the same population). Thus, not unlike the situation with reliability, the psychopathologist must be alert to the potential for latent mixtures to drive obtained correlational relationships at the manifest or observable level of analysis in the study of validity. Moral: In the case of intentional (or unintentional) sample construction, where a mixture of subject types has occurred, the magnitude of the obtained correlational relationships between dependent variables obtained for the combined sample will be overestimated or inflated. To check out the extent of bias, a study of the X × Y relationship in question should be conducted in a sample of subjects that have been selected across the full range of values (in proper proportions given their place in the distribution) on the selection instrument (e.g., the anxiety measure in the previous example; see also Rosenthal & Rosnow, 1991, 2008). How should one evaluate the meaning of the validity relations (i.e., correlations with criteria of validity) derived from samples in which latent mixture exists? This is a complicated issue. The manner in which we view

(A)

(B)

schizotypes controls

anhedonia

(C)

social anxiety

FIGURE 2.4.  (A) The values for symptoms X and Y correlate .50 in the overall sample, but they are essentially uncorrelated within the two subpopulations that constitute the overall sample (denoted by qualitatively distinct subjects marked as “c” or “t”). (B) The values for symptoms X and Y correlate .50 in the overall sample, which consists solely of individuals drawn from one population who vary quantitatively along the dimensions of symptoms X and Y. (C) A hypothetical bivariate distribution of anhedonia and social anxiety in a mixed sample of normal controls and schizotypes. Note that the slope of the smoothed regression line is relatively flat within groups, but steepens where schizotypes (n = 250) and controls (n = 250) are mixed. Panels A and B courtesy Niels Waller. Panel C adapted with permission from Beauchaine (2003).

41

42

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

the observed correlations and impact of mixture will depend on our theoretical and empirical understanding of the problem with which we are dealing. Not unlike the extreme-­groups example, latent mixture may bias obtained correlational relationships, typically increasing the magnitude of the relationship. Does this represent a problem, an artifact, or a bias? If one anticipates or knows a priori that latent mixture exists in the study sample, then one understands that the nature of the sample will serve to augment the r. In this instance, we may not think of the augmentation as a bias per se. If one is unaware that mixture exists, which is probably more typical in the modal situation (not unlike in the reliability scenario explored by Waller, 2008), and thinks that one is dealing with a latent situation consisting of dimensional/quantitative continua, then it is perhaps more sensible to think of the mixture impact as one that biases obtained relations. One should be open to examining this possibility using appropriate techniques, as is discussed later in this book (e.g., taxometric, finite mixture modeling, and latent class analyses).

Measurement, Scaling, Rating, and the Value of Counting Nearly every person who reads this book has completed some type of psychological questionnaire, either with paper and pencil or, perhaps, on the computer. The psychological questionnaires, in the main, probably concerned things of interest to psychologists, such as anxiety, depression, authoritarianism, creativity, and so on. These are constructs from the standpoint of Cronbach and Meehl (1955). Frequently the questionnaires will have had a format whereby a respondent had to express the degree to which he or she agreed or disagreed with a statement, typically choosing from 5 or, perhaps, 7 levels of agreement. An item might read something like “I get the shakes when I have to speak in public.” And one assigns a value to this item along the 5- or 7-point continuum. Many questionnaires probably also had simple true-­versus-false formats, and one was required to make a decision in this mode; for example, “I like art magazines.” True or False. What is wrong with this picture? As noted earlier, Cronbach and Meehl (1955) taught us that many of the things of interest to psychologists cannot be measured directly in the form of an accepted criterion, an “observable” gold standard; rather, we need to tap into constructs at the latent level via a pattern of divergent and convergent relations among fallible measures. The hypothetical items just listed could well be viewed as concepts tapped on typical psychometric measures.

Reliability, Validity, and How We Collect Data

43

The problem with the entire enterprise, as reflected in these hypothetical inventory foci, is that the fundamental process that has occurred in the completion of the items (or entire measures or inventories) is really just a form of self-­rating. Responses on self-­report inventories represent “educated guesses” about the self by the self that conform to no commonly accepted standard, measurement process, or operation and that may (or may not) have any validity.

On the Nature of the Data We Collect as Psychologists: Collecting LIST (LOTS) of Data Before probing the issue of measurement scaling and the difficulties imposed by a rating approach to the collection of data, let us briefly review the kinds of data collected by psychologists in their laboratories. The University of California–­Riverside personality psychologist David Funder (2007) has developed a handy method for describing the types of data that we collect in psychological science, and his scheme is quite applicable to psychopathology. Funder’s organizing scheme is excellent, and what appears here is adapted, in part, from his more detailed presentation (Funder, 2007). He describes four types of data that are gathered: life-­record data, self-rating data, informant (observer) rating data, and task-based data. Life-­record (also known as life outcomes) data refer to information that can be gleaned from objective records kept about our lives—for example, number of arrests, birth weight, court appearances, or years of schooling completed. Life-­record data tend to be intrinsically important (we record things that are important), and they tend to be of psychological relevance (e.g., arrest records). A down side or shortcoming of such rich events and outcomes is that they may reflect the impact of other factors beyond the personality or psychopathology (e.g., social class, poverty, education, and so on). Self-rating data are gathered typically from questionnaire methods and have the benefit of being economical to gather, as well as the claim to accuracy regarding the self (as who knows one’s innermost thoughts, feelings, and concerns better than oneself). However, self-­report data are open to criticism, as we are not always the most objective observers of ourselves, we may not have insight into our behavior or emotional lives, we may wish not to disclose things about ourselves (or even may misrepresent things), and our self-­ratings may be subject to variations in our mental state (see state–trait artifacts discussed later). Nonetheless, personality science and scientific psychopathology make extensive use of self-­rating data, as nearly

44

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

every self-­report questionnaire (including interviews7) regarding personality, psychopathology, and other aspects of psychological functioning relies on this methodology. Informant (observer) data (or data generated by others observing individuals) are very much what they sound like; they represent, typically, ratings or judgments made about a target subject by an observer. For example, a psychiatric nurse may report during morning rounds on the ward behavior of a newly admitted patient, an interviewer may rate the level of depression or thought disorder shown by a patient undergoing a psychiatric examination, or a spouse might report on personality disorder characteristics of his or her partner. Informant (observer) data are potentially of great use as they ostensibly are more objective than self-­rating data, can generate large amounts of data, possess a real-world basis, and reflect the impact of the common sense of the interviewer. However, they are also subject to limitations (e.g., observers can be biased; observers cannot observe someone all the time; some important things regarding psychological life cannot be observed, such as fear; human observers are known to make errors). Finally, there are task (or behavior) data. Such data derive from the application of experimenter-­designed procedures or tasks in which people generate some form of behavior (e.g., engaging in a simulated conversation or group tasks such as building structures from Legos). An example of naturally occurring task (behavior) data can be found in personal diaries or experience sampling methods. Some self-­report inventories such as the Minnesota Multiphasic Personality Inventory—given their unique nature—­ represent a form of task, as the subject does not really rate him- or herself with regard to a question; rather, he or she simply answers “true” or “false” to test items, and these items are added up for scoring purposes. Finally, a variety of neurocognitive tasks (e.g., sustained attention task, working memory tests), psychophysiological recording methods, and functional neuroimaging methods (positron emission tomography [PET], functional magnetic resonance imaging [fMRI]) represent methods or techniques for collecting task (or behavior) data. Task (or behavior) data can be rigorously quantified and can be considered reasonably objective when collected under proper conditions. Nonetheless, even carefully designed tasks (or behavioral protocols) do not generate data that are “self-­interpreting”; that 7 The

interview, whether in a traditional unstructured or contemporary structured format, is really a form of self-­report. Just as with paper-and-­pencil self-­report measures, one can be defensive, evasive, misleading, or nontruthful (i.e., lying) in an interview, as well as influenced by biases to agree (or acquiesce) or to appear socially appropriate (social desirability) and/or nearly flawless (e.g., “I read the newspaper from front to back every day”).

Reliability, Validity, and How We Collect Data

45

is, they must be interpreted, and that must be done by fallible human beings who are far from omniscient (which, of course, complicates interpretation). This organization of data types can be committed to memory by using the acronym LIST—Life record, Informant [Observer], Self, and Task. For a more detailed and extended presentation, the interested reader is referred to Funder’s (2007) outstanding volume The Personality Puzzle.

A Brief Detour on Scaling: The Metrics Underlying Our Data It is always useful to remind ourselves of the basics of scaling, especially as they are apply to psychological science and the scientific study of psychopathology. Owing much to the work of S. S. Stevens (1935, 1939), who was a Harvard experimental psychologist, we typically think of four primary types (metrics) of scaling: nominal, ordinal, interval, and ratio scaling. In nominal scaling, we are primarily interested simply in classifying phenomena into categories (e.g., animal vs. mineral; male vs. female), and the categories are not ordered in any fashion nor manipulated with mathematical functions. For example, we cannot add together “maleness” and “femaleness”; rather, we can simply count the frequency of males and females in a sample. Nominal scaling represents, for example, how we would answer the question, Are these objects equivalent for the purpose of categorization? Are these two people both female? Ordinal scaling is used to determine whether one object that possesses a certain amount of an attribute has a greater or lesser amount of that attribute in relation to another object that also possesses some of that attribute. Ordinal scaling, therefore, allows us to place phenomena in a rank order. We can rank things from “most” to “least” or “highest” to “lowest.” This type of scaling, however, (1) cannot tell us how much of a given attribute or disposition any object has in an absolute sense and (2) it makes no assumptions regarding the distance between the phenomena (i.e., how far apart objects are in terms of an attribute or disposition). We might, for example, order dogs from least friendly to most friendly, yet we do not assume that the differences between the ranks are equal (we cannot say Dog A with a friendliness ranking of “4” is twice as friendly as Dog B with a friendliness ranking of “2”), and we do not really know what a friendliness level of “4” or “2” means in any absolute sense. With interval scaling, we also order phenomena much like with ordinal scaling; however, we do explicitly assume that the distance of the intervals between values are equal (i.e., so-­ called equal interval scales). Importantly, however, with interval scaling, we

46

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

do not assume that the first value on the interval scale represents a genuine zero value (rather, it is an arbitrary zero); we do not really know the absolute magnitudes of the attributes we are measuring. Finally, with ratio scaling, we order objects in terms of their levels on an attribute and assume that the distance of the intervals between values is equal across the scale and, furthermore, that the zero value on the scale represents a true or genuine zero. The latter characteristic is important, as knowing that a zero value is indeed meaningful (zero weight, zero length) allows one to make meaningful ratios between any two measures.8 The value of ratio scaling is that it is permissible to perform all mathematical operations on the data that come from a ratio scale measurement device. The interested reader is encouraged to consult the classic psychometric text, Psychometric Theory (3rd ed.) by Nunnally and Bernstein (1994) for greater detail.

Rating: What Is Typically Done and How It Is an Ever-­Present Nightmare for Psychopathology Given the types of data collected and metrics used in psychological research, we must now confront a major methodological problem. Simply stated, it is the problem of rating as a method of data collection. Although experimental psychology relies in many instances on experimental tasks that are completed by subjects, this is by no means true for most data collected in psychopathology research. In fact, it is safe to assume that many of the most basic data collected in psychopathology still rely on self-­rating and observer rating techniques. For example, the diagnosis of a patient (e.g., schizophrenia vs. panic disorder vs. depression) is still made on the basis of a patient’s self-­report (symptoms) and the observations of a diagnostician (signs). It represents a rating. When a researcher assesses the level of thought disorder in a patient’s speech, a rating is made. When a symptom of schizotypic personality disorder is diagnosed (e.g., Does the patient have an odd or eccentric appearance?), a rating is made. When a patient completes an inventory regarding personality traits such as extraversion or neuroticism, a self-rating is made. The picture should be clear at this point—the process of rating plays a major role in psychopathology research, even in the day of experimental paradigms and laboratory science. This is not a new problem or a novel insight. It has long been known in personality science, and the pro8 The meaning of an absolute zero for most psychological variables (constructs) is obscure. Whereas our colleagues in chemistry know that there is an absolute zero for temperature on the Kelvin scale, the situation for psychologists becomes a bit murkier when we think of a person having zero intelligence, zero anxiety, or zero thought disorder.

Reliability, Validity, and How We Collect Data

47

ponents of experimental psychopathology have attempted to draw attention to this issue for decades (Maher, 1966, 2003). Nonetheless, although this cautionary song has been sung for some time, researchers continue to rely on the rating methodology for some of the most important data collected in psychopathology studies. So, in the words of the legendary folk singer Pete Seeger, “we might as well sing ’er once again.”9 In 1974, Donald Fiske posited what he termed the “limits of the conventional science of personality,” and his discussion has direct relevance to this issue in psychopathology research. He was concerned with the major dependence of personality science on the use of rater observations. Referring to the nature of data points based on rating, he remarked that the behavioral unit being studied is actually “the observer’s process in making his judgment and that the observer’s response recording his judgment provides the datum” (p. 2). Accordingly, he argued, the datum point is the combination of the processes of two people—one that of the person observed and the other that of the perceptions of the person doing the observing. The relevance of this concern to the diagnostic process, as well as all other ratings-based assessments in psychopathology, is obvious. Moreover, the rating conundrum does not evaporate just because one uses a structured diagnostic interview or any other form of rating system or scale. The fundamental process is the same across most instruments; the object of study is observed and rated for some attribute, quality, symptom, or feature. No genuine measurement is occurring in the sense of ratio-scale-based measurement. The problematic nature of ratings has not been noticed only in personality research. For many years, this problem of rating in psychopathology has been a focal issue for Brendan A. Maher (1966, 2003), one of the principal architects of experimental psychopathology. Maher has advocated what is essentially a mantra for the psychopathologist, namely, “don’t rate, count.” In counting, one should pursue ratio-scale measurement. Paul Meehl provided a compelling anecdote that serves to illustrate the concern and preferred position on this matter quite well: When you check out at a supermarket, you don’t eyeball the heap of purchases and say to the clerk, “Well it looks to me as if it’s about $17.00 worth; what do you think?” The clerk adds it up. (1986a, p. 372) 9 I

had the opportunity a few years ago to deliver an address to a gathering of experimental psychopathologists, and the address focused on a number of methodological issues in psychopathology research, one of which concerned the rating-­versus-counting problem in psychopathology. A number of attendees approached me after the talk and said something to the effect of “you know, Mark, I had never thought of the rating-­versus-counting issue before.” Clearly, the message, though oft repeated, has still not been fully appreciated.

48

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

Rating versus Counting in Psychopathology: Two Illustrations It may be useful to consider two examples of a rating approach versus a counting approach in psychopathology. First, consider the well-known dysfunction in attention in schizophrenia. Patients themselves complain of difficulty attending to information (e.g., reading a book, following a news program on television); family members of patients speak of “drift-outs” and “space-outs” on the part of their ill relatives; and observers notice an inability to concentrate in many patients during therapy sessions, occupational therapy activities, and so on. How best to capture this attentional dysfunction for the purpose of research? One can rate the attentional performance of a subject or actually measure it. This issue has relevance in schizophrenia, as a prominent negative symptom of attentional impairment is “rated” in a heavily used symptom rating scheme (e.g., the Comprehensive Assessment of Symptoms and History [CASH]; Andreasen, 1985). Most experimental psychopathologists, on the other hand, would prefer to measure the actual performance of an individual on an objective laboratory task, such as a computerized test of sustained attention (e.g., a continuous performance test [CPT]). On a CPT, a subject is asked to identify a given target or target sequence presented on a computer screen, and the investigator can count up the number of targets correctly identified, as well as the number of nontargets falsely identified. These measures of performance can then be submitted to additional mathematical analysis with confidence given their ratio-scale-based nature (e.g., true, nonarbitrary zero and equal intervals). In the first instance, the problem with attention is rated, whereas in the second actual attentional performance is measured or counted. A second example concerns motor dysfunction in schizophrenia. Many studies of motor dysfunction have also been concerned with the degree of brain lateralization shown via performance on such tasks by schizophrenia patients. Since Kraepelin (1919/1971), clinical observation has been used to detect motor abnormalities in schizophrenia via a neurological exam. In the neurological framework, these motor abnormalities would often be considered nonspecific “soft signs.” Laterality was often clinically assessed in somewhat subjective fashion (e.g., asking a patient which hand he or she uses for writing or taking a list of hand use preferences across a wide variety of tasks). When we examine these approaches, we notice that they are both fundamentally the same—they are “rating” approaches. The data gleaned from such ratings are, at best, ordinal-­scaled data (i.e., not either interval or ratio-­scaled).

Reliability, Validity, and How We Collect Data

49

An alternative approach to assessing motor dysfunction and laterality was developed by Maher (1993), and it relies on a simple line-­drawing task. In the Maher Line Drawing Task (MLDT), subjects are required to draw four lines (two with each hand) in a specified format. The lines drawn by the subjects can be read by a computer, the deviations of the drawn lines from perfect lines can be quantified, and global measures of both motor dysfunction and laterality can be made. “Perfect” line drawing performance would yield a deviation score of 0 (zero), whereas anything less than perfect performance would be quantified via a regression-based procedure (see later discussion for detail). A principal virtue of the MLDT is that the data generated by the measure are ratio scale in nature, which allows for increased precision, as well as the use of parametric statistical analysis. Here evidence in favor of motor dysfunction (as well as degree of lateralization) is gleaned via a counting (not a rating) procedure. The take-home message here should be clear: Whenever possible, the experimental psychopathologist should have a distinct preference for counting approaches. The benefits of ratio-based metrics are obvious. However, the realist must appreciate the fact that there remain many important phenomena and processes in psychopathology that still require a rating approach (though some day even these processes and phenomena may be measured with more refined approaches). Thus, although it is fair to say that some phenomena can be rated reliably, the precision and utility of count-based measurements should weigh heavily in favor of counting. Thus the student is advised to remember the Maher mantra: Don’t rate, count.

Two Worlds: The Correlational versus the Experimental Psychopathology arises quite naturally in human beings (it is not created by scientists), and it shows a considerable amount of variation across individuals. Thus one can say that nature has assigned “membership” to the group of human beings known to be affected by psychopathology. That is, nature has decided who shall develop schizophrenia, depression, panic disorder, or autism. This is so even if there are environmental triggers or modifying factors, simply because a person does not choose to be affected by psychopathology, nor does someone assign a person to develop psychopathology. Even in experimental research, in which a researcher might decide which patients with a disorder are assigned to one group or another (e.g., experimental vs. control group) in a treatment study, the actual psychopathology with which the person is affected was assigned by nature. What this

50

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

means, in practical terms, is that whenever we are studying psychopathology, what we are studying is the association or correlation of group membership with some dependent variable of interest. Thus, if we are studying the relationship between schizophrenia and daily cigarette use, we are really examining the correlation between group membership (schizophrenia vs. not-­schizophrenia status) with the dependent variable (number of cigarettes smoked daily).10 Interestingly, even though group membership is assigned by nature, nature does not make all people in the group the same. One must keep in mind that there is meaningful variation in psychopathology across individuals within a given diagnostic category. This variation across individuals is not “noise” or annoying “error”11; rather, it represents, again, a nature-­assigned variation in the phenomena of interest. The correlational nature of psychopathology research raises the opportunity to review the distinction between the worlds of experimentation and correlation in psychological science. The classic, and still stimulating, treatment of this issue was given by Lee Cronbach in his 1957 Presidential Address to the American Psychological Association and was titled “The Two Disciplines of Scientific Psychology.” This paper is, once again, one of those timeless chunks of gold in the psychological science corpus. Cronbach was concerned then with what appeared to be a widening gulf between the learning and perception-­oriented psychologists, who pursued an experimental approach, and the personality, social, clinical, and developmental psychologists, who pursued a generally correlational research paradigm. On the one hand, the experimental approach seeks maximal homogeneity in its research subjects (individual differences are an annoyance to the experimenter), maximal control over experimental (laboratory) conditions, and the ability to randomly assign subjects to various treatments (investigator­controlled manipulations, or independent variables). All of this is done to minimize or eliminate any extraneous source of influence on an experimental setup in order to, ultimately, be able to infer something about the “effect” of an experimenter-based manipulation on a dependent variable of interest. If there is any variation in subjects in the experimental setup, 10 This association actually happens to represent the effect size correlation (effect-size r) for the group difference (see Rosenthal, Rosnow, & Rubin, 2000, for extensive detail). 11 This

variation can be thought of as variation across a common underlying construct or as latent heterogeneity underlying the observed distribution of scores (i.e., a mixture of scorers). For example, we could assume that there is a singular latent construct known as schizophrenia and that it shows phenotypic variation or, perhaps more realistically, that there are multiple forms of the illness that are being lumped together on the basis of phenotypic similarity. This is a complex issue in schizophrenia and schizotypy research that is addressed later in this book.

Reliability, Validity, and How We Collect Data

51

then the experimenter has fallen short of total “control” over the protocol. On the other hand, the correlational approach embodies a great interest in the individual variation in subjects. This variation would be a source of great distress for the experimentalist. According to Cronbach (1957), the correlational psychologist sees this variation as arising from various biological and social causes (interestingly, a view that would be embraced by neuroscience nearly 50 years later; see Kosslyn et al., 2002). The correlational psychologist uses the powerful correlation coefficient to calculate the association between variation in some variable of interest (loosely, the independent variable, although the correlational research does not control the independent variable per se) with variation in another variable of interest (the dependent variable in the correlational setup). For example, one might be interested in the extent to which levels of depression are associated with variation in a particular attributional (cognitive) style. As Cronbach noted, “The correlational psychologist is in love with just those variables that the experimenter left home to forget” (p. 674). It must seem to some that the experimental and the correlational worlds exist in different universes. However, just as Cronbach urged in 1957, it makes good sense to use the best of both of these worlds to gain leverage on important problems in the genesis and development of psychopathology. Indeed, experimental psychopathology seeks to make good use of individual-­difference variation, as well as the power of the experimental method, when relevant. Cronbach (1957) noted: It is not enough for each discipline to borrow from the other. Correlational psychology studies only variance among organisms; experimental psychology studies only variance among treatments. A united discipline will study both of these, but it will also be concerned with the otherwise neglected interactions between organismic and treatment variables. (p. 681).12

Just as then, we can continue to think of Cronbach’s sentiments as a strong recommendation for the use of mixed designs in research, namely, designs that incorporate information from both the individual and group levels of analysis. Cronbach (1957) saw evidence that the correlational and experimental worlds were coming together to examine interesting questions. Cronbach’s perspective, namely that individual differences matter, has been variously 12 Treatment

here refers to any manipulation that is carried out by the experimenter with the intention of studying the impact of the manipulation on a dependent variable of interest. It does not merely refer to treatments in the sense of clinical interventions or educational intervention programs.

52

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

echoed during the past 50 years, particularly as psychology has embraced the importance of biological factors in affecting cognition, emotion, and behavior.13 For example, the Northwestern University experimental psychologist Benton Underwood (1975) argued for the utility of naturally occurring individual differences in efforts to illuminate the basic structure of psychological functions and, further, that insights deriving from the study of individual differences in relation to psychological phenomena could greatly enhance (even transcend) those obtainable from group-based (i.e., treatment, experimentation) methods. Underwood urged this attention to individual differences clearly: My proposal is that we should formulate our nomothetic14 theories in a way that will allow an immediate individual-­differences test. I am proposing this because, among other benefits, I believe this approach will make individual differences a crucible of theory construction. (1975, p. 128)

It is incumbent on the experimental psychopathologist to be attentive to individual differences and to make them important sources of leverage in experimental investigations, as well as a study in their own right. The view advocated here for experimental psychopathology—­paying attention to individual differences as potential sources of research gold— has once again been echoed recently in the literature. Implicitly inspired by the views expressed by Cronbach (1957),15 Kosslyn and colleagues (2002) emphasized the spirit of integration for the experimental and correlational paradigms. Driven, in part, by the emergence of neuroimaging as a potentially useful tool in the study of cognition and affect, as well as the role of biological processes in influencing nearly all psychological phenomena, Kosslyn and colleagues (2002) recognized the utility of individual differ13 Obviously,

not all psychologists have embraced the utility of individual differences. A colleague related an anecdote to me some years ago regarding a comment made by an otherwise well-­informed researcher in a well-­regarded department of psychology. In discussing individual variation in neurobehavioral systems, my colleague related that the psychologist to whom he was speaking responded to him, “Oh, individual differences, hmmm, we don’t do individual differences in my department.” Hence the need to revisit classic papers (e.g., Cronbach, 1957).

14 Nomothetic

is a descriptive term that refers to research efforts that seek to discern broadly applicable principles for understanding psychological phenomena. In contrast, the idiographic approach focuses on the intensive study of individual cases (e.g., case history method) to understand the psychology and behavior of one person. Experimental psychopathology is a nomothetic enterprise, although valuable hypotheses and insights can be gleaned from the study of individual cases. The heuristic potential of clinical observation cannot be ignored.

15 See Cronbach (1975) for his later views on the issue of individual differences and the experimental paradigm.

Reliability, Validity, and How We Collect Data

53

ences in gaining leverage on questions within an experimental approach. They note: Appropriately collected, group data can provide a good starting point, but individual differences need to be respected if researchers are to understand the nature of the alternative mechanisms. These mechanisms can be characterized at many levels of analysis, ranging from information processing (which may or may not include aspects of phenomenological experience) to the neural structures that underlie such processing to the neuropharmacological, hormonal, and immune systems that regulate events in the body and brain. (p. 341)

Interestingly, this is a position much the same as had been advocated in experimental psychopathology prior to the appearance of neuroimaging technology. It would be useful to provide an actual research example of the integration of individual-­difference information into a between-­groups research design to show the utility of the former. In a recent investigation of brain functioning of patients suffering from borderline personality disorder (a severe personality disorder), David Silbersweig, myself, and several colleagues (Silbersweig et al., 2007; see Figure 2.5) investigated the capacity of such patients to reveal inhibition (via an experimental task) within the context of negative emotion. In short, the subjects had to control their responses (button presses) across situations in which the emotional tone of experimental linguistic stimuli was varied from positive to neutral to negative. While the subjects were carrying out this task, they were undergoing very detailed brain scanning with fMRI. In comparing the subjects with borderline personality disorder with healthy controls, it was found that under conditions associated with the interaction of behavioral inhibition and negative emotion, the subjects with borderline personality disorder showed relatively decreased brain activity in the regions associated with behavioral control (as a group). Now, could this group difference be dissected further using individual-­difference information? Within the patients with borderline personality disorder, was there meaningful variation on some individual­difference variable(s) that would further illuminate the findings? We examined the correlations between psychometric measures of the personality constructs of constraint and negative emotion. The individual-­difference information further clarified the neuroimaging results for us. Specifically, we found that decreased levels of constraint were associated with decreased levels of ventromedial prefrontal activation (a brain region known to exert

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX BOLD response at 9 18 –15 (arbitrary units)

54

8.00

4.00

0.00

–4.00

–8.00

BOLD response at –15 3 –12 (arbitrary units)

60

50 40 MPQ score Constraint

30

5.00

0.00

–5.00

–10.00 50

60

70

80

MPQ score Negative Emotion

FIGURE 2.5.  Correlations between brain activity and individual-difference personality scores on the Multidimensional Personality Questionnaire (MPQ) in patients with borderline personality disorder. In the top figure, decreasing MPQ constraint scores are associated with decreased activity in the right posterior medial orbitofrontal cortex. In the bottom figure, increasing MPQ negative emotion scores are associated with increasing activity in the left amygdala. Measurements taken during an emotional linguistic go/no-go task (see Silbersweig et al., 2007, for final report).

Reliability, Validity, and How We Collect Data

55

control over behavior) and that increased levels of negative emotion were associated with increased extended amygdalar–­ventral striatal activity (a brain region implicated in the production of emotion). What was learned through the incorporation of the individual­difference data into this group-­difference paradigm? What became clear to us was that, beyond group differences, there was indeed meaningful variation on the constraint and negative emotion personality dimensions associated with brain activation patterns within the patients with borderline personality disorder. The results also provided us with additional methodological leverage in assembling future study samples for more neuroimaging probes. In the spirit of Cronbach’s analysis, individual differences are the wheat for some researchers and the chaff for others, to be discarded.16 The wise psychopathologist will retain individual-­differences information as potential wheat. An excellent discussion of the importance of individual­differences information in psychological research can be found in Lubinski (2000). The notion here is simple: Individual differences matter.

How, Then, Do We Best Proceed in the Correlational World of Psychopathology? A question that some might justifiably ask is, How, then, in a correlational world such as psychopathology, does research make headway toward determining causality or the truth-value of a model or theory? Even though one can utilize mixed designs that incorporate experimental procedures in the laboratory study of psychopathology, is it still not the case that nature has assigned membership in the various psychopathology classes? No experimenter has assigned someone to develop schizophrenia as a human being.17 16 Some students may wonder about this wheat-and-chaff business, given that few grow up on farms these days. The expression hails from the agricultural practice of threshing wheat in order to separate the dry bracts that enclose the mature grains from the grains themselves. Threshing involves beating the stems and husks of the grain with a machine or flail to separate the wheat (seed) from the chaff (husks, stems, bracts). Of course, only the wheat is retained and put to use as a food. In science, read wheat as something valuable or worthwhile, whereas chaff represents something of little value or simply a waste item. 17 Given

that the focus of this volume is on schizotypy and schizophrenia, one could raise the issue of animal models of schizophrenia. However, to date there does not appear to be a particularly compelling animal model of the illness (notwithstanding even so-­called knockout mice that have been genetically altered for research study). This is not to say that basic science inroads have not been made with the study of nonhuman species; rather, it serves to highlight the absence of an animal model that the seasoned observer of schizotypy and schizophrenia can readily identify as having some modicum of plausibility.

56

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

In short, the road to causality and truth value in the correlational world is complex. Not unlike driving a mountain road in Central America after a torrential rainstorm, when one must be alert to all sorts of potholes, rushing streams of uncertain depth and current, and opportunities to slide off the road completely, pursuing causality in the correlational world is tricky business. However, with caution and steady progress, the mountain road can be traversed, and the same is true with respect to causality and truth value in the evaluation of correlational models in scientific psychopathology. Although beyond the scope of this volume, these critical questions have received considerable attention by sophisticated methodologists and statisticians. Although uncommon in psychopathology research, two approaches have been developed to aid in the determination of causality and truth value in the analysis of empirical data.18 The first, developed by the Harvard statistician Donald B. Rubin, is known as the Rubin causal model (1974, 2006).19 The second, developed by Niels Waller and Paul E. Meehl, is an approach to path analysis that involves novel procedures for assessing the verisimilitude (or truth value) of competing models (Waller & Meehl, 2002; Meehl & Waller, 2002). Each of these two approaches is quite different from a statistical and analytic vantage point; however, both seek to address the important issue of cause within data that cannot be thought of as derived from true experiments. In other words, both the Rubin and Waller–Meehl approaches are seeking to glean information regarding causality (Rubin) and truth value of theories (Waller and Meehl) from observational and/ or correlational data. These are complex and challenging approaches to understand, but they are rich and well worth the study.

18 More

advanced students might wonder about the procedures referred to as “causal modeling” or structural equation modeling. This approach involves fitting plausible models to observed correlational (or, sometimes, longitudinal) data; however, it is something of a misconception to think that causality is illuminated by the causal modeling approach. The issue here is not a mathematical one; rather, it is a philosophical matter. See Meehl (1993), as well as Waller and Meehl (2002), for a discussion of this issue.

19 Another

valuable resource on the issue of causality is the monograph by Judea Pearl (2009), Causality: Models, reasoning, and inference. The reader is also encouraged to download Pearl’s excellent online tutorial on “Reasoning with cause and effect” (singapore.cs.ucla.edu/IJCAI99/index.html)

Chapter 3

Practical Tools and Pragmatic Issues

In this chapter, I review a number of practical tools that I have found useful in the experimental psychopathology laboratory. These tools have helped me shape studies, as well as analyze and understand the data from them. In addition, I discuss a number of conceptual issues that have pragmatic relevance to the conduct of science in the experimental psychopathology laboratory. Each of these pragmatic issues has the potential to shape the manner in which empirical questions are framed, as well as how we extract information from the extant empirical corpus. Finally, some of the conceptual issues speak to broader issues in the conduct and sociology of science that are relevant to the development of the emerging scientist in experimental psychopathology. Power and Precision in the Comparison of Means and the Null Hypothesis A good deal of research in psychopathology relies on the use of null hypothesis testing (NHT). We focus on NHT to review its fundamental utility and, importantly, lack of utility in psychopathology research. However, prior to that discussion, the issues of power and precision should be addressed. A good deal of psychological science research, even today, lacks both power (Cohen, 1988) and precision, though more studies possess the former than

57

58

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

was true in the past.1 We will not linger on the need for adequate power in a study, a positive attribute that is rarely disputed. Suffice it to say that, prior to undertaking a study, it is clearly worth the effort to simulate the power of the study (given a hypothetical effect size). That said, it is worth noting that many researchers still do not tap the full potential of their research questions through the use of procedures that enhance not only the power of their analyses but also their precision. What is fascinating is that many data analyses would accrue an increase in statistical power through an increase in the precision of the formulation of hypotheses. Precision in this instance is discussed with two distinct analytic strategies in mind. The first is the use of one-­tailed tests in hypothesis testing, and the second concerns the (strongly recommended) preference for focused contrast analysis in the statistical dissection of data whenever possible. The probability value associated with the typical test statistic is that associated with a two-­tailed test of statistical significance. What this means, in technical terms, is that the rejection region (critical region) for the null hypothesis statistical test under consideration is divided into two components, one in the upper tail and one in the lower tail of the probability distribution. The test statistic that ensures a p < .05 finding using a two-­tailed test places .025 in the upper tail and .025 in the lower tail of the distribution of p-values. This is so because the null hypothesis—that no difference exists between two means—makes no assumption regarding which mean is higher than the other (e.g., A > B or B > A). The splitting of the rejection region over two tails covers both possibilities. So far, so good, if one is not terribly concerned with precision. What is meant here? Let us assume there is good reason to suspect that a group of schizotypic subjects display markedly poorer sustained attention performance than a control group. Does it make sense to split the rejection region of the statistical test in two and place it in the respective tails of the probability distribution? Is this the most powerful way to evaluate the null hypothesis? Is this the most precise way to evaluate the null hypothesis? The answer is no to both questions. Assuming a relatively rigorous a priori prediction (or even a justifiable research hunch), a one-­tailed test of statistical significance better serves the investigator’s goal. This is so because the a priori hypothesis is focused (it has a directional nature and is therefore more precise) 1 Psychological

science owes much to the insights of Jacob “Jack” Cohen (1988). His seminal work on statistical power, or the ability to detect a genuine effect when it is present, transformed the field. Indeed, modern grant applications must (nearly always) have a “power analysis” section in them; absent such a section, one’s grant application is not likely to have a hope of funding by a major funding agency.



Practical Tools and Pragmatic Issues

59

and because it has increased power (because the entire rejection region for the statistical test has been placed in one tail of the distribution). This is rather a straightforward approach, especially as it buys the investigator both precision and power in the detection of real differences. However, for reasons that I cannot claim to understand, the one-­tailed statistical test still causes a certain amount of anxiety among some psychologists. I have seen reviews in which the criticism of the one-­tailed test very nearly implies a certain degree of “cheating” or “witchcraft” in statistical analysis. Such criticisms reflect a failure to appreciate the issues of power and precision. The one-­tailed testing option makes the investigator work a little harder on the substantive front end of a study, requiring a model or hunch worthy of one-­tailed testing. It is assumed that the model or hunch is not some gratuitous notion cooked up just to divide the p-value in half. If a one-­tailed test (and its associated p-value) really makes one nervous, I would recommend simply multiplying the one-­tailed value by 2.2 Continuing the discussion of precision and power, let us consider contrast analysis. Contrast analysis is an important data analytic approach within the analysis of variance (ANOVA) framework. I prefer to think of it as the “modern” approach to the evaluation of group means. Psychology research relies very heavily on the use of group comparisons, and this is particularly true where group status has been assigned by nature, such as in psychopathology research.3 The mantra I try to convey to my students goes something like this: “If you are going to take the trouble to think through your idea, read the literature carefully, design an experiment carefully, and collect your data with care, then why would you analyze your data in an unfocused manner that lacks power, precision, and the care reflected in the rest of your project? Use focused contrasts.” My use of contrasts has been influenced heavily by the work of Robert Rosenthal and Ralph Rosnow and their gem of a book, slender but potent, Contrast Analysis: Focused Comparisons in the Analysis of Variance (Rosenthal & Rosnow, 1985). I should note in this context that, although I refer to the focused contrast approach 2 A

colleague of mine once said of the one-­tailed test, “I don’t see what the big deal is, most psychologists can multiply or divide by 2 if they are so worried about one- and two-­tailed p-values.” Clearly the issue does not merely turn on simple mathematical operations but rather some a priori thinking on the part of many researchers.

3 For

reasons I fail to understand, some researchers continue to have a poor understanding of, and therefore bias against, focused contrast analysis. Some just seem to prefer the omnibus, unfocused ANOVA. I recall one particularly amusing circumstance in which an editor at a prestigious journal required a colleague to report the results of the unfocused ANOVA for an analysis that had been done initially using focused contrast analysis. This was requested even though the unfocused ANOVA results contributed essentially nothing of substantive value.

60

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

to ANOVA as “modern,” it is worth noting that Rosenthal and Rosnow (1985) developed ideas for this method that carried the spirit of data analysis embedded in an even earlier unpublished treatment (of which they were unaware at the time they wrote their book) by Robert Abelson. On the method of contrasts, Abelson wrote in 1962 (as quoted in Rosenthal & Rosnow, 1985, p. 90) (see Box 3.1): This method dates back virtually to the invention of the analysis of variance itself. . . . It is well-known to most statisticians and to some psychologists, but it has received only the most cursory and off-hand treatment in standard statistical reference works . . . and presentations by psychologists of some of its uses have tended toward very specialized applications. . . . Actually, the

BOX 3.1. Comparison of Unfocused ANOVA and Focused Contrast Analysis Mean performance at various age levels (10 subjects in each group) Ages:

11

12

13

14

15

Mean:

25

30

40

50

55

Theoretical question: Does psychomotor skill improve with age? Standard “unfocused” (aka “omnibus”) one-way analysis of variance: F (4, 45) = 1.03, p = .40 Problems with the unfocused ANOVA: Low precision, low power, omnibus F-test is largely uninformative as regards our question. Focused contrast analysis on same data: Converting our theoretical question into a set of ordered means depicting a linear trend using method of contrast weights (i.e., age levels are such that: 11 < 12 < 13 < 14 < 15) Focused contrast result: F (1, 45) = 4.06, p = .05. Value of the contrast: Power, precision (we actually answered our theoretical question), and interpretability (performance levels increase with age of the children). Adapted from Rosenthal and Rosnow (1985).



Practical Tools and Pragmatic Issues

61

method of contrasts is extraordinary for its wide range of varied uses. That the method has not heretofore received a comprehensive, unified treatment is a matter of some mystery. One compelling line of explanation is that statisticians do not regard the idea as mathematically very interesting (it is based on quite elementary statistical concepts) and that quantitative psychologists have never quite appreciated its generality of application.

Anecdote Some years ago I was coleading a data analysis seminar (known as “stat lunch”) at Harvard with my statistician colleague Donald Rubin. The idea of stat lunch was straightforward; students and faculty brought in all sorts of design, method, and statistical analysis questions for discussion. Students would routinely make a brief presentation, then we would chew on the research ideas (as well as our lunches) for an hour or so. One particular session stands out clearly in memory for what it told me about the (mis)use of ANOVA in psychopathology research. A student presented on results obtained from a psychophysiological investigation that involved a repeated-­measures design with one between-­subjects factor (2 levels) and 4 within-­subjects factors (2 levels each)—or a 2 × 2 × 2 × 2 × 2 design. The earnest (and smart) student presented the study design beautifully, brought us all up to speed on the methods and data idiosyncrasies of psychophysiological research, and then proceeded to the central question (of which we were unaware at the start of the lunch). The student stated, “I am trying to understand the five-way interaction that is significant.” One could hear a pin drop in the room (given that our philosophy was to emphasize a priori focused contrasts in ANOVA work). After a few moments passed, my colleague Rubin broke the silence with a simple question: “Hmmm, a five-way interaction. Do you know what a five-way interaction means? Because I don’t.” And so began another (à la Pete Seeger, “we might as well sing ’er once again”) discussion of the value of focused contrast analysis—power, precision, and meaning. Mindful of the complexities of psychophysiological research, I relate this anecdote because we must always remind ourselves to seek simplicity in our ANOVA analyses to foster the most power and precision and greatest meaning extraction we can in the work.4

4 In

this session we slowly unpacked the substantive questions at hand and boiled down the analyses to a few well-­articulated contrasts. We left the big, unfocused, multifactorial ANOVA by the side of the road, so to speak.

62

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

Anyways: The Null Hypothesis Is Quasi-­Nearly Always False Most psychology students are introduced to statistics in the form of a course taken normally in the second or third year of college. Such a course reviews basic principles of descriptive statistics (means, standard deviation, the normal curve) and introduces the student to a number of statistical procedures such as the t-test, the correlation coefficient (our good friend r), the chi­square test, and, typically, the one-way ANOVA. Statistical tests (inferential statistics) are taught in relation to null hypothesis testing (NHT). The context in which these tests are typically taught is the hypothesis that no effect exists. In the case of a difference between means for two subject groups on some measure of interest, the null hypothesis (H0) states that no difference exists between the two groups (X, Y), whereas the alternative hypothesis (Ha) states that a difference does exist. A test statistic (e.g., a t-value) is calculated, referenced against critical values for the sample size in question, and a probability (p) value is obtained. It is not unusual for the student not to be taught to specify a direction of the difference implied in the Ha; rather, it is just enough to assume a difference exists (either X > Y or Y > X). If the p-value attains the “sacrosanct” value of p ≤ .05 or less, then “a difference” has been found, and all is well in the world. The problem with the entire NHT enterprise is that the null hypothesis in psychological science is quasi-­nearly always false (Meehl, 1967). What does this mean? In short, given that psychologists rarely do more than test the presence or absence of differences between two or more groups or test the significance of a correlation coefficient (or chi-­square value), they do little more than hope for a statistically significant result (i.e., a p-value that allows one to reject the null hypothesis in good conscience). The difficulty with this approach is that, sooner or later, one will always be able to reject the null hypothesis, especially as one increases the size of one’s sample (which increases power). The problem here is not with the mathematics or any computational issue; the problem resides in the fact that we are attempting to evaluate hypotheses (or notions derived from models) using a method that will nearly always deliver the same result assuming large enough samples—­namely, rejection of the null hypothesis. Aside from the sample-size issue, following Meehl (1990b), there are other reasons the NHT approach is flawed as typically applied in psychology: such as (1) the (ir)relevance of NHT to theory testing, (2) the lack of well-­articulated and reasonable statistical expectations for most applications in psychol-



Practical Tools and Pragmatic Issues

63

ogy, (3) the usual focus on naturally assigned grouping distinctions (i.e., nonexperimental designs), and (4) although there is a negligible difference between the substantive theory of interest and the counter null hypothesis in agronomy, . . . in theoretical soft psychology they are distinctly different and frequently separated by what one could call a large ‘logical distance’ (Meehl, 1978). The problem with the NHT approach led Meehl (1990b) to assert that it was among the worst offenders in making most qualitative literature reviews uninterpretable. Because the null-­hypothesis is quasi-­nearly always false. The perplexed student may be wondering, What then? What am I to do? If I cannot rely on my NHT approach, then how best do I proceed with my research? If this is what is in your mind as you read this, then you are on your way to doing better psychological science. The fact is that the field still relies heavily on the NHT approach, the p-value still rules the day in the eyes of most investigators and editors,5 and alternative approaches to statistically evaluating data are looked at askance by many with a mixture of anxiety and resistance to change. To remedy this dilemma, I (and many others) believe the field should move more in the direction of evaluating point predictions (as is done in physics, for example), make use of confidence intervals more often, and keep effect-sizes in mind (as opposed to simply paying attention to p-values). The statisticians I have known show remarkably little interest in p-values when conducting their work, and there is probably a reason for that. The interested student is referred to Meehl (1998/2006) and references therein as well as Cohen (1994) for additional discussion of this issue.6

5 I

do not seek to irritate journal editors in suggesting an implicit (probably negative) publication bias with respect to the p < .05 criterion. But there really is nothing at all magical about the p < .05 criterion. I often tell my students an anecdote about an instance in which, during the review of a manuscript I submitted, an editor “insisted” that a p < .057 was “not significant,” despite a moderate to large effect size (Cohen’s d > .50). Master methodologists Robert Rosenthal and Ralph Rosnow quip, “we want to underscore that, surely, God loves the .06 nearly as much as the .05. Can there be any doubt that God views the strength of evidence for or against the null as a fairly continuous function of the magnitude of p?” (Rosnow & Rosenthal, 1989, p. 1277). I remind my students that God (or the Goddess) does not see the scientific bus going over a cliff just beyond p = .05.

6 The

controversy regarding the use of null hypothesis testing and statistical significance in psychological science has a long and rich tradition. It is not a new problem. The reader is referred to Meehl (1990) and references therein for a thoroughgoing discussion of the significance-test controversy. Classic early discussions of this issue can be found in Bakan (1966), Bolles (1962), Lykken (1968), Meehl (1967), and Rozeboom (1960). See also Shrout (1997) and the special issue of Psychological Science on this topic (8(1), January 1997); see also Hunter (1997).

64

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

Statistical Significance versus Scientific Significance: Appreciating the Effect Size One of the most challenging bits of thinking to undo in new graduate students, after we have spent a good deal of effort inculcating it in them as undergrads, concerns the issue of statistical significance and just how uninformative it can be. Clearly, students often throw a great deal of effort into learning how to use inferential statistics, and in the process they are empowered with a new set of tools. Think about it: You are suddenly capable of doing a t-test to compare means between two groups or running a correlation coefficient to assess the degree of association between two variables. One of my students once told me, with great enthusiasm, how good it felt to explain to her extended family at the Thanksgiving table the proper way to assess a presumed association between two variables. These are useful tools, but the degree to which these statistical tools have been wed to “statistical significance” and probability levels compared with their importance is what poses the problem. Statistical significance does not necessarily mean or translate into scientific significance. This can come as a rude awakening to some students, but it represents what I like to think of as one instance of very helpful “optimal disillusionment.” In this context we need to discuss and insist on the use of effect sizes in the reporting of statistical findings. Effect size (ES) is the name given to a group of quantitative indexes that measure the magnitude of a treatment effect or the strength or magnitude of a relationship. In other words, the ES is simply a way of quantifying the difference between two groups, the association of group membership (independent variable) with individual scores on a variable of interest (dependent variable), or the degree of association between two quantitative variables of interest. Note that none of these definitions involves the notion of statistical significance; rather, they have to do with size, magnitude, degree, and strength of relationships. Despite a long procession of individuals pointing to the utility of effect sizes in assessing the magnitude of findings as a way of extracting meaning in psychological research—­Hunter, Schmidt, and Jackson (1982); Cohen (1994), Rosenthal and Rosnow (1991; see also Rosnow & Rosenthal, 1989) to name but a few—the continued fascination with p-values remains strong in grant application study sections, journals, and dissertation prospectuses. When evaluating effect sizes, not unlike the situation involving directional testing, the substantive model guiding the work must be kept in mind. Typically, one is interested in seeing large effects in a research effort, which



Practical Tools and Pragmatic Issues

65

then speak to scientific significance of the work. However, “bigger is not always better.” For example, it is important to realize that sometimes a small effect is a large effect. What can this possibly mean? Imagine that one discovers through the study of a large number of individuals that a relatively inexpensive and easily available medication can reduce the risk of heart attacks. The ES associated with the treatment effect of the medication may actually be small, but when it is converted into the number of lives saved by use of the medication, one can see that the meaning of the small effect can be large. There may also be instances in which effect sizes are expected to be small and that would be completely consistent with the theoretical model at hand. For example, in a study of endophenotypes for schizophrenia liability in a large, unselected nonclinical population, we (Lenzenweger & O’Driscoll, 2006) found that the association between deviance on the endophenotypic indicator of schizotypy (eye-­tracking dysfunction) and scores on a measures of schizotypic personality features was relatively small by way of an effect size (but the association was statistically significant!). The magnitude of the effect for eye-­tracking dysfunction, in this instance, made perfect sense given the model, what was expected, and how it would relate to other findings of clinical populations that included many persons with schizophrenia (see Lenzenweger & O’Driscoll, 2006). In this example, a small effect was a small effect, just as it should be in light of theory.7 Most findings in psychological science are associated with r’s of .10 to .30, and this range of correlations suggests small to medium effect sizes. So, even when evaluating ES in relation to a research finding, one must always ask oneself, “Is this an effect that scientists would want to pay attention to, make use of in further work or practical application?” Perhaps most important of all, do not leave an ES out of the discussion of your results—it should always be considered. Over the years, in addition to the usual ES indexes such as Cohen’s d and the ES r, I have found it useful to use the handy technique known as the binomial effect size display (BESD) to understand and present the magnitude of effect sizes to students and colleagues. What is the BESD? Rosenthal and Rubin (1982) describe it as “an intuitively appealing general purpose effect size display whose interpretation is perfectly transparent” (p. 166). In short, the BESD is a very straightforward and clear-cut way to represent an ES. The BESD depicts the effect on the success rate of a manipulation or treatment. The change in the rate of success related to a treatment or interven7 It was fascinating to see some reviewers struggle with the notion that statistical significance was not at issue in this work and that we expected our effects to be relatively small. This position flew against the prevailing winds of the necessity of statistical significance and large effects. Sometimes, a small effect is a large effect vis-à-vis the theory at hand.

66

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

tion is portrayed in a simple two-by-two (two rows, two columns) setup. The BESD accomplishes something very elegant, namely, it conveys, according to Rosenthal and Rubin, the real-world importance or meaning of treatment effects. I have found many students can easily grasp the intuitive meaning of an effect from the BESD as compared with some other effect-size estimates (e.g., proportion of variance accounted for). Consider a study in which a treatment was administered (or not) to research subjects, and we measured the outcome of the study in terms of “less benefit” or “greater benefit” (or, roughly speaking, the survival rate). Let us represent a modest effect size corresponding to an r of .32 in the form of a BESD (see Table 3.1). Looking at the table, one sees that even in an instance in which a relatively modest effect was found in the results, the difference in the treated versus untreated subjects in terms of ultimate outcome is rather impressive. It surely could be easily dismissed by some as “too small to be important.” Consider that the treatment in this example yielded an improvement in the benefit (or success) rate from 34 to 66% (these data also suggest that the treatment reduced the poor-­benefit rate from 66 to 34%). How does one arrive at these figures? It is really quite an easy thing to do. Rosenthal and Rubin (1982) demonstrated that the effect size information in the form of the well-known correlation coefficient (r) can be easily converted into the entries for the BESD. The “success rate” (or “greater benefit” rate) in the treatment group is computed as .50 + r/2, whereas the control group success rate is computed as .50 – r/2.8 The BESD can be computed using the phi coefficient as well, and, as illustrated, the outcome (success rate) variable need not necessarily be dichotomous in nature (i.e., a quantitative outcome can be dichotomized). The BESD makes the practical impact of a treatment easily visible, and, when used appropriately (i.e., as intended by Rosenthal & Rubin, 1982), the TABLE 3.1. The Binomial Effect Size Display: A Treatment That “Accounts for Just 10% of the Variance” Treatment outcome classification Condition

Less benefit

Greater benefit

S

Treatment Control S

34 66 100

66 34 100

100 100 200

8 Rosenthal and Rubin (1982) provide a handy table for obtaining BESD entries for effect sizes of varying size.



Practical Tools and Pragmatic Issues

67

BESD is statistically well grounded and justified. When a more conventional ES measure does not convey the message, consider the BESD. The BESD has been particularly useful in trying to understand what might otherwise be regarded as small or subtle effects. Remember, “sometimes a small effect is a large effect”—for example, see Rosenthal and Rosnow’s (1991) discussion of a major study that found aspirin can reduce heart attack risk. In that particular study, the number of lives saved after heart attack in the aspirin condition of the study was small by most standards but highly meaningful when one considers the outcome was life versus death (see Rosenthal & Rosnow, 1991, pp. 42–43).

The Infamous Issue of Statistical Control Once students move on in their statistical training from basic correlational (Pearson r) methods and comparisons of means (e.g., t-test, one-way ANOVA), they are often introduced to complex methods of handling data. These methods are at once both powerful and seductive, while fraught with hidden interpretive dangers. For example, it is not uncommon for students to learn about partial correlation (as noted before) or analysis of covariance (termed ANCOVA). In partial correlation, the effect of a third variable (z) is removed from the relationships between two other variables (e.g., x and y). In ANCOVA the effects of a quantitative covariate are removed from the scores of study subjects (using a regression procedure) prior to the comparison of means. The resulting means—­referred to as covariance adjusted means—are then compared within an ANOVA (F-test) framework. In many instances, one conducts a partial correlation or ANCOVA in order to remove the effect of what one decides is a nuisance variable, a variable that muddies the water and one that the investigator would like to remove from the picture. Herein lies the seduction and the pitfall—it is seductive to think that one can use a statistical procedure to simply eliminate the effects of a problematic (nuisance) variable. However, the pitfall (unbeknownst to many, even some seasoned, investigators) is that in carrying out one of these statistical excisions, one has altered the underlying organization of those constructs that originally gave rise to the observed data. In short, one is left with the effects of a statistical manipulation that may have warped (corrupted?) the underlying nomological network to the point of rendering the remaining data as essentially uninterpretable. Meehl discussed this problematic issue in his classic “High School Yearbooks” (Meehl, 1971), in which he demonstrates the potential confu-

68

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

sion wrought by the idea of statistically controlling for the influences of variables that one would like to be rid of in one’s data set. In short, through a comparison of competing substantive models consisting of several variables in play in a previously published study, Meehl (1971) shows how one can truly obscure the meaning of obtained results if one is not reasonably clear on the relations among the latent constructs under study. Of course, statistical control approaches are carried out typically post hoc, namely, after the data have been collected. The methodological moral here is be careful with ex post facto statistical control approaches. Miller and Chapman (2001) present a useful discussion of the limitations and problems associated with the use of ANCOVA in psychopathology research. Similar substantive problems—­misalignment of the underlying network of relations—can be introduced into data from the inception of data collection, when one resorts to matching samples on one or another parameter in an effort to equalize the samples in some manner (e.g., matching on age, sex, education, or social class). The matching alters relationships among the constructs in play in a manner that often precludes unambiguous interpretation, at best, or, at worst, renders data relatively useless for addressing a problem. Finally, more defensible approaches to assembling samples with comparable background characteristics do exist. An excellent example is Rubin’s propensities analysis methodology (Rosenbaum & Rubin, 1984; Rubin, 1997; see also Vanderweele, 2006).

Post-Hoc Analysis of Data: It’s OK to Play One of the strangest things that I have encountered in students (and some faculty members) is the quasi-­unshakeable belief that one is allowed to test in a data set only hypotheses that were formulated before data collection. Undergraduates have said, “Professor X told me I could only test one hypothesis in my data.” I normally respond by suggesting, gently, that perhaps they misunderstood Professor X. Such students will reassure me that they were told that “only hypotheses specified prior to data collection can be tested.” I generally set about happily disabusing them of such notions by probing the data sets that they worked so hard to collect to find any number of interesting findings. I have had graduate students call me in a panic due to a research-­methodological crisis related to their desire to probe another hypothesis in their data set beyond those specified in their research prospectus. I respond, “Good grief! How sacrilegious! You mean you really want to run a t-test that was not specified in your proposal?” I continue, “Of course



Practical Tools and Pragmatic Issues

69

you do! Of course you can!” Moreover, I have seen otherwise talented faculty maintain with great vigor the belief that students must articulate a priori in their dissertation proposals every analysis that they plan to do. And that no others will be allowed! Finally, it has been my experience that in the process of publishing empirical research, it is not uncommon to run across what can only be termed a publication bias against post hoc analyses of any sort. My main point is simple: “Mindful” exploration—note the term mindful—of data after the a priori hypotheses have been examined through post hoc analysis is to be encouraged. There seems to be a largely unprincipled objection to post hoc analysis burned deeply into the cortex of many psychologists. Where does this objection come from? It comes from the mistaken notion that everything that can be possibly known about a phenomenon will be known beforehand, and, therefore, only analyses linked to that a priori (pseudo)-understanding of a phenomenon are allowed. Let us be rather straightforward about this: The data we collect are collected with a great expenditure of time, effort, money, and the kind cooperation of innumerable research subjects. It makes no sense to believe that one can tap a data set for only a selected few correlation coefficients, t-tests, or a single contrast and then pack it up, place it on a shelf, and allow it to gather dust in boxes. Hans Reichenbach (1891–1953) wrote in his 1938 monograph Experience and Prediction about the distinction between what he called the context of discovery and the context of justification. The context of discovery refers to the thinking processes of the scientist involved in the research process. The discovery process need not be particularly orderly, grounded in extensive theory or a model, or cleanly linear in the unfolding of new insights or knowledge. It is where we ponder a puzzle, consider various angles on a problem, and allow our ideas to develop freely. In terms of data analysis, this is the point at which we probe data, come to know them, ask questions of them, look at them from different angles, and seek illumination. Theory may play a little role here. It might provide some ideas about where to look for something interesting in the data or how to look at the data differently to gain some leverage, but it need not constrain the enterprise of discovery. Experienced researchers, for example, know that the material that ends up in scientific reports is highly ordered and coherent, whereas the nature of the investigative and creative process giving rise to the final published result is typically far from such a pristine ideal. This is really quite acceptable. Much work is done within the context of discovery, and one need not be preoccupied with confirming relationships in some definitive manner or hoping that the discovery process will be a highly polished, linear affair.

70

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

The scientist who discovers a theory is usually guided to his discovery by guesses; he cannot name a method by means of which he found the theory and can only say that it appeared plausible to him, that he had the right hunch, or that he saw intuitively which assumption would fit the facts. . . . The act of discovery escapes logical analysis; there are no logical rules in terms of which a “discovery machine” could be constructed to take over the creative function of the genius. But it is not the logician’s task to account for scientific discoveries. . . . (Reichenbach, 1956, pp. 230, 231)

In writing on the distinction between the context of discovery and the context of justification, Reichenbach (1956) also provided a profoundly rich description of the essence of the context of justification. The context of justification refers to the process of evaluating a formally presented theory or model (available in some written form). The justification notion concerns the effort to confirm or disconfirm, the seeking of definitive evaluation, or subjecting a theory (or model) to a genuine test or attempt at falsification. In other words, justification is where the “rubber meets the road” and we subject our claim, thesis, model, or hypothesis to some form of evaluation or test (see also Meehl, 1990c). Some might find this all rather perplexing. Much of this discussion flies in the face of what many believe (and may have even been taught) is the process of science. The illusion that science and the process of discovery is necessarily a highly linear, step-by-step process, moving from hypothesis to study to analysis to research report, is really rather something of a fiction. This seems like a particularly helpful time (and place) for a sermon on this topic. Box 3.2 presents the thoughts of the noted Cornell personality psychologist Daryl J. Bem.

Example Post hoc analysis and the context of discovery really go hand in hand. ­Consider this example of fruitful post hoc analysis and resultant discovery in research on psychomotor performance and schizotypy with my colleague Brendan Maher. We indeed had a priori hypotheses to examine during the initial analysis of the data, and we did so. For example, we argued that ­deviations in psychomotor performance, known to characterize people affected by schizophrenia, were associated with schizotypic deviance (assessed by measures tapping the putative liability for schizophrenia). Moreover, these associations could not be explained away by other factors, such as general intellectual ability, anxiety, depression, or inattention



Practical Tools and Pragmatic Issues

71

BOX 3.2. A Sermonette on the Analysis of Data: Erring on the Side of Discovery Daryl J. Bem The conventional view of the research process is that we first derive a set of hypotheses from a theory, design and conduct a study to test these hypotheses, analyze the data to see if they were confirmed or disconfirmed, and then chronicle this sequence of events in the journal article. If this is how our enterprise actually proceeded, we could write most of the article before we collected the data. We could write the introduction and method sections completely, prepare the results section in skeleton form, leaving spaces to be filled in by the specific numerical results, and have two possible discussion sections ready to go, one for positive results, the other for negative results. But this is not how our enterprise actually proceeds. Psychology is more exciting than that, and the best journal articles are informed by the actual empirical findings from the opening sentence. Before writing your article, then, you need to Analyze Your Data. Herewith, a sermonette on the topic. Analyzing Data Once upon a time, psychologists observed behavior directly, often for sustained periods of time. No longer. Now, the higher the investigator goes up the tenure ladder, the more remote he or she typically becomes from the grounding observations of our science. If you are already a successful research psychologist, then you probably haven’t seen a participant for some time. Your graduate assistant assigns the running of a study to a bright undergraduate who writes the computer program that collects the data automatically. And like the modern dentist, the modern psychologist rarely even sees the data until they have been cleaned by human or computer hygienists. To compensate for this remoteness from our participants, let us at least become intimately familiar with the record of their behavior: the data. Examine them from every angle. Analyze the sexes separately. Make up new composite indexes. If a datum suggests a new hypothesis, try to find additional evidence for it elsewhere in the data. If you see dim traces of interesting patterns, try to reorganize the data to bring them into bolder relief. If there are participants you don’t like, or trials, observers, or interviewers who gave you anomalous results, drop them (temporarily). Go on a fishing expedition for something—anything— interesting. No, this is not immoral. The rules of scientific and statistical inference that we overlearn in graduate school apply to the “Context of Justification.” They tell us what we can conclude in the articles we write for public consumption, and they give our readers criteria for deciding whether or not to believe us. But in the “Context of Discovery,” there are no formal rules, only heuristics or strate-

72

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

gies. How does one discover a new phenomenon? Smell a good idea? Have a brilliant insight into behavior? Create a new theory? In the confining context of an empirical study, there is only one strategy for discovery: exploring the data. Yes, there is a danger. Spurious findings can emerge by chance, and we need to be cautious about anything we discover in this way. In limited cases, there are statistical techniques that correct for this danger. But there are no statistical correctives for overlooking an important discovery because we were insufficiently attentive to the data. Let us err on the side of discovery. Reporting the Findings When you are through exploring, you may conclude that the data are not strong enough to justify your new insights formally, but at least you are now ready to design the “right” study. If you still plan to report the current data, you may wish to mention the new insights tentatively, stating honestly that they remain to be tested adequately. Alternatively, the data may be strong enough to justify recentering your article around the new findings and subordinating or even ignoring your original hypotheses. This is not advice to suppress negative results. If your study was genuinely designed to test hypotheses that derive from a formal theory or are of wide general interest for some other reason, then they should remain the focus of your article. The integrity of the scientific enterprise requires the reporting of disconfirming results. But this requirement assumes that somebody out there cares about the hypotheses. Many respectable studies are explicitly exploratory or are launched from speculations of the “I-wonder-if . . . ” variety. If your study is one of these, then nobody cares if you were wrong. Contrary to the conventional wisdom, science does not care how clever or clairvoyant you were at guessing your results ahead of time. Scientific integrity does not require you to lead your readers through all your wrongheaded hunches only to show—voila!—they were wrongheaded. A journal article should not be a personal history of your stillborn thoughts. Your overriding purpose is to tell the world what you have learned from your study. If your results suggest a compelling framework for their presentation, adopt it and make the most instructive findings your centerpiece. Think of your data set as a jewel. Your task is to cut and polish it, to select the facets to highlight, and to craft the best setting for it. Many experienced authors write the results section first. But before writing anything, Analyze Your Data! End of sermonette. From dbem.ws/online_pubs.html#writing. Reprinted with permission from Daryl J. Bem.



Practical Tools and Pragmatic Issues

73

(see  Lenzenweger & Maher, 2002). Thus our scientific venture unfolded nicely along theory-­guided lines and planned analytic strategies. However, data sets cost a good deal in time, energy, and money to collect. Thus we owe it to ourselves, our subjects, and the field to explore the data fully. As Bem notes (see Box 3.2), “Think of your data set as a jewel. Your task is to cut and polish it, to select the facets to highlight, and to craft the best setting for it.” In this spirit, the spirit of the “context of discovery,” we set about cutting, splitting, and polishing. One thing that we (Lenzenweger & Maher, 2002) were particularly interested in was an itemlevel analysis of the responses to the individual questions on the Perceptual Aberration Scale (PAS), which was the strongest predictor among the set of four schizotypy indexes in the prediction of psychomotor deviation (known as logRMS). Interestingly, although the PAS is an excellent psychometric instrument and the PAS items hang together in a manner that is the envy of many test construction efforts, the item content is, at the same time, varied and rich. Thus, although the test is very homogeneous, we suspected there was potential variability and richness to be explored in the PAS item set. In short, we wanted to know whether there might be specific items in the overall set that made up the scale that would be especially predictive of deviations on the psychomotor task we were studying.9 To accomplish this, we conducted an exploratory regression analysis at the item level for the PAS in relation to logRMS. What made this an exploratory analysis was that we had no a priori hypotheses as to which PAS items would emerge as particularly important as predictors of poor line-­drawing performance. Rather, we were operating in the context of discovery. We conducted this regression analysis using a forward-­stepping approach,10 and what did we find? The following two of the 35 PAS items entered the regression equation: “I have had the momentary feeling that my body has become misshapen” (r = .26, p < .004). “Sometimes I feel like everything around me is tilting” (r = .18, p < .05).

9 This 10 The

particular study is discussed in greater detail in Chapter 9, this volume.

same results emerged even when we used different methods of entering the data into the regression equation. It is always a good idea, in regression analysis, to take the time to use several different data entry methods to see whether generally the same results emerge from the alternative approaches as emerged from your favorite data entry technique (see Darlington, 1990; Cohen & Cohen, 1983) for a more detailed technical discussion.

74

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

What does the content of these items suggest? We see, first, an item that speaks to momentary experiences that suggest to a person that his or her experience of his or her body has changed, changed enough that one might think the body has become misshapen. Think of the feeling one has in the face and lips after an injection of procaine (Novocaine) during some dental work. One’s lip often feels warm, fuzzy, and as if it is ten times its normal size. It is an odd sensation indeed. Or consider the full feeling associated with the consumption of a large meal (e.g., say on Thanksgiving Day). One is convinced that the body has become misshapen. The second item speaks to the experience of the world seeming to tilt. Anyone who has been on a carnival amusement ride (e.g., the well-known Tilt-a-Whirl ride) can attest to oddness associated with the feeling of suddenly losing one’s bearings and feeling as if the world is not as level as one expects it to be. Or consider that odd feeling that some people have in very tall skyscrapers11 when the altered body position sense generates the idea that, “Whoa, this building just moved, the darned thing swayed.” To us, these items suggested something noteworthy regarding the proprioceptive system, the aspect of the nervous system that concerns body sense as well as the experience of kinesthetic stimuli (the stretching of tendons, tension on muscle tissue). We considered these post hoc analysis results as heuristically rich and possibly leading to new insights. Though we discussed these findings briefly in the original version of Lenzenweger and Maher (2002), we were asked to remove these “post hoc findings” from our paper during the review process. The findings were considered “too speculative.” So what happened? We removed the “offending” results and theoretical speculation from our report. However, we continued on with the heuristic supplied by this item analysis and were able to fruitfully explore the proprioceptive system in the first-­degree relatives of schizophrenia patients (see Chang & Lenzenweger, 2005; see also Chapter 9, this volume). The methodological moral here is a simple one: Allow yourself the freedom to conduct post hoc analyses of data and you just may stumble on some particularly luminous jewels. Psychological science might move ahead more quickly and in more interesting directions if our journals would become more comfortable with allowing investigators to include the results of post hoc analyses in their articles. To facilitate post hoc analysis, the interested student is encouraged to find an old copy of John Tukey’s (1977) classic volume titled Exploratory Data Analysis, break 11 Apparently the former World Trade Center towers that stood in New York City prior to September 11, 2001, would sway upward of 12 inches either way during a strong wind.



Practical Tools and Pragmatic Issues

75

out a ruler and some real graph paper (you can still buy it!), and make them your friends and helpers in the exploration of your data. Post hoc analysis is also another wonderful venue in which to use contrast analysis to “snoop around in your data” (Rosenthal & Rosnow, 1985). Go ahead, explore your data; do not be afraid to do so. You may find some real gems.12 Another way to think about post hoc analysis is that it almost necessitates a letting go of preconceptions about data and allowing the data to speak to you in some manner.13 In fact, to do so might be the only way to see order in the data. This discovered order can then be the focus of research downstream from the original study. Though from a different domain entirely, consider this attitude when exploring your data: It is said that if we take one thing to be the truth and cling to it, even if truth itself comes in person and knocks at our door, we won’t open it. For things to reveal themselves to us, we need to be ready to abandon our views about them. (Hanh, 1987, p. 42)

Cleaning, Deleting, and the Problem of Missing Data Graduate students often speak of “cleaning up their data” prior to statistical analysis. I am always curious as to what this means. Typically, it suggests pruning out of outliers, application of various transformations to normalize distributions, and the substitution of certain values in instances of missing data. I often ask students, “Why are you doing this?” They will typically respond, “Professor So and So or the Thus and Such text told me to do 12 Post hoc analysis, in some ways, can be thought of as allowing data to speak to us with a little coaching. On occasion, serendipity will play a role in facilitating the discovery process during post hoc analysis. Although one should not rely on it, serendipity is not to be underestimated as an important factor in scientific discovery. Moreover, as observed by Grinnel (1987), many advances in science are the result of “happy guesses” and “felicitous strokes of talent” (p. 24). Thus serendipity and a dose of good luck account for many strides forward in the corpus of scientific knowledge. For example, consider the psychopharmacological discoveries that antidepressant medication could improve panic disorder symptoms, that chlorpromazine (a medication for operative and anesthetic shock) worked well for psychosis, and that lithium (a salt and medication for gout) worked well to reduce manic symptoms. 13 I

note that post hoc exploration of data is entirely different from the somewhat driven (almost desperate) “slice and dice” approach to data in an effort to “squeeze a significant finding out of them.” In the latter, a preconceived idea about how results “should look” is the driving force in the analysis. Such an approach, I suggest, has left the world of science and moved a bit more (dangerously) close to dogma or faith. Nor should post hoc analysis be misunderstood to mean “let’s just push ‘run’ on the correlation program and see what pops out.”

76

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

it this way.” This is unsatisfactory, especially in psychopathology research. What does it mean to prune out outliers? Is it not the case, particularly in psychopathology, that nature will deliver up outliers? Is it not the case in psychopathology that many measures will yield distributions of scores that are skewed? That skew is not an artifact—again, it is what nature delivers up. In psychopathology, we are oftentimes very much concerned with precisely those subjects that normative research approaches might deem as outliers. In the realm of schizotypy, it makes considerable sense to think that schizotypes may actually live far out in the tails of a distribution; they do not represent mistakes or anomalies. My recommendation, which is short and sweet, is: Do not immediately jump to pruning and transforming your data to make them pretty—­nature delivers up messy data, and that is OK! A brief word about what one is to do about missing values. Please resist temptations to simply substitute means and such for missing values. If one must confront missing data—and we very nearly always do need to confront such a circumstance in the real world of psychopathology research— then proper methods should be used, specifically the multiple imputation approach developed by Rubin and colleagues (Little & Rubin, 1987; see Schafer, 1999, for an excellent tutorial). Multiple imputation is a complex topic beyond the confines of the current discussion; however, the psychopathologist should be aware that the “missing data” problem has been given extensive thought by informed statisticians and that rigorous methods exist for dealing with missing data.

When You Cannot Do a Real Experiment, Use Time as a Lever There are many interesting questions in psychopathology research concerned with etiology and pathogenesis. For example, we might believe that a particular genetic polymorphism is related to risk for schizophrenia in certain environments. We might hypothesize that the nature of one’s relationships with one’s peer group influences subsequent psychosocial development that predisposes to drug abuse. Many of the most interesting hypotheses and models involve the activity of variables that we simply cannot manipulate in the service of research. This is so largely due to ethical concerns (e.g., one cannot purposefully place a child without a genetic vulnerability for schizophrenia with two schizophrenia-­affected parents for child rearing); however, sometimes technical (e.g., we cannot replace genes in human beings to test the effect of such a manipulation) and other feasibility issues



Practical Tools and Pragmatic Issues

77

preclude such experimentation as well. Nonetheless, we can maintain an interest in the models and hypotheses we hold. Sometimes nature provides us with a natural experiment, as in the case of cross-­fostered children in schizophrenia (i.e., normal adoptees raised by a parent who subsequently developed schizophrenia after the adoption took place; Wender, Rosenthal, Kety, Schulsinger, & Welner, 1974), or consider monozygotic (MZ) twins who share an identical genetic makeup but who were reared in different environments due to being separated immediately after birth (i.e., the MZ– reared-apart strategy). Perhaps the most important tool students should understand is the use of time as a lever in the study of psychopathological development. Although for many good reasons (ethical and otherwise) important variables cannot be manipulated in the service of studying psychopathological outcomes, time is always marching on. We can rely on time to continue to change consistently from day to day, month to month, year to year. With the passage of time, the organism develops, changes, unfolds. Some of the most important questions of central interest to psychopathologists necessarily yield to powerful input of time passing. The Cornell developmental psychologist Urie Bronfenbrenner once said to me “when you cannot do the experiment, time may be your most important lever”—an axiom worth committing to memory (and West, 2009, describes other alternatives to randomized experiments). For example, consider personality disorders. For nearly 100 years it was believed that personality disorders—­typically described as trait-like, stable, and enduring personality deviations—were so consistent over the life span that it was as if a personality disorder were carved in granite. Indeed, even the American Psychiatric Association in its well-known diagnostic manuals has asserted (and continues to do so) that personality disorders are enduring entities (see all versions of the DSM since 1980). The only way to address this interesting hypothesis is to study it over time. If an entity or personality configuration is truly consistent over time—­varying little in the nature and level of disturbance—then personality disorder symptoms should remain essentially constant over time. Interestingly, the thrust of the findings across all of the major longitudinal studies of personality disorders is that they are quite malleable and show considerable variation both across and within individuals over time (e.g., Lenzenweger, Johnson, & Willett, 2004). Time may obviously be used in other ways as well, even over the relatively short duration spans that might occur in a laboratory experiment that is conducted over a series of minutes or hours. In short, although it is obvious to some, one must remember that time is an important tool in the study of psychopathology.

78

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

The Blind: Could I Really Affect the Experiment by Doing That? Can You Afford Not to Use a Blind? Using the Blind and “Experimenter Expectancy Effects” In much of our work in experimental psychopathology, a blind is necessary to avoid the untoward impact of experimenter expectancies. The experimenter expectancy is the documented reality that one (the experimenter) can impact the results of one’s study in very subtle ways that are not immediately obvious to the experimenter or subject (Rosenthal, 2003). Consider these examples regarding the necessity of a blind in psychopathology research: (1) in the administration of a thought disorder measure, one needs to be blind to group membership of the subjects under study; (2) when assessing degree of memory functioning in borderline personality disorder, one needs to be blind to group membership; (3) when assessing working memory in the biological relatives of individuals with certain forms of psychopathology (e.g., schizophrenia) and normal controls one needs to be blind to the presence or absence of psychopathology in the relatives; and (4) the need to be blind to the genetic background of the subjects in studies linking genomic factors with laboratory-­measured phenomena. Even with computerized tasks, there is a human being in the room, and that human being could influence the experimental situation. Moreover, expectancy effects exist not only in highly subjective rating tasks but also in protocols in which the dependent variables are collected with psychophysiological recording or other instrument-based assessments (e.g., pupillometry; see Rosenthal, 1994, 2003, for extensive reviews and summaries of this important area of research methodology).

Anecdote I once heard a competent scientist, when discussing the need for a blind in an experimental protocol in which information about the subjects could certainly impact the experimenter, state, “I don’t know why we need to bother with blinds, what’s the big deal? I work at an institution where we see people with autism, we know everything about these patients, and we test them, too. I don’t think a blind is important.” In this situation I asked, “Imagine that you are to decide if the cells you are about to examine under your microscope come from a person with a particular form of cancer or not. Your assistant hands you the slide containing the cells in question and notes that these cells come from subject #111, who has pancreatic cancer.” Now, is there not something wrong with this picture? This may be one



Practical Tools and Pragmatic Issues

79

instance in which drug researchers are far ahead of some psychological and psychiatric scientists. Can you imagine a drug study with no blind (i.e., in which the experimenter knew which subject got which drugs)? A blind requires planning a priori, staffing resources, and research funds, but it is well worth it.

Prediction Efforts: Behold the Beauty of Improper Linear Models (or, Simply Linear May Be Simply Better) Many psychology students are taught either explicitly or implicitly to view the world in terms of linear relationships between variables. Linearity permeates the methodological training of the beginning psychologist. Many statistical procedures assume linear relations among the variables under study (correlation coefficient, standard regression analysis, discriminant function analysis). Substantive models (theoretical models) are often conceived of as consisting of processes (or variables tapping such processes) that are in linear relationships with one another. Thus one expects X to have a linear relationship with Y. For example, as IQ increases, it is expected that processing speed on a cognitive task also increases. A proper linear model (Dawes, 1979) is one in which the predictor variables are “given weights in such a way that the resulting linear composite optimally predicts some criterion of interest” (p. 571). There are ample data to show that proper linear models do a pretty good job at predicting some criteria of interest (e.g., Meehl, 1954; Wiggins, 1973); however, one should be open to the possibility in our predictive work that an improper linear model, or even a nonlinear model, can do a pretty fine job at prediction as well.14 By improper linear 14 For

many years (and, for some, even to this day) it was thought that clinicians would obviously be the best people to consult when trying to predict some meaningful behavior. P.E. Meehl (1954/1996) argued that this was not the case in his formulation of the clinical versus statistical prediction problem. I do not rehash the issue of clinical versus statistical prediction, as the issue has been resolved for most enlightened psychological scientists. The masterwork done by Meehl (1954, see also Meehl, 1986a) was updated by Grove and Meehl (1996; see also Grove, Zald, Lebow, Snitz, & Nelson, 2000) nearly 50 years later, and the conclusions have remained the same. To make a long story short, however, combining data using some form of algorithm or mechanical means typically outperforms “clinical–­ subjective–­impressionistic” combinations of the same data in the prediction of some meaningful criterion (e.g., treatment relapse, recidivism/reincarceration). It is important to realize, however, that the keen eye of the clinical observer is not at issue here; rather, it is the manner in which data are combined in order to make a prediction that matters. Some participants in the “clinical vs. statistical” debate have never appreciated this distinction. We, as human beings, can be quite expert at detecting interesting relationships, patterns, or configurations among variables of interest (and that is why we need our brains in the enterprise), but we are not particularly good at combining observations in an

80

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

model (see Dawes, 1979), we mean one in “which the weights [in the prediction equation] are chosen by some nonoptimal method” (p. 572). Dawes (1979) states, “They [the weights] may be chosen to be equal, they may be chosen on the basis of the intuition of the person making the prediction, or they may be chosen at random” (p. 572). We are often called on to make some sort of prediction regarding an outcome, behavior, or other criterion of interest in research. To do so, it is quite logical to think that perhaps one should round up reasonable variables (perhaps informed by theory), measure them, and evaluate them in relation to the criterion of interest via regression. Then, to make the prediction of interest in some other sample or setting that is different from the initial sample that gave rise to the regression, one might apply the regression weights derived from the initial sample to the variables assessed in the new sample in order to make a prediction. It seems quite reasonable. Clearly, there will be some shrinkage in what is termed the multiple correlation that relates the predictors to the predicted criterion in the new sample. Does it not make sense to proceed in this manner? Not according to the psychologist and decision theorist Robyn Dawes at Carnegie Mellon University. Dawes, who wrote of the beauty of improper linear models (Dawes, 1979), has long suggested that the use of regression weights may not be the best way to apply what has been learned through regression analysis to prediction problems in new samples. In short, rather than going through all the trouble of making predictions based on computing regression weighted combinations of scores on variables of interest, Dawes (2000; Dana & Dawes, 2004) recommends simply unit-­weighting the variables of interest. For example, rather than applying, say, weights carried to the third decimal place to all variables involved in the prediction to make a prediction, one might only apply coefficients of +1 or –1 to the predictors.15 Dana and Dawes (2004) demonstrate the superiority of the unit-­weighting approach in most instances in efficient and consistent (reliable) manner in the service of predictions. Thus we should distinguish between the type of data and the means by which we gather them and the manner in which we combine them for decision and prediction purposes (Grove & Lloyd, 2006). Finally, it is noted that data can be combined either in a clinical (subjective/impressionistic) manner or in a statistical (mechanical/algorithmic) manner; there are no hybrid methods of data combination. 15 Thus

imagine 10 predictors relating to a criterion. In a regression coefficients approach, the prediction would be based on the equation that links the predictors with their regression coefficients. For the sake of illustration, .687*X1 + .613*X2 + –.542*X3 . . . = regression score, where the weights have been derived from prior research and the X variables represent a person’s observed values on the variables of interest. A unit-­weighting approach would be 1*X1 + 1*X2 + (–1*X3) = predicted score. Clearly, the second approach is simpler and improper, but it also happens to result in predictions that are more efficient (Dana & Dawes, 2004).



Practical Tools and Pragmatic Issues

81

which prediction is needed. The unit weights can be based on information from regression analyses in other samples (i.e., post hoc selection) or based on one’s theory or model (i.e., a priori selection). Sticking with both unit weights and a simple additive linear model, one can make the most efficient predictions, on average, relative to using regression coefficients, correlation weights, or even a “best weights” approach. The mantra here is “for prediction, simpler may be better.”16

Throwing Curve Balls to Our Friend r In psychological research, the correlation coefficient is truly a workhorse. Our friend r is used in so many applications to compute associations between variables of interest by taking individual differences into account. As long as one does the math correctly (and it is not terribly complex math), then r does reveal the degree of association (based on a linear relationship) that exists between any x and y of interest.17 How can one throw our buddy r a real curve ball? By that I mean, what features, characteristics, or artifacts in data can truly impact the magnitude and direction of a correlation coefficient. These are things that are always good to keep in mind (holding aside, of course, distributional issues such as normality, skewness, and kurtosis that are also known to affect r). There are four well-known factors that can affect the magnitude and direction of r: restriction of range, truncation, extreme groups, and extreme data points.18 As far as the direction of a correlation coefficient is concerned, one must always be sure to inspect 16 Consistent with the idea of “simpler is better,” it is worth noting that research on forecasting suggests that complex (nonlinear) models do not improve on simple additive linear models for prediction (Armstrong, 1985). 17 Meehl

(1956) recounted: “Back in the days when we were teaching assistants, my colleague MacCorquodale was grading a young lady’s elementary laboratory report on an experiment which involved a correlation problem. At the end of an otherwise flawless report, this particular bobbysoxer had written, ‘The correlation was seventy-five, with a standard error of ten, which is significant. However, I do not think these variables are related.’ MacCorquodale wrote a large red “FAIL” and added a note: ‘Dear Miss Fisbee: The correlation coefficient was devised expressly to relieve you of all responsibility for deciding whether these two variables are related’ ” (p. 263).

18 An

important rule that always should be followed is to examine one’s data carefully to be certain no highly deviant or implausible values have crept into the data. This kind of thing can happen easily, even in the highly automated age, and one wants to be sure one’s data do not harbor a highly deviant (and possibly implausible) value, such as, say, a 900, when the highest score possible on the scale in question is a 9. To see the impact of such a deviant value, assemble a set of data (x,y data) and calculate the correlation. Then simply change one value by adding 100 or so points to the observed value, recompute the r; and watch what happens. Try it.

82

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX 10.00 8.00

y

6.00 4.00 2.00 0.00 0.00

2.00

4.00

x

6.00

8.00

10.00

FIGURE 3.1.  The correlation between x and y for the full range of the scores is .51 (positive), whereas the correlation for those scores falling between the values of 2 and 6 on the variable x is –.31. Thus the overall pattern is a positive and substantial linear relationship; within a particular range of the scatterplot of x and y, their correlation actually reverses itself and is substantial in magnitude. The fit line indexes the .51 correlation for the entire sample, with y as a linear function of x.

the actual data underlying the correlation and how they are arrayed. The best way to do this to examine a scatterplot of the x and y data involved in the calculation. Figure 3.1 reveals a situation in which the x–y scatterplot underlying r is critical.

The Suppressor Relationship: Not Just an Arcane Theoretical Possibility A statistical effect that should be kept in mind, particularly in psychopathology research, is the “suppressor” variable. The suppressor variable concept has been known for many years, and Jerry Wiggins’s (1973) discussion of this important concept in his monograph Personality and Prediction remains the classic treatment. In many psychopathology studies, the investigator ends up being focused on bivariate relationships, typically some predictor (x) in relation to a criterion of interest (y). Following Wiggins (1973), in cases of multiple prediction, we think of the basic model as being one in which predictors (x1, x2, x3) are related to a criterion (y) yet are typically minimally



Practical Tools and Pragmatic Issues

83

correlated or (better yet) uncorrelated with one another. The fundamental assumption here is that each of the x variables will make relatively unique contributions to the prediction of variation in y. In an informal sense, each of the x variables predicts a slightly different chunk of the variation in y, and there is minimal redundancy or overlap in the prediction. However, the notion of the predictor variables (the x’s) being uncorrelated with one another, especially in the area of psychopathology, represents something of a theoretical ideal that is seldom realized. For example, measures of negative affect (depression, anxiety, anger) tend to be intercorrelated, or consider measures of schizotypy (e.g., perceptual aberration, magical ideation, and referential thinking; see Lenzenweger, Bennett, & Lilenfeld, 1997) that are frequently intercorrelated. What is more, the predictors in the prediction equation need not necessarily behave in the manner described here, yet they could still make substantial contributions to the prediction of the criterion in a multiple regression equation. For example, there can be variables within a set of predictor variables that do not behave anything like what is expected in the typical prediction setup, yet such predictors may make very substantial (and as Wiggins, 1973, described, “surprising”) increments in multiple prediction. In this situation a predictor may even show minimal association with the criterion of interest (y) and be substantially correlated with other predictors (other x’s) at the zero-order level. However, when such a predictor—with these unorthodox characteristics—is entered into a multiple regression along with the other predictors, it emerges as a powerful predictor. Such an unorthodox variable is known as a “suppressor variable.” Perhaps the best way to understand a suppressor variable is through consideration of an actual example. In the laboratory we studied the relationship between three broad domains of schizotypal personality disorder features—­reality distortion, disorganization, and negative features—in relation to associative frequencies in verbal utterances (Lenzenweger, Miller, Maher, & Manschreck, 2007). In this case, the schizotypal features were predictors (x’s) of our measure of the criterion, verbal utterances (y). Taking a focus specifically on disorganization and negative features, it was fascinating to observe that disorganization was correlated with associative frequencies (r = .30), negative features were uncorrelated with associative frequencies (r = .01), and disorganization and negative features were correlated highly (r = .72). These two predictors are clearly poorly behaved! When entered into a multiple regression, the suppressor role of negative features becomes clear (see Table 3.2).

84

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

TABLE 3.2. Regression of Associative Features on Schizotypic Features Unstandardized coefficients (Constant) SPQdisor SPQNEG

Standardized coefficients

B

Std. Error

Beta

6.476 .655 –.406

1.004 .194 .171

.618 –.435

Correlations t

Sig.

6.450 .000 3.366 .001 –2.370 .022

Zero-order Partial .303 .012

.426 –.315

Part –.426 –.300

Note. Summary of regression of associative features on disorganized schizotypic and negative schizotypic features. Data from Lenzenweger, Miller, et al. (2007).

The regression coefficients for disorganization and negative features in relation to associative frequency are .655 and –.406, respectively. The part correlations for disorganization and negative features in relation to associative frequency are .43 and –.30, respectively. What is going on here? Was it not the case that negative features were uncorrelated with associative frequencies? To gain a better sense of the situation, it is useful to ponder the relationships among these three variables in the form of a Venn diagram that depicts the components of variance. In Figure 3.2, we see the three constructs of interest: associative frequency, disorganization, and negative

Disorganized schizotypic features

x1 a Associative Frequency y

b

Negative schizotypic features x2

FIGURE 3.2.  Components of variance involved with suppressor effects (following Wiggins, 1973). Associative frequency (y) represents the criterion; disorganized schizotypic features represents (x1), the predictor; and negative schizotypic features (x2) represents the suppressor variable. Variables in study by Lenzenweger, Miller, et al. (2007).



Practical Tools and Pragmatic Issues

85

features. We see that disorganization predicts a portion of associative frequency (overlapping portions of the diagram for these two variables, area a). Clearly, as is evident from the diagram, disorganization does not explain all of associative frequency (in a sense, a goodly portion of disorganization is irrelevant to the prediction of associative frequency). Wiggins (1973) referred to this portion of a predictor that is irrelevant to the prediction of the criterion as “baggage,” or variation in the predictor that served no real purpose in the prediction of the criterion. We also see in Figure 3.2 that there is a portion of negative schizotypic features that overlaps with disorganized schizotypic features (area b); however, it is very important to note that this area of overlap (i.e., portion of variance) does not overlap with the portion of disorganized schizotypic features that is predictive of increased associative frequency. Thus we have a situation in which the suppressor variable (negative schizotypic features) is uncorrelated with the criterion (associative frequency) but is correlated with the predictor (disorganized schizotypic features). The critical feature of this three-way relationship is that the suppressor overlaps with that aspect of the predictor that is the unnecessary “baggage”—that portion of the predictor that gives us no help in predicting the criterion (in this case, associative frequency). This unnecessary baggage in the predictor can be removed via the suppressor variable in a multiple regression (or partial correlation) setup. One might think, “This is all well and good, but why is this interesting? How can suppressor variables be helpful in understanding experimental psychopathology results?” These are reasonable questions. Identifying suppressor variables can obviously be an aid in improving prediction, a practical benefit. Their presence can also be of theoretical interest. For example, in the Lenzenweger, Miller, et al. (2007) study just described, this suppressor relationship was helpful in understanding that an increased level of negative schizotypic features present for a given individual appeared to work to suppress or constrain the relationship between disorganization and associative frequency. This suppressor relationship was also consistent with other data that found increased negative schizotypic features to be associated with decreased verbal fluency (a rough proxy for associative frequency; Tsakanikos & Claridge, 2005). Thus the suppressor relationship revealed suggests the substantive possibility of an interaction between two symptom dimensions in schizotypic psychopathology in relation to a neurocognitive process. Knowledge of such an interaction can, as a result, aid in the development of models for understanding the associative process. Why is it that the suppressor variable is often not discussed in psychopathology research?

86

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

The answer is simple—­typically, any variable that is not correlated with a criterion is thrown away or removed from consideration in further analysis. This can be a costly mistake. The moral here is “stay alert” for interesting relationships in one’s data and do not discard a variable simply because it does not correlate with a criterion.

Lions, Tigers, and Collinearity, Oh My! Psychopathology research is frequently multivariate in nature, which means we are dealing with three or more variables (sometimes many more) at a time. Typically in a multivariate regression setup we are regressing a criterion variable onto a group or set of predictors or regressors (Darlington, 1990), and there is often considerable intercorrelation among the regressors. This intercorrelation is to be expected, partly due to genuine overlap and partly due to “crud” in the measurements. What is crud? Given that nearly everything is correlated with everything else, a feature of psychological data that has been termed the “crud factor,”19 it is not surprising, especially in psychopathology research, to find appreciable collinearity among predictor variables in a regression setup. Of course, there can also be collinearity driven by substantively meaningful overlap of construct indicators (e.g., depression and anxiety measures often correlate well above .50). This situation strikes fear into the heart of many beginning graduate students. This fear is not unique to students, however, as many manuscript reviewers feel compelled to note (assume ominous vocal tone) that “there is also considerable collinearity among the variables in the regression.” Should excessive fear be engendered by collinearity? No. Collinearity was taken on directly by Darlington (1990), and his views on it are well worth reviewing: Collinearity is often a far less serious problem than researchers fear. There are four reasons for this. First, collinearity affects only the power of tests on regression slopes—not their validity. Second, collinearity often affects only a few of the regressors. Third, although you cannot perform powerful tests on the individual effects of collinear variables, collinearity does not reduce the 19 From

A Paul Meehl Reader (Waller, Yonce, Grove, Faust, & Lenzenweger, 2006), “Crud factor— Term coined by Minnesota psychologist David Lykken to capture the empirical reality that many variables are intercorrelated for complex and substantively uninteresting reasons. . . . These variables are often numerous, unknown, uncontrolled, and not of experimental interest to the researcher. They nevertheless collectively act so as to ‘dirty up’ one’s results. . . . ” (pp. 488–489).



Practical Tools and Pragmatic Issues

87

power of a test on the effect of the set as a whole. Fourth, . . . [the] estimate of [shrunken R]20 is unaffected by collinearity. (pp. 130–131)

Although this volume is not intended as a statistical volume (and therefore extensive statistical notation and derivations are eschewed), the importance of this set of realizations regarding collinearity cannot be overstated. Plainly, in psychopathology research, when one is studying multiple variables (regressors) in relation to some criterion of interest, one should not be surprised by collinearity among the regressors and should forge onward in the analysis.

20 The

shrunken R can be thought of as the true predictive power of the regression weights bj in a multiple regression analysis, as per Darlington (1990, p. 159). The shrunken R concerns validity of the prediction in question.

Chapter 4

Analytic Heuristics, Caveats, and Soapbox Moments There are many clinicians who know nothing about research and have heart palpitations at the mention of the expression “correlation coefficient,” and there are many researchers that would not know a patient if they fell over one. —A nonymous—but well-known—psychopathologist

The Power of Quantitative Thinking and the Value of Quantification Many undergraduate and even some graduate students bridle at the requirement to take a course in measurement or a course in statistics as part of their training in psychological science. The typical basis for this objection (holding aside aversion to mathematics) is reflected in a comment such as, “I am interested in the life of the mind, what makes people tick, how personality is formed. I don’t know what statistics (or measurement) has to do with this interest or my interest in helping people.” In psychology, particularly clinical science, we are faced with some thorny questions about “how the mind works” and “what causes psychopathology”; however, I am inclined to think that the days of solving these problems from the “overstuffed-­leatherchair-as-­laboratory-don’t-­bother-me-with-­research” approach are long gone. A theme running through this book is “don’t rate something, count it,” and this mantra implies the value of quantification as a tool in approaching psychology generally and experimental psychopathology in particular. Meehl (1998/2006; see also Waller et al., 2006) argues that

88

Analytic Heuristics, Caveats, and Soapbox Moments

89

there are three kinds of quantification in science. The first is at the level of measurement, the numerification of observations. The second is summary statistics of the numerified observations, such as means, variances, correlations, and curve fitting. The third is mathematicization of the theoretical entities. A good science has all three, connected in nonarbitrary ways. (p. 434)

It is important to note that the degree to which quantification, although not the same as mathematical knowledge, plays a role in one’s view of psychological inquiry is somewhat reflective of the exposure one has to training in this mode of thinking. Being able to think in probabilistic terms and to conceive of variation in quantitative terms strike me as research essentials for psychological science. Although probably preaching to the choir for many, I note this because for some (including some faculty) any training beyond the minimum in quantitative thinking is unthinkable. From where I stand, the more training in this mode, the merrier.

Heterogeneity Can Be Your Friend: Embrace It, Don’t Avoid It! Symptomatic variability within diagnostic classes is the norm in psychopathology. Moreover, given the extensive reliance on subjectively rated phenomenology in the diagnosis of psychopathology, it is likely that even greater heterogeneity will characterize any group of patients despite their carrying a common diagnosis. For example, one patient with schizophrenia may have prominent persecutory delusions (e.g., the CIA has placed a small Martian in his brain to spy on the British Intelligence group MI-6), bizarre behavior (e.g., carrying a dead chicken around in a lunch bag), and diminished volition (e.g., no desire to get out of bed or bathe or go to a rehabilitation training program), whereas another patient with schizophrenia will display marked auditory hallucinations (e.g., she hears voices outside her head—when alone—­commenting on her behavior), severe thought disorder (e.g., incoherent speech), and flattened affect (i.e., she shows no emotion on her face). Both of these people suffer from schizophrenia, yet they seem so different with respect to phenomenology. This is so for several reasons. First, the current diagnostic systems define disorders using a polythetic criteria set, and diagnostic thresholds are set in terms of the number of criteria met (i.e., not which specific criteria are met). Thus there are any number of ways in which a patient can meet the diagnostic criteria for a disorder, and, therefore, two patients that have been diagnosed with the same

90

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

illness can display remarkable variation in their clinical phenomenology. Second, it is well known, particularly with respect to schizophrenia, that the illness itself displays considerable variation within its clinical presentation (an attempt to capture this reality of the illness is reflected, in part, in the polythetic approach to definition noted already). Thus one is bound to see a high degree of heterogeneity at the clinical or phenotypic level within well-­described categories of psychopathology. Third, diagnostic practice and diagnostic standards vary across diagnosticians and clinical sites, which combine to give rise to heterogeneity in patient samples, even though all patients carry the same diagnosis. This, however, is less a problem than it was 40 or 50 years ago. All three of these factors conspire to create what could be taken as evidence of phenomenological heterogeneity. Another reason, perhaps more interesting from the standpoint of theory and model building, that heterogeneity might appear in a clinical sample of similarly diagnosed patients is that the diagnostic rubric—say, schizophrenia—is really just an umbrella term to cover similar-­appearing clinical manifestations of multiple forms of psychopathology or multiple pathological processes. In other words, perhaps there are multiple types or forms of schizophrenia; this probably implies multiple etiological pathways to a similar-­appearing class of phenomenology. We would refer to the source of such variation as etiological heterogeneity. Finally, in experimental psychopathology, in which laboratory measures of processes such as sustained attention, working memory, context processing, executive functioning, and smooth pursuit eye movements are a study focus, one must also confront the issue of heterogeneity in performance on such measures in the same subjects. It is rarely the case (if at all) that all patients with schizophrenia (or schizotypes) in a given study sample will display deficits on any given measure. It is much more likely the case that, for the sake of illustration, 40% of an adult sample of patients with schizophrenia tested for sustained attention will actually display deficits in attention in their performance or that 60% of an adult sample will display evidence of eye-­tracking dysfunction. We speak of this type of variation as laboratory task performance heterogeneity. Heterogeneity in performance on laboratory tasks is a central problem in experimental psychopathology research (Lenzenweger, Jensen, & Rubin, 2003; Maher, 2003; see also Silverstein, 2008). Unfortunately, although many researchers are aware of the issue, they proceed as if it were merely a nuisance. One reason it is often ignored is that statistical procedures for dealing with the thorny problem posed by heterogeneity have only just begun to gain traction in psychological science. The reality of heterogeneity

Analytic Heuristics, Caveats, and Soapbox Moments

91

in laboratory task performance measures was made clear to me when we had the opportunity to examine the issue empirically. Some years ago (see Lenzenweger, 1998) we studied a normal subjects and schizotypes who had all completed the same large battery of laboratory tasks (e.g., sustained attention, working memory, negative priming, antisaccade, smooth pursuit eye movement, and several others). Deviance on any laboratory performance index was defined by scores that fell into the lowest 10% of performance found among the normal subjects. Thus we had separate cut scores for each task that identified deviant performance on that specific task. These cut scores were then applied on a case-by-case basis to the schizotypic subjects, which allowed us to classify a schizotype as showing deviant or nondeviant performance on a given measure. To our great surprise, we did not find even one schizotype that was deviant on all measures. In fact, it was unusual to find a schizotype who was classified as showing deviant performance on three or more measures. Rather, most schizotypes showed deviance on but one or two lab measures. As these subjects had been selected in a highly controlled manner, we did not see much in the way of phenomenologic heterogeneity in the sample. Thus we were left with a puzzle. How could it be that heterogeneity in the laboratory task measures could be so clearly the norm in this sample? Did it represent the imperfect nature of selection (was our selection index prone to falsely identifying some people as schizotypes, despite their similar scores on the measure)? Was there a core schizotype, even while different schizotypes displayed different performance profiles? Could it be that, even in a carefully selected sample such as we had, there was etiologic heterogeneity, and was this reflected in different patterns of laboratory task performance across the sample of schizotypes? The important methodological point here is that we sought out the heterogeneity in the sample; we did not choose to assume it did not exist or assume, if it did exist, that it was not a big deal. One of the most important things one must consider about heterogeneity in psychopathology is simply to expect it. Heterogeneity in phenomenology and laboratory task performance will always be a given in any study of schizotypy or schizophrenia. If you need to be further persuaded of this, simply examine a data set gathered from a group of patients. Look at the range of performance, the dispersion, the number of outliers (that are not artifacts), the standard deviation (especially vis-à-vis a normative group), and the degree of heterogeneity will become apparent. An illustration of this approach to heterogeneity in performance, especially as it serves to aid in the detection of a deviant subgroup of subject, can be found in Lenzenweger and Korfine (1994). In that study we examined the

92

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

FIGURE 4.1.  Distribution of schizotype and control cases as a function of their level of deviance as determined by a composite deviance index calculated across five Wisconsin Card Sorting Test performance indexes. Higher scores in the deviance index indicate worse performance. With a conservative cutoff score, 26.1% of the schizotypes versus only 3.6% of the controls would be considered deviant performers, a highly significant difference (Z = 2.33, p < .01). From Lenzenweger and Korfine (1994).

Wisconsin Card Sorting Test (WCST) performance in a sample of schizotypes and nonschizotypes. The subjects in this study were all relatively high­functioning and intellectually capable young adults, features that should have tended to compress potential differences both within and across subject groups. By defining deviance as a function of the dispersion of scores seen in the normal group on each of several WCST performance indexes, we calculated a “composite deviance index.”1 The distribution of scores on this deviance index for the two subject groups can be seen in Figure 4.1. Inspection of the figure, which simultaneously plots two histograms (one of each subject group), reveals that although most schizotypes scored comparably to the normals on the deviance index, there was clearly a group of schizotypes out in the right tail of the distribution. These right-tail-­dwelling schizotypes were particularly interesting as (1) they were largely the source of the heterogeneity observed in the two groups and (2) there was an identifiable group of subjects that could be studied in greater depth. 1 A

deviant subgroup of poorly performing subjects can be discerned through the use of multiple indexes, even in instances in which group mean differences do not exist on those indexes. A deviance index may capture the configuration or profile of deviant performance across multiple indexes that can elude univariate comparisons of subject groups.

Analytic Heuristics, Caveats, and Soapbox Moments

93

The exploration of heterogeneity is often a stimulus for further research. Although heterogeneity is viewed by many as a nuisance or annoyance, I see potential value lying within the heterogeneity observed in our samples. Consider that Meehl (1990) noted, “the qualitative heterogeneity of the syndrome [was] the jumping off point for my theory of schizotaxia” (p. 5). Heterogeneity represents at once perhaps the biggest stumbling block in all of schizophrenia and schizotypy research (at all levels of analysis, including the genomic), as well as one of the biggest potential sources of real gold in the entire schizophrenia research endeavor, perhaps holding the key to some of our most basic questions regarding etiology. Don’t run from heterogeneity, embrace it—you might find you like it.2

Most Interesting Findings in Psychopathology Will Cross Different Levels of Analysis As argued by Kosslyn and Rosenberg (2005), any single psychological phenomenon can be studied from multiple levels of analysis. This is an important concept to commit to memory. Particularly in the age of neuroscience and neuroimaging, it is relatively easy for students to err in their thinking and come to believe that only neuroscience investigations of psychological phenomena are worthy of attention. Or, worse yet, students might come to (wrongly) believe that only evidence directly related to brain functioning is worth studying. The “levels of analysis” approach advocated by Kosslyn and Rosenberg (2005) represents a way of thinking that places the brain in a broader context that allows “facts about the brain to illuminate facets of phenomena at other levels of analysis.” Just what is this levels-of-­analysis approach that Kosslyn and Rosenberg (2005) are advocating? What the approach entails is making distinctions among three levels of analysis: (1) level of the brain, (2) level of the person, and (3) level of the group. One can readily see how this dissection allows one to place the brain within the person and the person within the group, thereby capturing the essence of modern psychological science investigations and theory. The level of the brain really refers to biological mechanisms—think wet. Here it means neural circuits, functions of brain regions and lobes, neurobiological processes and neurotransmitters, and the effects of hormones. The level of the brain is 2 An

example of another potential statistical/analytic approach to heterogeneity in laboratory data is discussed in Lenzenweger, Jensen, and Rubin (2003).

94

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

also concerned with the effects of genes on the brain, neural development, neurobiology, and so on. The level of the person, which is not the same as the “whole person,” refers to the content of mental processes (such as beliefs and feelings). The level of the group refers to the physical (including natural and human-made) and social worlds. A key idea in the Kosslyn–­Rosenberg proposal is that “events at each of the levels affect events at the other levels” (2005, p.  78). All psychological phenomena emerge from interactions occurring between events at the three different levels proposed by Kosslyn and Rosenberg (2005). The “whole person,” so to speak, is the consequence of all such interactions. One might wonder about individual differences in personality, temperament, or even psychopathology in this context; how do these things come about within this framework? These variations, simply, arise from interactions between events in the brain, content (the results of experience/learning), and social context. Consider Box 4.1, for a description of how this organizing scheme works. I have found the Kosslyn–­Rosenberg levels-of-­analysis approach to be very helpful in encouraging students to understand the emergent nature of most psychological phenomena. By this I mean the fact that most psychological phenomena represent the final interactive product of multiple systems and that they cannot be reduced to a mere collection of constituent parts.3 For example, consider the topic of personality disorders. We (see Depue &

BOX 4.1. A Thought Experiment: Take a Moment and Think of What You Are Doing Right Now For example, right this minute your brain is processing these squiggly black lines in front of you, interpreting them as conveying meaning (level of the brain). These lines were created by others (specifically, we authors—level of the group) in order to convey specific ideas (level of the person). If we have successfully conveyed that information, your beliefs will change (level of the person), which in turn will affect not only how your brain organizes and stores information in the future, but possibly even how you interact with other people. From Kosslyn and Rosenberg (2005, p. 78).

3 The

concept of emergence is relevant to psychopathology, as most disorders represent complex configural outcomes of multiple interacting systems. Emergence, as a concept, plays a critical role in contemporary cognitive neuroscience, which views most psychological phenomena as having emergent properties, that is, the phenomena cannot be reduced to its constituent parts (Meehl & Sellars, 1956; Bickhard & Campbell, 2000; Rumelhart, 1984).

Analytic Heuristics, Caveats, and Soapbox Moments

95

Lenzenweger, 2001, 2005, for detail) have argued that these disorders are best understood within a framework of multiple interacting neurobehavioral systems, which are themselves influenced by genetic factors and are acted on by social and physical environmental inputs. From the standpoint of emergence, one cannot simply parse a personality disorder into its component parts; rather, the underlying component parts have come together interactively to form a distinctly rich phenotype. Interactions across levels facilitate emergent processes.

Caveat Emptor: Neuroimaging In seminars, it has sometimes seemed that every other comment or question that arose from the students during the discussion had to do with neuroimaging. Most of these questions were rarely guided by a specific question or testable idea; rather, they more often had the quality of “we have this cool technology, let’s use it” or the (mis)impression that “neuroimaging will solve psychological mysteries for us.” This view was not limited to undergraduate and beginning graduate students, either. At a recent international meeting that focused on genomics and psychopathology, a world-class geneticist ended a talk by saying to the assembled group of psychopathologists, “I think that your challenges and interests will be better addressed by neuroimaging than by genetics; it will give you the answers.” The speaker provided no rationale as to why neuroimaging technology would solve the major problems in understanding psychopathology. Clearly, the available neuroimaging technology is indeed powerful, if appropriately applied by informed parties. However, one must be careful to be aware of the seductive power of complex machines, the depiction of statistical comparisons in vivid (but largely arbitrary) color, and know that at its core neuroimaging data involves a level of inference regarding neural activation that is largely unappreciated by many, including some users of the technology. We revisit this theme in Chapter 12.

Specific Etiology In psychopathology research, our goal is to illuminate etiological factors that are uniquely or most powerfully responsible for pathological development for particular forms of psychopathology. We want to understand pathogenesis from beginning to end. Of critical importance in this quest is the identification of those etiological factors that have a high degree of specificity for the type of psychopathology under investigation. In general,

96

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

the more specific a causal or etiological input is to the determination of psychopathology, the better. Although a relatively straightforward idea, the definition of specific etiology requires clear conceptual thinking, as well as innovative research strategies. Some of the most careful thinking on this topic has been done by Meehl. In fact, necessary reading on this issue can be found in Part II: Specific Etiology in A Paul Meehl Reader (Waller et al., 2006). As an overview of the level and nature of Meehl’s discourse on this topic, consider the following from the introduction to Section II of the volume: Meehl articulated several “distinguishable and equally defensible meanings” (Meehl, 1972, p. 22) of specific etiology ranging from a qualitative (i.e., present vs. absent) factor that is both necessary and sufficient for the illness to occur, through progressively weaker meanings of the term. For example, one could have a necessary qualitative causal factor that is not sufficient to cause an illness on its own unless it interacts with a variety of nonspecific contributory factors. Moving away from a purely qualitatively structured causal factor, a dimensionally (or quantitatively) structured underlying specific liability could exert its influence with a threshold effect. In such a circumstance an illness would be likely to develop only when values above a certain threshold on the liability dimension were present, and only then would contributory factors play a role in the emergence of the illness. A fourth meaning of specific etiology, albeit weaker form of specificity, is what Meehl termed a uniformly most potent factor. There might be a given variable or factor that has the greatest impact everywhere in the multivariate array or space of variables known to influence the development of an illness—in this conceptualization, small differences in this causal factor are more potent than differences in other factors in the array. Meehl lists several other forms of specific etiology including “specific step function” etiology and “uniquely nonfungible factor” etiology. In each instance, Meehl develops the concept he has in mind, anchors it in a quantitative definition, and then relates it to a plausible example from medicine or behavioral genetics. (Waller et al., 2006, p. 173)

Bringing this down to earth, what should the practical, methodological implications be for our studies given our interest in specific etiology? Take the following example. At a grant proposal review panel—where applications for grant funding are reviewed for creativity, as well as scientific and methodological rigor—I was discussing one particular application, and in my evaluation I pointed out the absence of a psychiatric control group. I argued that this methodological shortcoming would in all certainty diminish the ultimate specific information value of the study. Another member of the panel thought the inclusion of a psychiatric control was unnecessary—

Analytic Heuristics, Caveats, and Soapbox Moments

97

a bother, a waste of money. Why should I argue for a psychiatric control group? Because absent a psychiatric control group, we would learn information only about what distinguished a pathological group from a normal control group. We would learn essentially nothing as regards specific etiology for the form of psychopathology in which the investigators were interested. Inclusion of a psychiatric control group is but one small (but important) methodological step in the direction of learning something specific about a disorder. By this I mean learning something that is not just about psychopathology in general, but about the disorder that one is specifically interested in studying and learning about. Specificity is the concept; the psychiatric control group gives us one method for discovering it.

Your Subjects: Where Did They Come From? How “Normal” Are Your Normals? As with any study involving human subjects, psychopathology research studies must disclose where subjects were recruited from, how the recruitment was done, how the subjects were diagnosed, and so on. Given that the vast majority of research in psychopathology is carried out using subjects collected from clinical facilities that cover the range from inpatient services to outpatient clinical to college student guidance clinics, it is essential to bear in mind the various biases that can be present among such subject samples. It has long been known that people who make their way to the hospital for one or another ailment frequently have other problems as well. Thus, when one studies samples of individuals drawn solely from hospital settings, one must be alert to the potential artifacts that come with such populations. For example, the subjects may be more severely impaired or more likely to have certain medical events in their histories (e.g., suicide attempts), or they may have less supportive extended families. This reality was discussed long ago by the epidemiologist Berkson (1946), and his description of the problem has become known as Berkson’s bias, which refers to a form of selection bias. The bias, in this instance, reflects factors that create systematic differences between hospitalized patients and comparison control subjects. Such a bias can have a direct impact on the structure of data that are to be analyzed. Consider the study by Maric et al. (2004). It argues that the association between positive and negative schizophrenia symptoms is spuriously high because of the effects of a selection bias when subjects drawn from clinical settings are compared with those from nonclinical settings. An additional concern, not unrelated to the issue of selection bias, is the fact that many

98

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

people suffering from schizophrenia also suffer from disproportionately high rates of medical illness (Cimpean, Torrey, & Green, 2005)—50% of people diagnosed with schizophrenia have a comorbid medical condition (e.g., obesity, hyperlipidemia, diabetes, cardiac disease, blood-borne viral disease)—and this reality further clouds the interpretation of data drawn from patients in clinical settings. The potential impact of selection factors and other co-­occurring conditions in patient populations must be borne in mind when evaluating the results of any form of case-­control study. It is the rare report in psychopathology research that does not include a sample of what are termed “normal control” subjects. Whether one reads a report on clinically expressed conditions or subsyndromal or at-risk populations, there is very nearly always a “normal control” group in a study when group comparisons are to be made. Whether one is using psychometric measures, cognitive neuroscience tasks, neuroimaging techniques, or genomic probes, there is nearly always a normal control group present. The meaning of normal seems straightforward enough, but it is not. In the world of individual differences and unexpressed and latent liabilities, the true meaning of normal is not so clearly known. Thus it is essential to give as much time and effort to the definition and nature of the “normals” to be selected as is typically devoted to the selection of the patient (experimental) group. It is well known that when healthy volunteers are screened to serve as a normal comparison group for biomedical studies, many of those selected into the normal group are often harboring some nontrivial level of psychopathology or other dysfunction (Halbreich et al., 1989; Shtasel et al., 1991; Tishler et al., 2007). Tishler et al. (2007) found that among subjects who considered themselves to be in good to excellent physical health and generally good mental health, 50% revealed one or more clinical elevations on the MMPI2, the well-known psychopathology measure. How does one best proceed in selecting normal subjects?4 This substantive question looms large for research that uses normal subjects for contrast purposes. How does one define normal? Should normal indicate being at the mean or well below the mean on some measure of psychopathology, personality deviance, or other index of dysfunction? Is being at the mean (average) normal in a clinical sense, not merely a statistical sense? If someone has had a prior history of a mood disorder (e.g., depression), for example, as apparently 21% of the U.S. population has had (Kessler et al., 2005), should that person be excluded from consideration as a potential normal subject? 4 A

potent illustration of the impact of normal subjects on research findings can be found in the brilliant analysis of Smith and Iacono (1986) who revealed that the ubiquitous finding of enlarged ventricles in the brains of persons affected with schizophrenia had more to do with the normal control groups used than with schizophrenia per se.

Analytic Heuristics, Caveats, and Soapbox Moments

99

If someone has ever used marijuana after age 12, as has 40% (94 million) of the U.S. population (National Institue of Drug Abuse, 2003), should that person be excluded from consideration as a normal? Another consideration, albeit somewhat different, of relevance concerns the meaning of the term normal range scores on measures of psychopathology. For example, having a low score on a measure of paranoid personality disorder does not imply that one is an outgoing, healthy person who displays the polar opposite orientation to life and functioning in society as that shown by someone who scores high on the measure. If someone reveals very low scores on a trait measure of negative emotion (negative affect), does that mean such a person must show high levels of positive emotion (positive affect)? No, not at all. The meaning of low scores on screening measures of psychopathology is complex, but one thing is certain: the absence of deviance on a screening measure should not be taken as evidence of health in the direction opposite of that which was screened for in the first place.

Stay in the Laboratory and Stay Close to Your Data Students sometimes get the mistaken impression that as one gets on in his or her career in psychological science, one should spend more and more time farther and farther away from the laboratory. If you have taken the time to be trained properly and seek to delve into psychopathology, then take the time to do it right. That is essentially the point of all those years of training in the laboratory. By “do it right,” I do not mean merely conduct the experiment properly, but stay in your lab and come to know your data intimately. My graduate advisor, Bob Dworkin, would frequently ask me, “Mark, what is your sense of the data?” He was not seeking an immediate response to a specific question—one does not run statistical tests in one’s ear. However, he wanted to know my impression of the data, whether I knew the hills, valleys, plains, seashore profile of my data set. To maintain an intimate grasp of one’s data, one must stay close to the laboratory. However, the odd thing in psychological science is that, unless one makes a concerted effort to do otherwise, one often moves farther and farther away from the actual data collection process as one moves further up the tenure ranks. Evidence of this mind-set is shown by many advanced researchers who spend more time in managing budgets, grant renewal applications, and staff management than they do in collecting or analyzing data. Data collection, data cleaning, and analysis are often delegated to graduate students, who often relegate the most basic tasks to an undergraduate psychology major. Many

100

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

of you reading this book will have collected data in a laboratory under the guidance of a graduate student and have only vague memories of a professor even being involved in the process. Indeed, some students who are completing research apprenticeships at laboratories around the country will remark to me, “yes, it is Professor So and So’s lab, but I’ve never seen him/her in the lab, ever!” This is an unfortunate development in our field, one that quietly works against creativity and risk taking (as well as the goals of quality science training and education). An interesting (and somewhat humorous) example drawn from real research experience serves to highlight the value of attending closely to one’s data. It comes from the late Brendan Maher. He related the following (in Maher & Lenzenweger, 2006): Some years ago I was involved with a national multi-site study of kidney dialysis. The study was designed to compare the medical and psychosocial effects of different treatment schedules. A battery of biological and psychological measures was administered at initiation and then at three-­monthly intervals. One psychological measure, IQ, was assessed at the start-point, but not repeated at later intervals. At initiation the IQ was entered into its own labeled column [in the database]. At later retests that column was given an entry code number signifying “no data collected.” The code was the set of digits 99. Some twelve months later, a preliminary analysis of the data accumulated to date revealed various changes over time. Among these effects was one suggesting that kidney dialysis acted to “normalize” IQ to a value of 99 with a standard deviation of zero. None of the central statistical team had noticed that a “code” had become a variable and thereby produced a nonsensical result. In short, always look at the data before announcing results.

Stay close to your data—do not become so distant from the actual data that you could not detect some anomaly that could potentially reveal a crucial error (as well as avoid later embarrassment).

How We Think When We Think about Psychopathology: The Confusion between P(E|S) and P(S|E) Many students learn how to compare the means (averages) of two or more groups (typically a psychopathology group vs. normal control group) in terms of any variety of outcomes or dependent variables (e.g., IQ, anxiety levels, depression levels). This is typically done, as noted earlier, through the use of t-tests or the unfocused ANOVA approach. These same students also spend a good deal of time discussing the selection of the risk factors or putative lia-

Analytic Heuristics, Caveats, and Soapbox Moments

101

bility indicators for schizophrenia (e.g., deficits in sustained attention, defects in smooth pursuit eye movements). Typically, discussions regarding such liability indicators take the form of a discussion of “predictors” of schizophrenia liability or “indicators” that tap schizophrenia liability. Such theoretical discussions have normally been buttressed by empirical results that have shown the presence of deficits in the processes or constructs of interest in schizophrenia patients, first-­degree relatives of schizophrenia patients, and/ or schizotypic patients otherwise defined as referenced against some sort of normal control group. Thus one learns that schizophrenia patients show lower accuracy scores than normal patients on a measure of eye tracking. Or that first-­degree relatives of schizophrenia patients display poorer average performance than normals on a measure of sustained attention. (Such studies often include a psychiatric control group as well, and the reason for a psychiatric control group is to evaluate whether an observed group difference is reasonably specific to schizophrenia or is merely reflective of general psychopathology.) This all sounds well and good—one learns about group differences in the constructs of interest and discusses them within a predictive framework. The problem with all of this is that the predictive framework used to discuss the so-­called “predictors” or “indicators” is wrongly configured! What I mean by this is simply that our discussions presume that we know something about the ability of a predictor or indicator to actually predict or identify the form of psychopathology (or psychopathology liability) in question, but we normally do not have this sort of empirical information at hand. What we do have at hand are data that come from studies in which we already know that a liability exists in our experimental group (they have an illness), and therefore we really are evaluating the extent to which deviance is found on an indicator or predictor given the presence of liability. Although we often discuss results for putative predictors and liability indicators in the following manner (P(Schizophrenia|Deviance on indicator)), what we actually know is only (P(Deviance on indicator|Schizophrenia). This is not a minor issue. One hears the same sort of error in argument at professional scientific meetings, as well as on review panels for grant applications. The moral is simple: One needs to have empirical data that have actually been derived from a setup consistent with the argument that one wishes to make.

Unit of Analysis: The “Expanded Phenotype” As I discuss in the following section, one needs to take the proposed classification systems in psychiatry—that is, the DSMs in their various incarnations—with a grain of salt and not be hampered by them in terms of

102

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

generating new ideas regarding the organization of psychopathology. There is no compelling reason to believe that the DSM approach has cornered the market on truth, nor good reason to believe that it has “carved nature at its joints” as per Plato (427–347 BCE). Thus I would encourage all aspiring psychopathologists to consider the proposed phenotypes in the DSM-IV (and the ICD-10 as well) as “suggestions” (somewhat like red traffic lights in Boston are thought of by many as merely “suggestions”) that could be altered (stretched or shrunken) as organizing heuristics in the interest of achieving greater insights into etiology and pathogenesis. Thus, when one speaks of schizophrenia, I think it is useful to indeed think of the classical phenotype characterized by the flagrantly psychotic phenomenology of hallucinations, delusions, thought disorder, bizarre behavior, flattened affect, asociality, and so on. However, I think it is also important to consider that schizophrenia liability—the thing we are most interested in as psychopathologists— may not always manifest itself in this classical form. Thus the phenotype of schizophrenia should be “expanded,” in a sensible and rigorous manner, to accommodate alternative expressions of schizophrenia liability for the purposes of laboratory, including genetic, study. For example, following my own laboratory studies, I would argue that an “expanded phenotype” or “extended phenotype”5 for schizophrenia liability ought to include schizotypic psychopathology (Lenzenweger, 1998). Must all instances of phenotype expansion reflect the incorporation of additional forms of pathology defined by signs and symptoms? Not necessarily. Others, for instance, would argue for the inclusion of other expressions of schizophrenia liability, such as that thought to be reflected in deviant eye tracking (Matthysse & Parnas, 1992). The notion of an expanded phenotype has begun to take hold in psychopathology research outside of schizophrenia, which attests to its broader utility. The term expanded is somewhat vague and essentially refers to the “broadening” of the definition of the phenotype under consideration. This can be accomplished in different ways. If a disorder normally requires, for example, five out of eight criteria for the diagnosis of a condition, then an “expansion” could mean including those with four or more criteria as having the phenotype in question. If the cut score is lowered a little, the 5 One

sometimes sees the terms expanded phenotype and extended phenotype used more or less interchangeably, but they are not synonymous. Extended phenotype, according to the definition offered by Richard Dawkins (1982), refers to all effects of a gene on the world. As always, “effect” of a gene is understood as meaning in comparison with its alleles. The conventional phenotype is a special case in which the effects are regarded as being confined to the individual body in which the gene sits. It is perhaps best to limit extended phenotype to cases in which the effects influence the survival chances of the gene, positively or negatively; ww.simonyi.ox.ac.uk/dawkins/WorldOfDawkins-­archive/Dawkins/ Work/Books/extend.shtml#definition.

Analytic Heuristics, Caveats, and Soapbox Moments

103

resulting phenotype is broader. An expanded phenotype could also include related pathology conditions, in addition to the core phenotype of interest, creating a broader phenotype. For example, inclusion of schizophreniform illness and psychosis (not otherwise specified) along with schizophrenia to define a broader unit of analysis in genetic analyses would represent an expansion of the phenotype. Such thinking can be found outside of schizophrenia research; for instance, there are reasonable data to suggest that tic disorder (a disorder characterized by sudden involuntary, repetitive, stereotyped, nonrhythmic movements) represents an alternative expression of obsessive–­compulsive disorder liability (Grados et al., 2001; Hanna, Himle, Curtis, & Gillespie, 2005). One might ask, “Why do we need expanded phenotypes?” The answer to this question comes in three parts. First, the use of an expanded phenotype can enhance the statistical power of certain types of investigations, such as genetic studies. Second, if the liability for an illness genuinely expresses itself in ways that cross the borders of the more traditional clinical phenotype, then greater precision is gained in the study of that liability by including valid expressions of it. Third, there are instances in which those conditions or entities that are thought to reflect valid expressions of underlying liability for an illness—such as the theme of this volume, which maintains that schizotypic psychopathology is a valid expression of schizophrenia liability—may actually be able to shed greater light on etiology and pathological development. For example, the study of the schizotype who has never before shown evidence of psychosis might be a very profitable venture when seeking clues to etiology that are not clouded by factors such as deterioration, medication, and hospitalization effects (Lenzenweger, 1998). Finally, within the context of this discussion of the utility of the expanded phenotype for psychopathology research, it is important to note that the concepts of “expanded” or “extended” phenotype are not fungible (i.e., interchangeable) with the concept of the “endophenotype” (see Chapter 7 in this volume).

The DSM System/Architecture Has Not Cornered the Market on Truth Many an instructor in abnormal psychology (undergraduate) and psychopathology (graduate) courses spends a good deal of time teaching students the DSM approach (or the American Psychiatric Association approach) to the definition and diagnosis of psychopathology. Students learn about the

104

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

so-­called multiaxial system, what disorders fall on which axes, and so on. The explicit approach of the system is categorical, that is, one is diagnosed as either having or not having a disorder. Such an approach is well and good just so long as one does not come to believe that the diagnostic scheme presented in the DSM amounts to the “truth.” Indeed, a particularly dangerous combination can be found in (1) thinking that the DSM amounts to truth and (2) having excessively high levels of confidence in one’s ability to apply the DSM system (see Berner & Graber, 2008, for an excellent discussion of the effects of overconfidence on diagnostic error in medicine). The DSM is a powerful professional–­social–political document (Meehl, 1986b; Lenzenweger, 2010a). This claim does not speak to the validity of the document or system; rather, it notes how the document affects the conduct of research, research proposal development, the treatment of patients, and public health planning. In considering the ways one could view the DSM, Meehl (1986b) noted that the manner in which one regards the document can have profound effects on research and clinical progress, as well as on the emergence of new ideas and themes for revision. Many discussions with researchers, practitioners, and students over the years suggest that Meehl’s analysis is worth repeating here. Thus Meehl (1986b) argued that there are those who view the diagnostic constructs explicated in the DSM as representing symptomatically defined syndromes that (1) hang together (descriptively or statistically), (2) have some unknown or unspecified etiology (that is likely shared by those diagnosed with the conditions), and (3) have some communicative value. This view reveals a reasonable intellectual approach to the thorny problem represented by the classification and treatment challenges in psychopathology. He described two other viewpoints, speaking coarsely (there is probably some gradient across these viewpoints), that one might see among those working with the DSM system (Meehl, 1986b). One is more common, reasonably harmless, although intellectually impoverished, whereas the other is, as Meehl (1986b) noted, “scientifically malignant” (p. 220) and speaks to a view that somehow the DSM articulates the truth. The view that is relatively harmless is one that holds that the constructs defined in the DSM system are somehow correct and the best we can do for now, with an implied openness to revision down the line. This is an OK view, just as long as those who think the DSM is the best we can do for now do not get in the way of those seeking to explore other entities or models of psychopathology. With respect to new roads and avenues of exploration in alternative approaches to psychopathology, adherents of this second view should not block progress based on the assumption that the DSM is the best we can do. As Bob Dylan

Analytic Heuristics, Caveats, and Soapbox Moments

105

sings, in “The Times They Are A-Changin’,” “Your old road is/Rapidly agin’./ Please get out of the new one/If you can’t lend your hand.”6 The mistaken and intellectually indefensible view that the DSM constructs represent the truth is indeed bad news. Not only can such a misguided view get in the way of progress, but it is also grounded in a view of entities and “operational” definitions that has long been abandoned by informed philosophers of science and psychological science researchers. What is meant here? If someone believes that the meaning of the conditions in the DSM is defined by the list of signs and symptoms (or DSM-defined diagnostic rules), then one is implicitly subscribing to an operationism (so-­ called operational definitions) that has long been discounted in philosophy and psychology. Conditions (or diseases) in traditional organic medicine are defined not merely by signs and symptoms; rather, they represent (implicitly) information regarding etiology, pathophysiology, and so on. If information about etiology and pathophysiology are absent from such constructs in organic medicine, then, at a minimum, the construct in question is viewed as in need of further research. In short, the constructs defined explicitly in the DSM7 do not represent the truth, so to speak, and they do not represent the intellectual end of the line. The reader might think this is self-­evident; however, one should remember the frequent precursor to the modal question that follows many conference talks or colloquia—­namely, “According to the DSM-IV, yadda, yadda, yadda.” I think a routine rejoinder after talks to such a preface should be “Just what do you believe about the constructs in the DSM manual?”

Don’t Let the DSM Get You Down— You Can Think Outside the Boxes One should always be free think outside the proverbial box when it comes to identifying meaningful parsings in the realm of mental disorder. Experimental psychopathology and clinical psychological science, it seems, have been more comfortable exploring the manifestations of severe psychopathology that fall outside what appears in print on the pages of the DSM. Concepts such as schizotypy (the liability for schizophrenia), psychopathy (as distinct from the 6 Copyright © 1963; renewed 1991 Special Rider Music. All rights reserved. International copyright secured. Reprinted by permission. 7 There

are no true “operational definitions” in the DSM. That is, operations by which the disorders are related to the signs and symptoms defining the disorder are not specified, nor are the operations needed to make the diagnosis specified in any strict sense of the term operational.

106

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

sociodemographically defined antisocial personality disorder), or borderline personality organization (e.g., Kernberg’s [1984] phenomenological organizing framework for personality pathology) serve as but a few rich examples. Each of these theoretical concepts has spawned rich research literatures that have illuminated important aspects of more traditionally defined psychiatric conditions. For example, the laboratory study of schizotypy has generated a remarkable corpus of findings that support schizotypic psychopathology as an alternative manifestation of schizophrenia liability. To work outside the realm of DSM disorders in psychopathology research, however, requires persistence and tenacity, as many reviewers and funding agencies feel comfortable dealing only with papers and proposals that seek to investigate “established,” if you will, entities. This is not completely unexpected, as review processes (including National Institute of Mental Health [NIMH] study sections) are characterized by an inherently conservative spirit and, according to some longtime informed observers of study section behavior, a “groupthink” process, which, taken together, limit the adventurousness of all concerned.

Genes Will Always Matter (If You Do the Experiment Right) Genes will always matter. Allow me to relate some anecdotes.

Anecdote During my first year as a new professor I was invited to give a “brown bag” lunch presentation on my research in schizotypy. I had just published my 1989 paper in the Archives of Psychiatry (Lenzenweger & Loranger, 1989a) that demonstrated that one could measure a schizotypy indicator in nonpsychotic individuals (who had never had psychosis) and find that elevated levels of perceptual aberration would predict higher risk for treated clinical schizophrenia in the biological first-­degree relatives of those assessed patients. This finding helped to establish the notion of unexpressed liability in relation to schizophrenia (cf. Gottesman & Bertelsen, 1989). I gave my presentation, discussed limitations of the study, and discussed implications of the findings, one of which was that these results were consistent with a model postulating that genetic influences for schizophrenia mattered. After my presentation, I was approached by some earnest senior attendees at the presentation, and these folks expressed great surprise (really, a notwell-­hidden discomfort) at any discussion or suggestion of genetic influences being related to behavior, personality, or psychopathology. I then (politely)

Analytic Heuristics, Caveats, and Soapbox Moments

107

endured an impromptu lecture on what the late psychologist and behavior geneticist David Rowe described as “socialization science”—the idea that only the way one was reared mattered (see Rowe, 1994). I was perplexed; I simply did not know how to respond to this sort of narrow viewpoint.

Anecdote A little background is required to place this next anecdote in context. As a graduate student, studying under the direction of Robert H. Dworkin, I conducted my master’s thesis research on positive and negative symptoms and genetic influences in schizophrenia. This study really represented a new look at the rich clinical data bases available for the major twin studies of schizophrenia, uniting the twin-study method with research on positive and negative symptoms (Dworkin & Lenzenweger, 1984). The study was exciting to carry out, and we found that negative symptoms were more closely associated with genetic influences for schizophrenia than were positive symptoms. A short while later I was out on the interview circuit as part of the clinical psychology internship application process. I was being interviewed by a well-known psychoanalyst who had focused a good deal on psychosis in children in his clinical career. During my interview, which happened after a grueling morning of repeated interviews with many staff members at the clinical site I was visiting, I described my research findings on genetics and symptomatology in schizophrenia. The interviewer looked at me in a stern (albeit somewhat kindly) manner and said “You don’t think genes matter in schizophrenia, do you?” Given that it was 1984, the corpus supporting genetic influences on schizophrenia was already mountainous, and I was probably a little mentally tired. I responded with “Of course I do” and then followed with “Don’t you think it is a little late in the day [speaking figuratively] for a view that would not see genes as important in schizophrenia?” In that moment, I knew two things: (1) I was face to face with my interviewer’s ideology and (2) I would probably never get admitted to that internship. (C’est la vie!) My senior interviewer slowly (and not so subtly) shook his head, ended the interview shortly thereafter, and said “good luck” as he showed me to the door.8 “Scratch that one off the list,” 8 I could not fathom why this well-­regarded, senior psychoanalyst could not understand that genetic factors mattered in schizophrenia as of the 1980s. Freud and Jung clearly saw a genetic component and an organic basis for schizophrenia as highly plausible. Moreover, I thought then (and still do) that there was nothing about genetics that was incompatible with understanding the psychological dynamics of someone afflicted with schizophrenia, even if the disease itself hailed in large part from genetic factors. The clinical psychologist should always be interested in and seek to understand and illuminate a person’s inner dynamic experience, whether it has a basis in genetic factors (e.g., schizophrenia) or is due to environmental inputs (e.g., HIV infection, surviving terrorist attack).

108

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

I thought. Until, several days later, I got a telephone call from the recently chosen new director for that particular internship site—a well-­regarded, scientifically research-­oriented psychopathologist—and that person said to me, “I understand you had an interview here last week where you discussed the role of genetics in schizophrenia.” “Yes, I did,” I replied candidly, “but I assume my scientific view on the matter sunk my interview with Dr. Soand-so.” “Well, I think you are just the person we want here. Would you please return for another interview, with me?” the new director asked. I was a bit flabbergasted, but, of course, I agreed to another interview. (I was offered a position at that site after all, but chose to go elsewhere for my internship training in clinical psychology).

Anecdote Some years ago I was attending a job talk being given by a sociologist with an interest in mental health matters. In the course of a reasonably well-­organized and well-­presented colloquium on the factors related to the emergence of major depression, the candidate ended the talk by summing up all the evidence for environmental causes for major depression. Dutiful caveats were given regarding methods and statistics, and that was the end of the talk. There was no mention whatsoever of genetics or potential biological bases for major depression. Afterward, as people were leaving the room, I quietly asked the candidate if there might be some other factors that could be the cause of depression. The candidate looked perplexed, and then responded to me, “Well, I don’t know, can you think of any? I mean, what do you have in mind?” I replied, “Well what might be going on in the people who developed major depression? Are there any background or baseline variables that should have been included in your regressions?” The candidate replied, “I don’t know, I mean, you must have some ideas.” I said, “Would you have considered possible family history of affective illness as a rough proxy for what could be a genetically influenced liability?” The candidate replied, “Well, I don’t know, I guess, maybe.” True story! Clearly, there has been a sea change in our scientific understanding of those factors known to influence human behavior, personality, temperament, and psychopathology (including schizophrenia, of course) in the past 20 years or so, and the role of genetics and genetic influences in this set of factors has the status of established fact. That said, I do not doubt that one could still encounter the erroneous view that genetic influences have no relevance to schizophrenia (as well as, more broadly, individual differences in behavior, personality, and/or psychopathology), but I hope the base rate

Analytic Heuristics, Caveats, and Soapbox Moments

109

of such thinking has declined in the ensuing decades. As Meehl (1972) asserted, “Genes will always matter if you do the experiment right” (italics in original; p.  196; as reprinted in Waller et al., 2006). Does this assertion and my (obvious) view on the issue mean that everything that matters is genetic? No! Does it mean that environment has no role in psychological development or the development of psychopathology? No! The student of psychopathology might merely consult the concordance rates for schizophrenia among monozygotic (identical) twin pairs, which run well below 100%, to understand that environment must matter. Does it mean there is no place in psychopathology for psychology, just a place for geneticists? No! But it does bear repeating that “genes will always matter” in some manner if one is studying variation in human behavior, personality, and/or psychopathology.

Beware of “Large-Scale, Low-Risk, Low-Gain, Big-Bucks” Research The saying goes that “size doesn’t matter.” This is something to keep in mind in evaluating some, not all, projects in psychopathology research today. There has been a palpable tendency for large-scale projects to begin to take up more space on the scientific stage. In some cases, this is really quite reasonable, and the scientific yield can be impressive. In other cases, the justification for large-scale collaborative research projects leaves something to be desired, as the scientific questions at stake are rather nominal in light of the existing corpus of knowledge, the design and methods that are settled on by the multitude of investigators lack innovation or seem cobbled together (some say “a camel is a horse built by committee”), yet the price tag on many such multisite, mega-­authorship projects is massive. Although the increase in sample size that typically comes with large-scale collaborative projects is a positive feature, one should not conflate size or statistical power with creativity, rigor, or innovation. I mention this concern as I have seen many students and even beginning faculty members seemingly dazzled by reports from large-scale projects and the implicit evaluation of the work seems to be a function of the sheer size of a project. “Professor Lenzenweger, the data I am discussing hail from the huge ‘do-dah-do-dah’ collaborative project” (usually referred to by some catchy acronym), a student might assert when challenged on a meaning and importance of a research finding. “Ah, yes, the old ‘do-dah-do-dah’ collaborative project, but what do you think of the design, methods, and analysis of data for the project?” I often query. When

110

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

the taxpayer’s dollar is being spent to support most of these large-scale projects, we owe it to ourselves as a responsible scientific community to remain critical and judicious in our evaluation of all projects, large and small. Thus beware of “large-scale, low-risk, low-gain, big-bucks research with which we are comfortable now, but will regret later.”9 Also, with respect to career development for the aspiring student, although large-scale research projects may have a certain appeal on first blush for those seeking a career in science, you must always consider your precise role in the project and determine whether you will have the chance to do leading research within the group (or will you merely be a member of the baseball team of authors in the byline). Large, multisite collaborative projects can have a factory-like quality, in which one is given the impression that one will be contributing in a major way; however, the reality is typically less exciting and rewarding than pursuing one’s own path.10 When contemplating involvement in mega-­projects, perhaps it is best for the student to ponder whether he or she would prefer even a “smallish” role in a highly creative, high-risk research project to functioning as something of a worker bee in an extremely largescale, scientifically low-risk mega-­project.

Remember, There Is a Scholarly Psychological Science Literature Before the PDF On occasion my students will say to me that they could not find anything on a topic prior to 1998 or so. After some gentle probing and a certain expression of disbelief on my part, I learn that the students have been looking only at the literature that can be found in electronic format, namely portable document format (PDF) articles. It also becomes evident that students have not gone to the library to look at the hard-copy journals; thus, with many journals, they are missing out on upward of 50–100 years of scientific literature in some cases. Dead tipoffs that this sort of scholarly literature research strategy may have been guiding a student’s research process include, for example, seeing things such as the following in term papers: (1) 9 I do not think all large-scale projects are hopelessly mediocre. Clearly, research of any sort can be weak. What I seek to remedy here is the (mis)perception that “bigger is always better.” 10 Early-­career

scientists often ask about the wisdom of signing on to mega-­multisite collaborative research projects. One must be careful to avoid hitching one’s wagon to projects in which one’s talents will be underutilized or horizons truncated owing to limited opportunities in light of a large cadre of senior researchers. Moreover, a colleague of mine once quipped, “If you are not the lead author on a paper, then you are simply part of et al.”

Analytic Heuristics, Caveats, and Soapbox Moments

111

the term schizotypy mentioned but no citation to Meehl; (2) twin studies of schizophrenia mentioned, but no citation to Gottesman; or (3) “prediction in personality” mentioned, but no citation to Wiggins. The student is encouraged to study the psychological literature in toto and not merely focus on the PDF papers available, say, after the year 2000. Psychology is an infant science, barely 100 years old, yet much of the real gold in the field remains in the original, hard-copy journals, as well as monographs and edited volumes. Although many journals are laboring to get their backfiles into PDF format, there remain numerous issues of many journals that still reside only within the stacks of the library.

On Translating Basic Science Paradigms for Use in Psychopathology Research The application of cognitive neuroscience frameworks and experimental protocols to psychopathology is rampant. One must be on guard for these wanton applications. “Oh, the cognitivists are using the Boombotz task— let’s give it to some schizophrenia patients to see what we find.” Moreover, one will see, at times, the same investigator giving the Boombotz task to patients with obsessive–­compulsive disorder, then to patients with posttraumatic stress disorder, then to patients with panic disorder, then to patients with XYZ disorder, and on and on. The moral here is simple—if you are going to import a cognitive neuroscience task or protocol into experimental psychopathology, do so mindfully and with due consideration for what the specific paradigm, protocol, or task will provide by way of genuine leverage on a theoretical matter of real interest for that psychopathology. This caveat should not be misread as to mean not to use cognitive neuroscience paradigms in psychopathology. On the contrary, they can be quite useful and provide genuine leverage. An example of this sort of highly productive use of a cognitive neuroscience paradigm can be found in the work of Korfine (Korfine & Hooley, 2000), who developed the “directed forgetting” paradigm for use with borderline personality disorder. An all­important consideration in this type of work is to make sure the task that is to be imported has been sufficiently evaluated for use with patients. On occasion, such tasks will need to be adjusted or modified in some manner to make the tasks patient friendly. An excellent discussion and proposed framework for such task modification efforts can be found in Luck and Gold (2008; see also Jonides & Nee, 2005).

112

THE EXPERIMENTAL PSYCHOPATHOLOGIST’S TOOLBOX

On Bulls, Royal Worcester China, Schizophrenia, and Control Tasks in Psychopathology Research It is not unusual for students of psychopathology to seek to come up with clever research designs by which they can illuminate one deficit or another in schizophrenia or schizotypic psychopathology. They are working hard to place their budding ideas into a research design that will be effective in answering some question, which usually takes the form of a deficit. Their preliminary research design normally has a pathology group being contrasted with a normal group (and usually a psychiatric control) but a focus on only one task or variable. Their hunch or hypothesis rides on this one task or variable. When I have detected that students have gotten to this point in thinking about the subject matter and are excited to try on their methodological new clothes, I tell them we need to consider Royal Worcester china for a moment. This announcement not infrequently generates some knit brows and looks of perplexity (others surely think, “he’s finally gone round the bend”). What is this Royal Worcester china business? The best way to answer this is to revisit some classic text by Brendan A. Maher that he included in a 1974 editorial piece at the beginning of his tenure as editor of the Journal of Consulting and Clinical Psychology, a venerable research journal of high quality (see Box 4.2).11

Words to Research and Write By: “Think Yiddish, Write British” Apparently years ago there was an advertising slogan on Madison Avenue— New York City home of many large, influential advertising firms—that went something like: “Dress British, Think Yiddish.” The idea is that inside one wants to think in the creative, divergent, yet critical attitude suggested in the idea “think Yiddish”—in short, a mode of thought suggestive of wisdom. However, when it comes to dressing, one should look quite proper, smart, and all rather British (think of the prime minister of Britain; i.e., good quality dark suit, white shirt, dark tie, dark socks, and black shoes). Thus, make a sharp, smart appearance, but maintain an inner attitude reflective of wisdom and of creative and critical thought.12 11 The 12 One

essential reading on this topic is Chapman and Chapman (1973, 1978).

need not worry over the intellectual talents of the British or the fashion sense of those who speak Yiddish.

Analytic Heuristics, Caveats, and Soapbox Moments

113

BOX 4.2. On Royal Worcester China and Psychopathology Research Strategies Brendan A. Maher In less formal settings, I have drawn attention of colleagues and students to the “Bull in a Royal Worcester china shop” strategy in research. With the hypothesis that bulls are characterized by a desire to break Royal Worcester china, we stock a shop exclusively with that item, turn the bulls loose, and watch the ensuing destruction. Our hypothesis is duly confirmed—especially if our control group is composed of mice. A lightly disguised version of the same thing is found when we compare a psychotic patient sample with a control sample at any task requiring motivation, attention, coordination, etc., and conclude that the reason for the patients’ deficiencies is to be found in some specific aspects of the particular task that we used. Just as bulls tend to break any kind of china, patient populations tend to do poorly on many tasks. Poor performance at a specific task is thus uninformative about the pathology unless it is accompanied by evidence of adequate performance at some other task that makes similar demands on general psychological functioning. A control task, or control response, is just as necessary as a control group when the hypothesis at test predicts poorer performance in one group than another. From Maher (1974, p. 2).

Rosnow and Rosenthal (1989) creatively applied this notion to psychological science when they wrote that “think Yiddish, write British” might be an apt slogan for the dominant discursive pattern of the intuitions and inductive inferences that characterize the scientific outlook in psychology during the 20th century. As is true in other fields, the inventive ways that psychological researchers think frequently seem to resemble the hunches and intuitions, the illogical as well as logical inferences, of an astute Jewish grandmother. In contrast, the rhetoric of psychological science, the tightly logical outcome of this “thinking Yiddish,” tends to be consistent with the traditions of British empiricist philosophy. As in the case of post hoc analysis and the context of discovery, I would encourage the attitude embodied in Rosnow and Rosenthal’s (1989) observation; indeed, if one wants to do interesting creative work in psychological science (or any science for that matter), one should “think Yiddish,” but when it comes time to write it up or apply for a grant, “write British.”

Part III

Schizotypy Viewed from the Laboratory

Chapter 5

Recognizing the Schizotype

How do we come to know the schizotype? What do we see when we observe the schizotype? What things do we hear when we speak to a schizotype? Recalling the previous clinical anecdote of the young man who asked me if I was taking him into the “star chamber,” we must ask, How do we come to know this man as a schizotype? What are the prominent clinical signs and symptoms of the schizotype? The schizotype is not necessarily easy to find owing to the fundamental interpersonal nature of the pathology. They do not spend a great deal of time interacting with other people. From a descriptive perspective, Kendler (1985) reviewed the signs and symptoms that were commonly found among observers of the schizotype. One group of observers was concerned with the phenomenology of the biological relatives of schizophrenia patients (e.g., Kraepelin, Bleuler). The other group of observers were clinicians in office practice. These practitioners described, over the years, a patient who presented for outpatient, office-based psychotherapy. This patient was nonpsychotic but presented “schizophrenia-like” symptomatology. Kendler (1985) proposed the former group of observers could be thought of as representing a “family tradition,” whereas the latter group he termed the “clinical tradition” observers. Among the relatives of schizophrenia patients, the following signs/symptoms/descriptors were noted by many observers: odd/eccentric or irritable/unreasonable behavior, social isolation, and aloof or cold demeanor. Among those clinicians in office practice who saw schizotypic patients, the following signs/symptoms/

117

118

SCHIZOTYPY VIEWED FROM THE LABORATORY

descriptors were most commonly noted: disordered thinking and lack of deep interpersonal relations. Many of those signs and symptoms contained in the four case histories presented in Chapter 1 of this volume are those features that have been described over the past century as indicative of schizotypic psychopathology.1 The signs and symptoms of schizotypic psychopathology include, but are not limited to, suspiciousness, odd/eccentric beliefs, unusual/odd behavior, lack of social connections (few or no friends), aversion/anxiety in the context of social interaction, referential ideas, magical thinking, perceptual anomalies (mistaking objects or shadows for people), mild thought disorder (speech that is difficult to follow, overly and/or oddly detailed, peculiar word choices and/or usage), inappropriate or blunted affect, and so on (see American Psychiatric Association, 2000, for the current DSM-IV-TR diagnostic criteria for schizotypal [p. 701] and paranoid personality [p. 694] disorders).

Three Ways to Define and Conceptualize the Schizotype Experimental psychopathologists have learned that schizotypic psychopathology is meaningfully related to schizophrenia liability. Many workers have sought to determine whether the organization of nonpsychotic schizotypic signs and symptoms bears any resemblance to what is known about the organization of actual (psychotic) schizophrenia phenomenology. In short, exploratory (see Andreasen, Arnott, Alliger, Miller, & Flaum, 1995) and confirmatory (Lenzenweger & Dworkin, 1996) factor-­analytic studies have suggested that schizophrenia symptoms are best organized into three factors: negative symptoms (flattened affect, avolition), reality distortion (hallucinations, delusions), and disorganization (thought disorder), with a fourth possible factor consisting of premorbid social impairment (see Lenzenweger & Dworkin, 1996). Factor-­analytic studies of schizotypic signs and symptoms yield solutions or conform to models that are broadly consistent with the picture observed for schizophrenia. For example, Raine et al. (1994) found that a three-­factor model, which consisted of what he termed cognitive/perceptual, interpersonal, and disorganization components, provided a good fit to observed data (see also Mason, 1995). Others have rather consistently obtained broadly convergent results (see Fossati, Raine, Carretta, Leonardi, & Maffei, 2003; Wuthrich & Bates, 2006, Badcock & Dragovic, 2006). 1 At

the time when the breadth of the diagnostic definition of schizophrenia was excessively broad, many schizotypes were probably (incorrectly) diagnosed as having full-blown schizophrenia.

Recognizing the Schizotype

119

Thus, at the phenotypic level, not only do schizotypic signs and symptoms bear some resemblance to schizophrenia manifestations (albeit attenuated), but they are also organized in a similar fashion at the latent level (i.e., they have similar factor structures).

What Is the Best Methodological Approach to Assessing Schizotypic Psychopathology? Although clinical psychiatry has always used the psychiatric interview as the workhorse assessment method, the interview is only one of several approaches to assessing schizotypic psychopathology. Much of the research on schizotypy has used alternative approaches to assessment and classification (and not limited itself merely to psychiatric interviews for assessment purposes). Thus no one assessment method has cornered the market on diagnostic or classification truth when it comes to detecting schizotypy. How best to assess the schizotype? The diagnostic interview is clearly an option. That said, given what we know about the phenomenology and subjective experience of the schizotype, the pros and cons of interviewing as the basis for the assessment of schizotypic psychopathology should be considered. Despite the enormous gains in reliability and validity of the assessment of personality disorders in general, typically via semistructured interviews (e.g., International Personality Disorder Examination [IPDE]; Loranger, 1999), it is well known that the level of diagnostic agreement across different personality disorder assessment methods is not nearly what it should be. Indeed, Meyer (2002), in a review of various psychopathology assessment methods (considering both reliability and validity), concludes by advocating strongly for the use of multiple independent methods and independent data sources. This, however, is rather rarely (if ever) done in research (or clinical) practice. On occasion, one will see the use of informant interviews to assist in the diagnosis of personality pathology. Although the informant interview approach can be helpful in the assessment of personality pathology—­ including schizotypic psychopathology (Lenzenweger, 2009)—the level of agreement between patient reports and those from an informant about the patient tend to be “modest at best” (Klonsky, Oltmanns, & Turkheimer, 2002, p. 300). Interviewing the schizotype requires an unusual degree of tact and sensitivity in order to facilitate the interview process. One must remember that the schizotype is a person who finds being around other human beings anxiety provoking, perhaps even terrifying. One must proceed in an interview sensitively with this in mind. Empathy and patience are always good

120

SCHIZOTYPY VIEWED FROM THE LABORATORY

ingredients for successful interviewing, but I stress that it has been my experience that even greater levels of empathy and patience seem indicated with the schizotype. This is especially true as many of the things that schizotypes talk about—what their experience is, what they believe, “causality” they have observed, and so on—as well as the manner in which they speak can be highly unusual, and it is incumbent on the interviewer to maintain an inquiring and nonjudgmental stance in exploring such material. Clearly, the interview method, given the empirical literature on the reliability and validity of the approach, is an essential approach in assessing the schizotype. However, the psychiatric interview method is by no means the only approach available. One should consider self-­report psychometric inventory methods, as well as other laboratory measure approaches, for the measurement of the features of schizotypic psychopathology.

How Is the Schizotype Defined? How Do We Find the Schizotype? Schizotypic psychopathology can be defined in one of three ways: (1) clinically, (2) in terms of deviance on reliable dimensional laboratory measures, or (3) by virtue of having a first-­degree biological relative affected with schizophrenia (Lenzenweger, 1998). The clinical approach implied in psychiatric diagnostic schemes involves, quite obviously, the use of explicit diagnostic criteria (e.g., DSM-IV-TR) to identify either schizotypal personality disorder (SPD) or paranoid personality disorder (PPD). A second approach—what I term the laboratory approach—involves the use of reliable and valid psychometric (or other laboratory) measures of schizotypy to detect schizotypic psychopathology as defined by quantitative deviance on such measures. In this approach, psychometric scales designed to assess various schizotypic manifestations serve to define and measure the schizotypy construct; schizotypic status may be defined by deviance on one or more of such measures. The nature and typical use of the psychometric high-risk approach has been discussed and reviewed extensively in the past (Chapman, Chapman, & Kwapil, 1995; Edell, 1995; Lenzenweger, 1994). It is important to note that the clinical and laboratory approaches are not completly overlapping. Neither psychometric assessments of schizotypic phenomena nor clinically assessed (interview-based) DSM-defined SPD and/or PPD measurements are perfectly related to the underlying schizotypy construct. This is due to the necessarily imperfect measurement of true schizotypy, which renders both fallible as approaches, as well as to differences in breadth and character of the identified units of measurement in

Recognizing the Schizotype

121

both approaches. By the latter I mean, for example, that DSM diagnostic constructs have a different breadth and nature as contrasted with those features of schizotypy assessed within the psychometric tradition. Finally, the third approach—known as the family or biological-­relatives approach—is concerned with the biological relatives of schizophrenia patients, and we can speak of “possible genotypic” schizotypes. Though many first-­degree relatives of schizophrenia patients will not evidence their underlying genetic predisposition to the illness through schizotypic symptomatology, and although some relatives will not harbor schizophrenia liability at all (Hanson, Gottesman, & Meehl, 1977), these relatives are, as a group, at increased statistical risk for schizophrenia and, therefore, can be spoken of as schizotypes. Some relatives of schizophrenia patients will, indeed, display schizotypic symptomatology (Kendler, 1985; Kendler et al., 1993; Maier, Falkai, & Wagner, 1999), but some, quite importantly, will harbor schizotypy yet show no signs or symptoms of schizotypic psychopathology detectable with the clinician’s eye.

Prevalence of Schizotypic Psychopathology How many individuals in the general population would be diagnosed as having schizotypic personality or psychopathology? This is not an easy question to answer. This is so because schizotypic individuals (owing to their aversion to interpersonal contact and detachment from the social world) are largely “invisible.” By this I mean that they do not typically draw attention to themselves through impulsive, aggressive, or other chaotic behavior. Many schizotypic persons live relatively quiet and withdrawn lives. They might appear as “loners,” “shut-ins,” or “detached eccentrics.” Rich clinical descriptions of such persons can be found in a number of sources, and they are well worth consulting (e.g., Meehl, 1964; Wolff, 1995; Kendler, 1985, and references therein). However, as a result, one rarely sees a schizotype in clinical settings unless that person has reached some crisis point or emotional or relationship impasse. Then, typically, issues such as suicidal behavior, substance abuse, or an increased level of depression might motivate the schizotype to seek out clinical attention. This picture, then, presents two important things to keep in mind when wondering about the natural history and typical presentation of the schizotype. First, a schizotype is relatively cut off from most of what we think of as the social world, hence they are not commonly seen or noticed in the community. Second, when a schizotype does present for clinical attention, it is likely that the phenomenological

122

SCHIZOTYPY VIEWED FROM THE LABORATORY

picture that emerges in a clinical assessment will be tainted to some extent by state-­related disturbance (e.g., depression, suicidal ideation). Given these considerations, how many schizotypic individuals exist in the general population? How effectively can we find them? Will a schizotype answer the doorbell when the epidemiologist comes a callin’? Can we be confident in such epidemiological estimates?

Epidemiology of Schizotypic Psychopathology: The View from the DSM Approach For most of the last century, as with other personality disorders, prevalence “estimates” for schizotypic psychopathology had been arrived at through indirect routes and were considered, at best, to be educated guesses. The DSM-IV-TR, as well as prior versions of the DSM, suggested prevalences for SPD of approximately 3% and for PPD of 0.5–2.5% in the general population. Such “guesstimates” were derived from relatively large clinical samples. For example, Loranger (1990) reported, in a large series of consecutive psychiatric admissions to a university teaching hospital, 2.1% for DSM-III SPD and 1.2% for PPD. Zimmerman and Coryell (1990) reported, based on telephone interviews, that SPD was found to occur in 3.0% of their subjects and PPD was found in 0.4%. Zimmerman, Rothschild, and Chelminski (2005) reported rates of 0.6% for SPD and 4.2% for PPD in a large series of outpatients at a university hospital. However, since 1997, a number of community-based samples have been studied using epidemiological methods and state-of-the-art diagnostic interviews, and we now, at least, have reasonable estimates for SPD and PPD rates in the population. Lenzenweger (2006a, 2008) has summarized the prevalence data for SPD and PPD from five community studies (three U.S. studies, two European studies). For SPD, the prevalences ranged from 0.06% to 1.6% (mean = 0.60%, median = 0.80%), whereas the prevalences for PPD range from 0.7% to 5.10% (mean = 1.98%, median = 1.00%). Lenzenweger, Lane, Loranger, and Kessler (2007), in the National Comorbidity Survey Replication (NCS-R), found a prevalence of 5.7% (SE = 1.6) for Cluster A disorders (which included schizoid personality disorder) for the U.S. population. In the stage 1 clinical reappraisal sample in the NCS-R, the prevalence of SPD was 3.3%, whereas the prevalence for PPD was 2.3%. One must, of course, consider that the prevalence estimates for the DSM-IV-defined disorders necessarily reflects both the diagnostic threshold set for the disorder in the DSM-IV system and the conservativeness of the diagnostic procedure used in any given study.

Recognizing the Schizotype

123

Epidemiology of Schizotypic Psychopathology: Thinking Outside the DSM Boxes To begin, one must remember that “schizotypic psychopathology” is a broader construct than the contemporary DSM definitions of SPD and PPD. Useful guidance on the epidemiology of this “broader construct” can be garnered from other sources as well. For example, Essen-Möller, Larsson, Uddenberg, and White (1956) reported from their landmark study of a rural Swedish population that schizoid personality, in the sense of “probably related to schizophrenia or to a schizophrenic taint” [sic] (p. 73), was found among 1.8% of women and 6.0% of men. Kety et al. (1994), in a recent report from their landmark Danish Adoption Study of schizophrenia, found that among the biological relatives of normal control adoptees, 0.8% had PDD, 3.3% SPD, and 2.5% “latent schizophrenia,” a pre-DSM-III diagnostic designation roughly akin to SPD. Kendler, Gruenberg, and Kinney (1994), in a secondary analysis of the Kety et al. (1994) data, found that, according to DSM-III criteria, from 3.1 to 3.7% of the relatives of the normal control adoptees had either SPD or a “schizophrenia spectrum” diagnosis (or schizotypic psychopathology more generally). Generalization from family-based data to population prevalences must be done with caution owing to various constraints inherent in family data (Carey, Gottesman, & Robins, 1980). Finally, based on a consideration of familial risk rates, Meehl (1990) argued that approximately 10% of the population are genotypically schizotypic, though not all manifest this predisposition in a visible manner. Meehl’s conjecture was supported by empirical taxometric (Lenzenweger & Korfine, 1992a; Korfine & Lenzenweger, 1995; Meyer & Keller, 2001; Linscott, 2007) and mixture modeling work (Lenzenweger, McLachlan, & Rubin, 2007).

Further Methodological Issues to Keep in Mind in the Detection and Assessment of Schizotypy The State–Trait Issue in the Assessment of Schizotypic Psychopathology For schizotypic individuals, their day-to-day, even moment-to-­moment, experience is one that is frequently riddled with anxiety and discomfort in interpersonal situations. Many live with profound levels of anxiety that they have, more or less, adapted to, typically by withdrawing from contact with other people, structuring their lives to minimize interpersonal con-

124

SCHIZOTYPY VIEWED FROM THE LABORATORY

tact with others, and learning to tolerate an ambient internal environment characterized by anxiety, perceptual aberrations, paranoia, and discomfort. Although 5.7% of the U.S. population would qualify for a DSM Cluster A SPD-related diagnosis (Lenzenweger, Lane, et al., 2007), most of these individuals likely never present for clinical attention. As noted earlier, one does not typically see a schizotype in the clinic or in private practice unless something has happened to push the person into a consultation, such as an increase in suicidal ideation or impairing levels of substance use. The assessment question then becomes a complicated one: How does one assess the schizotype for diagnostic purposes when (1) he or she tends to be very anxious on a trait basis and (2) he or she may be showing elevated levels of anxiety in the context of a clinical crisis? How can one sort out the differences between trait-like symptomatology and state-­related symptomatology? Can one assess schizotypic phenomenology with confidence that one is not merely tapping into state-­related disturbance? The landmark study by Loranger et al. (1991) provides some of the most useful evidence on this issue. In this study, more than 100 nonpsychotic patients who were admitted consecutively to a variety of clinical services at the New York Hospital—­Cornell Medical Center in White Plains, New York, served as the study subjects. They were assessed for Axis II personality disorder features—­including schizotypic features—at admission and then just before discharge. What is remarkable about this particular sample is that the individuals in the study had no prior history of psychosis; thus they were well suited for the study of nonpsychotic schizotypic phenomenology. Moreover, the subjects of the study had not been singled out for the study of schizotypic phenomenology alone but were assessed for the full range of Axis II features as defined by the DSM-III-R. These methodological aspects of the study are important, as all too often in schizophrenia research (or psychopathology research in general), patient samples are recruited according to a prespecified narrow set of criteria. The resulting sample becomes, by definition, somewhat idiosyncratic in its nature, and results derived from the study of such patient samples will (really, must) bear the imprint of this a priori conditioning. The sample in this study was drawn so as to generate a sample that would be comparable to what one would find in many clinical settings across the country. What was found in this study of the relationships between mental state factors (such as anxiety and depression) and schizotypic features over a relatively brief period of time? The patients in this study were, of course, in a hospital or outpatient clinic receiving treatment; thus treatment effects were potentially in play, and time was passing (although relatively brief amounts in comparison with life-span research), which could allow for some

Recognizing the Schizotype

125

developmental change. In summary, Loranger et al. (1991) found that paranoid, schizotypal, and schizoid personality disorder symptoms were all associated with increased anxiety and depression. Importantly, all changed over time, but changes in mental state were unrelated to changes in Cluster A symptoms.

Issues Related to Self-­Report in the Assessment of Schizotypy The two major assessment approaches to schizotypic psychopathology are interviews and psychometric inventories. Both the interview and the psychometric inventory actually represent forms of self-­report. However, in psychological science, the term self-­report is typically reserved for the psychometric-­inventory approach, in which an individual answers a set of questionnaire items as applied to him- or herself. Such assessments can be in either paper-and-­pencil or in the more common, computerized format. Given that schizotypy interviews are time-­consuming to conduct and require highly clinically skilled staff, it is desirable to have valid self-­report measures of schizotypy. What should we consider about self-­report in general? What should we bear in mind about self-­report as it pertains specifically to schizotypic phenomena? David Funder has detailed, in The Personality Puzzle (Funder, 2007), the considerable benefits of using self-­report methodology in the assessment of individual-­difference constructs. His comments are well worth considering as we discuss the assessment and classification of schizotypic psychopathology. Funder (2007) argues that self-­report data—or self-­judgments—are highly valuable because (1) the self is the best expert; (2) they possess causal force (can make themselves come true; i.e., if you describe yourself as honest, you are more likely to behave honestly); (3) they are cost-­effective (self­report data are relatively simple and easy to collect without spending a great deal of resources in time, money, and personnel). Funder (2007) notes that self-­report data are not perfect, as they have some disadvantages: (1) Some people will not tell you things about themselves, especially if they are negatively toned; (2) some people are unable to tell you things about themselves owing to memory problems, repression, and/or lack of insight; and (3) self­report data are probably overused because it is so inexpensive and easy to collect them. The utility of self-­report data, however, in cases of quality psychometric development to ensure high reliability and validity outweighs the potential disadvantages of the approach.2 2 This

should not be taken to mean that self-­report approaches are uniformly superior to other approaches, nor should it be taken to mean that self-­report processes cannot be corrupted. As regards the latter, consider this thought experiment: You are participating in a study of mental illness/health. You know you were selected because your brother has schizophrenia, and you are asked to fill out a

126

SCHIZOTYPY VIEWED FROM THE LABORATORY

Not all psychologists, however, are enamored of the power of self-­report technologies, particularly when applied to individual-­difference constructs such as personality and/or temperament (and, by extension, to many psychopathology constructs). The Harvard developmental psychologist Jerome Kagan (1994, 2007) has a strong predilection to altogether avoid self-­report assessments of temperament and personality for, principally, five reasons: (1) There is low agreement between self-­report and observation of behavior; (2) major constructs of temperament/personality are derived from the dictionary (by implication, much is left out of such a selection of constructs); (3) he perceives an overreliance of the field on the statistical procedure known as factor analysis in the identification of major conceptual entities; (4) the list of personality/temperament constructs that are used by most researchers contains constructs that are far too broad (i.e., insufficiently differentiated to be of use in other investigations, such as neural science studies); (5) the meaning of test items probably varies considerably across people to the point that one cannot assume a given item means the same thing to all people.3 The latter concern—­whether test items mean the same thing to all individuals—has existed in the field for many years (see Meehl, 1945; cf. Jackson, 1971), and some would consider it largely unresolved, whereas others would suggest that we have made headway on this vexing problem. questionnaire that contains many highly unusual items with content ranging from bizarre perceptions, magical ideation, and referential thinking to interpersonal aversion, isolation, and diminished emotional expression. Do you think your answers to the questionnaire could be affected by the knowledge that you are of interest to the researchers owing to your brother’s illness? This is an issue of debate among schizotypy researchers (e.g., Calkins, Curtis, Grove, & Iacono, 2004). 3 Kagan

(2007) argues that because some self-­report questionnaires can be completed in a relatively brief amount of time (e.g., 1–3 hours) they are somehow less valid than “a profile of blood flow or genetic polymorphism, each requiring many hours of tedious laboratory work and each based on a rationale resting on years of prior research” (p. 369). This argument is questionable, as, for example, image acquisition in neuroimaging normally occurs within seconds, and DNA can be gathered easily (a cheek swab), profiled very quickly with modern, automated equipment, and analysis can make use of little human input. I would argue that the speed of completion for a research procedure does not bear on validity. As regards supporting theoretical rationale, much neuroimaging research remains minimally guided by substantive models (see Chapter 12, this volume), and genome-wide scans have specifically eschewed theory for a shotgun approach to detecting relations between genetic influences and constructs of interest. In contrast, theory and rational test considerations have long played a considerable role in informed test construction (Jackson, 1971). Psychometric instruments are typically in development for decades, and such development is highly technical (see Lord & Novick, 1968; Embretson & Reise, 2000). The end product represents the fruit of inputs from many individuals (e.g., MMPI) and possesses high levels of reliability and validity. The cross-site reliability of neuroimaging measurements, although promising, has yet to reach the threshold possessed by major psychometric measures and has been minimally investigated. Kagan’s concern, I believe, is not a “high speed = low validity” problem, but he, rather, expects (and I agree) that an investigation will reflect creative, well­understood, theory-­guided integration of technologies that reach across levels of analysis—­individual differences, neuroimaging, and genomic.

Recognizing the Schizotype

127

Clearly, some variability can occur in the interpretation of otherwise highly structured stimuli. The astute assessor will consider this when designing and interpreting psychopathology research. In considering the relative strengths and weaknesses of any given data collection procedure in psychological science, one must always distinguish between a simple preference for an approach and a rationally based rejection of that approach. Given the extensive corpus of validation (criterion and construct) evidence that underpins most inventories (for psychopathology as well as personality and temperament), it must be acknowledged that a rich amount of information is contained within the scores that derive from self-­report inventories. Does this mean that an investigator should rely solely on one method of data collection when attacking a problem? Of course not. Ideally, data should be collected across different levels of analysis using a variety of data collection procedures (including self-­report, observation, laboratory, and other methods). As regards special considerations in the self-­report assessment of schizotypic psychopathology, two of Funder’s concerns are constantly in play. First, many schizotypes will have little insight or capacity to recognize oddities in their appearance, thought and speech patterns, beliefs, experiences, and so on. For example, in my laboratory we have frequently worked with individuals, quite schizotypic by any measure, who had no sense or awareness that their ability to communicate was impaired (due to mild thought disorder) or that their behavior might be justifiably described as “odd” or “eccentric.” Thus the issue of insight and the capacity to recognize aspects of one’s own behavior or experience are nontrivial issues in the assessment of schizotypic psychopathology. The second concern centers on the willingness of schizotypes to tell you about their experiences, beliefs, behavior, and so on. This defensiveness, if you will, is particularly pronounced in situations in which one is studying the relatives of schizophrenia patients. In short, if a person knows that he or she is the object of study due to the fact that he or she has a schizophrenia-­affected relative, he or she may be less willing to reveal aspects of his or her behavior and experience via self-­report questionnaires or interviews owing to concerns about social desirability and the wish not to appear odd, unusual, or in any manner atypical.4 4 The

defensiveness issue in relation to the assessment of schizotypic phenomena among first-­degree relatives of schizophrenia patients remains unresolved. Recent data (Calkins et al., 2004) suggest that schizophrenia patients’ relatives may not differ substantially from controls in terms of defensiveness; however, these authors acknowledge that the scale they used to measure defensiveness (MMPI-2 K scale) may not function appropriately in the context of schizotypy assessments (as opposed to a standard MMPI assessment context).

128

SCHIZOTYPY VIEWED FROM THE LABORATORY

OK, OK, Enough Already, How Do I Assess the Schizotype?: Classification and Diagnostic Technology This section focuses on specific tools for the assessment of schizotypy and schizotypic phenomena. An evaluation of many psychometric measures conjectured to be putative schizotypy indicators that were developed before 1980 is available in Grove (1982); data bearing on psychometric measures through the early 1990s can be found in Chapman et al. (1995). Not all of the assessment devices discussed here have been designed with Meehl’s model (1962, 1990) or early effort (1964) in mind, though clearly his influence is seen in them. Some emerged from the increased interest in personality pathology that followed the introduction of DSM-III in 1980. All of the measures discussed here demonstrate strong reliability and a reasonable degree of validity.

Clinical Interviews and Checklists for Schizotypic Psychopathology Four interview-based procedures have been developed to date specifically to assess schizotypic phenomena. A competent extended review of interviews available for the assessment of schizotypy through the early 1990s can be found in Benishay and Lencz (1995); more recent reviews have not been done in this area. In this context it is noted that the following assessment devices are tailored specifically for the schizotypic psychopathology. One could, of course, use the relevant diagnostic modules for SPD and/or PPD from an established Axis II structured interview (e.g., IPDE; Loranger, 1999) as an alternative to these specialized instruments.

Meehl’s Checklist for Schizotypic Signs Meehl’s (1964) Checklist for Schizotypic Signs is a treasure trove of clinical observation and phenomenological description for schizotypic psychopathology. The checklist and the complete Manual for Use with the Checklist for Schizotypic Signs can be downloaded from Meehl’s website (www.tc.umn. edu/~pemeehl/pubs.htm). The checklist, along with Meehl’s personal armchair weights for the individual checklist items, are contained in Appendix A in this volume. Consisting of 25 clinical features that Meehl argued were of diagnostic importance to the recognition and diagnosis of schizotypic features, it represents, arguably, the first genuine attempt to bring a structured diagnostic approach to the assessment and classification of schizo-

Recognizing the Schizotype

129

typic phenomenology. Although rarely used in actual research practice, the Manual and Checklist are worthy of careful study, as they contain a considerable wealth of clinical wisdom (as well as potential research ideas).

Symptom Schedule for the Diagnosis of Borderline Schizophrenia The Symptom Schedule for the Diagnosis of Borderline Schizophrenia (SSDBS), developed by Khouri, Haier, Rieder, and Rosenthal (1980), assesses the symptoms of “borderline schizophrenia” as defined by Kety, Rosenthal, Wender, and Schulsinger (1968). The schedule is administered in an interview format, with eight symptoms rated on a 3-point scale (0 = no evidence, 1 = some evidence, 2 = clear evidence), including perceptual changes, body image aberrations, feelings of unreality, thought disturbances, ideas of reference, ideas of persecution, self-­inflicted injuries, and preoccupation with perverse sexuality or violence. Interrater reliability for total scores was .83. Total scores of 2 or above appeared to accurately identify those individuals originally diagnosed with “borderline schizophrenia” in the Danish Adoption Study sample (Khouri et al., 1980). The diagnostic criteria for “borderline schizophrenia” in the SSDBS hail from the “clinical tradition” (cf., Kendler, 1985).

Schedule for Schizotypal Personalities Developed by Baron and associates (Baron, Asnis, & Gruen, 1981), the Schedule for Schizotypal Personalities (SSP) was designed to assess the diagnostic criteria for DSM-III SPD. The SSP assesses illusions, depersonalization/derealization, ideas of reference, suspiciousness, magical thinking, inadequate rapport, odd communication, social isolation, and social anxiety. The SSP also assesses delusions and hallucinations. Baron et al. (1981) report excellent interrater and test–­rerest reliabilities for the SSP scales. The kappa coefficient for the diagnosis of SPD using the SSP was .88.

Structured Interview for Schizotypy Kendler and colleagues (Kendler, Lieberman, & Walsh, 1989) developed the Structured Interview for Schizotypy (SIS) to assess schizotypal signs and symptoms. The SIS consists of 19 sections, 18 to assess individual symptom dimensions and 1 to assess 36 separate schizotypal signs (Kendler et al., 1989). For example, the SIS includes social isolation, interpersonal sensitivity, social anxiety, ideas of reference, suspiciousness, and other

130

SCHIZOTYPY VIEWED FROM THE LABORATORY

schizotypal features. The SIS is intended to be given in conjunction with an Axis I assessment device. The interrater reliabilities associated with various aspects of the SIS are generally acceptable, with intraclass correlation coefficients typically above .70. Preliminary data based on the study of nonpsychotic relatives of schizophrenic patients support the criterion validity of the SIS as a measure of schizotypy (see Kendler et al., 1989). Results from the Roscommon Family Study of schizophrenia (Kendler et al., 1993) provided additional validation of the SIS. The SIS assesses a broader range of schizotypic signs than the SSP, going considerably beyond DSM schizotypal personality disorder and including some aspects of Meehl’s construct of schizotypy. The SIS is clearly one of the most heavily used interview methodologies for the assessment of schizotypic features, probably representing the specialized interview of choice for research work today. A revised version of the SIS incorporates a number of methodological improvements over the original and also displays commendable psychometric properties (Vollema & Ormel, 2000).

Self-­Report Psychometric Inventories for Schizotypy Detection Chapman Psychosis Proneness Scales Guided by Meehl’s model of schizotypy and his clinical descriptions of schizotypic signs (Meehl, 1964), Chapman and Chapman (1985, 1987) developed several objective self-­report measures to assess traits reflective of a putative liability to psychosis, perhaps schizophrenia. Reviews of the early literature on these measures (Chapman et al., 1995; Edell, 1995) supported their reliability and validity. Two of these scales, the Perceptual Aberration Scale (PAS; Chapman, Chapman, & Raulin, 1978) and the Magical Ideation Scale (MIS; Eckblad & Chapman, 1983), have been used extensively in research to detect schizotypy and assemble samples of subjects presumed to be at increased risk for schizophrenia-­related psychosis from nonclinical populations. All of the Chapmans’ psychosis proneness scales have been carefully constructed from the psychometric standpoint to minimize correlations with social desirability and acquiescence factors while ensuring internal consistency, content validity, and construct validity. The PAS is a 35-item true–false measure of disturbances and distortions in perceptions of the body, as well as other objects. It includes such items as “Occasionally I have felt as though my body did not exist” (keyed “true”) and “I have never felt that my arms or legs have momentarily grown in size” (keyed “false”). Internal-­consistency

Recognizing the Schizotype

131

analyses typically reveal coefficient alphas around .90, with short-term test–­ retest stability of.75 (Chapman & Chapman, 1985). Regarding the MIS, Chapman and Chapman (1985) defined magical ideation as “a belief in forms of causation [italics added] that, by conventional standards of our society, are not valid but magical” (p. 164). The MIS includes items such as “I think I could learn to read other people’s minds if I wanted to” (keyed “true” and “At times I perform certain little rituals to ward off negative influences” (keyed “true”). Coefficient alphas run typically between .80 and .85. The PAS and MIS tend to be highly correlated (r’s at .68–.70). As a result both measures are often used in conjunction to select schizotypic subjects from nonclinical populations. The PAS and MIS have been used extensively in schizotypy research, and they are associated with an impressive body of empirical literature supportive of their validity. A third scale developed by the Chapmans, the Revised Social Anhedonia Scale (RSAS; Mishlove & Chapman, 1985), has also been used with greater frequency since deviance on the scale was linked to later psychosis in the presence of elevated PAS/MIS scores (Chapman, Chapman, Kwapil, Eckblad, & Zinser, 1994). Recent work by Kwapil, Barrantes-Vidal, and Silva (2008) provides compelling evidence in support of the construct validity of the scales developed by the Chapmans. The extent to which the RSAS assesses “anhedonia” versus “social withdrawal” has become a focus of recent substantive discussion and empirical investigation (Linscott, 2007). Additional issues concerning the assessment of anhedonia—­especially as regards the distinction between anhedonia on the one hand and disorganization and mood symptoms, as well as neurocognitive deficits, on the other—have been considered by Horan, Kring, and Blanchard (2006).

Schizotypal Personality Questionnaire The Schizotypal Personality Questionnaire (SPQ; Raine, 1991) is a 74 itemtrue–false self-­report questionnaire that assesses the features consistent with the symptoms for schizotypal personality disorder as defined by the DSM-III-R (American Psychiatric Assocation, 1987). The SPQ has excellent psychometric properties (Raine, 1991). The SPQ can also generate three general factors that correspond conceptually to the reality-­distortion, disorganization, and negative-­symptom components that are well known in the schizophrenia research literature (Lenzenweger & Dworkin, 1996). The SPQ has become one of the most heavily used psychometric assessment methods in the schizotypy/schizotypal personality research area. A current overview, as well as a bibliography of those studies supporting the reliabil-

132

SCHIZOTYPY VIEWED FROM THE LABORATORY

ity and validity of the SPQ, can be found at Raine’s website (www-rcf.usc. edu/~raine/).

Other Psychometric Measures of Schizotypy Several additional psychometric measures of schizotypy have been developed recently and should be mentioned. Unlike the PAS and MIS, these other measures have not yet been shown to be associated with a liability for schizophrenia (i.e., schizotypy) through systematic family, twin, or adoption studies. However, available validity data suggest that all are promising as schizotypy indicators. These measures include the Rust Inventory of Schizotypal Cognitions (RISC; Rust, 1988a, 1988b); the Referential Thinking Scale (Lenzenweger, Bennett, & Lilenfeld, 1997); the Social Fear Scale (Raulin & Wee, 1984); the Schizotypal Ambivalence Scale (SAS; Kwapil, Mann, & Raulin, 2002); the Schizotypal Personality Scale (STA; Claridge & Broks, 1984); the Schizophrenism Scale (Venables, 1990) and the schizoid, schizotypal, and paranoid personality disorder scales derived from the Minnesota Multiphasic Personality Inventory (MMPI; Morey, Waugh, & Blashfield, 1985). Finally, Harkness, McNulty, and Ben-­Porath (1995) have developed a five-scale dimensional system (the Personality Pathology Five; PSY-5), derived from MMPI-2 items, that can be used to describe personality and its disorders. One of the PSY-5 scales assesses psychoticism, a higher order construct of general relevance to schizotypy. Of these scales, Lenzenweger et al.’s (1997) Referential Thinking Scale, Kwapil et al.’s (2002) Schizotypal Ambivalence Scale, and Raulin and Wee’s (1984) Social Fear Scale were designed specifically to assess aspects of Meehl’s schizotypy construct. Finally, a promising new psychometric measure of schizophrenia liability is the Schizophrenia Proneness Scale (Bolinskey, Gottesman, & Nichols, 2003).

The Challenge of Heterogeneity: How Come My Schizotypic Subjects Are Not All the Same? In this context of description and assessment methodologies for schizotypy, one must ask a difficult question. Given all of these ways of detecting schizotypic psychopathology, is it the case that the unit of analysis we refer to as the schizotype is characterized by high levels of homogeneity? Simply stated, do all schizotypes look alike in terms of sign and symptoms (i.e., phenomenology)? No, they do not. Do all schizotypes perform similarly on

Recognizing the Schizotype

133

experimental psychopathology laboratory tasks? No, they do not. Do all schizotypes proceed through time in a similar manner such that they all share what would be termed a common growth trajectory or path? No, they do not. Are all cases of what we would identify as schizotypic personality or psychopathology caused by the same underlying processes and genetic influences? This is unknown at present and represents a conundrum for both schizophrenia proper and schizotypic psychopathology. We face considerable heterogeneity among the group of individuals we would designate as schizotypes, not unlike what we are faced with in the case of schizophrenia. Let us consider four types of heterogeneity: clinical, performance, etiological, and growth trajectory. Furthermore, let us ground this discussion in schizophrenia and, by analogy, extend the argument to the schizotype. Clinical heterogeneity refers to the large and diverse set of symptoms and other features commonly encountered in schizophrenia and detected, with varying degrees of overlap, from one case to the next. Performance heterogeneity refers to the reality that not all schizophrenia patients are deviant on all experimental measures used in the psychopathology laboratory. Etiological heterogeneity, which is dealt with in great detail in Chapter 7 in this volume, refers to the proposal that multiple etiologies can create these schizophrenia features. Although we do not know that there is etiological heterogeneity, it is widely presumed to be present. Finally, heterogeneity in growth (or change) of schizophrenia symptoms has long been known to exist. Simply stated, there is no one symptom pattern followed over time by all people with schizophrenia. The same is probably true for schizotypic features—there is no one path to follow through time. It is important to note that clinical, performance, and growth heterogeneity do not necessarily imply etiological heterogeneity, but such an implication is certainly plausible.

Heterogeneity in Clinical Presentation/Phenomenology Schizophrenia has long been characterized by considerable heterogeneity in its clinical presentation (Bleuler, 1911/1950; Kraepelin, 1919/1971). Indeed, Bleuler referred to the “group of schizophrenias,” and this heterogeneity has been a major source of frustration for schizophrenia researchers. It is well known that heterogeneity exists in all aspects of the illness, including symptoms, cognitive and behavioral dysfunctions, age of onset and type of illness, longitudinal course, and long-term outcome. Attempts to resolve this heterogeneity have usually taken the form of clinical subtyping approaches or multidimensional conceptualizations that seek to identify

134

SCHIZOTYPY VIEWED FROM THE LABORATORY

either homogeneous subgroups of patients or homogeneous dimensions of phenomenology or other characteristics (see Andreasen et al., 1995, and Neale & Oltmanns, 1980, for reviews of this extensive literature). For example, DSM-IV (American Psychiatric Association, 1994), like prior systems, classifies clinical subtypes (i.e., disorganized, paranoid, catatonic, and undifferentiated), even though these subtypes can be arbitrary and unstable over time within individuals (Andreasen et al., 1995). An empirical approach to the heterogeneity of schizophrenia phenomenology, based on confirmatory factor-­analytic results, organized the symptoms into four major dimensions—­namely, negative, disorganized, reality distortion, and premorbid social functioning (Lenzenweger & Dworkin, 1996). Nonetheless, echoing Gottesman’s (1987) trenchant analysis, aspiring cartographers of the heterogeneous phenomenological terrain of schizophrenia have been frustrated by this aspect of the disease for nearly 100 years. No one approach has emerged that can adequately describe the heterogeneity in schizophrenia phenomenology. However, contemporary discussions suggest that reality distortion, disorganization, negative symptoms, and deficits in premorbid adjustment reflect dimensions that capture much of the schizophrenic phenomenological landscape.

Heterogeneity in Performance on Laboratory Tasks Investigations of the experimental psychopathology of schizotypic psychopathology and schizophrenia have similarly encountered the effects of heterogeneity. This reality has forced many researchers to focus on the development of statistical or methodological strategies for dealing with heterogeneity (e.g., Chapman & Chapman, 1977, 1989). For example, there are some well-­established laboratory findings about the illness (e.g., eye-­tracking dysfunction; Levy, Holzman, Matthysse, & Mendall, 1993; and deficits in sustained attention; Cornblatt & Keilp, 1994), but not all schizophrenia patients show deviance on any given index. Similarly, as discussed earlier, most schizotypes do not display more than one of these deficits. The net effect of heterogeneity on any investigation of schizotypy or schizophrenia is increased “noise” and obscured “signal.” How are we to surmount clinical and performance heterogeneity? Although heterogeneity has long been observed and taken as a reality characteristic of the symptoms, as well as the laboratory task performance patterns, of those affected with the illness, there is also an underlying presumption that there must be some core illness patterns or sets of performance features that would uniquely demarcate relatively distinct groups of persons

Recognizing the Schizotype

135

who have the illness, perhaps reflective of different variants of schizophrenia. It is also hoped that at some point, with the aid of proper statistical techniques, reliable and valid subgroups (or natural classes) of individuals might be detected within the group of individuals who are affected by schizophrenia (or who have increased schizophrenia liability).

Heterogeneity in Etiology To what extent is schizophrenia caused by a common set of genetic influences? To what extent is schizophrenia caused by a common gene of large effect? To what extent can we assume that all forms of schizophrenia have a common underlying etiology? This issue is explored in greater depth in Chapter 7 (this volume), and thus we defer consideration of this thorny issue until then. Suffice it to say that the likelihood of heterogeneity in etiology for schizophrenia (and schizotypy) is nontrivial given the pattern of emerging findings in contemporary genetic research. However, this is a more complex issue than meets the eye. This is so because heterogeneity in potential etiology demands that we come to grips with the possibility that we are really faced with a group of similar-­appearing illnesses—maybe Bleuler’s “group of schizophrenias” after all—and that the meaning of heterogeneity itself would need to be reconsidered (i.e., if there is no one unitary illness known as schizophrenia).

Heterogeneity in Growth Many years ago the Harvard experimental psychologist William Estes made a very simple but profoundly important methodological point regarding group data in research (Estes, 1956). The averaged group curve for a set of subjects for some variable of interest does not determine the shape of the individual curves within the set. Despite the intuitive appeal of the notion that the profile obtained by a group of subjects across a set of variables may indeed represent an average or mean profile for the group as a whole, one cannot assume that the group profile is fungible with individual profiles. This bears repeating here. In other words, one cannot assume that the individual subjects within a group of subjects will show comparable patterns of performance across a set of measures, nor will all subjects mirror the profile obtained for the group data. This thinking can be extended easily to a consideration by which a person is measured on the same variable or dimension at different points in time (e.g., across the life course). When multiple subjects are followed over time, with each measured on the same variable or

136

SCHIZOTYPY VIEWED FROM THE LABORATORY

dimension on the same assessment schedule, it is safe to assume that there will be heterogeneity in growth or change on the variable of interest across subjects. Furthermore, the mean pattern of change across the dimension or variable of interest for the group will not necessarily apply to the individuals making up the group. In other words, Estes (1956) made us aware that one should not mistake averaged group data for individual data. How does this issue of “heterogeneity of growth” become relevant to our understanding of schizotypy? It does so by virtue of the fact that we as psychopathologists should assume that heterogeneity in growth, change, or profile will be the order of the day. An illustration of just this sort of thing can be found in Figure 5.1. In this figure we see the dependent variable Cluster A “schizotypic” personality disorder features assessed over time across 250 different subjects. Each line in the graph represents a person. Each person’s line has an origin (an intercept or initial level at time 0, or 30.00

Cluster APD

20.00

10.00

0.00

0.00

1.00

2.00 Time (yrs)

3.00

4.00

FIGURE 5.1.  Individual growth trajectories for DSM-III-R Cluster A personality disorder features in the 250 subjects from the Longitudinal Study of Personality disorders during the 4-year study period. Time is reported in years since the start of the study. See also Chapter 10, this volume.

Recognizing the Schizotype

137

the beginning of the study) and a rate of change (or slope) over time. It is very easily seen that some subjects start out the study low on Cluster A symptoms and gradually increase; others show the opposite pattern, with high initial levels followed by declines; some show little change at all or everything in between. The point derived from this depiction of what are termed individual growth curves (Lenzenweger, Johnson, & Willett, 2004; see Singer & Willet, 2003) is simple—there is considerable interindividual variation in patterns of growth or change over time. There is no one trajectory that fits all subjects. The mean or average trajectory could not be assumed to be appropriate for all individual subjects. The bottom line is that heterogeneity in growth is yet another form of variation in our data that we must be attuned to and comfortable with and make the focus of investigation.

Heterogeneity Resulting from Subject Sampling Methods: Where You Get Your Subjects Does Matter Perhaps one of the most important issues that we are faced with when undertaking research on schizotypy concerns where we gather a subject sample from and how we do it. Finding schizotypes is difficult; we are looking for a relatively low-base (i.e., infrequent) phenomenon, and, in this case, the phenomenon one is searching for often has little or no interest in interacting with people. The research situation (although easy to forget sometimes) is very much a social situation, whether one is being interviewed, tested on a computer-based cognitive science task, giving a cheek swab for DNA analysis, or being placed in the magnet for a neuroimaging study. Thus where you find or select your schizotypic subjects matters. In our work on nonpsychotic individuals who have clear-cut schizotypic features, we have often relied on an epidemiological approach to finding such persons. We have often begun with a finite list of persons who were eligible for study within a given population. We approach each of them individually, assess them for schizotypy using psychometric methods, and then draw our subjects from this pool. The advantage of this approach has been that we could generate our response rate and could determine to what extent our sampling had been representative for the population in question. Moreover, we did not gather subjects for a pool of persons who knew that they were being approached because, for example, they have a relative with schizophrenia. Unfortunately, many research contexts cannot pursue subjects in the manner in which we have done.

138

SCHIZOTYPY VIEWED FROM THE LABORATORY

Does the method of subject selection really matter in terms of symptoms, features, and other aspects of psychological function (or dysfunction)? Consider the family approach to assembling schizotypic subjects. The relatives of schizophrenia-­affected patients are often solicited, directly or indirectly (through bulletin boards), for inclusion in research on schizotypy. What could be some of the factors influencing a person to sign up for a study in such circumstances? Consider the laboratory/psychometric approach to identifying potential schizotypes in large mass screenings of students in college and university settings. Students are often invited to participate in mass screenings using psychometric instruments. What self-­selection is operative there? What if the mass screening is a “requirement” for a course? How will that affect the nature of the data collected? What is it like for students to read through a list of schizotypic behaviors and features and identify these within themselves while surrounded by an army of peers in a lecture hall? Any experienced psychology professor will tell you of the students who run quickly through questionnaires—­answering “true” or “false” quasi­randomly—only to finish the task, satisfy the course requirement, or collect some extra-­credit points. Finally, of course, consider the clinical approach to finding schizotypic subjects. Schizotypic subjects might be gleaned from patient populations simply because they happen to be in the hospital or attending a clinic. Are these representative schizotypes? Consider the issues raised earlier that might be responsible for leading a schizotypic subject into treatment or an evaluation. Consider clinical subjects gathered from highly distinctive clinical settings, such as the Veterans Administration medical system, versus public hospital systems versus private hospital systems. In schizotypy research, on occasion, one has the impression that some study groups have a stable of schizotypes whom they call on whenever a new study is initiated.5 One can only imagine what factors might be at play in the maintenance of a stable of schizotypic subjects. One of the biggest decisions in schizotypy research concerns whether to select one’s subjects from clinical or community settings. Based on impressions I have gleaned over the years in reviewing dozens and dozens of manuscripts concerning schizotypy research, many investigators seem to believe 5 This

state of affairs is troubling, as it suggests that the corpus of empirical findings generated by a laboratory that uses such an approach is, at its base, highly idiosyncratic. That is, if the same (let’s say) 15–30 schizotypes are used routinely in studies over the years, one is left with the potential artifacts associated with such a highly compliant, “on-­payroll” group of subjects, and the generalizability of the findings derived from different studies that repeatedly use the same subjects is greatly diminished. My advice to students is that, if one does not have the time to collect data, including ascertainment of fresh subject groups, correctly, then one should find something else to do.

Recognizing the Schizotype

139

that it does not matter where the subjects come from. I am convinced this is not true—that is, it does indeed matter where subjects come from, and the clinical-­versus-community source issue is nontrivial.6 To illustrate this point, let us consider an example from a different research venue. Consider the issue of sampling borderline personality disorder (BPD). Many researchers want to conduct a variety of laboratory investigations on BPD; however, such subjects are notoriously difficult to recruit for studies and, more to the point, difficult to process through research protocols. BPD patients can be found in clinical settings (Zimmerman et al., 2005), obviously, as well as in the community (Lenzenweger, Lane, Loranger, & Kessler, 2007; Lenzenweger, 2008). Thus one sees studies of BPD using subjects gathered from both clinical and community samples, and the question arises, Are the BPD patients from the two different venues essentially the same? Holding aside, for the moment, the vexing question of heterogeneity in BPD (see Lenzenweger, Clarkin, Yeomans, Kernberg, & Levy, 2008), let us consider the phenomenology of BPD patients recruited through different source streams (Korfine & Hooley, 2009). In short, what Korfine and Hooley (2009) addressed was the presence of absence of reliable differences in phenomenology across patients with BPD recruited for a cognitive neuroscience study from clinical and community sources. An implicit assumption in research is that the use of a diagnostic rubric that is reliable (and presumably valid) helps to create a unit of analysis that facilitates (1) research communication among scientists, (2) clinical communication among practitioners, and (3) development of treatment innovations. There are good reasons to believe these goals are largely achieved with many modern diagnostic constructs (at least, insofar as compared with earlier diagnostic approaches, e.g., DSM-II (American Psychiatric Assocation, 1968). However, just how similar or different are borderline subjects across settings, when diagnosed using a rigorous and conservative structured interview (IPDE)? In short, Korfine and Hooley (2009) reported that in a comparison of 22 hospitalized and 23 community­dwelling subjects with BPD, the hospital patients displayed a significantly 6 The

source of the subjects matters. However, there is a deeper issue at play here. If a person in the community is living his or her life in a manner with which he or she is content, is it acceptable to view him or her as evidencing psychopathology, even if the person does not see him- or herself as ill? The epidemiologist in us would say, of course, the person meets the criteria for illness. However, does it make sense to consider a person as ill even if he or she is not distressed by his or her life circumstances, interpersonal aversion, and so on? From the standpoint of research, we would likely view such individuals as potentially informative, and we would want them in our study; however, as clinicians, would we view them in the same manner as we regard individuals who come to the clinic?

140

SCHIZOTYPY VIEWED FROM THE LABORATORY

different profile of BPD symptoms.7 For example, the community subjects with BPD displayed lower levels of self-­mutilation, emptiness feelings, and dissociation but greater amounts of anger and unstable interpersonal relations as contrasted with the patient subjects with BPD. These symptom profile differences were such that the actual “shape” of the two mean profiles was notably different across the two groups of BPD subjects. Such a profile or shape difference can be taken as evidence suggestive of meaningful typological differences across two groups (see Lenzenweger, 1991). Korfine and Hooley (2009) noted the potential implications of such differences in BPD patients from different sources for neuroimaging and other important experimental psychopathology studies. Clearly, not all subjects who carry the same diagnostic classification are similar enough to justify uniformly regarding them as essentially interchangeable across sampling streams. The same is true for schizophrenia and schizotypy research. Finally, any consideration of the effects of subject sampling on heterogeneity would be incomplete without also mentioning the distinct possibility that heterogeneity can come to characterize research samples via another pathway as well. What could this pathway be? The manner in which normal control subjects are selected is the pathway. Normal control subjects can be selected in a fashion that either reduces or enhances heterogeneity within a sample, and the degree of heterogeneity can affect the emergence or absence of significant differences between experimental and control groups. This important point was elegantly demonstrated in a classic paper by Smith and Iacono (1986). They demonstrated that whether or not significant differences emerged in comparisons of computed tomography (CT) brain scans of schizophrenia-­affected persons and normal controls had more to do with the manner in which the normal controls were selected than with schizophrenia per se. Different selection criteria for normals across different studies yielded appreciable differences in heterogeneity across the CT measures, and these latter differences affected the group comparisons rather strikingly. Research moral: The manner in which all study subjects are selected matters.

7 Korfine

and Hooley (2009) also found that the clinical sample showed a somewhat more severe expression of BPD, somewhat greater Axis I comorbidity, and more medication and prior hospitalization than the community sample. However, on other clinical dimensions (e.g., depression, anxiety, dissociation, negative affect), the two BPD groups were quite similar.

Chapter 6

Begin with a Model

Research and clinical explorations of schizotypic psychopathology have ranged from atheoretical phenomenological observation to complex psychodynamic approaches. For example, Kraepelin and Bleuler are exemplars of the atheoretical phenomenological observation mode. These early observers of schizophrenia and schizotypic psychopathology were gifted in noticing and describing many aspects of the illness, both in schizophrenia patients and in their relatives. These observers were primarily interested in description and articulation of the phenomenology observed. Neither Kraepelin nor Bleuler presented a comprehensive theory or model of the pathogenesis and development of schizophrenia and schizotypic psychopathology, although Bleuler clearly made some strides in that direction. Thus these early observers of schizotypic psychopathology were generally not guided by an explicit model of etiology and development but provided rich descriptions. Some years later, after the development of psychoanalytic theory and therapy by Freud and his followers, many observers within the clinical/office practice tradition grounded their observations of schizophrenia and schizotypic psychopathology in rather complex psychoanalytical models. Such observers included Harry Stack Sullivan, Harry Guntrip, Gregory Zilborg, Sandor Rado, and others. These psychodynamic models were more akin to what one might think of as conceptual models; however, such psychodynamic models did not have the characteristics of a formal model that

141

142

SCHIZOTYPY VIEWED FROM THE LABORATORY

might be found in, for example, physics or chemistry.1 Unfortunately, those working within a psychodynamic tradition were burdened by a nonspecific model of etiology and development of psychopathology that proved essentially impossible to validate and, in retrospect, accorded far too much importance to psychosocial inputs in the determination of schizophrenia and related pathologies. The psychodynamic model/approach, as applied to the psychotic states, remained an essentially psychosocial model of etiology and development (e.g., that dysfunctional relations between parents and children caused schizophrenia). Concepts such as marital schism/marital skew, communication deviance, schizophrenogenic mothers, and the double bind were all representative of—now debunked—­socialization models with a psychodynamic heritage to one degree or another.2

Models and Operational Definitions: What They Are and Why They Are Useful Models and Theory The word model has been used already several times in this chapter, and it would be useful to take a moment to consider this term.3 Most scholars distinguish between a “model” and a “theory.” This distinction is typically such that a model might have a more limited explanatory purview or seek to describe the nature and workings of a more circumscribed process or phenomenon. For example, one might advance a model of sustained attention 1 Freud

often described the clinical insights that led to his understanding of his patients and how this understanding might give rise to more general theoretical principles for understanding human behavior. This form of thinking and theory has been referred to as “clinical theory.” For reasons not entirely clear but perhaps related to his desire to be accepted in the physicalistic and mechanistic science circles of his day, Freud also developed “metapsychological theory” in parallel with his clinical theory. Metapsychology sought to account for “how” he thought the mind worked (emphasizing principles related to thermodynamics, energy transfer, and so on). His clinical observations, by and large, have stood the test of time, whereas his metapsychological constructions, typically the focus of debunking research efforts, are viewed as unnecessary for understanding human development, behavior, and psychopathology. See George Klein’s (1976) masterwork on this topic.

2 It

may surprise the contemporary student to learn that there were ardent supporters of such socialization models of schizophrenia and schizotypy even into the 1980s. These views were not limited to the 1940s and 1950s. For example, the Yale psychiatrist Theodore Lidz remained energetically committed to a socialization science model of etiology for schizophrenia as of 1990 (Lidz, Blatt, & Cook, 1981; Lidz, 1990) even as the genetic corpus in schizophrenia research accrued and the evidence for genetic influences in the disorder became established fact.

3 I thank William M. Grove, Steven Matthysse, and Paul E. Meehl for useful comments on the “model” concept.



Begin with a Model

143

performance in conditions of great stress and seek to articulate the component parts and mechanisms of the system needed to render this psychological phenomenon amenable to research. This model would have a more limited scope than a theory of all forms of attention in human performance. One might also think of a model as a concrete (tangible) representation of a theoretical proposition. For example, consider a small-scale engineering model meant to be a tangible representation of water movements during tidal flows. Or, more relevant, consider that one might theorize that stereotypic motor behavior might result from excessive dopamine activity. In this instance one might model this by the study of stereotypic behavior in a rat in which one has augmented the dopamine system. Thus in both examples we have a concrete representation of a theoretical proposition. But what about the term model in psychopathology and psychology? Explication of the term model in psychological science is a bit more challenging than it would be in, say, physics or engineering. In the latter disciplines, one might actually build a small-scale physical device or system that is thought of as analogous to the real system. For example, one could model an earthquake, a tornado, or electrons swirling about a nucleus of protons and neutrons. In this type of situation, you might cut your model down to bare basics so as to concern yourself only with the most fundamental aspects of your problem. You might want to model the functioning of the human knee, and you create a model to do so. However, you may not build your model of the knee in such a manner as to be able to accommodate all possible human activity that would involve movement of the knee (e.g., jogging, alpine skiing, swimming, dancing). One might just focus on basic locomotion—­walking—in the model setup. Models such as we have discussed seem pretty straightforward. One could then move on to the purview of physicists, astronomers, and astrophysicists, and the nature of models begins to change. The change that is most evident is, again, that the effort in modeling might be directed at a circumscribed problem, but the model will be formulated largely in mathematical terms, equations, and so on. This is still a model in that it serves as a mock-up of the real thing—one might model the movement of planetary bodies and do so largely in mathematical terms. However, let us move from the realm of mathematical equations that might describe Newtonian phenomena or even nuclear events to the world of the statistical model. Here we would not be much concerned with the use of the term statistical model embodied in such distinctions as “the logistic model,” “a Poisson model,” and so on. By statistical model, what I have in mind is the use of probability relations to describe potential connections or associations among psy-

144

SCHIZOTYPY VIEWED FROM THE LABORATORY

chological and/or behavioral constructs of interest. Thus we might model “truth telling” behavior in children as a function of potential rewards and the likelihood of being caught telling a lie. Here the term model suggests a statistical construction. The statistical model is a descriptive framework, which does not address causality. When the concept of causality comes into play in scientific psychological thinking, the term model morphs yet again dramatically. By this I mean that for many psychologists the term model in this instance implies causal modeling, or what is termed structural equation modeling (SEM).4 In SEM one seeks to construct a series of regression equations that specify hypothetical relations among observed (fallible) measurements of psychological or behavioral phenomena and unobserved latent variables in an effort to explain an outcome or dependent variable (DV) of interest. Within the SEM approach, one makes explicit the assumptions about what variables dictate or influence change in other variables in the “model.” The structural model is then “fit” to observed data using the methods of SEM, and one basically seeks to find a model that fits (according to statistical criteria) the observed data well. This is where things become very slippery indeed. First, there is no reason to believe the structural model specified by the investigator actually maps truth. Second, fitting a model to observed data in the interest of minimizing a likelihood function does not really address the issue of causality. This so as all of the relations in the setup are correlational by definition. Third, one can tinker with SEM models until the cows come home in search of a better fit to the observed data and thereby follow statistical paths to good fit that are not compelling. Finally, the quality of data and level of artifact due to flawed measurement attending the values put into a structural equation setup is frequently overlooked in the interest of model fitting.5 Thus the term model is a rather plastic concept. However, for the purposes of this exposition, we should think of a model as creating a conceptual specification of the core constructs in play. Whether one can actually take these constructs and make real-world models of them (whether mechani4 A

rigorous, high-­quality introduction to the methodology of SEM can be found in Bollen (1989). It is important to note that Bollen and others present the mathematics of SEM, but one must distinguish between the mathematical underpinnings of the SEM approach and how some users of the method interpret the results of the approach. See also the seminal discussion of path analysis by Waller and Meehl (2002). 5 Mindful

that one can rarely, if ever, collect near-­perfect data in psychological science, one must keep the dictum “garbage in, garbage out” in mind when contemplating the complex analysis of behavioral and psychological data. The SEM program is completely agnostic regarding the quality data used (aside from basic conditioning concerns).



Begin with a Model

145

cal, physical, computer-based [e.g., connectionist6], or other) represents a research challenge. For schizotypy, the term model would mean the specification of the primary components involved in the etiology and pathogenesis of schizophrenia liability. Such a model should make an effort to specify the nature and direction of causal effects and, ideally, yield testable and refutable conjectures. Many of these conjectures will be testable in statistical form only in humans, although some might translate into behavioral neuroscience protocols (e.g., consider the rat, dopamine, and stereotypic behaviors).

On “Operational” Definitions I would not be surprised to learn that many readers of this book have heard, been told, or even taught that, for example, the DSM contains “operational definitions” of psychopathology. Professor So-and-so begins his talk, “The DSM-IV-TR provides an operational definition for schizophrenia.” This is simply not true. The DSM does not contain operational definitions of mental disorders; rather, it contains explicit delineation of the signs and symptoms that constitute the diagnostic criteria of the disorders, and it specifies how many criteria are required to be met to receive a diagnosis for a disorder. The DSM does not tell one how to go about diagnosing a disorder; it does not provide a list of operations to be followed to generate a diagnosis, nor does it specify the operations by which signs and symptoms are related to a disorder construct. The term operational came to psychology in the 1930s and 1940s from physics through the work of the Harvard physicist and Nobel laureate Percy W. Bridgman.7 Remembering he was a physicist, Bridgman (1927) noted, “the concept is synonymous with the corresponding set of operations” (p. 5, italics in original). The idea of an operational definition 6 Especially popular in the early 1990s, connectionist models attempt to model neural network activity by evaluating different numeric activation values spread over hypothetical neural units in a network. This type of modeling is essentially another form of quantitative modeling of psychological processes. 7 Sigmund

Koch (1992) claims that psychology has very nearly completely misunderstood Bridgman’s ideas. He argues that psychology latched onto merely a phrase—“operational definition”—to put to use for its own purposes and, while doing so, failed to comprehend most of what Bridgman really meant. See also Green (1992, 2001) for a similar position, in which he notes “Furthermore, ‘operationism’—as developed by psychologists in the 1930s and 1940s—was based on a misunderstanding of Bridgman’s intent from the outset.” Hardcastle (1995), on the other hand, sees those espousing operationism in psychology (notably S. S. Stevens) as trying to help establish and bring order to the emerging laboratory science of psychology. He suggests that Stevens sought to establish a climate in which to increase precision, validity, and rigor of both theory and experimentation in psychology (cf. Ribes-Iñesta, 2003).

146

SCHIZOTYPY VIEWED FROM THE LABORATORY

was imported into psychology by people such as S. S. Stevens (1935, 1939) and Boring (1935). It is rather straightforward—­namely, the specification of highly detailed and, presumably, quantified relations between carefully and precisely described concepts, typically behavior. For Stevens the meaning of concepts depended on the specific, concrete operations that determined the concept (see Stevens, 1935), and this effort toward operationism represented both a philosophy of science and a methodological attitude that valued precision and objectivity (Hardcastle, 1995; Ribes-Iñesta, 2003). Interestingly, many philosophers of science and psychologists have rejected Bridgman’s ideas as unworkable for most complex problems, such as those encountered in psychology. To some extent, even the ideas of Stevens have been questioned as to their relevance to complex problems. However, the attitude toward precision, careful description, and articulation of precise relationships among variables espoused within Stevens’s philosophy of the laboratory live on. That said, for the most part, in psychopathology (as in most of all other areas of psychology) we do not have Bridgman-­approved operational definitions for the phenomena and processes under consideration (but, somehow, textbook writers in psychology and psychiatry sure like the term operational definition!).

Latent Constructs in Models of Psychopathology: On Risk, Liability, Vulnerability, and Susceptibility In psychopathology research, the language used to describe what it is that we are interested in studying can be imprecise and confusing (and confused) once we move beyond a discussion of signs and symptoms (and perhaps psychometric values from well-­validated instruments). This confusion can creep in around the terms we seek to use to describe latent hypothetical constructs related to risk, vulnerability, liability, and susceptibility. Some may dismiss the possibility of any substantive differences between these terms and regard them as largely synonymous. Surely, one can take that position; however, it strikes me that some valuable meanings can be lost by clumping the terms together. Thus it makes sense to take some time to clarify what is meant by certain terms. The term liability is, as the reader has probably noticed, the term I prefer when discussing the hypothetical latent construct of schizotypy. Specifically, schizotypy is taken to mean the latent liability for schizophrenia (schizotypy does not refer to phenotypic level indicators). The term liability tends to be associated with genetics, and liability is often thought of as an



Begin with a Model

147

underlying character (variable, construct) that is related, ultimately, to the expression of disease or dysfunction at the phenotypic level: The underlying continuous variable has been called the liability in the context of human diseases as threshold characters. . . . The continuous variation of liability is both genetic and environmental in origin, may be thought of as the concentration of some substance, or the rate of some developmental process—of something, that is to say, that could in principle be measured and studied as a metric character in the ordinary way.” (Falconer, 1989, p. 300)

Therefore, we think of liability as an underlying character with a (usually, but not always) continuous nature. We think of this underlying continuous character as having a threshold, “which imposes a discontinuity on the visible expression” (Falconer, 1989, p.  300). However, it is worth noting that one need not subscribe to a threshold model to use the term liability. I would also modify this view of liability to emphasize that it is going to express itself always in some form at the phenotypic or endophenotypic (Gottesman & Gould, 2003) level. It may not express itself necessarily as full-blown clinical disease—for example, schizophrenia—but it will show itself in some fashion. I do not see liability as needing “triggering” in some manner; although factors may exist that push one to express the liability, it need not be triggered in all-or-none fashion. The term susceptibility, which hails principally from molecular genetic studies of disease, shares much in common with liability. The primary difference is that susceptibility is normally linked with the words locus or loci. In that construction, susceptibility locus or loci, the genetic basis of the susceptibility is clear and unambiguous. We think about the word susceptible as meaning the “state or capability of being affected,” and in this instance the genes confer that state or capability within a probabilistic framework (i.e., you could get sick given the presence of the genes, but you will not necessarily become sick). Carey (2003) refers to a susceptibility locus as one that increases the likelihood of developing a disorder but does not guarantee it (also thought of as a “risk factor gene”). The term vulnerability tends to be associated more with a psychological perspective (Zubin & Spring, 1977; Ingram & Price, 2010). Price and Lento (2001) describe vulnerability as a subset of risk factors that are endogenous to the individual that may serve as mechanisms in the development of the disorder (Figure 6.1). In this view, vulnerability can be genetically or environmentally based; vulnerability is thought of as stable and enduring. Moreover, vulnerability is typically juxtaposed with the notion of resilience,

148

SCHIZOTYPY VIEWED FROM THE LABORATORY

FIGURE 6.1.  Theoretical relationships between resilience, vulnerability, stress level and psychopathology. From Ingram and Price (2010). Copyright 2010 by The Guilford Press. Reprinted by permission.

as depicted in Figure 6.1. This depiction plots vulnerability and resilience as opposite ends of a general vulnerability continuum, which is plotted against stress. A hypothetical threshold is represented by the diagonal that demarcates the likely appearance of pathology. Unlike discussions of liability, which often assume a normal distribution for underlying liability or assume other features of the underlying liability (e.g., qualitative in structure; Meehl, 1977, 1990), most discussions of vulnerability do not address the shape or structure of the underlying vulnerability construct. In the vulnerability model, it also typically assumed that there is an interaction between stress level and vulnerability, with this interaction being determinative of illness (or illness expression). Thus the vulnerability model makes a fairly clear assumption that triggering is required to express clinical dysfunction, whereas triggering is not necessarily a part of the liability model. For example, Zubin and Spring (1977) speak of “challengers [that] elicit a crisis in all humans, but depending on the intensity of the elicited stress and the threshold for tolerating it, that is, one’s vulnerability, the crisis will either be contained homeostatically or lead to an episode of disorder” (p. 103). The vulnerability model is essentially agnostic as to the origin of vulnerabil-



Begin with a Model

149

ity; it could be genetic or it could hail from some other source. Zubin and Spring (1977) hypothesized that all people are at risk of developing schizophrenia depending on the stress level involved in their lives. However, it is not clear from descriptions of the vulnerability model (Zubin & Spring, 1977; Price & Lento, 2001) that vulnerable individuals will always show some manifestation of their underlying diathesis. Thus in the vulnerability model it is essential to note that the emergence of psychopathology is really the result of stressors overwhelming one’s level of resilience. The level of vulnerability one shows represents essentially an inverse of his or her level of resilience (see also Belsky & Pluess, 2009). As I see it, vulnerability thus differs from liability in that liability will always manifest itself in some fashion, even if invisible to the unaided naked eye; the vulnerability model does not imply manifestations across a range of compensation. Finally, we consider the term risk. Risk is fundamentally a statistical notion that, at the most basic level, attempts to assert the degree to which someone is likely to develop a disorder such as schizophrenia. Although the “risk” concept as typically used in psychopathology research has never really reflected an exceptionally well-­defined metric, it has been used to make a quantitative/statistical (probability) assertion of an increased likelihood for developing the illness, particularly vis-à-vis a hypothetical case that carries no risk. The term risk has strong conceptual ties to the world of epidemiology. From this perspective, the degree of risk attached to a person in terms of his or her likelihood to develop schizophrenia has most typically been defined as a function of the degree of biological relatedness one has to a blood relative with a diagnosed case of schizophrenia. Thus risk is a rather atheoretical notion that attempts to quantify a likelihood of clinical disease (typically genetic relatedness to one affected by schizophrenia but can also include things such as birth complications, exposure to excessively noisome work conditions, exposure to influenza in utero during the second trimester of gestation, etc.). We can think of “risk” as simply the greater propensity for developing a disorder. Risk does not per se involve assumptions about thresholds, alternative expressions of the illness, or triggering; rather, it is simply a statistical comment on the likelihood of illness. For example, in Figure 6.2 we see the statistical risk for the expression of clinical schizophrenia plotted against the degree of genetic relatedness one has to a person who does have the illness (i.e., the amount of DNA one shares with an affected person). As the degree of genetic relatedness to an affected person rises, so does the statistical risk of developing the illness in the unaffected person in question (recalling that risk rates really refer to groups of individuals and cannot be applied with precision to a single person). Got-

150

SCHIZOTYPY VIEWED FROM THE LABORATORY General population

12.5% 3rd degree relatives

1%

First cousins

2%

Uncles/Aunts

2%

Nephews/Nieces 25% 2nd degree relatives

50% 1st degree relatives

4%

Grandchildren

5%

Half siblings

6%

Parents

6%

Siblings

9%

Children

13%

Fraternal twins 100%

17%

Identical twins

48% 0

Genes shared

Relationship to person with schizophrenia

10 20 30 40 Risk of developing schizophrenia

50

Genes Shared 12.5% Third degree relatives: First cousins 25% Second degree relatives: Uncles/aunts, nieces/nephews, grandchildren, half siblings 50% First degree relatives: children, siblings, parents, fraternal twins 100% Identical twins

FIGURE 6.2.  Risk for schizophrenia defined as a function of the degree of biological relatedness that one has with an affected individual. Adapted with permission from Gottesman (1991).

tesman (1991) reported, based on a summary of older studies, that the risk of schizophrenia to the offspring of two parents affected with schizophrenia was 46%. Recently, Gottesman, Laursen, Bertelsen, and Mortensen (2010), using the Danish Psychiatric Central Register system, reported that 39.2% of the offspring of two schizophrenia-­affected parents had some form of schizophrenia-­related psychopathology. Having examined liability, susceptibility, vulnerability, and risk, we can move on to a review of Paul Meehl’s (1962, 1990) model of schizotypy. In the model, Meehl (1962, 1990) proposed a specific genetic etiology for schizophrenia that held as a central concept the hypothetical latent construct



Begin with a Model

151

known as schizotypy. His model is essentially a liability model, as it does not allow for all persons to be at risk for schizophrenia. His model, which links the core hypothetical constructs he asserted were central to schizophrenia etiology, respects the different levels of analysis that are necessarily implied in attempting to understand a complex gene-to-­behavior pathway.

On Placing Meehl’s Model in Context: Both Here and Beyond I was tempted initially to provide a cursory overview of Meehl’s model of schizotypy. However, to be consistent with how I teach this material, as well as to place the entire venue of schizotypy research into a proper intellectual and historical matrix, I have opted to walk the reader through the model carefully. I take this tack for several reasons. First, it is important for contemporary students of experimental psychopathology to see where the major intellectual milestones are in this area, particularly within a methodological matrix such as this. Interestingly, in some more recent discussions of schizotypy, the optics involved, so to speak, seem a little fuzzy for writers, and at times the lacunae in the literature reviews are rather striking. Is it really intellectually defensible to write on the topic of schizotypy without mention of Meehl’s model? Second, the model espoused by Meehl really, nearly single-­handedly, ushered in a mode of thinking that explicitly contained multiple levels of analysis (genes, neural processes, cognitive processes, behavioral outcomes) and emphasized connections across these levels. In many respects Meehl’s model embodies all the features that a modern multiple levels of analysis theory piece would wish to have (cf. Kosslyn & Rosenberg, 2005) and represents an excellent mode of exposure to this way of thinking.8 Third, Meehl’s model represented one of the first and richest statements of what would become known as the “diathesis–­ stressor” model in psychopathology research. It presents a wonderful opportunity to gain an appreciation for what is meant by this terminology. Finally, Meehl’s model, both in the original statement (Meehl, 1962) and in revision (Meehl, 1990), contains a wide variety of untested hypotheses that could still be tapped by the motivated student in search of meaningful and challenging problems in schizotypy. Some colleagues have told me that they do 8 He

himself spoke of “order of dispositions” in his thinking on schizotypy, a rigorous analytic organizing scheme for theoretical conceptualizations influenced by analytical philosophy (see Meehl, 1972b; Waller et al., 2006).

152

SCHIZOTYPY VIEWED FROM THE LABORATORY

not teach Meehl’s model because it is simply “too complicated” for students to grasp—­needless to say, I accord this view little weight. My experience is that many undergraduate, graduate, and medical students apply their intellect, dig into this rich substantive viewpoint, and learn many important things about schizotypy and schizophrenia, as well as psychological science writ large, along the way. There can be no doubt that Meehl’s model has had a profound impact on the manner in which the schizophrenia research enterprise has unfolded since 1962. His original (1962) and his later (Meehl, 1989, 1990) papers that outline the model have been cited more than 1,500 times (not counting dissertations or theses). I would say that his formulation has become so implicitly a part of how we think of schizophrenia, schizotypy, and the schizophrenia spectrum conditions that some might “forget” to acknowledge it.9 Indeed, I have reviewed grant proposals and seen large review and theory articles in respectable journals using the terms schizotaxia and schizotypy without citation of Meehl. However, despite the impact of his proposition and the attention his model garnered, Paul frequently remarked to me (and others, I am told) that he felt that many in the fields of clinical psychology and psychiatry did not take the time to really understand his model of schizotypy, noting that many (especially textbook authors) frequently “get it wrong!” What is problematic is that those papers seeking to amend, revise, or reformulate Meehl’s ideas are typically rife with conceptual errors, suggesting that the authors either never read or understood Meehl. With new generations of clinical science graduate students and psychiatrists coming along, this is a fitting opportunity to review Meehl’s model of schizotaxia, schizotypy, and schizophrenia.

Meehl’s Integrative Model of Schizotaxia, Schizotypy, and Schizophrenia As noted in Chapter 5, many of the early depictions of schizotypic pathology were merely descriptive in nature. Although the peculiarities of the relatives of schizophrenics or the symptoms of schizophrenic-like outpatients were noted and conjectured to be related to schizophrenia in some manner, 9 In

the creative arts it is not unusual to see good ideas borrowed or “stolen” without credit. One hears sentiments such as “Good artists borrow; great artists steal” (P. Picasso) or “Mediocre writers borrow; great writers steal” (T. S. Eliot). However, in science one should give credit where credit is due; thus one can never be faulted for providing a citation to the originator of the idea. Always better to be overdressed than underdressed.



Begin with a Model

153

none of the early workers advanced a model that unambiguously posited a genetic diathesis for schizophrenia and traced its influence through neurodevelopmental and behavioral paths to a variety of clinical (and nonclinical) outcomes. Meehl (1962) described his model of schizotaxia, schizotypy, and schizophrenia in his American Psychological Association presidential address. He proposed a model that was (and is) clearly neurodevelopmental in nature and that came to have a profound impact on the manner in which informed psychologists and psychiatrists would think about schizophrenia. Meehl’s model explicitly or implicitly serves as a guiding framework in the laboratory and in the genetic study of schizophrenia and schizotypy, reflected in some incarnation in nearly all contemporary models of the disorder, even when new terms are used (e.g., cognitive dysmetria, developmentally reduced synaptic connectivity, neurodevelopmental disease process).

The Influence of Sandor Rado on Meehl’s Thinking The roots of Meehl’s model can be found in the observations and psychodynamic formulations of Sandor Rado, MD (1953, 1960), and Meehl (1962, 1990) always readily acknowledged this inspiration. Working within the clinical tradition, Rado made initial strides toward an integrative model that sought to link genetic influences for schizophrenia and observed schizotypic personality functioning. Rado, a psychoanalyst at Columbia University, theorized from a psychodynamic position informed by an appreciation for genetics that schizotypal behavior derived from a fundamental liability to schizophrenia. Rado originally coined the term schizotype to represent a condensation of schizophrenic phenotype (Rado, 1953, p. 410; Rado, 1960, p. 87). Rado did not suggest schizotype as a condensation of the terms schizophrenic and genotype (a frequently misunderstood point). Furthermore, Rado (1960) has carefully noted that the individual possessing the schizophrenic phenotype was a schizotype, whereas the correlated traits deriving from this “type” were termed schizotypal organization and the overt behavioral manifestations of the schizotypal traits were termed schizotypal behavior (see p. 87). For Rado, the causes of schizotypal “differentness” were to be found in two core psychodynamic features of such patients, both of which were thought to be driven by “mutated genes.” The two core defects present in the schizotype’s personality organization were: (1) a diminished capacity for pleasure, or pleasure deficiency, speculated to have a neurochemical basis deriving from an inherited pleasure potential coded in the infant’s genes (Rado, 1960, p. 88), and (2) a proprioceptive (kinesthetic) diathesis

154

SCHIZOTYPY VIEWED FROM THE LABORATORY

that resulted in an aberrant awareness of the body (a feature giving rise to schizotypic body image distortions; Rado, 1960, pp. 88, 90). Rado believed the physiological nature of the proprioceptive diathesis was obscure and remained to be explored (1960, p. 88). According to Rado, integration of the “action self,” a necessity of psychodynamic/psychological health, was endangered by both the diminished binding power of pleasure (p. 90) and the proprioceptive diathesis found in the schizotype. Consequently, Rado describes the schizotype as struggling to retain a sense of personality integration through several compensatory mechanisms (see Rado, 1960, p. 90), and such mechanisms frequently manifest themselves as schizotypal traits and behaviors. An important feature of Rado’s model concerned what he termed “developmental stages of schizotypal behavior,” essentially a continuum view of clinical compensation (a view echoed later by Meehl, 1990, p. 25). Rado’s continuum notion suggested that a common schizophrenia diathesis could lead to a variety of phenotypic outcomes ranging from compensated schizotypy to deteriorated schizophrenia; thus an etiological unity was proposed as underlying a diversity of clinical manifestations.

Schizotaxia, Schizotypy, and Schizophrenia Meehl proposed his theory of the etiology and pathogenesis of schizophrenia in his classic 1962 position paper, “Schizotaxia, Schizotypy, Schizophrenia.” In doing so, he created a model that would become a landmark in the theory of psychopathological development and a potent stimulus for decades of research. The model not only encompassed genetic factors, social learning influences, and clinical symptomatology but also contained hypotheses about the precise nature of the fundamental defect underlying schizotypic functioning and its interactions with what he came to term polygenic potentiators. Elaboration and refinement of the original 1962 theory can be found in his later papers on the topic (e.g., Meehl, 1972b, 1975). The theory was updated and described fully in a subsequent extended position paper (Meehl, 1990), and he discussed the origins of some of his more speculative assertions in Meehl (1993; see also Meehl, 1989). What follows is a distillation of the major points contained in Meehl’s monumental effort to illuminate the development of schizophrenia. The reader is encouraged to consult both Meehl’s original position statement (Meehl, 1962) and his 1990 treatise for additional detail. In brief, Meehl’s (1962, 1990) model of schizotypy holds that a single major gene (what he termed the schizogene) exerts its influence during brain



Begin with a Model

155

development by coding for a specific “functional parametric aberration of the synaptic control system” in the central nervous system (CNS; 1990, pp. 14–15). The aberration, present at the neuronal level, is termed hypokrisia and suggests a neural integrative defect characterized by an “insufficiency of separation, differentiation, or discrimination” in neural transmission. Meehl argued that his conceptualization of schizotaxia should not be taken to represent a simple defect in basic sensory or information-­retrieval capacities (1990, p. 14), nor a CNS inhibitory function deficit (1990; p. 16). The defect in neural transmission amounts to the presence of “slippage” at the CNS synapse, and such slippage at the synapse has its behavioral counterparts (at the molar level) in the glaring clinical symptomatology of actual schizophrenia. In other words, just as the synaptic functioning in schizophrenia is characterized by slippage, so too are the symptoms of associative loosening and cognitive–­affective aberrations observed in the schizophrenic patient. Hypokrisia was hypothesized to characterize the neuronal functioning throughout the brain of the affected individual, thus producing what amounts to a rather ubiquitous CNS anomaly (1990; p. 14) termed schizotaxia (see Figure 6.3). In the model, schizotaxia is the “genetically determined integrative defect, predisposing to schizophrenia and a sine qua non for that disorder” (p. 35) and is conjectured to have a general population base rate of 10% (see Meehl, 1990, for derivation of the base rate estimate; see also Lenzenweger & Korfine, 1992a, for empirical support). Schizotaxia describes an aberration in brain functioning characterized by pervasive neuronal slippage in the CNS; it is not a behavior or observable personality pattern. The schizotaxic brain, however, becomes the foundation on which other factors build and interact adversely with to possibly produce clinically diagnosable schizophrenia. The other factors that interact with the schizotaxic brain and influence individual development (as well as clinical status) are an individual’s social learning history and other genetic factors termed polygenic potentiators. Meehl (1962, 1990) generally held that all (or nearly all) schizotaxic individuals develop schizotypy (i.e., a schizotypal personality organization) on existing social reinforcement schedules. Schizotypy, therefore, refers to the psychological and personality organization resulting from the schizotaxic individual interacting with and developing within the world of social learning influences. An individual who displays schizotypy is considered a schizotype. In this context it is essential to note that Meehl’s “schizotypal personality organization” is not the same as the DSM-IV Axis II disorder schizotypal person-

156

SCHIZOTYPY VIEWED FROM THE LABORATORY

FIGURE 6.3.  Causal chains in schizophrenia, minimum complexity (Meehl, 1972b, p. 16; 1973, p. 190; 1989, p. 941; 1990, p. 27). Reprinted with permission from Leslie J. Yonce.



Begin with a Model

157

ality disorder. Meehl (1990) considered the possibility that a schizotaxic individual might not develop schizotypy if reared in a sufficiently healthful environment (p. 35), but such an outcome was not viewed as likely. The second major set of factors influencing the development of clinical schizophrenia in the schizotypic individual is a class of genetically determined factors (or dimensions) termed polygenic potentiators. According to Meehl (1990), “a potentiator is any genetic factor which, given the presence of the schizogene and therefore of the schizotypal personality organization, raises the probability of clinical decompensation” (p. 39). Potentiators include personality dimensions (independent of schizotaxia) such as social introversion, anxiety proneness, aggressiveness, hypohedonia, and others. Such potentiators do not modify (in the technical genetic sense of the term) the expression of the putative schizogene but rather interact with the established schizotypic personality organization and the social environment to facilitate (or, in some cases, “depotentiate”)10 the development of decompensated schizotypy, namely schizophrenia. Meehl (1990) stresses, “It’s not as if the polygenes for introversion somehow ‘get into the causal chain’ between the schizogene in DNA and the parameters of social reinforcement” (p. 38); rather, the potentiators push the schizotype toward psychosis. Viewed from genetics theory, Meehl’s model represents a “mixed” model of genetic influence, namely, a single major gene (i.e., an autosomal diallelic locus) operating against a background due to an additive polygenic (or cultural) component. Meehl maintained his view of a major locus playing a key role in the etiology of schizophrenia throughout his career. However, the model is best viewed as a “mixed model.” In summary, according to Meehl (1962, 1990), the development of diagnosable schizophrenia is the result of a complex interaction among several crucial factors: (1) a schizotaxic brain characterized by genetically determined hypokrisia at the synapse; (2) environmentally mediated social learning experiences (that bring about a schizotypal personality organization); and (3) the polygenic potentiators.

Implications of the Model and Further Clarifications The modal schizotype does not decompensate into diagnosable schizophrenia; however, Meehl suggested that all schizotypes reveal the influence of their latent diathesis through aberrant psychological and social functioning. 10 The idea of genetic factors acting to protect one against emergence of illness was echoed recently in Belsky and Pluess (2009).

158

SCHIZOTYPY VIEWED FROM THE LABORATORY

This simple yet core assumption, namely a latent liability that necessarily manifests itself subtly in neurocognitive processes, would stimulate and direct years of research on laboratory risk indicators of, and endophenotypes (Lenzenweger, 1999b; Gottesman & Gould, 2003) for, schizophrenia liability. Meehl (1962) argued that there were four fundamental clinical signs and symptoms of schizotypy: cognitive slippage (or mild associative loosening), interpersonal aversiveness (social fear), anhedonia (pleasure capacity deficit), and ambivalence. In fact, he developed a clinical checklist for schizotypic signs that included rich clinical descriptions of not only these four signs and symptoms but also several others, which he suggested were valid schizotypy indicators (the manual remains a treasure trove of clinical observation to this day; see Meehl, 1964). Basically, all aspects of the core clinical phenomenology and psychological functioning seen in the schizotype were hypothesized to derive fundamentally from the aberrant CNS functioning (i.e., hypokrisia) as determined by the schizogene. For example, “primary cognitive slippage” gave rise to observable secondary cognitive slippage in thought, speech, affective integration, and behavior. He saw hypokrisia as the root cause of “soft” neurological signs, as well as what he termed “soft” psychometric signs that could be detected among schizotypes. Finally, Meehl argued that hypokrisia also led to what he termed primary aversive drift or the steady developmental progression toward negative affective tone in personality functioning across the life span among schizotypes (see Meehl, 1990, p. 27, Figure 1). This primary aversive drift across the life span was thought to give rise to social fear, ambivalence, and hypohedonia. Meehl often noted Sullivan’s (1956) expressed concern that some individuals with schizophrenia had essentially given up on life. Hedonic capacity was of great interest to Meehl, and the role played by anhedonia in his model changed over the years. In the 1962 model, anhedonia was hypothesized to represent a fundamental and etiologically important factor in the development of schizotypy, actually falling somewhat “between” the genetic defect hypokrisia and the other schizotypic signs and symptoms—­interpersonal aversiveness, cognitive slippage, and ambivalence. Later, Meehl deemphasized anhedonia (then termed hypohedonia; but see Meehl, 1964) as a fundamental etiological factor in the development of schizotypy and schizophrenia (see Meehl, 1987). In the 1990 revision, Meehl strongly suggested that associative loosening and aversive drift are those key psychological processes (deriving from hypokrisia) that determine the behavioral and psychological characteristics of the schizotype (see Meehl, 1990; p. 28). Hypohedonia was now viewed as playing an etiological role in the development of schizotypy by functioning as a dimensional polygenic potentiator (i.e.,



Begin with a Model

159

not deriving from the core genetically determined schizophrenia diathesis). The major reconfiguration of hypohedonia’s role in the model was discussed further by Meehl (1993, 2001). In short, Meehl (1975, 1987, 1990) proposed that all persons displayed some level of hedonic capacity, which was conceived of as a normal-range, dimensional, individual-­differences construct, and it functioned in a “potentiator” role, as noted earlier. Meehl (2001) clearly noted that a pathological variant of hypohedonia determined, perhaps, by a genetic defect similar to that proposed by Rado could also exist in some people. However, the etiological basis of such a hedonic defect may or may not be directly attributable to a “schizogene.” He did not see these two possibilities—a normal-range quantitative system and an anhedonic taxon or class—as mutually exclusive. Meehl (2001) discussed the challenges posed by interpretation of results from latent structure analyses of phenotypic indicators of hedonic capacity with reference to his model of schizotypy and the possible etiology of deviations in hedonic capacity. Meehl viewed this specific terrain (i.e., hedonic capacity) as ripe for continued exploration and saw it as consisting of open questions with respect to schizotypy.

How Did Meehl Describe the Schizotype? The answer to this question is “it depends on the level of compensation that characterizes the individual.” A most important assumption in Meehl’s model is that schizotypy, as a personality organization reflective of a latent liability (i.e., not directly observable) for schizophrenia, can manifest itself phenotypically (i.e., behaviorally and psychologically) in various degrees of clinical compensation. This personality organization gives rise to schizotypic psychological and behavioral manifestations (Meehl, 1962, 1964), such as subtle thought disorder (cognitive slippage) or excessive interpersonal fear, yet it may be manifested relatively “quietly” through deviance detectable only on laboratory measures as endophenotypes (e.g., eye-­tracking dysfunction, sustained attention deficits, psychomotor impairment, somatosensory dysfunction). In short, the schizotype may be highly compensated (showing minimal signs and symptoms of schizotypic functioning), may reveal transient failures in compensation, or may be diagnosably schizophrenic—­ essentially ranging clinically from apparent normality through psychosis— yet all share the schizophrenia diathesis and resultant schizotypic personality organization. A crucial implication of this assumption is that not all schizotypes develop diagnosable schizophrenia (i.e., one could genuinely be at risk yet never develop a psychotic illness); however, all schizotypes will display some evidence of their underlying liability in the form of aberrant psychobiological and/or psy-

160

SCHIZOTYPY VIEWED FROM THE LABORATORY

chological functioning. This implication of the model has guided nearly 40 years of research on the valid and efficient detection of schizotypy endophenotypes (through clinical, psychometric, or other means), and it established the “diathesis–­stressor” model/approach for psychopathology.

Frequent Misunderstandings of Meehl’s Model Paul Meehl’s schizotypy model represents one of the most fruitful heuristics in modern psychopathology research. Many researchers and clinicians, across numerous disciplines (e.g., psychology, psychiatry, genetics, philosophy of science, and so on), have some familiarity with it. The model is typically discussed briefly, as well, in numerous abnormal psychology, clinical psychology, and psychiatry textbooks. In descriptions of his model by others, several misconceptions and various misapprehensions occur not infrequently. •• Issue 1: “Schizotypy is not the same as DSM-IV schizotypal personality disorder.” Meehl emphasized that his conceptualization of schizotypy was not synonymous with the DSM-IV diagnosis of schizotypal personality disorder (see 1990, pp. 24–25). Although there is some degree of phenomenological similarity between schizotypic symptoms and signs and the diagnostic criteria for DSM-IV schizotypal personality disorder, important differences exist between the two concepts. Schizotypy refers to a latent personality organization and is a broader construct linked to a developmental theory. DSM-IV schizotypal personality disorder, on the other hand, is a cluster of observable signs and symptoms that tend to cohere, and the disorder is described in an atheoretical manner. Meehl’s schizotypy construct may underlie or encompass several of the personality disorder diagnoses on the DSM Axis II. For example, the schizotype may not only display some schizotypal symptoms but may also reveal paranoid, compulsive, avoidant, and/or schizoid phenomenology. The term schizotypy should never be taken to imply solely phenotypic manifestations of schizotypal personality pathology (see Figure 6.4). It is also noteworthy that the World Health Organization’s (WHO) International Classification of Diseases (ICD-10) concept of “schizoid personality disorder” is also not isomorphic with either Meehl’s schizotypy or DSM-IV schizotypal personality disorder. •• Issue 2: “Schizotypy” is not entirely genetic in origin. Meehl has been quite clear on this point. Schizotypy per se (i.e., as a personality organization) is not inherited; all that can be spoken of as inherited is the defect of hypokrisia and, by definition, the “schizotaxic brain” (Meehl, 1990, p. 35).



Begin with a Model

161

Schizotypy and schizotypy indicators: Don’t confuse the latent construct with the measured indicator of the construct

Schizophrenia

Schizotypal PD features

Laboratory measures

Psychometric indexes

Indicators are not isomorphic with the latent construct.

Plane of observation

Schizotypy

Schizotypy is a latent construct invisible to the naked, unaided eye

Liability for Schizophrenia

FIGURE 6.4.  The relationship between the latent construct schizotypy and indicators of schizotypy, such as clinical, psychometric, and laboratory measures. One should not speak of observed indicators of the latent construct as schizotypy, for example, schizotypal personality disorder features should be described as a schizotypy indicator. See Cronbach and Meehl (1955) and/or MacCorquodale and Meehl (1948) for extended discussion of these points.

Although most schizotaxics develop schizotypy on existing social learning regimens, there is the theoretical possibility that a schizotaxic will not become schizotypic (although the prevalence of such cases is probably rather small). The important point concerns what is inherited versus what develops from the inherited diathesis in interaction with polygenic potentiators and the environment. For Meehl, schizotaxia is genetically determined and, simply put, is based in DNA, whereas schizotypy develops from schizotaxia in interaction with (noninherited) environmental influences and, therefore, cannot be spoken of as inherited. Meehl (2001) stated, “I specifically denied that schizotypy as a personality make-up [italics added]—with its characteristic signs, symptoms, traits, and psychodynamics—is inherited; I cannot understand why articles and textbooks have attributed that absurd belief to me” (p. 188). It should be noted that this point does not concern the conventionally defined heritability concept, which is estimated via the decomposition of phenotypic variation into variance components reflecting shared and nonshared environmental effects and, typically, additive

162

SCHIZOTYPY VIEWED FROM THE LABORATORY

genetic effects (using ANOVA or modeled using latent variable techniques; cf. Boomsma, Busjahn, & Peltonen, 2002). Clearly, variation on measures of schizotypy can be shown to be heritable; however, this was not Meehl’s point in delineating these differing levels of analysis. Thus, although Meehl viewed schizotaxia as genetically determined (and therefore highly heritable, in the conventional sense of the term), he emphasized that environment does affect its expression at the level of schizotypy and, therefore, that schizotypy cannot be spoken of as entirely genetic in origin. •• Issue 3: The term schizotypy is not reserved only for clinical (read DSM) schizotypal features. This issue reflects a relatively common misunderstanding of the terms schizotype and schizotypy. Meehl’s model holds that schizotypy can manifest itself in different manners of expression ranging from fullblown schizophrenia to schizotypic psychopathology (e.g., DSM-IV SPD or PPD) to deviance on valid laboratory measures, including psychometric measures, of schizotypy (endophenotypes). This point warrants repeating: The schizotype, per se, can be identified on the basis of deviance on laboratory measures (e.g., psychometric or neurocognitive measures) or on the basis of observable clinical signs and symptoms. This clarification is driven by the presumption by some that the term schizotypy per se is reserved only for interview-­assessed clinical features, whereas other approaches must be somehow qualified (e.g., “psychometric schizotypy”). It makes little to no sense to speak of “psychometric schizotypy” (or “psychometric depression” or “psychometric intelligence”), just as it makes no sense to speak of “interview schizotypy” (or “interview depression” or “interview intelligence”). If one wishes to specify the mode of assessment or measurement, then one can do that in the methodological description section of a paper. However, there is no intellectual or conceptual gain in designating schizotypy features assessed using psychometric measurement techniques as “psychometric schizotypy.” •• Issue 4: Shouldn’t all (or nearly all) schizotypes develop schizophrenia? Although one would not ever expect to hear such a question based on what Meehl argued for in his theory papers, I have indeed been asked such a question during the question-and-­answer period following a colloquium, and I have seen such an assumption reflected in “comments to authors” in manuscript reviews and in “pink sheet” comments from grant application reviewers. The assumption underlying this question is simply incorrect. Meehl’s model makes it abundantly clear that not all schizotypes will develop clinical schizophrenia during the life course. Furthermore, he emphasized the point that “schizotypes” per se should not be thought of as



Begin with a Model

163

watered-down or dilute variants of schizophrenia (Meehl, 1972a). What proportion of schizotypes do develop clinical schizophrenia across the life span? This remains an open question, with very little empirical data available that speak to it.

On “This and That” in the Meehl Model What is the precise recipe of polygenic potentiators, life stressors, and random events in interaction with the schizotaxic brain that might lead one to move from being a compensated schizotype to clinical schizophrenia? Simply stated, the answer is not known, but this is the “billion dollar question” in schizophrenia research. Meehl articulated the rich matrix of components and developmental processes that he believed could eventually yield schizophrenia in some instances, but he was not able to identify those specific factors (genetic or otherwise) that propel one to transition from the nonpsychotic schizotype to clear-cut schizophrenia (i.e., psychosis). Clearly Meehl viewed the polygenic potentiators noted previously as playing an important role in this developmental process (Meehl, 1962, 1990). However, he also stressed the importance of what he termed “unknown critical events” as well as the “random walk” (i.e., life histories may reflect divergent causality, rather than the impact solely of well-known systematic factors such as social class or birth order) in the determination of schizophrenia (Meehl, 1978; cf. Meehl, 1971, 1972a, b). In this context it is worth noting that although Meehl saw the polygenic potentiators as important, it should be noted that he argued that the polygenic potentiators “do not in the least ‘modify’ the schizogene’s endophenotypic expression as schizotaxia, a CNS parametric aberration” [italics in original] (Meehl, 1972a, p. 380). Rather, they simply alter the probability that a schizotype might move on to clinical schizophrenia. The precise manner whereby a schizotype moves on to schizophrenia, in those instances in which it happens, remains an open issue and is ripe for life span developmental studies of schizotypy. Such research should also seek to understand those factors—­polygenic potentiator or otherwise—that might buffer a schizotype from transitioning to schizophrenia. The impact of Meehl’s “schizotaxia, schizotypy, and schizophrenia” model speaks for itself; it represents perhaps one of the richest heuristics ever proposed in psychological science, surely in clinical psychology. It remains a potential gold mine for valuable hypotheses that might be used to gain leverage on schizophrenia and schizophrenia liability—one merely needs to read Meehl (1990) to find an interesting hypothesis or two to investigate. Notably, the model, as mentioned previously, consists of multiple levels of

164

SCHIZOTYPY VIEWED FROM THE LABORATORY

conceptualization, and each of these levels represents a strand in a network that can be explored in turn (Lenzenweger, 2003, 2004), which makes the model particularly appealing for investigations from different methodological and analytic vantage points or levels (e.g., experimental psychopathology, taxometrics, genetics). Regarding genetics specifically, as some readers may wonder about this issue, Meehl maintained his allegiance to a single major-locus theory of schizophrenia (dominant with complete penetrance for the schizotaxic endophenotype and 10–20% phenogenocopy rate), yet, as I noted before, his model is legitimately best understood as a “mixed model.” Even in 2010, the jury remains out on the nature of the underlying structure of the genetic liability for schizophrenia, as most linkage studies remain underpowered and/or do not adequately incorporate endophenotype measurements or an expanded phenotype and therefore have limited resolving power. There is considerable enthusiasm for the polygenic model of liability; however, the challenge posed by heterogeneity is palpable and this challenge serves to keep the issue of liability structure open. Meehl’s 1962 conjecture that schizotypy (schizophrenia liability) could manifest across varying degrees of compensation turned out to be spot-on accurate; hence the volume of modern laboratory work linking endophenotypes (e.g., deficits in sustained attention, smooth pursuit eye movement, fine motor performance, somatosensory functioning), as well as schizotypic psychopathology, to schizophrenia liability (see Figure 6.5). Finally, although nearly 50 years have passed since Meehl proposed his model of schizotypy, one has a “back to the future” sense when reading contemporary theoretical models of schizotypy and schizophrenia, which emphasize such concepts as “diminished synaptic connectivity,” “cognitive dysmetria,” “diminished tuning,” “diminished updating,” and the ubiquitous “neurodevelopmental disorder,” while reflecting on his notions of hypokrisia, neuronal slippage, and primary cognitive slippage.

Revisionist Efforts: A Case Study on Levels of Analysis and Precision in Language There are times when Meehl’s model is presented in the contemporary literature as a springboard for movement toward new ideas, whereas at other times the model is presented as one in need of revision. Both of these instances are perfectly acceptable, as science depends on open discourse and debate. However, sometimes position papers appear that seek to amend flaws or revise particular aspects in Meehl’s (1962, 1990) model, yet it is not



Begin with a Model

165

entirely clear why various revisions and amendments are being proposed. A case in point can be found in Stone, Faraone, Seidman, Olson, and Tsuang (2005), in which the authors report that they “reformulated the term schizotaxia to include newer data” (p. 405). These authors refer repeatedly to “schizotaxia as a syndrome of liability to schizophrenia,” (p. 403) and it is not entirely clear what this means, as the term syndrome is typically associated with a disease, disorder, or condition that is characterized by a pattern of interrelated (phenotypic) symptoms. In classification, one speaks of a syndrome even before one speaks of a disorder or disease. However, as argued by Meehl, schizotaxia is a latent entity, and, therefore, it is not observable, whereas a syndrome is, by definition, an observable clustering of features suggestive of a potentially cohesive disorder or disease entity. Stone et al. (2005) argued that Meehl’s (1962, 1990) notion of schizotaxia was not associated with an observable phenotype or clinical syndrome. This concern reflects, more than anything else, a failure to appreciate the levels of analysis implicit in Meehl’s model. Schizotaxia in Meehl’s model was never intended to be linked directly to an observable phenotype—­schizotaxia was intended as a descriptor of the pathology in the brain, whereas schizotypy (at a level beyond) would reveal itself phenotypically. Schizotaxia was always thought of as a latent construct, and it was not conjectured to be linked directly to an observable phenotype or syndrome. Recall that Cronbach and Meehl (1955) proposed that latent constructs, as discussed earlier, are related (typically via probabilistic [stochastological] relations, which presumably reflect nomological relations) to observable entitites. Meehl (1962, 1989, 1990) was consistently clear that an observable phenotype derived from schizotaxia. This phenotype was in the form of a specific personality organization that reflected itself in schizotypic signs. The beauty of the formulation was that it not only accounted for the flagrant signs and symptoms of schizophrenia, but also encompassed the signs and symptoms of schizotypic psychopathology (which Meehl detailed in 1964). In the age of the DSM, there seems to be an interest in twisting DSM diagnostic entities onto theoretical models. In the case of schizotaxia, there has been an urge to engage in Procrustean11 11 According

to Greek mythology, Procrustes (he who stretches) was a rather odd innkeeper. He kept a house by the side of the road and offered hospitality to passersby, who were invited in for a pleasant meal and a night’s rest in his very special bed. Procrustes described his bed as having the unique property that its length exactly matched whoever lay down on it. What Procrustes did not volunteer was the method by which this “one-size-fits-all” was achieved; namely, as soon as the guest lay down, Procrustes went to work on him, stretching him on the rack if he was too short for the bed and chopping off his legs if he was too long. Theseus turned the tables on Procrustes, fatally adjusting him to fit his own bed. Thus, with respect to science, we think of the effort to fit data to a theory that really does not fit the theory as a Procrustean effort (see Hamilton, 1940).

166

SCHIZOTYPY VIEWED FROM THE LABORATORY Latent level

Manifest level

(unobservable)

(observable) “2nd hit”

Schizophrenia DNA

SZ gene(s)

Epigenetic factors?

CNS the brain

Schizotaxia

Personality organization

Prodrome ?

Schizotypic disorders

Schizotypy

(Synaptic slippage due to hypokrisia)

SL? SL? Social learning influences

Schizophreniarelated psychoses

S?

PGP? PGP?

S?

Stressors and polygenetic potentiators

Endophenotypes

Not visible to “naked” eye Plane of observation

Candidates: sustained attention, eye tracking,working memory, motor function, thought disorder (secondary cognitive slippage), psychometrics

FIGURE 6.5.  Developmental model relating the genetic diathesis for schizophrenia, schizotaxia, and schizotypy and implied levels of analysis (inspired by Meehl 1962, 1990), with modifications. Those factors to the left of the vertical broken line (i.e., plane of observation) are “latent” and therefore unobservable with the unaided naked eye, whereas those factors to the right of the plane of observation are manifest (or observable). A DNA-based liability—primary synaptic slippage (or Meehl’s hypokrisia)—creates impaired CNS-based neural circuitry (schizotaxia) that eventuates in a personality organization (schizotypy) that harbors the liability for schizophrenia. This liability could be one major gene, several genes of moderate effect, or numerous small-effect genes that have summed to pass a critical threshold. Social learning schedules interact with schizotaxia to yield schizotypy. Psychosocial stressors and polygenic potentiators interact with schizotypy to yield manifest outcomes across a range of clinical compensation. Various possible manifest developmental outcomes are schizophrenia (which may involve an optional “second hit,” e.g., in utero exposure to maternal influenza), schizotypic psychopathology (e.g., schizotypal and/or paranoid personality disorders), or schizophrenia-related psychoses (e.g., delusional disorder). So-called prodromal features (withdrawal, reduced ideational richness, disorganized communication) may precede the onset of some (but not all) cases of schizophrenia. Endophenotypes (e.g., sustained attention deficits, eye-tracking dysfunction, working memory impairments, motor dysfunction, thought disorder [secondary cognitive slippage], and/or psychometric deviance [PAS]; see Gottesman & Gould, 2003), which are invisible to the unaided, “naked” eye (but detectable with appropriate technologies), are found below the plane of observation. Epigenetic factors refer to nonmutational phenomena, such as DNA methyla-

S c h i z o t y p e s



Begin with a Model

167

efforts to establish DSM SPD as the manifestation of schizotaxia. Let us consider other positions taken by Stone et al. (2005). •• “We proposed an operational, research definition of schizotaxia that would allow the concept to be validated or disconfirmed experimentally” (Stone et al., 2005, p.  405). These authors do not specify operations, in the Bridgman sense (see earlier discussion), by which schizotaxia can be defined. Their suggestion that experimental laboratory tasks could be used in the investigation of schizotaxia (and, by definition, schizotypy) echoes Meehl’s call for laboratory study 50 years earlier (Meehl, 1962). Meehl (1990) explicitly discussed experimental laboratory tasks in the study of schizotaxia and schizotypy (e.g., eye tracking). •• “The clinical outcome of the ‘reformulated version of schizotaxia’ represents a second point of divergence from Meehl’s view. While he proposed that most cases progressed to show symptoms of schizotypy or schizophrenia, we hypothesized that schizotaxia results in a stable syndrome that does not progress to schizotypal personality disorder or to schizophrenia in most cases” (p. 406). This “reformulated” view of schizotaxia as manifesting itself across a range of compensation merely restates a central point in Meehl’s model, discussed at numerous points in the 1990 opus. The authors conflate schizotypy and SPD in their position, as well as conflating schizotypy and schizophrenia. Meehl did not propose that schizotaxia eventually manifests itself in the form of SPD. Rather, his position was that schizotaxia, which describes the brain condition of the affected person, yields schizotypy, which is a personality organization that harbors the liability for schizophrenia. At the phenotypic level, schizotypy can manifest from essentially no visible symptoms whatsoever to full-blown schizophrenia. (The terms schizotypy and schizophrenia are not synonymous, as suggested by Stone et al., 2005). Finally, Meehl suggested that schizotypy (as the manifestation of schizotaxia) represented a stable, brain-based personality organization; schizotaxia is not the personality organization per se.

tion and histone acetylation (modification), that alter the expression of the schizophrenia gene (or genes). For example, there is the possibility that a hypermethylation process may serve to downregulate genes of relevance to schizophrenia (see Tsankova, Renthal, Kumar, & Nestler, 2007). Finally, all individuals represented across this range of manifest outcomes are considered “schizotypes,” which does not necessarily imply an ICD or DSM diagnosis. Copyright 2008 by Mark F. Lenzenweger. Reprinted by permission.

168

SCHIZOTYPY VIEWED FROM THE LABORATORY

•• Stone et al.’s (2005) third point of putative disagreement with Meehl’s view involves his proposition that the etiology of schizotaxia is entirely genetic. These authors implicitly suggest that schizotaxia is not entirely genetic in the following: “in part because the neurobiological effects of genes cannot always be separated from the biological effects of adverse environmental variables, we view schizotaxia as the combined effect of both factors” (p. 406). Meehl never maintained that schizotypy, as a manifestation of schizotaxia, is entirely genetic; his model is one that implicitly embraces gene–­environment interaction. Meehl did view schizotaxia as the genetically inherited liability for schizophrenia. Meehl saw environmental inputs as critical in the development of schizotypy. To the extent that Stone et al. (2005) believe that an environmental input can create a genetic diathesis, Meehl would probably part company with them (as would I). Environmental factors may serve to trigger or modify a genetic predisposition; however, factors such as exposure to influenza during the second trimester of gestation, birth complications, and/or noisome work conditions do not create schizotaxia. •• “A fourth point of modification involves the nature of the genetic influence in schizophrenia. While Meehl suggested that schizophrenia resulted from a dominant schizogene interacting with polygenic “potentiators” and environmental factors, the more current, consensual view is that most cases of schizophrenia result from combinations of multiple genes of small or moderate effect, together with adverse environmental factors. Thus, schizotaxia (like schizophrenia) is a complex genetic disorder. . . . ” (p. 406). Stone et al. (2005) reveal further imprecision in their language that complicates the understanding of their position—for example, schizotaxia is not a complex genetic disorder, as schizotaxia itself is not a disorder. Meehl’s (1962, 1990) model is fundamentally a mixed model of genetic influence whereby a major locus operates against a background of polygenic potentiators. He was well aware of the polygenic position, especially as it was espoused by his long-time colleague and former University of Minnesota psychology department neighbor, Irving I. Gottesman. Whether or not all forms of schizophrenia are found to have a polygenic nature (with a marked threshold effect) remains to be demonstrated. The dozen or so candidate genes that currently occupy the interest of psychopathology geneticists may actually add up to (or combine to form) a liability for schizophrenia, or they may be found to be of relevance to different schizophrenias. •• Finally, Stone et al. (2005) maintain, by virtue of their third and fourth points of disagreement with Meehl, that schizotaxia may express



Begin with a Model

169

itself through a variety of clinical phenotypes, including endophenotypes. Meehl stated as much in both of his major position papers on schizotaxia, schizotypy, and schizophrenia (1962, 1990). On balance, Stone et al. (2005) have not provided substantial amendments or extensions to Meehl’s (1962, 1990) original model, nor have they pursued empirical programs of research that he did not already advocate. What Stone et al. (2005) have done is, like many others, be inspired by Meehl’s (1962, 1990) model in the search for endophenotypes through the lab study of schizophrenia liability indicators.

Excursus on Alternative Views of Schizotypy: “Healthy Psychosis” and Claridge’s Dimensional Approach A discussion of contemporary views of the schizotypy construct would not be complete without an examination of the views of Gordon Claridge, a psychologist at Oxford University (England). He has pursued his interest in schizotypy largely outside the central stream of research and theory in the area (Claridge, 1997). The most distinctive features of his approach to schizotypy concern his propositions regarding: (1) the putative existence of “healthy” manifestations of schizotypy and (2) the proposal that the schizotypy construct has a dimensional (quantitative) structure at the latent level. Before considering these views specifically, it is wise, as always, to consider the intellectual heritage from which these views emerged. Unlike the views of Meehl (1962, 1990) or those I have advocated here and elsewhere (Lenzenweger, 1998, 2006c), Claridge sees schizotypy as a personality trait varying by degree along a continuum. In adhering to the methodological view of his mentor, the British personality psychologist Hans J. Eysenck, as well as guided, in part, by the original content of Eysenck’s conceptualization of “psychoticism” as a personality trait that emphasized impulsivity, antisocial behavior, and aggression, Claridge places his conceptualization of schizotypy squarely within the traditional dimensional view of personality. Indeed, Claridge’s ideas regarding schizotypy have been introduced by his collaborators as consistent with those “writers who conceptualise the spectrum of schizophrenia-­related characteristics as a continuous dimension, akin to other dimensions of personality,” which represents a view “championed by writers such as Eysenck” (Eysenck & Eysenck, 1976; Rawlings, Williams, Haslam, & Claridge, 2008b, p. 1641). Claridge’s specific view of schizotypy has its foundation in the methodological perspective on personality that views all aspects of normal personality as dimensional in

170

SCHIZOTYPY VIEWED FROM THE LABORATORY

nature. This view raises two questions: (1) Is schizotypy best thought of as a component of normal personality? and (2) Does the available evidence support a dimensional view of schizotypy?

Schizotypy as Normal and “Healthy” Psychosis Is schizotypy best thought of as a component of normal personality? Unpacking this further, is schizotypy normal? Is schizotypy part of personality? These issues boil down to whether one views schizotypy as (1) the liability for schizophrenia (e.g., Meehl, Lenzenweger) or (2) a trait characterized by certain cognitive features and psychotic-like phenomena that is part of the general system of personality (Claridge, Bentall). As summarized recently by Rawlings, Williams, Haslam, and Claridge (2008a): Claridge and his colleagues have investigated schizotypy from many points of  view. They have concluded that psychotic traits constitute an essentially healthy dimension of personality [italics added], which in adaptive form contributes to such psychological variations as creativity, non-­threatening hallucinations, and rewarding spiritual and mystical beliefs and experiences. (p. 1670)

What does it mean to argue that “psychotic traits constitute an essentially healthy dimension of personality”? In light of the observations of Kraepelin, Bleuler, Rado, Meehl, and many others, one must ponder carefully the views on schizotypy held by Claridge, particularly as regards the term psychosis. What does it mean to designate an individual or behavior “psychotic”? In traditional psychiatric usage, psychotic as a descriptive term has typically one of three potential meanings: (1) the impairment of reality testing as indicated by the presence of particular psychopathology signs and/or symptoms (hallucinations, delusions, thought disorder), (2) the depth or severity of an impairment (e.g., a psychotic depression, meaning a very deep or profound case of depression), and/or, less frequently, (3) a degree of regression, within a psychodynamic framework, to a developmentally primitive stage of psychological organization wherein thought and experience are characterized by primary process (i.e., not secondary process). In light of how the term psychotic is used, can we conceive of “psychotic traits” as being consistent with a “healthy dimension of personality?”12 To do so, one must 12 Resorting to the locution “psychotic-like” does not get one out of this conceptual pickle if one is serious about the notion that psychotic traits are representative of a healthy dimension of personality.



Begin with a Model

171

really confront the implication of this statement and consider the notion of “healthy psychosis.” My impression of the implicit argument posed by this juxtaposition of terms is that it lacks an appreciation for the clinical and research basis13 supporting the notion of schizotypy as schizophrenia liability. In short, those who see patients in intensive diagnostic or therapeutic capacities may find an eerie unfamiliarity in concepts such as “healthy psychotic traits.” Can we realistically speak of “healthy” schizophrenia or schizophrenia as a healthy dimension of personality? Thus, from the standpoint of clinical relevance, Claridge’s theoretical position seems distinctly ungrounded in the clinical realities of schizotypic pathology. Moreover, from the research standpoint, the literature by and large does not support a view of schizophrenia (the illness) as reflective of an extension of a normal personality trait. Rather, schizophrenia reflects a complex pathological process, not a deviation in a normal personality process or dimension. My students have struggled with the Claridge proposition regarding schizotypy, often wondering if there is an explicit contradiction embodied in this view of schizotypy as a dimension of healthy normal personality. An anecdote from the classroom speaks directly to this possibility. A student once asked me in seminar, “Professor Lenzenweger, this formulation, ‘healthy psychosis,’ puts me in mind of ‘jumbo shrimp’ or ‘Kosher ham.’ Does it make sense to consider psychotic phenomenology as being healthy, or isn’t this an oxymoron?”14 This comment/question led to a fascinating discussion regarding how far one can extend concepts of pathology into the realm of normal personality functioning (e.g., thought disorder vs. divergent thinking, bizarre body image aberrations vs. creativity in imagery, or referential thinking vs. normal self-­consciousness).

Schizotypy as a Fully Dimensional, Quantitative Construct The second issue central to Claridge’s view of schizotypy concerns the basic nature of the construct’s (latent) structure. Is it quantitative in nature at

13 This

issue received considerable discussion at a research workshop convened by NATO on the topic of schizotypal personality in 1993 (see Raine, Lencz, & Mednick, 1995). At the 1993 workshop, one well-known schizophrenia researcher expressed his exasperation at the idea of “healthy” psychosis by saying, “But, Gordon, these are sick people!” 14 I

might add that this particular student was not given to the comedic side of discourse or presentation of ideas. He was genuinely confused by the idea of “psychotic traits” as being “consistent with healthy personality.”

172

SCHIZOTYPY VIEWED FROM THE LABORATORY

both the phenotypic level and the latent level? This issue received considerable discussion during the 1993 North Atlantic Treaty Organization (NATO) workshop on schizotypy held in Tuscany, Italy. At that time, although Claridge maintained a strong commitment to a dimensional view, there were no empirical data available to support a view that the schizotypy construct was quantitatively distributed—­varying by degree (not kind)—at the latent level. Indeed, as the designated commentator on his paper, I noted at the time that all empirical evidence marshaled by Claridge and colleagues in support of the dimensional latent structure of schizotypy came from analytic techniques (i.e., factor analysis) that could not determine whether a latent entity was quantitatively (dimensionally) or qualitatively (taxonically) structured at a deeper level. In that setting, we had the opportunity to highlight the distinction between the measurement of some phenomenon at the phenotypic level and the deeper question regarding the latent structure of the construct in question. One can surely measure a psychopathological feature, symptom, or character in a quantitative manner, but that, in and of itself, does not ensure or mean that the construct measured is dimensional at the latent level. What is the picture painted by the contemporary empirical research corpus regarding the latent structure of schizotypy? In short, the picture is one of discontinuity, which is either representative of a latent taxon (class, natural subgroup) or severe step function (threshold) in the structure of the schizotypy construct. As is presented in Chapter 11 in this volume, there is an abundance of evidence drawing on taxometric and finite mixture modeling studies that are supportive of the discontinuous underlying nature of schizotypy. In brief, we reported (Lenzenweger & Korfine, 1992a) on the taxometric analysis of the PAS that strongly supported a marked discontinuity underlying scores on that index. We replicated this original finding in 1995 (Korfine & Lenzenweger, 1995), and it has been replicated many times since. The corpus of evidence drawn from empirical data is inconsistent with a fully dimensional view of schizotypy such as that argued for by Claridge. Yet one will see claims to the contrary, such as “Suffice it to say that the evidence is strongly weighted in favour of the fully dimensional model” [of schizotypy] (Mason & Claridge, 2006, p. 205). This position is simply incorrect, as the bulk of the evidence that Claridge interprets as supportive of dimensionality comes from (1) a committed position to dimensionality à la Eysenck, (2) visual examination of the distributions of phenotypic psychometric values (remember that distributions of scores cannot resolve the



Begin with a Model

173

latent structure question),15 (3) results of factor analyses of psychometric values (remember that factor analysis is a technique that always finds factors by organizing larger numbers of variables into a smaller number of large “factors”), and (4) a single taxometric investigation. Aside from evidence drawn from the one taxometric study (Rawlings et al., 2008b)—which suffered from marked methodological artifacts (Beauchaine, Lenzenweger, & Waller, 2008)—that argued for a dimensional view of schizotypy, the empirical picture is one in which “the existence of a discrete class of people vulnerable to schizophrenia spectrum disorders is the most replicated finding” (Rawlings et al., 2008b, p. 1640). Regarding Claridge’s theoretical commitment to a dimensional model of personality as reflective of the methodological approach of Eysenck, let us return to the teacher of the student here to see if we can glean any insights that might help illuminate this argument. Was Hans Eysenck himself truly committed to a dimensional view of personality across the board? No, he was not. Eysenck himself stated that he would not wish to dismiss the possibility or even the likelihood that in any random group of clinically diagnosed neurotics there would be found a small number of people who might “constitute a group apart, different not in degree, but in kind, by reason of some specified biochemical error, which is highly predictable in terms of inheritance, and which operates in a manner quite different from anything observed” in the kinship relations of the remainder of that group. (Eysenck, 1958, p. 431)

This view is commensurate with what is known about schizotypy from modern empirical studies of latent structure.

Claridge’s View of Meehl’s Model as “Quasi-­Dimensional” In this context we should also evaluate Claridge’s view of Meehl’s (1990) model of schizotypy as “quasi-­dimensional,” whereas he refers to his own model as “fully dimensional,” as discussed earlier (Claridge & Beech, 1995; Claridge, 1997). What is meant by the term quasi-­dimensional? If we take the word quasi to mean “having a likeness to, having some resemblance to,” 15 The distributions of scores cannot answer a latent structure question. Eysenck (1958) himself noted that “no faith can be put in the distribution of scores on any one test in arguing for or against the continuity hypothesis” (p. 429).

174

SCHIZOTYPY VIEWED FROM THE LABORATORY

we would say that quasi-­dimensional would logically mean “having a likeness to or resembling a dimension.” One would be hard pressed to find an indication in Meehl’s writing that schizotaxia (or, by definition, schizotypy) is in any manner dimensional, quasi or otherwise. I argue that quasi-­dimensional as a descriptor is really merely another way of saying “continuous latent liability with a threshold”—this not what Meehl proposed. Meehl (1962, 1990) himself was quite clear as to the latent structure of schizotypy as reviewed previously—he saw schizotypy as having a taxonic (qualitative) latent structure. As noted, he did speak of “polygenic potentiators,” which could have a dimensional nature; however, schizotypy, according to his model, was taxonic. It may be that Claridge intended the notion of a “quasi-­continuous” model of genetic influences, akin to a polygenic model with a distinct threshold effect, when describing Meehl’s model as “quasi-­dimensional.” In fact, behavior geneticists distinguish between a polygenic model with continuous variation in a phenotype (e.g., height, IQ) versus one in which there is some form of discernible demarcation in the phenotype (e.g., cleft palate, diabetes; see Falconer, 1989). However, Meehl’s model does not encompass the polygenic perspective that embraces fully continuous variation or quasi-­continuous variation. His model, rather, as noted, represents a “mixed model,” whereby a single major schizophrenia­relevant gene operates against a background of polygenic modifier effects (his so-­called potentiators). To review, Meehl was rather clear on this issue—­although not fully understood by some—in advocating for a taxonic view of schizotypy. In Meehl’s view there is no gradation or quantitative variation insofar as schizotypy is concerned. One was either a schizotype or was not; there was no in-­between place. Claridge (1995, 1997), in contrast, advocates a fully dimensional view with continuous variation at the phenotypic level; his model is most consistent with a polygenic model (without a threshold) that reflects a continuous additive model of genetic influences.

Parting Thoughts on Claridge’s Model of Schizotypy In summary, Claridge has emphasized that his view of schizotypy differs from that construct of a broadly similar nature proposed by his mentor Eysenck, namely “psychoticism,” which was an amalgam of aggression and impulsivity. (Psychoticism, incidentally, is a construct that has remarkably little to do with psychosis; see Chapman, Chapman, & Kwapil, 1994.) However, it may be that Claridge has defined the term psychotic in a manner far more similar to that of Eysenck than he (Claridge) maintains. The notion



Begin with a Model

175

of healthy psychosis strikes me as inherently illogical and inconsistent with both clinical experience and the research literature on schizophrenia as an illness. Finally, the taxometric and finite mixture modeling results available across many studies support a taxonic view of schizotypy in contrast to one study favoring a dimensional conceptualization (see Beauchaine et al., 2008).

A Model-­Guided Strategy to Bridge Schizotypic Psychopathology and Schizophrenia via Latent Schizotypy When I began my empirical investigations into schizotypic psychopathology and schizophrenia in the middle 1980s, there were still relatively few laboratory studies of what one would term schizotypy. Aside from the work of the Chapmans at Wisconsin (and their students), the methods of the experimental psychopathology laboratory had not been fully applied to a deep probing of the schizotypic proposition—in short, probing whether or not schizotypes would manifest many of the same deficits, albeit in diluted form, as those characteristic of schizophrenia. The empirical planks, drawn from the laboratory, that would bridge schizotypic personality and psychopathology to schizophrenia needed to be fashioned and put in place. Meehl’s model (1962, 1964, 1990) would serve as a guide in this bridging process. This enterprise represented an exciting criterion and construct validation proposition. If one could systematically explore aspects of neuro­ cog­nitive, personality/psychopathology, psychophysiological, social cogni­ tive, somatosensory, and familial history of psychopathology among well-­characterized schizotypes, then the strands in the network linking schizotypic states with criteria of validity from the schizophrenia realm would, in time, speak directly to the construct validity of Meehl’s schizotypy model. The goal, therefore, was to follow the path laid down by Cronbach and Meehl (1955) in empirical efforts to establish criterion and construct validity of schizotypy. Thus I followed a path defined implicitly by the seminal notion of the hypothetical construct as advanced by MacCorquodale and Meehl (1948). In this instance, schizotypy as the hypothetical latent construct was central to the whole venture. The ideas of Robins and Guze (1970) were relevant in a pragmatic manner in developing a criterion validity research strategy. Recall that Robins and Guze (1971) stressed empirical evaluation in several domains when attempting to establish the validity of a diagnostic entity, namely: (1) clinical description/phenomenology, (2) labo-

176

SCHIZOTYPY VIEWED FROM THE LABORATORY

ratory studies, (3) delimitation from other disorders, (4) follow-up study, and (5) family study. These authors argued that the pattern of results across this set of domains could be taken to be supportive of the validity of a psychiatric illness, a view consistent with that embodied in the notions of criterion and construct validity (à la Cronbach & Meehl, 1955). Finally, by studying schizotypy across multiple domains (e.g., neurocognitive, family history), we could learn how consistently the correspondences between schizophrenia proper and schizotypic pathology emerged. If the correspondences were to hold up in a robust fashion, then one could have more confidence in the likelihood that a common liability construct might underlie both expressions of pathology (namely schizophrenia and schizotypic pathology; see Chapter 12, this volume, on the “damn strange coincidence”).

Chapter 7

Genetics, Genomics, Phenotypes, and Endophenotypes The Challenge of Complex Disease

The

whole of prior genetic and contemporary genomic1 research into schizophrenia owes its existence to the clinical observations of both the biological family members of individuals thought to be suffering from schizophrenia and those deeply impaired individuals who appeared in office practice for the treatment of schizophrenia-like personality deficits. As mentioned earlier, the early psychiatrists—such as Kraepelin and Bleuler— spent years to decades with their schizophrenia-­affected patients in psychiatric hospitals. Kraepelin worked at the Munich Psychiatric Clinic (later the Max Planck Institute for Psychiatry) in Germany. Bleuler, Jung, and, later, Manfred Bleuler worked with schizophrenia patients at the Burghölzli Clinic (Zurich, Switzerland; Figure 7.1). In doing so, they got to know the family members of the affected patients well. They observed that one often 1 The

terms genetics and genomics are often used interchangeably; however, there are meaningful differences between the two concepts. Following the National Genome Research Institute’s glossary (www.genome.gov), gene refers to the functional and physical unit of heredity passed from parent to offspring. Genes are pieces of DNA, and most genes contain the information for making a specific protein (though coding regions usually make up only a small portion of each gene). In contrast, genome refers to all of the DNA contained in an organism or a cell, which includes both the chromosomes within the nucleus and the DNA in mitochondria. Genetics refers to the scientific study of heredity, or how particular qualities or traits are transmitted from parents to offspring. Genomics refers to the scientific study of an organism’s entire genome; in humans, the study of all the genes in a person, as well as the interactions of those genes with each other and with the environment.



177

178

SCHIZOTYPY VIEWED FROM THE LABORATORY

FIGURE 7.1.  Top: Emil Kraepelin and the Munich Psychiatric Clinic (later to become the Max Planck Institute for Psychiatry) in Munich, Germany, where Kraepelin treated patients with schizophrenia. Bottom: Eugen Bleuler and the Burghölzli Clinic in Zurich, Switzerland, where Bleuler, Carl Jung, and, later, Bleuler’s son Manfred Bleuler treated patients suffering from schizophrenia, as well as conducted psychopathology research.

saw higher rates of schizophrenia proper, as well as what we would term schizotypic conditions, among the biological relatives of these patients. As noted earlier, the clinicians in office practice in the early part of the 20th century frequently encountered deeply disturbed, schizoid, quasi-­psychotic individuals in therapy work and quickly learned that such individuals were not well suited for psychotherapy, usually psychoanalysis. Many of these clinicians speculated about connections between these patients and the likelihood of schizophrenia being in their families and, typically, the likely presence of increased schizophrenia liability, possibly genetic, in the patients themselves. Interestingly, although many psychoanalysts would subscribe to psychodynamic explanations for the etiology of schizophrenia (see Holzman, 1976, for a historical review of these viewpoints) and would attempt to treat the illness via this psychological method, the two preeminent psychoanalysts of the last century—­Sigmund Freud and Carl G. Jung—were quite clear that they saw schizophrenia as hailing from constitutional factors and beyond the reach of psychological interventions. Freud viewed psychotic illness, principally schizophrenia, as a form of narcissistic neurosis that should not be treated with psychoanalysis (see Freud, 1905, 1914). Jung had a great interest in schizophrenia early in his career and conducted experimental psychopathology word-­association studies in patients. However, he also thought that the condition should not be treated through psychological means. Jung thought that, ultimately, some sort of neurobiological factor would likely be determined to be the cause of schizophrenia. Jung referred to this unknown, but likely, neurobiological factor as “toxin X” (Jung, 1907).

Genetics, Genomics, Phenotypes, and Endophenotypes

179

Thus, it is clear that the descriptive psychopathology master observers, Kraepelin and Bleuler, who saw many cases of schizophrenia, frequently observed oddities among the biological relatives of schizophrenia patients as evidence that, at a minimum, the illness was familial. As discussed previously, office practitioners noted what they believed were phenomenological consistencies between schizophrenia and schizophrenia-like conditions, suggesting the notion of schizophrenia liability manifesting itself in forms that fell short of the illness proper. Über-­analysts Freud and Jung, as noted, gave a big push to the notion that the field should be looking at constitutional factors if one hoped to discover the cause of schizophrenia and discouraged psychological (i.e., psychoanalytic) interventions. Oddly enough, many of these early guideposts that should have kept the field on track in its search for the etiology of schizophrenia were ignored. From the 1920s through the early 1960s, socialization theories of the etiology of schizophrenia abounded, genetic research was looked on askance (particularly in light of the horrors of World War II, Nazi-era eugenics, and the Holocaust) and struggled to survive as a mode of scientific inquiry, and the psychoanalytic treatment of schizophrenia was having a heyday.2 The pendulum would eventually swing back to a position favorable to genetic research and generate considerable empirical data regarding the genetic basis of the liability for schizophrenia, schizotypic psychopathology, and related constructs. An excellent overview history of these historical trends can be found in Gottesman’s (1991) landmark monograph, Schizophrenia Genesis. In this chapter I examine a variety of methodological and conceptual issues that bear on genetically oriented research that links schizophrenia with schizotypic psychopathology. This corpus of work interweaves several threads, such as (1) the necessity of a latent liability construct, (2) quiet “unexpressed” transmission of this latent liability, (3) schizotypic psychopathology as an alternate expression of the liability, and (4) the endophenotype framework for schizotypy research. The focus is on necessary principles for the pursuit of research in this area, as well as a discussion of selected studies that illustrate highly creative insights that have advanced our understanding of schizophrenia, schizotypic psychopathology, and indicators of schizotypy. However, before addressing these seminal studies, we must first confront some terribly challenging features of the schizophrenia puzzle and consider notions such as complex disease, heterogeneity, endophenotypes, 2 This

was due in part to the fact that psychoanalysis was essentially the only available treatment prior to the introduction of antipsychotic medications in the 1950s and that the tools for doing genetic research then were primitive.

180

SCHIZOTYPY VIEWED FROM THE LABORATORY

and epigenetics. I like to consider such notions as “things to bear in mind” when contemplating schizophrenia and schizotypy. By “bear in mind,” I do not mean to consider them lightly in some sort of cocktail-party “lite” intellectual manner, but rather that these ideas must be kept in mind continuously to advance our understanding of schizophrenia and schizotypy.

Complex Diseases, Assumptions, Endophenotypes, Epigenetics One of the most interesting clinical learning experiences of early career psychologists and psychiatrists is the discovery of just how variable the symptom picture of schizophrenia and schizotypic psychopathology can be. In preparing for clinical work, beginning psychologists and psychiatrists are taught that schizophrenia patients typically present with psychotic features such as hallucinations, delusions, and thought disorder. The symptoms are described and neatly organized into categories, which are committed to memory, and a mental image of schizophrenia begins to take shape in the mind of the student. The same thing happens for schizotypic psychopathology. The student learns that such people are described as odd, eccentric, and unusual in thought, affect, speech, and appearance, albeit nonpsychotic, and conjures an image of a putative prototypic schizotype. Then, an interesting thing happens: The theory and textbook rubber of the lecture hall meet the road in the form of real people, displaying real symptoms, and the beginning psychopathologist is knocked over intellectually by the great heterogeneity of symptom manifestations and the subtlety of clinical skills needed to elucidate what is often a foggy diagnostic picture. Many trainees recoil from the task of diagnosis in these cases. They seem genuinely baffled by the fact that every (validly) psychotic person seems quite different from another who is psychotic. More disconcerting is the fact that many of the patients suffering from schizophrenia, for example, do not fit neatly into the categories (subtypes) or along the dimensions that were studied in the textbooks. Thus real patients often bear little resemblance to the preconceived image of what schizophrenia is “supposed to” look like. I often tell my students that they will have the experience of hikers when they begin to integrate their clinical experience with their lecture hall and textbook preparation when confronted with psychotic illness. There is the map and there is the territory, but one should not confuse the map for the territory. Coming to know the territory will take time, patience (as well as patients), and require a fairly high tolerance for ambiguity and complexity. Schizo-

Genetics, Genomics, Phenotypes, and Endophenotypes

181

phrenia is a complex disease pheomenologically. Importantly, this complexity is highly relevant to our search for clues to etiology and pathogenesis.

On the Nature of a “Complex Disease” and the Nature of the Complexity of Schizophrenia A number of disease phenotypes have shown themselves to have an underlying Mendelian pattern of inheritance. This is the case in which the disease phenotype is reliably related to the presence or absence of a given gene and the illness follows, by and large, transmission rules laid out by the Bohemian monk Gregor Mendel nearly 150 years ago. Many students will recall the genetics they learned in high school, particularly as regards tall versus short and smooth versus wrinkled garden peas. This form of genetic understanding is known as Mendelian genetics. In the search for actual genes that conform to Mendelian inheritance and that underlie a particular disease, positional cloning techniques (a molecular genetics methodology) have helped to point the way to actual genes involved in physical diseases. Unfortunately, many forms of psychopathology do not reveal themselves among biologically related individuals in a manner that is consistent with strictly Mendelian inheritance. These disorders have not yielded their genetic nature when subjected to genetic research techniques such as those used in the study of classically Mendelian disorders. The diseases are often described as “polygenic,” “multifactorial,” or “complex” in nature (Risch, 2000). Thus conditions that do not yield a genetic picture of inheritance consistent with simple Mendelian principles of transmission reflect a “complex genetic” nature, and we speak of the diseases that result from these complex genetic substrates as “complex diseases.” In referring to a complex disease, we normally mean a complex disease phenotype3 and complex underlying genetic components to such a disease phenotype. Typical Mendelian diseases can be detected through what is known as linkage analysis, or a technique whereby the associations between polymorphic DNA makers and the disease phenotype in related individuals are tested. In linkage analysis, it is assumed that when a strong association between a known DNA marker and the disease phenotype is detected, then the gene responsible for a disease (i.e., disease locus) resides somewhere nearby the marker (or includes the marker). Mendelian trnasmission (dominant or recessive) can also often be traced rather easily via observed phe3 Phenotype

refers to observable characteristics of an organism produced by the organism’s genotype interacting with the environment; genotype refers to genetic constitution of an organism.

182

SCHIZOTYPY VIEWED FROM THE LABORATORY

notypes in an extended family over two or three generations. This research approach has worked reasonably well for diseases with an underlying Mendelian genetic nature but has, by and large, failed to generate convincing results in the study of complex diseases, such as schizophrenia or other psychiatric conditions (see Risch, 2000; Merikangas & Risch, 2003). “Where misdiagnoses, heterogeneity, complex inheritance or frequent phenocopies are abundant—­particularly when they result in the inclusion of individuals who have a different disease or no disease at all in the affected group—­ linkage analysis can fail even in very large cohorts” (Botstein & Risch, 2003, p. 229), and, indeed, all of these potentially confounding characteristics (basically reflective of false-­positive classifications) are commonly true of psychopathological conditions. According to Merikangas and Risch (2003), the sources of the complexity observed in complex diseases hails from (1) lack of an adequately valid classification system in psychopathology4 and (2) the complexity of the pathways from the genes causing illness to the actual illness phenotypes. The latter issue regarding the pathways implies the presence of multiple genes, as well as the complexity of the roadway—if one will—­leading from the actual genes to the illness expressions. There are many factors that preclude a neat, oneto-one relationship between genetic factors and expressed psychopathology—­ including schizophrenia—and this list includes factors such as: penetrance (i.e., probability of phenotypic expression among individuals with a susceptibility gene), variable expressivity (i.e., variation in the clinical expression associated with a particular gene), gene–­environment interaction (i.e., differential expression of a genotype in the presence of particular environmental exposures), pleiotropy (i.e., capacity of the same genes to manifest several different phenotypes simultaneously), genetic heterogeneity (i.e., different genes leading to indistinguishable phenotypes), and polygenic and oligogenic5 models of inheritance (i.e., simultaneous contributions of multiple genes rather than Mendelian single-gene models are characteristic of the mental disorders.) (Merikangas & Risch, 2003, p. 628) 4 The

nature of the relationship between the genetic factors responsible for psychopathology and how knowledge of such factors may play a role in increasing the precision of the nosological system in psychopathology has been addressed in detail by Kendler (2006).

5 The term oligogenic is used to describe what is essentially a polygenic system of inheritance, but one which has some reasonably limited number of genes in play rather than what can be thought of as a nearly quasi-­infinite number of genes, as implied by the term polygenic. The term mutagenic is also used synonymously with oligogenic. Thus, oligogenic allows for number of genes at work in a complex disease, but a number that is somewhat limited and that represents what Risch (2000) describes as “a tractable degree of complexity” (p. 847).

Genetics, Genomics, Phenotypes, and Endophenotypes

183

What must be kept in mind when considering the question of illuminating the genetics of schizophrenia and schizotypy is that this disease entity (schizophrenia) and its related manifestations (e.g., schizotypic personality features) represent a complex disease construct, and the underlying nature of the liability (in this case, what we think of as schizotypy) is most likely going to reveal itself as having knotty characteristics such as those noted by Merikangas and Risch (2003).

On the Nature and Assumptions of “Genetalk”: What We Should Mean When We Say Something Is “Genetic” It is not unusual for students learning about the worlds of behavioral genetics, molecular genetics, and genetic epidemiology to speak of this or that behavior or condition as “being genetic.” For example, a student might say “negative symptoms are genetic in schizophrenia” or “schizotypal personality disorder is genetic.” This is an imprecision in language that can be clarified for most students when they learn to distinguish between a phenotype and genetic influences on a phenotype. Thus they come to say “negative symptoms of schizophrenia appear to be subject to genetic influences,” or “schizotypal personality disorder is known to be subject to genetic influences.” The latter mode of expression captures the statistical relationship that is known to exist between the genetic influences and the construct in question. It also serves to remove the imprecision implied in simply calling something “genetic” (i.e., many other factors probably play a role in the emergence of negative symptoms or SPD; there is no one-to-one relationship here between genes and phenotype). Given the massive amount of molecular genetic research that now pours from the psychopathology journals on a monthly basis, it is not unusual to hear a new form of expression in the seminar room, in the clinical case conference, or at grand rounds or colloquia. This new form of expression has been described as “genetalk” by the psychiatric geneticist Kenneth S. Kendler (2005). It goes something like “X is the gene for Y” or, by way of an example, “The Val-Val COMT polymorphism is the gene for schizophrenia.” Kendler (2005) provides a useful tutorial on why this form of expression—or genetalk—is perhaps best avoided. He outlines five criteria that should be met before one can justifiably speak of “X as the gene for Y,” and, as one might expect, genetic findings in schizophrenia (and throughout psychopathology generally) fail to meet these five criteria. The criteria for judging the validity of the claim of “X is a gene for Y” are: “(1) strength of association of X with Y, (2) specificity of the relationship of X with Y,

184

SCHIZOTYPY VIEWED FROM THE LABORATORY

(3) noncontingency of the effect of X on Y, (4) causal proximity of X to Y, and (5) the degree to which X is the appropriate level of explanation for Y” (Kendler, 2005, p. 1245). Kendler (2005) suggests that the typical notions of a gene and how a gene is supposed to exert its influence on a phenotype represent problematic areas in discourse in psychopathology genetics. Following Kendler’s analysis, it is useful to simply note that no genes thought to be related to the development or pathogenesis of schizophrenia meet the criteria set out by Kendler to justify the expression, “X is the gene for Y” or “X is the gene for schizophrenia.” In sum, it remains advisable to speak of genetic influences that are associated with the phenotype of schizophrenia or variation in genetic influences that is known to be associated with variation in the schizophrenia phenotype. Although we are looking for genes that are responsible for schizotypy, which are by definition causally related to the development of schizophrenia or schizotypic psychopathology, we should be alert not to overstate what we know about any genetic influences that we do discover. Finally, it is essential to keep in mind the levels of analysis framework engaged when considering the study of genes and behavior—­simply put, it is a very long and winding road from gene to behavior, and there are substantial levels of organization lying within this road. Recall that genes code for proteins, proteins influence structure and function of cells, cells organize into higher order units (organs), organs are organized within systems, systems are organized within the person, and the person functions within the world of environmental influences (including other persons). Psychopathological disorders or constructs do not reside on the genome; there are no DNA addresses for clinical schizophrenia per se.

A Further Conceptual Necessary Excursus (or Horror Ride): The Big Assumption At the beginning of my seminars I often ask my students, “What is our unit of analysis in this course?” Oftentimes, the students will respond quickly, though a little hesitantly, “schizophrenia.” I normally respond by saying, “Yes, that could be our unit of analysis, but do you think schizophrenia is a singular, unitary thing, something that can be thought of as truly a unit of analysis?” I follow with, “Is schizophrenia a single thing—­namely, a homogeneous, coherent, indivisible whole?” The students appear perplexed, at which point I assume the seminar has begun. Much discourse in research on schizophrenia (including discussions of schizotypy and schizotypic psychopathology) is predicated on the fundamental assumption that schizophrenia is indeed the unit of analysis in the experi-

Genetics, Genomics, Phenotypes, and Endophenotypes

185

mental psychopathology of schizophrenia. The implicit assumption undergirding virtually all research—typically left unaddressed—is that schizophrenia is a plausible, coherent “unit.” Many workers will often pay lip service to this issue of heterogeneity, both at the causal and phenotypic levels, to show that they are aware of the matter but then proceed to approach schizophrenia as if it were a unitary whole. What is particularly fascinating about this issue is that the person who named the illness—Eugen Bleuler (1911/1950)—noted himself that we were probably talking about the group of schizophrenias. Or, if one were to state it differently, what we call schizophrenia actually represents a collection of similar-­appearing illnesses that were sufficiently similar—on a phenotypic level—as to encourage a conceptual taxonomy that placed them under one diagnostic umbrella or organizing rubric. Although many psychopathologists working in labs around the world will speak of schizophrenia as a quasi-­unitary construct (admitting the possibility of heterogeneity), the fundamental question about the nature of schizophrenia that continues to go unanswered concerns the question of heterogeneity of illness. This heterogeneity question can be addressed at both the causal level and the phenotypic­expression level. It is the rare study that takes heterogeneity head-on. Instead, most studies seek to emphasize the absence of differences on certain variables within a sample in the hope that the lack of such differences will support an assumption of homogeneity. Let us think about this issue in a more pragmatic manner. What if there is not just one thing called schizophrenia? What if schizophrenia is truly a “collection” of similar-­appearing illnesses or a genuine “group of schizophrenias”? The latter view is strongly advocated by those scientists who support a “common disease–rare allele” hypothesis for schizophrenia (McClellan, Susser, & King, 2007). In contrast to the prevailing view that schizophrenia results from the additive effect of multiple common genes (the “common disease–­common allele” hypothesis), the “common disease– rare allele” hypothesis posits that schizophrenia is genetically highly heterogeneous, reflective of highly penetrant, individually rare alleles.6 That is, it is a collection of similar-­appearing symptom pictures caused by many syndromes with different etiologies. The student of psychopathology is encouraged to ponder, contemplate, and mull over this “heterogeneity question.” Let us ask it again. What if there is not just one thing called schizophrenia? What if it truly is a “collection” of phenotypically similar illnesses or a genuine “group of schizophre6 The

implications of the “common disease–rare allele” theoretical position are profound. It is a view that turns the traditional psychiatric genetics perspective on its head and argues against combining research data across families.

186

SCHIZOTYPY VIEWED FROM THE LABORATORY

nias”? If what we call schizophrenia is truly more than one illness, then the implications of this reality would be profound. If schizophrenia does actually encompass a number of similar-­appearing illnesses, then one could make the argument that we need to bring the schizophrenia research machine to a halt—­unplug the neuroimaging magnets, shut down the DNA analysis, turn off our neurocognitive and psychophysiological task computers— until we resolve this very basic and fundamental nosological issue. Clearly, this is not going to happen, but I encourage my students to ponder this question deeply. In most instances, lip service or a nod in the direction of heterogeneity is given by researchers, and quasi-­nearly all schizophrenia research continues apace as if we are studying one unitary, singular entity. This remains a huge assumption. Nowhere else does the assumption matter more, perhaps, than in an effort to understand the genetics of schizophrenia and schizotypy. Are we looking for a powerful set of genes that can account for all forms of schizotypy (i.e., schizophrenia liability)? Or are we looking for a variety of different genes, each of which may be a biological subtype of schizophrenia (or its possible nonpsychotic schizotypic manifestations)? The data do not allow us to make an informed choice here; thus we labor on under the implicit assumption—the big assumption—that schizophrenia is one thing (perhaps with a little symptom variability along well-known dimensions, such as positive and negative symptoms; see Fanous & Kendler, 2005). We must consider that schizophrenia may, in fact, not be just a single, unitary disease. It is quite conceivable that there are actually different schizophrenias. I mean really different—as in a collection of vaguely similar symptom pictures that correspond to etiologically distinct mechanisms.7 I do not see this as some sort of nosological nihilism, but rather a fact we need to face and a challenge we actually need to resolve to move forward. Nor do I view this issue as something of an arcane concern discussed by ivory tower academics who prefer to ponder the esoteric in psychopathology research rather than see patients. Simply stated, heterogeneity represents, perhaps, the single greatest obstacle to progress in schizophrenia research, including genetic research on the disorder. Heterogeneity is probably the Achilles’ heel of all schizophrenia research. If schizophrenia research is to advance appreciably, heterogeneity within phenotype and, most likely, the genotype must be resolved. 7 The

issue of etiological heterogeneity is both conceptually and empirically challenging, but it has been confronted in relation to other complex illnesses, such as coronary artery disease. The work of the University of Michigan geneticist Charles Sing and colleagues on etiological heterogeneity and the possibility that different subsets of genes will influence phenotype variation in different subsets of people in the same population in a nonadditive fashion is well worth consulting (Sing, Stengard, & Kardia, 2003, 2004; Dyson, Frikke-­Schmidt, Nordestgaard, Tybjaerg-­Hansen, & Sing, 2007, 2009).

Genetics, Genomics, Phenotypes, and Endophenotypes

187

The Endophenotype: An Essential Concept in Experimental Psychopathology On the assumption that schizotypy (i.e., schizophrenia liability) has its basis largely in a heritable genetic substrate, that it is present from conception onward and reflects the brain-based developmental unfolding of a pathological process over the life course, then it is reasonable and highly plausible that the underlying liability will manifest itself in some fashion long before the emergence of psychotic symptoms of the illness, even before the appearance of the so-­called prodromal symptoms of schizophrenia (see Chapter 10, this volume). This simple but highly important conceptual and empirical point was implied clearly in Meehl (1962). The genotype for schizophrenia, which can be manifested early as nonpsychotic schizotypic features as well as through other subtle anomalies, will always be detectable if an appropriately sensitive assay is done. If the brain, behavior, or psychological experience of the schizotypic person is examined closely, then evidence of this underlying liability will be detected. One should be able to detect some internal manifestation of this genotype below the surface, or within the person. The embodiment of this fundamental theoretical assumption is the concept of the endophenotype (Gottesman & Shields, 1972, 1973; Gottesman & Gould, 2003). The endophenotype model is an essential building block of the experimental psychopathology approach. Irving I. Gottesman, the renowned behavioral geneticist and psychopathologist, is the principal architect and theoretician responsible for the endophenotype construct. Although his 2003 paper with Gould that documents the background and meaning of the endophenotype concept has rapidly become a modern classic8 and represents “required reading” for any informed psychopathologist, the endophenotype model has long characterized Gottesman’s thinking about the genetics of schizophrenia. The notion of the endophenotype did not begin in 2003; rather, Gottesman and his then colleague James Shields advocated the notion clearly in their landmark volume Schizophrenia and genetics: A twin study vantage point (1972), as well as in a 1973 position paper in the British Journal of Psychiatry. The endophenotype concept reflects the impact of two major intellectual currents, one deriving from the biological literature and the other from theoretical and methodological work on hypothetical constructs. Inspired in part by the insect biology literature (John & Lewis, 1966), as well as by the seminal substantive distinction between “hypothetical constructs” and “intervening variables” made by MacCorquodale and Meehl (1948; see also Cronbach & Meehl, 8 The

Gottesman and Gould (2003) article has been cited more than 1,000 times within the first 7 years postpublication.

188

SCHIZOTYPY VIEWED FROM THE LABORATORY

1955), Gottesman and Shields advanced the argument that endophenotypes should be considered internal phenotypes that might someday be detectable with either “a biochemical test or by microscopic examination” (1972, p.  319). An essential notion here is that the endophenotype represents a hypothetical latent entity that cannot be directly observed with the unaided naked eye; rather, an appropriate technology would be needed to “see” the endophenotype. Although somewhat dormant during the decades following the initial introduction of the concept, the endophenotype concept was imported into high-risk research (Erlenmeyer-­Kimling and colleagues in the New York High Risk Project) (e.g., Erlenmeyer-­Kimling and Cornblatt, 1987), the study of schizophrenia relatives (Holzman et al., 1974, 1988), and schizotypy investigations (Lenzenweger & Loranger, 1989a, b). Lenzenweger (1999b) argued strongly for the use of endophenotypes to advance schizophrenia research.9 The reintroduction of the endophenotype as a concept in 2003 (Gottesman & Gould, 2003) provides an example of how psychopathology—not unlike other fields—often needs to be reminded of important ideas before the intellectual fertility of an idea is fully appreciated. What is an endophenotype? According to Gottesman and Gould (2003; see also Gould & Gottesman, 2006), an endophenotype is a measurable component, unseen by the unaided naked eye, that lies along the pathway between disease and distal genotype. An endophenotype may be neurophysiological, endocrinological, neuroanatomical, cognitive, or neuropsychological in nature, and it can include configured self-­report (e.g., inventory) data. Gottesman and Gould (2003) argue that the endophenotype represents a simpler clue to genetic underpinnings than the disease syndrome itself. They take considerable care to distinguish the endophenotype notion from other concepts, such as “biological marker,” “intermediate phenotype,” “vulnerability marker,” or “subclinical trait.” A key distinguishing feature of an endophenotype is the requirement that an endophenotype must be cofamilial and heritable, whereas these other concepts do not imply or require either as a definitional criterion. What are the criteria for an endophenotype? Again, working from the original Gottesman and Gould (2003, p. 639) position paper, an endophenotype should meet five important criteria (see Table 7.1). Gottesman and colleagues (Gould & Gottesman, 2006; Chan & Gottesman, 2008) subsequently added a sixth criterion for an endophenotype, 9 Experimental

psychopathology has long embraced the endophenotype concept, whereas psychiatry has really only begun to do so since the 2003 paper by Gottesman and Gould. This may reflect, in part, the former’s research tradition, including a close relationship to the methods of the psychological science laboratory, in which an emphasis on detecting disruptions in underlying processes has been a central focus for decades.

Genetics, Genomics, Phenotypes, and Endophenotypes

189

TABLE 7.1.  Criteria for an Endophenotype 1. The endophenotype is associated with illness in the population. 2. The endophenotype is heritable. 3. The endophenotype is primarily state-independent (manifests in an individual whether or not the illness is active) but may require a challenge to elicit the indicator. 4. The endophenotype is more prevalent among the ill relatives of ill probands compared with the well relatives of the ill probands (i.e., within families, endophenotype and illness cosegregate). 5. The endophenotype found in affected family members is found in nonaffected family members at a higher rate than in the general population. 6. The endophenotype should be a trait that can be measured reliably and ideally is more strongly associated with the disease of interest than with other psychiatric conditions.

Note. Adapted from Gottesman and Gould (2003, p. 639) and Chan and Gottesman (2008, pp. 962– 963).

namely, that the putative endophenotype can be reliably measured and be relatively specific to those persons with conditions related to the disorder (i.e., it should be found in those persons thought to carry the liability for a particular disorder at a higher rate than among those persons who do not carry the liability, such as unaffected persons in the general population). A visual model of the endophenotype concept is helpful for understanding just what is meant by this term. Figure 7.2 depicts the key ideas of the endophenotype concept in relation to other aspects of the schizophrenia liability landscape. It is important to note that this schematic could be applied to disorders other than schizophrenia, such as bipolar disorder (see Gould & Gottesman, 2006) and to nonpsychiatric disorders as well. As can be seen in the figure, endophenotypes have their basis in the genetic substrate for the illness (although the precise connection may not be clear until the genetics is fully understood), and their appearance precedes both prodromal features of schizophrenia and manifest illness. The probability surface depicting the joint interaction of liability, environmental stressors, and time—known as a reaction surface—can vary considerably. Nodes and regions of the reaction surface that rise above hypothetical thresholds (the planes running through the surfaces) represent likelihoods suggesting the emergence of spectrum (or subclinical) variants of schizophrenia and, at higher levels, full-blown disorder expressions. What role does the endophenotype concept play specifically in relation to schizophrenia and, by implication, schizotypy? Given that most persons vulnerable to schizophrenia may never show flagrant psychosis or easily detectable clinical signs and symptoms of schizotypic personality

Liability to Schizophrenia

Reaction Surface Schizophrenia Schizophrenia Spectrum

Envi

ronm

Harmful

ent

Protective -9 Months

25 Years

Age

PRODROMAL SYMPTOMS

Candidate Endophenotypes

working memory

sensory motor gating

personality traits

QTLs in Genome

m ic s T r a n s c ri p t o

i bioinformatic n o inspirations

glutamatergic mechanisms glial cell abnormalities

Proteomics

etc.

epigenetic influence

SYMPTOMS

candidate regions 1q41, 1q42.1 22q11.21 ? 8p21-22 6p22.3 15q14 13q14-21 1q21-22 6p21.3 10p11-15 13q32-34 2p, 2q Epistasis + g x e

candidate genes DISC1 COMT,VCFS ? NRG1, PPP3CC DTNBP1 CHRNA7 HTR2A RGS4 TNFA

?x?

FIGURE 7.2.  Endophenotypes are characterized by simpler neurobiological and genetic antecedents than exophenotypic psychiatric disorders, thereby employing optimal reductionism. Schizophrenia is associated with a number of candidate genes and chromosomal regions, the influence of which can be observed either at the levels of behavior or through endophenotypes. Endophenotypes, located closer to genes in the pathway from genes to behaviors, have fewer genes associated with them and thus are more amenable to genetic investigations and studies in model systems. This skeleton (genes to endophenotypes to behaviors), which allows for epigenetic, “environmental” and purely stochastic influences on clinical observations, can be applied to other diseases of complex genetics with the input of disease-specific candidate genes/regions and endophenotypes (Gottesman, 1997; Gottesman & Gould 2003; Sing, Zerba, & Reilly, 1994; Sing, Haviland, & Reilly, 1996). Copyright 2008 by Irving I. Gottesman and Todd D. Gould. Reprinted by permission.

190

Genetics, Genomics, Phenotypes, and Endophenotypes

191

f­ unctioning, the schizotype researcher has needed to find ways to detect schizotypy using more sensitive detection approaches (i.e., various laboratory and psychometric measures). Examples of potential endophenotypes for schizophrenia would include, but not be limited to, deviance in working memory, sustained attention, smooth pursuit eye tracking, sensory gating, thought disorder, and schizotypy-­related psychometric profiles. Considerable effort has been expended to discover valid objective indicators of schizotypy that function efficiently across a range of clinical compensation as well as mental state and that are capable of detecting liability even in clinically unexpressed (nonsymptomatic) cases. Such indicators, psychometric and otherwise, that are the focus of this research are, in many instances, endophenotypes. One might reasonably ask, What benefits accrue from the endophenotype concept and the identification and study of endophenotypes? Chan and Gottesman (2008, pp. 958–959) described the probable benefits as: 1. Physiological and more elementary-based endophenotypes may more directly reflect the activities of synaptic and other neuronal mechanisms than does the more complex illness itself, and therefore they are more likely to reflect genes with larger effect sizes. 2. Both the patients and their unaffected relatives may show a fairly extensive range of scores on the endophenotypes, making such measures ideal for quantitative trait linkage analysis (analysis of quantitative measurements related to the clinical phenotype will provide more statistical power to detect linkage, compared with the smaller number of clinically defined psychiatric relatives/patients). 3. To the extent that the biology of the endophenotype is understood or can be investigated via brain-­imaging studies and infrahuman animal model research, candidate genes can be identified more systematically in the areas of linkage. 4. Endophenotypes may lend themselves directly to the use of animal models (Gould & Gottesman, 2006). The identification and resolution of valid endophenotypes for schizotypy have been guided by the wish to detect them not only for their obvious potential predictive power and their promise for illuminating underlying pathology but also, importantly, for their likely impact on possible genetic investigations into schizophrenia (Matthysse & Parnas, 1992). Despite the thousands of linkage and association studies done in schizophrenia (Allen et al., 2008), the vast majority of them have relied on a schizophrenia diag-

192

SCHIZOTYPY VIEWED FROM THE LABORATORY

nosis as the phenotype serving as the unit of analysis. However, due to sample size and the relatively low frequency of appearance of the disorder in schizophrenia-­affected families (≈6.5%; Kendler et al., 1993), the vast majority of such studies have been statistically underpowered. What does this mean? This means, simply, that even if linkage or association between a locus and schizophrenia validly existed within a study sample, the study would not have the statistical ability (power) to correctly detect it.10 A practical consequence of this for the scientific literature on the genetics of schizophrenia is a dramatic increase in the risk of false-­negative reports11 (i.e., failing to detect linkage that is really present; Matthysse & Parnas, 1992). Thus the concept of the endophenotype has major implications for the design and analysis of future genetic studies in schizophrenia (and in other forms of psychopathology as well). Gottesman and Gould (2003) have argued that inclusion of endophenotypes (even if not always so named by others) in research investigations of the genetics and familiality of schizophrenia is likely to enhance the statistical power of those efforts. Support for this position has been demonstrated through careful statistical modeling. Even when putative indicators are only modestly correlated with latent liability, the increment in statistical power gained through the inclusion of endophenotypes in studies is substantial (e.g., Smith & Mendell 1974; Matthysee & Parnas, 1992; see also the innovative proposal by Sung, Ji, Levy, Matthysse, & Mendell, 2009 as regards endophenotypes and power). Indeed, endophenotypes have proven to be essential in detecting linkage for schizophrenia (Freedman et al., 1997; Matthysse et al., 2004); they are critical in aiding studies achieve power beyond the standard phenotype.

Clarifications, Distinctions, and Critique: The “Biomarker” and “Intermediate Phenotype” Concepts As the endophenotype concept has “gathered steam” in schizophrenia research, it has become evident that two other concepts may generate confusion in relation to endophenotype. The other concepts are “biomarker” and “intermediate phenotype.” Let us consider the term biomarker. The easiest way to remember the distinction between these terms is that all endophenotypes are, by definition, biomarkers, but not all biomarkers are endo10 From

the standpoint of the economics of scientific research funding, it is rather staggering to realize that the many millions of research dollars spent on previous linkage and association studies in schizophrenia have been invested in studies with a low probability of delivering the hoped-for results despite all good scientific intentions. 11 The

rate of false-­negative findings is due, in part, to the fact that nonpenetrant gene carriers (i.e., persons who harbor a genuine genetic liability for schizophrenia) are misclassified as unaffected.

Genetics, Genomics, Phenotypes, and Endophenotypes

193

e

si

es

Endophenotypes

Bi

olo

As po soci pu ate lat d ion wi s th

g ic

illn

al m

ns

om

ark e

rs

phenotypes. An endophenotype must meet the criteria presented earlier, whereas a biomarker need only reflect a deviation in the illness construct, in some cases, that has some basis in a biological substrate. For example, a biomarker could be an elevated metabolite level that appears in those affected with the illness—it may have a biological substrate, but its nature fails to conform to the definition of an endophenotype. A most important difference is that a biomarker need not meet the heritability requirement of an endophenotype (see Figure 7.3). Thus the term biomarker is not fungible with (or equivalent to) endophenotype. Another term that is often used but erroneously considered by some to be the equivalent of, or fungible with, endophenotype is intermediate phenotype. Meyer-­Lindenberg and Weinberger (2006) discuss the use of this term

1) 2) 3) 4) 5)

Associated with illness Heritable State-independent (but may require challenge/provocation) Familial cosegregation with illness Found in some unaffected relatives (probabilism vs determinism)

FIGURE 7.3.  Biological markers (a.k.a. subclinical traits and vulnerability markers) may be primarily environmental, epigenetic, or multifactorial in origin. For this reason, criteria useful for the identification of markers to study psychiatric genetics have been proposed, adapted, and refined over time (see Gottesman & Gould, 2003; Gould & Gottesman, 2006). Current criteria for an endophenotype, to be distinguished from biological markers, are designed to direct clinical research in psychiatry toward genetically and biologically meaningful conclusions. Copyright 2007 by Todd D. Gould and Irving I. Gottesman. Reprinted by permission.

194

SCHIZOTYPY VIEWED FROM THE LABORATORY

(i.e., intermediate phenotype) to identify a “biological trait that is in a predictable path from gene to behaviour” (p. 820) in the study of psychopathology. Unfortunately, the term intermediate phenotype introduces vagueness into our discourse. When we unpack the terminology, intermediate phenotype as used in psychopathology currently is not only potentially suggestive of alternative interpretations but also conflicts with an established usage in genetics. Drawing on Lenzenweger (2010 in prep.), the term intermediate, as a modifier, leaves the interpretation of intended meaning rather open. For example, intermediate could connote “in between,” as suggested by Meyer­Lindenberg and Weinberger (2006); however, one could also interpret the term, consistent with typical usage, as connoting “almost,” “halfway,” or “not quite” a phenotype. By definition, a phenotype is an established, visible manifestation of the genotype; thus it is unclear what a “not quite” or “almost” phenotype would look like to the unaided naked eye. (In contrast, the term endophenotype clearly implies that only the aided eye can detect a phenomenon, aided by some sort of tool; e.g., electrocardiogram [EKG], glucose tolerance test, MMPI configuration). The ambiguity that also accompanies intermediate derives from the question as to the level of analysis intended by users of the term. One can conceive of analyses conducted at the level of the person (typically as revealed in the study of individual differences) or within the person (typically as revealed in the study of underlying neural mechanisms and brain structures; Kosslyn & Rosenberg, 2005). What is unclear about the term intermediate phenotype, therefore, concerns the level of analysis implied by the expression, as plausible alternative interpretations of the term exist. In the “not-quite” or “almost” sense, intermediate phenotype could plausibly mean an observable phenotype that falls short of the typical phenotype—that is, schizophrenia. This would suggest a level of analysis that is at the level of the person. In this sense, it would be justifiable to see the term as implying a “subsyndromal” phenotype (e.g., SPD vis-à-vis schizophrenia). Alternatively, intermediate phenotype could plausibly mean a measurable phenomenon of some sort within the person that falls somewhere between the unobservable genotype and the observable phenotype. This meaning seems to be closer to that intended by Meyer-­Lindenberg and Weinberger (2006), but it is still ambiguous, as this measurable phenomenon (e.g., working memory deficits12) does not bear resemblance to the phenotype in 12 A construct—such as “working memory”—of putative importance that is placed rationally within a nomological network that characterizes pathogenesis of a disorder could be a valid endophenotype (e.g., Gottesman & Gould, 2003) even though an endophenotype need not bear any resemblance to the phenotype ultimately of interest.

Genetics, Genomics, Phenotypes, and Endophenotypes

195

question (i.e., schizophrenia). Recalling that intermediate is modifying phenotype, the term phenotype must retain its intended and established meaning in genetics, namely a visible manifestation of the genotype. Assuming the phenotype in question is that of schizophrenia, the term intermediate phenotype could be taken to mean “almost” schizophrenia, “not quite” schizophrenia, or “subsyndromal” schizophrenia. One can easily see how “working memory deficit” bears no resemblence to the schizophrenia phenotype. Thus, although the ­intention of users of the term may be to suggest a “within-­person” level of analysis—­pointing to an underlying process thought to be reflective of an unfolding schizophrenia liability—intermediate phenotype falls short in terms of definitional clarity. There is yet another interpretation of the word intermediate as a modifier of phenotype that further muddies the conceptual water. Intermediate is not uncommonly taken to mean “midway, middle, or halfway” and, therefore, suggests a level of precision in plotting a concept in some sort of semantic or conceptual hyperspace. Thus, although the term intermediate is suggestive of coordinates demarcating a location halfway between X and Y, or, in this instance, genotype (X) and phenotype (Y), it is simply not possible to maintain such certainty with respect to the underlying topography spanning the distance from genotype to phenotype (cf. Waddington’s epigenetic landscape; Gottesman, 1974). Again, an accepted meaning of the word intermediate serves to undermine the clarity of the concept intended by intermediate phenotype. Another shortcoming of the intermediate phenotype concept is that it fails to adequately fall into either the “hypothetical construct” bucket or the “intervening variable” bucket of MacCorquodale and Meehl (1948). As defined, the intermediate phenotype has its conceptual toes in each bucket, and as such the concept does not enhance clarity. Finally, the term intermediate phenotype has been used in genetics previously with an entirely different meaning from that suggested by Meyer­Lindenberg and Weinberger (2006), namely, to suggest “incomplete dominance” (also known as “partial dominance,” when known a priori as a true autosomal dominance genetic condition) or a form of intermediate inheritance in which heterozygous alleles are both expressed to varying degrees, resulting in an intermediate phenotype that represents a combination of the parent phenotypes. In this sense, the intermediate phenotype is indeed a phenotype somewhere (but not exactly halfway) intermediate between the corresponding homozygote phenotypes. For example, in cross-­pollination research, one could see a white flower and red flower give rise to a pink flower. The “palomino” phenotype (in horses, due to the incomplete dominance of a cream-color gene for coat color) is an intermediate phenotype.

196

SCHIZOTYPY VIEWED FROM THE LABORATORY

One form of familial hypercholesterolemia13 (in humans) represents an intermediate phenotype reflective of incomplete dominance. Will incomplete dominance always yield an intermediate phenotype? No. Consider recent research (Squitieri et al., 2003) that supports the notion that individuals homozygous for the Huntington’s disease genotype show a more severe form of the illness and more rapid progression in decline as compared with the more typical heterozygous Huntington’s disease sufferers. Do such results mean that the typical form of Huntington’s disease is akin to an intermediate phenotype? Probably not. The typical form of Huntington’s disease— found in individuals heterozygous for the gene—does not differ markedly in terms of the phenotype as compared with the disease manifestations in those homozygous for the gene. Although this technical definition of intermediate phenotype is not what is intended by those using the term in psychopathology genetics, this meaning of the term intermediate phenotype is accepted as an established meaning in genetics, predating current use in psychopathology (e.g., Meyer-­Lindenberg & Weinberger, 2006).14 However, none of the foregoing interpretations of the term intermediate phenotype, all of which are entirely plausible, is what Meyer-­Lindenberg and Weinberger (2006) would agree to as their preferred meaning for the term intermediate phenotype. They provide the example of neural circuitry of putative relevance to schizophrenia as an “intermediate phenotype,” reflective of an interpretation of the concept that they prefer. However, such a plausible interpretation does not obviate the alternative interpretations of intermediate as a modifier. Given the terminological ambiguity of the modifier intermediate, as well as the preexisting usage of the term in genetics in connection with incomplete dominance, it seems that the likelihood of ambiguity attached to the term intermediate phenotype as used by some psychopathology researchers is nontrivial (see Lenzenweger, 2010). In contrast, 13 The “low-­density lipoprotein receptor” (LDLR) gene for hypercholesterolemia follows a pattern of autosomal dominance, such that heterozygous carriers express a certain degree of elevated cholesterol that is strangely predictive of early heart disease in later adulthood (in the early 40s or 50s), whereas carriers homozygous for the LDLR mutation express very severe hypercholesterolemia, typically emerging in childhood. 14 These examples, by definition, draw on genuine cases of autosomal dominance. Genetic research in schizophrenia does not generally support the likely existence of a simple autosomal-­dominant genetic architecture for schizophrenia. The “intermediate phenotype” concept may mislead some readers toward an autosomal-­dominance model. If we were to draw on Mendelian genetics to very roughly approximate how we think about genetically influenced liability, then an autosomal-­recessive model would be more appropriate. In the recessive model, unaffected individuals can still “quietly” carry the liability for an illness yet be often completely (or relatively) asymptomatic (noting only homozygous recessive cases are expressed), though some illness-­related deviations could be detected with biological tests. There is no “intermediate phenotype” in the case of recessive conditions (e.g., phenylketonuria [PKU], or cystic fibrosis).

Genetics, Genomics, Phenotypes, and Endophenotypes

197

the concept term endophenotype, as a noun, enjoys freedom from the terminological ambiguity suggested by intermediate phenotype, and, as a concept in its own right, it can be defined with considerable precision as reflected in the development of the concept by Gottesman and colleagues (Gottesman & Gould, 2003; Gould & Gottesman, 2006; Chan & Gottesman, 2008; Ritsner & Gottesman, 2009). Clearly, the biomarker and intermediate phenotype concepts are not fungible with the endophenotype concept and should not be confused with the latter. Both “biomarker” and “intermediate phenotype” fall short of the precision and conceptual richness found in the endophenotype concept. Thus endophenotype is the preferred concept for psychopathology research. The biomarker and intermediate phenotype concepts have different utility, however. The biomarker term is useful in that it captures the domain of any biologically influenced factor or deviation in relation to psychopathology (including endophenotypes), and it may be useful in some instances to distinguish between biological factors that occur secondary to an illness but fall outside the realm of endophenotypes (e.g., state markers). The term intermediate phenotype is best used to describe a subclinical variant of a form of major psychopathology—such as schizotypic psychopathology vis-à-vis schizophrenia—in which the phenotype is visible to the unaided eye and bears some resemblance to the classic phenotype of interest. Intermediate phenotype in this usage is not representative of a hypothetical within person process; rather, it describes a dilute form of an established phenotype (or unit of analysis). Unlike the concept of pleiotropy, which allows an alternative phenotypic manifestation of a gene to possess little similarity to a disease phenotype, the intermediate phenotype, in the proposed usage, appears as a “watered down” or diminished (albeit fundamentally similar) version of the illness phenotype.

Marker versus Indicator: Preferred Usage in Experimental Psychopathology Given that genetic influences are important to the development of psychopathology and to the utility of laboratory methods for measuring processes that are fundamental to schizophrenia, there is a tendency to want to view laboratory-­assessed processes as “markers” of liability. The term marker is used this way to designate one or another psychological, psychophysiological, or neural circuitry-based phenomenon as indicative of schizophrenia liability. It is, perhaps, unwise to use the term marker in such discussions. The term marker has been used extensively in genetics, namely as “genetic marker.” Genetic marker, as a terminological distinction, has an established

198

SCHIZOTYPY VIEWED FROM THE LABORATORY

and accepted meaning that is typically not what many psychopathologists have in mind when they use the expression marker. A genetic marker is, simply stated, a gene or other identifiable portion of DNA whose inheritance can be followed.15 In this technical sense, the markers that most psychopathologists have in mind are not markers at all. “But,” an irritated psychopathologist reading this might exclaim, “I did not say ‘genetic marker’.” I would respond, “that is true enough, but that is what you were likely thinking, and in doing so you may seek to elevate your process of interest to the same level of meaning and conceptual importance as that attached to a genetic marker.” I suggest that we use the term indicator to identify those psychological, psychophysiological, or neuroimaging-based (and other) phenomena we wish to designate as tapping liability16 for psychopathology. The term indicator can be used to denote a latent construct or latent entity, which is really what liability is in this framework. This usage has a statistical basis (Bollen, 2001), as well as a long tradition in psychometrics and the construct validity discussion (Cronbach & Meehl, 1955). Indicator, as a term and a concept, is particularly well suited to a situation in which some observed or measurable phenomenon is thought to fallibly17 tap a latent entity, such as a liability construct. This represents an emphasis on precision in language; however, by keeping our discourse as clear as possible, we experience a net gain in the long run by avoiding conceptual confusion in the short term.

Schizophrenia, Schizotypic Pathology, Genetics, and Genomics: Considering Warp Threads of the Tapestry To understand schizotypy and schizophrenia research, it has always been useful for me to think of the entire enterprise as assuming that genetic influences play a central organizing role, and this assumption provides the structure on which other findings rest. By analogy, consider the components of a woven fabric tapestry. A tapestry consists of a major structural 15 The term genetic marker and many other useful terms in genomics and genetics can be found at: www.ornl.gov/sci/techresources/Human_Genome/glossary/glossary.shtml#geneticmarker. 16 In this context “tapping liability” means correlating, however imperfectly, with the underlying liability construct. 17 The

fallibility notion is central to the latent construct concept as applied in virtually all of psychological science, as well as in psychiatric research. The intention of highlighting fallibility is to ensure that the reader realizes that indicators are linked to a putative latent construct in a probabilistic or stochastological manner (even holding aside measurement error), rather than in a truly nomological manner, which implies a more law-like/causal relationship (Meehl, 1978). For example, questionnaire items assessing body image aberrations and perceptual distortions are linked to the latent construct schizotypy in a statistical/probabilistic manner, not in a law-like (causal) manner.

Genetics, Genomics, Phenotypes, and Endophenotypes

199

backbone on which the interesting colors, designs, and images are woven. The structural backbone is referred to as the warp, or a set of lengthwise yarns, and through the warp, the weft is woven. Warp means “that which is thrown across” (derived from the Old English wearp, from weorpan, “to throw”). The core genetic findings underpinning the schizotypy model represent the warp threads on which the corpus of schizophrenia research findings are woven.

A Tour of Basic Models of the Structure of Schizotypy (Schizophrenia Liability) The basic models to be considered when evaluating the genetic architecture of complex diseases, such as schizophrenia, are relatively few in number. There is the single major locus (SML) model, in which a single diallelic locus is responsible for a disorder in either a dominant or a recessive manner. This model can be thought of as a one-gene–one-­disorder (OGOD) model of genetic influence. An illness that conforms well to this model is Huntington’s disease, caused by a single autosomal dominant gene. There are few, if any, proponents of an SML model for schizotypy and schizophrenia (although Meehl was a major proponent). A second model of relevance— the multifactorial polygenic model—­posits that there are many genes of small effect contributing to the liability for a complex illness and that these many and diverse genes sum to create an individual’s level of liability. For example, general intellectual ability (as indexed by IQ) is probably polygenically determined. This means that the quantitatively varying construct of IQ is underpinned by quantitative variation in the number of genes contributing to intelligence. Oftentimes, the basic polygenic model is modified to incorporate a threshold assumption in which an illness emerges once the polygenically determined liability exceeds a certain break point or threshold. The threshold is an important component of this modified model, as it specifies that there is a jag or sharp demarcation point on the underlying continuum of liability that corresponds to a transition or shift point. Illness appears after this transition or shift point is passed. The primary proponent of the multifactorial polygenic threshold model of schizophrenia has been Irving I. Gottesman (Gottesman & Shields, 1967, 1972; Gottesman, 1991; Cardno & Gottesman, 2000; International Schizophrenia Consortium [ISC], 2009). A noteworthy variation on the multifactorial polygenic threshold model is the oligogenic (or mutagenic) model, which has many of the same features of the polygenic model but assumes that there is some limited, finite number of genes (of moderate influence) contributing to liability. Risch (2000) refers to these models as preferred by geneticists “unwilling to cede to a notion of

200

SCHIZOTYPY VIEWED FROM THE LABORATORY

‘infinite’ genetic complexity,” who prefer the term “ ‘oligogenic’ or ‘mutagenic,’ implicating a tractable degree of complexity” (p. 847). The polygenic model is somewhat agnostic as to the relative effect of the independent genes that come together—­ostensibly in additive fashion—to determine genetic liability.18 The genes could be many of very small effect (Sing, Stengard, & Kardia, 2003) or relatively few but of larger effect (Lander, 1996). In practical terms, this means that gene hunters could be looking for anywhere from a half-dozen or so genes (of larger effect) to upward of several hundred genes (of smaller effect) for a disorder such as schizophrenia.19 There are two additional models relevant to an understanding of the genetics of schizotypy and schizophrenia, namely the mixed model and the latent trait model. The mixed model, described earlier in our review of Meehl’s (1962, 1990) model of schizotypy, involves a combination of the components of SML and polygenic models. The mixed model involves a locus of major effect (necessary but not sufficient for disease expression) that operates against a background of polygenic effects in determining illness liability. Thus the disease-­specific major locus interacts with other nonspecific, polygenically determined factors that combine to create liability.20 The latent trait model advanced by Matthysse and Holzman (Matthysse, Holzman, & Lange, 1986) assumes that there is a latent entity or construct—the so-­called latent trait—that is causally related to the development of schizophrenia. This latent trait can manifest itself as schizophrenia or, by assuming pleiotropy,21 as deviations in smooth pursuit eye movements or both. Through joint consideration of both schizophrenia and/or eye-­tracking 18 That

there may be multiple genes or polygenes does not imply that all are necessary for illness expression in any given instance (i.e., there may be, for example, 200 genes of small effect, but various combinations of 5 or 10 or 50 of them may be sufficient to cause the illness).

19 The polygenic model, whether incorporating a threshold or not, normally assumes an additive effect across disease-­relevant genes and does not typically call into play the notion of interaction among the genes, or the process known as epistasis. 20 Another

theoretical possibility is a mixed model that contains a limited number of genes specific for a disease operating against a background of polygenic effects. Such a model would be termed an oligogenic mixed model to distinguish it from the more typical mixed model that assumes a disease­specific SML.

21 Pleiotropy

refers to the phenomenon whereby a single genetic mutation affects several apparently unrelated aspects of the phenotype. In the case of schizophrenia, Holzman and colleagues (1988) argued that eye-­tracking dysfunction was a pleiotropic manifestation of the gene that caused schizophrenia. Pleiotropy is a common component of genes. In the disease neurofibromatosis, which is inherited as an autosomal dominant, an affected person can display tumors (neurofibromas) of the nerve cells around the body or light-brown skin pigment discolorations known as café au lait spots, typically in the groin or axilla (the armpit). Thus, in pleiotropy, the genotype can give rise to vastly different phenotypic manifestations of genetic liability for the illness.

Genetics, Genomics, Phenotypes, and Endophenotypes

201

dysfunction in the biological relatives of those affected with schizophrenia, Holzman et al. (1988) argued that a single autosomal dominant gene could account for the transmission of schizophrenia.

The Pattern of Evidence in Support of a Genetic Component to Schizophrenia and Schizotypy We begin with a statement of basic scientific fact: Schizophrenia represents a disease phenotype that is subject to very considerable genetic influences. A confluence of family, twin, and adoption studies have generated a pattern of evidence that makes it overwhelmingly clear that schizophrenia has its roots in genetic factors (see Gottesman, 1991; Cardno & Gottesman, 2000). There is relatively little, if any, dispute about this fact among enlightened psychopathologists. Contemporary genetic research, much of which is molecular in nature, is now focused on the identification of actual susceptibility loci (i.e., specific genes) for schizophrenia. Although there have been many interesting leads in this gene(s) hunt, the definitive set of genes responsible for the disorder continues to elude the herculean efforts under way (for reviews, see Harrison & Owen, 2003; Owen, Craddock, & O’Donovan, 2005). A variety of genes have garnered some empirical support and, therefore, considerable research interest—such as dysbindin (DTNBP1), catechol-O-methyltransferase (COMT), neuregulin-1 (NRG1), D-aminoacid oxidase (DAAO), regulator of G-protein signaling-4 (RGS-4)—and new findings continue to appear (O’Donovan et al., 2008). Meta-­analyses of genome-wide scans in search of areas that might contain susceptibility loci for schizophrenia have pointed to a number of promising chromosomal regions (Lewis et al., 2003; Allen et al., 2008), with some regions of interest emerging that heretofore had gone unconsidered. However, this brief review of molecular findings risks “jumping the gun” and moving too quickly to the molecular level of analysis. Before “going molecular,” how do we know that schizotypy is a plausible construct underlying schizophrenia, schizotypic psychopathology, and the major schizophrenia liability endophenotypes?

What Aspects of the Schizophrenia Phenomenological Picture Are Related to Genetic Influences? That schizophrenia is subject to considerable genetic influences represents a starting point for more refined analyses. What aspects of schizophrenia phenomenology are most closely related to the genetic influences for schizophrenia? This type of question highlights a central theme in this book;

202

SCHIZOTYPY VIEWED FROM THE LABORATORY

namely, that questions and analyses that cross levels of analysis (genetic and psychological in this instance) are likely to be most fruitful in terms of advancing our understanding of schizophrenia. At first blush this seems like a relatively straightforward question; however, the question is a bit trickier than it appears on the surface. This is so because the definition used for the schizophrenia diagnostic phenotype matters insofar as it demarcates the unit of analysis. Moreover, such limitation or constraint will inevitably leave its imprint on the statistical relations among the symptoms used, that is, how these symptoms will be associated with one another (i.e., their covariance structure)—whether definitions or rules built into the diagnostic procedure will subsequently shape all downstream relations between the individual schizophrenia symptoms and any dependent variable of interest. For example, if all persons who receive a diagnosis of schizophrenia are required to have certain symptoms before other symptoms of the illness can be considered, this will impact the relations. How could the nature of the definition of schizophrenia affect the relations among the symptoms across persons? In the prevailing DSM systems (i.e., since DSM-III’s appearance in 1980), there is indeed such a bias. Simply stated, the diagnosis of schizophrenia is largely conditional on the presence of positive symptoms. Of the five symptoms in section A of the diagnostic criteria for schizophrenia in DSM-IV-TR, four of them are positive symptoms. Moreover, bizarre delusions and voices commenting in auditory hallucinations are given particularly heavy weighting in the diagnostic scheme. This matters because the only way to receive the diagnosis of the illness is to have a preponderance of positive symptoms in the symptom picture. To the extent that other symptoms are important for the diagnosis, those symptoms are important only after positive symptoms weigh in, so to speak. Statistically, the associational relationships among all clinical features of schizophrenia will depend on the presence of positive symptoms. A practical implication of this constraint is that one cannot receive the diagnosis of schizophrenia—at least, according to the DSM-IV-TR approach—with only negative features or with only thought disorder. Interestingly, both negative features and thought disorder were viewed by Bleuler as fundamental (primary) to the illness. In contrast, he viewed hallucinations and delusions as accessory (or secondary) in nature, that is, nonspecific manifestations of psychosis that can be found in illnesses other than schizophrenia. We probed this issue in the early 1980s, when we (Dworkin & Lenzenweger, 1984) found that higher levels of negative schizophrenia symptomatology (flattened affect, asociality/withdrawal, anhedonia) were associated with higher rates of concordance for schizophrenia in 151 pairs of MZ

Genetics, Genomics, Phenotypes, and Endophenotypes

203

twins. This study made use of the published psychiatric case histories of MZ twins who had been studied previously in five landmark twin studies of schizophrenia. What was particularly informative about these case histories was the range of pathology noted by the observing clinicians. Particularly salient was the attention given to all forms of clinical phenomenology in the histories. They included positive and negative symptoms, as well as other noteworthy developmental events and/or stressors. Moreover, the subjects in these investigations were studied, by and large, well before the introduction of the phenothiazines (i.e., early neuroleptic medications) and other antipsychotic medications, which today are known to complicate the assessments of negative phenomenology. Finally, all of the twins were diagnosed as having schizophrenia based on European criteria that were conservative in nature and that possessed no implicit hierarchy or order in application. By hierarchy I mean that, unlike the DSM approach to the diagnosis of schizophrenia, the diagnosis of the illness was not dependent on (conditional on) the presence of positive symptoms. Where are we now with respect to the relationship between phenomenology and genetic influences for schizophrenia? In a recent twin study, Cardno and colleagues (Cardno, Sham, Murray, & McGuffin, 2001) also reported that negative features were likely associated with genetic influences. However, these same investigators reported that the broad composite symptom dimension known as disorganization—a subdimension of positive schizophrenia symptoms—also aggregated in such a manner consistent with a genetic effect in these twins. In fact, in their most recent work, Cardno, Rijsdijk, Murray, and McGuffin (2008) suggest that the disorganization dimension of psychotic symptomatology may hold the greatest promise as a potential focus in genetic analyses of schizophrenia. In pushing these relationships toward the molecular genetic level of analysis, Ritsner et al. (2002) reported that the increased levels of negative schizophrenia features were associated with an increased number of the trinucleotide CAG repeats (CAG; cytosine–­adenine–­guanine; the codon that codes for the amino acid glutamine) in the KCNN3 gene, a gene known to influence one member of a known family of calcium-­activated potassium channels. Thus, crossing levels of analysis, what Ritsner et al. (2002) show is that the level of negative symptomatology in schizophrenia-­affected individuals is actually associated positively with an increasing number of repeat sequences on the genome in relation to a gene of potential psychiatric interest (Dror et al., 1999). More recently, Wang et al. (2008) reported that increased levels of negative schizophrenia symptoms were associated with the 5-HT2A receptor 102-T/T genotype, a genotype that may have prognostic significance

204

SCHIZOTYPY VIEWED FROM THE LABORATORY

with respect to certain drug treatments for schizophrenia. Clearly, these are but two of what will likely be more reports linking negative symptoms to structural variations and/or particular polymorphisms of interest to schizophrenia researchers. What in this story of negative symptoms, genetics, and schizophrenia is of interest to the experimental psychopathologist? Several observations are in order here. First, the relationship between “negative symptoms ´ genetic influences” in schizophrenia was suggested by clinical observations in the Danish Adoption Study. Second, this putative symptom–­genetic liability connection was empirically verified through the use of MZ-twin case studies that found an association between increased levels of negative schizophrenia symptomatology and increased concordance rates for schizophrenia. Third, this basic association was independently confirmed in a modern twin study using explicit diagnostic criteria and a structured interview approach. Finally, this dimension of schizophrenia symptomatology was linked provisionally to a pattern of CAG repeats connected with a gene that is of theoretical interest in schizophrenia. By moving systematically across levels of analysis, the basic findings concerning negative symptoms at the observed level were eventually linked to molecular genetic findings of great interest. Thus bridges were built across the levels of schizophrenia phenomenology and genetic influences for the illness. What is essential here is the methodological approach implied in this work. Will these specific bridges hold up over time? Are these bridges unequivocally established as fact? We simply do not have answers just yet. Moving on, what is the next question of relevance to this scientific story? Can we systematically assemble bridges that link schizotypic psychopathology to schizophrenia and, similarly, move to a molecular level of analysis? Can we articulate a model that provides compelling connections between schizotypy as the latent liability for schizophrenia construct and the various ways in which it comes to phenotypic and endophenotypic expression?

Bridging Schizotypy and Schizophrenia: Latent Constructs, Empirical Connections, Levels of Analysis The primary assumption of the book that you are holding in your hands is that schizophrenia liability can express itself in ways other than full-blown, classic schizophrenia. The central argument explicates that there can be manifestations of schizotypy—­conceived of as a latent construct (MacCorquodale & Meehl, 1948; Cronbach & Meehl, 1955)—as tapped by observable phenomena (either literally observable or through appropriate

Genetics, Genomics, Phenotypes, and Endophenotypes

205

aids to the naked eye) that are indicators22 of the presence of the liability for schizophrenia. One manifestation of schizotypy is, of course, schizophrenia. Other manifestations, more interesting in some ways, are schizotypic psychopathology; various psychological (e.g., thought disorder), neurocognitive (e.g., eye-­tracking dysfunction, working memory impairments), and neurological (e.g., somatosensory dysfunction) indicators; and as yet unknown derivatives of schizophrenia liability. This conceptual claim could be made from the armchair; however, there is a corpus of empirical data that supports this assumption. There are different strands of evidence, each a pillar supporting this fundamental hypothesis. The strands concern (1) the schizophrenia–­schizotypic pathology link, (2) the plausibility of a latent liability construct, (3) the notion of “quiet” (i.e., phenotypically unexpressed) transmission of schizophrenia liability, and (4) the links between laboratory endophenotypes, schizotypic psychopathology, and clinical schizophrenia connecting to schizotypy. 1. Does schizotypic psychopathology run in families? An important place to begin is with the time-­honored family study method in behavioral genetics research (Carey, 2003). Recall that if a condition of interest (or trait) is subject to the same genetic influences as the disease of interest, then it should be found among the biological family members of an affected person at rates higher than those observed in the biological relatives of an unaffected control subject. However, it is essential to remind ourselves of the family-study mantra: “just because something runs in a family does not necessarily mean that it is genetically influenced.” As Seymour Kety, a pioneering and highly creative early psychopathologist, was fond of saying, poverty, royalty, and silverware run in families but are not genetically transmitted. Nonetheless, the family-study method is a fine place to start in our examination. As noted, both Kraepelin (1919/1971) and Bleuler (1911/1950) had long observed that nonpsychotic variants of schizophrenia were found at increased rates among the biological family members of schizophrenia patients (see Box 1.1 in Chapter 1, p.  12). Clearly, what Kraepelin and Bleuler were noting in these observations was that (by the way, this is a superb example of the value of clinical observation) schizophrenia could show itself in ways other than in its most classic, fulminant form and that there appeared to be a dilute or somewhat attenuated form of the same psychopathology. The latter was difficult to describe; hence the terms latent 22 See Bollen (2001) for an excellent, succinct discussion of the term indicator as used in the social sciences.

206

SCHIZOTYPY VIEWED FROM THE LABORATORY

schizophrenia and eccentric personalities were the most apt. In subsequent years, many family studies found that schizotypic psychopathology could be found among the biological relatives of schizophrenia-­diagnosed probands. The general thrust of these family studies was that schizophrenia was familial and schizotypic psychopathology, when assessed, also aggregated with schizophrenia in these families, suggesting a familial nature (see Gottesman, 1991). A study many regard as a benchmark in bolstering the scientific corpus in support of the familial relationship between schizophrenia and schizotypic psychopathology is known as the Roscommon Family Study (RFS). It has been conducted in County Roscommon, Ireland, under the direction of the psychiatric geneticist Kenneth S. Kendler. The RFS recruited its subjects using an epidemiological approach based on a case register, and the vast majority of the subjects in the study were interviewed face-to-face by experienced clinicians using structured interviews for major psychiatric disorders, as well as many expressions of schizotypy (Kendler et al., 1993). Kendler and colleagues (1993) found that SPD had a strong familial relationship with schizophrenia. They also reported that the rate of schizotypal personality was elevated in the biological family members of probands who also had SPD. Of course, one would think it would be interesting to know whether there were individual schizotypic features that helped to separate the relatives of individuals with schizophrenia from those relatives of persons that did not have schizophrenia. These investigators agreed and sought to answer this question. Kendler, McGuire, Gruenberg, and Walsh (1995) reported from the RFS that odd speech, negative symptoms, social dysfunction, and avoidant symptoms were best at discriminating the relatives of schizophrenia probands from matched controls. An especially interesting finding from the RFS was the relatively strong associations between forms of positive and negative schizophrenia symptoms found in the psychotic probands and the corresponding positive-­symptom-like and negative-­symptom-like schizotypic dimensions assessed in their biological relatives (Fanous et al., 2001). This latter analysis highlights the utility in approaching both the psychotic symptomatology and schizotypic symptomatology as continua at the phenotypic level and the resulting gold found in individual differences. Finally, it is important to consider issues of replication for this pattern of associations. This is poignant, as many family studies of schizophrenia and schizotypic psychopathology have taken place across time and continents, using varying diagnostic schemes and different sampling methods. Kendler and Gardner (1997), in a meta-­analysis of three major family studies that used DSM-III or DSM-III-R diagnostic criteria, concluded that SPD

Genetics, Genomics, Phenotypes, and Endophenotypes

207

(as a form of schizotypic psychopathology) strongly aggregated in the biological relatives of schizophrenia-­affected individuals. The beauty of this meta-­analysis is that it included three high-­quality family studies conducted in three different time periods in three different countries (United States, Denmark, and Ireland).23 2. Does schizotypic psychopathology show evidence of heritability? As is well known to the serious student of psychological science, the heritability of a construct or factor of interest is a critical datum to have in hand. Heritability, in review, means the proportion of phenotypic variance resulting from additive genetic variance. Although heritability has meaning only within the study in which it was derived (and cannot be compared across samples24), it provides us with a useful handle on the degree to which a trait, construct, or factor is subject to genetic influences (Carey, 2003). The experiment of nature that helps us to establish heritability is the twin-study method. Recall that the comparison of concordance rates for a qualitative phenotype or the comparison of correlations for continuous metrics from MZ and same-sex DZ twin samples are traditionally used to establish heritability (see Box 7.1). The strongest data in support of a genetic component for schizophrenia come from the body of twin research (Gottesman, 1991; Cardno & Gottesman, 2000). They clearly support a very substantial heritability for the illness. The twin method can be implemented as well for an evaluation of the heritability of schizotypic psychopathology, separate and apart from schizophrenia. In short, if the schizotypy construct is, in large part, driven by genetic factors, then its manifestations should reveal considerable evidence of heritability. The data most directly relevant to this particular question come from twin studies that have studied the heritability of individual-­differences dimensions related to schizotypal personality. For example, Livesley, Jang, Jackson, and Vernon (1993) conducted a twin study using volunteer twin pairs (175 pairs: 90 MZ pairs, 85 DZ pairs) from the general population. These twins completed a paper-and-­pencil questionnaire that contained a variety of inventory items covering a wide array of personality-­disorder-­related dimensions, two of which immediately concern 23 The reader is encouraged to ponder these results in contrast to the anomalous reports of nonfamiliality for schizophrenia that followed the introduction of DSM-III (American Psychiatric Assocation, 1980; see Chapter 1 in this volume). 24 Another

way to think of this “within” vs. “between” groups issue in relation to heritability is to keep in mind that heritability, as a concept, belongs to populations, not to traits or disorders. Thus it says something about a group of people in a sample or population, but not about the individuals in the sample.

208

SCHIZOTYPY VIEWED FROM THE LABORATORY

BOX 7.1.  Sources of Variation in Twins and Heritability Conceptual basis of the twin-study method: Differences in MZ twins:

Environmental influences (E)

Differences in DZ twins:

Environmental influences (E) + Genetic influences (G)/2

Thus, assuming E is equal, the within-pair observed differences between MZ and DZ Twins = G/2. Total estimate of genetic influence = 2 * (G/2).

Making it quantitative for continuous traits: Correlation between MZ twins (rMZ ) = G + E. Correlation between DZ twins (rDZ ) = G/2 + E. Again, assuming E is equal in MZ and DZ twin pairs, G/2 = (rMZ – rDZ ). Estimating heritability [h2] = 2 (rMZ – rDZ ). [Note. h2 yields values falling between 0 and 1.0.] Estimating E [shared common environment] = rMZ – h2.

us—that is, “suspiciousness” or paranoia25 and cognitive distortion (schizotypal cognition). Suspiciousness and cognitive distortion showed evidence of relatively high heritability (additive genetic factors) and the influence of nonshared environmental factors.26 In a twin study conducted by the Norwegian psychologist Svenn Torgersen and colleagues (Torgersen et al., 2000), twin pairs were drawn from a twin register that was maintained to record twin births in Norway, as well as from several clinical sources (MZ pairs = 92, DZ pairs = 129). The sample did not include any individuals with schizophrenia, and all subjects were personally interviewed using a structured interview for personality 25 The

type of suspiciousness or paranoia presumably was nonpsychotic in nature; however, this is not entirely clear.

26 Nonshared

environmental factors are all those factors that make relatives who live together different from one another (Carey, 2003). These factors are sometimes also called nonfamily environment, unique environment, or idiosyncratic environment.

Genetics, Genomics, Phenotypes, and Endophenotypes

209

disorders. Broadly defined Cluster A personality disorders (PDs; namely, schizotypal, paranoid, and schizoid PDs) were found in both MZ and DZ pairs, with MZ twins being concordant more frequently than DZ pairs for such pathology. Important clues regarding the heritability of dimensions of relevance to schizotypy could be studied in these subjects. The heritability of Cluster A disorder dimensions was as follows: .61 for schizotypal, .28 for schizoid, and .29 for paranoid. Although the prevalence of definite Cluster A pathology (i.e., diagnosed cases) was relatively low in these twins, the data are consistent with schizotypal features being subject to noteworthy genetic influences. Finally, most recently, Kendler and colleagues (Kendler, Myers, Torgersen, Neale, & Reichborn-­Kjennerud, 2007) reported on yet another twin study conducted in Norway. In their study, 1,386 twin pairs from the Norwegian Twin registry were examined for Cluster A features (schizoid, schizotypal, paranoid PDs) using both self-­report and structured interviews. The heritability of the latent liability for each of the PDs were as follows: schizotypal = .72, schizoid = .59, paranoid = .66. As in prior research (e.g., Livesley et al., 1993), no evidence of shared environmental effects on the Cluster A phenotypes was observed. In this study, SPD had the strongest genetic relationship to the common genetic liability for the Cluster A disorders. Clearly, the pattern of evidence from these twin studies supports the heritability of schizotypic psychopathology, which is consistent with a critical assumption of the general schizotypy model linking schizophrenia and schizotypic pathology via genetics. 3. Is there a schizophrenia and schizotypic psychopathology connection holding environment aside? Although Kraepelin and Bleuler had long observed the presence of what we know to be schizotypic psychopathology among the biological relatives of schizophrenia patients, and although this clinical observation has often been confirmed empirically (Kendler et al., 1993), a critical link between clinical schizophrenia and schizotypic psychopathology came from the renowned Danish Adoption Studies conducted by the early psychopathology research pioneers Seymour Kety, David Rosenthal, Paul Wender, and Fini Schulsinger (Kety et al., 1975; Rosenthal, Wender, Kety, Welner, & Schulsinger, 1971). These studies were prescient in that they took a fine-­grained view of the schizophrenia phenotype and considered three forms of schizophrenia: chronic or process, acute or reactive, and borderline27 27 Here

the term borderline meant “on the border of schizophrenia,” “nearly schizophrenia,” or “within the schizophrenia spectrum.” The term borderline, in these studies, did not denote the phenotype known in contemporary psychopathology as borderline personality disorder; rather, it was analogous to “latent schizophrenia.”

210

SCHIZOTYPY VIEWED FROM THE LABORATORY

cases. The relationship between definite schizophrenia-­spectrum disorders and these classifications—­process versus acute versus borderline—­revealed profoundly important information for the schizophrenia–­schizotypy model. The borderline schizophrenia group was defined by phenomenology that would later come to define, in part, the diagnostic criteria for SPD in the DSM system, beginning with DSM-III (Endicott et al., 1978). In the Kety et al. (1975) adoption study, definite schizophrenia-­spectrum disorders were found only among the biological relatives of chronic and borderline schizophrenia adoptees, with no cases found among the biological relatives of the acute schizophrenia adoptees. Rosenthal et al. (1971), who examined the rates of schizophrenia among the adopted-away offspring of schizophrenia-­affected persons, found definite schizophrenia-­spectrum disorders among the adopted-away offspring of chronic schizophrenia and borderline schizophrenia parents but not among the adopted-away offspring of the acute schizophrenia parents. Thus these classic adoption studies provided empirical evidence that the genetic liability for schizophrenia could be found in classic, process or chronic schizophrenia as well as, importantly, in the so-­called borderline forms of the illness. The Danish Adoption Study was originally focused exclusively on the residents of Copenhagen. Fortunately, the study was later extended to the entire country. The results from the extended version of the Danish Adoption Study, referred to as the Provincial Sample (Kety et al., 1994), were highly consistent with those obtained in the Copenhagen sample. This classic study—­clearly linking schizophrenia with schizotypic psychopathology—has been essentially replicated in a more recently completed larger scale adoption study in Finland (Tienari et al., 2003). An interesting aspect of the Danish Adoption Study diagnostic criteria is that the joint consideration of the diagnostic criteria and the patterning of schizophrenia across the three diagnostic classes suggested a potentially important linkage between specific symptoms and the genetics of schizophrenia. One of the important similarities between the process or chronic schizophrenia and borderline schizophrenia was the emphasis in both criteria sets on negative schizophrenia symptoms (Dworkin & Lenzenweger, 1983), suggesting a possible genetic basis for negative features. As mentioned earlier, we (Dworkin & Lenzenweger, 1984) tested this hypothesis and found that higher levels of negative symptomatology were associated with higher rates of concordance for schizophrenia in the twin pairs. Thus negative schizophrenia features did seem to be tracking closely with genetic influences for schizophrenia. The results of this study had the added benefit of deriving from an examination of phenomenology in persons originally

Genetics, Genomics, Phenotypes, and Endophenotypes

211

treated before the onset of drug treatments, which can mimic some negative symptoms (e.g., flattened affect), and long before the current interest in a positive-­symptom-­dominated schizophrenia construct.28 4. Does schizotypy show “quiet” transmission? Can the liability remain phenotypically unexpressed? I have emphasized that Meehl’s schizotaxia–­ schizotypy–­schizophrenia model hypothesized the existence of a latent construct—termed schizotypy—that unifies schizophrenia and other liability manifestations. The liability, per se, is the unobservable latent entity (MacCorquodale & Meehl, 1948; Cronbach & Meehl, 1955). One implication of this theoretical supposition is that the liability for schizophrenia should be detectable, even when it is not entirely observable to the naked eye. In a sense, we ask Can this liability be transmitted “quietly”? The issue of quiet transmission or “unexpressed liability” was tested through the use of twin-study data. In an ingenious investigation, Irving I. Gottesman and Axel Bertelsen (1989) made use of the twin-study sample initially assembled by the Danish psychiatrist Margit Fischer. The original Fischer study consisted of the typical twin-study setup, namely MZ and DZ twins pairs in which one twin was typically designated the proband (or index case) and the other was the cotwin. As has been typical in twin studies of schizophrenia (Cardo & Gottesman, 2000), the concordance rate for schizophrenia was considerably higher among the MZ twins than in the same-sex DZ twins (Fischer, Harvald, & Hauge, 1969). However, the extraordinarily clever piece of analysis done with the Fischer data set came through examination of the rates of schizophrenia that appeared among the offspring of the twins. Gottesman and Bertelsen (1989) posed the questions, Would the liability for schizophrenia be transmitted in unexpressed fashion to the offspring of the twins in this sample, even if a twin parent was not ill with schizophrenia? Could the liability be passed along from “well” twins to their offspring? The answers to these questions were nothing short of stunning. Let us review them for all possible parental situations, MZ versus DZ and well versus ill, in Gottesman and Bertelsen (1989) (see Table 7.2). The rates of schizophrenia in the offspring of the MZ parents were essentially the same regardless of whether the parent was ill or well. The liability for schizophrenia could be transmitted quietly (by unaffected parents), providing compelling support for an unexpressed (latent) liability. Even though schizophrenia manifestations were not evident in the parents who were the well members of the discordant MZ twin pairs, they nevertheless passed along 28 The Dworkin and Lenzenweger (1984) study also highlights the utility of using case-­record data for research.

212

SCHIZOTYPY VIEWED FROM THE LABORATORY TABLE 7.2.  Summary of Data from Gottesman and Bertelsen (1989) •• •• •• ••

Rate of schizophrenia in the offspring of the ill MZ twins = 16.8%. Rate of schizophrenia in the offspring of the well MZ twins = 17.4%. Rate of schizophrenia in the offspring of the ill DZ twins = 17.4%. Rate of schizophrenia in the offspring of the well DZ twins = 2.1%.

the liability for schizophrenia to their children. The importance of this finding supporting the contribution of genetics to schizophrenia liability (schizotypy) cannot be overemphasized. 5. Can we get from the schizotype to schizophrenia? At about the same time Gottesman and Bertelsen were conducting their study, I devised a study to come at the latent liability issue from another angle. As a postdoctoral fellow at the New York Hospital—­Cornell Medical Center in White Plains, New York, I had the good fortune to access a large sample of psychiatric patients who had been characterized with extraordinary care in terms of both Axis I and Axis II psychopathology. Importantly, none of these patients had ever shown any evidence of any psychotic disorder, and thus they represented an ideal sample to assess for schizotypy. The purpose of the study was to make use of these subjects as potential probands in a family history study of schizotypy and schizophrenia. I had each of these patients complete the Chapmans’ Perceptual Aberration Scale (PAS; Chapman, Chapman, & Raulin, 1978).29 Then, blind to the PAS scores of these subjects, the highly detailed and rich case histories of these patients were examined carefully for compelling evidence of treated schizophrenia, bipolar disorder, and/or depression in their first-­degree biological relatives. After data on the relatives were collected, the probands were partitioned into those with higher PAS scores versus lower PAS scores, the former designated as “schizotypy­positive” (or schizotypy-­present) and the latter as “schizotypy-­negative” (schizotypy-­absent). Meehl’s (1962) model suggested that even compensated (nonpsychotic) schizotypes should show some evidence of their schizotypy 29 Selection of the PAS as a measure of perceptual anomalies in the Lenzenweger and Loranger (1989a) study was based on both my clinical experiences with schizotypes, as discussed in Chapter 1, as well as the extant research corpus at the time documenting the PAS as a reasonable psychometric measure of schizotypy. The PAS remains, to date, the most heavily validated psychometric measure of schizotypy in use in psychopathology research. The number of studies reporting informative results using the PAS alone or in conjunction with the Magical Ideation Scale (MIS) continues to surpass the number of studies completed using competing measures of schizotypy or schizotypal features. Given the heritability of the PAS (Miller & Chapman, 1993; see also Kendler & Hewitt, 1992), as well as the massive body of results supportive of the validity of the PAS as a schizotypy indicator, one can safely assume the PAS to be a strong endophenotype candidate (Gottesman & Gould, 2003).

Genetics, Genomics, Phenotypes, and Endophenotypes

213

status. One possible way that liability for schizophrenia might be expressed in schizotypes is through an increased rate of clinical schizophrenia in their first-­degree relatives. Prior studies had found increased schizotypic pathology in the biological relatives of schizophrenia patients, but no prior study had ever gone the other way, that is, from asymptomatic but hypothetically schizotypic cases to familial schizophrenia. What we discovered helped to cement the concept of unexpressed liability in schizophrenia. As reported in Lenzenweger and Loranger (1989a),30 an increased morbid risk for treated schizophrenia was found among the biological first-­degree relatives of schizotypy-­positive probands as contrasted with schizotypy-­negative probands (see Table 7.3). Importantly, the morbid-risk rates for treated depression did not differ across the two proband groups. Almost all cases of bipolar disorder were found only among the relatives of the schizotypy-­negative probands. Complementing Lenzenweger and Loranger (1989a), Fanous, Gardner, Walsh, and Kendler (2001) examined whether the dimensions of positive and negative symptomatology found in psychotic relatives corresponded to positive and negative dimensions of schizotypic features in nonpsychotic relatives. Thus the basic idea was to determine whether, within families, one would see a broad correspondence between the nature of the schizophrenia phenomenology observed once psychosis has emerged and the features of schizotypic psychopathology. Fanous et al. (2001) reported how negative symptoms in schizophrenia-­affected probands were predictive of negative-like schizotypy features in the unaffected (well) relatives within schizophrenia-­affected probands. When the unit of analysis in the probands was broadened to include several illness groups (schizophrenia, simple schizophrenia, and schizoaffective disorder), positive symptoms in TABLE 7.3.  Summary of Results from Lenzenweger and Loranger (1989a) Morbid risk rates in Probands

30 In

Illness

SZT-positive

SZT-negative

z

p

Schizophrenia

3.75%

0.00%

2.559

.005

Bipolar

0.92%

9.81%

0.049

ns

Unipolar

9.62%

2.08%

0.734

ns

one of those interesting moments in science, the findings from both the Gottesman and Bertelsen (1989) and Lenzenweger and Loranger (1989a) studies appeared, along with an updated theoretical position piece on schizotypy by Paul Meehl (Meehl, 1989), in the same issue of the Archives of General Psychiatry. To my knowledge, none of us knew that the others were publishing current work on unexpressed liability issues.

214

SCHIZOTYPY VIEWED FROM THE LABORATORY

the probands were also correlated with positive-like schizotypy features in the relatives. 6. Schizotypy is a latent construct manifesting itself in varying expressions. Is there compelling evidence for such variable expression of a latent construct? Another way to think about schizotypy—the latent liability for schizophrenia—­emerged from the study of eye-­movement abnormalities in schizophrenia. As is discussed later in this book, the study of abnormal eye movements in schizophrenia has a long history, dating back to the early 1900s.31 It is generally acknowledged that the modern pioneer in the study of deviations in smooth pursuit eye movements in schizophrenia was the Harvard experimental psychopathologist Philip S. Holzman. Holzman and colleagues (see Chapter 8, this volume), beginning with work done at the University of Chicago, were able to make a compelling empirical argument that abnormalities in eye tracking (i.e., abnormalities in the ability to smoothly follow a moving target) could be found principally in schizophrenia and that these abnormalities were not artifacts of one sort or another (Levy et al., 1993; Levy, Holzman, Matthysse, & Mendell, 1994). A highly creative use of the eye-­tracking abnormality in schizophrenia came in the form of a theoretical proposition that such abnormality could be viewed as a valid expression of schizophrenia liability—it could be a valid endophenotype (Holzman et al., 1988). In short, the leap from an empirical finding to a theoretical model brought the eye-­tracking findings in schizophrenia to center stage in experimental psychopathology. Assuming that eye tracking was an endophenotype was an important step in the development of a model that went even further—­Steven Matthysse, Holzman, and others would propose that deviance in eye tracking was a pleiotropic manifestation of the genetic diathesis for schizophrenia (Matthysse et al., 1986; Matthysse & Holzman, 1987). According to their model, expressed schizophrenia and the endophenotype of abnormal eye tracking (measured, of course, with finely tuned technology) were both seen as manifestations of a latent construct, which was called the latent trait. Therefore, one could possess the latent trait (the liability for schizophrenia) by virtue of deviance in eye tracking but not necessarily reveal any schizophrenia phenomenology. Indeed, this was the usual case, because the latent trait 31 In this context eye-­movement abnormalities concern the relative inefficiency of the ability to track a moving target with the eye. Eye movements are recorded with a complex technical apparatus and measured with great precision. This branch of psychopathology research has nothing to do with a using eye movements as a putative psychotherapeutic clinical intervention (so-­called “eye movement desensitization reprocessing” [EMDR], that inhabits the fringes of clinical psychology (better designated pseudoscience).

Genetics, Genomics, Phenotypes, and Endophenotypes

215

had a higher probability of being expressed as eye-­tracking dysfunction than as schizophrenia. Moreover, Holzman et al. (1988) showed that an autosomal dominant genetic locus could account for both schizophrenia and abnormalities in eye tracking. This was a rather bold proposal and one that had a profound impact in shaping the use of experimental psychopathology laboratory findings in genetic studies. Finally, the approach of Holzman and colleagues represents a fine example of (1) careful detection and measurement of a viable endophenotype and (2) development of a creative theoretical framework into which that empirical finding could be fit, thus advancing our understanding of schizophrenia. All too often in psychopathology research, especially in the area of schizophrenia, one or another deviation in the performance of schizophrenia subjects is identified, even replicated across laboratories, but the trail runs cold eventually. By this I mean the empirical finding is not put to use in advancing our understanding; rather, it more or less stands as an empirical correlate of schizophrenia. Holzman and colleagues provide an exemplar of not remaining content with simply finding an empirical correlate. From the standpoint of how best to think about schizophrenia and schizotypy, the work of Holzman and colleagues again highlights the plausibility and utility of a latent construct formulation. In short, when considering the liability for schizophrenia, it makes sense to move beyond the study of only cases of expressed schizophrenia. Rather, one should employ the latent construct notion (MacCorquodale & Meehl, 1948; Cronbach & Meehl, 1955) to inform model development and potentially to advance our understanding of schizophrenia as a complex disease. The findings from Holzman’s laboratory (and those of subsequent workers) fit well with schizotypy as a latent construct and with the endophenotype conceptualization (Gottesman & Shields, 1972; Gottesman & Gould, 2003). The foregoing studies further advanced the model that links the underlying liability for schizophrenia—schizotypy—with observable manifestations that are nonpsychotic and often well-nigh invisible. The notion that a latent liability construct in schizophrenia could be supported via empirical evidence represented a distinct stride forward beyond the purely theoretical models of Meehl (1962, 1990) and others. As we moved into the new millennium, a sea change in the genetic study of schizophrenia, as well as other forms of psychopathology, occurred—­namely, we moved into the realm of assessing candidate genes (polymorphisms) in relation to schizotypic features, as well as schizophrenia proper. Genome-wide scans in schizophrenia were beginning to appear late in the 1990s, followed by genome-wide scans of relevance to schizotypy

216

SCHIZOTYPY VIEWED FROM THE LABORATORY

and schizotypic psychopathology. These early molecular studies placed the schizotypy model on yet an even firmer foundation, and they have provided more cement undergirding the schizophrenia–­schizotypic psychopathology connection. 7. Moving further toward the molecular: Can we link schizotypic features— as indicators of schizotypy—to polymorphisms or chromosomal regions of interest in schizophrenia? As discussed earlier, there has long been interest in the enzyme catechol-O-methyltransfease (COMT), which is involved with dopamine degradation, as a potential etiological factor or liability indicator in schizophrenia. The three genotypes associated with COMT activity have been linked to neurocognitive performance, particularly executive functioning, which is of relevance to schizophrenia (Egan et al., 2001). One of the three COMT genotypes, known as the val-val genotype, is particularly related to poorest performance on neurocognitive measures. The COMT gene has itself been linked to the schizophrenia phenotype (Owen et al., 2005). Is there a link between COMT and schizotypic features? Two studies from the Stefanis group in Greece have contributed important data on this question. In an initial study of nonpsychotic Greek Air Force recruits, Avramopoulos et al. (2002) reported that the high activity (val-val) COMT genotype was significantly associated with higher levels of scores on the PAS, as well as higher overall levels of total schizotypal features (assessed by the SPQ; Raine, 1991). In a subsequent study, using an expanded sample of those nonpsychotic men drawn from a nonclinical population (Avramopoulos et al., 2002), Stefanis et al. (2007) found that disorganized schizotypic and negative schizotypic features were associated with the val-val COMT genotype. This group recently reported (Stefanis et al., 2008) an association between RGS4 (regulator of the G-protein signaling 4 gene) and negative schizotypic personality features in a large, nonclinical normative sample. Thus the COMT and RGS4 genes are apparently associated with schizotypic features among nonclinical populations.32 Are there other schizophrenia-­relevant polymorphisms associated with schizotypic features? Lin et al. (2005) examined the association between the neuregulin 1 (NRG1) gene on chromosome 8p22-p12 and measures of schizotypic features in a nonclinical population. The NRG1 gene has also been found to be associated with the schizophrenia phenotype and represents a gene of interest (Owen et al., 2005). In a large sample of randomly selected adolescents, Lin et al. (2005) found that there was a substantial allele-dose trend for the NRG1 polymorphism and the PAS. This study pro32 Whether

the COMT gene (or any other, for that matter) continues to be an active focus of schizophrenia and schizotypy investigations remains to be seen. The methodological/conceptual approach is what is being illustrated.

Genetics, Genomics, Phenotypes, and Endophenotypes

217

vided the first empirical association between the NRG1 gene and schizotypy. To the experimental psychopathologist there is much going on here that is of great interest! Clearly, these studies help to further demonstrate that observed or measurable indicators of schizotypy can be linked to a latent construct—in this case, genotypes. These studies also highlight the utility of using configured psychometric values as an endophenotype for schizophrenia. Additionally, the association between the psychometric values of the PAS and the genes of interest demonstrates the clear value of moving across levels of analysis in our efforts to understand schizotypy and schizophrenia (see Kosslyn & Rosenberg, 2005). Finally, these results suggest it is the experimental psychopathologist, with the methods of the experimental laboratory, who may ultimately be able to provide the most sensible anchor points for schizophrenia-­related polymorphisms in the form of measurable neurocognitive processes and psychometric values. By this I mean that polymorphisms may be related (downstream)33 to other configured psychometric values, as well as being linked to other measurable neurocognitive processes, using methods of the experimental psychology laboratory (e.g., working memory, sustained attention, executive control, eye-­tracking dysfunction). These latter processes will be indexed by tasks such as those we discuss throughout this book (e.g., delayed-­response task, continuous-­performance task, smooth pursuit eye movement tasks, n-back task, and so on).34 The constructs tapped by such laboratory tasks, developed by psychopathologists, cognitive neuroscientists, and others, have long been regarded as important tools for solving the schizophrenia puzzle. Connecting task performance to polymorphisms may illuminate their role in the illness. 8. Molecular on a grand scale: Genome-wide approaches to schizotypy. We have discussed attempts to link schizotypy indicators (typically phenom33 One

must always keep in mind that genes do not code for schizophrenia, divorce, social dominance, or any other construct. Nor do they code directly for processes such as working memory, sustained attention, context processing, or smooth pursuit eye movement. Rather, they exert their effects at the cellular level, and any dysfunction at that level will be felt downstream in processes dependent on proper cellular/molecular functioning (not unlike Meehl’s 1962 proposition for schizophrenia regarding hypokrisia and synaptic slippage giving rise to cognitive slippage).

34 Some

experimental pathologists come at the polymorphism puzzle from a different direction. Rather than relating task performance directly to polymorphisms, they begin with an understanding of a neurobehavioral process or system and seek to determine whether the polymorphisms known to influence that particular system of interest are well related to schizophrenia. For example, Talkowski, Bamne, Mansour, and Nimgaonkar (2007) examined the extent to which dopamine (DA)-related genes are associated with schizophrenia, given the well-known connection between DA and schizophrenia. However, Talkowski et al. concluded that the connection between DA polymorphisms and schizophrenia remains uncertain, especially as many association studies were underpowered or suffered from methodological artifacts.

218

SCHIZOTYPY VIEWED FROM THE LABORATORY

enological and/or or psychometric features) to specific loci of interest to schizophrenia researchers. There is currently a short list of loci of interest for schizophrenia (and, by implication, for schizotypy), although its composition and length depends on who one talks to. For example, Harrison and Owen (2003) examine the data from linkage studies and discuss seven genes of interest. These seven genes have demonstrated linkage with the schizophrenia phenotype. Harrison and Owen (2003) evaluate the data supporting the importance of these seven genes, in terms of both replication of the linkage findings and whether or not there is a relevant transgenic mouse phenotype. Of interest, Harrison and Owen (2003) view all of these genes as having plausible biological consequences, though less in the way of functional (i.e., symptomatic) consequences. The genes themselves, as a group, seem to point to involvement with the glutamatergic and other neurotransmitter synapses. Others have summarized this literature as well. For example, Straub and Weinberger (2006) view 17 genes of potential interest in schizophrenia. Owen, Craddock, and O’Donovan (2005) see the data for dysbindin and neuregulin as particularly promising. Finally, in a massive meta-­analysis of all association studies completed as of April 2007, Allen and colleagues (2008) concluded that the evidence about four genes is especially well documented. They are DRD1 (dopamine receptor 1), DTNBP1 (dysbindin), MTHFR (5,10 methylenetetrahydrofolate reductase, an enzyme related to a downstream intracellular methylation process), and TPH1 (which encodes tryptophan hydroxylase 1, the rate-­limiting enzyme in the biosynthesis of serotonin). The Allen et al. (2008) meta-­analysis is remarkable in at least two aspects. First, the list of the four genes that show the greatest evidence of potential involvement in schizophrenia contained some real surprises. For example, some of the horses that others have been betting on, such as COMT, did not appear. Second, the methodology used by Allen et al. (2008)—the meta-­analytic approach to association studies—­ represents a creative use of meta-­analytic methodology for combining research findings in the quest for meaning and direction. Insofar as genetic association studies go, the field is marked by an array of findings that one could consider as either highly inconsistent across studies or potentially of some level of consistency (and worthy of pursuit). This is the old “Is the glass half empty or half full?” dilemma.35 Given the impor35 The

proverbial fullness or emptiness of a glass depends largely on one’s view of heterogeneity in schizophrenia. If one really believes schizophrenia to be a homogeneous illness construct with homogeneity in pathological processes underlying the phenomenology, then the inconsistency of findings really looks like a glass that is half empty. In short, one should not see such inconsistency across genetic findings if the illness is truly homogeneous.

Genetics, Genomics, Phenotypes, and Endophenotypes

219

tance of substantial heterogeneity confronting schizophrenia research, any degree of consistency in findings across studies at the molecular genetic level of analysis is particularly intriguing. One might ask, Do we always need to look solely at loci of a priori interest (i.e., candidate genes) in our search for the genetic basis of schizophrenia? Might it be wiser to take an agnostic approach? By that I mean something of a shotgun36 approach to examining the genome in search of regions potentially harboring a susceptibility locus (or loci) of interest. Unlike the association studies that focus on specific loci of a priori interest (e.g., DRD1, COMT), the genome-wide scanning approach to association does not make any prior assumptions regarding the likelihood that any genetic region is of greater relevance for a phenotype than any other region. Rather, not unlike a shotgun being fired at a target, the genome-wide scan “shoots” at the entire genome to see if any regions emerge as potentially informative with respect to a phenotype. The wideness of the shot pattern—or potential data-­gathering breadth of such studies—­depends in large part on the thoroughness of commercially available gene chips or the density of the marker distribution (i.e., the chips used to interrogate the genome). Finally, despite the potential utility of this method for use with complex illnesses, it is not without critics (e.g., Yoo et al., 2010). 9. What has been found with the genome-wide approach to schizophrenia? What has been found with this approach insofar as schizotypy and schizotypic psychopathology is concerned? First, what do we know regarding schizophrenia from the genome-wide scanning approach? Lewis et al. (2003), in a meta-­analysis of genome-wide scan study results, reported that 12 areas37 (or regions) of interest with respect to schizophrenia emerged from 20 different genome-wide scans across 14 different research groups around the world. The conclusion from this meta-­analysis was that “some or all of these regions contain loci that increase susceptibility to schizophrenia in diverse 36 My students have sometimes asked “what does a shotgun approach mean?” Well, since you asked . . . a shotgun is a firearm that discharges the contents of a shell, and that shell contains numerous small lead pellets (i.e., “shot”). This collection of pellets travels through the air toward a target in an ever-­spreading diffuse “pattern” (or cloud). As such, it is easier for most people to hit a target at which they are aiming with a shotgun as opposed to with a pistol or rifle, which require acuity in aiming at a specific target. The latter devices discharge only a single projectile (i.e., the bullet) per shot, and thus the ability to hit a target with the bullet requires considerably more skill and training. In research, therefore, a “shotgun” approach is one that looks very broadly at a problem and is set up to maximize the chances of making a discovery. The notion is somewhat akin to “casting one’s net widely,” in fishing parlance, in the hope of catching more fish in the effort. 37 The specific regions were found on the following chromosomes: 5q, 3p, 11q, 6p, 1q, 22q, 8p, 20q, and 14p.

220

SCHIZOTYPY VIEWED FROM THE LABORATORY

populations” (p.  34). As noted earlier, genome-wide scans have relied on commercially available gene chips. Thus one must realize that genome-wide scans are limited by the density of the marker arrays that are employed and the distribution of the markers, as well as the number of markers that are assayed (Barrett & Cardon, 2006). Given this concern, how effective can genome-wide scans be? Do they have adequate coverage of the genome? Barrett and Cardon (2006) argue that the first wave of genome-wide scans appears to provide adequate coverage of the world of single-­nucleotide polymorphisms (SNP) in search of loci of relevance to complex phenotypes, such as schizophrenia. However, McCarthy et al. (2008), in a discussion of genome-wide association studies for complex traits, reiterate the importance of sample size, power, and the impact of heterogeneity on such analyses. These authors highlight the importance of the genome-wide scanning approach, yet urge caution in the interpretation of findings from any one study that has not been replicated, a view that clearly makes good sense (although it is not conducive to good headlines in the media that like to report genetics findings all too readily). Second, what do we know regarding schizotypic psychopathology from the genome-wide scanning approach? Here the database is far more limited than what is available for schizophrenia proper. However, what is available is indeed encouraging in supporting a connection between schizotypic psychopathology and schizophrenia from the standpoint of genetic influences. If we take schizotypal symptom features as our indicator of schizotypy, is there evidence suggesting that comparable genetic regions and/or polymorphisms are implicated in both schizophrenia proper and schizotypic psychopathology? Continuing with the tapestry analogy, this is an important warp thread or link to consider. Such a connection would be expected based on prior family and adoption studies that showed an association between schizophrenia and schizotypy. For example, consider the association between schizotypal pathology and schizophrenia in the Kety and Rosenthal Danish adoption studies results or the association between schizotypal pathology and a family history of schizophrenia in Kendler’s RFS. Consider also the Lenzenweger and Loranger (1989a) finding that a schizotypic feature—­perceptual and body image aberrations—in nonpsychotic individuals predicted an increased morbid risk for treated schizophrenia in first-­degree biological relatives. None of these important pieces of evidence had been confirmed by genetic linkage methods prior to 2007. Thus the recent study by Fanous and colleagues (2007) demonstrating significant correlations in linkage signals

Genetics, Genomics, Phenotypes, and Endophenotypes

221

from genome-wide scans of schizophrenia and schizotypy38 (defined as a schizotypal PD feature score derived from the DSM-III-R SPD diagnostic criteria) is both timely and important. These investigators (Fanous et al., 2007) used data from the Irish Study of High-­Density Schizophrenia Families (ISHDSF; Straub et al., 2002), which consists of 270 families in Ireland in which at least two members are affected by psychotic illness. Using a complex regression approach that made important statistical corrections for potential artifacts (i.e., autocorrelation), the NPL score for schizophrenia and the NPL score for schizotypal scores were analyzed in the ISHDSF sample (specifically, schizotypal NPLs were regressed onto schizophrenia NPLs at all chromosomal locations). Fanous et al. (2007) provide an extended discussion of their approach and emphasize analytical practices they adopted to ensure conservative results. What did they find? They found a highly significant correlation between schizophrenia and schizotypal NPLs in two different multipoint analyses. Moreover, their results did not appear to be due to chance when this possibility was evaluated by testing what are known as null scans for the schizotypal and schizophrenia genotypes. Probing these results further, Fanous et al. (2007) reported that two chromosomal regions contained evidence of a common genetic component in both schizophrenia and schizotypal features.39 Those two regions were located at 5q22.2 and 16q22.1-q22.1; two additional regions were identified as suggestive, 6q25.3 and 19p13.3. What is going on in these regions? Are there genes in these “neighborhoods” that have particular relevance for schizophrenia and schizotypy? These questions remain to be answered. However, these studies build important bridges between schizotypy and schizophrenia at the genetic level, providing critical evidence for continuity between the two phenotypes. Although there is a conspicuous lack of molecular genetic research on schizotypy, the Fanous et al. (2007) data complement those reported by Avramopoulos et al. (2002) and Lin et al. (2005) for COMT and neuregulin, respectively. I would suggest that this continuity is consistent 38 These

authors use the term schizotypy to refer to what is a continuous score of SPD symptom features. In the interest of clarity and consistent with the model emphasized in this discussion, the term schizotypal is used to describe their putative schizotypy indicator. The reader will remember that schizotypy, per se, is not measured directly; rather, it is a latent construct, and it is assessed indirectly through putative indicators that have a fallible and probabilistic relation to the latent construct.

39 Fanous

et al. (2007) reported that regions containing the highest schizotypal NPL scores were in regions that have been previously linked to schizophrenia (e.g., Brzustowicz et al., 1997, positive schizophrenia symptoms and chromosome 6p). Using a modified threshold criterion for NPL scores, they noted that the two regions with the highest NPL score for both schizophrenia and schizotypy contained the DTNBP1 (dysbindin) and neuregulin-1 genes.

222

SCHIZOTYPY VIEWED FROM THE LABORATORY

with a model that holds that the latent construct schizotypy underlies schizotypic features and schizophrenia, as has been argued throughout this book. Clearly, the molecular genetic bridge undergirding both schizophrenic and schizotypic phenomenology is coming together. Where in this process can the experimental psychopathologist contribute to the effort? The answer is, in many places! For example, there are as yet really no substantial data bearing on the genetics of endophenotypes in relation to known regions of interest in schizophrenia. The genome scan correlation methodology of Fanous et al. (2007) shows considerable promise for use in future investigations with putative endophenotypes. However, any study seeking to link endophenotypes to the genetic substrates for schizotypy/schizophrenia will need to do so with full appreciation for heterogeneity in both performance on endophenotype measures and the possible heterogeneity of genetic influences themselves. Of course, the selection of endophenotypes for such molecular genetic studies must be based on the construct validity of those endophenotypes considered.40 10. Endophenotypes, schizotypy, and schizophrenia: Pulling it together while facing heterogeneity. There are many contenders for potential endophenotype status in relation to schizophrenia liability (schizotypy). It is, however, highly unlikely that any one endophenotype will represent the royal road to schizotypy owing to the fallible (probabilistic) relations that nearly all endophenotypes will have with the underlying construct. Any potentially fruitful research on schizotypy, endophenotypes, and genetics will need to deal with the issue of heterogeneity head on. The heterogeneity concern is not an arcane matter or trivial fine point; rather, it strikes at the heart of the entire research effort involving endophenotypes. For example, it is known from multivariate research on putative endophenotypes that not all schizotypes are deviant on all measured processes. In a laboratory study we conducted 40 I

should imagine that there will be any number of molecular genetic endophenotype studies conducted that will, despite their apparent technical complexity, be studies of convenience. By this I mean I could well imagine that some endophenotypes, despite their superior construct validity, might be overlooked in favor of others because, perhaps, measurement of the former is more difficult in some manner. Moreover, I suspect hobby-horse endophenotypes will be examined more because they are favorites of the laboratory doing the study, even though they are lacking in overall validity as indicators of schizotypy (i.e., schizophrenia liability). For example, despite trenchant critiques by Levy et al. (2004; 2008) that should temper genuine enthusiasm for antisaccade performance as an endophenotype, I imagine one will find it included in some endophenotype research. Thus, although there has never been a failure to replicate the difference between normals and schizophrenia patients on the antisaccade task (cf. Levy et al., 2008), that pattern of results does not promise a valid endophenotype despite its apparent glitter. Research moral from the Bard: “all that glitters is not gold” (Shakespeare, The Merchant of Venice, 1596).

Genetics, Genomics, Phenotypes, and Endophenotypes

223

in the early 1990s, we examined multiple potential endophenotypes in the same subjects (sustained attention, executive functioning, spatial working memory, negative priming, smooth pursuit eye movement, antisaccade performance, and thought disorder; Lenzenweger, 1998). When considering deviant performance (as referenced against the distribution of performance among the normals) across each of these processes, we discovered that only about 20% of the schizotypic subjects displayed markedly deviant performance on three or more of these candidate endophenotype tasks. Clearly, not all schizotypes are deviant on all candidate endophenotype tasks, and the pattern of deviance varies across schizotypic subjects.41 For endophenotype research to progress, it must embrace methods models for resolving performance heterogeneity on candidate measures. We have studied heterogeneity in putative endophenotypes in two different ways. The first involved the development of an analytic strategy whereby, with certain statistical assumptions, we could parse a group of schizotypic subjects into those who were “genuine schizotypes” and those who were considered “false positives” (Lenzenweger, Jensen, & Rubin, 2003). The second involved the systematic study of leading putative endophenotypes (e.g., sustained attention deficits and smooth pursuit eye movements) in a large, relatively unselected quasi-­population sample and the subsequent application of the technique of finite mixture modeling to the data (Lenzenweger, McLachlan, & Rubin, 2007; see also Chapter 11, this volume). In the first study, we (Lenzenweger, Jensen, & Rubin, 2003) began with two different groups of subjects, one a normal group and the other a putative schizotypic group. Membership in each group was defined as a function of deviance on the well-known psychometric measure of schizotypy, the PAS (Chapman et al., 1978). Given that the PAS, like all psychometric measures, is assumed to be fallibly related to the underlying schizotypy construct, then those subjects identified as schizotypic on the PAS will consist of two groups: those who are really schizotypic and those who show elevations on the PAS for reasons other than schizotypy. As far as those subjects in the group showing essentially no elevation on the PAS (i.e., nor41 The

same is true for schizophrenia patients as well. Not all schizophrenia-­affected individuals are comparably deviant across all endophenotype tasks, and patterning of deviant performance varies greatly across endophenotypes in schizophrenia cases. For example, a schizophrenia patient might display highly deviant sustained attention and poor executive functioning, whereas his or her performance on smooth pursuit eye movement and context processing tasks may be unremarkable. Another patient, by contrast, might display poor context processing, impaired executive functioning, and impaired smooth pursuit eye tracking but largely intact sustained attention performance. No one endophenotype has cornered the market on truth.

224

SCHIZOTYPY VIEWED FROM THE LABORATORY

mals), we made the working assumption that the PAS rarely misclassified a schizotype as normal, given all that we know about the scale (Chapman et al., 1995; see also Kwapil et al., 2008).42 In the Lenzenweger, Jensen, and Rubin (2003) study, we used the probability structure observed for the normal subjects as defined by performance on two laboratory measures, eye­tracking dysfunction (i.e., poor smooth pursuit) and failure to maintain set (an index of poor performance on the well-known Wisconsin Card Sorting Test; Heaton, 1981) as a starting point in our effort to parse the schizotypic subject group. We hypothesized that normals misclassified as schizotypic subjects would have the same probability structure as correctly classified normals, whereas the true or genuine schizotypes would have a different probability structure from the normals. In order to parse the schizotypic group, therefore, we needed to solve for an unknown variable that would help us execute the parsing. We were able to compute such an unknown variable by treating the overall classification problem as similar to a missing data problem, wherein we did not know the values of the individuals initially classified as schizotypic on this unknown variable (see Lenzenweger, Jensen, & Rubin, 2003, for technical detail). Using the expectation­maximization (EM; Dempster, Laird, & Rubin, 1977) algorithm, this otherwise daunting statistical task became tractable, and we were able to classify the schizotypic subjects into two subgroups, one we termed true or genuine schizotypes and the other false-­positive schizotypes. In order to examine the validity of this parsing strategy, we compared the resulting three groups of subjects (normals, false-­positive schizotypes, genuine schizotypes) on three performance measures (also considered possible endophenotypes) that were not included in the initial statistical model. Our hypothesis was straightforward: if our statistical model and method for heterogeneity reduction were worth their salt, we expected that the genuine schizotypic subjects would show greater deviance on the measures within this set of external validity criteria than the normals and false-­positive schizotypes. Indeed, that is what we found. The genuine schizotypes displayed slower reaction-time performance on a Continuous Performance Test (CPT; Cornblatt, Lenzenweger, & Erlenmeyer-­Kimling, 1989), higher levels of thought disorder (Coleman, Levy, Lenzenweger, & Holzman, 1996), and greater impairment on a measure of spatial working memory (Park, Holzman, & Lenzenweger, 1995) than the other two groups. This model and method represent a pos42 Another

way to think about our assumptions regarding the diagnostic efficiency of the PAS is that the instrument will generate more false positives (falsely identify some individuals as schizotypic when they are not) than false negatives (falsely identify some schizotypic subjects as normals).

Genetics, Genomics, Phenotypes, and Endophenotypes

225

sible approach to reducing heterogeneity within a mixed set of study subjects (normals and schizotypes), a fairly common setup in experimental psychopathology research.43 The second study in this program of research also used endophenotypes to approach the heterogeneity problem and the evaluation of competing models of the structure of the latent liability for schizophrenia (i.e., schizotypy; Lenzenweger, McLachlan, & Rubin, 2007). This study was guided by several concerns. First, although for many years it has been assumed that deviance on a putative schizophrenia endophenotype predicted the presence of liability, most research on the endophenotypes had been done in a manner that did not actually address this conditional relationship. That is, most research on endophenotypes actually finds deviance on a putative endophenotype given the presence of schizophrenia liability, rather than the other way around (e.g., schizophrenia patients display poor spatial working memory, rather than that those deviant on spatial working memory measures possess schizotypy or schizophrenia liability). Thus a study needed to be done in which individuals were not selected a priori for the presence of schizotypy (schizophrenia liability) in order to see whether deviance on a putative endophenotype really was associated with an increased likelihood of the presence of schizotypy-­related features. Second, prior to this study, there had been relatively few studies in which more than one candidate endophenotype had been examined in the same people. Multivariate data sets bearing on the latent structure of the construct defined by a multivariate endophenotypic hyperspace were essentially nonexistent. Although prior studies had used psychometric measures of schizotypy as the basic data for latent structure analysis (as detailed in Chapter 11, this volume), there had been no prior study using laboratory-based measures. In the Lenzenweger, McLachlan, and Rubin (2007) study, we tested nearly 300 individuals with no prior history of psychosis on measures of sustained attention, smooth pursuit eye movements, schizotypic personality features, and other measures. In order to examine the latent structure of the multivariate space defined by deficits in sustained attention and eye tracking (indexed by two well-­regarded quantitative measures; Lenzenweger, Cornblatt, & Putnick, 1991; O’Driscoll, Lenzenweger, & Holzman, 1998; Bergida & Lenzenweger, 2006; Lenzenweger & O’Driscoll, 2006; O’Driscoll & Cal43 This

exercise and project were stimulated by the fact that traditional approaches to the reduction of heterogeneity—such as factor analysis and cluster analysis—have been deemed fundamentally inadequate for redressing the substantive heterogeneity problems we face in experimental psychopathology research (see Lenzenweger, Jensen, & Rubin, 2003).

226

SCHIZOTYPY VIEWED FROM THE LABORATORY

lahan, 2008), we used a statistical technique, also based computationally on the EM algorithm, known as finite mixture modeling (McLachlan & Peel, 2000; Titterington, Smith, & Makov, 1985). Finite mixture modeling, which seeks to resolve the number of relatively distinct qualitative normal components underlying a data array, was particularly useful in this context (see Lenzenweger, McLachlan, & Rubin, 2007). We found that two components provided the best fit to the multivariate data array for the sustained attention and eye-­tracking data in this sample of community subjects. The resolution of these two components was consistent with theoretical predictions regarding the latent structure of endophenotypic measures of schizotypy (cf. Meehl, 1990; Holzman et al., 1988; Lenzenweger & Korfine, 1992a), as well as a theoretical model that posits a severe threshold effect on an underlying, continuous liability construct (e.g., the multifactorial polygenic threshold model; Gottesman, 1991). In this sample of 300 individuals, we estimated that approximately 27% of the sample might be regarded as potential schizotypes, whereas the remaining 73% would not be so classified.44 The putative schizotype class displayed higher levels of schizotypic features as indexed by Raine’s SPQ (Raine, 1991) compared with the subjects in the nonschizotype component. These differences in schizotypic phenomenology were reflective of medium-sized effects. An important question for the Lenzenweger, McLachlan, and Rubin (2007) study was whether the deviance on the endophenotypes of sustained attention and eye tracking, reflected in the subjects inhabiting the smaller of the two components, would be associated with schizophrenia-­related psychopathology. Clearly, our subjects did not have schizophrenia; they were not expected to, as this was a study of endophenotypes of schizotypy in subjects ascertained from the community. Would schizophrenia be found in the first-­degree biological relatives of these subjects, and, if so, where would those cases be concentrated? All cases of treated schizophrenia were found among the first-­degree relatives of subjects within the putative schizotype (i.e., second) component revealed by the finite mixture modeling.45 Our study (Lenzenweger, McLachlan, & Rubin, 2007) demonstrated that the 44 A

supplementary taxometric analysis yielded results highly consistent with those obtained using the finite mixture modeling approach described here (see Lenzenweger, McLachlan, & Rubin, 2007).

45 Subjects in the two components identified in this study did not differ on metrics such as age, education, intellectual speed of processing, or parental educational levels. Moreover, the vast majority of general psychopathology (including bipolar disorder, depression, eating disorders, and so on) was found among the first-­degree relatives of those subjects in the nonschizotype component. Thus the schizotype component was not merely identifying persons who revealed generalized intellectual deficits or a propensity for all sorts of psychopathology.

Genetics, Genomics, Phenotypes, and Endophenotypes

227

heterogeneity of performance on various endophenotypic measures across individuals could be resolved using a statistically well-­principled technique. The resultant parsing made sense in terms of phenomenology in the subjects themselves, as well as in terms of their family history of psychopathology. For the experimental psychopathologist, the message here is simple—use the endophenotype measures that are well substantiated in the extant research corpus, but be sure to take heterogeneity into account when probing these data for meaning and direction. Appropriate statistical methodologies now exist for such probing, chief among them the mixture model-based methods (McLachlan & Peel, 2000; McLachlan, Do, & Ambroise, 2004). Using such data (i.e., endophenotype-based data) and appropriate statistical methods, one increases one’s ability to refine units of analysis that are robust (i.e., not based on only one endophenotype; not based on subjectively determined cutoff scores or artificial demarcations) and well suited for genomic analysis. The modern experimental psychopathologist—­especially one with an interest in polymorphisms, genome-wide scanning, and the like—will find such statistical methods useful in addressing heterogeneity. Importantly, these methods will help find order in data through the organization of persons or cases, as opposed to simply reorganizing variables as is done in factor analysis (e.g., Lenzenweger, McLachlan, & Rubin, 2007; McLachlan et al., 2004).

The New Frontiers: Incorporating Epigenetics, Structural Variation, and Other Assumptions into Genetic Models of Schizotypy and Schizophrenia Most of the theorizing and empirical research in the genetics of schizophrenia has focused on the phenotype of schizophrenia as the unit of analysis in relation to presumed genetic influences. As noted, the corpus supporting genetic factors in schizophrenia now has the status of established scientific fact (Gottesman, 1991; Cardno & Gottesman, 2000). Indeed, most (if not all) experimental psychopathologists work within a framework that holds genetic factors as causally intrinsic to the disorder. However, as the field of genetics/genomics has developed, we have learned that other important factors or mechanisms modify expression of genes outside of the gene proper, so-­called epigenetic influences. Recent research has also pointed to the importance of variations in the genome that are structurally changed, which is manifested in what are termed copy number variations.

228

SCHIZOTYPY VIEWED FROM THE LABORATORY

Epigenetics: Acting upon the Actors Is it the case that only that information contained directly within our genes is responsible for determining the impact of those genes on the development and behavior of the organism? The short answer is no. Clearly, the role of environment is important in shaping the outcome of a genotype, as is well known. For example, although one might carry the genetically determined potential to be rather tall, extremely poor nutrition during critical periods of childhood and adolescence will modify this potential and influence the height the person attains. However, are there other influences within us, close to our genetic structure, that can influence outcome? The short answer is yes, and it is a very exciting yes! We now know that there are epigenetic influences on the activation, or nonactivation, of our genes. The activation or nonactivation of genes results in a process of differential gene expression, which has been termed genetic regulation, gene expression, epigenetic control, or epigenesis. The study of such influences is known as epigenetics. The term epigenetic literally means “upon (epi-) the genes (-genetics),” or factors that act upon genes from outside the genes themselves. An epigenetic influence or factor helps to modify of the activation of certain genes without altering the basic structure of DNA. Thus epigenetic influences are potentially at play when one sees inherited changes in gene expression that are not reflective of nucleotide sequence variation.

Example Consider the following example. The offspring of tigers are typically similar to their tiger parents in size. The same is true of the offspring of lion parents. However, when a male lion mates with a female tiger, the offspring (a liger) is typically exceptionally large in size and stature and dwarfs both of its parents (see Figure 7.4). In contrast, when a male tiger mates with a female lion, the offspring (a tigon) does not exceed the size of the biological parents. What is going on here? In the case of the liger, current scientific opinion suggests that a growth inhibitory epigenetic influence normally inherited from the female lion is not present, as the mother of the liger is a female tiger. Normally, this growth inhibitory epigenetic influence from the mother lion constrains the possible reaction range for physical size among lions, but it is not present in the case of the liger, because tiger moms do not have it. Basically, gene expression depends on whether the gene has been inherited from the mother or father in this case. This would represent

Genetics, Genomics, Phenotypes, and Endophenotypes

229

FIGURE 7.4.  The animals in the photographs are known as “ligers.” Ligers are the result of the mating between a male lion and female tiger. The unusual size of the animal is the result of diminished epigenetic control over growth that normally derives from the female lion. The animal in the left panel is 10 feet tall and will grow to 12 feet at maturity, considerably larger than the normal offspring of tigers. Photos copyright 2006 by Alison West. Reprinted by permission.

a form of genomic imprinting, or an epigenetic process outside the realm of normal Mendelian inheritance. There are other forms of epigenetic influence as well, and they can be described as examples of transcriptional control (i.e., whether messenger RNA is or is not transcribed from DNA; see Carey, 2003, for an excellent discussion). Not only are epigenetic effects likely to be important in illuminating the etiology and pathogenesis of schizophrenia, but they may also be of considerable utility in unraveling one of the longtime mysteries of schizophrenia genetics research, namely, discordance for schizophrenia in MZ twin pairs (see Wong, Gottesman, & Petronis, 2005). In short, the role of epigenetic factors in the etiology and development of schizophrenia will need to be carefully considered to determine whether epigenetic influences shape or alter the expression of schizophrenia liability genes insofar as final outcome (clinical illness) is concerned. An excellent introduction to this model of genetic theorizing, with special relevance to psychopathology, including schizophrenia, can be found in the work of Petronis (2001, 2004, 2006; see also Carey, 2003).

230

SCHIZOTYPY VIEWED FROM THE LABORATORY

Structural Variation: The Case of Copy Number Variation Most modern molecular genetic studies of schizotypy and schizophrenia take the form of linkage studies or association studies. In linkage studies, the linkage procedure uses information regarding established genetic markers to determine whether these markers tag along with a phenotype of interest (e.g., schizophrenia). If a marker is found to tag along with a phenotype of interest, then one speaks of “linkage,” and the scientist knows that he or she is in the neighborhood of a putative susceptibility locus for the illness phenotype. In a sense, using an analogy to street addresses, you know by virtue of the address of the marker that the susceptibility locus probably resides nearby on the same street as the marker, but the specific address of the susceptibility locus is not known. In association studies, one determines whether specific genes have some elevated probability of tracking with a phenotype of interest. Association studies tend to be done to further probe a gene region after linkage studies, perhaps, suggested a region of interest (via linkage). An alternative use of the association study involves the study of polymorphisms in a protein-­coding gene that has substantive relevance to a process (e.g., working memory, executive functioning), trait (e.g., agentic positive emotion), or illness (e.g., schizophrenia, depression)—for example, the focus on the COMT gene, which codes for an enzyme that catabolyzes dopamine, in studies of prefrontal cortex functioning in schizophrenia as manifested on a neuropsychological task (Egan et al., 2001). Extended discussion of the specific features of linkage versus association methodologies can be found in Cardon and Bell (2001); Risch (2000); and Carey (2003). Both linkage and association studies focus on connecting specific gene regions or genes with illness as the phenotype. The fundamental goal here, with either linkage or association studies, is to determine whether single genes contribute to the risk for an illness (or to an endophenotype). Is it possible that there are other forms of genetic variation that might be associated with increased risk for illness? Yes! There may be genes or groups of genes that act together to cause an illness and that are quite penetrant but that reflect structural changes in genes rather than sequence changes. They can be inherited or they can occur as sporadic events. These would be referred to as rare variants. As discussed by Levy and Sebat (2010), the mechanism by which these rare variants confer increased risk for disease is genomic rearrangement, which changes gene expression by causing structural alterations in genes:

Genetics, Genomics, Phenotypes, and Endophenotypes

231

Genomic rearrangements refer to duplications, deletions, inversions, or other alterations of chromosomal material that affect gene copy number (hence the term copy number variant or CNV). Genomic rearrangements alter gene function by changing the structure of genes, not by changing sequence. When these structural alterations occur within a coding region, they can impact gene function in a variety of ways—by disrupting genes, by changing gene dosage and/or expression, by producing major alterations in protein sequence, or by positional effects on neighboring genes. (p. 3)

Clearly, there is considerable evidence of a good deal of structural variation in the human genome (e.g., Khaja et al., 2006), and CNVs are now well documented as a phenomenon on the human genome (Jakobsson et al., 2008; Redon et al., 2006). The existence of structural variation in the human genome opens up entire vistas for research in psychopathology. As in the autism research area (Sebat et al., 2007), the search for rare structural variants in relation to schizophrenia is clearly on and represents an additional new frontier for further exploration (McClellan et al., 2007; Walsh et al., 2008; Levy & Sebat, 2010; Stefansson et al., 2008). Of course, a major question regarding structural variants is, What proportion of the cases assigned the diagnosis of schizophrenia is accounted for by structural variants? The answer to this question is unknown at present, and extended, focused study will be required to resolve it.

Not One, Maybe Not Sum, but Possibly Configuration Initially, those seeking to understand the genetics of schizophrenia, after swimming against the tide of socialization science46 models of etiology and pathogenesis, sought evidence for a contribution to etiology from a schizophrenia gene or multiple schizophrenia genes. Indeed, Meehl’s seminal model held the existence of a dominant schizogene as a core component. Others have advocated the possible existence of multiple genes that play a role in the determination of schizophrenia liability. Further, this liability converts to expressed disease when the final sum total of assets and liabili46 The

term socialization science was proposed by the late developmental behavioral geneticist David Rowe (1994). He intended it to describe those theoretical and ideological points of view that held that the formative and driving influences in charge of intellectual, personality, and psychopathology development were to be found solely in the psychosocial environment and in the socialization experiences of the individual. The “socialization science” view, according to Rowe, (incorrectly) gave little credence to the importance of genetic factors and influences in intellectual, personality, and/or psychopathology development.

232

SCHIZOTYPY VIEWED FROM THE LABORATORY

ties passes some threshold (Gottesman & Shields, 1972, 1973; Gottesman, 1991). A critical notion in this model is the summing of the genetic effects through an additive mechanism.47 The assumption of the summing of deleterious gene effects sets the polygenic threshold model apart from another theoretical perspective on the manner in which the genes might possibly exert their influence on schizophrenia liability. Could it be that the genes that contribute to schizophrenia do not simply “add up” to schizophrenia liability levels? Rather, might it be that they interact with one another, and that it is the specific combination of genes that matters? Could it be that the genes might “multiply” one another and that schizophrenia liability really represents the “product,” rather than the sum? Consider that the individual genes responsible for schizophrenia liability represent a profile (not unlike an MMPI or Wechsler Adult Intelligence Scale [WAIS] profile). Maybe it is really the shape or configuration of that profile that really matters. Not that one needs 5 out of 20 possible genes related to schizophrenia to throw one past a liability threshold, but rather one requires a specific “combination” of genes to put one into the schizotypy-­positive (or liability-­positive) basket. Geneticists speak of such multiplicative relationships among disease-­relevant genes as indicative of epistasis, or the interaction between genes (in short, the effect of one gene is influenced or modified by other genes). Could it be that in seeking the genes that “add up” to schizophrenia, we have overlooked the possibility that the multiplication of gene influences is what matters? Cardiovascular disease (stenosis or “blocking” of coronary arteries) represents a complex, multifactorial disease entity that has defied geneticists, not unlike schizophrenia. The coming to terms with the complexity of the etiological factors responsible for cardiovascular disease, as well as the likely existence of epistatic effects in the systems underpinning susceptibility, has been a slow process. However, in a brilliant discussion of cardiovascular disease, Sing et al. (2003) state: The distribution of disease among individuals, families, and populations is a direct consequence of the distribution of interactions [italics added] between the effects of many susceptibility genes and many environmental exposures, that, through dynamic, epigenetic, regulatory mechanisms, ultimately become integrated to generate the disease phenotype. (p. 1190) 47 The threshold notion is the other critical component in this model. A polygenic threshold model that assumes a threshold or jag is sometimes referred to as a “quasi-­continuous” polygenic model.

Genetics, Genomics, Phenotypes, and Endophenotypes

233

Indeed, Sing’s group (Hamon et al., 2004) has shown evidence of epistatic effects in relation to the apolipoprotein E (APOE) gene in males, a gene that is known to be related to forms of cardiovascular disease (as well as senile dementia, Alzheimer’s type). To what extent has epistasis been found in relation to genes thought to confer increased liability for schizophrenia? This fascinating issue is really just beginning to be explored.48 For example, recent reports have provided evidence consistent with epistatic effects for several genes (COMT, GAD1, and ATK1) thought to be related to schizophrenia liability (Buchholtz et al., 2007; Straub et al., 2007; Tan et al., 2007). These new studies suggest that for schizophrenia it may not be that just one gene is of great importance or that an additive sum of influences is important but rather that the configuration of genes and their interaction matters most. Given that the effects of susceptibility genes for schizophrenia play out their effects in neurocognitive and neuroaffective dysfunction, that may be where experimental psychopathologists will play a lead role in research on epistatic effects.

Heterogeneity versus Homogeneity in Genetics, Pathology, and Phenomenology: A Question of Pathways Throughout this discussion, the theme of heterogeneity has arisen again and again. It represents, at once, both a reality of schizotypy/schizophrenia and an unmitigated challenge to all researchers. We need to grasp fully the impact of this notion. Our job as psychopathologists is to discern the precise nature of the heterogeneity that we observe, as well as to understand the levels at which it exerts its influence. One way to ponder this important issue is to consider at least three levels of analysis in relation to the notions of homogeneity and heterogeneity: (1) genetic, (2) pathological, and (3) phenomenological. The level at which heterogeneity occurs has important implications for understanding schizotypy and schizophrenia. It not only influences the manner in which we regard the disease construct (one illness vs. several) but also affects the manner in which research on the causal inputs can proceed. In short, research will necessarily proceed differently if we accurately understand potential variation in genetic influences, pathological processes, and phenomenology. 48 The possibility that epistatic effects are related to the etiology of schizophrenia suggests the importance of using research methods that can actually detect epistatic interactions (e.g., linkage as opposed to association studies; see Culverhouse, Suarez, Lin, & Reich, 2002, for details).

234

SCHIZOTYPY VIEWED FROM THE LABORATORY

In this context the importance of the concepts of equifinality and multifinality (Cicchetti & Rogosch, 1996, 2002) becomes apparent. Derived from general systems theory (von Bertalanffy, 1968), these concepts reference the relationship between causal factors and final outcomes. They have considerable relevance to this discussion insofar as they help to organize the various possibilities at the three levels of analysis in question. Multifinality means that diverse or divergent outcomes can arise or evolve from a common, original starting point. In short, varied outcomes can emerge despite a common origin. For example, a common genetic substrate may eventually reveal different phenotypes downstream as a result of developmental forces at work (cf. Waddington’s developmental–­epigenetic landscape notion; Waddington et al., 2008). The notion of equifinality “specifies that a common outcome will develop over time from different starting points, indicating that diversity in processes is involved in attaining the shared outcome” (Cicchetti & Rogosch, 2002, p. 12). Cicchetti and Rogosch (2002) discuss equifinality through consideration of adolescents who develop depression; whereas some adolescents develop clinical depression due to a history of emotional and physical abuse, others develop the same phenotype (i.e., clinical depression) due to a genetic liability for the illness. Let us consider some interesting possibilities concerning genes, pathology, and phenomenology in light of homogeneity and heterogeneity. Perhaps the simplest possibility regarding the basic nature of schizotypy and the ultimate outcome of greatest clinical salience—­schizophrenia—is embodied in Model 1 in Table 7.4. Model 1 holds that there is relative homogeneity in terms of genetic influence, pathological process, and final symptom picture. Although less than plausible, the model should be defined. Our TABLE 7.4. A Comparison of Models across Three Levels of Analysis and the Influences of Homogeneity and Hetero-geneity Assumptions Model 2

Model 3a

Model 3b

Final-common-pathway variants Equifinality perspectives

Level of analysis

Model 1

Quasimultifinality

Genetic

Homogeneous

Homogeneous

Heterogeneous

Pathological

Homogeneous

Homogeneous

Phenomenological

Homogeneous

Heterogeneous

Model 4 Truemultifinality

Model 5

Heterogeneous

Homogeneous

Heterogeneous

Homogeneous

Heterogeneous

Heterogeneous

Heterogeneous

Homogeneous

Homogeneous

Heterogeneous

Heterogeneous

Genetics, Genomics, Phenotypes, and Endophenotypes

235

understanding of schizotypy and schizophrenia suggests some heterogeneity exists, minimally at the level of phenomenology and pathology, as well as, most probably, genetic influence. Variants of multifinality can be found in Models 2 and 4, whereby there is truly a common genetic substrate underlying all variants of the illness. These models would be agnostic as to whether such a genetic architecture would be additive, epistatic, or reflective of a mixed model (relatively major locus or loci interacting with a background of polygenic effects). The important consideration is that schizotypy and, therefore, schizophrenia results from a variable set of genetic factors at its origin. Models 3a and 3b refer to what I call “final common pathway variants/equifinality perspectives.” The “final common pathway” conceptualization is well known generally, and the current discussion unpacks the notion a bit further within a context of equifinality. What is meant by the “final common pathway variants/equifinality perspectives”? By this I mean that the construct of schizotypy (and, therefore, schizophrenia) has its origin in divergent (different) genetic factors, yet these factors begin to converge (reflect homogeneity) with development. In Model 3a, the pathological process consolidates into a final common pathway, and this common pathway is further exemplified in a relatively homogeneous phenotype. Thus in Model 3a different genes converge on a common pathology and common symptom picture. Model 3b represents an importantly different variant on the final common pathway notion. In 3b, the illness system, if you will, begins with divergent genetic inputs, which play themselves out in heterogeneous (different, variable) pathological processes, yet end with a roughly common phenomenological phenotype. Thus the phenomenological end point for Model 3b reflects a “final common phenomenological pathway.” It is important to realize that both Models 3a and 3b have different starting points and potentially different pathological processes (3b) but a consistent phenomenological end point. Model 5 must be confronted and represents what is perhaps the most challenging and vexing possibility in terms of understanding schizophrenia, because it suggests different genetic inputs, yielding different pathological processes, and relatively striking phenomenological heterogeneity. Model 5, more or less, represents “the nightmare scenario” for schizophrenia research and treatment—­namely, that we are dealing with a collection of vaguely similar illnesses that coalesce into a coarse and variable symptom picture while having different genetic origins and different pathological processes.

Chapter 8

Probing Critical Neurocognitive Endophenotypes Attentional Dysfunction, Executive and Working Memory Functioning, Eye-­Movement Dysfunction, and Thought Disorder

The value of clinical observation in the study of schizotypic pathology cannot be stressed enough as it is the source of hypotheses. That is, one should stay attuned to the signs, symptoms, and experiential components of psychopathology as one seeks to glean insights into the underlying processes that are disrupted. Recall the patient whom I was evaluating who wondered if he was being taken into a “star chamber” as we entered a case conference room, and recall also how this phenomenological moment, if one will, led to my ongoing research interest in perceptual aberrations. Putting such observations to work in the laboratory is where the exciting and challenging work of experimental psychopathology lies. It is where the intellectual rubber meets the laboratory road. However, and of critical importance, one must understand that the process by which one gets from the clinical observation to an experimental protocol is often not terribly linear. To illustrate this, I share my own observations, hunches, and conceptual leaps that led me to do research on a group of cognitive and motor processes that constitute potential endophenotypes in schizophrenia and schizotypy. I also share stories of discovery from others, such as Philip S. Holzman and his pursuit

236



Probing Critical Neurocognitive Endophenotypes

237

of smooth pursuit eye-­movement dysfunction in schizophrenia, as well as Sohee Park and her discovery of working memory deficits in schizophrenia. Both of these individuals shaped the course of modern experimental psychopathology by following, in a nonlinear manner, early observations and making intuitive intellectual leaps. The intention in these examples is to show how one can move from an observation or a hunch to a hypothesis and on to a finding of scientific value. In this chapter, I discuss the establishment of what many regard as the central neurocognitive endophenotypes in schizotypy and schizophrenia research, namely, attentional dysfunction, executive processing dysfunction, and eye-­tracking dysfunction.

On Missing Every Other Bit (or Byte): Sustained Attention and Schizotypy Imagine that for every ten tiny bits (or bytes) of information coming your way, you missed one, two, or three out of the ten. Imagine the havoc such spotty information processing would cause for you while driving, taking a test, conversing with a friend, writing a letter, or monitoring a radar screen as an air traffic controller. In short, imagine that you could not sustain your attention very well when you wanted to do things in the world that required your full attention. What must it be like to miss pieces of information in a social interaction, while watching the news on the television, or listening to a piece of music? Listening for intelligible information in the Beatles song “Number 9” (from the White Album) while it was being played backward must surely be easier than missing, for example, every fourth or fifth piece of information coming your way. Imagine further that this erosion of your ability to attend came and went in an intermittent fashion or seemed worse at some times than at others. That is, your ability to attend degrades momentarily, and you simply do not know when that will happen. We depend on our ability to sustain attention to information, to take it in, to process the context in which it occurred, to digest the full stream of data in the conduct of our everyday lives. We need efficiently functioning attention to do really most anything that matters, whether in the technical, social/interpersonal, emotional, educational, or other psychological domains. Many people who have schizophrenia have talked about the difficulties that they experience with their attention and concentration. Whereas most of us take for granted our ability to read a page in a book (such as this one), attend a lecture, listen to a news broadcast, and so on. We simply sit down and “pay attention.” Both Kraepelin and Bleuler observed that their

238

SCHIZOTYPY VIEWED FROM THE LABORATORY

patients with schizophrenia had difficulties with attention. The descriptive literature regarding the experience of the symptoms of schizophrenia, particularly during the early stages of the illness, is overflowing with accounts of how hard it is for people with schizophrenia to attend to information, whether the information comes from visual, auditory, or other types of stimuli.1 That patients suffering from schizophrenia, whether they are in an acute full symptomatic episode, in their first episode, in remission, or following a chronic course of illness, have problems in maintaining their attention is a well-­established fact. This empirical finding, especially as regards sustained attention (one of several forms of the broad array of attention processes), had been described for many years (Cornblatt, Risch, Faris, Friedman, & Erlenmeyer-­Kimling, 1988; Cornblatt & Malhotra, 2001; Cornblatt & Keilp, 1994; Nuechterlein & Dawson, 1984). But what about attention in the schizotype? Do schizotypes show deviance in their attentional processing consistent with their subjective experiences of drift-outs, space-outs, and moments of confusion? Influenced in part by the seminal study of Cornblatt and Erlenmeyer­Kimling (1985), which documented the early presence of attentional dysfunction in children who were born to parents suffering from schizophrenia, Meehl’s model of schizotypy that suggested that the liability should show itself in some manner long before clinical illness, and my own observations of schizotypes, I pondered the subjective experience of the schizotype and the processes underpinning that experience. Through continued clinical work with schizotypic individuals, I had heard many of them describe how they would intermittently drift off during a conversation or therapy session. Or some would describe how they would be walking along, perhaps at night, and, just for a moment, not be sure that they had seen something correctly (e.g., a shadow or bush was mistaken for a person). In these instances many schizotypic persons would say to me, “You know, I just spaced out for a moment, and then I wasn’t sure if a person was there or not.” This sort of clinical observation had been noted by Meehl (1964) in his Manual for Use with Checklist of Schizotypic Signs (see checklist in Appendix A, this volume) under the rubric “micropsychotic episodes.” He viewed these micropsychotic episodes, which could be brief, as diagnostically important as long as the episode involved “elements of confusion, or altered consciousness, or delusional distortion” (p. 32) and were not limited to periods of extreme 1 These descriptive accounts are not reviewed here. The classic McGhie and Chapman (1961) paper on

disorders of attention and perception in early schizophrenia is remarkable for lucid personal accounts. The series of “first person accounts” in Schizophrenia Bulletin, which are written by schizophrenia patients and/or their family members, also reveal many instances and descriptions of the personal impact of the failures in attention.



Probing Critical Neurocognitive Endophenotypes

239

anxiety. Meehl (1964) saw such micropsychotic episodes or “drift-outs” as so important that he assigned them the heaviest armchair weighting in his informal system of weights (which have been published only recently).2

Initial Study of Sustained Attention in Schizotypy As reviewed earlier, in my first study of schizotypy (Lenzenweger & Loranger, 1989a), I found that in individuals with no prior history of psychosis elevations on a psychometric measure of schizotypy predicted an increased morbid risk for treated schizophrenia among biological first-­degree relatives. These data built an important bridge; in short, we had gone from the nonpsychotic, schizotypy-­positive individual to a family history of diagnosed and treated schizophrenia.3 Findings going in that direction had not been reported, as far as I could discern from the literature. I interpreted those data as consistent with Meehl’s (1962, 1990) model of schizotypy. The model was yielding empirical fruit, and I wanted to pursue it further. A core feature of the Meehl model was synaptic slippage, which he conjectured as occurring at the level of the neuronal synapses, and this defect was ubiquitous in the schizotaxic brain. The manner in which synaptic slippage displayed itself phenotypically would be reflected in what he termed cognitive slippage. That slippage I thought most likely lay beneath the experiences of many schizotypes across numerous domains, such as perceptions of self, others, objects, and even less palpable notions, such as time. In short, any information that required the integration of multiple information streams and/or neurocognitive processes was going to be more inefficient if slippage was occurring. One way to think about this is to consider how well a car can be stopped if (1) it has worn brakes, (2) the level of brake fluid is low, (3) the tires are relatively bald, and (4) the roadway is covered by a layer of wet autumnal leaves. Probably not so well! This is so because, although no one problem is likely to impair the car’s ability to stop, the sum total or combination of factors (remember, whether additive or configural rules are at work is always worthy of consideration) is likely to spell trouble for stopping. Slippage throughout the attentional processing of information will 2 These armchair weights can be found in Appendix A in this volume, as well as in the Manual, which is available in PDF format at www.tc.umn.edu/~pemeehl/061ScChecklist.pdf. 3 Some

might wonder why I would emphasize the “treated” descriptor of the schizophrenia cases in the study in question. This reflected a criterion that helped ensure that the psychotic illness described in various clinical sources in this family-­history study was sufficiently severe so as to come to the attention of someone providing clinical care. It represented a raising of the threshold for what would be evidence of the presence of schizophrenia. In establishing this threshold, the goal was to minimize false-­positive detections, even at the expense of false negatives.

240

SCHIZOTYPY VIEWED FROM THE LABORATORY

ultimately impair one’s ability to attend well, especially in instances where multiple data streams are monitored simultaneously (as in conversation). Therefore, I undertook a study of objectively assessed sustained attention processing in schizotypes and controls. The subjects were initially selected on the basis of psychometric deviance on a schizotypy indicator using an epidemiological-style door-to-door survey distribution and collection technique.4 I used the PAS (Chapman et al., 1978; see Chapter 5, this volume) as my indicator of schizotypy. A group of putatively nonschizotypic subjects were also selected from the large sample. Schizotypes were defined as being 2 standard deviations or more above the group mean on the schizotypy index, and the controls were selected randomly from among those scoring no higher than one-half of a standard deviation above the mean. This sort of selection allowed for substantial separation between the two subject groups on the schizotypy indicator but did not constitute an extreme-­groups design.5 The subjects were carefully screened to ensure that they had never experienced an episode of psychosis prior to testing. They were tested on a measure of sustained attention, namely the Continuous Performance Test—­Identical Pairs Version (CPT-IP; Cornblatt et al., 1988; Cornblatt et al., 1989). Importantly, both the clinical screener for psychosis and the laboratory personnel were blind to group membership of the research subjects. (As noted earlier in this book, the blind is a critical component in experimental psychopathology research; failure to maintain a blind renders a study largely without merit.6) 4 Although more labor intensive, our method of sampling that tracked responses against the total num-

ber of subjects sought (allowing a response rate to be calculated) and also capitalized on the human context (a research assistant was at the door) helped to ensure representative sampling. This survey method should be considered by anyone seeking to do schizotypy research in nonclinical populations. It helps to combat factors adversely impacting self-­selection, particularly for methods such as bulletin board sign-up sheets and questionnaire completion in public spaces. Screening subjects in the context of undergraduate psychology classes must be viewed with some measure of caution because many students in mass-­testing scenarios assume test-­taking attitudes, augering against valid responding. Many simply complete questionnaires to “get the credit,” zooming through the items “just to get done.” 5 There

is nothing particularly magical about the upper cut score in this selection. One could use the top 5%, top 10%, or top 25% of a sample identified on some measure of interest. The 2 SD approach largely became convention in studies that relied on psychometric detection of schizotypy. What is important, however, is that the control group is not selected from 2 SDs below the mean (or some other highly deviant definition of normality), as this would constitute an extreme-­groups design, which would overestimate the correlation between group membership and a dependent variable of interest. The traditional psychometric selection procedure used in schizotypy studies does somewhat overestimate this r, but not as much as might occur with, say, a 2 SD above versus 2 SD below approach.

6 If

one cannot take the time and devote the necessary planning energy to include a blind in a psychopathology study, then one should find something else to do and should not waste taxpayer dollars on a study without a blind.



Probing Critical Neurocognitive Endophenotypes

241

What does a subject do in a study of sustained attention? What exactly is a continuous performance test (CPT)? The history of the CPT method can be found elsewhere (e.g., Parasuraman, 1984) and will not be reviewed here. The basic task, however, should be described. Basically, a subject is required to carefully monitor a computer screen on which targets appear in succession over a protracted period of time. So as not to create a task that would grind on for hours, researchers have designed tasks to have what is termed a “heavy processing load”—meaning that they are challenging tasks to complete and require substantial effort at maintaining attention over relatively brief periods of time. Moreover, in many modern CPT protocols, the target that one seeks to detect comes along infrequently, thus ensuring that the task is demanding; one needs to keep vigilant. The particular CPT used in this initial schizotypy study was a version of the CPT-IP, and it is depicted in Figure 8.1. In short, a subject needs to carefully monitor successively appearing stimuli on a computer screen. When a subject sees two stimuli in succession that are identical—a so-­called “identical pair”—he or she needs to indicate that he or she saw this pairing. The subject does so with a click of the computer mouse. As depicted in Figure 8.1, targets appear on the computer screen for a short duration (50 milliseconds), and then the screen goes black for a longer period (950 milliseconds). A subject needs to maintain the target in his or her attention—not in memory per se—in order to compare it with the next stimulus coming along. Once the next stimulus appears, the subject must decide whether or not it matches identically the preceding target. When an identical pair is correctly detected, it is considered a “hit.” When a pairing is ostensibly detected as “identical” but the two stimuli are not the same, it is an incorrect detection, and this is considered a “false alarm.”7 What was found in this early investigation of sustained attention in relation to schizotypic subjects? We found that schizotypic subjects do indeed show impairments in sustained attention relative to controls and that this association could not be explained away by other factors, such as mental state (anxiety, depression), general intellectual ability, or age, as well as, obviously, prior psychosis. These findings (Lenzenweger, Cornblatt, & Putnick, 1991) helped to establish, beginning with a clinical observation (i.e., 7 The

astute reader will also notice that one could indicate that an identical pairing occurred where there is virtually no similarity between the preceding stimulus and the target stimulus. These sorts of errors are called random errors on the CPT-IP, and our research has shown that they are important to take into account when seeking to illuminate the relationship between schizotypy, whether expressed as schizophrenia or schizotypic states, and sustained attention (Cornblatt et al., 1989; Bergida & Lenzenweger, 2006).

242

SCHIZOTYPY VIEWED FROM THE LABORATORY

Dark Time 950ms

3598 50ms

Dark Time 950ms

5491 “Hit Pair”

50ms

Dark Time 950ms

Correct Detection

2720 Time (ms)

50ms

Dark Time 950ms

2720 Dark Time 950ms 50ms

“False Alarm Pair” Incorrect dtection

1385 50ms

1384

FIGURE 8.1.  Schematic depicting the Continuous Performance Test—Identical Pairs version developed by B. A. Cornblatt (Cornblatt, Lenzenweger, & Erlenmeyer-Kimling, 1989). In this task the subject monitors a computer screen on which stimuli are presented, and the basic experimental task is to note when two identical stimuli occur in succession (i.e., back–to-back).

“driftouts,” “spaceouts”), a further laboratory connection between schizotypic personality pathology and the corpus of research in schizophrenia. In those subjects with no prior history of psychosis and who were reasonably well matched on all background variables aside from level of perceptual aberration, a deficit in overall level of sustained attention was found. This pattern of findings, coupled with evidence of the heritability of sustained attention (Cornblatt et al., 1988), suggested that deficits in sustained attention might be considered an endophenotype (Gottesman & Shields, 1972; Gottesman & Gould, 2003) for schizophrenia. This finding raised the possibility that one might also find an association between deficits in sustained attentional functioning in subjects who were known to be genetically at risk for schizophrenia but who also had never been psychotic. It suggested that the level of schizotypic features in such atrisk subjects should be related to deficits in sustained attention. In order to test this hypothesis, we consulted the immense data base of the New York



Probing Critical Neurocognitive Endophenotypes

243

High Risk Project in which children at genetic risk for schizophrenia (as well as affective disorder) and normal children had been followed longitudinally for many years. During this study period, these children were tested on measures of attentional dysfunction (typically as youngsters, 7–11 years old), and those nonpsychotic subjects were subsequently assessed in their 20s by clinically experienced diagnosticians for schizotypic pathology. Despite the passage of nearly 15 years or more of time, we (Cornblatt, Lenzenweger, Dworkin, & Erlenmeyer-­Kimling, 1992) found that early deficits in attention predicted later nonpsychotic schizotypic psychopathology. These longitudinal data complemented the study of sustained attention we had conducted in the laboratory (Lenzenweger, Cornblatt, & Putnick, 1991).

The Current State Deficits in sustained attention represent one of the most well-­validated findings among the various competitors for laboratory-­assessed endophenotypes in schizotypy research. Since the results of Lenzenweger, Cornblatt, and Putnick (1991) appeared, there have been a variety of important replications and extensions to other subject samples (e.g., subjects with SPD). The original Lenzenweger, Cornblatt, and Putnick (1991) results have been replicated using the same measure of sustained attention (Obiols, Garcia-­Domingo, de Trincheria, and Domenech, 1993; see also Rawlings & Goldberg, 2001; Gooding, Matts, & Rollmann, 2006). Grove et al. (1991) reported a significant association between high PAS scores and poor sustained attention performance among the first-­degree biological relatives of individuals with diagnosed schizophrenia (see Chen et al., 1998). A deficit in sustained attention characterizes clinically defined schizotypic individuals (SPD; Condray & Steinhauer, 1992; Harvey et al., 1996). An important issue to consider when evaluating the sustained attention deficit as a potential endophenotype concerns the relationship between schizotypic features and such a deficit in the general population. Whereas prior to the late 1990s many prior studies had examined the relationship between sustained attention deficits and schizotypy in carefully constructed samples (i.e., psychometric high-risk schizotypes; clinical SPD), it was not known whether deficits in sustained attention would be found to be associated with schizotypic features in an unselected nonpsychotic population. A considerable amount of psychopathology research has taken the form of detecting deviance on some possible indicator or process of interest in well-­defined criterion groups such as schizophrenia patients or schizotypic subjects. Research in this form, which detects a probability that is different

244

SCHIZOTYPY VIEWED FROM THE LABORATORY

in form from how we actually conceive of the predictive function of putative endophenotypes, really addresses only the likelihood of deviance on an indicator or process given the presence of preselected psychopathology. However, as noted, the manner in which we actually think of endophenotypes as predictors—that is, that deviance on this measure predicts the presence of schizophrenia liability or schizotypy—is quite the opposite, and empirical research bearing on this viewpoint has been sorely lacking. Thus what was needed was a population study of community subjects, all screened for the absence of any prior psychosis, to determine whether deviance on a validated index of schizotypy (i.e., schizotypic features) was predicted by deviance on an endophenotype (such as sustained attention deficits). Such a study was a building block that was missing from the validity data for sustained attention. With support from NARSAD, Bergida and Lenzenweger (2006) showed that deficits in sustained attention are predictive of schizotypic features within a quasi-­random, unselected population sample. What is actually going on in the sustained attentional dysfunction observed in schizotypes? It is clearly not the result of state-­related psychosis, the artifact that has long hobbled research on sustained attention in actual schizophrenia patients. What future directions should be taken in research on sustained attention as an endophenotype? For example, the neural signature of sustained attention anomalies in relation to schizotypy has only recently been studied by Sponheim, McGuire, and Stanwyck (2006). Speculation regarding brain areas involved in attentional processing in schizotypy and schizophrenia continues to evolve (Fernandez-Duque & Posner, 2001; Danckert, Saoud, & Macuff, 2004; Posner, 2004; Wang et al., 2005). Moreover, careful consideration of the processes (e.g., working memory, context processing, vigilance) involved in alternative sustained tasks remains an area of open investigation (Lee & Park, 2006). Although evidence has long suggested that the sustained attentional problem, both in schizotypes and schizophrenia patients, is not related to a decrement in performance over time (i.e., it is not what is termed a vigilance decrement; Cornblatt et al., 1989; Lenzenweger, Cornblatt, & Putnick, 1991; Bergida and Lenzenweger, 2006), the precise nature of the so-­called capacity deficit remains to be illuminated. To what extent do deficits in sustained attention really reflect a deficit in basic attentional processes versus deficits in deployment of those processes in specific task situations (e.g., context processing; Barch et al., 2004; Delawalla, Csernansky, & Barch, 2007). How would such basic neurocognitive processes connect to the underlying neurobehavioral and neurobiological systems related to reward and context processing (Grace & Moore, 1998)? Moreover, future work needs to integrate the role of social



Probing Critical Neurocognitive Endophenotypes

245

and emotional processes into our understanding of attentional processing as suggested by Ochnser (2008). The real-world consequences of missing a bit of information—­whether in a consistent fashion or in an intermittently degraded manner (see Levy, Wu, Rubin, & Holzman, 1999)—in the moment-to-­moment conduct of everyday life must be explored. Work of this sort is underway in our laboratory (see Miller & Lenzenweger, 2010).

Drifting Offline: Executive Functioning and Working Memory in Schizotypy At the time I was pondering the meaning of sustained attention deficits in schizotypic pathology and schizophrenia, considerable attention began to be focused on difficulties in abstract reasoning, “executive functioning,” and novel problem solving in schizophrenia (Gold & Harvey, 1993). It was thought that these executive, problem-­solving processes were mediated by the prefrontal cortex. (We now know the story is more complex, with input from other brain regions beyond the prefrontal cortex.) This conceptual view built on a research corpus derived from nonhuman primate research by the late Yale neuroscientist and psychologist Patricia Goldman-Rakic (Goldman-Rakic, 1991). It also built on a nascent literature that sought to link some symptoms of schizophrenia to a dysfunctional frontal system (e.g., Levin 1984a, 1984b). The early positron emission tomography (PET) work by Weinberger, Berman, and Zec (1986) served to link diminished accuracy on the WCST (Berg, 1948; Heaton, 1981), conceived of as a measure of abstraction ability and “executive functioning,” and diminished activation in the frontal lobes of the brain—the beginnings of the view that the schizophrenic brain was, in part, characterized by hypofrontal (low frontal) brain activation. But what did we know about executive functioning in the schizotype? Not much, if anything. In light of what we learned about sustained attention among schizotypes (Lenzenweger, Cornblatt, & Putnick, 1991), I found myself wondering to what extent one might be able to tap into the tendency for schizotypic subjects to drift “off task.” If their attention did flag periodically, was it possible that they would show intermittent failures in information processing that would require effortful application of principles or concepts? How did I arrive at this line of thinking about “drifting offline” or “off task”? I found it through observations of the performance of schizotypic subjects in psychotherapy sessions (“I just sort of spaced out, Dr. Lenzenweger, I’m a little out of whack—what were we just talking about?” or “I was following you,

246

SCHIZOTYPY VIEWED FROM THE LABORATORY

Dr. Lenzenweger, I was interested in the theme. I had it, then I lost it; it is so frustrating.”) and observations in the laboratory. What could account for the dysfunctions in what we call executive functions? This work is an executive-­dysfunction-to-­working-­memory journey. During the early stages of our laboratory work on exploring deficits in executive functioning in schizotypes, I shared the following moment with one of the study subjects. Unbeknownst to me at the time, I had just tested one of the schizotypic subjects on the WCST. This particular subject was an earnest young man, by all accounts engaged in the task and working hard to follow my instructions as to how to perform the task. The fundamental challenge in the WCST is to discern the sorting principle in use in the task and to apply that principle to the cards that are being placed in front of you. Thus, if the proper sorting principle is color, then one should use color to sort the target cards according to color (see Figure 8.2). If the sorting principle is shape, then the target cards should be sorted according to shape. Importantly, the task requires a person to keep the sorting principle in use at the moment in his or her head (online, so to speak) in order to apply it until the principle is changed by the examiner. The particular subject I was testing began the task, discovered the sorting principle, and then applied it correctly in several instances. He then seemingly lost the principle. It was as if the sorting principle, which had been detected and applied, simply slipped away, sort of evaporated from the subject’s mind. He failed to maintain the proper sorting set. He continued to sort the cards, was informed on a trial-by-trial basis that his responses

FIGURE 8.2.  Examples of the cards from the Wisconsin Card Sorting Test (Berg, 1948; Heaton, 1981). The cards vary in terms of color, form, and number. The subject’s task is to determine the sorting principle currently in use during the test administration and sort accordingly. For example, if the sorting principle is number, then the subject responding correctly will sort the cards according to the number of figures on the card. Reproduced by special permission of the Publisher, Psychological Assessment Resources, Inc., 16204 North Florida Avenue, Lutz, Florida 33549, from the Wisconsin Card Sorting Test by David A. Grant, PhD, and Esta A. Berg, PhD. Copyright 1981, 1993 by Psychological Assessment Reources, Inc. (PAR). Futher reproduction is prohibited without permission of PAR.



Probing Critical Neurocognitive Endophenotypes

247

were wrong,8 and continued on his way through the task, making many mistakes. On occasion, he would happen on the correct sorting principle again, sort correctly for two or three trials, and, once again, lose the set. His emotional state was unremarkable; he seemed completed unfazed by the experience of making numerous errors, and he eventually finished the task (actually, the task ended as the target cards were exhausted) having made many errors of all sorts. The clinician in me was intrigued—what was going on here? This young man, otherwise bright, motivated, and engaged, could not do this task to save his life. I asked him, “How did you find this task?” He responded, “Oh, it was easy, I figured out what you were doing quickly.” I said, “Please tell me what was happening.” He said, “Well, I realized you were taking the second derivative of the function that linked the shapes on the cards as the basis for categorizing them . . . it was easy.” I was aghast! First of all, this fellow had no clue as to how poor his performance was (e.g., he received a “failure to maintain set” score of 5, which is highly unusual) on the WCST. Second, his explanation for his performance was not only incorrect, it was absolutely arcane and odd in rationale, which suggested no real insight into the process (but it somehow made sense to him!). It represented, in fact, some degree of disordered thinking. Finally, he had no prior medical or psychiatric history that would explain his performance on the task, other than that he was psychometrically identified as a schizotype. We analyzed the WCST performance data from that sample of schizotypic and normal control subjects that included that particular subject. In Lenzenweger and Korfine (1991, 1994) we presented evidence that schizotypic subjects indeed displayed evidence of executive dyscontrol and inefficient executive performance on the WCST. However, what was particularly illuminating was the fact that the clinical observation of the WCST 8 This

particular testing session provided another important lesson for both me and my research assistants. One of my research assistants was in the laboratory during this testing, working behind a screen, but within earshot of the testing area where I sat with the subject. She heard the repeated “Wrong, wrong, wrong, wrong,” that I announced. By the end of the task, the RA was quietly sobbing. I only discovered this after I finished testing with the subject and sent him along his way. This particular assistant had a solid psychological foundation, was not given to inappropriate emotional displays, and had good judgment. What was going on here? She told me it was very upsetting for her to think that here was an otherwise healthy, high-­functioning young adult at a most selective academic institution who could not do this simple neuropsychological task. In a flash, this moment brought home to her the nature of what one does in psychopathology research—­namely, one must probe dysfunction and do so with living, breathing human beings. I saw this as a wonderful teaching opportunity to discuss the importance of empathy, as well as the need for interpersonal awareness and sensitivity in our work in the psychopathology laboratory. One must never forget that we are dealing with fellow human beings who are indeed challenged in one way or another. All subjects should be treated with an empathic attitude that respects their dignity and shows a deep appreciation for their contribution to the research process and also for the difficulties they likely face in living in the world. We are at once both researchers and clinicians in this business.

248

SCHIZOTYPY VIEWED FROM THE LABORATORY

performance of the subject just described was actually revealed in the pattern of group average data observed for the two subject groups. By this I mean that the schizotypic subjects displayed a significantly greater level of a very particular WCST error, namely elevated levels of “failure to maintain set” (FMS). The FMS index actually empirically captures one’s tendency to acquire a correct sorting principle on the WCST and then to lose that principle during its application. We found this form of WCST error to be especially interesting as (1) it was consistent with clinical observations, (2) it suggested potential impairment in the dorsolateral prefrontal cortex, and (3) it had never appeared before in the description of WCST performance in schizophrenia patients. Our speculations regarding the dorsolateral prefrontal cortex (DLPFC) could not be evaluated in this particular research design; however, they would eventually be confirmed by later groups (Delawalla et al., 2007; Mohanty et al., 2005; Minzenberg, Laird, Thelen, Carter, & Glahn, 2009). However, one must ask, Is it the case that only the DLPFC is implicated in poor performance on the WCST? Given what we know about the two-­process model of dopaminergic dysfunction in schizophrenia, one that poses both phasic and tonic disruptions within the midbrain and prefrontal cortex (e.g., Grace, 1991), could a midbrain dopaminergic process also be implicated in the poor WCST performance? Prentice, Gold, and Buchannan (2008) have added an important insight to this puzzle in suggesting that there is a disruption in reward-based learning, which is evident early on in WCST performance in schizophrenia, that is, in part, reflective of phasic dopaminergic irregularities emanating from the midbrain (consistent with our view, as well as with Grace’s, 1991; Grace & Moore, 1998; see also Howes et al., 2009). The fact that our FMS error finding had not been reported in connection with prior studies using schizophrenia subjects was somewhat troubling—was it an artifact or chance finding? Our data for the schizotypes did indicate the presence of some impairment on some of the more frequently reported WCST performance indexes, such as number of categories achieved or “trials to complete first category” (Heaton, 1981). Replications would later support the robust nature of the FMS finding in another independent sample of schizotypic subjects (Park, Holzman, & Lenzenweger, 1995), as well as in the large nonclinical community sample (Lenzenweger, unpublished data, 20099). Other laboratories have found broadly similar results with the 9 Lenzenweger (2009, unpublished data) found that increased levels of reality-­distortion-­related schizo-

typic personality features were associated with an increased level of failure to maintain set errors in a sample of 310 community subjects with no prior history of psychosis.



Probing Critical Neurocognitive Endophenotypes

249

WCST (e.g., Raine, Sheard, Reynolds, & Lencz, 1992; Gooding, Kwapil, & Tallent, 1999; Gooding, Tallent, & Hegyi, 2001), though not in all studies (Condray & Steinhauer, 1992). WCST findings for the biological relatives of schizophrenia-­affected probands are mixed (Franke, Maier, Hardt, & Hain, 1993; Scarone, Abbruzzese, & Gambini, 1993; cf. Snitz, MacDonald, & Carter, 2006). One of the challenges in understanding this literature on the WCST in relation to schizotypy concerns methodological variability across studies. For example, studies that define their schizotypic subjects differently have revealed variations in WCST results. This raises the possibility that variation in WCST results could reflect the impact of different subject populations. Furthermore, the research corpus also shows some variability in the WCST performance variables on which deviance has been found (e.g., categories completed vs. % perseverative errors vs. failure to maintain set). Nonetheless, the convergence of findings suggests that performance on the WCST—as complex a neuropsychological task as it is—could represent a viable endophenotype for schizotypy (schizophrenia liability), as they are consistent with the criteria established by Gottesman and Gould (2003).

Working Memory and Schizotypy: From Primate Research to an Endophenotype The meaning of the deficient performance on the WCST was not entirely clear to us (or others). The cause of the deficient WCST performance was (and remains) opaque at the level of specific neuropsychological dysfunction or aberrated neural circuitry. The WCST task is a highly complex neuropsychological task. Thus it is not safe to assume that the FMS index of the WCST, for example, implies deficient inhibitory control, deficits in working memory, lapses in attention, or more (or less). The complexity of task requirements on the WCST represents one of the drawbacks of using established neuropsychological tests—tests that were originally developed for the clinical assessment of brain damage in many instances—in experimental psychopathology research.10 An important shift in the experimental psychopathology approach derived from the emerging field of cognitive neuroscience in the early 1990s. At that time a number of experimental psycho10 It is interesting to note, however, that despite its limitations, the WCST continues to deliver fascinating results for the psychopathologist to ponder. Consider findings of Egan et al. (2001) that reported a strong association between the val-val COMT genotype and poor WCST test performance, whereas the more modern, streamlined cognitive neuroscience task designed to tap working memory (the so-­called N-back task) did not distinguish across genotype groups. Adapting an adage, “sometimes old wine in old bottles might be preferable to new wine in new bottles.”

250

SCHIZOTYPY VIEWED FROM THE LABORATORY

pathologists sought what Lee and Park (2005) aptly termed a research vessel to hold the varied neurocognitive deficits that were being discovered in schizophrenia patients, their first-­degree relatives, and schizotypic subjects. The research vessel that came to organize at least some of the executive dysfunction findings—such as those seen in WCST performance by schizophrenia patients—was working memory. What is working memory? Memory itself is a broad and complex set of cognitive processes that has many facets and subprocesses (see Tulving & Craik, 2000, for reviews), and a variety of memory deficits have been found reliably in schizophrenia over the years (Gold, Randolph, Carpenter, Goldberg, & Weinberger, 1992; Heinrichs & Zakzanis, 1998). Working memory is thought of as a specific type of memory, separate and apart from short-term memory, as well as episodic and procedural long-term memory. The original definition of the working-­memory construct and related system is largely attributed to Baddeley (1986), who defined it as an active short-term memory11 system consisting of a central executive and modality-­specific slave systems (the so-­called phonological loop for auditory stimuli and the visuospatial sketch pad for visual stimuli). Others see the working-­memory system as that system that helps to keep information needed for task completion “online” for a short period of time (Goldman-Rakic, 1991). Spatial working memory has been a central focus in schizophrenia research for nearly 20 years. It is assessed using a delayed-­response task in which a subject is to retain specific spatial location information during a delay period and utilize that information to complete the task. As described in Park’s overview of her journey to discovering the spatial­working-­memory deficit in schizophrenia (see Box 8.1), her 1992 paper with the late Philip S. Holzman was the first to carefully document a working­memory deficit in relation to this illness. What is to be emphasized is that this new finding in schizophrenia was more than just another new finding.12 11 There

is some debate in the literature as to whether short-term memory and working memory are the same or different systems/processes. It is generally acknowledged that the theoretical distinction (especially as defined originally by Baddeley) is an important one, with the overall pattern of empirical evidence suggesting it is also a valid distinction. Working memory tends to be very active, whereas short-term memory tends to refer to brief storage. An interesting discussion of the working-­memory concept continues nonetheless (e.g., Unsworth & Engle, 2007a, 2007b).

12 So-­called new findings in schizophrenia are not that difficult to find, because many of these new findings document one or another deficit to be found among schizophrenia patients. Deficits are not that hard to find in schizophrenia. Indeed the “generalized deficit” (Chapman & Chapman, 1973) concept suggests that patients often do poorly on most any task set for them. Brendan A. Maher (1974), in an editorial piece in the Journal of Consulting and Clinical Psychology, described the “bull in a Royal Worcester china shop” issue mentioned ealier.

BOX 8.1. Working Memory and Schizophrenia: A Journey to the Experimental Psychopathology Laboratory Sohee Park, PhD When I was growing up in Korea, I was set on becoming an anthropologist and studying shamans. I did not have a specific plan but a vague idea that I would be living in a tent somewhere in Siberia or in the Plains of Dakota, seeking out the last Medicine Man who traverses the whole gamut of human consciousness, someone to be respected and feared. On the surface, my life now cannot possibly be farther from that adolescent vision. As I type this essay on my sleek silver Macintosh in my solidly conventional office, one might wonder, “well, what happened?” A short answer is that surprisingly, after years of meandering through physics, developmental psychology, and cognitive neuroscience, I seem to be where I was going to be. Let me try to explain. I study the most fascinating, intangible, and often, tragic condition, schizophrenia, in which the sacred and the profane are fused in one mind. I came to study it during graduate school at Harvard by a fortunate series of accidents. I say accidents, but one thing to bear in mind is that “accidents” happen when one is primed for them one way or another. I had been interested in individual differences in spatial navigational abilities. I had read an ethnographic book called East Is a Big Bird: Navigation and Logic on Puluwat Atoll by Thomas Gladwin which described how Puluwat islanders use a radically different navigational method to travel thousands of miles across vast expanses of the Pacific Ocean in their canoes, using the direction east (Big Bird in the sky) and other celestial positions to guide their voyage. To do so, they imagine their canoe to be stationary in their spatial framework and imagine that various islands move past them. Cartographic maps or compasses are unknown and not needed, yet they never got lost. I found such tremendous variability in spatial sense fascinating, for example, remembering locations or finding one’s way around a city or even estimating whether a desk would fit into a tight space in an odd-shaped room. My advisor at the time in the Department of Psychology at Harvard was Stephen Kosslyn, one of the most distinguished cognitive psychologists studying visual imagery. He was forging a revolutionary movement to bring the brain into cognitive psychology at the time. Now in the year 2008, this does not sound very radical but at the time (mid-1980s), it was heretical to dream that the brain had anything to do with cognition! This movement, led by Steve Kosslyn, Mike Posner, Mike Gazzaniga, and others would be coined “cognitive neuroscience” within a couple of years and the rest is history. In Steve’s lab, I worked on how we integrate bits of information across eye movements to form a coherent visuospatial framework. This gluing of spatial information over time gives us the impression we live in a stable, physical world; that is, if we can glue them together. I wondered what it would be like if we fail to do so; what would that experience be like? What was it like to live in a fragmented mental landscape? I did not realize the answer might lie in the lab just one floor above in William James Hall.



251

In the same psychology department, there was a professor who studied eye movements in schizophrenic patients, but I had hardly any contact with him beyond his interesting proseminar lecture on smooth pursuit eye movement in my first year. Here comes the ‘accidental’ part. Philip S. Holzman had begun to collaborate with Patricia Goldman-Rakic (then at Yale) on a groundbreaking project to directly link eye-movement physiology data from nonhuman primates to those from humans in the context of schizophrenia. Pat had been looking at neural firing rates in the dorsolateral prefrontal cortex of the monkey while the monkey performed a short-term memory task. So she had the frontal cortex, memory, and eye movement parts of the story. Phil had discovered that schizophrenic patients cannot track moving targets with their eyes and with his student Smadar Levin, he had begun to look at the role of frontal cortex in eye movement abnormalities. He was looking for a graduate student or two to work with him on closing the loop. My officemate and friend Anne Sereno and I had the ideal training and background for what Phil was envisioning. Phil and I asked whether schizophrenic patients indeed have the glue that pieces bits of information together in the mental space. It turned out that under certain circumstances, they could not hold on to even a single piece of information over a short period of time. This is how my work in spatial working memory in schizophrenia and schizotypal personality began. I remember vividly the first time I met someone with schizophrenia. He was a highly intelligent and articulate young man, the same age as I was. Lacking any clinical training, I could not see how he could be diagnosed as having schizophrenia, but this patient could not follow a moving dot on the computer screen with his eyes, nor could he remember where he had seen a simple shape merely 5 seconds ago. It was absolutely fascinating, and after we collected enough data that convinced us that the effect size was decidedly large, we wrote up the results with great enthusiasm, which was not reciprocated by the reviewers of the Archives of General Psychiatry. We had great difficulty convincing them that our findings were important. In the end, Phil’s persistence and optimism won, and we were able to report this impairment in spatial working memory in 1992. At the time nobody paid much attention. Schizophrenia was largely thought of in terms of thought disorder and hallucinations, both being largely language related. Then luck struck again. I met Mark F. Lenzenweger at a Society for Research in Psychopathology meeting in 1991 at Harvard and he saw the significance of our results. He invited me to Ithaca to collect data on psychometric schizotypals. We found that this spatial working memory deficit could also be detected, albeit in a weaker form, in healthy people who may carry liability for schizophrenia. Over the last 15 years, working memory deficit has become a staple in schizophrenia research and now students entering the field think of it as a “fact.” But is it? Author Note: Professor Park’s original 1992 paper on working memory in schizophrenia, published in the Archives of General Psychiatry, is now regarded as an experimental psychopathology classic, cited well over 500 times. Copyright 2008 by Sohee Park. Reprinted by permission.



252



Probing Critical Neurocognitive Endophenotypes

253

The Park and Holzman (1992) paper marked a watershed or ­turning point in our understanding of schizophrenia. The original study (Park & Holzman, 1992), in combination with two subsequent studies (Park, Holzman, & Goldman-Rakic, 1995; Park, Holzman, & Lenzenweger, 1995) helped to change the face of neurocognitive research in schizophrenia, as well as charting a new course in the search for valid endophenotypes for the illness. In this program of studies Park showed that schizophrenia patients (Park & Holzman, 1992), the first-­degree biological relatives of schizophrenia patients (Park, Holzman, & Goldman-Rakic, 1995), and nonpsychotic schizotypic subjects (Park, Holzman, & Lenzenweger, 1995; see also Park & McTigue, 1997) all revealed deficits in spatial working memory. They were unable to retain spatial location information across the delay period and utilize it effectively in the response trial, as compared with relevant controls. In the research on schizotypic subjects, we were able to investigate how well performance on the spatial-­working-­memory task related to WCST performance (Park, Holzman, & Lenzenweger, 1995). An especially interesting finding in light of our prior work with the WCST was that elevated rates of error on the FMS WCST performance index correlated significantly with decreased accuracy on the spatial-­working-­memory task. It is important to note that the 10-second delay period used in the task depicted in Figure 8.3 was longer than that occurring between stimulus trials on the CPT-IP described earlier (in which the dark time was only 950 milliseconds between stimuli) and shorter than that typically associated with the transfer of information into memory storage systems, either short term or long term. Working-­memory impairments in schizophrenia can now be regarded as having the status of scientific fact (see meta-­analysis by Lee & Park, 2005; see also Piskulic, Olver, Norman, & Maruff, 2007). Executive-­function and working-­memory deficits remain of great interest to experimental psychopathologists working on schizotypy-­related research questions. This is so because early changes in working-­memory efficiency may harbor clues to early pathological processes of schizophrenia and, more to the point, working-­memory deficits may represent a compelling endophenotype of schizotypy (Snitz et al., 2006; cf. Skelley, Goldberg, Egan, Weinberger, & Gold, in press). The seminal work of Goldman-Rakic (1994; Sawaguchi & Goldman-Rakic, 1991) implicating dopamine mediation (both D1 and D2 activity) of information processing within the prefrontal cortex provides a neurobiological platform from which to further probe working memory in schizotypy and schizophrenia. The temporal processing of information within the DLPFC represents a particularly attractive target for future experimental psychopathology investigations, especially those incorporat-

254

SCHIZOTYPY VIEWED FROM THE LABORATORY

U Subject fixates

U Target Display

Time (seconds)

U

Delay period (10 seconds)

Target Flashes (200 ms)

apple

Target is absent during delay, distractor prevents rehearsal

Response

U

U

Move eyes to the remembered target position

FIGURE 8.3.  Schematic depiction of the oculomotor delayed response task used in the studies of spatial working memory (e.g., Park, Holzman, & Lenzenweger, 1995).

ing genomic components (e.g., Tan et al., 2007). Another potential puzzle awaiting illumination is the fact that, whereas prefrontal cortex volumes are diminished in schizophrenia but largely intact in schizophrenia spectrum disorders (Siever & Davis, 2004; see also Abi-­Dargham et al., 2004), prefrontal-­mediated neurocognitive functioning is impaired in both schizophrenia and schizotypic pathology. Thus, although structural defects in the prefrontal regions differ between the expressed schizophrenia phenotype and the nonpsychotic schizotype, similar functional deficits are apparent in both. Finally, from the standpoint of intellectual history in experimental psychopathology, the issues of dysfunctional information tuning (Tan et al., 2007), updating (Miller & Cohen, 2001), or gating (Grace & Moore, 1998; Grace, 2000; cf. Braver, Barch, & Cohen, 1999) within the prefrontal cortex and in relation to working memory are remarkable in two ways: (1) they have potential relevance to our understanding of symptom formation, as well as the development of social impairments, and (2) each embodies the primary synaptic slippage notion hypothesized by Meehl nearly 50 years prior.



Probing Critical Neurocognitive Endophenotypes

255

What We Learn from the Eyes: Eye-­Tracking Dysfunction and Schizotypy One of the most well-­validated and carefully studied endophenotypes in schizotypy/schizophrenia is that of eye-­movement dysfunction (Levy et al., 2004; see also Sponheim et al., 2003; O’Driscoll & Callahan, 2008). Eye­movement dysfunction (or eye-­tracking dysfunction) concerns an abnormality in the ability to smoothly and accurately track a moving target with the eyes. Although there are many types of eye movements, there are two types of movements that work together—­really interactively—­during an eye­tracking task, namely, smooth pursuit and saccades (fast eye movements). As described by Levy et al. (1993), “the smooth pursuit system stabilizes the image of a moving target on the fovea by matching the velocity of the eye to that of the target” (p. 462). Compensatory fast eye movements (saccades) help the eyes to stay on a target by either catching up to a target when the smooth pursuit system has fallen behind the target or backing up when the smooth pursuit system has overshot the target. This is a complex yet seamless psychophysiological/neurocognitive process. Most of us take for granted our ability to follow a moving target, whether it is a baseball approaching on a pitch, a Frisbee floating just ahead of one’s hand, a flying bird passing by, or a bus pulling into a nearby bus stop. That an anomaly could exist in this system never occurs to most people, much less the fact that such an anomaly could be connected to schizophrenia. However, that there is a well-­documented abnormality in the smooth pursuit eye movement (eye tracking) of people with schizophrenia, their first-­degree biological relatives, and schizotypes is now an established scientific fact in schizophrenia and schizotypy research (Levy et al., 1993; Levy et al., 1994; O’Driscoll & Callahan, 2008). One could argue that no other candidate indicator meets the validity criteria established by Gottesman and Gould (2003) for an endophenotype better than does eye-­tracking dysfunction (ETD). The fascinating thing about ETD in relation to schizotypy and schizophrenia for my students is the relatively subtle nature of this deviancy. “Just how was this anomaly, eye tracking, discovered, Professor Lenzenweger? It seems so subtle and so far away from schizophrenia symptoms.” I validate the latter comment from my students: “Indeed, it does seem, as a phenomenon, rather far afield from clinical schizophrenia,” and I comment on the subtle nature of the deficit. “Yes, the deviant tracking we are discussing is not easily detected with the unaided naked eye” (see Figure 8.4). It is in this context that I discuss how the role of serendipity (chance, fortune, luck) in

256

SCHIZOTYPY VIEWED FROM THE LABORATORY A R

10°

L 1 sec

B

C

FIGURE 8.4.  Eye-tracking patterns in normal and abnormal pursuit. (A) 0.4 = Hertz sinusoidal target; (B) qualitatively normal eye tracking of the target in A; (C) qualitatively abnormal eye tracking of the target in A. In normal tracking of a target, the eyes move with the target in a relatively smooth manner, whereas in schizophrenia and schizotypic pathology, the eye-tracking record reflects a jagged, “bumpy,” uneven effort to track the target. From Levy, Holzman, Matthysse, and Mendell (1993).

psychopathology research, as in all science,13 should not be ignored and that it is important for researchers to be open to the random happenstances that may lead to genuine insights. Some of the most famous discoveries in experimental psychopathology have emerged from serendipitous insights, observations, and unusual moments in the process of discovery. Atypical features in the ocular motor performance of schizophrenia patients were described over 100 years ago by Diefendorf and Dodge (1908), who described these 13 For

example, the compound chlorpromazine, which would go on to transform the care of schizophrenia patients and usher in the era of psychopharmacological intervention for mental disorders as the medication Thorazine, was discovered quite by accident, as investigators were seeking a medication of use in the relaxation of surgery patients (see López-Muñoz et al., 2005). Outside of psychopathology, the structure of the benzene ring (consisting of a six-­membered ring of carbon atoms) was allegedly happened upon in a daydream or reverie by the German organic chemist Friedrich August Kekulé (some historians of science dispute this account of Kekulé’s discovery). The daydream was of a snake seizing its own tail. Never discount the role of serendipity in science. One should celebrate the nonlinearity of the pathways to discovery, remaining open to chance opportunities and possibilities.



Probing Critical Neurocognitive Endophenotypes

257

deficits with the term praecox pursuit (Levy et al., 1993). But these early clinical observations escaped scientific attention for the most part until the late 1960s and early 1970s, when eye-­tracking deficits were essentially rediscovered. Let us consider how Philip S. Holzman, the psychoanalyst and experimental psychopathologist, came to rediscover the robust eye-­tracking abnormality in schizophrenia patients. Holzman’s long-time colleague and collaborator Deborah L. Levy relates the history of Holzman’s discovery process as follows (see Box 8.2). Although the presence of ETD in schizophrenia, in the minds of most informed psychopathologists, is a well-­validated and consistent empirical finding beyond dispute, the real import of the eye-­tracking finding hails from the creativity that has gone into fully understanding all those factors that could impact eye-­tracking performance, as well as establishing its relatively unique connection to schizophrenia. Importantly, the specificity of ETD to schizophrenia, although not perfect, has been painstakingly established (Levy et al., 1993, 1994; O’Driscoll & Callahan, 2008). The array of potential artifacts that could creep into the measurement of smooth pursuit is now well known and taken into consideration in contemporary eye-­tracking research (e.g., alcohol use, barbiturate abuse). In the decades since Holzman brought the eye-­tracking anomaly in schizophrenia to the front burner of psychopathology research, many people have worked to articulate the fundamental nature of the deficit (e.g., low frontal eye-field activation and peak gain; see O’Driscoll & Callahan, 2008). Some of this work has focused on ETD and schizotypy, whereas another important vector has been the development of theoretical genetic models incorporating ETD as an alternative expression of schizophrenia liability (see Holzman et al., 1988). What do we know about ETD in relation to schizotypy? As I have done so often in this discussion, I remind the reader that schizotypy is a latent construct that represents schizophrenia liability and is invisible to the naked eye. This is a reminder well worth heeding, as research on ETD and schizotypy has approached schizotypy energetically, using clinical schizotypal personality disorder, the first-­degree biological relatives of schizophrenia patients, and psychometrically identified schizotypes as units of analysis indicative of schizotypy. In terms of ETD among individuals with schizotypic psychopathology, such deficits are clearly found both among clinically defined schizotypes (e.g., Lencz et al., 1993; Siever et al., 1990; Siever et al., 1994; cf. Thaker, Cassady, Adami, & Moran, 1996) and psychometrically identified schizotypes (Simons & Katkin, 1985; O’Driscoll et al., 1998; Gooding, Miller, & Kwapil, 2000). Eye-­tracking dysfunction has been found to aggregate in the biological family members of schizophrenia

258

SCHIZOTYPY VIEWED FROM THE LABORATORY

BOX 8.2. How Dr. Philip S. Holzman Serendipitously Discovered Smooth Pursuit Eye-Movement Dysfunction in Schizophrenia Deborah L. Levy, PhD What happened is this. We were doing clinical testing to assess the vestibular system, because the most consistent finding in the schizophrenia literature was that schizophrenics had absent or hyporeactive vestibular responses. We were using the caloric test, in which a temperature gradient is induced in the inner ear by warm or cool water irrigation of the outer ear canal. The temperature gradient induces fluid movement in the inner ear balance organ, and this fluid movement simulates the natural stimulation that occurs with head movement. The result of this caloric stimulation is a jerking of the eyes, called nystagmus. Nystagmus consists of a slow eye movement in one direction followed by a fast eye movement in the opposite direction. The only way to assess the response to this stimulation is to analyze the resulting nystagmus. Because the usefulness of the test depends on analyzing eye movements, it is first necessary to be sure that eye movements are intact and normal. The standard clinical battery to assess vestibular function therefore begins with an assessment of visually evoked slow and fast eye movements. Any abnormality of visually evoked eye movements will be useful in the diagnostic evaluation. Thus, we assessed saccades (the rapid refixation eye movements made with shifting gaze, the visually induced eye movement counterpart to the fast phase of nystagmus) and smooth pursuit (the slower movement of the eyes as a moving target is followed visually, the visually induced eye movement counterpart to the slow phase of nystagmus). The assessment of visually evoked eye movements was thus an incidental but scientifically appropriate add-on to a study whose primary focus was assessment of vestibular function. As it turned out, vestibular responses and saccadic eye movements were normal, but smooth pursuit was not. Had we not included the whole clinical battery, we would never have rediscovered eye-tracking dysfunction. Although the initial rediscovery was serendipitous, it was what Dr. Holzman did with that discovery that was the real test of his brilliance. Author Note: Philip S. Holzman’s two initial papers on this topic, appearing in Science (Holzman, Proctor, & Hughes, 1973) and the Archives of General Psychiatry (Holzman et al., 1973), are citation classics. This pair of papers has been cited in total more than 700 times. Copyright 2008 by Deborah L. Levy. Reprinted by permission.



Probing Critical Neurocognitive Endophenotypes

259

patients across numerous studies (Levy et al., 1994; Sponheim et al., 2003). Chen, Bidwell, and Norton (2006) argue persuasively that unpacking the findings for the visual system in relation to schizophrenia and schizotypy may shed light on trait-based (vs. state-based) indicators of schizophrenia liability. The genetic model developed by Holzman and colleagues is one that assumes that the schizophrenia liability is a latent construct—which is termed a latent trait—and that the construct can manifest itself in at least two forms, clinical schizophrenia and/or ETD, using the creative assumption of pleiotropy (see Chapter 7, this volume). This elegant statistical–­genetic model shares much in common on a conceptual level with the Meehl (1962, 1990) assumptions about schizotypy and varying expressions of that latent entity. Using the Matthysse–­Holzman statistical model, which involves a joint consideration of ETD and clinical schizophrenia in the transmission of schizophrenia liability (i.e., their “latent trait”), yielded, as discussed earlier, evidence consistent with a single autosomal dominant gene being implicated in (at least some cases of) schizophrenia. Whether or not a single major gene (with pleiotropy) for some forms of schizophrenia and, more to the point, schizophrenia liability retains explanatory power over time will depend on the results of ongoing genetic and genomic investigations. The important take-home message here for the student of experimental psychopathology is the fact that Holzman did not merely stop at specification of the eye-­tracking anomaly in schizophrenia. He did use the methods of the experimental psychology laboratory to pin it down, but, importantly, he took that candidate endophenotype and placed it into a falsifiable genetic model for further evaluation. This is an important research moral for the beginning experimental psychopathologist: Do not merely seek to detect an interesting empirical finding, but continue on to incorporate it into a falsifiable model to advance our understanding of schizotypy/schizophrenia. Although most prior research on ETD was conducted on highly selected samples (which can exaggerate relations between ETD and criterial groups), Lenzenweger and O’Driscoll (2006) showed that an increased rate of catch-up saccades, as well as impaired gain (poor smooth pursuit), can be found in relatively unselected adult subjects from the general population and that these deficits are related to increased schizotypic features. Just as is the case with sustained attention deficits (cf. Cornblatt & Malhotra, 2001), eye-­tracking dysfunctions do not occur in all cases of schizophrenia and not all schizotypes evidence the dysfunctions, either (cf. Lenzenweger, 1998). Finally, not only does the consistency in findings across both schizophrenia patients and individuals with schizotypic psychopathology inform us of the

260

SCHIZOTYPY VIEWED FROM THE LABORATORY

information processing and psychophysiological deficits found in schizotypes, but also these very deficits further link the schizotype to schizophrenia.

An Antisaccadic Interlude: What to Do with a Finding? Another neurocognitive process that has been studied in individuals with schizophrenia, in relatives of schizophrenia patients, and in variously identified schizotypic individuals is the antisaccade task. The antisaccade task is one that requires a subject to inhibit a saccade (or fast eye movement) to a target appearing in the periphery of one’s visual field and “to generate a voluntary saccade to the mirror location in the opposite periphery, where there is no visible target” (Levy et al., 2004; p. 114). Although this task has shown considerable effectiveness in distinguishing between normal individuals and those with schizophrenia, the meaning of performance on the antisaccade task, as well as its potential role as an endophenotype, have been trenchantly criticized (Levy et al., 2004; Levy et al., 2008). Levy and colleagues have noted that performance on antisaccade tasks appears to show some evidence of heritability. The corpus of existing studies, when examined through the meta-­analytic lens, fails other criterion tests for an endophenotype (cf., Gottesman & Gould, 2003; Gould & Gottesman, 2006). Though they are clearly distinguished in the research literature, some confuse the ETD findings with the antisaccade findings. The antisaccade task is unlike the smooth pursuit task, and the two tasks index very different processes and should not be confused with one another.

What We Learn from Words: Disordered Thinking Disordered thinking has long been considered a cardinal sign of schizophrenia. In fact, Bleuler (1911/1950) considered the loosening of associations to be a hallmark of the schizophrenia process. In Meehl’s (1962, 1990) model, he refers to the term cognitive slippage in describing the theoretical basis for thought disorder. For him, primary cognitive slippage reflects neuronal or synaptic slippage—a slippage at the level of neurobiological information transfer across the synapse—­deriving from what he terms hypokrisia. Meehl also discusses secondary cognitive slippage, which is downstream from the primary deviation and reflects a more molar-level slippage, that manifests itself as subtle thought disorder in some compensated schizotypes and flagrant thought disorder, as well as other psychotic phenomena, in decompensated schizotypes (i.e., schizophrenia proper).



Probing Critical Neurocognitive Endophenotypes

261

“Loosening of associations” means the breakdown of meaningful connections between thoughts, as well as between thoughts and feelings. This breakdown manifests itself through speech14 and is reflected in the diminished communication value of a spoken expression. Thus the form of the thought is what is at issue, not so much the content of the thought. For the most part, when clinicians or researchers speak of thought disorder, they have in mind “positive” thought disorder, and terms such as derailment, tangentiality, incoherence, and cognitive slippage are used to describe the observed behavior. There is also a form of thought disorder known as “negative” thought disorder, which is reflected in either the markedly diminished amount of speech produced and/or markedly diminished content of speech. Negative thought disorder has been described by terms such as alogia, poverty of content of thought, or poverty of thought. Experimental psychopathology efforts have tended to focus more on positive formal thought disorder, and it is worth considering several examples (see Box 8.3).15 There are three primary approaches to the assessment of thought disorder. The first is clinical rating, and this can be done via either unstructured or structured interviews. An interviewer listens to the quality of the speech

BOX 8.3. Examples of Schizotypic Thought Disorder “My angular walk to your office felt rather curb-like in its emotional landscape.” “The inward outboundedness of the essential depth of the relationship is what proved rather bending to my thoughts.” “The upper portion of his friendly-ish facial components led me to diverge my ideas around the perimeter of his feelings in that precise moment.”

14 It

is important to note that schizophrenia patients do not have speech or language disturbances. They can articulate the sounds needed to generate speech and be highly proficient in language use. The fundamental problem, which is inferred through the disorganized speech, is the disorganization of thought (see Johnston & Holzman, 1979).

15 By “thought disorder” we do not mean clever turns of phrase or creative prose. This is an important distinction, as some workers have, to my mind, inappropriately cast a net too widely in discussions of thought disorder as inclusive of creative speech and/or writing. Disordered thinking, by and large, cannot be controlled by a person or tapped only when the muse strikes, whereas creative thinking and/ or writing is more of an effortful process (albeit easily accessed by those truly gifted). Thus, although the prose of James Joyce, Jack Kerouac, or Thomas Wolfe, the song lyrics of Bob Dylan, or the poems of Patti Smith may give the appearance of random construction, they actually reflect considerable controlled effort and brilliant creative insights into the relations of ideas, symbols, and meaning.

262

SCHIZOTYPY VIEWED FROM THE LABORATORY

produced by a schizophrenia patient, judges the extent to which it deviates from conventional, logical thought, and makes a rating regarding the presence of thought disorder (as well as, typically, the intensity or severity of the thought disorder). Thus thought is identified (rated) as disordered (or not), and there is some effort to order the level of severity of the observed disturbance. The prototypical approach to clinical rating of thought disorder can be found in the richly detailed and carefully constructed scales by the University of Iowa psychiatrist Nancy C. Andreasen (e.g., Thought, Language, and Communication Scales [TLC], Andreasen, 1986; Andreasen & Grove, 1986; see also the positive-­symptom portion of the CASH; Andreasen, Flaum, & Arndt, 1992). Although the structured interview approach to rating thought disorder has been in use for a long time, the overreliance on unstandardized assessment and varying definitions has limited enthusiasm for clinically rated thought disorder as an endophenotype. This limited enthusiasm, however, reflects diminished support for the methodological approach (i.e., clinical ratings) as opposed to diminished enthusiasm for the phenomenon. We sought to study thought disorder among schizotypes but were faced with an assessment challenge. Although the clinical approach can be applied directly in the evaluation of psychotic patients for whom disorganized thought is rather glaring in the presentation, such an approach was ill suited for the detection of subtle thought disorder among schizotypes. The thought disorder in schizotypes might be clinically detectable through interviews, but the particularly subtle nature of schizotypic thought disorder required a more sensitive methodological approach. Importantly, I did not want to simply rate the “oddness” of schizotypic speech. This research direction brought me into contact with the two other traditions of the thought-­disorder measurement in schizophrenia research: the thought disorder index (TDI) approach developed by Johnston and Holzman (1979), the second approach, and the experimental laboratory approach developed by Brendan Maher (1972; Maher, Manschreck, Linnert, & Candela, 2005), the third approach. The thought disorder index approach grew out of early psychological testing observations of the intrusion of formal thought disturbance on psychological test performance (Johnston & Holzman, 1979; Holzman, Shenton, & Solovay, 1986). The TDI approach is a highly reliable assessment system for the evaluation of clearly defined forms of disorganized thought processes. Based on explicit definitions of thought disorder types, as well as a weighting system for combining the ratings of thought disorder types, the TDI is highly reliable (Coleman et al., 1993) and sensitive to many levels of thought disorder (from the subtle to the severe). As a system



Probing Critical Neurocognitive Endophenotypes

263

it can be applied to any speech sample that has been transcribed verbatim. In practice, those using the TDI system have used the well-known Rorschach inkblot16 plates for a standard set of stimuli that is useful in eliciting speech samples. In the context of a large, multivariate study of schizotypy, we assessed all of our subjects for thought disorder using the TDI (Coleman et al., 1996). In that study, we had expert TDI administration and scoring done by those centrally involved in the psychometric and clinical development of the TDI, namely, Philip S. Holzman, Deborah L. Levy, and Michael J. Coleman. Levy and Coleman assessed numerous study subjects using the Rorschach inkblot plates in my laboratory. The assessors were, of course, blind to the group membership of the subjects. The subjects had been drawn from a relatively high-­functioning university population; thus issues of generalized deficit, neuropsychological impairment, and so on were largely irrelevant. The two subject samples were virtually identical on any demographic variable of interest. Would we be able to pick up on thought disorder differences in this sample of high-­functioning subjects? Would they show identifiable, in terms of the TDI, thought disorder? We were all very curious indeed! The protocols for these subjects were sent to McLean Hospital/Harvard Medical School for scoring in the Holzman Psychology Research Laboratory. We waited in Ithaca, New York, with the sealed code that told us what subjects belonged to which groups in the sample. Then I received a phone call from Philip Holzman. “Mark, are you sure that none of these subjects has schizophrenia? The reason I ask is that we are seeing TDI levels that indicate fairly severe disruption of thought! None of these folks has schizophrenia?” I assured Holzman that, indeed, none of these subjects had ever had a psychotic episode of any sort. They were completely nonpsychotic by any informed clinical standard. Needless to say, we were all interested in breaking the diagnostic code, once the data had been scored blindly. The findings were striking. As would be predicted by Meehl’s model of schizotypy, the schizotypic subjects displayed considerably more thought disorder according to the TDI. Approaching the TDI from a variety of different perspectives, we found the schizotypes to differ significantly from the controls at magnitudes consistent with medium effect sizes. Moreover, when we examined the most highly deviant subjects using different approaches, 16 The TDI does not involve the use of any psychoanalytic interpretive principles. It is not a projective test. Rather, it is a system for scoring thought disorder. The stimuli used often with the TDI are the Rorschach cards. Some workers have misunderstood the TDI to be a Rorschach-­specific instrument. It is not (e.g., Lilienfeld, Wood, & Garb, 2000).

264

SCHIZOTYPY VIEWED FROM THE LABORATORY

the most deviant subjects according to the TDI were always found entirely within the schizotype group. Finally, the two subject groups did not differ on a test of general intellectual functioning. The implications of these results were helpful to the ongoing bridging strategy we were pursuing in our study of schizotypy. Recall that the strategy set out to build empirical linkages between schizotypic psychopathology/personality and schizophrenia, thereby buttressing the underlying model of schizotypy. These data—­focusing on the “tried and true” clinical feature of thought disorder (recalling Bleuler’s interest in associations in schizophrenia)—provided a useful plank in that bridge between schizotypic psychopathology/personality and schizophrenia. Although the specific forms of thought disorder observed in these students did not contain some of the most severe forms of thought disorder known, the thinking of at least some of the schizotypes was nonetheless impaired. Could this thought disorder be detected by the unaided, naked “ear,” as it were (cf. Gottesman & Gould, 2003)? Probably not. To the clinically sensitive ear of the experienced TDI scorer, perhaps; to virtually all others, no. These deficits in thought were clearly in the realm of a potential endophenotype (as opposed to a clinically expressed symptom). What impact might this thought disorder have on the lives of these nonpsychotic, high-­functioning schizotypes? We could not say then; this question could only be answered with the passage of time. Uhlhass, Silverstein, Phillips, and Lovell (2004) found that schizotypic subjects with thought disorder have significantly more difficulty in processing visual contextual information, which could impair navigation of occupational and social tasks. This brings us to the third approach to assessing deviations in thought and language. The approaches that rely on clinical evaluation or application of the TDI both involve the use of rating. Simply put, one gathers samples of speech and then evaluates those samples against established criteria for thought disorder. A determination is then made as to whether a given speech sample constitutes thought disorder. This determination is a judgment, a rating. Maher (1972), in his preference for laboratory approaches and counting (as opposed to rating), pursued the measurement of language abnormalities differently. His approach also began with speech samples, but the constituent components of the speech—the actual words—are evaluated with respect to their relative frequency vis-à-vis normal speech use, the frequency with which a word is associated with others (Maher et al., 2005), and/or the number of word types versus the total number of words produced (the so-­called type–token ration, a measure of utterance diversity or repetition in language; Maher, 1972; Manschreck, Maher, Hoover, & Ames,



Probing Critical Neurocognitive Endophenotypes

265

1984). These investigators found that counting actual speech characteristics and the information value of the spoken utterance is useful in dissecting speech patterns in schizophrenia. These characteristics and patterns would be what many would call thought disorder. Importantly, this methodological approach could have utility in the detection of subtle thought disorder, such as that found in schizotypes. To put this notion to the test, we sought to determine whether one could use Maher’s methods to find reliable differences between nonpsychotic schizotypic subjects and normal controls. Clearly, the TDI picked up differences. How would a counting approach perform in this sort of investigation? We applied Maher’s (Maher et al., 2005) Computerized Assessment of Sequential Test (CAST) system for quantitative assessment of the frequency of normative associations in ordinary language samples in a group of schizotypic and control subjects. The CAST system is founded on the theoretical assumption that the “intrusion of associations into the utterances of schizophrenic individuals typically disrupts the coherence of the patient’s utterances” (Maher et al., 2005, p. 219). Maher (2003) hypothesized that increases in activity in associational networks are related to language disturbance in schizophrenia. Our question was rather straightforward, once again: Could abnormalities akin to what have been observed in the laboratory study of speech among schizophrenia patients be found among nonpsychotic schizotypes? The answer to this question, from a preliminary study, is yes. We (Lenzenweger, Miller, et al., 2007) found that the total number of schizotypic features, particularly those involving reality distortion and disorganization, were associated with increased levels of normative associations in a reasonably neutral, ordinary language sampling task.17 Once again, in a sample of high-­functioning, nonpsychotic schizotypic subjects, subtle deviance in the use of language could be detected. However, the added value of the Lenzenweger, Miller, et al. (2007)18 study was the fact that the deviations could be simply counted (rather than rated). These findings (Lenzenweger, Miller, et al., 2007) were discussed in light of their potential utility in endophenotypic studies. Finally, the fact that both a rating system (the 17 For the CAST scoring system we used a painting known as “The Wedding Feast” by the Dutch artist Pieter Bruegel. We gathered utterances by the subjects about the painting in a manner consistent with the guidelines of Maher et al. (2005). Subjects described what they saw in the Bruegel painting, and the subjects were encouraged to respond until at least 100 words had been spoken. It is a very simple and easy task. 18 The

Lenzenweger, Miller, et al. (2007) findings using the OLS/CAST system have recently been replicated in an unpublished study that found that elevated levels of schizotypic features, particularly the disorganization dimension, predicted greater levels of associative activity (Milné et al., 2008).

266

SCHIZOTYPY VIEWED FROM THE LABORATORY

TDI; Coleman et al., 1996) and a computerized counting based methodology (CAST; Lenzenweger, Miller, et al., 2007) found evidence for subtle thought disorder among psychometrically identified schizotypic individuals augers well for (1) the importance of language assessment in the search for valid endophenotypes of schizotypy, (2) the validity of the psychometric high-risk approach to schizotype identification (Lenzenweger, 1994, 1998), and (3) another plank in the bridge linking schizotypy to schizophrenia and schizotypic pathology.

Coda In this chapter, I have reviewed four domains of neurocognitive processes that I argue represent terrain from which especially promising endophenotypes for schizotypy should be selected.19 Without proceeding through every shred of supportive data, I think it can be safely argued that deficits in sustained attention, working memory (executive processing), eye movement/tracking, and form of thought (secondary cognitive slippage) represent some of the most valuable paths to follow in seeking insights into relatively basic processes that will prove useful in getting a handle on early morbid expressions of schizophrenia (as well as the functioning of compensated schizotypes). I suggest that these domains will serve the search for putative schizotypy endophenotypes well and have the largest potential for payoff in seeking to understand the underlying genetics of schizotypy (schizophrenia liability). That a large-scale, properly designed genetic study of these endophenotypes is needed should be axiomatic.20

19 Other endophenotypes, for example, are the psychophysiological indexes (P50, P300) and sensory gating (Hon et al., 2008). 20 To

date there exists no properly designed study for the neurocognitive endophenotypes discussed here. By this I mean a study that incorporates the methodological safeguards needed to ensure the generation of viable data.

Chapter 9

Motion and Touch Simpler May Be Better

An aspect of the experience of the schizotype that is incredibly inter-

esting to me concerns the subtle oddities one sees in motor movement and somatosensation in these fascinating people. We have probed somatosensation and psychomotor performance in a series of studies in an effort to bring the empirical lens of the laboratory to bear on these features of experience in the schizotype. The goals of such explorations have been twofold and are best viewed as questions:

1. Can the clinical observations of apparent somatosensory and motor dysfunction be grounded in empirical data (a goal of experimental psychopathology research)? 2. Could the deviations found in such simple processes (haptic perception and basic motor performance) serve as potential endophenotypes (cf. Javitt, 2009)? In this chapter I consider the development of the somatosensory research we have undertaken in some detail in order to (1) show the student how one proceeds in the development of an experimental paradigm and (2) illustrate the value of specific experimental psychology methods in this process.

267

268

SCHIZOTYPY VIEWED FROM THE LABORATORY

Simple versus Complex?: Sometimes the Simplest Experimental Tasks Can Tell Profound Stories In psychopathology research, we seek to develop models that try to explain, or at least describe, some aspect of an illness, or sign/symptom of an illness, or an aspect of cognitive or emotional processing in those affected with the illness. Given that the vast majority of signs and symptoms in psychopathology consist of cognitive and emotional phenomena, which are known to be relatively complex phenomena even in the normal state, we are, at a minimum, seeking to model some pretty complex stuff. Much of the terrain that needs to be mapped in psychopathology is uniquely parameterized by our biological (read, large neocortex) and psychological status (consciousness) as Homo sapiens. This complexity is one of the reasons, by the way, that rat and mouse models of psychopathology often run aground. Translating the cognitive and emotional domains of psychopathology into rat/mouse behavior adds yet another level of complexity to an a priori ultra-­complex human system.1 We are often faced with the basic decision as to whether to model a process or behavior of interest in as simple manner as possible (perhaps only grasping a small slice of a problem) or whether we should seek to go broadly and deeply to comprehensively model a process or behavior in all its complexity (recall the earlier discussion of “models” in Chapter 6). Students frequently (and, seemingly, instinctively) want to pursue the latter tack— the grand approach to the most complex phenomena. However, sometimes, I argue, simplicity is your best friend en route to understanding complex phenomena. Thus, before delving into the research program we have built in the area of somatosensation and psychomotor performance, I think it is worthwhile to digress a little on the issue of simplicity2 in experimental psychopathology protocols. Just as we prefer a single degree of freedom test via focused-­contrast analysis in ANOVA (rather than the unfocused, omnibus approach), we profit from exploring simpler rather than more complex tasks when studying psychopathology (cf. Jonides & Nee, 2005). This is the reason, for example, that we might prefer the working-­memory tasks (e.g., delayed-­response task) to measure executive-­processing deficits as opposed to the WCST. However, even with apparently simple neurocognitive or other psychological tasks, they are often not so simple in nature on closer 1 The generalizability of rat/mouse behavioral models to Homo sapiens’ emotional and cognitive psychopathologies is a thorny issue beyond the scope of the current discussion. 2 I

encourage the reader to not confuse simplicity with simplistic or simple-­minded.



Motion and Touch

269

inspection. A case in point is the antisaccade task, which is considerably more complex than it appears at first glance (see Levy, 1996).3 Students will ponder in seminar the best way to get at some complex underlying neurocognitive or other process in schizotypy or schizophrenia. For example, in discussions of dopamine and its relationship to the incentive motivation system in normal personality (and psychopathology), as well as its role in schizophrenia, students will initially seek to propose complicated biological assays and intricate neurobiological challenges using a variety of pharmacological agents to investigate experimental questions. They are interested in dopaminergic activity in the brain; thus they think of accessing brain functioning (typically through neuroimaging) and its neurochemistry. I then ask them to tap their fingers on their desks and tell me what it might suggest to them. Typically, most cannot imagine what I am driving at in this exercise. I then discuss one of my favorite examples of how a simple behavioral task can tap a complicated underlying neurobehavioral system that comes from the work of neuroscientist Nora Volkow. In 1998, Volkow and colleagues (Volkow et al., 1998) studied a variety of neuropsychological tasks in 30 normal, healthy volunteers. They assessed performance on tasks that they thought might plausibly be related to dopaminergic activity, specifically involving D2 receptors. Some of the tasks were simple (e.g., finger tapping) in nature, whereas others were considerably more complex (e.g., WCST). The researchers actually measured D2 receptor availability in the brain using PET. What did they find? They found that finger tapping, of all things, was the behavioral performance index most closely associated with D2 receptor availability, even taking age (known to affect dopamine activity) into account. In fact, the rate of finger tapping was correlated .56 with D2 receptor availability in the caudate and putamen, two areas of the striatum that are of considerable interest to schizophrenia researchers (cf. Grace, 1991). The association between simple finger tapping and D2 receptor availability was the strongest found in the study! These findings clearly have considerable substantive meaning, but, perhaps just as importantly, there is a methodological moral in there—­perhaps it might be stated as sometimes simpler is better. Much of schizotypy and schizophrenia research has focused on relatively complex neurocognitive processes using 3 It

is also the case that many times in experimental psychopathology one will see that a simple task is described as tapping a function in a particular brain area. Just as simple tasks can be more complex than they initially appear, it is also true that brain processes subserving task performance can be more complex than implied in theory (e.g., one often hears “working memory resides in Brodmann’s area 46”). Do not assume that functional brain areas are “task areas” (Petersen & Fiez, 1993; Levy, 1996). There are no “antisaccade” or “WCST” brain areas.

270

SCHIZOTYPY VIEWED FROM THE LABORATORY

complex neurocognitive tasks—but are there simpler processes that might advance our understanding of schizotypy and schizophrenia?

Somatosensory Function: Exteroception Clinical Observations Pointing to Variations in the Somatosensory Terrain in Schizotypy My own work in somatosensation grew out of the clinical observation of schizotypes in the laboratory. I usually make anecdotal observations of subjects in the laboratory, record them in a laboratory log, and then, once the diagnostic blind is broken,4 I revisit these observations periodically. Invariably the oddities that I observe in subjects are found most often among our schizotypes. I have noted peculiar speech patterns, diminished affect, and odd appearance disproportionately more frequently among the schizotypes we tested. Other clinical observations of likely schizotypes often strike me as worth recording, for example, in vivo behavior of odd or eccentric persons on the street. One set of notes I kept about my observations of study subjects had to do with what I came to call “cold days in Ithaca, hot days in Harvard Square.” Thus I recall during one series of studies being conducted at Cornell in the cold days of late January (Cornell is in Ithaca, New York, which is known for rugged winter weather) when two research subjects arrived for their appointments dressed in minimal clothing, which seemed quite out of touch with the outside temperature that was well below 20°F (< –7°C). For example, one subject arrived in a skimpy pair of running shorts, flip-flops on his feet, and a short-­sleeved T-shirt. Both subjects reported to me that they “didn’t really feel the cold,” and both turned out to be schizotypes when I broke the blind on group membership. Did these folks not feel the ambient temperature on their skin? Were they less sensitive to the cold somehow? Other observations hailed from the warmer end of the temperature scale. For example, during a sabbatical leave at Harvard University in 1993, I recall sitting at a café in Harvard Square on a very warm summer day (98°F / 37°C)—a toasty, humid afternoon—­sipping iced coffee with a colleague when I was struck by the sight of a fellow sitting nearby dressed in a knit cap, and what appeared to be a goosedown parka and heavy pants. 4 Earlier

I discussed the need to maintain the blind in laboratory research in schizotypy or any other form of disorder or liability, for that matter. Had I not been blind to the diagnostic group status of the subjects we have tested over the years, I would have had considerably less faith in my observations as being neutral and unbiased.



Motion and Touch

271

This person struck an odd appearance; he sat alone reading Heidegger’s Being and Time, and appeared to mumble to himself periodically. Was he psychotic? Was he a schizotype? I cannot say; however, I was struck by his unusual attire in the blazing heat of an urban summer afternoon. Did he not feel the heat? Did he really need a goosedown parka in Cambridge in August? When I shared these observations with a colleague, he remarked that it brought to mind a very odd and eccentric philosopher (schizotypic by all accounts) that he knew who had a predilection for wearing woolen undergarments even during the summer months. Again, what was going on here? Could it be that such people were less sensitive to warmth on their skin? Were they simply less sensitive to stimulation on the skin in general? It struck me that some study of the somatosensation system in relation to schizotypy would be worthwhile.

Somatosensation, Schizophrenia, and the Schizotype: Disturbed Perception, Disturbed Body Image The somatosensory system processes multiple types of sensation from the body—light touch, pain, pressure, temperature, and joint and muscle position sense. Exteroceptive somatosensation refers to the perception of stimuli touching the skin from external sources (e.g., light touch). The somatosensation system/process that detects and integrates muscle and body position is known as proprioception and reflects kinesthetic awareness. That an exteroceptive somatosensory dysfunction might be an important component of the schizophrenia disease process has long been suggested by psychopathologists. Bleuler (1911/1950) noted “very often it is assumed that the sensations derived from the body organs are altered in these patients” (p. 57) and “even in well oriented patients one may often observe the presence of complete analgesia which includes deeper parts of the body as well as the skin” (p. 57). Others have conjectured, more specifically, that a proprioceptive somatosensory dysfunction is an important feature of the schizotype, that is, the person who carries a liability for schizophrenia whether expressed clinically or not. Rado (1960) observed among schizotypes that “the individual’s awareness of his own body is, or tends to become distorted . . . precipitated by what we provisionally call a proprioceptive (kinesthetic) diathesis” (p. 88). Meehl (1964), in his classic Manual for Use with Checklist of Schizotypic Signs, noted a proprioceptive diathesis described as a “spatial–­motoric–­ kinesthetic defect” as an important diagnostic sign for schizotypy, his putative schizophrenia liability construct. Meehl (1990) later described this as

272

SCHIZOTYPY VIEWED FROM THE LABORATORY

a fundamental dysfunction in a “spatial–­kinesthetic–­vestibular” (SKV) system representing central nervous subsystems “that must be hierarchically integrated for a human being to locomote, stand straight, orient in space and have ‘normal’ perception of his own body (and, psychodynamically, his ego boundaries)” (p. 19). The overall impression of these views suggests an enduring and fundamental dysfunction in the perception and integration of both exteroceptive and proprioceptive stimuli (i.e., two domains of the somatosensory system) in clinical schizophrenia and, presumably, those carrying a liability for schizophrenia (cf. Holzman, 1969). The proprioceptive component of the somatosensory (or body sense) system provides information about both the position of the body in space and the relation of the body segments to one another (Kolb & Whishaw, 1996). This system involves integration of body position information through both kinesthetic and static stimuli arising from the body. Therefore, it is not surprising that theoretical conjectures regarding a proprioceptive dysfunction in schizophrenia have derived in part from the frequent occurrence of body image and perceptual distortions in the illness. For example, Rado (1960) was impressed by the body image distortions and perceptual anomalies that characterized the psychological experience of the schizotype. Meehl denoted body image aberrations as a schizotypic sign in his 1964 Manual, providing rich descriptions of the clinical manifestations of such phenomena (pp. 24–27), and he (Meehl, 1990, pp. 9, 19, 23) referred to body image distortions several times in his revised theory of schizotypy. Perceptual and body image distortions as phenomenological manifestations of a liability for (or expression of) schizophrenia have a long history in descriptive psychopathology (Chapman et al., 1978; Erwin & Rosenbaum, 1979; see also Fisher, 1964). We know there is solid (and growing) body of evidence that has shown nonpsychotic individuals scoring high on a measure of body image and perceptual distortions (i.e., putative schizotypes) and demonstrating a multitude of deficits on laboratory tasks and other correlated features comparable in quality to those seen in schizophrenia (see Lenzenweger, 1998).

Body Image Disturbance, Proprioception, and Exteroception: A Parietal Connection? What might be the basis for a somatosensory dysfunction involving both proprioceptive and exteroceptive components? The neuropsychological literature suggests that disturbances in body image (or body schema) require parietal lobe involvement (Benton & Sivan, 1993; Hecaen & Albert, 1978; Kolb & Whishaw, 1996). Kolb and Whishaw (1996) suggest that area PE (Brodmann’s Area 5) of the posterior parietal lobe is especially relevant



Motion and Touch

273

to body image disturbances. However, in order not to localize the CNS site subserving body image awareness with undue certainty, it is noted that lesions to the thalamus can create the impression of body part loss (see Hecaen & Albert, 1978). Nonetheless, parietal involvement is strongly suggested in the area of body image disturbance, as well as the detection of proprioceptive sensory information (Kolb & Whishaw, 1996). Indeed, recent evidence from a primate study clearly supports the importance of Area 5 neurons in the integration of visual and somatosensory information in the monitoring of limb position (Graziano, Cooke, & Taylor, 2000). Is there evidence to suggest parietal involvement underlying actual deficits in the detection of external (i.e., exteroceptive) sensory information? Disturbances in the somatosensory system, typically in the form of increased somatosensory thresholds, have long been associated with parietal lobe damage (Kolb & Whishaw, 1996). Damage to the anterior parietal areas (areas 1, 2, and 3; i.e., postcentral gyrus) has been closely associated with disorders of tactile function, most typically assessed using a 2-point discrimination threshold procedure, such that discrimination thresholds are increased significantly (Corkin, Milner, & Rasmussen, 1970; Pause, Kunesch, Binkofski, & Freund, 1989; Salanova, Andermann, Rasmussen, Olivier, & Quesney, 1995; Semmes, Weinstein, Ghent, & Teuber, 1960; see also Forss, Hietanen, Salonen, & Hari, 1999; Martin, 1996). Moreover, it has been shown that 2-point discrimination task performance is associated (r = .83) with the N20 component in psychophysiological analysis, which is generated by the S1 area of the postcentral gyrus (most likely areas 3b and 1 of the anterior parietal; Knecht, Kunesch, & Schnitzler, 1996; see also Wikström et al., 1999). Anterior parietal damage is associated with deficits in the perception of exteroceptive stimuli in the general somatosensory system. Damage to other brain areas does not affect the 2-point discrimination threshold notably (Corkin et al., 1970; Semmes et al., 1960). Thus parietal lobe damage can result in somatosensory dysfunction involving both exteroceptive stimuli (anterior parietal), in the form of tactile sensation, and proprioceptive stimuli (posterior parietal), in the form of body schema disturbances.

Prior Empirical Research on the Somatosensory System in Relation to Schizophrenia and Schizotypy I find it useful to remind my students that the energetic research focus on schizophrenia has existed for some time. Therefore, it is always wise to consult the older—­sometimes considerably older—­literature (e.g., consider the eye-­tracking dysfunction “rediscovery” in the 1970s vs. the early work of

274

SCHIZOTYPY VIEWED FROM THE LABORATORY

Diefendorf & Dodge, 1908), to see what has been done, if anything, and what can be learned. I did so with respect to somatosensation, and, to my intellectual delight, there was a limited, somewhat problematic, but interesting literature to digest. Despite the importance attached to the notion of somatosensory deficits in schizophrenia, little prior empirical research has been done in the area. For example, only two studies have previously examined exteroceptive deficits using two-point discrimination thresholds in schizophrenia patients (Broekma & Rosenbaum, 1975; Malamud & Nygard, 1931), and both employed definitions of schizophrenia according to DSM-II or earlier criteria. Malamud and Nygard (1931) qualitatively contrasted the detection of touch versus noxious (pain) stimuli within four schizophrenia patients but did not compare their schizophrenia results with those obtained from both normals and neurotic patients. Secondary analysis of their published data revealed that schizophrenia patients had higher, though not statistically significant, two-point discrimination thresholds than normals. Broekma and Rosenbaum (1975) found schizophrenia patients (n = 20) to display higher two-point discrimination thresholds relative to 20 normal controls. Others have used weight discrimination (kinesthetic) tasks to assess proprioceptive functioning in schizophrenia and other psychiatric patients (Ritzler & Rosenbaum, 1974; Ritzler, 1977; Leventhal, Schuck, Clemons, & Cox, 1982), and these studies have suggested that a proprioceptive deficit exists in, but is not specific to, schizophrenia. Javitt, Liederman, Cienfuegos, and Shelley (1999) found evidence of proprioception deficits in schizophrenia using a weight discrimination task; however, the specificity issue was not addressed, as that study did not have a psychiatric control group for comparison. These data, such as they exist, are, of course, limited in terms both of generalizability due to sample sizes and the well-known third-­variable confounds attending the study of expressed schizophrenia (i.e., deterioration, institutionalization, medication, and motivation effects; cf. Lenzenweger, 1998). Therefore, from where I stood, armed with my clinical observations of putative schizotypes and a scant empirical literature on somatosensation in schizophrenia to provide direction and guidance,5 I decided to, first, pur5 Students

occasionally ask me, “how do you develop your ideas—do you read the literature and put things together?” For me, that has rarely been the pattern. Most of the time I begin with an observation or idea and then poke around in the published literature to see if anyone has done work on the question in the past. I find that, for me, consulting the current literature often can be a limiting influence rather than a generative one. David Lykken (1991) suggests that about 1% of the published articles “actually appear to make some sort of contribution to the discipline” (p. 6). Although I cannot speak to his assessment of the proportions involved, the sentiment expressed is important.



Motion and Touch

275

sue exteroceptive processing and then, second, proprioceptive processing in schizotypy. This avenue of research led to a fascinating back-and-forth between the substantive focus of the work—­somatosensation—and the methodological necessities for it.

Study 1: Two-Point Discrimination Thresholds and Schizotypy The first study we undertook focused on exteroceptive processing. This investigation sought to determine whether, in a series of randomly ascertained individuals with no prior history of psychosis, those persons who display relatively high two-point discrimination thresholds would be characterized by elevated levels of schizotypic features. In this study (Lenzenweger, 2000), 100 young adults drawn randomly from a university population were evaluated for their two-point discrimination thresholds. We collected individual-­difference information on these subjects in several areas, especially schizotypic features. The schizotypy measures used in this study were the PAS (Chapman et al., 1978), the MIS (Eckblad & Chapman, 1983), the Referential Thinking Scale (REF; Lenzenweger, Bennett, & Lilenfeld, 1997), and the Rosen Paranoid Schizophrenia Scale (Pz; Rosen 1952, 1962; see Lenzenweger, 2000, for details). For the purposes of this study, two-point discrimination thresholds were determined using a standard two-point anesthesiometer (see Figure 9.1).6 Two-point discrimination thresholds were determined for each subject on both the right and left palms, along the lateral medial transverse axis, in both an ascending and descending series. Both ascending and descending

FIGURE 9.1.  A two-point anesthesiometer (Model # 16011, Lafayette Instrument Company). Copyright 2007 by Lafayette Instrument Company, Inc. Reprinted by permission. 6 There

are at least three approaches to the assessment of two-point discrimination thresholds. The first, and traditional, approach derives from neurology/neuropsychology, and it involves the determination of thresholds in the manner as was done in this study. This approach was used in this initial study, namely, the traditional (clinical) anesthesiometer approach. The second approach is in the tradition of psychophysics in experimental psychology and involves approaches such as the method of limits or, preferably, adaptive assessment (e.g., “staircase method” or “method of constant stimuli”). The third approach involves adaptation of the two-point discrimination task for signal-­detection analysis. The three methods are complementary but allow for different inferences.

276

SCHIZOTYPY VIEWED FROM THE LABORATORY

series were used given that both approaches have been used in the determination of two-point thresholds in the neurological literature (Kolb & Whishaw, 1996). A subject was told that his or her palm would be lightly touched and his or her task would be to respond as to whether he or she felt one point or two points touching his or her skin. Assessments were done on each subject’s hands, with the subject’s test hand occluded by a screen that prevented him or her from seeing the procedure. The two-point discrimination threshold was determined for each hand of each subject for the ascending and descending series of stimulations; thus each subject received four two-point discrimination values. For the purposes of this study, the smallest interval at which the subject could discern two points touching his or her skin was recorded as the two-point discrimination threshold for a given series. Extensive detail on this procedure is given in Lenzenweger (2000). I found in this initial study that the two-point thresholds derived from the ascending stimulation series were associated with schizotypy, whereas the descending series data were less strongly associated with schizotypy. Thus the initial focus was on the ascending series data, and I used these data to answer the question, Do individuals with relatively high two-point discrimination thresholds differ from those with more average thresholds in terms of schizotypic deviance on well-­established measures of schizotypy? To address this question, I parsed the subjects into two groups defined by their two-point threshold value based on the mean (average) threshold obtained for the ascending series in the total sample. Such an analysis can be thought of in probability terms as having the structure “given deviance on the twopoint threshold, what is the probability of deviance on the schizotypy scales?” Therefore, using the average ascending two-point threshold values, the subject pool was broken into those subjects representing the highest 10% of the distribution, those falling at or below a cut score equal to 0.50 SD above the group mean, and those subjects falling between these two cuts. The highest 10% group was contrasted with the lower group, holding aside the middle group, on the various schizotypy feature measures. Group means were compared using the t-test, and the results for this analysis were very clear-cut. The subject group defined by the most deviant (i.e., highest 10%) two-point thresholds was significantly elevated on all four schizotypy scales relative to the contrast group. The test statistics for these contrasts are summarized as follows: MIS (p < .001, d = 1.16, effect size r = 0.36), Pz (p < .001, d = 1.14, effect size r = 0.38), REF (p < .03, d = 0.59, effect size r = 0.23), and PAS (p < .03, d = 0.63, effect size r = 0.23). Finally, I wanted to determine whether other factors were driving this set of relationships, and therefore I investigated mental state factors (anxiety, depression) and intellectual functioning (e.g., SAT scores, Wechsler Adult Intelligence



Motion and Touch

277

Scale [WAIS] digit-­symbol performance). These factors were unrelated to the two-point discrimination threshold values. Statistically removing their influence from the associations between the schizotypy measures and twopoint discrimination values had no effect on the latter.

What Was the Meaning of These Initial Exteroceptive Findings? These results were interpreted as providing some preliminary evidence of an association between an exteroceptive somatosensory process and schizotypy. Higher levels of schizotypy were associated with less exteroceptive sensitivity as indexed by the traditional determination of two-point discrimination thresholds. At the same time, these results helped to raise some important substantive and methodological issues, which were pursued in our subsequent studies. At the substantive level, these data seemed consistent with some of the earlier clinical observations (e.g., Bleuler) and theoretical speculations (e.g., Rado, Meehl) regarding somatosensory abnormalities in relation to schizophrenia. They linked reliably assessed schizotypic deviance with increased thresholds. Moreover, the results suggested the possibility of a link between schizotypic deviance and, perhaps, a subtle, parietally mediated somatosensory deficit, given the well-­developed relations between anterior parietal lobe functions (areas 1, 2, and 3) and the two-point measure (Lenzenweger, 2000). These results also raised some important methodological questions for consideration. I emphasize to students consistently that initial studies are incredibly valuable as crucibles in which to discover what you would do differently in the next study, and this initial project was very much such a crucible. For example, there were at least four “big” issues that jumped out at me, after these data were collected, reviewed, and published (Lenzenweger, 2000). First, an important issue raised by these findings concerned the stability of the estimate of the two-point threshold determined through the use of the anesthesiometer using single ascending and descending series of stimulations. In short, was this the best way to derive a stable threshold estimate? Could a method be used to arrive at a more stable estimate of the threshold? Second, although it was appealing to consider that the elevated two-point thresholds observed in relation to elevated schizotypic signs indicated a decreased tactile sensitivity in the presence of increased schizotypy, there existed the possibility that the process driving the correlations between the ascending series thresholds and schizotypy was one concerned with response bias (or response criterion) rather than sensitivity. Could it be that schizotypic subjects are just more conservative in their response styles? Did they simply withhold judgment because they needed more information

278

SCHIZOTYPY VIEWED FROM THE LABORATORY

to make a decision? Was this a motivational difference in responding to the basic two-point discrimination task? These considerations had to be addressed in the laboratory. Therefore, it seemed that it would be optimal to consider adapting the two-point threshold task to a signal detection format in which sensitivity (i.e., discriminability) could be effectively separated from response bias.7 Third, the first study constrained itself to psychometrically assessed schizotypy. It would be important to determine whether the relations between schizophrenia-­related liability and poor performance on the twopoint discrimination task would also be found among individuals defined as schizotypic using one of the other strategies noted previously (e.g., first­degree biological relatives of schizophrenia patients). A fourth issue raised the question, To what extent were the observed relations among the schizotypy measures and the two-point thresholds indicative of a schizophrenia­specific association? Although anxiety and depression features in these subjects did not account for the observed associations, this issue raised the need for additional study using the equivalent of a psychiatric control group.

Study 2: Using the Method of Constant Stimuli to Find Values of Stimuli for Use in a Signal Detection Protocol A primary concern arising from the first study described concerned the robustness of the discrimination threshold estimate obtained using the traditional anesthesiometer approach to the assessment of two-point thresholds. Specifically, the value retained as an individual’s two-point threshold really reflected a single stimulus interval that appeared in either an ascending or descending stimuli series. Clearly, such an estimate may be less robust than one obtained through multiple trials. The anesthesiometer approach to the determination of two-point thresholds has been the standard approach in clinical neuropsychology and neurology; however, we sought to improve the method for our studies. To do so, we turned our attention to the method 7 The

theory of signal detection (TSD) is a well-known methodological approach to helping distinguish between signal and noise in making decisions under conditions of uncertainty. The approach, developed carefully in psychophysics by Green and Swets (1966), has proven useful in separating information regarding one’s level of sensitivity from one’s criterion (or response bias) in a decision task. When monitoring a radar screen, how apt are you to indicate that a new plane just appeared within the flight area for which you are responsible as an air traffic controller? Or, as a radiologist, how likely are you to rate a mammogram for the presence of indicators of cancer? TSD methods allow one to separate one’s detection ability into sensitivity and criterion. Excellent introductions to TSD are found in the following: Wickens (2002), MacMillan and Creelman (2005), and Swets and Pickett (1982).



Motion and Touch

279

of constant stimuli. The method of constant stimuli involves the presentation of stimuli to a subject, not in serial order but in a random or quasi­random fashion. This feature of the method of constant stimuli eliminates the errors of anticipation and habituation known to characterize a methodof-­limits approach. Moreover, the method of constant stimuli yields more informative psychometric functions that provide data that cannot be easily discerned from functions that derive from the method-of-­limits approach (see D’Amato, 1970, for illustration). Interestingly, we discovered that the method of constant stimuli had been advocated for determining two-point thresholds long ago (Titchener, 1905; Gates, 1915). The first step in our development of a protocol for the determination of two-point thresholds using the method of constant stimuli was to select a range of stimuli values that bracketed the probable value of the two-point threshold. This range of values was informed by the preliminary study (Lenzenweger, 2000). The range of stimuli would extend from those that would be rather difficult to detect as two points (e.g., 4 mm) through those that should be fairly easy to detect (e.g., 15 mm). The specific details of this experiment can be found in Lenzenweger, Nakayama, and Chang (2003). In brief, we tested 20 subjects, using this range of values with the method of constant stimuli, to estimate a threshold. We hoped to use these results to inform the development of a new, signal-­detection-based two-point task that would help with the response bias (criterion) issue noted earlier. We plotted the data from the subjects, and they estimated nicely using a logistic function. In this model, the intercept was defined as the inflection point of the function and represented the point of 50% accuracy in performance. The psychometric functions for the averaged data of the 20 subjects, one each for the right and left hands, are presented in Figure 9.2. Inspection of the two functions reveals that the averaged curves conform well to traditional psychometric functions, as described in the psychophysics and experimental psychology literature (cf. Nunnally & Bernstein, 1994). The stimulus values that we chose to bracket the likely two-point discrimination threshold performed well in that the mean threshold values across the subjects were 8.76 mm (SD = 1.78; right hand) and 8.86 mm (SD = 1.10; left hand), with no evidence of outlier or extreme values upon boxplot analysis. A paired t-test analysis revealed that the thresholds across right and left hands did not differ significantly (t[18] = .37, p = .72). The results of this study suggested that a threshold for two-point discrimination on the palm could be located within a 4- to 14-mm bracket of stimuli. Moreover, performance for the group, as a whole, appeared to be well characterized by a logistic function. Finally, the range of stimuli values

280

SCHIZOTYPY VIEWED FROM THE LABORATORY

1.0

Correct Detections (%)

Correct Detections (%)

1.0

0.8

0.6

0.4

0.2

0.0 2

4

6

8

10

12

Stimulus Width (mm) Right Hand

14

16

0.8

0.6

0.4

0.2

0.0 2

4

6

8

10

12

14

16

Stimulus Width (mm) Left Hand

FIGURE 9.2.  Average psychometric functions for the detection of two-point stimuli on the palm (right and left hands) in 20 normal subjects (grouped data) using the method of constant stimuli. Two-point stimulus values varied from 4-mm to 15-mm widths. See Lenzenweger, Nakayama, and Chang (2003) for greater detail.

suggested to us that stimuli below 8 mm would be relatively difficult for many people to detect, whereas stimuli at or above 8 mm would be easier to detect.

Study 3: A Signal Detection Approach to Two-Point Discrimination: Separating Sensitivity from Bias The results from Study 2 using the method of constant stimuli revealed that a stable estimate of the two-point discrimination threshold could be found for our particular task. The next step in the development of the method for our purposes involved adaptation of the task to a signal detection framework, which would allow us to actually disentangle sensitivity (or discriminability) from response bias (or criterion). For this work, we used the wellknown measures of d′ (sensitivity) and in ln b (response bias; Green & Swets, 1966; Swets & Pickett, 1982; MacMillan & Creelman, 2005). Based on the results from Study 2, we selected two stimulus values to represent those that would be used within a signal-­detection-­oriented protocol. We selected 6 mm and 10 mm as our test values. The 6 mm appeared to represent a challenging stimulus to detect, whereas 10 mm appeared to be considerably easier to detect. We used 6 mm then as our “experimental value,” and used the 10-mm stimulus value in order to facilitate active engagement of the subjects with our task by not making the task extremely frustrating.



Motion and Touch

281

These two stimulus values were then embedded into 10 stimuli sequences, each sequence containing 10 stimuli. Each sequence contained, based on a quasi-­random ordering, two 10-mm stimuli, two 6-mm stimuli, and 6 single-point stimuli. Therefore, there were 100 stimuli in total, 20 6 mm, 20 10 mm, and 60 single-point stimuli; thus, each two-point stimulus class had a 20% signal probability. The single-point stimuli offered subjects the opportunity to actually commit “false alarm” errors (i.e., report a twopoint perception in the presence of a single-point stimulus) and thus creating what is termed an objective two-point discrimination task (Craig & Johnson, 2000). We note that two-point discrimination tasks that do not actually present a single-point stimulus during the procedure are known as subjective tasks (Craig & Johnson, 2000). Thus, for the purposes of calculating two sets (separately for 6-mm and 10-mm stimuli) of d′ and ln b values (Green & Swets, 1966; Macmillan & Creelman, 1991), there were 20 possible hits for each stimulus (i.e., target 6-mm or target 10-mm stimuli) and 60 nontargets (i.e., single-point stimuli). Thus, we calculated two sets of d′ and ln b, one for the 6-mm data and one for the 10-mm data. The primary objective of this study was to determine that false-alarm errors would be made to the single-point stimulations and to determine that the 6-mm stimuli were, indeed, significantly more difficult to detect than the 10-mm stimuli in terms of d′. We were also interested to determine whether statistically reliable differences in response criterion (ln b) would emerge across the 6-mm and 10-mm trials.For the 6-mm stimulus, the mean d′ was 0.93 (SD = .76), and the mean ln b was 0.62 (SD = .93) and for the 10-mm stimulus, the mean d′ was 2.30 (SD = .78) and the mean ln b was –.01 (SD = 1.27). For the d′ indexes, the 6-mm stimuli were considerably harder to detect than the 10-mm stimuli (paired t[19] = 8.789, p < .001). The 6-mm and 10-mm d′ indexes were substantially correlated within individuals (r = .59, p < .006). The ln b indexes for the 6-mm and 10-mm stimuli also differed significantly (paired t[19] = 4.151, p < .001), with a more conservative criterion found for the 6-mm stimuli. The 6-mm and 10-mm ln b indexes were highly correlated within individuals (r = .85, p < .001). The results from Study 3 indicated to us that the signal-­detection version of the two-point discrimination task functioned well, with the 6-mm task indeed being harder than the 10-mm task. The beginning student of experimental psychopathology is always rather amazed when he or she realizes that one does not go directly from a hypothesis to empirical evaluation of the hypothesis. The “in-­between work” tends often to be very substantial, and, in reality, a considerable amount of time, energy, and creativity is required during the period in which a proto-

282

SCHIZOTYPY VIEWED FROM THE LABORATORY

col and all related methods are developed. Moreover, the pace at which this kind of work moves can be slower than one expects—­surely slower than most students expect. My former long-time, now late, colleague Brendan Maher typically recommended that one double the amount of time that one thinks it will take to do an experiment when planning a project; in my experience, I find that tripling the amount of time has been about right. The work I have just described was very much the “in-­between” sort of work that set the stage for an evaluation of our basic hypothesis regarding diminished two-point stimuli detection sensitivity8 and schizotypy (schizophrenia liability).

Study 4: Two-Point Discrimination in the First-­Degree Biological Relatives of Schizophrenia-­Affected Individuals Having developed the two-point discrimination task for use within a signal­detection framework, we then proceeded to conduct a fourth study of the two-point discrimination task in a population of relevance to schizophrenia (Chang & Lenzenweger, 2001). We chose to focus on the first-­degree biological relatives of individuals with schizophrenia for this study, and in doing so, we extended the exploration of exteroceptive sensitivity to another of the classic approaches for the study of individuals at increased risk for schizophrenia, the biological schizotype9 (as discussed earlier). This study was undertaken, in part, to further investigate exteroceptive sensitivity using standardized two-point stimulation in an effort to separate the issues of sensitivity and response bias. It was hypothesized, guided by the results of Study 1 (Lenzenweger, 2000), that the biological relatives of schizophrenia patients would display deficits in the discrimination of two-point stimulation relative to normal control subjects, whereas the relatives and controls should not differ with respect to response bias. I note that this study was less concerned with two-point discrimination “thresholds” per se, and more with the capacity to detect two-point stimulation. As detailed in Chang and Lenzenweger (2001), we examined the twopoint discrimination performance in 39 subjects who are the first-­degree 8 With the adaptation of the two-point discrimination task to the signal-­detection framework, we moved away conceptually from two-point discrimination thresholds per se and adopted a focus that emphasized detection of two-point stimuli, which is relevant to a threshold but not directly indicative of the threshold concept. 9 We

understood that not all biological first-­degree relatives of schizophrenia-­affected persons would be schizophrenia liability carriers. However, we knew that on average these people had a higher likelihood of carrying increased schizophrenia liability. One should be aware, however, that even among the first-­degree relatives of schizophrenia patients, not every one of them will carry liability (see Hanson, Gottesman, & Meehl, 1977).



Motion and Touch

283

biological relatives of individuals with schizophrenia and who themselves had no history of psychosis and 30 normal adult control subjects recruited from the community. The subjects completed the objective two-point discrimination task that we adapted for use with a signal-­detection approach detailed in Study 3. We again employed the 6-mm and 10-mm stimuli for use in this task. The 6-mm interval was a challenging stimulus to detect, but not one that was unduly difficult, and it constituted our “experimental” task. The 10-mm task was considerably easier to complete with high levels of accuracy; we viewed it as our “control” condition to help to ensure that subjects would remain engaged with the task and not become easily frustrated during the protocol. As in Study 3, the 100 stimulations were organized into 10 sequences, each containing 10 stimulations (two 6 mm, two 10 mm, and six single-point stimulations). Each sequence was randomly ordered, and the order of administration of the 10 sequences was randomized across subjects. The relatives of schizophrenia patients revealed (M = 2.10, SD = 0.39), as predicted, poorer performance on the 6-mm d′ index as compared with the controls (M = 2.29, SD = 0.40, t[67] = 2.06, p < .05, d [effect size] = 0.50), and the two groups did not differ on ln b (relatives M = 1.94, SD = 0.52 vs. controls M = 1.90, SD = 0.60, t[67] = –.25, p < .80, Cohen’s [1988] d [effect size] = 0.06) , which suggested a genuine difference in sensitivity and not response bias. The deficit in sensitivity (i.e., d′) was driven principally by a lower “hit rate” on the two-point 6-mm trials and not an elevated false-alarm rate on the single-point stimuli. The relatives and control subjects did not differ significantly on either d′ or ln b for the 10-mm “control” task (Chang & Lenzenweger, 2001). Importantly, we found the relatives of the schizophrenia patients as contrasted with the normal controls not to be deficient in their performance on several neuropsychological tasks that were also computed (e.g., Rey Complex Figures Test; Meyers & Meyers, 1995). This pattern of results argued against a generalized deficit explanation of these findings. The poor performance on the 6-mm d′ index seen for the biological relatives was most closely associated with two schizotypic features that were measured in all the subjects, namely, odd beliefs and magical thinking. We found, as predicted, that the first-­degree biological relatives of schizophrenia patients performed significantly worse on the two-point discrimination task, and the deficit was found in the discriminability (i.e., sensitivity) aspect of performance (not in response bias). The results of this study were largely consistent with those observed initially in Study 1 (Lenzenweger, 2000). We have continued to conceptualize these findings within a framework that emphasizes a parietally mediated somatosensory deficit

284

SCHIZOTYPY VIEWED FROM THE LABORATORY

in schizophrenia and schizotypy. However, we cautioned against an undue rush to localization to the anterior parietal cortex (areas 1, 2, and 3) but rather prefer more of a network-­oriented conceptualization that takes into account the rich complexity of the exteroceptive somatosensory system and proprioception (Lenzenweger , 2000; Chang & Lenzenweger, 2005).

Interim Summary: Exteroception and Schizotypy In exploring a possible somatosensory processing deficit in schizotypy, our work proceeded from clinical observations to classic descriptions by Bleuler, Rado, and Meehl through an exploration of neuropsychological methods and refinement of our methods using the tools of experimental psychology. We brought this phenomenon into the experimental psychology laboratory and, in doing so, we encountered any number of methodological challenges. We addressed them using methods from psychophysics and signal-­detection frameworks. What has been particularly exciting to learn is that, quite apart from the work involving the two-point discrimination threshold in psychopathology, there has been substantial interest in this phenomenon for nearly 100 years both in applied disciplines (e.g., neuropsychology, neurology) and in experimental psychology itself (e.g., Gates, 1915; Loomis & Lederman, 1986; Titchener, 1916). Although the two-point discrimination task has been criticized for one or another shortcoming, it is reasonable to assert that the basic two-point discrimination task is viewed as one that does tap the exteroceptive somatosensory function in a systematic fashion (Loomis & Lederman, 1986; Vallbo & Johansson, 1978). Johnson and his colleagues have devoted a considerable amount of effort to the study of the two-point discrimination threshold (Johnson & Phillips, 1981; Craig & Johnson, 2000). An interesting question raised by Johnson and colleagues concerns the precise nature of the process that is involved in two-point discrimination performance. In a sense, just what is being measured here? It has long been suggested that the two-point discrimination threshold provides a measure of spatial resolution; however, that view is not shared by all workers in this area (e.g., Craig & Johnson, 2000). According to Johnson and colleagues, due to the nature of two-point stimulation, performance on the task may represent either decreased spatial acuity and/or impaired intensity cue processing of tactile stimuli, and alternative methods have been proposed for studies directed at spatial resolution (e.g., gap detection, grating resolution, letter recognition; Johnson & Phillips, 1981). For our purposes in psychopathology, we would find either possibility (i.e., spatial resolution or intensity processing deficits) to be worthy of further investigation.



Motion and Touch

285

Finally, in this context, I would like to mention the value of replication in experimental psychopathology. I have in mind not only exact, operational replication of findings, in which one follows a prior procedure precisely with a new sample (a literal or direct replication), but also replication in which the substantive study question is asked and answered with a varying methodology and/or varying subjects (a construct or systematic replication). In our study of exteroception we have both forms of replication: Chang and Lenzenweger (2001) replicated Lenzenweger (2000); then we replicated Chang and Lenzenweger (2001) a few years later (Chang & Lenzenweger, 2005).

Somatosensory Functions: Proprioception A New Look at Proprioception in Relation to Schizophrenia Liability What is meant by the term proprioception? Proprioception refers to the sensory process that helps guide an individual’s awareness of body position and balance (Kolb & Whishaw, 1996; Martin, 1996). Specialized cells (termed proprioceptors) are located in a wide number of areas in the body, from joints to deep muscles and tendons. There are several types of proprioceptors (e.g., Golgi tendons, intrafusal fibers; Marieb, 1998; Martini, 2001); however, all proprioceptors send information regarding the stretch/tone of a muscle or connective tissues to the nervous system, where the information is used to gauge body position and balance. Prior research has typically used weight discrimination tasks as one way of assessing proprioceptive processing. Clinical description and extant theory make the case for the presence of proprioceptive disturbances in both schizophrenia and those at risk for schizophrenia (i.e., schizotypes). There has been some modest research interest in proprioception in schizophrenia per se. To our knowledge there had been no previous studies of proprioceptive processing in those at increased risk for schizophrenia (namely, schizotypes) when we began our work. Would impairments in weight discrimination similar to those seen in persons with schizophrenia be seen in first-­degree biological relatives of schizophrenia patients? If schizophrenia relatives displayed weight discrimination impairments, then perhaps the weight disturbances in schizophrenia may be associated with some core liability to schizophrenia rather than with the disorder itself (or some third-­variable confound). Thus we began to move from our prior studies that focused just on exteroceptive perception to include proprioception. This work was undertaken with my then graduate student Bernard Chang. We evaluated proprioceptive functioning in a group of individuals (i.e., first-­degree biological

286

SCHIZOTYPY VIEWED FROM THE LABORATORY

relatives of schizophrenia patients) who represent, as a group, individuals at increased statistical risk for carrying schizophrenia liability. Not unlike in the situation for exteroception described earlier, we needed to make a number of methodological adjustments and introduce some innovation in the assessment of proprioceptive processing to rule out artifacts (e.g., response bias, specificity to schizophrenia liability). We employed several methodological features in our study that represented advances over prior work: first, use of a signal detection methodology; second, use of a psychiatric control group to assess the specificity of the observed deficits; and third, use of focused-­contrast analysis (Rosenthal et al., 2000) to specify our hypotheses with greater precision and power in our statistical analyses. In brief, as adapted from Chang and Lenzenweger (2005), we compared 30 first-­degree biological relatives of schizophrenia patients to 30 first­degree biological relatives of persons diagnosed with bipolar affective disorder (psychiatric family controls) and 30 subjects with no family history of schizophrenia (normal controls). We included a psychiatric family control group (the relatives of bipolar-­affected patients) to address the possibility that weight discrimination deficits arose from a generalized psychopathology deficit not specific to schizophrenia liability.10

How Does One Evaluate Proprioceptive Processing?: A Weight Discrimination Task In order to assess proprioception, we decided to use a weight discrimination task. The hefting of weights, which would stress muscles and tendons, would create the demand we needed to place on the proprioceptive system. Subjects compared a standard weight to a stimulus weight and judged whether the stimulus (experimental) weight was heavier than the standard weight. The weight task was a unidirectional forced-­choice design; subjects judged simply whether the weight was heavier or not (i.e., no distinction was made between the weight being lighter or the same as the standard weight). Not unlike our prior work on exteroceptive processing and the twopoint discrimination task, we needed to develop the proprioceptive task in order to make it both engaging to subjects and informative to us as experimenters. In pilot work, we found that a stimulus weight of 210 grams, when compared with a standard weight of 200 grams, represented a challenging stimulus to detect but one that was not unduly difficult. In the present study, we presented a 210-gram weight in comparison with a standard 10 Extensive

methodological detail on this study can be found in Chang and Lenzenweger (2005).



Motion and Touch

287

weight of 200 grams. This 210-gram stimulus, therefore, constituted the “experimental” task. In this protocol, we presented twenty-six 210-gram comparisons intermixed randomly with fifty same-­weight (i.e., 200-gram) comparisons and twenty-six 220-gram comparison stimulations, for a total of 102 stimulations. We included the twenty-six 220-gram stimulations in the protocol because this weight was very easy to detect as being heavier in pilot studies. It was included as a “control” condition to help to ensure that subjects remained engaged with the task and did not become easily frustrated during the protocol. The 102 weight comparisons were randomly ordered to avoid any potential ordering effects. Furthermore, in pilot work we found that the order of presentation for each paired-­weight trial (i.e., stimuli weight presented first vs. comparison weight presented first) did not result in any significant differences in weight-task performance. However, in order to be completely certain of no potential order effects in the study, we presented the weight stimuli in two orders. For the twenty-six 210-gram stimulations, we had thirteen trials of order 1 and thirteen trials of order 2. In order 1, we presented the test (experimental) weight (210 grams) followed by the standard weight stimuli (200 grams). In order 2, we presented the standard weight stimuli followed by the presentation of the test stimuli. The twenty-six 220gram trials were also divided up into thirteen order 1 trials and thirteen order 2 trials. Presentation of the separate orders was randomized. Performance on the task consisted of hits (correct detection of heavier weight) and false alarms. Hit rates were calculated as the percentage when the subject correctly stated the stimuli weight was heavier than the standard weight. The false-alarm rate represented the percentage of errors in which subjects erroneously said the 200-gram weight was heavier than the same-­weight 200-gram stimuli. Using the hit and false-alarm rates for each subject, we calculated the two signal-­detection indexes, d′ and ln b (Green & Swets, 1966; MacMillan & Creelman, 1991) for each subject. The comparison that was of greatest interest to us was one that would place the relatives of schizophrenia patients lower in performance accuracy than either the control relatives or normals. The focused-­contrast weights for this analysis would be: schizophrenia relative (2), control relatives (–1), and normals (–1). As seen in Table 9.1, our contrast for predicted group differences on the 210-gram hit rates was significant and represented a medium effect (rcontrast = .28; Cohen’s d = 0.58). Schizophrenia relatives had significantly lower hit rates than both of the other groups. The same contrast was not significant for 210-gram false-alarm rates. Our contrast for predicted group differences on the 210-gram d′ measure was significant, representing

288

SCHIZOTYPY VIEWED FROM THE LABORATORY

TABLE 9.1.  Weight Discrimination Performance in Controls and Schizotypes Healthy controls Index

Schizophrenia relatives

Bipolar relatives

M

SD

M

SD

M

SD

t

p

210-g Hit Rate 210-g False-Alarm Rate

.683 .181

.086 .051

.619 .184

.100 .052

.677 .175

.117 .054

2.70 -.513

.008 .609

Alarm Rate 210-g d′ 210-g ln b

1.42 .304

.306 .234

1.23 .356

.329 .225

1.44 .290

.453 .282

2.44 -1.06

.017 .291

Note. Weight discrimination task performance (210 g) for control subjects and the first-degree biological relatives of schizophrenia and bipolar disorder patients. Hit rate is the percentage of correct detections, falsealarm rate is the false-positive rate for errors (commission errors), d′ is the signal detection term that indexes sensitivity, and ln b is the signal-detection term that indexes criterion or response bias.

a medium effect (rcontrast = .25; Cohen’s d = 0.52). Schizophrenia relatives had lower d′ measures than both the normal and family-­control groups. The contrast for ln b was not significant for differences among the three groups, suggesting no response bias differences. In psychopathology research, it is always worth asking additional post hoc questions of your data; remember, it took you considerable energy, time, and money to collect them. One additional question that we had was, Holding the schizophrenia relatives aside, would the normals and the family­control relatives differ on our dependent variables of interest? We thought that they should not differ if the weight discrimination deficit seen in the schizophrenia relatives was relatively specific to schizotypy. We conducted another focused linear contrast using the lambda weight assignments of schizophrenia relatives = 0, normal controls = +1 and bipolar relatives = –1. This contrast analysis revealed no significant differences between the bipolar relatives and healthy controls on the 210-gram d′ measure (t[87] = –.244, p < .81) or the ln b measure (t[87] = .219, p < .83). The presence of weight discrimination impairments in schizophrenia relatives demonstrates that weight impairments seen in schizophrenia are also observed in their biological relatives. This study represented the first confirmation of a proprioceptive deficit in persons who carried a statistically increased risk for schizophrenia but who have never been psychotic. We (Chang & Lenzenweger, 2005) viewed these findings as consistent with the theoretical conjectures of both Rado and Meehl, who argued for the presence of a proprioceptive impairment associated with the liability for schizophrenia. Furthermore, because group differences were limited to d′ values on the weight discrimination task, these results allowed us to argue



Motion and Touch

289

against the suggestion that differences in discriminability or sensitivity to proprioceptive stimuli were due to response bias (motivation) differences.

On the Value of Peeking in Places Neglected by Others: The Parietal Lobe and Schizotypy Some observers of the field have suggested that psychopathology research is at times dominated by one or another hobbyhorse issue and that bandwagon science is prevalent (though I doubt psychopathology research has cornered the market on this sort of thing). Clearly, there is good reason to avoid “faddism and one-shot papers” (as decried by Maher, 1974), not the least of which is the fact that such work creates the illusion of progress and wastes valuable laboratory time (and resources). Therefore, I often encourage my students “not to follow the crowd” when discerning a research question of interest to them. In following the crowd, one might miss some important clues or interesting alternative routes (stated differently, one is more likely to see interesting things in the backcountry in Yellowstone National Park than at the drive-up campground with 500 other RVs parked there). Our work on somatosensation had a backcountry feel to us and took us to a place and network worthy of closer scrutiny, the parietal lobe. Based on the results from this series of studies (Lenzenweger, 2000; Chang & Lenzenweger, 2001, 2005), it appears that schizotypy is associated with at least two forms of somatosensory impairments, each of which potentially implicates parietal brain area involvement. It is well established that all basic somatosensory processes have major projections to the anterior parietal area known as the primary somatosensory cortex (Kolb & Whishaw, 1996; Martini, 2001). Damage to the primary somatosensory cortex results in a wide number of basic somatosensory impairments, such as disturbance in touch processing and pain perception (e.g., Jones, 2000). Furthermore, complex cognitive somatosensory processes have been linked to the secondary somatosensory association cortex (Kolb & Whishaw, 1996; see also Kennedy & Bai, 2002; Romo, Hernandez, Zainos, Lemus, & Brody, 2002; Yasuda, Watanabe, & Ogura, 2000). The pattern of weight sensitivity (proprioception) and touch sensitivity (exteroception) deficits seen in both schizophrenia and schizotypes is similar to deficits seen in patients with primary and secondary somatosensory cortex damage. Thus we suggest that the somatosensory deficits in the first-­degree biological relatives of schizophrenia patients and in connection with psychometrically assessed schizotypic features, as well as in schizophrenia proper, can be potentially understood from the perspective of a parietal-­related dysfunction.

290

SCHIZOTYPY VIEWED FROM THE LABORATORY

Indeed, one of the interesting issues that arose in our somatosensory research in schizotypy was an increased awareness of the possible role that the parietal cortex plays in schizotypy and schizophrenia. The parietal lobe, obviously, could be of interest in and of itself. However, its gateway function for somatosensory stimuli en route to other brain areas, as well as neural circuitry connections to other brain areas (e.g., frontal cortex), make it worthy of increased scrutiny. For example, Zhou et al. (2007) have recently reported decreased parietal lobe volumes (postcentral gyrus) in both schizophrenia and schizophrenia spectrum cases. Torrey (2007) has recently called for more research attention to be paid to the parietal lobe, particularly the inferior parietal lobule (a part of the posterior parietal). Fascinating research also implicates the anterior parietal lobe—the focus of our exteroceptive research—as an important integration point for internal state information and emotional feelings (Anders et al., 2004).

Motor Functions Informal Clinical Observations of Motor/Mechanical Awkwardness Just as clinical observation of inadequately dressed subjects arriving for research appointments on cold January days in Ithaca led to hypotheses regarding exteroceptive somatosensation deficits, my observation of subjects navigating through the lab provided additional food for thought and hypothesis generation.11 Over the years, my log book and “interesting observation file” accumulated entries regarding awkwardness and clumsiness on the part of schizotypic subjects. I would make observations blind to clinical or group membership status of the subjects we were testing, then, after a study was done and the blind was broken, I would go back and visit these observations. The schizotypes were variously described as “seems clumsy,” “bonked into the table,” “nearly fell over the equipment cart,” or “bumped into the room divider, nearly knocking it over.” The subjective, clinical, impressionistic take on these observations was that schizotypes seemed awkward. Did 11 To

my mind these observations highlight the importance of the point made early in this discussion regarding “staying close to one’s data.” Simply put, I would never have had the opportunity to generate these hypotheses if I had not been in my laboratory and actively observing. Thus, no matter how advanced one becomes in one’s career, it always makes sense to me to maintain close proximity to one’s data collection setting. It really is a fertile ground for hypothesis generation. My colleague Jerome Kagan similarly advocated the benefits of being involved in data collection, citing as an example of potential benefits, his insights regarding behavioral inhibition that grew from the clinical/naturalistic observation of children being tested in his laboratory on one or another protocol.



Motion and Touch

291

they have trouble navigating through space? Did they not quite know their body position with respect to such things as furniture, doorways, and so on? What did we know about their body sense, their internal map of their body in relation to spatial information? Clearly, navigating through space requires multiple sources of information input, integration of such information across a wide parameter space, and computation in real time while behavior is being executed (one does not really stop to think, “Hey, I am walking down the street, and I shouldn’t trip over that garbage bag in the middle of the sidewalk”—rather, one simply adjusts one’s path with little effort in real time). Clearly, the body sense functions described previously in connection with the parietal area is relevant here, but these observations also raised issues regarding the implementation of motor actions.

Has Anyone Discussed Motor Awkwardness in the Original Descriptive Literature? Of course . . . Motor abnormalities have long been observed in schizophrenia, and it has always been assumed that their basis lies in the biological substrate of the illness. Kraepelin (1919/1971) observed in schizophrenia what he termed “various and profound disorders” in the “psycho-motor domain” (p. 79), noting among schizophrenia patients that the “the out-­spread fingers often show fine tremor” (p. 83). Bleuler (1911/1950) noted that “the tremors, which in acute conditions often are quite similar to the coarse shivering of the feverish, and which in the chronic [patient] arise quite independently of agitations, excitements or strains, can also be interpreted as organic” (p. 352). Rado (1960) described a proprioceptive (kinesthetic) diathesis in those carrying a liability for schizophrenia (so-­called schizotypes), which manifested itself in part in a distorted awareness of one’s body and its movement. Meehl (1962, 1990) proposed a “ubiquitous CNS anomaly” reflected in his neurointegrative deficit, schizotaxia. For Meehl (1990), any neurocognitive domain requiring complex integration of information from several different controlling subsystems (e.g., fine motor movement) is likely to be affected by the proposed neurointegrative defect. Empirical studies have also identified motor abnormalities in schizophrenia and schizophrenia-­related psychopathology. Bender (1938) reported noteworthy abnormalities in the productions of schizophrenia patients on her measure of visual motor performance. King (1954) reported on deficits in motor performance in both chronic schizophrenia patients and pseudoneurotic schizophrenia patients on tasks requiring fine motor dexterity (e.g., Purdue pegboard, assembly task). Fish (1977, 1987; Fish, Marcus, Hans, Auer-

292

SCHIZOTYPY VIEWED FROM THE LABORATORY

bach, & Purdue, 1992), in her classic developmental studies, showed that a neurointegrative disorder that included motoric dysfunction elements and that was observed early and found to be measurable on behavioral developmental tests was shown to be an antecedent to early-onset, poor premorbid chronic schizophrenia. The motor characteristics of preschizophrenia cases has received renewed attention in recent neurodevelopmental models of schizophrenia (e.g., Erlenmeyer-­Kimling & Cornblatt, 1987; Walker, Lewis, Loewy, & Palyo, 1999), as well as in empirical studies. For example, Crow, Done, and Sackler (1996) reported lower lateralization on pegboard task performance by children in early adolescence who later developed schizophrenia, whereas children who subsequently developed other disorders did not reveal such a neuromotor performance pattern. Finally, neurologists have long described motor abnormalities in schizophrenia (Manschreck, 1986) and neurological investigations (Ismail, Cantor-Graae, & McNeil, 1998) report an elevated rate of motor dysfunction (e.g., dysdiadochokinesia) in schizophrenia patients and in their biological relatives. Overall, there is a rich descriptive, theoretical, empirical, and clinical corpus of information that implicates motor dysfunction as a manifestation of schizophrenia. Importantly, the developmental studies (e.g., Fish, 1977, 1987; Erlenmeyer-­Kimling & Cornblatt, 1987) suggest that it is plausible to view motor dysfunction as an early manifestation of the schizophrenia liability. Additional evidence in favor of such a developmental view could come from the study of individuals with schizotypic features who have no prior history of psychotic illness.

The Methods of the Experimental Laboratory: Moving Motor Assessments Forward in Terms of Precision Despite the obvious importance of motor dysfunction in schizophrenia, empirical definition and reliable assessment of such a dysfunction represent research hurdles in this area. A challenge to defining the precise nature of the motor abnormalities has to do with the wide variation in assessment procedures across investigations and diagnostic frameworks within neurology (e.g., soft signs; see Ismail et al., 1998). The need for a simple, objective measure of fine motor performance was recognized by Maher (1993), and he developed such a measure. Blyler, Maher, Manschreck, and Fenton (1997) and Manschreck et al. (2000) reported on the utility of this simple fine motor task in relation to clinical schizophrenia (see also Maher & Manschreck, 1998; Manschreck, Redmond, Candela, & Maher, 1999) and Ballard (2000) employed the technique in the study of first-­degree biological relatives of individuals affected with schizophrenia. In discussions of



Motion and Touch

293

schizotypic pathology, my late colleague Brendan Maher and I wondered whether nonpsychotic schizotypic subjects display evidence of fine motor dysfunction.

What Is the Maher Line Drawing Task? A full description of the Maher (1993) Line Drawing Task is given in Blyler et al. (1997). The procedure provides a simple and reliable quantitative measure of motor coordination that employs ratio scaling with a true zero, is not time-­consuming, involves a response that is familiar to subjects, and does not require rating scales or other indices dependent on human judgment. It is noted that performance on the line drawing task is unrelated to dyskinetic movement disorders (Blyler et al., 1997; see Figure 9.3). On this task, the subject is asked to draw a series of four straight lines, two with the right hand and two with the left hand. Each line is drawn in a 2-inch square (5.08 cm) from one of the bottom corners to the upper corner obliquely opposite. For each hand one such line is drawn from the bottom left to the upper right of the square; the other is drawn from the bottom right to the upper left. A perfect response would consist of a straight line at an angle of 45 degrees with no deviations from linearity. Each of the four lines is scanned separately with a flatbed optical scanner, and the image is saved in a computer graphic format. The resulting graphic is then digitized to produce a series of X–Y coordinates. A first-order line regression is computed, with the root mean square (RMS) defining the error score. A perfect line would, of course, have RMS = 0. From the four RMS scores that are obtained, two main derivative measures are computed. One is the total RMS for the four lines summed. This is a measure of overall accuracy. Separate subtotals for the right hand and left hand are also computed and form the basis for computing laterality scores. A relative laterality index is computed as (Total Left RMS – Total Right RMS) / Total RMS, and the absolute value of this relative laterality index is taken to create an index of absolute laterality (i.e., all values have a positive sign and are not dependent on handedness of the subject). In nonpsychiatric and psychiatric populations, the resulting distributions of scores tend to be skewed, and the scores have therefore typically been transformed logarithmically. Thus the two primary measures are known as “log of root mean square” (log RMS) and “log of absolute laterality” (log AL). We set out to determine whether fine motor performance and an estimate of performance laterality, assessed by the Maher (1993) Line Drawing Task, were associated with psychometrically assessed schizotypy. Specifically, it was hypothesized that the presence of elevated amounts of error,

294

SCHIZOTYPY VIEWED FROM THE LABORATORY

FIGURE 9.3.  Maher Line Drawing Task (Maher, 1993). The image above depicts the Maher Line Drawing Task that was used in the study of psychomotor performance and schizotypy (Lenzenweger & Maher, 2002). In this task a subject draws two sets of lines, one set with the left hand and one set with the right hand. Each of the four lines drawn by the subject is then scanned, digitized, and scored for total error (i.e., deviations from a perfect line). These four values are summed to create a total error index, and this index is typically log transformed to enhance normality. A precise, ratio-scale-based metric of error is obtained by comparing drawn lines with a perfect, error free 45° line using regression procedures. Reprinted with permission from Winifred B. Maher.



Motion and Touch

295

indexed by the RMS measure derived from the line drawing task, would be associated with higher levels of schizotypy as measured by several well­established psychometric measures of schizotypy. What did we find? The results of our study suggested that increased amounts of residual error (i.e., RMS) on the line drawing task were clearly associated with higher levels of schizotypy, particularly as measured by the PAS in both the combined and female samples and the Rosen Pz Scale in the males (see Table 9.2). We found no compelling relationships between absolute laterality and the psychometric schizotypy measures. We have recently replicated these basic findings in an independent sample of psychometrically identified schizotypic subjects.12 Might there be other factors that might have led these subjects—with no prior history of psychosis—to nonetheless have some troubles with the Maher task? What if they did not pay attention well during the task? What if they were not so quick in their speed of processing? What if they were a bit under the emotional weather that day in the lab—that is, what if they were a little depressed or anxious? To address this important methodological concern, we carried out a series of control regression analyses that included psychological state, intellectual functioning, and sustained attention variables in the prediction of line drawing performance. These regressions produced TABLE 9.2.  Schizotypy Scale Values and Performance on the Maher Line Drawing Task in 115 Subjects Subject sample Males (n = 50)

Females (n = 65)

Referential Thinking

.33*

.20

.21**

Magical Ideation

.17

.25*

.19*

Rosen Paranoid Schizophrenia Scale (MMPI)

.38**

.20

.31***

Perceptual Aberration

.29*

.36**

.33***

Schizotypy index

Combined (n = 115)

Note. Correlations among psychometric schizotypy indexes and log of root mean square for line drawing (n = 115). Values are Pearson product–moment correlation coefficients. Correlations were tested for statistical significance using a one-tailed procedure based on a directional a priori hypothesis. MMPI, Minnesota Multiphasic Personality Inventory. Adapted from Lenzenweger and Maher (2002). Copyright 2002 by American Psychological Association. Adapted by permission. * p < .05; ** p < .01; *** p < .001. 12 Unpublished data (Roché, M. W., Milné, D. A., Sloat, V. C., Maher, B. A., & Lenzenweger, M. F. (2008, September). Psychomotor dyscontrol and disorganization in psychometrically defined schizotypes. Poster presented at the annual meeting of the Society for Research in Psychopathology, University of Pittsburgh, Pittsburgh, PA.)

296

SCHIZOTYPY VIEWED FROM THE LABORATORY

results that clearly indicated that these factors (these potential artifacts) were at best only weakly associated with line drawing performance (i.e., log RMS). Most important, however, they did not account for the observed significant relations between the schizotypy scales and line drawing (log RMS) performance (i.e., the semipartial correlations in the regression analyses). We also discovered that performance on the WAIS-R digit-­symbol subtest, a test that involves both processing speed and psychomotor agility under highly structured and timed conditions, was not related to performance on the line drawing task, which is less structured and untimed. Whatever was behind the psychomotor dysfunction and schizotypy associations we observed, it was not one of the factors we had entered into the control regressions. This kind of control analysis is in the self-­critical spirit of “let’s try to make this finding disappear” that any experimental psychopathologist should espouse in evaluating the robustness of his or her findings.

Fitting In These Results with What We Know about Schizophrenia How do the results of this study compare with those obtained in other studies using the line drawing task? Blyler et al. (1997) found that schizophrenia patients displayed higher total RMS error scores than control subjects, whereas the laterality index derived from the task did not differentiate schizophrenia patients from control subjects. In a study of the first-­degree biological relatives of schizophrenia patients, one of my undergraduate students at Harvard, Jennifer Ballard, found that the relatives displayed a trend toward higher total RMS error (p < .08), as well as significantly lower levels of absolute laterality (p < .03), as contrasted with control subjects (Ballard, 2000). Of interest, Ballard (2000) also reported that higher levels of schizotypal symptoms were associated with lower levels of absolute laterality and that higher levels of schizotypal symptoms were positively associated with higher total RMS scores on the line drawing task. Thus both the Blyler et al. (1997) and Ballard (2000) studies also suggested an empirical relationship between schizophrenia and schizophrenia liability (i.e., first-­degree relatives) and performance on the line drawing task.

A Kinesthetic Connection: Making Sense of These Results We could not specify the precise etiology of the motor deficit we found. Nonetheless, based in large part on the results for the PAS (largely a measure of body image aberration) in this study, we were intrigued by the notion



Motion and Touch

297

that the psychomotor deficit we found in relation to schizotypy could represent the sort of dysfunction consistent with that hypothesized by models emphasizing impaired neural integrative processing of basic proprioceptive and kinesthetic stimuli (e.g., Rado, Meehl). The proprioceptive and kinesthetic systems involve integration of information regarding body awareness, orientation in space, and experience of movement (Hecaen & Albert, 1978; Kolb & Whishaw, 1996). It is entirely conceivable that the body image–­ perceptual distortions content of the PAS might be, in part, responsible for its stronger relationship with log RMS as opposed to that observed for the MIS, which is largely concerned with cognitive phenomena. To test this idea, we actually conducted an item-level regression analysis in which the individual PAS items were regressed onto the log RMS score. This analysis was clearly post hoc and exploratory in nature. This analysis was, in fact, the very analysis that we were asked to remove from the scientific paper that reported these original findings (Lenzenweger & Maher, 2002). As noted earlier, this analysis produced fascinating and generative findings. Let us remind ourselves of what was found. The two following PAS items predicted significant amounts of variance in the log RMS dependent variable: “I have had the momentary feeling that my body has become misshapen” (r = .26, p < .004). “Sometimes I feel like everything around me is tilting” (r = .18, p < .05). To us, the content of these items brought together the body image, kinesthetic, and proprioceptive in a powerful little dyad. As mentioned earlier, this content also spurred on our research in proprioception (Chang & Lenzenweger, 2005). We are continuing to prove the nature of the motor dysfunction that we found among the more schizotypic subjects. One of our research directions is the development of a quantified approach to evaluating the quality of the lines drawn by subjects on the Maher Line Drawing Task. Not unlike the manner in which the quality of eye tracking tracings can be assessed, we hope to capture the quality of production with a quantitative method.

C h a p t e r 10

The Schizotype through Time . . .

Over time, the latent liability for schizophrenia or schizotypy can develop in any number of directions. One of the central propositions in Meehl’s (1962, 1990) model was that schizotypy could manifest itself across a range of compensation, from essentially nondetectable with the naked (unaided) eye through various schizotypic conditions (e.g., schizotypal personality) on to expressions of flagrant psychosis. For example, if we could locate 100 individuals who were known to be “schizotypy positive,” and we assessed them in a cross-­sectional fashion (i.e., at that one point in time), we would find many without any visibly detectable schizotypic features but who would manifest subtle disturbances in neurocognitive or motor functioning (endophenotypes); a smaller proportion would present a range of diagnosable schizotypic phenomenology (e.g., schizotypal or paranoid personality disorder features; subclinical thought disorder, or elevated referential and/ or magical thinking and so on); and an even smaller proportion would have (or have had) a psychotic schizophrenic illness. This span of pathological manifestations of schizotypy is the reality that gave rise to the “expanded phenotype” discussed in Chapter 4 in this volume. What happens to a schizotype over time? Relatedly, what happens, on average, to a group of schizotypes over time? Unpacking these questions requires us to define what we mean by “what happens?” One way of interpreting this question concerns what outcomes are observed in schizotypes at the end of some follow-up period. By “outcomes” we mean cross

298



The Schizotype through Time . . .

299

s­ ectional clinical status at follow-up, typically diagnosable schizophrenia and related psychotic disorders. Clinical status at follow-up could also include schizophrenia-­related Axis II personality disorders (assuming the subjects were assessed for same at baseline),1 as well as various life data domains at follow-up (marital, occupational, and/or social functioning and such). This is the typical form of follow-up study: a group of subjects is identified, time passes, the same subjects are examined again at the follow-up time point, and, typically, the findings for the identified high-risk or at-risk group are contrasted with those obtained for a broadly comparable group of control, or “normal” subjects. A second way of interpreting the “what happens” question is one that highlights stability and change in the same measured construct over time within people. The focus is not on a cross-­sectional outcome but rather on the patterns of intraindividual stability and change. The pattern of individual growth (or change) within subjects is of great interest, and various predictors or background variables are used to predict the components of growth over time. Individual growth is indexed by an individual growth curve (IGC), which represents the characterization of some variable or construct of choice as a function of time. For example, one might be interested in the stability or changeability of SPD symptoms over time. SPD symptoms would then be assessed in a subject over time, and the data from the multiple assessments of that subject would be defined by a growth function as a function of time. Each subject in a sample has his or her own unique growth curve—that is why the word individual is used in IGC—and the components of this curve (see later discussion) can then be used as dependent variables that can be studied in detail. Finally, there are many times when, as experimental psychopathologists, we would like to actually do an experiment to isolate causal relationships and resolve important theoretical questions. However, as should be well understood, many of the experimental investigations that might actually be highly informative would be either infeasible, unethical, or both. For example, is being reared from birth by parents suffering from schizophrenia deleterious to children who do not carry a schizophrenia liability? Or, does exposure to hallucinogenic drugs in those who carry the liability for schizophrenia really push them toward psychosis at greater rates than if they were not so exposed? In the world of individual differences, in which disposi1 Having

baseline assessments for conditions, such as nonpsychotic Axis II schizophrenia-­related personality disorders, are essential if one intends to speak of change or development of a specified nonpsychotic outcome. This is so simply because if a schizotype was diagnosably SPD at baseline and was similarly diagnosed at follow-up, then one cannot really speak of change or outcome per se.

300

SCHIZOTYPY VIEWED FROM THE LABORATORY

tions, latent liabilities, and the like are assigned to humans by nature, true experimentation is simply not possible. Nonetheless, there are interesting questions on which we can gain some leverage, and one of the most powerful levers in our toolbox is time.

Development of Schizophrenia among Those Harboring Schizotypy Psychopathologists have long been interested in schizophrenia over time. Classic studies in the area include Manfred Bleuler’s (Eugen Bleuler’s son) original follow-up study, as well as the well-known study of Harding, Brooks, Ashikaga, Strauss, and Breier (1987) to name but two. In these studies, individuals affected by schizophrenia were studied after the passage of time, and the investigators sought to understand what happened to them. By “what happened,” we mean long-term outcome in terms of psychiatric status, occupational functioning, and social functioning. Moreover, many investigators who followed schizophrenia patients over time sought to characterize the course that the illness took as patients aged. Namely, did patients stay consistently psychotic, did they move in and out of psychosis over time, and/ or did they improve, even recover? For example, Bleuler (1978) reported that 22% of his schizophrenia sample recovered over time, whereas 22% had severe end state impairments; his data were, by and large, confirmed in a recent reanalysis (Modstein, Huber, Satirli, Malti, & Hell, 2003) that reported 12–15% recovery and 28% severe end states. Harding et al. (1987), in the landmark Vermont Follow-up Study, reported that 45% of their subjects had no schizophrenia symptoms at the time of follow-up. The most important findings from these are (1) even if a rigorous, narrow definition of schizophrenia is used (e.g., DSM-III, DSM-IV, Research Diagnostic Criteria [RDC]) the course and outcome of the illness is heterogeneous (i.e., it varies), and (2) the proportion of schizophrenia-­affected persons who continue on to severely impaired end states is relatively low. These findings are important to keep in mind as we ponder the course of schizotypy manifestations over time. Accordingly, we should anticipate a heterogeneous course and outcome and that only a small proportion of schizotypy-­affected cases will go on to full-blown schizophrenia. Given the importance in understanding developmental outcomes of schizotypic psychopathology, we begin with the striking realization that there simply is not a great deal of information available on the longitudinal outcome of well-­characterized schizotypic subject samples. What is



The Schizotype through Time . . .

301

particularly evident, for those follow-ups that do exist, is that the methods used by experimental psychopathologists for decades (e.g., assessments of attentional, cognitive, memory, and psychophysiological processes) have only rarely been incorporated into the empirical studies. Unlike the studies carried out within the genetic high-risk research paradigm (e.g., Cornblatt & Erlenmeyer-­Kimling, 1985), which have incorporated such laboratory methods in the prospective study of the offspring of schizophrenia patients, there are essentially no completed studies that have used laboratory methods to augment prediction of clinical course in schizotypy.

The Clinical Approach: Follow-Up Study of Diagnosed Schizotypic Psychopathology There have been few studies of clinical diagnostic outcome in clinically identified schizotypic psychopathology. The first study of significance was done by the late psychiatrist Wayne Fenton and the psychoanalyst Thomas McGlashan (1989), who used the incredibly rich medical chart systems at the exclusive Washington-area psychiatric hospital known as Chestnut Lodge. Among 105 former Chestnut Lodge patients with personality disorders, Fenton and McGlashan found that after the passage of 15 years, 4 of the 18 (or 13%) people who developed DSM-III schizophrenia during the follow-up period were initially diagnosed with DSM-III SPD. Thus, looking backward from schizophrenia cases, one finds some evidence of early SPD in the cases. These investigators explored these data closely, and they did something very useful. They expanded slightly the boundaries of the SPD definition to see whether it helped to illuminate further the question of SPD as a precursor to schizophrenia. They noted that if the diagnostic threshold for SPD at admission was relaxed from four to three criteria met, then 12 of the 18 cases of schizophrenia found at follow-up (or 40%) were among these “probable + definite” SPD cases. This was an important finding linking SPD to later schizophrenia. It showed a temporal relation between the two conditions. Importantly, their data also showed that not all individuals who develop schizophrenia would necessarily show SPD before the onset of psychosis. Sula Wolff, regarded widely as one of the founders of child psychiatry in Britain, has focused extensively on the issue of schizoid children and their developmental life course (Wolff, 1995). Wolff, Townshend, McGuire, and Weeks (1991) pursued the question of outcome in schizotypes in a prospective or “looking forward” manner. They began with children who displayed some variant of clinically diagnosable schizotypic psychopathology, what

302

SCHIZOTYPY VIEWED FROM THE LABORATORY

they termed schizoid. Such children were characterized by their “solitariness, unusual fantasies, [and] special interests” (Wolff et al., 1991, p. 629), and they were considered to be diagnostically distinct from Asperger syndrome.2 These children grew up to be adults, and their adult psychiatric status was assessed. Wolff and colleagues (1991) found that, among 32 children diagnosed as “schizoid” in childhood, two developed schizophrenia as adults. A fascinating finding was that 75% of these children at follow-up were considered to be showing DSM-III SPD as adults. The Wolff et al. (1991) study again demonstrates an important fact with respect to schizotypic psychopathology, namely that what is detectable in childhood as schizoid psychopathology may lead to schizophrenia, but not necessarily so. The continuity of childhood schizoid psychopathology and adult SPD provides a long-term window on longitudinal stability of schizotypic psychopathology as well. In another study that began with individuals with schizotypic psychopathology—that is, SPD—a similar pattern emerged in the follow-up data. Nordentoft et al. (2006) reported that during a 2-year follow-up period that did include treatment (i.e., medication), 23 of 65 individuals diagnosed with International Classification of Diseases (ICD-10) SPD did develop psychotic illnesses—some presumably with schizophrenia. Although this subsample of schizotypal patients, recruited from hospital settings, was not formally identified as a “prodromal schizophrenia” sample, the overall study was focused on an early intervention program in the model of many prodromal/ intervention studies. Thus the subsample of schizotypal patients may have been more severely affected from the start of the study, thereby increasing risk for psychosis. In a smaller scale study of 10 children diagnosed with schizotypal personality disorder, Joan Asarnow, the UCLA developmental psychopathologist, found that after a period of 3 years following the initial intake diagnosis, 1 of the children (10%) developed a full-blown case of schizophrenia, whereas 5 of the children (50%) remained diagnosed as schizotypal (Asarnow, 2005). These three prospective studies indeed show that schizophrenia does emerge over time in individuals initially diagnosed with schizotypic psychopathology (typically SPD), but this outcome represents only a subset of the subjects followed. Importantly, these studies also support the continuity of schizotypic psychopathology in childhood with later 2 Asperger

syndrome (see Wing, 1981) is a childhood disorder marked by severe impairments in social reciprocity (e.g., eye-to-eye gaze, facial expression, body gestures) and communication skills despite having intact, normal-range intelligence, as well as the presence of restricted repetitive and stereotyped patterns of interest, behavior, or activity (e.g., hand or finger flapping; see American Psychiatric Association, 1994).



The Schizotype through Time . . .

303

schizotypic psychopathology in development. Finally, an additional empirical perspective on this issue comes to us via an unusual route, namely from the psychiatric screening procedures in place with the Israeli Defense Force. In another “looking backward”—or retrospective—study, Weiser et al. (2001) found, in an investigation of young people excluded from military service in Israel, that 7 of 149 adolescents hospitalized for schizophrenia had either PPD, SPD, or both prior to their psychotic illness. The overall thrust, it seems, from these studies is that the vast majority of individuals clinically diagnosed with SPD do not go on to develop a schizophrenic illness. In fact, it appears that most schizotypal individuals remain schizotypal in personality presentation over time. Nonetheless, the fact that some schizotypal individuals do go on to schizophrenia provides an important link in the schizotypal–­schizophrenia chain, which is underpinned by the latent construct schizotypy. These data also highlight the important finding that not all those people who go on to have schizophrenia had clinically diagnosed SPD prior to their schizophrenic illness.3 Thus schizotypal signs and symptoms are not to be considered uniformly to be prodromal signs of schizophrenia, although that may be true in some subset of cases.

Decompensating Schizotypy: An Alternative “Clinical” Approach Using the Prodromal (“Ultra-High-Risk”) Research Paradigm and the “Conversion” to Psychosis Whereas the clinical approach to risk research described previously begins with individuals who are clearly nonpsychotic and are not typically viewed as being on the doorstep of psychosis, the so-­called “prodromal” or “ultrahigh-risk” approach to the study of people en route to schizophrenia focuses on those persons considered close to psychosis who are studied over time. The “prodrome” or “prodromal period” is thought of as that period occurring just prior to the onset of clinical psychosis (Cornblatt, Lencz, & Obuchowski, 2002). In considering the “ultra-high-risk paradigm,” it is essential to understand that the study of prodromal schizophrenia (emerging psychosis) is not to be considered to be isomorphic with the study of phenotypically unexpressed 3 The

Fenton and McGlashan (1989) and Weiser et al. (2001) data underscore an important conceptual feature with respect to Meehl’s (1962, 1990) model. Some researchers and clinicians have misunderstood the model to suggest that all those en route to clinical schizophrenia must appear clinically schizotypal personality disordered prior to the psychotic illness. One need not pass through a schizotypal phase on the way to schizophrenia. Meehl’s (1962, 1990) model does not maintain this, nor do the empirical data support it. Some may have confused the term schizotypy with schizotypal personality disorder, in which the former is a latent, nonobservable construct and the latter is a visible, clinically detectable diagnostic entity.

304

SCHIZOTYPY VIEWED FROM THE LABORATORY

schizotypy per se, that is, cases in which the schizotype is nonpsychotic and not likely to be showing any signs and symptoms of impending psychosis. The “prodromal symptoms” and “prodromal period” concepts are not new; rather, they have a long history in descriptive psychopathology of schizophrenia and psychosis. For example, Anton Boisen (1936), Harry Stack Sullivan (1962), Malcom Bowers (1974), John Weir Perry (1976) and others have provided highly detailed accounts of the emerging “prodromal” symptom picture as psychosis unfolds from both the patient’s and the clinician’s perspective. Personal accounts of emerging psychoses, including schizophrenia, can be found in Kaplan (1974).4 Thus contemporary researchers and clinicians with an interest in the prodrome have built on these early descriptive accounts by extending them to a prospective/ predictive framework for short-term forecasting of psychosis. Researchers interested in prodromal research represent a confluence of two streams of thought. One group of contributors has come principally from the world of clinical psychiatry (McGorry et al., 1996) and those clinician-­scholars interested in early intervention and treatment of those at risk for psychosis, typically schizophrenia (e.g., Patrick McGorry, Thomas McGlashan). The other group of prodrome researchers comes from the more laboratory-based experimental psychopathology/high-risk research perspective (e.g., Barbara A. Cornblatt, Tyrone D. Cannon). The clinical features typically associated with the “prodromal” state or stage, which can last from a few weeks to a couple of years, consist of things such as attenuated positive symptoms (e.g., ideas of reference, paranoid ideation, odd appearance) or transient psychotic symptoms that have resolved within a week. From the standpoint of Meehl’s model of schizotypy (Meehl, 1962, 1990; see also Lenzenweger, 2006c), the individual who is described as “prodromal” is someone who should be considered as a “symptomatic schizotype” or a “decompensating schizotype.” Conceptually, therefore, one should remember that the individual who is in the schizophrenia prodrome is, by definition, a schizotype (albeit decompensating); however, only a small fraction of genuine schizotypes move on to the prodromal stage and eventually schizophrenias. Variation in the goals and tactics of those prodrome researchers interested in early intervention versus those prodrome researchers interested principally in accurate detection and refinement of scientific methods for doing so can be considerable. Accordingly, the world of “prodromal research” has 4 Mark Vonnegut, son of the late writer Kurt Vonnegut, provides a highly lucid account of an emerging affective psychosis (not schizophrenia) in his autobiographical The Eden Express (Vonnegut, 1975). After his psychosis resolved, he attended Harvard Medical School and is now a practicing pediatrician in Massachusetts.



The Schizotype through Time . . .

305

been characterized by lively debate on a number of issues, particularly the ethics of using powerful antipsychotic medications in young people who are, by definition, not psychotic5 in an effort to stave off or prevent psychosis. One of the major problems facing this emerging area of inquiry concerns the definition of the prodrome and what constitute the agreed-on prodromal signs and symptoms. Although some common ground has been found across researchers (Cannon, Cornblatt, & McGorry, 2007; McGlashan et al., 2007), the core construct of the “prodrome” remains in need of critical analysis and refinement (see Schultze-­Lutter, Ruhrmann, Berning, Maier, & Klosterkötter, 2008). For example, most prodromal research tends to focus either on attenuated positive psychotic symptoms that suggest that the emergence of psychosis is imminent or on brief intermittent psychotic episodes as precursors to full-blown psychosis (see McGlashan et al., 2007). An alternative approach to determining at-risk status could focus on more basic, albeit subtle, indicators of underlying liability for psychosis (typically schizophrenia), such as disturbances in thought and speech or disturbances in perception not visible to the naked eye (cf., Schultze-­Lutter, Ruhrmann, Berning, Maier, & Klosterkötter, 2010; Parnas, 2005). This latter perspective is embodied more fully in the laboratory approach to risk research and schizotypy. What are the major findings in prodromal research? The so-­called conversion rate—or that rate at which putative prodromal subjects develop a full-blown psychosis—has been a central concept in the area. As detailed by Cannon et al. (2007), early prodromal studies suggested that somewhere between 40 and 60% of study samples went on to psychosis within a year of identification as prodromal, whereas contemporary studies reveal conversion rates between 20 and 35%. The discrepancy in these rates may reflect (1) earlier studies using a more lax definition of psychosis, (2) contemporary studies enrolling prodromal subjects earlier in the prodromal/ risk period and having greater exposure to treatment, or (3) both. However, the reason for the decline in conversion rates from the early to the more contemporary studies is not understood in any definitive manner. What are the major prodromal features that are predictive of psychosis? Perhaps 5 The

ethical challenges facing those wishing to implement early intervention in nonpsychotic, prodromal youths using antipsychotic medications are complex and beyond the scope of this volume. The issue of early intervention finds itself in the gray area of medical ethics, with no party able to claim the ethical high ground. Moreover, the ethical debate is subject to the nontrivial forces embodied in the pharmaceutical industry and the desire to design, market, and profit from an “early intervention” medication. See a special issue of the journal Schizophrenia Research (2001, Volume 51, Issue 1, August) for extended discussion of this important topic; see also Corcoran, Malaspina, and Hercher (2005) and Haroun, Dunn, Haroun, and Cadenhead (2006).

306

SCHIZOTYPY VIEWED FROM THE LABORATORY

the best data on this issue come from the North American Prodrome Longitudinal Study (NAPLS; Cannon et al., 2008), a study in which 35% of the subjects became psychotic after a 2½-year period. Cannon et al. (2008) reported on five major predictors of conversion to psychosis: genetic risk for schizophrenia (i.e., psychosis in a first-­degree relative with functional decline), unusual thought content, suspicion/paranoia, social impairment, and a positive history for substance abuse. This set of five predictors covers the full range of domains of potential relevance: genetic liability, positive symptoms, negative symptoms, and environmental risk (drug abuse). Each of these five predictors, taken in univariate fashion (i.e., one at a time), was a significant predictor of conversion, with all having broadly comparable hazard ratios. Unsurprisingly, genetic risk was the factor associated with the highest positive predictive value for conversion to psychosis. But, the student might wonder, what would happen if all five of these predictors were entered into a prediction equation in simultaneous fashion, in order to sort out which works best? What is particularly interesting is that each one of these five predictors actually makes a statistically significant contribution to the prediction of conversion in a simultaneous regression (Dr. Tyrone D. Cannon, personal communication, July 1, 2008), with genetic risk producing the highest hazard ratio6 of the five predictors. None of the predictors falls out of the analysis! This feature of the NAPLS data argues for continued exploration to discover what the mechanism of action would be for each. The clinical features predictive of conversion to psychosis in the Cannon et al. (2008) report were all assessed using an interview (rating) approach. What if different phenomenological features would emerge in such a prediction problem if a self-­report assessment were used? One might make the case that in a self-­report situation, prodromal subjects might be somewhat more disclosing. Fortunately, there is an approximate answer to this empirical question. Using a self-­report assessment of prodromal features, the positive symptom-like reality distortion features are those that best predict prodromal/psychotic status (e.g., Loewy, Bearden, Johnson, Raine, & Cannon, 2005). Holding aside the predictive power of a positive family history of schizophrenia—which should, obviously, be a powerful predictor of psychosis—it appears that the more positive symptom-like 6 Hazard

ratio is a statistical concept hailing from the analytic method called survival analysis. It is the ratio of the hazard rates over time for each group in a study or the relative likelihood of experiencing an event. In the NAPLS study the hazard rates being compared are those subjects who converted to psychosis versus those who remained nonpsychotic for variables of interest. A hazard ratio is a version of the relative risk statistic. Thus, if cigarette smokers have a 30% rate of developing lung cancer, whereas nonsmokers have a 1% risk, then cigarette smoking would have a relative risk of 30. A hazard ratio says essentially the same thing (see Singer & Willett, 2003; Kay, 2004).



The Schizotype through Time . . .

307

features of the prodrome are particularly effective in predicting conversion to psychosis over the relatively short time spans covered by the NAPLS and similar prodromal studies. The prodromal research approach, as noted, has built on the early clinical observations that certain signs and symptoms were detected by observers and/or reported by patients prior to the emergence of frank psychosis. As noted, some contemporary prodromal research workers are interested in this approach, as they see it largely as an entry point at which clinical intervention might be appropriate (possibly fostering secondary prevention7), although the ethics of such intervention remain an area of considerable and justified debate. Other prodromal researchers are interested in the predictors of conversion from more of an etiological/pathogenesis perspective, as an understanding of the predictors could foster basic advances in our understanding of the emergence of psychosis (as well as absence of psychosis). Moreover, a good portion of this discussion of prodromal research has used the term psychosis rather than schizophrenia, and this terminological ambiguity is reflective of the prodromal research literature generally. The outcomes seen in the short-term longitudinal study of many prodromal cases are not just schizophrenia per se; rather, outcomes include schizoaffective illness, manic-­depressive (bipolar) illness, and psychotic unipolar depression. Thus for the most part the prodromal features that are assessed in these “ultra high-risk” research subjects are nonspecific with respect to schizophrenia. This is an issue that is widely recognized by prodromal researchers (Cannon et al., 2008). One could argue that it is not only schizophrenia that matters as regards outcome, and from the clinical perspective that is indeed true. However, from the standpoint of schizotypy and schizophrenia, the resolution of prodromal features having appreciable specific predictive power for schizophrenia and schizophrenia-­spectrum outcomes should represent a research priority. Recall that one of our conceptual tools is the notion of specific etiology (Meehl, 1972b), and that is what we seek in prodromal research cases—­information relevant to specific etiology for schizophrenia. Another feature of the prodromal research efforts worthy of note, not unlike the follow-up studies of clinically diagnosed schizotypal and/or schizoid individuals, is that the vast majority of those individuals classified as “prodromal,” in fact, do not go on to develop schizophrenia or, more 7 Prevention

efforts are normally referred to as primary, secondary, or tertiary. Primary prevention refers to application of some treatment to all persons in an effort to prevent the expression of pathology (i.e., efforts applied to all persons in the population to prevent disease). Secondary prevention refers to application of some treatment to those persons thought to be specifically at risk for an illness (i.e., early disease detection). Tertiary prevention refers to the application of treatment to expressed illness (i.e., clinical treatment of expressed disease).

308

SCHIZOTYPY VIEWED FROM THE LABORATORY

broadly, psychosis. The reasons for this could include the relatively brief follow-up periods used in most prodromal studies (i.e., with longer followups, perhaps more cases would convert to psychosis) or the poor sensitivity of some prodromal signs and symptoms. It is also the case, as noted earlier, that schizotypal personality signs and symptoms should not be considered uniformly to represent prodromal signs and symptoms; only a subset of schizotypal-­appearing cases may really be prodromal cases, whereas the others might represent a more enduring schizotypal personality configuration (not necessarily en route to schizophrenia). Clearly, the length of follow-ups can be increased, and the predictive efficiency of certain prodromal signs and symptoms could be established more effectively. In the case of most prodromal research, ratings approaches are used, and, given the concerns regarding ratings discussed earlier, it is suggested that prodromal research protocols would do well to include more ratio scale-based laboratory measures of psychological processes underpinning prodromal constructs of interest.8 Parnas (2005) has argued that the current approaches to rating signs and symptoms of the prodrome are insufficient, as they do little to incorporate other important features of emerging psychosis, such as anomalous self­experience. Interestingly, a focus on self-­experience would be a reasonable approach given what is known about the unusual and pathological experience of self during the emergence of psychosis (see Boisen, 1936; Perry, 1976; Bowers, 1974; Sullivan, 1962, for rich examples) as well as the considerable research corpus supporting the PAS, which has a prominent body image distortion component, as a measure of schizotypy. Finally, the fact that any number of subjects initially identified as prodromal on the basis of signs, symptoms, and background variables remain nonpsychotic is consistent with Meehl’s model of schizotypy, which holds a large proportion of schizotypes will remain compensated (nonpsychotic) over the life span.

Study of Individuals Genetically at Risk for Schizophrenia: “Long-Range” Schizotypy Forecasting Another approach to defining schizotypes can be referred to as the genetic or family approach, whereby individuals thought to be at increased biological risk for schizophrenia (but who are nonpsychotic) can be designated as an experimental group to be contrasted with controls (i.e., persons without a biological relative afflicted with schizophrenia). Although there currently 8 The

NAPLS study has utilized a limited number of laboratory-based measures of neurocognitive function, but the data for these measures have not been published yet (B. Cornblatt, personal communication, July 2, 2008).



The Schizotype through Time . . .

309

exists no genetic test for specific schizophrenia liability, increased risk for the illness can be approximated by considering those people who are first­degree biological relatives of individuals affected with clinical schizophrenia. The rough and ready estimate of risk for schizophrenia if one has a schizophrenia-­affected first-­degree relative is about 10%—that is, one has a 1 in 10 chance of developing schizophrenia with this biological/genetic background. Application of such expectancies in the design of studies for high-risk populations was originally proposed in a brilliant 1957 paper by two scholars, John Pearson and Irene Kley, who were at the former Rochester State Hospital in Rochester, Minnesota.9 Therein lies the straightforward idea of the genetic high-risk study for schizophrenia. It is nonetheless useful to review the basic outline of a genetic high-risk study in greater detail. First, one assembles a high-risk subject group (i.e., offspring of schizophrenia-­affected parents), a psychiatric control group (offspring of affective-­disorder-­affected parents), and a normal control group (children without any schizophrenia in their biological relatives).10 These children then serve as the core subjects to be followed longitudinally (over time) for what could be termed long-range schizophrenia forecasting. Second, one carefully assesses these children on a variety of psychological, biological, and other parameters over time at meaningful intervals. Third, the subjects are followed through the risk period for schizophrenia, and the appearance of psychopathology of any sort is assessed. When one considers undertaking a study—a really long-term study—of the sort implied in high-risk research, then one is looking at decades of research commitment. The children need to grow up to adulthood, traversing the period of risk for schizophrenia, normally ending at about age 50 or so. This sort of study requires a lifetime of commitment from the investigators as well; thus there are only a few of these high-risk studies that have remained active and productive with the passage of decades.11 However, despite their small 9 The

Pearson and Kley (1957) paper is interesting, as it clearly laid out the rationale for the high-risk study based on what the authors termed “genetic expectancies.” However, the paper has been only minimally cited over the years.

10 The

selection of children for such a study is really quite complicated and rife with challenging sampling and methodological considerations. Consider one sampling matter—the issue of “cohort effects.” A cohort effect refers to the impact of shared temporal or cultural experience on psychological or social development. Children growing up in the Great Depression (roughly 1929–1939) in the United States had a distinctly different experience from those growing up in the period from 1962– 1972, or “the sixties.” Thus, in selecting children for a long-range schizophrenia project, one should consider the potential impact of cohort effects on the assembled samples. For example, consider the impact of selection of subjects during the recent global economic crisis, beginning in 2008. 11 A

rich compendium of older high-risk research in schizophrenia is Watt, Anthony, Wynne, and Rolf (1984).

310

SCHIZOTYPY VIEWED FROM THE LABORATORY

number, they represent a gold mine of data relevant to the development of schizophrenia across the life span. The high-risk studies done to date have been divided into “first-­generation” and “second-­generation” studies, with the first-­generation studies begun in the 1960s and 1970s and the second­generation studies begun as of the mid-1990s (Cornblatt & Obuchowski, 1997). High-risk studies have also contributed to the understanding of the natural course of schizotypes.

The New York High-Risk Project: A Landmark First-­Generation Study The landmark New York High-Risk Project (NYHRP), conceived of and directed by the geneticist and psychopathologist Nikki Erlenmeyer-­Kimling at the renowned New York State Psychiatric Institute, stands out as an exceptional first-­generation study and has provided the most comprehensive view of the long-term clinical outcome of such cases over a 25-year follow-up (Erlenmeyer-­Kimling et al., 1997, Erlenmeyer-­Kimling et al., 2000; Erlenmeyer-­Kimling, Roberts, & Rock, 2004). In the NYHRP, two groups of children, sample A and sample B, were followed over time. Each of the samples contained children born to a schizophrenia-­affected parent, an affective-­illness-­affected parent, or normal parents. The children were studied carefully over many years on a variety of clinical (Axis I and Axis II disorders), neurological, laboratory (e.g., sustained attention), and other measures. The ultimate goal was to determine what might be the predictors of schizophrenia in the children across all three subject groups in both samples (Erlenmeyer-­Kimling et al., 2000). The key NYHRP finding was that definite schizophrenia was seen only among children at risk for schizophrenia (target subjects and siblings combined) and characterized 13% of those children, whereas definite schizophrenia was not observed among the contrast samples that consisted of children at risk for affective illness or normal controls. Even in this enriched sample of children at risk for schizophrenia (enriched in that children are at statistically higher risk for the illness), only a subset of such children develop schizophrenia. The remainder of the children at risk for schizophrenia displayed a variety of features, with some displaying schizophrenia-­related personality disorder features (see Squires-­Wheeler, Skodol, Bassett, & Erlenmeyer-­Kimling, 1989). The NYHRP has generated other insights into the developmental predictors of schizophrenia and schizophrenia-­related behavioral disturbance. Several important findings have emerged from the NYHRP. First, and what could be viewed as perhaps one of the most important early findings, it was



The Schizotype through Time . . .

311

found that severe behavioral disturbance during the late teens was strongly predicted by deviance in attention functioning at an early age (Cornblatt & Erlenmeyer-­Kimling, 1985). A substantial proportion of those children with what was termed global attentional deviance were found among the children at high risk for schizophrenia (Cornblatt & Erlenmeyer-­Kimling, 1985). This proportion exceeded rates for attentional deviance found in the normal children or those at risk for affective disorder. The clue as to attentional dysfunction as a potent predictor of psychotic outcome was confirmed later in analyses of the combined NYHRP sample (Samples A and B combined; Erlenmeyer-­Kimling et al., 2000; Erlenmeyer-­Kimling et al., 2004). Attentional deviance, memory functioning, and gross motor skills all emerged as significant mediating variables lying between a familial liability for schizophrenia and the final clinical outcomes of schizophrenia-­related psychoses in the NYHRP. Moreover, beyond the prediction of schizophrenia and schizophrenia­related psychoses (Erlenmeyer-­Kimling et al., 1998; Erlenmeyer-­Kimling et al., 2000), the NYRHP found that among those children at high risk for schizophrenia who were not psychotic at 25-year follow-up, one sees high levels of interpersonal indifference and detachment (Cornblatt et al., 1992). Importantly, Cornblatt et al. (1992) reported that childhood attentional difficulties predicted, in those subjects who were nonpsychotic, a relative insensitivity to other individuals, an indifference to their feelings, and avoidance of interpersonal interactions whenever possible. Finally, additional analysis of the entire NYHRP dataset (samples A and B) revealed that attentional deviance in childhood predicted a personality style characterized by suspicion and solitude in early adulthood (Freedman, Rock, Roberts, Cornblatt, & Erlenmeyer-­Kimling, 1998). These findings, as well as the results from other high-risk studies (see Watt, Anthony, Wynne, & Rolf, 1984), helped to establish that attentional deviance was a valid neurocognitive marker of schizophrenia liability. They also highlighted the utility of the laboratory approach to measurement of subtle psychological processes in subjects who were years away from behavioral disturbance.

The Edinburgh High-Risk Study: A Second-­Generation Study Viewpoint An example of a promising second-­generation high-risk project that is also based on the notion of genetic expectancies is the Edinburgh High-Risk Study (EHRS), begun in 1994 under the direction of the British psychiatrist Eve Johnstone (Johnstone et al., 2000; Johnstone, Ebmeier, Miller, Owens,

312

SCHIZOTYPY VIEWED FROM THE LABORATORY

& Laurie, 2005). The EHRS began with an adolescent–young adult sample (ages 16–24 years), who were psychiatrically healthy (nonpsychotic), and who had at least two first-­degree or second-­degree biological relatives with diagnosed schizophrenia. Johnstone and colleagues began their study with 193 young people meeting these criteria. The study also included two contrast groups, a normal control (n = 36) sample, and a psychiatric control sample consisting of young people in their first episode of schizophrenia (but who had no familial evidence of the disorder). The subjects were recruited for the study between 1994 and 1999, with detailed results provided as of mid-July 2003. Within the first 8 years of the study, 20 of the high-risk subjects had developed schizophrenia, whereas none of the normal controls developed the disorder. Importantly, the 20 subjects that fell ill (developed schizophrenia) differed at baseline from the control subjects, high-risk subjects without symptoms, and high-risk subjects with symptoms (psychotic but nonschizophrenic) on schizotypic features, particularly social isolation, as well as schizotypal cognitions. This is particularly remarkable given that among the 20 subjects who developed schizophrenia during the initial 8 years of the EHRS, 45% revealed no evidence of psychotic-like phenomenology at baseline. However, as Johnstone et al. (2005) note, many of the high-risk subjects who did not fall ill also showed elevations on schizotypal phenomenology dimensions at baseline. Thus, although schizotypic features were highly discriminating in terms of separating those subjects who became ill from those who did not, not all those at risk (even with elevated schizotypic features) developed schizophrenia. By implication, therefore, only a subset of those subjects with elevated baseline schizotypic features went on to schizophrenia.

The Laboratory Approach: Follow-Up Study of At-Risk Subjects as Defined by Psychometric Measures Unlike the clinical and genetic (family) high-risk methods for assembling a study sample, the laboratory index method represents an approach to assembling a high-risk sample that does not rely on ratings of schizotypic symptomatology (e.g., SPD) or the approximated probability of developing schizophrenia as a function of having the illness among one’s biological relatives. One could argue that the clinical approach to the longitudinal study of schizotypy is focused more on partially expressed schizotypes (e.g., SPD) or partially decompensated schizotypes (i.e., prodromal schizophrenia). Thus the clinical approach is really wed to the study of partially symp-



The Schizotype through Time . . .

313

tomatic conditions. Unlike the clinical approach, the laboratory approach seeks to dig a bit deeper into the realm of schizotypy and seeks to tap the construct in those persons who are far from being fully diagnosable as having SPD and who are clearly not on the doorstep of psychosis, as in the prodromal states. Because the laboratory approach is more focused on measurement and detection of the latent construct of schizotypy, it encompasses potentially symptomatic conditions, as well as the range of nonsymptomatic variants of schizotypy. The logic of the laboratory high-risk method is relatively straightforward. Namely, one begins with an indicator of the latent construct schizotypy—it could be psychometric, neurocognitive, or neurobiological, for instance—and that indicator is used as the tool for selecting individuals deemed at risk for schizophrenia, as well as a contrast group of those not at risk for the illness. The risk or presence of schizotypy is defined as quantitative deviance on the selection measure of choice. There are no hard and fast rules as to what constitutes deviance, and the cut score defining deviance, therefore, is up to the discretion of the investigator. The convention has been to consider those subjects who score 2 standard deviations (SD) above a group mean as at risk (or schizotypy positive). The normal or contrast group selected on the basis of the same measure is normally made up of persons who score no higher than ½ SD above the same group mean. Thus this method is referred to generically, by some, as consistent with the extreme-­groups approach, and it has been the focus of a number of methodological discussions (Feldt, 1961; Rosenthal & Rosnow, 1991; Preacher, Rucker, MacCallum, & Nicewander, 2005).12 However, the schizotypy research design described earlier is not a typical extreme-­groups approach design (Feldt, 1961; Preacher et al., 2005) in that deviantly low scorers are intentionally chosen for study. There are other ways to define deviance, of course, for the purposes of laboratory index-based high-risk research. One can define risk in the laboratory approach using percentile cut scores; thus the at-risk group might be defined as the most deviant 10% or most deviant 25% of a sample, whereas normal controls can be defined as those subjects in the least deviant 10 or 25%. Regardless of the precise cut scores used, what should be evident is that selection is made a priori on the basis of a quantitative indicator and the resulting samples represent groups of people that are quite different, by definition, on the indicator (i.e., there is considerable separation 12 The

expression extreme groups does not convey a value judgment or implicit criticism. Rather, it merely denotes that two study groups have been selected to be considerably different on some measure or metric of choice.

314

SCHIZOTYPY VIEWED FROM THE LABORATORY

between them on the selection construct). The laboratory index13 method for assembling subject groups for high-risk study, typically referred to as the psychometric high-risk approach, has been discussed in the literature (see Chapman, Chapman, & Raulin, 1976; Chapman & Chapman, 1978; Lenzenweger & Korfine, 1992b; Lenzenweger, 1994; Gooding, Tallent, & Matts, 2005).

Follow-Up of Schizotypic Subjects Initially Identified with Laboratory Methods: The Chapmans’ 10-Year Follow-Up A landmark laboratory risk study was carried out by the University of Wisconsin psychopathologists Loren J. Chapman and Jean P. Chapman (Chapman, Chapman, Kwapil, Eckblad, & Zinser, 1994). The Chapmans were instrumental in creating during the late 1970s the psychometric measures used widely in assembling at-risk groups by operationalizing a number of the clinical schizotypic signs discussed by Meehl (1964) in his seminal “checklist.” Importantly, they began large-scale screenings using their measures (e.g., Perceptual Aberration, Magical Ideation, Social Anhedonia, Impulsive Nonconformity) in the late 1970s and early 1980s and planned to conduct a long-term clinical follow-up study of those subjects identified as “psychosis prone,”14 as well as those deemed to be normal controls. They studied 508 subjects, distributed across several at-risk groups and a control group, with the group identified by deviance on the Perceptual Aberration and/or Magical Ideation Scale of principal interest (n = 182). The normal control group consisted of 153 subjects who were not elevated on any of the selection scales. The Chapman team completed the herculean task of relocation and reassessment of these subjects with a stunning rate of cooperation of subjects (95% success rate; 508 of the original 534 were located and interviewed), which is particularly notable as this work was done prior to the dawn of the massive Internet and World Wide Web resources that are available today for such work. 13 Laboratory

methods for assembling high-risk samples are described as the behavioral high-risk paradigm (Miller, 1995), the behavioral paradigm for identifying persons at risk (Depue et al., 1981), or the biochemical high-risk paradigm (Buchsbaum, Coursey, & Murphy, 1972). 14 The

Chapmans initially referred to their various psychometric measures as assessing “schizophrenia proneness”; however, they later reconceptualized the construct as “psychosis proneness.” Given that their measures, in large part, were operationalizations of Meehl’s (1964) schizotypic signs, I have always viewed them as schizotypy indicators. The Chapmans’ description was linked more to presumed predisposition to a psychotic outcome, whereas my theoretical position concerns the latent construct that is putatively tapped by the measures.



The Schizotype through Time . . .

315

Let us consider what the Chapmans discovered in this seminal follow-up study. To begin with, of critical importance, they found at their 10-year follow-up assessments of the subjects that DSM-III schizophrenia and schizophrenia-­related psychopathology was concentrated primarily among those subjects who initially displayed deviantly high scores on the Perceptual Aberration and/or Magical Ideation Scales (Per–Mag). This is precisely what one would want to see in a study of individuals selected on the basis of a presumed schizophrenia-­related predisposition to psychosis. In fact, 5.5% of the Per–Mag subjects at the 10-year follow-up were psychotic; 3.3% were diagnosed with schizophrenia or Psychotic Disorder Not Otherwise Specified (NOS) “mainly schizophrenia” without functioning decline (Chapman, Chapman, Kwapil, et al., 1994, p. 175). Chapman, Chapman, Kwapil, et al. (1994) also found schizotypal, schizoid, and paranoid PD scores (i.e., dimensions of schizotypic psychopathology) to be elevated in the psychometric high-risk group versus normal controls at follow-up. This was a critical finding in that it spoke to the long-term stability of the schizotypic proclivity of the high-risk (Per–Mag) subjects. This is so as it was likely that some of the subjects who were initially assessed may have appeared schizotypic—even scored in the schizotypic range on the scales—­during their first-year in college but would not necessarily have remained so over time. Finding that the Per–Mag group remained significantly more schizotypic than the controls after 10–15 years of time passing suggested that schizotypy, as an enduring latent construct, was tapped and continued to exert its effects across the life course.

Appraisal and Meaning of the Chapmans’ Findings The Chapman, Chapman, Kwapil, et al. follow-up study is one of the most important studies in schizotypy completed in the past 20 years. It is also perhaps one of the most misunderstood studies in the field of schizotypy research. In presenting colloquia and grand rounds about the country, as well as dealing with comments from reviewers in connection with journal articles on the topic of schizotypy over the past 15 years, I have come across a variety of misconstruals, misunderstandings, and outright mistakes in the interpretation of the results of the Chapmans’ study. Allow me to detail these comments and dissect their meaning, or lack thereof (I am not making these questions up out of thin air—every one of these was put to me in an earnest fashion).

316

SCHIZOTYPY VIEWED FROM THE LABORATORY

•• Misunderstanding 1: “The Chapmans didn’t find anything in their study” or “The Chapman study was a bust.” I have always been rather hard pressed to know how to respond to this sort of iconoclastic statement. Normally this type of comment comes from a person who has not actually read the Chapman, Chapman, Kwapil, et al. (1994) report in its entirety, oftentimes being someone who merely skimmed the abstract or “heard about” the study from someone else. In the latter case, it is, of course, possible that the one making the comment was misinformed by a colleague. Nonetheless, I have typically responded by saying that it is difficult to know what to make of such a statement, given the rather impressive results that were found. I often attempt to find a gentle way to encourage the person to “reread” the report. Once in a while I also detect a perhaps guilt-­driven quality to such a proclamation about the Chapman, Chapman, Kwapil, et al. (1994) research, such that it may be coming from an individual highly enamored of the DSM system and simultaneously lacking in an appreciation for quantitative approaches to measurement and psychopathology research generally. The Chapman study was not a “bust”; rather, it yielded a spectacular array of important data that continue to shape schizotypy and schizophrenia research at all levels of analysis (e.g., molecular genetic level; see, e.g., Lin et al., 2005). •• Misunderstanding 2: “Weren’t all of the Chapman psychosis-prone subjects supposed to develop psychosis?” No. This sort of comment is a bit more innocuous and really just reflects a fundamental ignorance regarding the relationship between liability and emergence of clinical schizophrenia. It may be that the commenter has taken the name of the Chapman scales a bit too literally, assuming that if one is psychosis prone, then one should become psychotic. Clearly not all those at risk for schizophrenia develop the illness; typically, a reminder about concordance rates for schizophrenia in MZ twins suffices to drive home the substantive point. •• Misunderstanding 3: “The rate of schizophrenia is just too low in the Chapmans’ psychosis-prone subjects.” I am always very interested in this sort of comment, as it presumes some accurate a priori knowledge regarding the increase in risk for schizophrenia (psychosis) that accrues from being deviant on a quantitative schizotypy indicator. In other words, the commenter is playing something of the role of an “omniscient one” with respect to the increment in risk associated with schizotypy measures. Nobody knows exactly how much of an increase in risk for schizophrenia (or psychosis) goes along with having a deviantly high score on the Per–Mag scales, for example. It is safe to hypothesize that the risk should be increased above the normal, not-at-risk 1% level. Should it exceed that level of risk that is seen



The Schizotype through Time . . .

317

in the first-­degree biological relatives of someone affected with schizophrenia? Does it make sense to think that a psychometric measure detecting schizotypy could outperform the strength of genetic effects on risk for psychosis? Should it be lower than that rate? The short answer is that we do not know. Moreover, one must examine the entire corpus of results presented by the Chapman team when considering the rates of pathology seen in their sample. As noted by the University of North Carolina—­Greensboro psychopathologist Thomas R. Kwapil, “when multiple predictors were considered, the rate of psychosis increased dramatically [in at-risk subjects] (e.g., in the Chapman et al. [1994] study, 40% of participants identified by the combination of the Magical Ideation and Revised Social Anhedonia Scales, and who exhibited moderate psychotic-like experiences at the initial assessment met criteria for psychotic disorders at the follow-up assessment)” (T. R. Kwapil, personal communication, July 9, 2008). The whole idea of assessing schizotypy using such psychometric measures is to provide a reliable and efficient method for assessing risk—in theory. We do know that the information about and benefits to statistical power provided by a quantitative indicator of schizotypy—­assuming it is reliable and valid—can be rather substantial in, for example, genetics research (Smith & Mendell, 1974; see Brzustowicz et al., 1997; Fanous & Kendler, 2005, for empirical examples). In order to fully answer this sort of question, however, we would need information for the subjects in the Chapman study after they had fully traversed the risk period for schizophrenia (psychosis). Recalling that the risk period for schizophrenia runs up to, at least, 50 years of age, then it is not too difficult to see that college students assessed 10 years into their lives (late 20s on average) have a considerable amount of the risk period yet to navigate. •• Misunderstanding 4: “Why does the conversion rate in the Chapman study differ from that in prodromal studies?” It was not a prodromal schizophrenia study. This misunderstanding represents a fundamental confusion between prodromal schizophrenia research and schizotypy research. Prodromal schizophrenia research is focused on persons, already partially symptomatic, and on the road to psychosis in the relatively short term (e.g., 2- to 2½-year follow-ups). Schizotypy research as embodied in the Chapman and other psychometric high-risk studies seeks to tap the underlying construct responsible for schizophrenia (or, more broadly, psychosis) long before a person is anywhere near psychosis. They seek to tap latent liability and observe the long-term (i.e., decades) development of the schizotype (in all possible manifestations, ranging from full-blown psychosis through partially

318

SCHIZOTYPY VIEWED FROM THE LABORATORY

symptomatic state to subtle deviance on valid endophenotypic markers). So, the reader should remember two things: (1) The Chapman study and similar psychometric high-risk studies were (are) not prodromal schizophrenia studies and (2) whereas all prodromal schizophrenia cases represent an expression of latent schizotypy, not all those who harbor latent schizotypy will develop observable prodromal symptoms or clinical schizophrenia. Alternatively, consider those schizotypes studied in the psychometric highrisk approach as those persons on a ship potentially (but not necessarily) steaming toward schizophrenia, whereas prodromal schizophrenia cases are those persons who have fallen off the ship and are barely hanging on to the hull of the ship (those individuals afflicted with schizophrenia would be those unfortunate folks that have fallen completely overboard). In further addressing these sorts of misunderstandings, it is essential to review the Chapman, Chapman, Kwapil, et al. (1994) findings in a more fine-­grained manner to illustrate just what was really found in this gold mine of a study. Therefore, consider several core findings in the Chapmans’ 10-year follow-up study that are often underappreciated. First, the proportion of psychotic cases found among the Per–Mag group was 5 times higher than that observed among the controls. Second, for six of seven core predictions for clinical and functional outcomes, the Per–Mag subjects significantly exceeded the control group as predicted (e.g., higher rates of psychosis, higher levels of Cluster A Axis II schizotypic features, poorer global adjustment). Third, Kwapil, Miller, Zinser, Chapman, and Chapman (1997) found additional evidence supportive of the basic findings of the Chapmans by detecting expressed psychosis only among those subjects psychometrically identified as “at risk” for psychosis (i.e., 7% of at-risk subjects). Moreover, Gooding et al. (2005), in a 5-year follow-up study of psychometric high-risk subjects, found that the rate of schizophrenia spectrum personality disorders in a group of Per–Mag subjects was 5.08% versus 0% for the normal controls at follow-up.15 Gooding et al. (2005) also reported that the Per–Mag subjects showed higher levels of psychotic-like experiences than the controls. No cases of psychosis have emerged to date in the Gooding study; however, the study will continue for some time, and additional results will be forthcoming that should prove helpful in illuminating this area further. 15 Gooding

et al. (2005) did not conduct formal Axis II assessments on their subjects at study inception (i.e., baseline); thus it is not clear whether the schizophrenia spectrum personality disorders diagnosed at follow-up emerged over the 5-year time span or were already in place at baseline.



The Schizotype through Time . . .

319

What Were the Real Limitations of the Chapmans’ Follow-Up Study? The Chapman, Chapman, Kwapil, et al. (1994) study, despite its uncompromising rigor and overall excellence, was not without some limitations or shortcomings. But that is life in the laboratory—all studies could be improved, and no study is perfect. How was the Chapman study limited? What were its shortcomings? The primary shortcoming of the Chapmans’ study was that it lacked additional measures that might have helped to moderate (i.e., potentiate) the prediction of clinical and functional outcomes in their subjects. It did not, for example, include any laboratory-­assessed measures of biobehavioral or neurocognitive processes such as sustained attention or eye-­tracking dysfunction. The study relied solely on initial psychometric status in defining risk and prediction of later dysfunction. Secondarily, additional limitations of the Chapman study included: (1) a truncated assessment of Axis II symptoms (not all PDs were assessed at follow-up16), (2) a truncated assessment of Axis I conditions (not all major mental disorders on the DSM Axis I system were evaluated at follow-up, (3) little to no assessment of psychiatric treatment histories (it is always clinically and scientifically interesting to find out if someone sought out treatment and what sort of treatment they received) and (4) no assessment of life course trajectories.17

The Lenzenweger 18-Year Follow-Up Study of Schizotypy I have conducted a number of cross-­sectional studies of schizotypic subjects over the past 25 years. Several of the study samples were initially examined in the late 1980s and early 1990s. Each contained subjects assessed initially with the PAS. Thus, all studies consisted of subjects who were classified as either schizotypy-­positive or control subjects, selected such that the schizotypes were gathered from those individuals scoring 2 SDs or more above the group mean on the PAS and the normal controls were selected at random from among that portion of the distribution with scores no higher than ½ SD above the group mean. All of those subjects included in the stud16 For example, Fogelson et al. (2007) reported that “avoidant personality disorder” could be justifiably included as a schizophrenia-­related personality disorder; however, this personality disorder was not assessed in the Chapman et al. (1994) study. This was not known at the time the Chapman follow-up assessments were done. Moreover, one can only conduct just so many assessments with subjects during follow-up evaluations See also Gooding, Tallent, and Matts (2007). 17 At this time, there are no plans to reexamine the Chapman (Chapman, Chapman, Kwapil, et al., 1994) sample in an extended follow-up (L. J. Chapman, personal communication, July 7, 2008).

320

SCHIZOTYPY VIEWED FROM THE LABORATORY

ies were screened for the presence of any form of psychosis prior to being enrolled in the study; thus all subjects were nonpsychotic at study entry (overall sample approximately 180). Importantly, in addition to schizotypy status defined by the PAS, all subjects in the samples completed the Continuous Performance Test—­Identical Pairs versions (CPT-IP; Cornblatt et al., 1989; Lenzenweger, Cornblatt, & Putnick, 1991). Therefore, we can determine if performance on a neurocognitive indicator of schizophrenia liability moderates the prediction of outcomes at the 18-year follow-up. A preliminary analysis of these data strongly supports the PAS as an index of schizotypy by virtue of strong associations with elevated rates of diagnosed schizophrenia-­related psychopathology at follow-up. Finally, in the context of a discussion of the psychometric high-risk approach to schizophrenia development, it is noteworthy that Bolinskey, Trumbetta, Hanson, and Gottesman (in press) reported the results of a well-­conducted retrospective study supportive of this high-risk approach. These authors reported on MMPI indicators that, when measured in normal nonpsychotic adolescents, predicted later schizophrenia in adulthood, suggesting that psychometrically detectable (but phenotypically invisible) featues could function as endophenotypes for later diagnosed schizophreia.

Stability of the Schizotypic Features over Time Much of what we have been discussing concerns the clinical outcome seen in schizotypic subjects followed over time. The clinical outcome of interest has largely been the emergence of psychosis, specifically schizophrenia, schizophrenia-­related psychoses, and schizophrenia-­related PDs (e.g., SPD). However, there is another perspective on the question of longitudinal course in schizotypy. That perspective views schizotypic psychopathology from the standpoint of stability over time. It is assumed that the liability for schizophrenia—that is, schizotypy—is thought of as an enduring and trait-like latent disposition within the person. This latent liability can express itself across a range of outcomes, as per Meehl’s (1990) model, with some individuals moving on to clinical psychosis, whereas others reflect a range of clinical outcomes, from essentially nonsymptomatic (displaying deviance only on endophenotypes) to schizotypal symptomatology that can be assessed clinically (e.g., SPD and PPD symptoms). A further implicit assumption in this discussion is that a person who carries schizotypy (but does not move into clinical psychosis and appears schizotypic at the level of phenomenol-



The Schizotype through Time . . .

321

ogy) should appear rather schizotypic across the life span. The schizotypic features that hail from schizotypy should be consistently visible over time; they should be stable from a longitudinal perspective. This view is embodied in the official view of PDs in the DSM system.18 One of the cardinal assumptions, and perhaps most important, concerning the PDs is that they are enduring trait-like conditions and relatively stable over time (American Psychiatric Association, 1980, 1987, 1994).

Schizotypic Personality Pathology over the Short Term: Test–­Retest Studies Schizotypal personality disorder symptoms are reasonably consistent over relatively short test–­retest periods (Loranger et al., 1991; Loranger et al., 1994; see also McDavid & Pilkonis, 1996). Thus, over a period of a few weeks to two months, individuals displaying SPD or PPD symptoms are likely to continue to display them consistently. This makes good sense, as the time frame is short and one would not expect a great deal of development or change to occur during such a short period. This is important information as well for diagnostic instruments, and, typically, the discussion of test–­retest reliability is focused on its psychometric implications—test–­ retest reliability is a good thing—­rather than on substantive implications (e.g., is the pathology in question really stable?). In short, test–­retest studies have usefully established the test–­retest reliability of the primary Axis II assessment devices (e.g., Loranger et al., 1994; Trull, 1993); however, such studies simply cannot illuminate long-term stability issues in the realm of schizotypy or any other realm of PD inquiry. Test–­retest reliability is a different concept from stability per se. By the term stability, I mean consistency in personality features over meaningful periods of time—­typically years, not merely a few weeks or months. In addition to being concerned with relatively brief periods of time, the test–­retest study design itself—even if applied over a long period of time (years)—has noteworthy methodological shortcomings. These shortcomings limit the utility of test–­retest studies, and they have contributed little to understanding long-term (e.g., years) stability of the PDs. 18 This issue raises the interesting question as to whether psychopathology that hails from schizotypy—

such as SPD or PPD—should be considered justifiably as personality pathology or whether it should be viewed as merely an expression of the liability for an Axis I disorder, namely schizophrenia. Regardless of one’s theoretical position on that matter, SPD and PPD symptoms should be stable over time.

322

SCHIZOTYPY VIEWED FROM THE LABORATORY

On Studying Stability the Right Way: Beyond Test–­Retest Studies The greatest limitation of all test–­retest (Time 1–Time 2) studies is found in the research design itself and the fundamental inability of test–­retest observations to adequately address stability, an established fact in life-span research methodology (Rogosa, 1988; Rogosa, Brandt, & Zimowski, 1982; Nesselroade & Baltes, 1979; Nesselroade, Stigler, & Baltes, 1980). The use of two waves of longitudinal data (even if separated by a long period of time) is an extremely limited design for investigating stability or change because (1) the amount of change between Times 1 and 2 cannot tell one anything about the shape of each person’s individual growth trajectory over the long term and (2) with only two waves of data, estimates of true change cannot be teased from the observed data (Willett, 1988; Singer & Willett, 2003). Moreover, two-wave data cannot discern regression-to-the-mean effects in empirical data (Nesselroade et al., 1980). That is, it cannot help you determine what amount of observed change is real and what amount can be safely ascribed only to the statistical reality (and, potentially, artifactual) of regression to the mean (high scorers at Time 1 will drop at Time 2; low scorers at Time 1 will rise at Time 2). How, then, best to proceed in the study of stability in schizotypy or, for that matter, any psychological construct of interest? The answer is the prospective multiwave longitudinal study design. The scientific utility and unambiguous superiority of the prospective multiwave design for studying continuity and change in personality and other aspects of human growth has long been known in the developmental science area (Collins & Sayer, 2001; Nesselroade & Baltes, 1979; Nesselroade et al., 1980; Rogosa, 1988; Rogosa et al., 1982; Singer & Willett, 2003; Willett, 1988). The multiwave design approach allows for effective examination of the major classic vantage points on stability, namely (1) individual differences (rank order), (2) level (group means), (3) structural (factorial invariance), and (4) ipsative (intraindividual or profile) stability (Kagan, 1980; Caspi & Roberts, 1999; see also Robins, Fraley, Roberts, & Trzesniewski, 2001; Roberts & DelVecchio, 2000; Roberts, Walton, & Viechtbauer, 2006). Unpacking these concepts is necessary before proceeding. Rank order, or “normative stability,” concerns the extent to which individuals maintain their relative position within a group ranking on a variable of interest from Time 1 to Time 2. Level stability concerns the extent to which group means remain invariant over time on a variable (or disorder) of interest. Structural stability refers to the consistency over time of the factor structure that underpins a psycho-



The Schizotype through Time . . .

323

logical domain or array of measures tapping a psychological domain. Finally, ipsative stability concerns intraindividual consistency in the organization of PD features or personality traits over time (cf. Mortimer, Finch, & Kumka, 1982). Finally, of methodological importance, prospective multiwave longitudinal designs allow for state-of-the art analysis of individual growth curves within a multilevel modeling (or hierarchical linear modeling) framework (Bryk & Raudenbush, 1987; Raudenbush & Bryk, 2002; Rogosa et al., 1982; Rogosa & Willett, 1985; Singer & Willett, 2003; Lenzenweger, Johnson, & Willett, 2004).

Long-Term Stability of Schizotypic Pathology: Illustrations from Schizotypal PD and Paranoid PD If we assume that DSM-defined schizotypal and paranoid personality disorder represent, for the most part, valid expressions of schizotypy (i.e., schizophrenia liability), then we would expect them to be reasonably stable over time. We, of course, do not expect them to be completely stable, as there is ebb and flow in development (e.g., some genes turn on and off over time), and environmental constraints clearly affect the expression of both normal personality and psychopathology over time. We would, however, expect these schizophrenia-­related personality disorders to be reasonably stable through time. What do we know about the stability of schizotypic psychopathology as embodied in SPD and PPD? There are really only three prospective multiwave longitudinal studies that speak to this question, two of which concern samples drawn from nonclinical populations and one that drew its sample from clinical and hospitalized cases. These studies are the (1) Longitudinal Study of Personality Disorders (LSPD; Lenzenweger, 1999c, 2006a), (2) Children in the Community Study (CIC; Cohen, Crawford, Johson, & Kasen, 2005), and (3) Collaborative Longitudinal Personality Disorders Study (CLPS; Skodol et al., 2005). We begin with our study, the LSPD, which began in 1991 and was the first National Institute of Mental Health (NIMH)-funded prospective multiwave longitudinal study to focus on personality disorders diagnosed using modern methods. In this study 258 young adults have been followed in their early adult development. These subjects are the focus of intensive long-term life-span study and are now nearing their late 30s. The initial reports come from the study period covering the ages from 18 to 21. These 258 individuals were evaluated three times using state-of-the-art diagnostic methodology and were never seen by the same interviewer more than once over a period of 4 years. In the first longitudinal report from the LSPD (Lenzenweger,

324

SCHIZOTYPY VIEWED FROM THE LABORATORY

1999), a traditional repeated measures analysis of variance (ANOVA) was conducted for the interview assessed PD symptoms (International Personality Disorder Examination; Loranger, 1999), as well as self-­report-inventory­measured (Millon Clinical Multiaxial Inventory-II; Millon, 1987) PD features. With respect to mean level or group stability, both SPD and PPD features declined in terms of average levels over the 4-year study period on both the interview and self-­report assessments. Although statistically significant, the magnitude of these effects (symptom declines) ranged from small to moderate, albeit somewhat larger for the self-­report PD assessments. In short, these data suggested that the mean (group) levels of these PD features remained relatively unchanged over time, suggesting some change. At the level of individual differences or rank-order stability—that is, the maintenance of the ranking or ordering across the individuals across time on the PD variables—again, both SPD and PPD features showed relatively high correlations across the various study waves (e.g., Wave I × Wave II, Wave II × Wave III, and Wave I × Wave III), with evidence for higher levels of rank-order stability found for the self-­report PD assessments as compared with the interview-based PD assessments. Overall, the picture that emerged from this initial consideration of two forms of stability (group, rank order) for SPD and PPD in the LSPD data set was one largely of stability. There were some clues in the results that more change over time lurked within the data than was captured in the group-level analyses.

Probing the LSPD Data More Deeply: On Assumptions and Proper Methods for the Study of Change The initial repeated-­measures ANOVA analytic approach was subject to a number of technical limitations, which have received considerable attention in the longitudinal methodology literature (Singer & Willett, 2003). What were the technical limitations of the repeated-­measures ANOVA approach? First, there was clearly interindividual variability in assessment intervals for the LSPD subjects, and repeated-­measures ANOVA cannot tolerate this feature of longitudinal data. In longitudinal research, not every subject is assessed on exactly the same schedule. There is variation that comes from the realities of conducting numerous subjects over many years (e.g., one subject might have had 365 days between assessments 1 and 2, whereas another subject might have had 402 days between the same assessments.) Second, the repeated-­measures ANOVA approach cannot tolerate missing data, yet a reality of longitudinal research is that subjects in such an investigation often have incomplete data. For example, a subject might not be available at the



The Schizotype through Time . . .

325

time a certain assessment wave is carried out but is available for subsequent waves. Clearly, we want to use this subject, even if some data are missing for one assessment. Third, for the most part, repeated-­measures ANOVA is really only focused on between-­subjects change and does not make particularly good use of within-­subject change. Fourth, typical repeated-­measures ANOVA is based on a linear model of change, whereas other approaches permit the flexible specification and investigation of nonlinear individual change over time. Finally, the ANOVA approach assumes that all subjects display the same pattern of change, and this is not tenable. What does the pattern of growth and change for the SPD features look like for subjects in the LSPD? How varied are patterns of growth? The answer is that the patterns of individual growth are highly varied. For example, Figure 10.1 (which appeared in Chapter 5 as Figure 5.1) depicts the individual growth curves for each of the 250 subjects in the LSPD for

30.00

Cluster APD

20.00

10.00

0.00

0.00

1.00

2.00

3.00

4.00

Time (yrs)

FIGURE 10.1.  Individual growth trajectories for DSM-III-R Cluster A personality disorder features in the 250 subjects from the Longitudinal Study of Personality Disorders during the 4-year study period. Time is reported in years since the start of the study. Symptom assessments were done with International Personality Disorder Examination (IPDE, Loranger, 1999).

326

SCHIZOTYPY VIEWED FROM THE LABORATORY

Cluster A personality disorder features. One feature of these data that should immediately appear obvious to the reader is the considerable variation in the patterns of change seen in the LSPD subjects over time. Clearly, all subjects do not show the same pattern of growth over time. Therefore, we adopted an IGC analysis methodology to investigate change in PD features over time. This method of analyzing within-­subject change was popularized by Rogosa and colleagues (Rogosa et al., 1982; Rogosa & Willett, 1985) and represents the most powerful way to assess change in a continuous dimension over time within subjects (Rogosa & Willett, 1985; Singer & Willett, 2003; Bryk & Raudenbush, 1987). The IGC approach is conceptually straightforward. One must, for the most part, dust off some high school linear algebra and remember that the key parameters to a line are its slope (rate of change) and intercept (intersection with y-axis). The equation y = mx + b should come to mind, where m = slope and b = y-intercept. This linear function is applied in IGC analysis. The dependent variable from the LSPD database used in these IGC analyses was the number of PD features rated as present on the IPDE, which yielded continuous dimensional scores for the DSM-III-R Axis II PDs. We examine schizotypal and paranoid personality disorders in this context. The IGC approach hypothesized that, for each person in the LSPD, the continuous outcome variable (e.g., schizotypal PD features) was a specified function of time, called the individual growth trajectory, plus error (Lenzenweger et al., 2004). This trajectory was specified as a simple linear function of time, which contained two important unknown individual growth parameters (intercept and slope) that determined the shape of individual true growth over time. The individual intercept parameter represents the net “elevation” of the trajectory over time—that is, the true mean level of the PD features for the individual at the onset of the study (or, alternatively, whenever the origin of the time scale has been defined). The individual slope parameter represents the rate of change over time, and here is the within-­person rate of change in PD features over time.19 Once an individual growth trajectory was specified (termed the “level-1” model) to represent the individual change over time, a “level-2” model was specified to describe our hypotheses about the way that the individual growth parameters contained in the level-1 model are related to important between-­subjects factors (e.g., subject sex, diagnostic group) in the LSPD. 19 Despite the obvious theoretical importance of individual slope in studies of change, it has not been widely examined in research on psychopathology. In short, we often want to know how quickly change is happening in psychopathology, but this information is not available in the comparisons of group means.



The Schizotype through Time . . .

327

What did we learn about schizotypic personality pathology from this IGC approach? The IGC results painted an interesting picture. Taking into account the considerable intersubject variation in growth, the IGC results suggested that, whereas SPD showed a significant rate of change in the direction of declining symptoms over time, PPD did not. SPD displayed a rate of change of –.24, which meant that SPD features were decreasing 0.24 units per year. PPD, in contrast, showed a rate of change of only –0.04, which represented minimal change over time. Thus, based on the LSPD results, schizotypal symptoms did show some amount of flexibility over time, whereas PPD showed considerably less so. We need to understand these results suggesting that the phenotypic indicators of schizotypy, in this case SPD, may show some flexibility over time. Namely, what predicts change in these symptoms over time? We pursued this question in a recent analysis of the LSPD data (Lenzenweger & Willett, 2007), in which we examined whether the initial status and/or rate of change seen in normal personality systems (agentic positive emotion, communal positive emotion, negative emotion, constraint) were related to the initial status and/or rate of change in schizotypic features (i.e., Cluster A DSM-III-R PD). In sum, change in normal personality systems did not correspond with changes (declines) in schizotypic features. Whatever is changing in the LSPD subjects that is related to changes in Cluster A features over time, it is not something related to changes in what we would think of as normal personality, as best we can tell.20

Consistency with Other Prospective Longitudinal Multiwave Studies: The CIC and CLPS Projects There are two additional prospective multiwave longitudinal studies that bear directly on the issue of the stability of schizotypic features over time, one conducted in the community and one conducted with cases initially selected from treatment settings. The Children in the Community Study (CIC), under the direction Patricia Cohen at Columbia University, has focused on the ongoing development of a large sample of individuals initially recruited from the community at a young age. Conducted in Albany and Saratoga Counties in Upstate New York, the CIC has been a significant investigation given that it has not restricted itself to the study of hospitalized or clinic-­treated cases. Johnson et al. (2000) reported from the CIC that they also observed a reduction in personality disorder traits over time 20 We also examined whether having a comorbid Axis I mental disorder and/or exposure to treatment during the study period might have accounted for the rate of change seen in the Cluster A PD features over time. They did not.

328

SCHIZOTYPY VIEWED FROM THE LABORATORY

in a representative community sample of 816 youths. For the two PDs of interest to this discussion, schizotypal and paranoid, Johnson et al. (2000) reported a 46% and 47% decline in paranoid and schizotypal PD symptoms, respectively, over the period from 14 to 22 years of age. In fact, the correlation between age (increasing) with PD features (decreasing) were –.20 for PPD and –.24 for SPD. These declines are consistent with what was observed earlier in the LSPD data. Interestingly, the CIC reported (not unlike the LSPD) that rank-order stability—or the stability of individual differences—for PPD and SPD was significant, that is, individuals maintained their positions in rank over time as defined by their PD features.21 The Collaborative Longitudinal Study of Personality Disorders (CLPS), begun in 1996 under the primary direction of the psychiatrist John G. Gunderson at McLean Hospital, is a large-scale effort to study individuals over time that began with treated cases. The individuals in the CLPS were recruited from multiple clinical sites, and they were diagnosed as having one of four PDs at the inception of the study: borderline, schizotypal, avoidant, or compulsive PD. The subjects in the study have been followed over time in prospective multiwave fashion and examined for PD features at each assessment point. Not unlike the LSPD and CIC, the CLPS is an ongoing study, and thus results are available only from the first few years of the project. The PD of interest in the CLPS is obviously SPD for this discussion. The patterns reported from the CLPS for SPD closely mirror those reported earlier by both the LSPD and CIC. Shea et al. (2002) reported for 82 schizotypal patients followed over a 2-year time span and assessed three times that only 34% of the subjects diagnosed as SPD at Time 1 (baseline) were still diagnosed as such at the third assessment. When considering the SPD features as a dimension, a repeated-­measure ANOVA revealed a highly significant effect for the influence of time in relation to declining schizotypal features. This picture of declining SPD features with time in a clinical sample is highly consistent with that reported by the LSPD and CIC, both community studies.22 21 The rank-order stability for the Cluster A PD features as a composite score was even higher than that found for the paranoid, schizotypal, or schizoid PDs taken singly. 22 Interpretation

of the CLPS data, however, is not unambiguous due to the fact that the CLPS investigators intentionally selected the study participants to be elevated on the SPD dimension, as all met DSM criteria for the presence of the disorder at baseline. The subjects really had only one direction in which to change, namely, in the direction of symptom declines, and this raises the likelihood of regression to the mean as a mechanism largely responsible for change in the CLPS data. Moreover, all of the subjects in the CLPS were recruited from within treatment settings and, therefore, were the recipients of psychiatric treatment. Treatments for PDs should diminish symptoms; thus treatment is another complication in interpreting the CLPS data. In fact, Shea et al. (2002) reported a strongly significant statistical interaction between time and treatment intensity for SPD features.



The Schizotype through Time . . .

329

Summary The schizotype through time—what do we know at this point? Irving I. Gottesman (1987) once noted “that the ‘proof of the pudding’ will always be in the follow-up” (p. 566) when considering the value of one or another predictive construct in schizophrenia research. I wholeheartedly agree with this view, as it represents one of our most important levers in psychopathology research, namely that of time and, by implication, development. What do we know about the follow-up pudding in schizotypy? From the follow-up study of SPDs (and related disorders), we know that some of these individuals do go on to develop psychotic illnesses, many in the schizophrenia spectrum. However, it is important to note that the vast majority of such individuals do not transition to psychosis; rather, they remain schizotypic in symptom profile, or they show a diminution of schizotypic features over time. Perhaps the million-­dollar questions are, What accounts for the change seen in these individuals over time? What accounts for individuals that transition to psychosis (e.g., Lataster, Myin-­Germeys, Derom, Thiery, & Os, in press). What accounts for the symptom declines observed in the longitudinal study of schizotypic PD features over time? Only time will tell . . .

C h a p t e r 11

Now, Just What about This “Type” Business in “Schizotype”?

Many students in psychological science are taught to think of the world of psychological constructs as inhabited solely by dimensions or continua. They are taught that any construct of interest varies by degree or quantitatively. Anxiety ranges from being essentially absent through middle levels of severity on to extreme levels. The degree to which one is authoritarian in personality style presumably covers a wide range of values extending from low to high. The student of psychology is taught to believe—I use the word believe here quite intentionally—that all constructs of interest to psychologists behave as if they were wired to dimmer switches, whereby levels can grade slowly and evenly across a wide range of scores (essentially from theoretically absent to theoretically very high). Moreover, they are taught that values tapping a construct are arranged neatly in a bell-­shaped curve distribution. Low values and high values on a dimension are somewhat less common and occur, respectively, in the left and right tails of the bell-­shaped distribution, whereas more common middle-range values inhabit the range of ± 1 s either side of the mean of the distribution. One aspect of psychological science education that helps to cement this view for many is the exposure to statistical procedures that assume the presence of quantitative variation that is normally distributed and is underpinned by ratio-scale measurement. In a sense, the statistical training helps to “pseudo-­confirm,” if you will, that the world is dimensional in nature. Thus I never fail to be

330

What about This “Type” Business

331

amazed by the stunned reaction of many of my students in psychometric theory courses or seminars on psychopathology when I raise the possibility that “types” exist in the psychological and behavioral world. Could it be that not all variation in observable phenotypes hails from underlying processes that are quantitative in nature? Is it not possible that some variation reflects “qualitative” variation, or a difference in type or “kind”?

Brief Excursus on Types and Natural Kinds To pursue discussion of qualitative or discontinuous variation in relation to schizotypy, it is necessary to briefly consider issues related to what we mean by a “natural kind.” By this we mean a nonarbitrary category, or a species, or a type, or natural class. For example, as Paul Meehl was fond of saying, “there are chipmunks, there are gophers, but there are no gophmunks” (Meehl, 1995, p. 268). We know that dogs and cats are fundamentally different, we know that gold differs from lead, we know that measles is a different illness than chicken pox. These are all differences of kind or type, not of degree or amount. Regarding what constitutes a kind, Ayers (1981) states, “Membership of the kind is determined by the presence of a presumed underlying common nature which may be unknown to us, rather than by the satisfaction of a definition consisting of a list of those properties which we happen to use as criteria for identifying things as members of that kind” (p. 247).1 Some would say a natural kind relates to the world in a special manner. For example, Putnam (1983) suggests that a natural kind is defined in part by the role it plays in an interconnected network of laws of nature. Furthermore, some philosophers (e.g., Hacking, 1991) would distinguish types of people as “social kinds” rather than natural kinds. The natural kind concept has received considerable attention, especially, in philosophy.

Discontinuities in Psychology and Psychopathology: A Further Detour on Biases and Methods We consider that types of people exist and that they can be considered as evidence of a natural kind. Thus the concept of kind represents a distinct taxonomic class (of things or people) and, in order to denote this notion, 1 The

issue of natural kinds has generated considerable discussion in the philosophy and philosophy of science literatures (Quine, 1969; Putnam, 1983; Hacking, 1991; Boyd, 1991, 1999a, 1999b).

332

Schizotypy Viewed from the Laboratory

the word taxon is frequently used. Meehl (1992) defines taxon, a word that hails from the Greek, to mean arrangement or ordering, as “a nonarbitrary class whose existence is conjectured as an empirical question, not a mere semantic convenience” (p. 117). Taxa (plural of taxon) that exist in nature or society are easy to find: chemical elements, biological species, organic diseases, geological strata, kinds of stars, elementary particles, races, cultures, vocations, ideologies, religions, political parties (see Meehl, 1992, p. 117). Finally, we assume that in the presence of a genuine taxon, indicators of that taxon will display, at the latent2 level, evidence of this taxonicity. This is so even if inspection of the observed distributions of these indicators fails to provide hints as to the latent state of affairs. As we ponder the issue of types of people, we must consider the issue of continuity versus discontinuity in connection with (specifically) psychological and/or psychopathological constructs (see Lenzenweger & Korfine, 1995). To review, when one speaks of a taxon (latent class or “nonarbitrary” natural subgroup), one is concerned with a difference of “type” or “kind,” rather than a difference of “degree” or “intensity.” Hypothesizing the existence of discrete types in psychological science, especially within the realm of personality and psychopathology, has been the object of lively debate (see Gangestad & Snyder, 1985; Meehl, 1992, 2001). Whether due to training (as suggested earlier) or other factors, many psychologists seem opposed to the very existence of types, though the reasons for such opposition often may have more to do with one’s point of view (or ideology) on the conduct of science and structure of nature rather than otherwise. I have found that looking for “types” in the psychological realm is unpopular and runs counter to the thinking (biases?) of most psychological theorists (cf., see Eysenck, 1986, on personality dimensions; Claridge, 1997, on a dimensional approach to schizotypy). Although the dimensionality of many constructs in psychology seems plausible (e.g., sociability, impulsivity) and many of these are measured using an explicitly dimensional approach, it is important to understand that the act of “measuring” a variable continuously does not necessarily “make” the latent construct continuous in nature. There are striking examples of graded or continuous measurement illustrating difficulties with an assumption that, somehow, continuity in measurement implies continuity in nature or underlying structure. To begin coarsely, for example, the temperature of water can be measured continuously; however, temperatures above 212°F or 2 What

does latent mean? We can define latent as referring to the inner, unobservable, below the surface, or theoretical nature of a phenomenon under consideration (see Meehl, 2001, for further considerations).

What about This “Type” Business

333

below 32°F are associated with qualitative changes of organizational state (or “type”), namely transitions to a vapor (gas) or solid (ice), respectively. In a more closely related vein, we regard “health” as a reflection of body temperature, and we can measure reliably the temperature of the human body in a continuous fashion. Once body temperature passes 98.6°F, however, we typically speak of the presence of “illness” (i.e., we recognize a meaningful discontinuity in continuous data). Perhaps closer still to our subject matter, although intelligence is routinely measured in a continuous manner in the form of IQ scores, we speak of retardation as we descend into the lower (left) tail of the population distribution of IQ in recognition of a readily apparent qualitative change. The basic point I wish to make is relatively straightforward: One’s approach to measurement should not determine one’s views of the structure of nature. One should not be persuaded that nature is structured in a dimensional manner merely because one has relied on continuous measurement approaches. One’s views of the structure of nature must be open to empirical confirmation or disconfirmation. As Meehl (1992) argues: whether or not the entities, properties, and processes of a particular domain (such as psychopathology or vocational interest patterns) are purely dimensional, or are instead a mix of dimensional and taxonic relations, is an empirical question, not to be settled by a methodological dogma about how science works. (p.119)

Whether or not a construct has a discontinuous latent structure is not dependent on beliefs, convictions, or guild preferences (e.g., certain professionals prefer to think of constructs in preferred ways, based on preference and not data) but, rather, represents an empirically researchable scientific question.

How to Find Discontinuities (and How Not To) Finding compelling empirical evidence for the existence of a discontinuity in the realm of personality or psychopathology is not an easy task, partly because most workers have relied traditionally on methods for the detection of latent taxa that are either largely inadequate for the task (i.e., group contrasts, factor analysis) or are potentially misleading (e.g., seeking bimodality in the distribution of scores on a variable of interest; Murphy, 1964; Grayson, 1987; see also Levy et al., 1993; or cluster analysis; Golden & Meehl, 1980;

334

Schizotypy Viewed from the Laboratory

see Everitt, Landau, & Leese, 2001). Factor-­analytic approaches will always yield continuous factors, yet a dimensional latent structure to the data is not necessarily ensured; cluster analysis will always yield qualitative clusters,3 yet a typological latent structure to the data is not ensured. Furthermore, the existence of bimodality in a distribution of scores for a phenomenon under study does not ensure the existence of a latent discontinuity (see Grayson, 1987, for a classic discussion), and bimodality may fail to surface in a score distribution when, in fact, it should be apparent (see Beauchaine, 2003, 2007; Lenzenweger, McLachlan, & Rubin, 2007). For example, major gene effects on a quantitative character may not reveal themselves in an easy, discernible manner (e.g., “bimodality” in a metric character distribution), yet a major gene (a latent taxonic entity) is active nonetheless (e.g., Falconer, 1989). Moreover, unimodality does not ensure the presence of a continuum at the latent level. For example, what appears to be a generally unimodal distribution of scores or values could, in fact, harbor a mixture of distributions that hail from qualitatively different sources (see Figure 2.3 in Chapter 2). Finally, to complicate matters further, a qualitative phenotypic character (e.g., extra toes vs. normal number of toes in guinea pigs or cats) can be the result of an underlying system that is quantitative (e.g., polygenic) in nature, in which genetic influences are functionally distributed in a normal fashion (see Gottesman, 1991; Cardno & Gottesman, 2000). The very nature of variability in human behavior, coupled with the multitude of facets of human psychological functioning worthy of scientific study, makes the task of finding a discontinuity in an aspect of personality organization, trait structure, or behavior a relatively daunting undertaking. Whereas some observable human traits or behaviors are likely to be truly discontinuous in structure (Meehl, 1992), many will not be so. My experience in over 25 years of pondering these issues and reading the empirical corpus is that there are probably very few genuine types or kinds of people. Thus my view is that one must be carefully grounded in theory and empirical evidence before advancing a case for types in personality or psychopathology (Lenzenweger, 2004). Many “continuous” human characters—­traits or dimensions that vary by degree or quantitatively—­though clearly not all, will be expressions of continuously distributed genetic determinants. Indeed, as Falconer (1989) so aptly notes, “One has only to consider one’s fellow men and women to realize that they all differ in countless ways, but that these differences are nearly 3 The

situation with cluster analysis, as typically implemented and typically interpreted (e.g., K Means clustering), is that there really is no statistically well-­principled basis for selecting the optimal number of clusters from a solution. At present, there are better approaches for seeking groups or types that are well principled (see McLachlan & Peel, 2000; Lenzenweger, Jensen, & Rubin, 2003).

What about This “Type” Business

335

all matters of degree and seldom present clear-cut distinctions attributable to the segregation of major genes” (p. 104). In other instances, however, a complex behavioral or trait phenotype will be an expression of a major gene or genes. How, then, best to proceed? The search for a qualitative break in some human behavior or trait must first be founded on solid observation and theoretical conjecture (cf. Meehl, 1990, 1992; see also Matthysse, 1993; Lenzenweger, 2004; Lenzenweger, McLachlan, & Rubin, 2007), and appropriate statistical procedures that are “up to the job,” so to speak, must be used. Fortunately, statistical techniques have been developed that can be used to discern discontinuities in human traits and behaviors (e.g., finite mixture modeling; Titterington et al., 1985; McLachlan & Peel, 2000; McLachlan et al., 2004; Rubin & Wu, 1997; latent class analysis; Lazarsfeld & Henry, 1968; complex segregation analysis; Lalouel, Rao, Morton, & Elston, 1983; and taxometric analysis; Meehl, 1973; Meehl & Yonce, 1994, 1996; Waller & Meehl, 1998; Beauchaine, 2007), as well as for detecting “types” of developmental trajectories (Nagin, 1999, 2005). We can discuss the nature of schizotypy, thus, with two assumptions in mind: (1) qualitative “types” (taxa) of human behavior (traits, conditions) can exist and (2) their accurate detection requires use of suitable statistical procedures.

Meehl’s Model of Schizotypy Created His “Need” for Taxometrics Given that Meehl’s model of schizotypy (Meehl, 1962, 1990; see also Lenzenweger, 2006b) posits that one is either a schizotype or one is not, t here has been considerable interest in determining whether various putative measures of schizotypy (i.e., schizophrenia liability) reveal themselves to be distributed in a qualitative or discontinuous fashion at the latent (unobservable) level. More specifically, this interest actually began, in earnest, with Paul Meehl himself and his desire to understand just how valid indicators of schizophrenia liability could be essentially uncorrelated in large samples of subjects that contained people with schizophrenia as well as other conditions (i.e., a mixed sample; Meehl, 1973). In short, his theoretical model itself provided the substantive basis (and need) for his methodological development of what is known as coherent cut kinetics or, more commonly, taxometric methods. Also highly relevant to the development of taxometric analysis was Meehl’s view of what available cluster-­analytic approaches had failed to deliver much gold in helping to parse the phenotypic hyperspace in psychopathology (Meehl, 1979), a view informed by his own empirical research on the topic (Golden & Meehl, 1980). Waller (2006) provided an

336

Schizotypy Viewed from the Laboratory

extended and fascinating account of this process of discovery and invention. In short, the taxometric approach came to be in an effort to test a model that suggested that “types” should exist where schizophrenia liability was concerned. The manner in which taxometric analysis works, its underlying mathematical assumptions, and the specific procedures followed in a taxometric analysis have been covered many times in the extant literature and, indeed, entire books have been written on the topic (the best of which remains that by Waller & Meehl, 1998). An excellent primer was written by Beauchaine (2007), which is remarkable for its lucidity and accuracy. The important concept to understand regarding taxometric analysis is that it represents a family of methods that seek to answer a basic question using quantitative data: Does this construct, measured with this set of fallible indicators, have a dimensional (quantitative) or taxonic (qualitative, discontinuous) latent structure? A very brief conceptual overview of maximum-­covariance analysis (MAXCOV), which is the most widely used taxometric technique, would be useful (see Meehl, 1973; Meehl & Yonce, 1996; Waller & Meehl, 1998, for details). Recall that one can have a data situation in which two variables can be correlated and the sample of individuals under consideration can harbor two “types” of people, such as that depicted in Figure 11.1 (which appeared in Chapter 2 as Figure 2.4A). How would MAXCOV analysis enable one to detect the latent situation depicted in this figure?

FIGURE 11.1.  A scatterplot depicting the relations between symptoms X and Y. There is a clear positive association between the two forms of symptomatology. Underlying this relationship is the presence of two qualitatively different types of subjects (type t and type c).

What about This “Type” Business

337

Following Beauchaine’s (2007, pp.  659–660, adapted by permission) tutorial: Using the MAXCOV procedure, one evaluates the correspondence (covariance) between two variables across the entire range of a third variable. Because it is not intuitively obvious how this practice might distinguish typologies from continua, MAXCOV is best explained by way of example. The top panel of Figure 11.2 illustrates the MAXCOV procedure with three variables, psychomotor retardation (x), early morning awakening (y), and weight loss (z). Here, the covariance of psychomotor retardation (x) and early morning awakening (y) is computed across the entire range of weight loss (z), within 16 successive intervals. As the top panel of Figure 11.2 illustrates, if a taxon is present and the effect size separating the two groups is adequate for all three variables, then a substantial peak is observed in the covariance function, indicating the value of weight loss (z) that best differentiates between groups. All trivariate combinations of variables are subjected to MAXCOV, and the consistency of results is evaluated. When there is no taxon present, or when one or more indicators are characterized by inadequate effect sizes, no peak is observed in the covariance function, as depicted in the bottom panel of Figure 11.2. The location of the MAXCOV peak changes with differing taxon base rates (i.e., proportions of taxon members to nontaxon members). With a base rate of .50, for example, MAXCOV functions peak near the mode of the cut variable (z). As the base rate decreases, the peak shifts toward higher z values. At very low base rates, a rise in the covariance function (rather than a peak) occurs at the right end of the plot. Distinguishing between a taxon-­generated rise to the right and an upward inflection caused by some kind of measurement­induced nonlinearity can at times be difficult, which is why “consistency tests” are very important.

Hold the Horses: Confronting the “Who Cares?” Question At this juncture, some readers might be thinking, “OK, I ‘get it’ about types, I see the connection to schizotypy, the weakness of clustering approaches, but who really cares about ‘types’ anyway? How can knowledge about the existence of a taxon matter? What can it do for knowledge?” Meehl (1992) provided some guidelines for how the existence of a taxon might aid in the advancement of psychological science. He proposed that there are at least four reasons for determining whether or not a construct in psychology or psychopathology is structured qualitatively or taxonically. According to Meehl, if genuine taxa exist, then:

338

Schizotypy Viewed from the Laboratory

FIGURE 11.2.  Examples of MAXCOV with taxonic data, as in the case of melancholia (top panel) and nontaxonic data, as in the case of exogenous depression (bottom panel). The top panel includes analyses with two groups of n = 900 (exogenous depression) and n = 100 (melancholia) and an effect size of d = 2.0. The bottom panel includes analyses using continuous normal distributions of n = 1,000. In the case of melancholia (top), the covariance between early-morning awakening (x) and psychomotor retardation (y), calculated within 16 adjacent intervals of weight loss (z), is maximized at the amount of weight loss (z) that best differentiates between groups, referred to as the hitmax value (dashed line). In the nontaxonic case (bottom), the covariance values of sadness (x) and crying (y) fluctuate unsystematically across levels of insomnia (z). These variables do not differentiate melancholia from endogenous depression. Adapted with permission from Beauchaine (2007).

What about This “Type” Business

339

1. Theoretical science should come to know them. 2. The construction of assessment devices will proceed differently given that the goal would be the assignment of individuals to a category versus location of individuals on a dimension. 3. We could determine whether the classification of patients, as in organic medicine, is justified in terms of both improved treatment and prognosis. 4. Causally oriented research will often proceed differently if a taxonic conjecture has initially been taxometrically corroborated (see Meehl, 1992, pp. 161–162). These are four very powerful and complex arguments, and they require a little unpacking and tuning. I would suggest that the first of these reasons could be amended in a friendly fashion to emphasize the need for taxometric investigations to pursue questions that have the potential utility to inform theoretical science in a meaningful way. In short, what are not needed are, say, taxometric investigations of knuckle cracking or vegetarianism. The second and third points raised by Meehl (1992) are particularly important, as they speak to a very likely application of knowledge derived from taxometric studies. In short, somehow (1) researchers will pursue assessment and diagnosis differently, (2) new research assessment or diagnostic strategies will accrue from this knowledge, or (3) researchers will be forced to rethink prior decisions regarding assessment or diagnosis. For example, through rigorous application of taxometric methods, researchers may discern what psychopathological entities genuinely seem to possess a taxonic (qualitative) latent structure, and, through an analysis of taxometric results, researchers may determine a more appropriate cutting score or demarcation point for the assignment of a diagnosis (rather than use arbitrary rules to guide the process). One could also imagine that scale construction might proceed differently once it was known that the construct for which an assessment device is being developed is taxonic in nature. For example, only those items that serve to characterize taxon members reflective of the construct would be included in the scale under construction. There are any number of other potential applications for taxometric methods and the results derived from taxometric analyses for the purposes of test construction.4 The fourth issue 4 The use of item-­response theory (IRT; Embretson & Reise, 2000) to guide test construction has gained considerable popularity in recent years given the many technical and theoretical advantages the approach has over classical test theory (Lord & Novick, 1968). Interestingly, it assumes that the latent trait on which every individual can be placed in the computation of IRT parameters is a continuous quantitative dimension. How would an IRT approach to test construction handle the situ-

340

Schizotypy Viewed from the Laboratory

raised by Meehl—that causally oriented research will proceed differently— is particularly important and requires deeper contemplation to appreciate its implications. What is implied in this point is that, via taxometric research, we may discover that a particular genetic model is more likely to fit the observed data for a disorder than others. For example, should evidence of a well-­defined taxon emerge in the analysis of various schizotypy indicators, one might then be encouraged to look for a particular genetic polymorphism that might be associated with membership in the discovered taxon. Or, perhaps, in neurobiological investigations—­neuropharmacological probe studies—one might be inclined to select only putative taxon members for inclusion in the experimental group.

Back to Schizotypy: On the Need for a Latent Liability Construct Much of the foregoing discussion has assumed a common underlying liability for schizotypic psychopathology (e.g., Cluster A personality disorders, schizophrenia).5 What is the empirical basis for such an assumption? The evidence in support of a latent liability conceptualization in schizophrenia is robust. First, schizotypic psychopathology is linked, presumably via genetics, to schizophrenia (Kendler, 1985; Fanous et al., 2007; Lin et al., 2005). However, before considering modern genome-wide, molecular genetic studies that address this point, it is wise to consult a database that has been a veritable gold mine for schizophrenia research. Thus, perhaps the most influential evidence that helped to establish a link between schizotypic phenomenology and clinical schizophrenia came early and clearly from the Danish Adoption Study of Schizophrenia (Kety et al., 1968). Kety and colleagues (1968), using a clinically based definition of “borderline schizophrenia,” found elevated rates of borderline or latent schizophrenia in the biological relatives of schizophrenic adoptees. These results provided compelling evidence for a genetically transmitted component underlying both manifest schizophrenia and the less severe schizophrenia-like disorders. ation whereby the latent trait or construct is taxonic or qualitative in nature? This is a complicated question, beyond the scope of this volume, but one that has begun to generate interesting discussion (DeBoeck, Wilson, & Acton, 2005). 5 Very

nearly all research into the determinants of schizophrenia implicitly assumes that we are dealing with one disorder and, by implication, one liability pool underlying that disorder. However, as noted previously, it is possible that we really are dealing with a collection of psychotic illnesses, all marching along under the banner of schizophrenia and each having its own genetic substrate.

What about This “Type” Business

341

The hypothesized continuity between the conditions was thus not merely phenomenological, but also genetic. Moreover, numerous family studies have found an excess of schizotypic disorders in the biological relatives of schizophrenic individuals (see Kendler et al., 1993). Clearly, the boundaries of the phenotypic expression of schizophrenia liability extend beyond manifest psychosis. Thus liability manifestations are not isomorphic with expressed psychosis. More recently, using the tools of the modern genetics laboratory, several studies have provided strong evidence linking schizotypic pathology and schizophrenia to some common genetic loci that have emerged as potential susceptibility genes. Avramopoulos et al. (2002) found that higher scores on two different psychometric measures of schizotypy—the PAS and SPQ—were significantly related to the high-­activity genotype for catecholO-methyl transferase (COMT), an enzyme that breaks down dopamine. Chen and colleagues (Lin et al., 2005) found that, indeed, perceptual aberrations—the well-known schizotypic feature—were found to be associated with the neuregulin 1 (NRG1) gene at chromosome 8p22-p12. The NRG1 gene is regarded by many researchers as a promising candidate susceptibility gene for schizophrenia. Finally, Kendler’s research group (Fanous et al., 2007) extended this line of research with a study that sought to detect correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. They found associations between schizotypic features and six areas on the genome (5q, 9q, 10p, 6q, 6p, 8p). What is exciting is that two of the regions found to be associated with schizotypy contain two genes of considerable interest to schizophrenia researchers (DTNBP1 within 6p; NRG1 within 8p). These data, albeit modest in amount, provide essential data linking schizotypic psychopathology features to a genetically influenced liability for schizophrenia, consistent with the links established via the adoption studies. Furthermore, the notion of an underlying liability suggests that, in some instances, liability will not express itself phenotypically but be carried along by at-risk individuals just the same. Is there evidence for this? The existence of a clinically unexpressed liability for schizophrenia has long been confirmed. As noted in Chapter 7 in this volume, Gottesman and Bertelsen (1989) found that the rates of schizophrenia among the offspring of MZ twins discordant for schizophrenia were not significantly different. Thus the liability for schizophrenia was passed along “quietly” from unaffected yet genetically at-risk individuals to their offspring. We demonstrated (Lenzenweger & Loranger 1989a) that a high level of schizotypy in a person who had no prior history of psychotic illness did, in fact, predict a higher rate of

342

Schizotypy Viewed from the Laboratory

treated schizophrenia in their biological first-­degree relatives. Again, data consistent with the notion that the liability for schizophrenia could reside quietly (i.e., without any phenotypic indications of psychosis) within a person and knowledge of the presence of schizotypic features (i.e., perceptual aberrations) in such people were predictive of genuine schizophrenia. Thus liability can exist without obvious phenotypic, or symptomatic, manifestations. A third line of evidence—­supportive of the notion of unexpressed liability—can be found in the study of eye-­movement dysfunction in schizophrenia. In short, eye-­tracking dysfunction (Holzman et al., 1988; Levy et al., 1993), which bears no immediately discernible phenotypic connection to overt schizophrenia, is known to be associated with a latent diathesis for the illness. Thus liability can manifest itself in an alternative phenotypic form and be essentially unexpressed insofar as clinical symptoms are concerned. Finally, additional evidence supportive of the notion of unexpressed liability can be garnered from epidemiological data regarding schizophrenia and other related disorders. If the base rate of schizophrenia liability (or the schizotypy taxon) is, in fact, 10% as conjectured by Meehl (1990), then perhaps about 40–50% of those carrying liability for schizophrenia may go clinically “undetected” across the life span (i.e., an estimate derived from combined prevalence of schizophrenia, SPD, and PPD is roughly 5%; see Loranger, 1990; Lenzenweger, Lane, et al., 2007; Lenzenweger, 2006a, 2008). This is so because we assume that 10% of the population is made up of 1% of schizophrenia-­affected cases plus 5% of Cluster-A-related personality disorders, which leaves about 4% or so unaccounted for. The remaining 4% of people making up the 10% estimate, therefore, likely carry the liability for schizophrenia with little or no indication of their genetic diathesis. Taken together, these theoretical and empirical considerations argue strongly for the plausibility of a complex latent liability construct in schizophrenia.

On the Structure of the Latent Liability: Empirical Investigations, Replications, and Considerations Assuming that schizotypy,6 as conceptualized by Meehl (1962, 1990), represents a defensible latent schizophrenia liability construct and the potential research utility of valid schizotypy indexes is evident, a basic question 6 Consistent with the above-­mentioned definition of schizotypy as the latent construct that encompasses schizophrenia liability, it is important to remind ourselves again that schizotypy is to be conceptualized as distinct from schizotypy indicators, which can include phenomenological features as well as other measures (e.g., sustained-­attention deficit, eye-­tracking dysfunction).

What about This “Type” Business

343

about the fundamental structure of schizotypy presents itself—­namely, Is this latent liability continuous (i.e., “dimensional”) or is it truly discontinuous (or “qualitative”) in nature? For example, at the level of the gene, both Meehl’s model (1962, 1990) and the “latent trait” model (Matthysse et al., 1986; Holzman et al., 1988) conjecture the existence of a qualitative discontinuity, whereas the polygenic multifactorial threshold model (Gottesman, 1991) predicts a continuous distribution of levels of liability with a marked step function (i.e., threshold). Clarification of the structure of schizotypy might help to resolve debate concerning appropriate genetic models for schizophrenia, and such information may aid in planning future studies in this area. At the time we undertook our initial studies into the nature of the structure of schizophrenia liability (i.e., late 1980s), nearly all investigations of the structure of schizophrenia liability done to that time had relied exclusively on fully expressed, diagnosable schizophrenia (see Gottesman, 1991), and the results of those studies left the question of latent liability structure unresolved (note that, in expressed schizophrenia, the liability is no longer latent). Some initial attempts at illuminating this issue simply could not address the basic question: Is schizotypy structured in a qualitative fashion? For example, one group of investigators reasoned, from the unimodal distribution of phenotypic schizotypic traits in nonpsychotic individuals, that the unimodal nature of the distribution supported the existence of a continuum of schizophrenia liability (e.g., Kendler et al., 1991). Unfortunately, a unimodal distribution (i.e., absence of bimodality) of scores has essentially no probative value with respect to the issue of continuity–­discontinuity. An apparently unimodal distribution can harbor a mixture of relatively distinct distributions that would actually be suggestive of a meaningful discontinuity in underlying structure of observed values (e.g., phenotypic schizotypic traits). The question regarding the nature of the latent structure of schizotypy was one that required analytical approaches that could answer what can be termed the “taxonic question.” We completed a series of studies that explored the latent structure of schizotypy. Long guided by the endophenotype model, this program of research began with a focus on analysis of psychometric values drawn from a well-­validated measure of schizotypy, the PAS discussed previously, and continued along to investigations of actual ratio-scale-based measurements of sustained attention and eye-­tracking dysfunction completed in the laboratory. Our initial latent structure work used a well-­validated measure of schizotypy, namely the Chapmans’ PAS. In the late 1980s my laboratory staff collected a great deal of data using the PAS from randomly drawn samples of university students. The manner in which we collected the data

344

Schizotypy Viewed from the Laboratory

helped to ensure that our subsequent taxometric analyses would be carried out on data that were reasonably representative of the student body then at the university.7 In our first taxometric study (Lenzenweger and Korfine, 1992a) we analyzed, using Meehl’s MAXCOV method, data from the PAS drawn from well over 1,000 randomly ascertained subjects.8 We (Lenzenweger & Korfine, 1992a) reported that for the eight PAS items we analyzed, the results of our MAXCOV analysis were highly consistent with the presence of a low-base-rate taxonic entity. This meant that it appeared that the latent structure of schizotypy as indexed by the PAS appeared to be qualitative or categorical in nature. Furthermore, the percentage of the population falling into the taxon that was identified seemed to be nearly 10%. We found this figure to be rather astonishing, as Meehl (1990) had conjectured that the base rate (population prevalence) of the schizotypy taxon should be 10%! We performed an additional analysis as part of that study (Lenzenweger & Korfine, 1992a) to determine whether the rate at which each of the PAS items that we analyzed was endorsed was not somehow driving our results. These additional analyses revealed that the endorsement rates for the items in the analysis did not determine estimates of the taxon base rate. This was an exciting time in the laboratory, yet as there was no other literature on this problem based on large nonclinical samples, we were left to wonder whether what we found was robust. As is common in science, we immediately began to wonder whether our finding would replicate, whether other methodological refinements were necessary in future studies to rule out artifact, and whether there were additional controls needed to clarify the results picture. In the next study, again using a large, randomly ascertained sample of subjects drawn from the university setting, we conducted a second MAXCOV analysis of the same eight items as initially examined in our 1992 study (Korfine & Lenzenweger, 1995). In this particular study we also 7 It

is worth noting that, contrary to popular belief, the undergraduate student body at Cornell University is not made up solely of ultra-high academic achievers drawn from a narrow band of upper-crust families. The range of SAT scores among Cornell students is impressive. Also, given that the university is made up of private (endowed) colleges, as well as colleges of the State University of New York system (statutory colleges), the resulting demographic distribution across the entire student body is impressive. Finally, the level of diagnosable psychopathology among Cornell students is highly consistent with that found in the general population (Lenzenweger, Loranger, Korfine, & Neff, 1997; Lenzenweger, 2006; cf. Lenzenweger, Lane, et al., 2007). Although the occasional reviewer has suggested that “there cannot be anything wrong with Cornell students,” the reality is quite otherwise.

8 Random

ascertainment was an important feature of our data set as, even to this day, one will often see samples used in taxometric analysis that have been preselected or conditioned in some a priori manner, and this immediately raises concerns about the validity of any results obtained.

What about This “Type” Business

345

incorporated an additional analysis to address whether the structure of the responses to the PAS might be interacting with the MAXCOV technique to more or less fool us into thinking we were dealing with a latent taxon for schizotypy. But first, consider the results for the schizotypy measure analysis. The MAXCOV analysis once again revealed a characteristic pattern suggestive of a low-base-rate taxon. The frequency of the taxon was 5.0%, clearly lower than our initial finding of 10%. The reason for the discrepancy is probably best understood in terms of sampling fluctuations.9 We (Korfine & Lenzenweger, 1995) also found that the rate at which PAS items were endorsed was not related to the estimates of the base rates obtained in the analyses. This, as in the first study, was reassuring in that it suggested that the base-rate estimates were not simply a derivative of endorsement frequencies for the questionnaire items. One question that would come to dominate the discussion of latent structure studies of schizotypy concerned the nature of those people identified as “taxon” members. This remains an important issue in taxometric studies in psychopathology generally; that is, many taxometric studies put considerable effort into the taxometric analysis, find evidence for a taxon, and then fail to convey any information about the putative taxon members (see Lenzenweger, 2004). Given that we presumably were tapping into a schizotypy taxon in this work, it would make considerable sense that the members of the putative taxon appeared schizotypic in terms of phenomenology. If we found evidence for a “schizotypy taxon” and the members of the taxon bore no semblance of schizotypic features, then we might wonder about the construct validity of the taxon we had detected. Imagine if the schizotypy taxon were made up of extraverted, thrill-­seeking rock climbers—that would make no sense! So we undertook a careful inspection of the putative taxon members, as contrasted with subjects in the sample who were not at all likely to be taxon members. We, fortunately, had additional personality disorder assessment information on these subjects; we had each of them complete the newly developed International Personality Disorder Examination—­Screen (IPDE-S; see Lenzenweger, Loranger, Korfine, & Neff, 1997), and we consulted those data. The putative taxon members revealed strikingly elevated levels of schizotypal, paranoid, and schizoid (Cluster A pathology) PD features on the IPDE-S as compared with nontaxon mem9 Consider

what might happen if we were able to repeat this study 1,000 times. What would happen, of course, would be the generation of 1,000 taxon base-rate estimates, some lower and some higher, with a central tendency (the mean) representing a good overall estimate for the base rate. In light of how the subsequent replications have gone for the basic PAS finding, it seems a good estimate of the population parameter would be, in fact, about 10%.

346

Schizotypy Viewed from the Laboratory

bers. Thus the marked presence of schizophrenia-­related personality disorder features in the taxon members argued against the extraverted, thrill­seeking rock-­climber possibility, to our theoretical comfort. As the corpus of studies from taxometric investigations began to grow, so did concern as to whether one could ever “fool the method” or have the results “fool the investigator,” which would lead to erroneous scientific conclusions and inferences. In the Korfine and Lenzenweger (1995) study, we addressed one of the more interesting methodological “worries” that had been in the air, so to speak, at the time. The methodological question that we studied carefully was whether the MAXCOV analytical procedure would be unduly influenced by the format of items fed into the analysis. Was it the case that if the items fed into the analysis had a dichotomous format (i.e., true vs. false, present vs. absent), then the MAXCOV procedure would simply generate results suggestive of a latent taxon? This interesting question was first raised by Golden (1991). One way to examine this issue with real data would be to start with a truly dimensional construct, force the data for that construct into a dichotomous measurement format, and subject these data to a MAXCOV analysis. This is what we did with the well-known dimensional construct of “femininity,” for which we had measurements on all of our subjects. We selected eight items from the well-known Bem Sex Role Inventory (Bem, 1974) femininity scale for MAXCOV analysis (see Korfine & Lenzenweger, 1995, for details), converted these eight items to dichotomous format using a rational median split strategy, and subjected the data to MAXCOV analysis. Our prediction was straightforward—in spite of being converted to a dichotomous format, the MAXCOV analysis should generate results suggestive of a latent dimensional structure for femininity. In theory, the dichotomous measurement format should not force the MAXCOV method to falsely identify the latent structure of femininity as taxonic, and the results strongly supported this hypothesis. The results of this MAXCOV analysis, using dichotomous input, suggested that femininity had a dimensional latent structure, consistent with the corpus of theory regarding femininity as a psychological construct. Thus, using real data, we found evidence that the format of the data entering the MAXCOV analysis did not create spurious results. I undertook a third taxometric analysis of psychometric values derived from schizotypy indicators to further address the issue of the potential impact of data format on MAXCOV taxometric results (Lenzenweger, 1999a). Thus, although in our 1995 study we discounted the possibility that data input format alone would ipso facto drive the results of MAXCOV analysis, the results from the 1992 and 1995 studies were restricted to only

What about This “Type” Business

347

eight items from the PAS, which had a true–false item format. In a new study, I used fully quantitative scores from the entire PAS, as well as two additional schizotypy scales, the Magical Ideation Scale (MIS) and the Referential Thinking Scale (REF), from a large sample of university students (n > 400). The results of this MAXCOV analysis, based on three fully quantitative schizotypy measures, were highly consistent with those obtained previously in the earlier studies, namely that schizotypy, as assessed psychometrically, appeared to have a taxonic latent structure. Moreover, the base rate of the schizotypy taxon was, again, in the range of .10; this time it was actually .13. Also, those subjects that would be thought of as being members of the schizotypy taxon based on an empirical probability estimation procedure (known technically as posterior probabilities) were found to show dramatically elevated scores on an independent psychometric index known to be associated with schizophrenia liability. The basic pattern of results—­ taxonic latent structure, low base rate for taxon—was, of course, welcome as evidence of replication. However, what was more important about this study was the somewhat subtle methodological finding that fully quantitative (continuous) psychometric measures of schizotypy, when analyzed using the same taxometric methods, revealed a pattern of results highly similar to those obtained early with the true–false format data. Thus it appeared less likely that earlier findings that had relied on true–false data gave rise to pseudotaxonicity, or the false impression of taxonic results due to methodological artifact. The basic finding of our laboratory studies of the latent structure of the PAS and related scales has held up and been replicated often in different labs around the world. An early, high-­quality replication came from the Raulin laboratory at the State University of New York at Buffalo. Raulin, Lowrie, and Brenner (1994) reported that their taxometric analysis of the PAS also revealed a qualitative discontinuity underlying the psychometric values, and their taxon base rate estimate was approximately 10% as well. Additional replications followed (MacFarlane, 1996; Meyer & Keller, 2001; Horan, Blanchard, Gangestad, & Kwapil, 2004; Linscott, 2006, 2007). The consistency of these findings has led one reviewer of this literature to view the taxonic nature of psychometrically assessed schizotypy, particularly the positive-­symptom-­oriented component (e.g., perceptual aberrations) as solidly established (Haslam, 2003, 2007). Our original 1992 taxonic schizotypy finding has been repeatedly replicated around the world, in different laboratories, with varying samples, and with measures translated into languages other than English. Thus it was all that more surprising when a report by Rawlings and colleagues (2008b)

348

Schizotypy Viewed from the Laboratory

appeared and claimed strongly that schizotypy was dimensional in nature. This was a particularly striking claim in light of the conclusions drawn in Haslam’s (2003, 2007) own encyclopedic reviews. These authors went further, suggesting, on the basis of their (single) study, that “a re-­evaluation of previous taxonic conclusions regarding the latent structure of schizotypy is indicated” (p.  1640). Rawlings et al. (2008b) argued that skewness of the schizotypy indicators entering into the taxometric analysis accounted for any taxonic findings that emerged in their data. Their conclusion was that a “dimensional” latent structure for schizotypy was more appropriate. The meaning and direction that can be extracted from this study is marred by substantial methodological artifacts in key areas such as sampling,10 a priori conceptualization and assessment of schizotypy (Claridge, 1997), and taxometric simulation methods (see Beauchaine et al., 2008) for a thorough review and critique. Rawlings et al. (2008a), in response to our critique, sought to argue that skewness is a problem in values that can be removed without impact on the genuine meaning of the data. Their approach to skewness was to rely on a simulation technique that has proven to be deeply problematic, particularly when examining data for a low-base-rate taxon such as schizotypy (Beach, Amir, & Bau, 2005; Beauchaine et al., 2008). Skewness is a commonplace phenomenon in distributions of psychopathology measures, and it is not something that can be easily vanquished with a statistical intervention. The statistical transformations to alter distribution shapes (e.g., to normalize) may cause more problems than the skewness itself. If the underlying metric has real meaning, the transformation alters that metric, thus reducing meaning (or clouding interpretation). Nature sometimes delivers up skewed data for a reason. Some of the most interesting people for psychopathologists will live in the outer tails of such skewed distributions. Simply making the skewness “go away” may actually corrupt the observed data more than one can know. A thought question is appropriate here: Do the contrary results of one taxometric study require the reevaluation of all prior schizotypy studies? No, especially given (1) the corpus of countervailing results, as well as (2) the problematic nature of the study in question. 10 For example, Rawlings et al. (2008b), despite the need for great care in ensuring that sampling methods do not contain artifacts that could affect taxometric results, note that 408 of their 1,073 subjects (nearly 38%) were recruited initially for the presence of “out-of-body” experiences. By mixing in such subjects into their overall pool, the authors probably substantially altered the prevalence of schizotypy in their sample vis-à-vis other conditions. Sampling for taxometric research is critically important (see Beauchaine, 2003; Lenzenweger, 2004).

What about This “Type” Business

349

An Interpretive Interlude: What the Taxometric Findings Mean (and What They Don’t Mean) We began this chapter with a discussion of natural kinds, types, or taxa. The gist of that discussion was to define what was meant by a natural kind and to present a basis for explorations directed at detecting a latent taxon, class, natural kind, or subgroup in quantitative data. By any measure, the taxometric of analysis of psychometric values from schizotypy measures has provided a consistent picture that strongly supports the existence of a latent class or natural subgroup of individuals, particularly those studies involving the PAS and its close cousins (e.g., Linscott, Marie, Arnott, & Clarke, 2006; Linscott, 2007). Let us place these results, then, into some form of substantive framework. How do they fit? What do they tell us? What do they not tell us? We must ponder the meaning of the taxometric results that have come together so clearly in terms of our understanding of schizotypy and schizophrenia liability. In short, the taxonic findings that I and others have reported are consistent with the following theoretical positions: (1) Meehl’s principal suggestion that schizotypes are distinct from nonschizotypes (Meehl, 1962, 1990); (2) Matthysse and Holzman’s (Matthysse et al., 1986; Matthysse & Holzman, 1987) latent-trait model of schizophrenia liability (which assumes a qualitative discontinuity in liability); and (3) Gottesman’s (1991) multifactorial polygenic threshold model with the implication of a marked step function (or pronounced threshold) on an underlying distribution of liability. However, we must also ask ourselves, can the method (i.e., taxometric analysis) genuinely speak to whether the observed discontinuity is truly “qualitative” in nature, or perhaps a severe step or jag in an underlying continuum (not unlike Hilary’s Step on Mt. Everest)? Absolutely not! As Meehl (1995) stated years ago, “No statistical procedure is self-­interpreting as to the nature of the inferred theoretical entities or their causal relations. Equating taxon with disease entity with specific etiology with germ or gene is unwarranted and further intensifies psychologists’ antitypological prejudice” (p. 274). Moreover, as we have argued elsewhere (Lenzenweger, McLachlan, & Rubin, 2007): Any statistical approach will necessarily reveal only part of the story and cannot conclusively resolve a substantive issue . . . we believe the substantive discussion regarding the fundamental nature of the latent structure of schizophrenia liability will be informed not only by statistical methods . . . but also by reference to other data from other levels of analysis. (p. 27)

350

Schizotypy Viewed from the Laboratory

Thus we found good evidence for a latent taxon, and its members appear duly schizotypic, as one would predict. Yet one must view taxometric analysis as but one tool in our toolbox, and we have never claimed that we have located anything more than a putative taxon harbored within the psychometric values we have analyzed using MAXCOV (Lenzenweger, 2003).11 Theory-­guided research at other levels of analysis is needed to flesh out the full meaning of our taxometric findings. Moving forward, we will need to establish connections between the putative taxon and other factors of relevance to specific etiology and pathogenesis (causality) in schizotypy and schizophrenia.

Beyond Psychometric Measures and Taxometric Methods in the Exploration of Schizotypy Latent Structure From the beginning of my taxometric work on schizotypy indicators, I argued for the need to move to taxometric study of measures that were not psychometric in nature. The reasoning here was simple: The sorts of measures that I had in mind—­namely, laboratory measures such as indexes of sustained attention and eye-­tracking dysfunction—held considerable appeal owing to their ratio-scale measurement characteristics and objectivity in assessment (i.e., they were free from such potentially annoying factors as response biases). In making this suggestion I was, by no means, denying the utility of the grand and venerable tradition of psychometric assessment. Rather, I wanted to move psychopathologists closer to these new and potentially informative statistical procedures vis-à-vis their theoretical propositions and models (Lenzenweger, 1999). The rich marriage that was possible through the joining of count data (with its ratio-scale nature) with taxometric methods became evident in work derived from the infant-­research laboratory (Woodward, Lenzenweger, Kagan, Snidman, & Arcus, 2000). In this investigation, we were able to explore the latent structure of various behaviors that had been observed and counted (e.g., hyperextension of limbs, back arching, leg movements, crying) in the study of behavioral inhibition and found evidence for a latent taxon of children, separable from the remainder of the others, in a sample of nearly 600 four-month-old infants. With this in mind, I undertook a large-scale, community-based study (Lenzenweger, McLachlan, & Rubin, 2007) of sustained attention and 11 Widiger (2003) serves as an example of inferences drawn from one level of analysis (taxometric results) being overextended to another level of analysis (genetic). See Lenzenweger (2003) for a critical analysis.

What about This “Type” Business

351

smooth pursuit eye movements (eye tracking) in a quasi-­randomly ascertained sample of adult subjects (n = 300) (Lenzenweger, McLachlan, & Rubin, 2007). Deficits in sustained attention, as well as eye tracking, represent, arguably, the most well-­studied and documented endophenotypes for schizophrenia and were thus ideal candidates for this investigation. What would a laboratory study offer to the question at issue here—the latent structure of schizotypy? This study offered the opportunity to (1) move beyond the use of psychometric values, (2) move beyond the university population to the general adult community population, and (3) move beyond reliance on a sole family of methods for latent structure study. The 300 individuals studied had no prior history of psychosis, were evaluated in the laboratory on computerized measures of sustained attention and eye-­tracking performance, and represented a wide range of educational and social class backgrounds. The data collected, as they were fully quantitative, could be analyzed both by taxometric analysis and by another highly regarded, stateof-the-art procedure known as finite mixture modeling (McLachlan & Peel, 2000). What was particularly appealing about finite mixture modeling, although it differs in its mathematical basis from taxometric methodology, was that it offered an alternative approach to the same question. Namely, would there be evidence of a latent taxon or natural group harbored within the overall distribution of scores obtained from the computerized measures of attention and eye tracking? The findings from this study—which used both finite mixture modeling and taxometric analysis—­provided additional important evidence in support of a latent discontinuity within the multivariate space defined by measures of sustained attention and eye-­tracking functioning. The finite mixture modeling results clearly indicated that there were two components residing within the data—not one, not three or more—and that these two components were relatively unequal in size. The first component was rather large and accounted for about 75% of the sample, whereas the second component was smaller, accounting for the remaining 25%. We came to view the second component as the “schizotypy component,” as its members displayed significantly elevated schizotypic features (recalling that these subjects had no history of psychosis) and as they showed a higher rate of treated schizophrenia in their first-­degree biological relatives. A striking feature of the psychiatric family-­history data was that all subjects with a family history of bipolar disorder (a non-­schizophrenia-­related psychotic affective illness) were found within the normal component; thus the schizotypy component was not tapping a generic psychosis risk group. Importantly, the members of the schizotypy component did not differ from those subjects in the “nor-

352

Schizotypy Viewed from the Laboratory

mal” component on sundry background variables such as age, education, general intellectual functioning, maternal education, or paternal education. We submitted the sustained-­attention and eye-­tracking data to a taxometric analysis, as well, and the results from the MAXCOV analysis were highly consistent with those from finite mixture modeling, again providing evidence for a latent discontinuity in data of considerable relevance to schizotypy and schizophrenia. This study paid immense dividends in that (1) laboratory measures were yielding results comparable to those obtained with psychometric values, (2) two mathematically independent statistical approaches yielded highly convergent evidence for the presence of a latent class, and (3) evidence from family history for psychopathology helped to validate the obtained statistical solutions. We worked across levels of analysis—brain-based measures of neurocognition and psychophysiology, individual-­difference measures of schizotypic phenomenology, and between­persons family histories of psychopathology.

An Interesting Sidebar on Latent Structure Issues in the Study of Schizotypy: The Case of Hypohedonia An interesting sidebar in the taxometric study of putative indicators of schizotypy has come from the analysis of values derived from psychometric measures of social anhedonia. Meehl initially viewed hypohedonia as a potential indicator of schizotypy in early formulations of the model (Meehl, 1962); however, he later reformulated his model in light of his changing views on the importance of hedonic capacity in schizotypy. He eventually came to view primary hypohedonia—or a markedly diminished pleasure capacity—as being an extreme condition on a normal-range, quantitative (continuous) polygenically determined personality dimension. That personality dimension could, of course, as with others, interact with schizotaxia en route to the development of schizotypy. Primary hypohedonia was not viewed as directly (causally) derivative from schizotypy per se; it merely represented the low end scores or rank order of the normal range hedonic capacity continuum. However, Meehl (1990) also noted that many schizotypic individuals suffer the consequences of the slings and arrows of life in a particularly malignant manner, and this results in what he termed “aversive drift” (or the proclivity to shift from positive to negative tone across many aspects of psychological and emotional life in response to the negative impact of

What about This “Type” Business

353

schizotypy). The aversive drift process—­affecting many life domains—has particularly pronounced effects, according to Meehl, in the pleasure domain, such that many schizotypes are quite hypohedonic. The hypohedonia of the schizotype, however, is best viewed as a secondary hypohedonia, the net result of the aversive drift process in response to being a genetic schizotype. This theoretical reformulation would, of course, allow for the possibility that hypohedonia-­related measures, when assessed in schizotypes, might actually provide evidence for a latent taxon when subjected to taxometric analysis. In other words, “the phenomenological (psychometric) anhedonia could get its statistical taxonicity from the taxonicity of the schizotype” (Meehl, 2001, p. 190). The appearance of a taxon in the analysis of (psychometric) anhedonia values would, therefore, be functionally ambiguous as to meaning. Such an anhedonia taxon could be the severe end of primary anhedonia congealing in some detectable fashion, or it could represent the impact of schizotypy and the emergence of secondary anhedonia due to aversive drift.12 So what has been found when values from an anhedonia scale are subjected to taxometric analysis? Such a study was done by Blanchard, Gangestad, Brown, and Horan (2000), and the results are intriguing. These investigators used a measure of social anhedonia (Revised Social Anhedonia Scale; RSAS) that was developed by Loren and Jean Chapman in their early work on schizophrenia proneness (Eckblad, Chapman, Chapman, & Mishlove, 1982), as described earlier. Here it is essential to note that the Chapmans devised and revised this particular scale to focus on schizoid withdrawal, and, as a result, the item content of the scale has an interpersonal nonrelatedness quality rather than a hedonic capacity focus. Sample items would be “I attach very little importance to having close friends” (keyed true), “I don’t really feel very close to my friends” (keyed true), “Making new friends isn’t worth the energy that it takes” (keyed true), and “I prefer hobbies and leisure activities that do not involve other people” (keyed true). This content is contrasted with Meehl’s (1964; following Rado, 1960) descriptions of anhedonia that emphasized notions such as “capacity to experience pleasure” (p. 11), “just doesn’t have any fun” (p. 11), or “There is almost no area of experience in which this person seems ever to get a real wallop of pleasures, even when he does things, or things befall him, that normally would, and which he thinks should . . . ” (p. 12). 12 One

could say that neither of these possibilities applies; rather, one might view anhedonia as derivative of a schizophrenia liability. This would be a theoretical proposition that does not derive from Meehl (1990, 2001).

354

Schizotypy Viewed from the Laboratory

In a large sample of university students (n > 1,500) that completed the RSAS, Blanchard et al. (2000) decomposed the RSAS into four subscales13 and found evidence, based on taxometric analysis, that there appeared to be a qualitative discontinuity (a taxon) underlying the RSAS scores. These investigators, based on the taxonic finding and other research, concluded that “reduced hedonic capacity in the social domain (as measured by the RSAS) is an indicator of schizotypy” (p. 93). How could the Blanchard et al. (2000) findings be best understood? Clearly, the mere taxonic nature of the RSAS scores could not be taken to confirm that the RSAS tapped a schizotypy taxon, regardless of other prior taxometric research on schizotypy indicators linked to schizophrenia liability (e.g., PAS).14 Interestingly, Blanchard et al. (2000) suggested that Meehl erred in reformulating his schizotypy model to deemphasize the causal role of hypohedonia. Meehl (2001) himself pointed out that, according to his model, the taxon discovered by Blanchard et al. could represent (1) the low end of the normal range of hedonic capacity or (2) the impact of aversive drift and the statistical appearance of taxonicity in the RSAS brought about by being “dragged along” by schizotypy. This exchange of ideas is an example of the relatively rare and complex dance between theory/model, method, and interpretation, where the study in question was done well yet the theoretical (mis) interpretation of the data (Blanchard) was handled masterfully from the pedagogical point of view by the original theoretician (Meehl). The stage was set for a reinvestigation of the latent structure of hypohedonia. As Meehl (2001) carefully noted, the fact that Blanchard et al. (2000) found evidence for a taxon harbored within RSAS scores did not refute his reformulation of the role hypohedonia played in his model. What else 13 Decomposition of a psychometric measure, such as the RSAS, that was designed to measure a single homogeneous construct and has very high internal consistency into subscales runs the risk of resolving subscales that have diminished substantive meaning. The reason is that the factor analysis of a highly homogeneous item set may actually end up factoring item difficulties rather than substantive content (see Bernstein & Teng, 1989; cf. Lenzenweger, 2004). Clearly, caution is needed when evaluating subscales derived in such a manner. It should be noted that the use of factor analysis for subscale creation discussed here concerns the use of one highly homogeneous measure, not the factor analysis of multiple independent measures for purposes of data reduction. 14 In

mathematics the transitive property of equality is such that if A = B and B = C, then A = C. Application of the transitive property in domains other than mathematics is, however, hazardous. For example, one cannot reason with confidence that if horse A beats horse B in one race, and horse B beats horse C in another race, then horse A will beat horse C in yet a third race. Similarly, in research on hypothetical constructs, latent structure, and fallible indicators, the transitive property is not applicable. One cannot reason with confidence that, if schizotypy is taxonic in latent structure and the RSAS yields evidence of a taxonic latent structure, then the RSAS measures schizotypy.

What about This “Type” Business

355

could be done to shed light on the issue? The substantive discussion was advanced in an important manner through the clever and insightful study done by Richard Linscott, the University of Otago (New Zealand) psychopathologist. Linscott (2007) raised the interesting possibility that the RSAS, though widely used to assess social anhedonia, was not really measuring anhedonia per se; rather, it was really a measure of schizoid detachment or the predisposition not to seek out or enjoy human relationships. In a sense, the RSAS conflates asociality with hedonic capacity, and this diminishes its utility for assessing the latter. Therefore, Linscott (2007) developed and validated an alternative measure of hedonic capacity. His measure tapped pleasure capacity related to socialization, emotion, taste and smell, and exertion, as well as aesthetic and tactile stimuli—that, in his view, more validly sampled the domain of hedonic experience. A review of the item content on Linscott’s “hypohedonia” subscales, indeed, more fully approximates the intent of Meehl’s (1964) description of anhedonia. Linscott applied taxometric analysis to the hedonic capacity subscales and the results were clearly suggestive of a nontaxonic dimensional latent construct. This pattern of results—based on a measure that more closely approximates the hypohedonia construct—was highly consistent with the view that hedonic capacity could represent a quantitative (dimensional) normal-range personality construct. Taxometric analysis of the schizotypy subscale items in Linscott’s data (suspiciousness, disordered thinking, perceptual aberration, magical thinking) revealed clear evidence of a latent taxon. Finally, on an independent laboratory measure of a well-­established schizophrenia endophenotype (sustained-­attention performance), Linscott (2007) found, using contrast analysis, that members of the schizotypic taxon performed much worse (as expected) than either control or hypohedonia subject groups on the attention task, whereas the controls and hypohedonic subjects did not differ. Linscott (2007) concluded that his “results are consistent with Meehl’s (1975, 1987) proposal that hypohedonia independent of schizotypy at the population level and not inherently pathological” (p. 236) and the role of hypohedonia in “Meehl’s (1990) model need not (italics added) be reconsidered” (p. 237). The substantive position of Meehl (1990, 2001), as well as the fascinating taxometric studies of both Blanchard et al. (2000) and Linscott (2007), offer an unusual suite of contributions in psychopathology research. They are unusual for the theoretical richness that flows through all the papers, as well as illustrative of the importance of basic test construction issues (i.e., content validity and the hypohedonia construct). The utility provided by

356

Schizotypy Viewed from the Laboratory

taxometric analysis in this discussion was also impressive. Those with an interest in taxometric analysis and/or hypohedonia should find this collection of papers particularly illuminating.15

Guidelines for Conducting and Consuming Taxometric Research The research literature dealing with taxometric analysis has grown immensely over the past 25 years, and that growth shows no sign of slowing. Both published research reports and unpublished reports such as doctoral dissertations continue to appear at a stunningly high rate. I suspect we are not that far from a “point-and-click” software program for taxometric analysis, a development that will serve to increase the corpus exponentially (not unlike the situation when factor-­analysis routines became easy to use). I for one have had a steady flow of taxometric manuscripts submitted to research journals landing on my desk for many years and have had the opportunity to study many different applications of the family of taxometric methods to many different problems in psychological science and beyond. In doing so, I have kept a rather informal log of the various issues that have come up in the review of those many manuscripts. I published (Lenzenweger, 2004) a version of this set of notes on invitation in the Journal of Abnormal Psychology; therefore, I do not repeat those concerns, admonitions, and suggestions here. I would like to provide for the reader, however, my Reader’s, Writer’s, and Reviewer’s Guide to Assessing Taxometric Research Reports for handy reference (Box 11.1). I am reliably informed that a number of colleagues, students, journal editors, and other reviewers have found this list useful in examining taxometric reports. It is by no means definitive or exhaustive but rather a reasonable starting place for all those interested in taxometric research. It may help those so interested to separate the wheat from the chaff in the growing taxometric database. 15 I would add to this discussion of primary hypohedonia, secondary hypohedonia, and aversive drift consideration of what Sefton & Cantor-Graae (2005) refer to as “social defeat.” Social defeat refers to a subordinate position or outsider status in society, often found among migrants to a society, in which they are faced with intense social competition. Such social defeat might reflect the impact of external forces on the individual, but possibly, I suggest, it may also represent the demoralization and negative tone associated with the presence of schizotypy (or, of course, the interaction of social forces and schizotypy).

What about This “Type” Business

357

On the High Seas of Taxometrics and the Journey Ahead My students inevitably ask, “What lies ahead for taxometric analysis?” “What are the problem areas?” and “How do I learn more?” The last question is, perhaps, the easiest to answer. As suggested earlier, a good place to start is in reading Meehl’s papers on the topic, specifically Meehl (1973), Meehl and Yonce (1994, 1996), and Meehl (1999), as well as the relevant material in A Paul Meehl Reader (Waller et al., 2006). Additional superb resources can be found in the volume by Waller and Meehl (1998), as well as in tutorials (e.g., Beauchaine, 2003, 2007). As for problem areas in taxometrics,16 it strikes me that some of the more recent recommendations for the simulation of data for use in making decisions regarding the meaning of taxometric results (e.g., Ruscio & Ruscio, 2004) will require careful statistical scrutiny, as well as thorough study through Monte Carlo investigations to determine how useful such approaches are. Such work must be carried out in independent laboratories, as is customary in science, to ensure objectivity and neutrality in evaluation, of course. This process has already begun (Beach et al., 2005), and critical doubts have been raised regarding the approach advocated by Ruscio and Ruscio (2004). In a nutshell, what the Ruscio approach seeks to do is to create simulated data sets that presumably match the key parameters of the actual data under study in an investigation and taxometrically analyze those simulated data in an effort to determine whether the real (actual) data are more suggestive of a latent taxon or latent dimension. In a sense, the approach they advocate seeks to create data, based on a real data set, that might be falsely understood as taxonic when they actually harbor a latent dimension. This approach has both technical problems (see Beach et al., 2005) and conceptual/logic problems. For example, Beach et al. (2005) found that the Ruscio and Ruscio (2004) approach performs poorly in the face of low-base-rate taxa and when the indicators under analysis are correlated above a certain level (i.e., so-­called nuisance covariance). One of the conceptual problems with the approach concerns what I might describe as its lopsided nature. Although the Ruscio and Ruscio (2004) approach seeks to determine whether a dimensional data set might be falsely identified as taxonic, it does not provide a framework for determining whether a truly 16 Critical views (attacks) on the taxometric approach have appeared on occasion. An example of one such attack can be found in Maraun and Slaney (2005) and is rebutted effectively by Grove and Waller (personal communication, June 18, 2008).

BOX 11.1. A Reader’s, Writer’s, and Reviewer’s Guide to Assessing Taxometric Research Reports   1. What is the substantive question? Is the theoretical model at stake well articulated? Is the rationale for a putative taxon or qualitative discontinuity well developed and plausible? Is the reasoning involved minimally ad hoc or post hoc in nature? Are reasoned estimates of the hypothetical taxon’s prevalence provided prior to the actual taxometric analyses?   2. Is the sample used one that makes sense? Was it merely a sample of convenience? If university students are used as subjects, is this a defensible decision on substantive grounds? Is the sample adequately large (n not less than 300)? Did the construction of the sample reveal any artifacts that might influence the taxometric results adversely (e.g., pseudotaxa)?   3. Has the amount of text devoted to a description of taxometric procedures been kept to a minimum? What software was used to do the taxometric analyses?   4. Have the measures used in the analysis been chosen wisely? Were the best available measures used? Were the measures used just because they were available on that sample?   5. What sort of cleaning and/or transformation procedures, if any, were done with the data prior to taxometric analysis? Were the data normalized? Were outliers or extreme values pruned without regard to the substantive implications of such a procedure? Were subscales created out of highly homogeneous measures merely to produce continuous indicators for taxometric analysis?   6. Was more than one taxometric procedure used? Were consistency tests run in a thorough manner? Were other approaches to latent class detection considered or used? Relatedly, were the results of the analysis presented thoroughly and correctly (e.g., were the y-axes scaled consistently across all covariance curve plots of a MAXCOV analysis)?   7. Did the authors use only psychometric measures? Were other measures used (e.g., laboratory measures)?   8. Were any control variables calculated or measured on the same sample in order to show that a dimension reveals itself as a dimension?   9. Are important characteristics of the putative taxon members described (optimally in quantitative terms)? Who are those taxon members? Do they reveal phenotypic characteristics that make sense in light of the substantive issues at stake in the study? 10. Were the results of the analysis interpreted correctly? Has the existence of a putative taxon been used to argue for some theoretical question that it cannot address? Does the investigator understand the extent to which taxometric analysis results may or may not address aspects of a model under consideration? Has the investigator shown an awareness of the level of analysis at which the data were collected and how it speaks to other processes or mechanisms at other levels of analysis? From Lenzenweger (2004). Copyright 2004 by the American Psychological Association. Reprinted by permission.



358

What about This “Type” Business

359

taxonic data set might be falsely identified as dimensional. This asymmetry leads to a second concern, which is the implicit assumption of the Ruscio and Ruscio (2004) approach that a dimensional latent structure is somehow the default latent structure for psychological data or, by analogy, that the null hypothesis in the evaluation of latent structure is that of dimensionality. Although I suspect that over the years we will discover that far more constructs have a dimensional latent structure and that relatively few taxa (natural kinds or types) will be found in the psychological and psychopathology worlds, that does not necessarily justify a default assumption of dimensionality (see Beauchaine et al., 2008, for more detail). As to “what lies ahead?” I think we will continue to see that application of taxometric methods to laboratory-­assessed data will enable researchers to move beyond self-­report psychometric data in taxometric studies. We have tried to do this in my own laboratory with promising results (Woodward et al., 2000; Lenzenweger, McLachlan, & Rubin, 2007). The benefits that accrue from the study of genuine ratio-scale data, as well as rigorously conducted count data, are appreciable. I can only believe that this will advance our understanding of substantive issues of interest, as well as expanding the domain in which taxometric study can be helpful. I would also imagine we will see more attention paid to the relationships between taxometric analysis and other latent structure methods (e.g., latent class analysis, finite mixture modeling), both in terms of the formalisms and of empirical results. Finally, we will always see the misapplication of taxometric methods and misinterpretation of taxometric results, but these sorts of problems would not represent problems with the methods. But happily, I have the conviction that Abusus non tollit usum (“Wrong use does not preclude proper use”).

Part I V

Reactions, Reflections, and Projections

C h a p t e r 12

Thoughts on Impediments, Imaging, Environment, Intervention, and Innovation

The moral of the story is, don’t let anyone tell you what the moral of the story is. —R ichie Stearns, Fingerlakes Grassroots Festival of Music and Dance (2006)

When I decided to subtitle this book “The View from Experimental Psychopathology,” I did it to reflect the fact that I was picking and choosing the issues that I wished to highlight. I have tried to cover them in an accessible manner, especially for beginning psychopathologists, as well as to make them relevant to the general psychopathology research enterprise. In closing this volume I wish to share my thoughts on the issues that I believe continue to hang out there in the wind for our field. Many of these conceptual and methodological issues have been with us for some time, and they are not going to go away any time soon. These substantive and methodological challenges will need to be confronted and surmounted to move our scientific understanding of psychopathology forward. Thus, again, somewhat idiosyncratically, I share my reactions, reflections, and projections on the experimental psychopathology enterprise and, more important, the road ahead. The road ahead will be challenging given the nontrivial impedi

363

364 REACTIONS, REFLECTIONS, AND PROJECTIONS

ments in the way. There will be any number of false starts, blind alleys, and empty intellectual parking lots that may serve to distract us along the way toward real progress. Where are we in schizotypy research? Where are we going in the experimental psychopathology of schizotypy? Will research into the fundamental nature of schizotypy become the purview for geneticists only? No. Will it become the purview of neuroimagers only? No. Perhaps the most important thing for a contemporary student or aspiring psychopathologist to keep in mind is that no single method is going to take us home to the discovery of what has caused schizotypy, schizotypic psychopathology, and schizophrenia. It might be helpful to reread the prior sentence. I say this as each of many research methods we have covered in this volume has many enthusiastic proponents, each with one or two vibrant proponents hoping to mount the podium in Stockholm to claim his or her prize. Thus the discovery process in illuminating the etiology and pathogenesis of schizotypy and schizophrenia will not be found solely in genomics, neuroimaging, psychophysiology, or advanced statistical analyses. To solve this scientific problem we will need to break down boundaries, work together, and share our methods and our different talents with one another. The role to be played by experimental psychopathology in this ongoing scientific saga will be substantial. One sees evidence of the critical role for the experimental psychopathologist already as geneticists and neuroimagers seek to incorporate the probes, tasks, and protocols developed in the experimental psychology and psychopathology laboratory into their research. To wit, observe the number of research projects that now include neurocognitive endophenotypes that have been developed in the experimental psychopathology laboratory.

Reactions The Schizotypic Pathology–­Schizophrenia Connection: Considering the “Damn Strange Coincidence” Argument Some years ago I gave a colloquium on schizotypy at a reputable research institution. I presented a detailed overview of a number of studies from my laboratory, some of which are discussed in this book, and arrayed the final set of findings across a wide domain for schizotypic psychopathology (as an indication of schizotypy) next to findings for schizophrenia in the same domains. I pointed out that we had found deficits in the following areas—­sustained attention, abstraction ability, working memory, attentional inhibition, smooth pursuit eye movement, antisaccade performance, thought disorder, MMPI Personality/Psychopathology, motor performance,



Impediments, Imaging, Environment, Intervention, Innovation

365

somatosensory processing—for schizotypes and that the same pattern had been found among schizophrenia patients. I argued that these empirical planks, in toto, built a compelling bridge between schizotypic deviance and schizophrenia deviance in the same domains, pointing to a possible common underlying liability (i.e., schizotypy). To my surprise, one member of the audience—a seemingly earnest fellow—asked me, “Couldn’t the consistency of your findings for schizotypy and schizophrenia all be a big coincidence?” I thought for a moment and responded: “Are you advocating that the schizotypy model—the theoretical infrastructure underlying this program of work—has no truth value?” He responded, “Well, maybe, I’m not sure, actually, I am thinking, couldn’t it be a coincidence?” I wondered out loud, “Sort of like the possibility that the NASA Apollo 11 crew had no real idea where they were going, and the systems heaped together in the Saturn V command-­service modules were really not assembled in a manner so as to actually function efficiently and in an integrated fashion, but they got to the moon just the same?” He responded, “Well, maybe, I guess that is possible.” “That would be a damn strange coincidence, don’t you think?” I asked.1 Wesley C. Salmon, the late University of Pittsburgh philosopher of science and student of Hans Reichenbach, argued that if a theory, model, or proposal has no truth value, nothing going for it, or low to no verisimilitude,2 then a set of results that array themselves in such a manner as to be consistent with what a theory predicts is what he termed a “damn strange coincidence” (Salmon, 1984; see also Meehl, 1990). Bringing this down to earth, if schizotypic psychopathology has nothing to do with schizophrenia and if the theoretical argument suggesting that the latent construct “schizotypy” underlies both domains of psychopathology is essentially bogus, then how else can we explain the remarkable congruence between research findings for schizotypic pathology and schizophrenia other than to consider it a “damn strange coincidence”? If the theory has low validity, then the array of findings we have discovered across schizotypic pathology and schizophrenia would be antecedently improbable—which means not likely from the getgo—and we would have no way of explaining the patterning of results other than to throw up our hands and say it was a “damn strange coincidence.” 1 I

found myself wondering if this fellow was putting me on, but based on discussion after the talk, I think that was not the case. This moment during a research presentation puts me in mind of how I have felt when some people at clinical presentations still wonder whether schizophrenia is “just a label” or a “myth” or “a sane reaction to an insane world.” The truth is, some sort of question like this will nearly always come your way sooner or later, out of left field, and you will need to deal with it nonetheless.

2 Verisimilitude

(or truth-­likeness) is discussed in depth by Meehl (1990; see also Waller et al., 2006). The degree of truth value or verisimilitude possessed by a theory or model can vary in a quantitative fashion; it need not be regarded as an “all-or-none” proposition.

366 REACTIONS, REFLECTIONS, AND PROJECTIONS

As scientists, we generally do not subscribe to the damn strange coincidence (Salmon, 1984; Meehl, 1990) model of scientific explanation. That the notion of a latent construct of schizotypy (i.e., schizophrenia liability) has something going for it and helps to explain the congruence of findings across a diverse set of domains for schizotypic psychopathology/personality and schizophrenia strikes me as well supported at this point in experimental psychopathology. Did the astronauts on the Apollo 11 mission make it to the moon by virtue of a big coincidence? Probably not.

Leverage Gained with the Schizotypy Model It is a reasonable question to ask, What leverage is gained on schizophrenia by working within the schizotypy model as proposed here? The leverage provided is considerable. First, empirical research has now built enough bridges between the schizotypic sychopathology/personality phenotype and schizophrenia to view the former as an alternative expression of a common underlying schizophrenia liability. I argued this theoretical position explicitly in 1998 (Lenzenweger, 1998), and I believe the data continue to grow to support the validity of both the bridges and the alternative expression assumption. Second, given that the schizotype as a unit of analysis genuinely has rarely come to the attention of clinicians and, therefore, to conventional treatments of any sort,3 the schizotype does indeed represent a relatively pure culture case of expressed schizophrenia liability, albeit in dilute form. Thus, if one wants to study basic neurocognitive processes, neural circuitry, and so forth uncontaminated by clinical illness, medication, and deterioration, the schizotype truly represents an elegant window for such exploration. Third, inclusion of the schizotype as a schizophrenia-­related phenotype in contemporary genetic and genomic investigations clearly increases the statistical power of such investigations. On this theme, it probably also provides a more accurately devised net by which one can catch polymorphisms of interest—in other words, an expanded phenotype (which includes schizotypic psychopathology) probably has greater construct validity. Finally, but by no means least important, the use of the schizotypy model to organize research in the area of schizophrenia liability, genetics, and so forth is helpful (see Lenzenweger, 2006c). By placing bets, guided by 3 This

is not to say that some schizotypes, like others, have not sought out alternative “new age” therapies (e.g., integrated energy therapy, rebirthing therapy; see Singer & Nievod, 2003) outside the bounds of conventional clinical psychology and psychiatry. I raise this point as, on occasion, clinicians (myself included) will learn from schizotypes during the course of an evaluation that they have tried any number of alternative approaches to dealing with their intense ambivalence, diminished hedonic capacity, interpersonal aversiveness, and transient cognitive confusion before seeking out more traditional help.



Impediments, Imaging, Environment, Intervention, Innovation

367

a model, we are in a better position to create testable and, hopefully, falsifiable conjectures in our scientific work and to be able to allow our search for consistencies in results to be reasonably circumscribed.

Reflections on Neuroimaging: Selling Bridges versus Building Them—Where Are We, Are You Sure?4 We are now in a most fortunate position in psychological science generally and in experimental psychopathology in particular with respect to the tools at our disposal. Foremost among the newly developed tools are the various neuroimaging methodologies (PET, single photon emission tomography [SPECT], fMRI, magnetoencephalography [MEG], diffusion tensor imaging [DTI]) for use in imaging the structure and functioning of the living and active brain. Neuroimaging has come to occupy the energies and interests of any number of experimental psychopathologists (as well as absorbing untold grant funding dollars). However, as of 2010, the insights gained from neuroimaging in schizophrenia and schizotypy can be described as modest without denying their importance in a few specific areas (e.g., illumination of the actively hallucinating brain; Silbersweig et al., 1995). This view is based on two major considerations: (1) we are not appreciably much closer to understanding the origins and development of schizophrenia now as compared to the preneuroimaging period5 and (2) neuroimaging, in the opinion of some, has contributed little to the diagnosis and treatment of schizophrenia. Admittedly, the latter point is a tall order to fill in schizophrenia, no matter how one slices the pie, as one could level this criticism at many laboratory explorations of schizotypy and schizophrenia. However, one hears this criticism at a higher volume for imaging work, probably due, in part, to the considerable resources expended. Today’s students often display a rather knee-jerk proclivity to ask “Has anyone done an imaging study of that?” This tendency typically diminishes over the semester, as that question is normally met with my counterquestion, “Why would you want to do that?” followed simply by “and therefore?” My students have usually learned (or, at least, I hope they have learned) 4 Lest

I be accused of castrative intent vis-à-vis neuroimaging, I would like to go on record as being generally supportive of the enterprise. I have been part of exciting research projects in which neuroimaging has played an important role and seen the methodology complement existing research approaches (e.g., Silbersweig et al., 2007).

5 Advances in the neurobiology of the illness have been made. Consider the elegant model development of Grace (1991) on the tonic and phasic components of the dopaminergic aspects of the pathology. Consider also the fruitful work on glutamatergic-­mediated systems in relation to schizophrenia symptomatology (see Javitt, 2007).

368 REACTIONS, REFLECTIONS, AND PROJECTIONS

that neuroimaging is a new tool—and a rather glitzy one at that—but it does not represent the key to the psychological science knowledge kingdom.6 Encouraging students to adopt a critical attitude toward neuroimaging is challenging at times, especially when they are bombarded by reports in the lay media (e.g., The New Yorker, The New York Times) regarding this-or-that new finding—“where jealousy or virtue lives in the brain” or “what men’s brains want from women.” Imaging is even being sold as a tool in political consulting (“Here’s a Republican’s brain; now there’s a Democrat’s brain”). The presence of colorful depictions of statistical comparisons of changes in blood flow activation are also appealing to many, as they can create, for some, the illusion of certainty in understanding neuronal activity.7 There are several forms of neuroimaging, as mentioned previously. None can claim to be superior to the other in all cases, yet all seek to characterize behavior (e.g., psychopathology) from what is essentially a biological (within the person) level of analysis. Will we explain schizotypy or schizophrenia from one level of analysis? I think not. Although it is something of a truism, I want my students to always remember that complicated phenomena such as schizotypy, schizophrenia, or, generally, psychopathology will not be illuminated or understood from one model, theoretical perspective, methodological technique, disposition, or level of analysis (see Meehl, 1972b; Lenzenweger, 2003; Kosslyn & Rosenberg, 2005; Kendler, 2008). 6 Some

long-time and sophisticated observers of scientific psychopathology research, who have watched new technologies come and go, view neuroimaging with considerable caution as to its ultimate value in resolving important questions in schizophrenia and schizotypy. Although I do not align myself with this view, one of my colleagues describes neuroimaging as the “new phrenology.” Phrenology, which emerged in the 19th century, describes a (pseudoscientific) view, advocated by Franz Gall (1758–1828), that the contours, bumps, and shapes on someone’s skull provided telltale signs regarding personality and psychopathology, ostensibly enabling one to make important clinical predictions for a person. Needless to say, phrenology faded from the scene due to its lack of validity. Phrenology argued (indirectly) that the brain (in the head) had meaningful connections to thought, emotion, and behavior, but it left the tracks in a major way when the bumps on the head told the story. Only time will tell whether neuroimaging technology genuinely advances our understanding of schizophrenia and schizotypy. We may (or may not) move beyond neuroimaging methods, only to look back and see all of it as something of a distraction.

7 The

view on these pretty pictures is not simply my own. Consider the following, by recognized experts: Despite the language used to discuss them, the brain images displayed in scientific publications and in the popular press are not representations of changes in brain neuronal activity or areas of “activation,” or even the magnitude of the BOLD signal. Rather, the images are computer-­generated, color-coded “maps” of statistically significant comparisons. It is important to stress that the finding of statistically significant differences and a measured change in the actual magnitude of the signal acquired are not necessarily interchangeable. (Fitzpatrick & Rothman, 2002, p. 807)

To be sure, numbers and data can fool us as well if we are not alert to their impact on our decisions (Gigerenzer, 2002).



Impediments, Imaging, Environment, Intervention, Innovation

369

To be clear, neuroimaging methodology is very impressive, and, in the right hands, it can be used to begin to gain leverage on some important questions within constraints related to speed and resolution. There is also no doubt that neuroimaging “sells.” Ask any member of a NIMH Study Section in which grant proposal applications undergo peer review if the presence or absence of neuroimaging makes a difference in how an application is viewed. It is not uncommon for reviewers to suggest (almost insist) that investigators consider adding a neuroimaging component to their applications upon revision. Why is this? Consider the following experiments done recently by a Yale psychology graduate student, Deena Skolnick Weisberg, and her colleagues that appeared in the distinguished Journal of Cognitive Neuroscience titled “The seductive allure of neuroscience explanations” (Weisberg, Keil, Goodstein, Rawson, & Gray, 2008). In the first of a clever triad of experiments, she found that scientific explanations that contained neuroscience information (i.e., neuroimaging-based information) were rated as significantly more satisfying than the same basic explanation without such information by novice subjects without a neuroscience background. In the second experiment, Weisberg et al. (2008) found that even students in a neuroscience course in which critical evaluation skills were being taught rated neuroscience-laden explanations as more satisfying than those without such information. Finally, in a third experiment, Weisberg et al. (2008) found that neuroscience experts were not unduly swayed in their views of scientific explanations whether or not neuroscience information was contained therein. These latter data are both somewhat comforting and discomforting. It is comforting that neuroscience experts should be able to read explanations of scientific results in a manner that is appropriately appreciative of what neuroscience information adds (or does not add) to such explanations. These results are discomforting in that the vast majority of the people in psychological science are not neuroscience (or neuroimaging) experts, which includes the vast majority of members of study section review panels and ad hoc reviewers of journal manuscripts.8 In pondering neuroimaging and what it can (and cannot) tell us, I think we should consider four basic questions. 1. In simple terms: Where and how quickly does the interesting stuff happen in the brain? Answer: It happens at the levels of inter- and intracellular transmission, and it occurs at very high speeds. Those research8 Another

caveat to prudent interpretation concerns the rather large correlations between variables that are often reported in neuroimaging studies—­correlations of a magnitude rarely seen in scientific psychology (e.g., rs > .70 or .80) and so large that some refer to them as “voodoo correlations” (Vul, Harris, Winkielman, & Pashler, 2009). Are such rs to be trusted?

370 REACTIONS, REFLECTIONS, AND PROJECTIONS

ers who conduct single-cell recordings are well aware of the high speed at which information is moved through neural pathways (events occur quickly in the brain, typically within milliseconds). This raises the question, To what extent can neuroimaging capture the events we want to see? Is it fast enough to capture events as they happen? Given that events happen at the level of single cells and networks of cells, one must ask whether neuroimaging is fine grained enough to capture the picture we want to capture (or, perhaps, is it too coarse). Are the temporal resolution and spatial resolution of the methods sensitive enough for the study of in vivo brain-based psychological processes? Consider the following analogy: If the brain process or event we want to see represents a pea in magnitude or activity level, yet neuroimaging can resolve only to an expanse of a six-lane highway, will we see the pea? Moreover, if it can only generate results for what happened six exits ago on the highway (the hemodynamic response that follows the neuronal event by 2000 ms), does it capture the pea when we really want to image it (i.e., in real time)? We must confront the issue of speed and resolution in neuroimaging vis-à-vis what we really want to see (or understand). 2. What does the cognitive neuroscientist really see when he or she considers what the fMRI signal taps into? A useful perspective is provided by Fitzpatrick and Rothman (2002): Cognitive neuroscientists, particularly those not actively engaged in fMRI research, when asked the question “what does the fMRI signal measure?” often answer (in decreasing order of frequency and increasing order of accuracy): regional neuronal activity, then incremental changes in regional neuronal activity, and, finally, incremental changes in regional cerebral blood flow. None of these descriptions is completely accurate. An MR physicist would describe the most popular fMRI method, blood oxygen level-­dependent (BOLD) imaging, as measuring the change in the intensity of the nuclear MR signal due to changes in the transverse relaxation time of the protons of water molecules in the blood and brain tissue as a result of changes in hemoglobin oxygenation and blood volume. The difference signal is referred to as having BOLD contrast. (p. 806)

Therefore, it is essential to understand that the fMRI is a method that measures changes in hemodynamic events in the brain; it does not measure neuronal activity in a direct manner.9 Rather, it is only by inference that a 9 An

accessible account of fMRI procedures and issues is that by Cacioppo et al. (2003). Bandettini (2002) offers an excellent overview of the limits of fMRI in terms of spatial resolution, temporal resolution, and interpretation.



Impediments, Imaging, Environment, Intervention, Innovation

371

neuroimager can make statements linking changes in such hemodynamic events and nearby brain tissue (areas). The operative word in the prior sentence is inference. Thus bringing psychological meaning to the statistical comparisons conducted in the analysis of the neuroimaging data is no mean task. This chore, however, is not unique to brain imaging. For example, when a child is asked either to wait for an adult to return to a room in order to get a special treat or to summon the adult back to the room and receive a lesser quality treat, one child will oblige and wait for the adult to return, whereas another will summon the adult to return. We could measure the amount of time it takes until any given child summons (or does not summon) an adult. This dependent variable—the amount of time—then needs to be understood psychologically. What this means is that we have to infer what it means. Does it mean “delay of gratification” and “good ego control” (one possible interpretation; see Mischel, Shoda, & Rodriguez, 1989), or does it merely correspond to how obedient some children are as opposed to others (another interpretation; see Funder, 2007)? We “assign” the psychological meaning to what is measured, which was time to behavior in this example. The same is true, in essence, when trying to “bring meaning”—by inference—to data concerning changes in hemodynamic events and nearby brain tissue in neuroimaging studies. We “infer” what is happening in the brain. 3. The third basic question I routinely pose for my students regarding neuroimaging is, What is the question? As discussed in Lenzenweger (2004), the early period of neuroimaging research consisted of relatively unfocused use of the technology, and there was often no real theoretical question at stake. The reality of this state of affairs stimulated Stephen Kosslyn, the Harvard psychologist and neuroscientist, to write his powerful 1999 paper titled, “If Neuroimaging Is the Answer, What Is the Question?” Clearly one needs to have a question in mind before undertaking a neuroimaging study. There should be a model in place, and there should be some clear sense of what one is trying to do in conducting such an experiment. I would add that the level of post hoc speculation—that is, coming up with a “story”—after the data are in should be kept to a minimum. Let us consider the comments in Box 12.1 and ponder them. 4. Finally the fourth question: Just how reliable is neuroimaging across different laboratory sites? In the rush to embrace the technology of neuroimaging, some research basics were overlooked and only came in for scrutiny once scientists realized that somehow they had missed a step. In the spirit in which we began an exploration of necessary tools for the experimental

372 REACTIONS, REFLECTIONS, AND PROJECTIONS

BOX 12.1. What Is the Student in Psychological Science to Do with Neuroimaging as a Tool for Understanding Mind–Brain–Behavior Relations? We are duly warned by a leading neuroimager in 1999: If neuroimaging is the answer, what is the question? —Stephen M. Kosslyn, PhD (1999) But almost 10 years on, in 2008, we still hear the following regarding neuroimaging: The key is do not go on fishing expeditions. Have specific, testable hypotheses. That’s not currently happening; 98 percent of brain imaging is just blindly groping in the dark. —Vilayanur S. R amachandran, MD, PhD (quoted in Dingfelder, 2008) Overheard recently (plainly and clearly stated among a group of first-rate scientists): Oh, it doesn’t matter what the results are for the neuroimaging study. Whatever they are, I will be able to tell a story from them. —Unnamed world-class cognitive neuroscientist And, the danger, of course, is: As observers and interpreters, human beings are always vulnerable to seeing what they want to see or hearing what they want to hear in data, while disregarding other aspects of the data.

psychopathologist, let us ponder a basic research staple, namely reliability, in relation to neuroimaging. Let us consider the issue of reliability. If Jones is running a cognitive neuroscience protocol on a magnet in New York City, will her results match those obtained by Smith, who is running the same protocol in San Francisco? One would hope so—a hope that assumes reliability. This issue is basic. Imagine if one wanted to analyze data hailing from a new psychometric measure, yet did not have reliability established for the psychometric instrument. How would the instrument and collected data be regarded? The reliability of neuroimaging is no different in that, simply stated, it must show evidence of reliability across sites and comparable technical setups. Reliability assessments for neuroimaging have been explored on a very limited scale, and there are reasons to be both comfort-



Impediments, Imaging, Environment, Intervention, Innovation

373

able and uncomfortable with the level of reliability achieved across sites in neuroimaging research (Casey et al., 1998; Billingsley-­Marshall, Simos, & Papanicolaou, 2004; Manoach et al., 2001).

Impediments to Our Future Progress in Understanding Schizotypy and Schizophrenia It would be relatively easy to reel off a dozen or so candidates for potential conceptual impediments to our future progress in understanding schizotypy and schizophrenia. However, this is not the place for such an extended list. What are the two biggest impediments that we face on the road ahead? First and foremost in order of importance is the issue of heterogeneity. By this I mean heterogeneity at several levels of analysis. For example, heterogeneity is present in the actual phenotype of schizophrenia and in the schizotype in cross-­section, as well as over time (i.e., trajectories). Heterogeneity occurs within the data that we collect for every endophenotype of interest. Heterogeneity probably exists at the level of genetic factors in relation to what we term schizotypy and schizophrenia. I, like very nearly all others in our field, work with the assumption that schizophrenia represents a disease construct that is characterized by some degree of homogeneity. This allows us to assemble patient samples for study, schizotypy samples for study, and so forth. However, as I discussed in Chapter 5, the assumption of homogeneity (even if lip service is given to the reality of heterogeneity) is likely problematic. Simply stated, we need to continue to move forward with a more engaged theoretical and methodological approach vis-à-vis heterogeneity; we need to embrace it. We need to embrace it in our theory development, in our models, and, importantly, in our statistical analytic strategies (cf., Lenzenweger, Jensen, & Rubin, 2003; Lenzenweger, McLachlan, & Rubin, 2007). Failure to fully grasp the challenge posed by heterogeneity will only serve to thwart even the most thoughtful and clever approaches to research in this area. The issue of heterogeneity is intimately and profoundly connected with the notion of schizophrenia as a complex disease and the related genetic/genomic research strategies. First of all, heterogeneity will be present, through and through, in the various indicators we seek to use to tap schizotypy, whether they be signs, symptoms, endophenotypes, or any other feature. It is a complex phenotype, in part, I would argue, because of heterogeneity. Second, the search for genes or susceptibility loci of relevance to schizotypy (schizophrenia liability) must more fully embrace the possibil-

374 REACTIONS, REFLECTIONS, AND PROJECTIONS

ity that the fact that multiple genes seem to be in play with schizophrenia is because there may well be more than one form or type of the illness. That schizophrenia represents a unitary illness with an associated, but still unknown, common polygenic genetic architecture remains, most certainly, an open question. How does this concern about heterogeneity of illness and likely associated heterogeneity among causal genetic factors play itself out? One frequently hears at psychopathology research meetings, “We know that one gene does not cause schizophrenia; there are multiple genes, presumably of small effect at work in the illness.” This sort of statement is normally offered as an objection to simple, single major locus (SML) models, as well as an objection to mixed models (such as Meehl’s). The simple SML models (single gene, no variation in expressivity, complete penetrance) clearly do not fit schizophrenia, and this has been long known. The mixed model proposed by Meehl does fit data when assessed in model-­fitting exercises; however, it does assume a gene of relatively powerful effect (the so-­called schizogene), but the jury is out on the existence of such a gene. However, the statement that schizophrenia must be the result of numerous small­effect genes is often implicitly founded on the assumption that schizophrenia is a unitary, homogeneous illness that possesses a consistent genetic architecture across all cases. The idea that schizophrenia may be a unitary, reasonably homogeneous disorder may simply not be true. Thus, our future efforts, both substantive and methodological, need to take on heterogeneity head-on. We need to view it as a major problem of scientific interest, not merely a nuisance. I would go so far as to predict that we do not solve the schizophrenia puzzle until we resolve the heterogeneity issue. The second major conceptual impediment to our progress in understanding schizotypy and schizophrenia is that there is still far too much rating going on in our laboratories and not enough counting. We need not revisit the relative merits of counting and ratio-scale measurement versus the rating (ordinal scaling at best) approach. Although the reader should surely appreciate the high regard with which I view phenomenology and the value of careful diagnosis and classification, I think that for our field to move forward we need to consistently seek to develop counting-based approaches for our laboratory probes, tasks, and measures. The diagnosis of schizophrenia, more than 100 years after Kraepelin and Bleuler, is still fundamentally at rating-based exercise. The loss in precision that comes from reliance on a rating approach to psychopathology (vs. a counting approach) cannot be estimated easily, though I suspect it is one of the issues that continues to hold back research progress. Don’t rate, count!



Impediments, Imaging, Environment, Intervention, Innovation

375

Thoughts on the Environmental Inputs to Schizotypy and Schizophrenia As far as schizotypy and schizophrenia are concerned, there is surely something going on in the environment that is worthy of our scientific attention. This kind of comment always stirs up some intellectual perplexity for my students; this is so because much of what we do in seminar is discuss the brain, genes, endophenotypes, and analyses conducted within and at the level of the person. Thus, when we tackle the environmental inputs (or at least suspected environmental inputs), some students become worried that they might hear something like “a hideous mother (or father) can raise one in such a manner as to cause schizophrenia.” I usually tell the following story when I see my students verging on this moment of panic for fear that a socialization science explanation of schizophrenia is steaming down the tracks toward them. When I was a clinical trainee completing an externship at the Bronx Municipal Hospital Center (Jacobi Hospital) in the Bronx, New York, I remember vividly seeing an announcement on the bulletin board in the psychiatry department that Seymour Kety, MD, would be presenting a paper on the “environmental causes” of schizophrenia. Long before then I had come to appreciate the role that Kety had played in establishing the importance of genetic influences for the development of schizophrenia through his influential Danish Adoption Studies. As a graduate student interested in schizophrenia, I was truly intrigued by the notion of a Kety presentation on “environmental causes,” because much of what I had learned emphasized that genes were surely involved. However, it was the early 1980s, and there were still readily identifiable pockets of intellectual resistance to the notion of a genetic basis for schizophrenia (though things were changing palpably toward the genetic viewpoint owing to accumulating research data). Thus I was not surprised to overhear remarks by some of the local psychodynamic psychiatrists to the effect of “can’t wait to hear the Kety talk; glad Seymour has finally come to his senses; he is finally going to discuss the role of environment in bringing about schizophrenia; it’s about time.” For those making such proenvironment comments, the “environment” they envisioned was the “schizophrenogenic mother” who was busy doling out “psychoti-genic” double binds, vague and fragmented communication, and emotional coldness to her children, all in the context of marital schism and marital skew. Well, the day came when Professor Kety delivered his lecture, and—good grief—how the environment he had in mind differed from that reflected in the views espoused by the champions of the “schizophrenogenic mother.”

376 REACTIONS, REFLECTIONS, AND PROJECTIONS

Kety discussed issues such as birth complications, viral infections, famine, winter birth, and exposure to various psychoactive drugs (there was essentially no mention of parenting, dyshygenic child-­rearing practices, and/or familial conflict as environmental risk factors). His focus was on these environmental factors as contributors to risk, and he saw them as interacting with a genetically determined liability. This sounds familiar, no? He did not view these environmental factors as causal in any strict sense; rather, they represented stressors. Needless to say, the old-guard psychiatry folk were pretty grumpy as they left the lecture.10 But, as was his way, Kety indeed helped to predict a crisper research focus on environmental factors that might increase the likelihood of the expression of schizophrenia liability or shape the phenotypic expression of that liability along Meehl’s (1962, 1990) continuum of compensation (i.e., level of schizotypic disorganization). Does the environment matter in the etiology and development of schizophrenia? Of course it matters. The best evidence, bar no other, for the role of environmental factors in the etiology and development of schizophrenia comes, ironically, from the same data source that has helped to establish the heritability of schizophrenia—the tried-and-true twin method. In short, the very existence of discordant MZ twins represents a reality that confirms the necessity for us to consider environment as important in the pathogenesis of the disorder. Given that the MZ twins in a given pair have essentially the same (identical) genetic complement,11 then it follows that any difference between the two twins in a pair at the level of phenotype confirms the existence of nontrivial environmental inputs. Consistent with the lecture I heard delivered by Kety almost 30 years ago, we need to continue to look in the environment for clues as to the stressors that could be impacting schizotypy—those features that serve to move one from the unexpressed liability, determined in large part by genes and epigenetic influences, to various expressed levels of disorganization ranging from the relatively nonsymptomatic schizotype to the fully decompensated schizotype, namely, the individual with diagnosable schizophrenia. Simply 10 I, on the other hand, enjoyed the first-rate lecture by a legendary figure in psychopathology research, and I also had had Dr. Kety autograph my copy of The Transmission of Schizophrenia (Rosenthal & Kety, 1968). 11 It

has long been assumed that MZ twins are truly identical, even at the level of their DNA, and that any difference between the members of an MZ pair for a phenotypic trait or disorder must be due solely to environmental influences. There is a growing body of evidence that suggests there are meaningful differences at the level of DNA in MZ-twin pairs. Such differences have been described in terms of epigenetic factors (Petronis, 2006) and copy number variation (Bruder et al., 2008). Thus, although the environment remains the major suspect, so to speak, in understanding differences between members of an MZ-twin pair discordant for some phenotypic characteristic, ironclad statements about identical DNA in MZ pairs are being rethought.



Impediments, Imaging, Environment, Intervention, Innovation

377

put, if you are standing with one foot on a banana peel, you are more likely to slip and fall if someone bumps into you. If we think of schizotypy as the banana peel, then the environment can be thought of as delivering some of the bumps. What are the candidate bumps that might tilt one toward a psychotic spill? They clearly come from an array of different sources in the environment. Very nearly all environmental inputs to schizotypy and schizophrenia are related to relatively small effects in terms of predicting psychotic illness. However, there are now well-­documented environmental inputs that are worthy suspects to play some role in the development of schizophrenia in those at risk for the illness. Notice, I did not say that these environmental inputs cause schizophrenia; rather, they serve as stressors in relation to a compromised system. A candidate list of environmental inputs that have garnered some degree of empirical support in playing a role in schizotypy and schizophrenia includes: noisesome work conditions (Link et al., 1986), exposure to urban environments (Spauwen, Krabbendam, Lieb, Wittchen, & van Os, 2006; Weiser et al., 2007), exposure to cannabis [marijuana] (Barkus & Lewis, 2008; Henquet, Murray, Linszen, & van Os, 2005; Arseneault, Cannon, Witton, & Murray, 2004),12 birth/obstetric complications (especially perinatal hypoxia, prenatal complications; Cannon, 1997; Cannon, Tones, & Murray, 2002; Clarke, Harley, & Cannon, 2006; Byrne, Agerbo, Bennedsen, Eaton, & Mortensen, 2007; Verdoux et al., 1997; Wolff, 1991a, b), season of birth (Bradbury & Miller, 1985), and viral exposures such as influenza (e.g, Brown et al., 2004; Brown, 2006; Dalman et al., 2008; Limosin, Rouillon, Payan, Cohen, & Strub, 2003), as well as Toxmoplasma gondii (Niebuhr et al. 2008; Torrey, Bartko, Lun, & Yolken, 2007). Congenital anomalies, hailing in part from environmental insults, have also generated interest as of late given their association with later schizophrenia­spectrum illness (Waddington et al., 2008). Is there evidence that stressors interact with systems and genotypes known to be of interest in schizotypy and schizophrenia? Yes, there is a growing body of exciting evidence along this vector—a vector that represents an important part of the schizotypy model of schizophrenia (Meehl, 1962, 1990; Lenzenweger, 2006). For example, it is well known that stress adversely affects the dopaminergic system (Deutch, Clark, & Roth, 1990; 12 It

is important to distinguish between an environmental input as a stressor that merely interacts with an underlying liability and an environmental input that causes brain changes, in and of itself, that can lead to psychosis. DeLisi (2008), in reviewing the evidence linking cannabis and schizophrenia, concludes that cannabis does not induce brain structure changes that cause psychosis or schizophrenia. Rather, DeLisi (2008) views cannabis as a potential stressor that likely affects the dopaminergic pathways that are relevant to the emergence of schizophrenia.

378 REACTIONS, REFLECTIONS, AND PROJECTIONS

Thompson, Pogue-Geile, & Grace, 2004) and may serve to augment the dysfunctional phasic dopaminergic response hypothesized to be important to the development of schizophrenia (Grace, 1991). Thus the impact of environment on internal neurobiology awaits greater exploration. Interesting new study designs that link genetics and environmental stressors are beginning to appear; consider, for example, elegant demonstrations of interactions between putative schizophrenia-­relevant polymorphisms and exposure to cannabis (marijuana; Caspi et al., 2005; McIntosh et al., 2007) and exposure to birth complications (Nicodemus et al., 2008).

Projections Putting together a selection of projections for any scientific topic is always an enjoyable thing to do, albeit a little dicey in that one places one’s bets and waits for the horses to run. However, it is my distinct impression that experimental psychopathology and allied disciplines are on the brink of some truly exciting times, with major discoveries likely to occur in the next 10 years or so. This excitement is fueled in part by the new advances in our understanding of neural circuitry in the brain, the accruing knowledge we have regarding the genetic components of liability, and advances in statistical methods that are helpful in sorting through massive amounts of data in an efficient and powerful manner. In this context, I offer a few selected projections.

Intervention Early Detection and Prediction Given our accruing knowledge about the onset of schizophrenia, as well as the manifestation of very early signs of the illness (particularly motor phenomena), advances in early detection and intervention are likely to occur more quickly in the next 10 years than in the prior 60 years or so. The chief advance that I can imagine occurring in this domain is the improvement in the predictive power of screening instruments for early manifestations of schizophrenia. Considerable research has gone into the development of excellent measures of schizotypy, any number of experimental methods have been developed and evaluated in extensive research, and an array of polymorphisms have been associated with schizophrenia and schizotypy. This information, combined in either some additive or configural fashion, in the prediction of schizophrenia liability strikes me as increasingly feasible. I say



Impediments, Imaging, Environment, Intervention, Innovation

379

this with full knowledge that, absent some highly valid genetic test (e.g., number of CAG repeats in Huntington’s disease), we will be faced with false-­positive and false-­negative classifications in any such venture. This is a reality that attends the use of fallible predictors, especially in a situation in which the predicted criterion may be characterized by heterogeneity (i.e., perhaps one is not predicting just one outcome when one is predicting the appearance of schizophrenia; maybe there are multiple disorders in play). Moreover, given the relatively low base rate of schizophrenia, the prediction task will be that much more difficult. This difficulty could be offset depending on the manner in which one wants to include information about schizotypy indicators in any such prediction, assuming schizotypy (schizophrenia liability) occurs in 10% or so of the general population. Where are we with respect to detection of schizotypy? The early genetic high-risk studies of schizophrenia (e.g., New York High-Risk Project) provided us with some interesting leads (e.g., sustained-­attention deficits). Cross-­sectional research on psychometric and clinically defined nonpsychotic schizotypes has yielded important clues as to potential endophenotypes. Clinical symptomatology, notably in the prodromal schizophrenia research, continues to offer clues as to predictive signs and symptoms of schizotypy. Nonetheless, we are still at the early stages. Can we pluck a random person from the general population and offer some informed, principled statement of their likelihood of having schizotypy or perhaps even of developing schizophrenia? No, we cannot do so with assurance. This is THE prediction challenge in psychopathology as far as I am concerned. We must begin to move away from studies of this and that schizotypy group and the description of deficits vis-à-vis some manner of control groups. We need to move more toward prediction based on our understanding of deviance on candidate endophenotypes that have not been assessed in persons conditioned on the presence of increased schizophrenia liability. Studying the predictive efficiency of a putative endophenotype for schizotypy in those deemed a priori to be more likely to be schizotypy positive from the get-go will not illuminate the basic detection task in the general population. Some investigators are pursuing this question using laboratory-­assessed endophenotypes (e.g., Lenzenweger, McLachlan, & Rubin, 2007). Whereas other initial efforts have taken a clinical tack and focused on schizotypic cognition, such as the study by Johnstone et al. (2007), in which schizotypal cognitions predicted schizophrenia-like disease in those with mild intellectual impairment. The large number of prodromal schizophrenia studies should help in this regard; however, it is important to realize that such studies are already focused on persons that many clinicians would describe as symptomatic (some informed researchers see prodromal patients as having

380 REACTIONS, REFLECTIONS, AND PROJECTIONS

one foot in psychosis, so to speak, already). These studies do hold potential, perhaps more for understanding the so-­called “conversion to psychosis” process and for illuminating some aspects of the prediction challenge. We still need to see prediction evidence from studies that begin by screening large numbers of putatively nonpsychotic individuals on measures and endophenotypes of interest. There remains a fundamental gap in this area—that is, studies that begin by assessing deviance on some index or endophenotype of choice and then determining how well such deviance predicts later illness. This type of prediction is really where the rubber will meet the road. Ideally, any rigorous and rich prediction approach will utilize, in some configuration, information from genomics, laboratory measures of endophenotypes, and appropriate statistical models (e.g., finite mixture modeling, taxometric analysis). Much work needs to be done to improve the efficiency of the prediction framework in schizotypy and schizophrenia. In comparison with Huntington’s disease (Kremer et al., 1994; Greenamyre, 2007), in which the number of CAG repeats in exon 1 of the gene that encodes huntingtin protein is predictive of disease, we have a long, long way to go.13 A related issue concerns the issue of “conversion” to psychosis as it is known among prodromal researchers. Although this issue is by no means a new issue in the clinical world, the research world has begun to take a much greater interest in what factors cause conversion to psychosis. I would suggest that a potential gold mine exists here in that, although it would be interesting to know what causes conversion to psychosis—­especially at the cellular and neural circuitry levels—it would be equally, if not more, important to determine who does not develop schizophrenia. Experimental psychopathologists should not neglect this important avenue for insights. What causes conversion? How do schizotypes and schizophrenia patients differ?

Early Intervention and the Risk of Playing God As one who still sees patients clinically in my office practice, I am as attentive to the developments in the area of early intervention as I am to the developments in prediction. When I am treating a young person in the first 13 In

this discussion of early detection and prediction, one can still speak of early detection and prediction even without a full understanding of the pathogenesis of schizophrenia. For example, considering the Huntington’s disease situation with respect to pathogenesis, although detection and prediction are now very efficient, a debate regarding transcriptional dysregulation versus mitochondrial impairment as regards pathogenesis continues (Greenamyre, 2007). Students wishing to learn more about the interface of genomics and modern medicine and disease will find a helpful introduction in Guttmacher and Collins (2002).



Impediments, Imaging, Environment, Intervention, Innovation

381

episode of schizophrenia—or, more typically, in the period following the first episode—I often wonder what could have been done to prevent this. It is a truism in clinical psychopathology that we all want to engage in prevention—­ideally primary prevention, but most of us would even settle for secondary prevention. The harsh reality is that what we really continue to do is some form of tertiary prevention; even so-­called prodromal studies with early intervention strategies tend to be treating a patient who is already somewhat symptomatic. There are clearly more questions here than there are answers to ponder. To what extent can we intervene early in an effort to ward off an emerging schizophrenia? How best to do that? Should it be done using psychopharmacological agents that are used to treat clinical illness, albeit in lower doses? What are the costs and benefits in carrying out such early intervention? Importantly, what are the ethical issues in such early intervention work? What would it mean to be treated for prodromal schizophrenia when the diagnosis was wrong (i.e., a false positive)? Would this increase the risk for other adverse outcomes (e.g., suicide)? What are the risks associated with exposure to potentially disabling (even life-­threatening) side effects of medications used in early intervention programs? Are there elevated risks for other adverse outcomes, even in the case in which someone has been correctly identified as en route to schizophrenia and early intervention is instituted (so-­called true positives; see Corcoran et al., 2005; Cornblatt, Lencz, & Kane, 2001)? How do the ethical issues confronting the early interventionist in schizophrenia differ (or not differ) from those facing other early intervention quandaries in brain-based illness (e.g., Alzheimer’s disease; Post, 2001)? A review of all the ethics involved is prohibitive here; however, the experimental psychopathologist must ponder these issues, as our work indeed seeks to advance the understanding of psychopathology (including early detection). One thing is certain regarding efforts at early intervention, particularly those with a psychopharmacological basis: The decision to intervene early must be examined very carefully from numerous vantage points, first and foremost those related to clinical care, the potential life course of the patient, and, without a doubt, ethics. These decisions must be done fully insulated from the desires and influences of the pharmaceutical industry. No amount of free pens, clipboards, dinners at five-star restaurants, chunky honorariums for giving PowerPoint presentations pushing a new medication to physicians’ groups, and/or “all-­expenses-paid-­exclusive-­Caribbean­getaways” should be allowed to dictate the decisions made on such issues as early intervention.

382 REACTIONS, REFLECTIONS, AND PROJECTIONS

Innovation (Paths Waiting to Be Probed and Mapped) A fair portion of this book has been devoted to research strategies that are intended to combine the best of the experimental psychopathology laboratory, genomics/genetics, and the methods (both conceptual and statistical) that we use to gain leverage on schizotypy and schizophrenia. By way of projections regarding innovation, I point to several areas to which I believe we need to direct our energies. As regards neuroimaging, I would like, once again, to state my enthusiasm for the approach. Lest my critical attitude as reflected in some of my comments be misunderstood, allow me to say that we need to push to get that 2% of neuroimaging research deemed to be of good, model-­driven, hypothesis-­testing quality (as suggested by Vilayanur S. Ramachandran; see Box 12.1) to a greater proportion. Creative and rigorous neuroimaging work is both expensive and takes considerable time, effort, and intellect. Thus, with all due respect to the fascination that many have with neuroimaging, I would argue that if someone does not have the time, resources, and creative juices to do it well, then perhaps they should do something else. We need a literature that we can read with confidence, not a litter-ature. One neuroimaging methodology that I believe will potentially yield considerable gold is the newer method known as diffusion tensor imaging (e.g., Cascio, Gerig, & PIven, 2007). Diffusion tensor imaging may be ideally suited to one of the vexing challenges of our understanding of the human brain—it is geared toward illuminating connectivity of neural pathways, and that is precisely the map we need to develop to better understand schizotypy, schizophrenia, and, for that matter, all other forms of psychopathology. I think a quality diffusion tensor imaging study of schizotypes and first-­episode schizophrenia patients, suitable psychiatric control groups, and normals would be a first-order study. As regards genetics, genomics, endophenotypes, phenotypes and more, the future ahead is exciting indeed, with ample opportunities for the experimental psychopathologist to be involved. A list of possibilities can be generated easily and is surely not exhaustive by any stretch. We need to increase our understanding of epigenetics in relation to the development of schizotypy and schizophrenia. Remember those ligers (and tigons). For example, we need to understand how epigenetic influences can account for discordance for schizophrenia in twin pairs (Wong, Gottesman, & Petronis, 2005). We need to determine, for example, to what extent some of the endophenotypes that we might be interested in probing are either the result of epigenetic factors or, perhaps, influenced by epigenetic factors. We must



Impediments, Imaging, Environment, Intervention, Innovation

383

ponder the role that structural variants in the genome will play in influencing our thinking about the pathogenesis and development of schizotypy and schizophrenia. Is schizophrenia the result of relatively rare structural variants, such as copy number variations (Walsh et al., 2008)? Our triedand-true genetic workhorse methodology—the twin-study method—can continue to yield potential gold on this issue. Could structural variation help to explain discordance for schizophrenia in MZ-twin pairs? Clearly, somatic mutation can occur in one twin of a pair and not in the other. The exciting possibilities for research in this area are presaged by Bruder et al. (2008), a study that reported that structural variants can occur in one twin and not the other. The endophenotype concept in psychopathology is roaring along the tracks of many research laboratories around the world, and justifiably so (see Ritsner & Gottesman, 2009; Chen et al., 2009). The endophenotype approach, long advocated by Gottesman (e.g., Gottesman & Shields, 1972; Gottesman & Gould, 2003) and implemented in empirical studies for years (e.g., Lenzenweger & Loranger, 1989a), is likely to provide considerable leverage with respect to schizotypy. This is so for two reasons: (1) many endophenotypes are measured with greater precision and reliability than the diagnosis of the polythetic phenotypes of schizophrenia or schizotypal personality disorder and (2) a focus on more basic, oftentimes neurocognitive, psychophysiological, and/or psychomotor processes will provide an approach for getting around heterogeneity (i.e., by embracing it with good, ratio-scale, quantitative measures appropriately amenable to statistical analyses). A tall order remains for the panorama of potential endophenotypes—­ especially the particularly promising ones, such as sustained-­attention deficits, working-­memory deficits, and eye-­tracking dysfunction—and that means that we must illuminate their underlying genetic architecture. This will require the dedication of considerable resources and energies within the context of an appropriately designed empirical study.14 Excellent strides in this direction are under way in terms of analytic approach (see Lenzenweger, McLachlan, & Rubin, 2007; Sung et al., 2009), as well as actual genomic study (Tuulio-­Henriksson, Perälä, Gottesman, & Suvisaari, 2009). 14 Although

there have been initial forays into the study of the genetics of endophenotypes in schizophrenia, some of these efforts lack proper methodological safeguards. For example, at a minimum, any study of the genetics of endophenotypes must commit resources to maintaining experimental blinds at several points in a protocol. Thus those personnel who recruit subjects for study, with full knowledge of their personal clinical status, as well as that of their family members, should not also be the same personnel who conduct the testing on those subjects willing to participate. The importance of the blind cannot be overstated in experimental psychopathology research.

384 REACTIONS, REFLECTIONS, AND PROJECTIONS

I would also like to suggest that we will need to flip some endophenotypes on their heads and try to understand good performance on the tasks and what distinguishes schizophrenia patients or schizotypes who perform well on such tasks (an approach reflected in the clever study of ”good” WCST performance by Thurston-Snoha & Lewine, 2007). There are other additional challenging issues that will face the experimental psychopathologist hoping to illuminate the basic nature of schizotypy, as well as help in the development of prediction strategies for the condition. Without developing these ideas deeply, I think there are three issues that should be confronted, and one might view these as more theoretical than otherwise. Firstly, as regards liability, if we assume that schizophrenia and schizotypic pathology hail from a common, homogenous liability (i.e., schizotypy), then considerable effort should be directed at trying to unravel whether those factors that contribute to liability—­especially genetic factors—are simply summed together in an additive fashion or whether, as alluded to earlier, the “shape” or “configuration” of the influences matters. Second, regarding the notion of heterogeneity, any serious student of schizotypy and schizophrenia must confront and engage heterogeneity. We cannot simply assume heterogeneity is not there. The level at which heterogeneity exerts its influences as detailed earlier—­genetic, pathology, and/ or phenotypic expression—will need to be explored in a more fine-­grained manner. Are we indeed looking at an illness with a final common pathway, or are we looking at multiple illnesses, unfolding over multiple pathways, and linked together only coarsely through a noisy, inconsistent, and plastic phenotype? Third, a more thoroughgoing analysis of why schizotypy continues to “hang around” in the human population is warranted. Should it not get selected out? Does it need to confer some benefit to maintain (cf. the notions of developmental instability and balancing selection; see Keller & Miller, 2006). These are clearly “big” issues that require considerable breadth and depth of consideration; however, they should be addressed alongside the highly focused laboratory study of putative endophenotypes. Finally, I got into this business by attending to individual differences. The more we learn about individual differences at the level of the individual, the more we potentially learn about underlying neurobehavioral systems (e.g., Depue & Lenzenweger, 2001, 2005). Thus the individual difference perspective should yield very useful information regarding schizotypy in the years to come. This is so because the individual-­difference approach is implicit in the endophenotype approach, the stance of the clinical observer, and the study of individual growth across the life course (see Lenzenweger, Johnson, & Willett, 2004). To this end, I ponder the question, What is it



Impediments, Imaging, Environment, Intervention, Innovation

385

like to be a schizotype? What is the social–­cognitive–­affective world like for such individuals, beyond what we think of as clinical dysfunction? The life­course trajectories of schizotypes remain to be explored using the rich new methods of longitudinal analysis that tap individual differences in search of potential group-based trajectories in longitudinal perspective. My students often ask me, “What more can we learn about the personalities of those persons we designate as schizotypic?”15 This is a good question. I am not entirely sure that the current approach to academic personality psychology has much to offer our understanding of the schizotype. For example, it does not strike me that we are going to see much in the way of gold coming from the application of the so-­called five-­factor approach to the study of the schizotype. This may be due to at least two factors. First, the reality seems to be that the schizotype is genuinely cut from different cloth as compared with other individuals owing to the presence of the latent liability for schizophrenia. This is true whether one subscribes to a taxonic view of latent liability that hails from taxometric and other latent class-type analyses or to the view that there are numerous polymorphisms that, in certain allelic configurations, throw one into a different risk category (e.g., COMT, val-val), particularly when they sum past a given threshold. Thus it may genuinely be the case that the personality processes that we see as relevant to the vast majority of people who do not carry a liability to schizophrenia are simply irrelevant (or less relevant) in the study of personality processes in schizotypy and schizophrenia (see Depue & Lenzenweger, 2001, 2005). This view raises the issue as to whether one ever has the opportunity to view the development of personality in any sense akin to normative within the schizotype. Might it be that the latent liability for schizophrenia simply begins to exert its influence on brain development from the moment of conception and that one never really gets to see what one might call “normal personality development” in such schizophreniaprone persons? A second possibility is that the prevailing theoretical systems that claim to map normal personality are, by definition, rather constrained and thus simply may not include factors or dimensions of relevance to a person carrying the liability for schizophrenia. For example, does it make a great deal of sense to discuss neuroticism (at either the coarse factor or finer-­grained15 For

some students this question is intended to address various unusual aspects of the schizotype’s experience, such as oddities in time perception, conditional reasoning, olfactory sensitivity, unusual creativity, alternative belief systems, interest in extrasensory perception (ESP), and so on. For others the intention is really one that is directed at personality per se, namely, those underlying processes that operate interactively to create what we call personality.

386 REACTIONS, REFLECTIONS, AND PROJECTIONS

facet level) in the case of someone at risk for schizophrenia by virtue of being schizotypy positive? The anxiety and negative-­affect components of most superfactors identified as neuroticism may not map the intense anxiety of the schizotype whose anxiety hails from a morbid anxiety associated with interpersonal contact. To move forward we need to break away from more traditional approaches to personality and individual differences (e.g., questionnaire measurement of superfactors) and continue to move more in the direction of neurobehavioral systems (e.g., Depue & Lenzenweger, 2001, 2005) and the integration of affect, emotion, and social cognition within a laboratory-based neuroscience (e.g., Ochsner, 2008). In doing so, we might have a chance at describing the personality/psychological processes thought to reside within the schizotype—sort of all that other interesting stuff in Meehl’s model (1962, 1964, 1990, 2001). Perhaps the most important message I would want to leave with the reader, as reflected in the Stearns quote at the beginning of this chapter, is to pursue your own interests16 —learn what you can from the work of others, but do not allow it to limit you. Follow your own path.

16 There

is an increasing emphasis on the research scene today to, as I like to say, “do science by committee.” In this model, one convenes lots of scientists, conducts various polls and opinion surveys, and then decides, on the basis of the results, what tack the field should take. One might even use such an approach to cook up a “top 10” or “top 20” “facts about schizophrenia list.” However, as the saying goes, “a camel is a horse built by committee.”

App e n d i x A

Summary Rating Sheet from Manual for Use with Checklist of Schizotypic Signs

Name 

  Sex 

  No. 

Date  Rater  P. E.Meehl

  Hours contact 

Diagnosis   Check (X) those symptoms or traits which you are highly confident are present, and in the degree implied by the phrase and its modifiers. Thus, if “Ambivalence” is present, but is not clearly “intense,” this sign should not be checked. Scoring, weighting, cutting, and validation are based on such strict rating instructions. Whatever your views about the diagnostic meaning of these signs, please try to set all such thoughts aside, judging each item “by itself” as objectively as possible.   1   1 Ambivalence, intense   2   3 Anhedonia [pleasure-deficit]   3   3 Body-image aberrations   4   1 Chaotic sexuality   5   3 Cognitive slippage   6   1 Countertransference strain on you   7   1 Deflated self-esteem: Severe + inappropriate + diffuse   8   3 Dependency, demandingness

  9   2 “Different from others” feeling explicitly stated 10   2 Distrust, testing operations, closeness-panic 11   1 Failure to achieve, gross [corrected for capacity] 12   2 Flat or spotty affectivity 13   1 Hatred of mother, manifest, expressed 14   2 Magical ideation or action

Armchair weights by Paul E. Meehl. Reprinted from Manual for Use with Checklist of Schizotypic Signs. Copyright 1964 by Paul E. Meehl. Reprinted with permission from Leslie J. Yonce. Manual for Use with Checklist of Schizotypic Signs can be downloaded at www.tc.umn.edu/~pemeehl/061ScChecklist.pdf.



387

388 Appendix A 15   6 Micropsychotic episodes [include 21   2 Repetition of material “drift-outs” in interview] 22   1 Self-injury (physical, social, professional, sexual) 16   1 Narcissism, extreme 17   1 Pan-anxiety 18   1 Poor outcome [include clearly premature termination] 19   1 Psychosomatic or neurological signs [See next page]

23   1 Social fear [include marked preference to “be alone”] 24   2 Special signs [See next page] 25   2 Suicidal [attempt, or dread, or chronic “thoughts”]

20   2 Rage: Intense, phenotypic, verbalized, disproportionate       Column 1 sum

     Column 2 sum

Cut at wc = 12/13 for baserate ∂ .40

wc = 

SCHIZOID TENDENCY, YOUR JUDGMENT

1 2 Almost surely absent

3 4 Probably absent or weak

5 6 7 8 Probably present Unmistakable and but moderate strong

19. Psychosomatic or neurological signs

  a. Psychosomatic



  1. Skin (urticaria, neurodermatitis, eczema, dermographia, excoriation,     acne)





  2. Weight loss due to anorexia





  3. Psychosomatic fever





  4. Vasomotor dyscontrol



  b. Conversion symptom



  c. Neurological signs

24. Special signs

  a. Hopelessness



  b. Hypochondriasis



  c. Sensory input compulsion



  d. Noise oversensitivity



  e. Touch aversion



  f. “Night owl” syndrome



  g. Energy depletion

Appendix A

  h. Gullible–suspicious paradox



  i. Spatial–motoric–kinesthetic defect (“proprioceptive diathesis”)



  j. Humor defect



  k. “Paranoid headlights”



  l. Panic when alone



  m. Sleeping with clothes on; or on couch, chair, floor; or with light on



  n. Photophobia



  o. Name or address depersonalization



  p. Facial asymmetry



  q. “Inappropriate appearance”

389

App e n d i x B

Selected Quantitative Measures of Schizotypy

• Cognitive Slippage (Miers & Raulin, 1987) • Magical Ideation Scale (Eckblad & Chapman, 1983) • Perceptual Aberration Scale (Chapman, Chapman, & Raulin, 1978) • Referential Thinking Scale (Lenzenweger, Bennett, & Lilenfeld, 1997) • Revised Social Anhedonia Scale (Mishlove & Chapman, 1985) • Rosen Paranoid Schizophrenia Scale (Rosen, 1962) • Schizophrenia Proneness Index (Bolinskey et al., 2003 ) • Schizotypal Ambivalence Scale (Raulin, 1986; Mann et al., 2008) [Note. This is not the Intense Ambivalence Scale.] • Schizotypal Personality Questionnaire (Raine, 1991) • Schizotypal Personality Scale (Claridge & Broks, 1984) • Social Fear (Raulin & Wee, 1984)



390

App e n d i x C

Getting Started A Provisional Reading List

Classics and Shiny Diamonds Bollen, K. A. (1989). Structured equations with latent variables. New York: Wiley. Cohen, J., and Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Darlington, R. B. (1975). Radicals and squares: Statistical methods for the behavioral sciences. Ithaca, NY: Logan Hill Press. Darlington, R. B. (1990). Regression and linear models. New York: McGraw-Hill. Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical methods for rates and proportions (3rd ed.). New York: Wiley. Gottesman, I. I., & Shields, J. (1972). Schizophrenia and genetics: A twin study vantage point. New York: Academic Press. Maher, B. A. (1966). Principles of Psychopathology: An Experimental Approach. New York: Wiley. Meehl, P. E. (1973). Psychodiagnosis: Selected papers. Minneapolis: University of Minnesota Press. Nunnally, J., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill. Tukey, J. W. (1977). Exploratory data analysis. Reading, MA: Addison Wesley. Wiggins, J. S. (1973). Personality and prediction. Reading, MA: Addison Wesley.

391

392 Appendix C

Currents Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective. New York: Wiley. Bremner, J. D. (2005). Brain imaging handbook. New York: Norton. Carey, G. (2003). Human genetics for the social sciences. Thousand Oaks, CA: Sage. Cicchetti, D., & Cohen, D.J. (Eds.) (2006). Developmental psychopathology (Vols. 1, 2, & 3). New York: Wiley. DiLalla, L. F. (Ed.). (2004). Behavior genetics principles. Perspectives in development, personality, and psychopathology. Washington, DC: American Psychological Association. Lenzenweger, M. F., & Hooley, J. M. (Eds.). (2003). Principles of experimental psychopathology: Essays in honor of Brendan A. Maher. Washington, DC: American Psychological Association. Matthysse, S., Levy, D. L., Kagan, J., & Benes, F. M. (Eds.). (1996). Psychopathology: The evolving science of mental disorder. Cambridge, UK: Cambridge University Press. McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley. Millon, T., Krueger, A. F., & Simonsen, E. (Eds.). (2010). Contemporary directions in psychopathology: Scientific foundations of the DSM-V and ICD-11. New York: Guilford Press. Pearl, J. (2009). Causality: Models, reasoning, and inference (2nd ed.). New York: Cambridge University Press. Rosenthal, R., & Rosnow, R. L. (2008). Essentials of behavioral research: Methods and data (3rd ed.). New York: McGraw-Hill. Rosenthal, R., Rosnow, R. L., & Rubin, D. B. (2000). Contrasts and effect sizes in behavioral research: A correlational approach. New York: Cambridge University Press. Rubin, D. B. (2006). Matched sampling for causal effects. Cambridge, UK: Cambridge University Press. (See references for the Rubin causal model.) Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analyses: Modeling change and event occurrence. New York: Oxford University Press. Susser, E., Schwartz, S., Morabia, A., & Bromet, E. J. (2006). Psychiatric epidemiology: Searching for the causes of mental disorders. New York: Oxford University Press. Waller, N. G., & Meehl, P. F. (1998). Multivariate taxometric procedures: Distinguishing types from continua. Thousand Oaks, CA: Sage. Waller, N. G., Yonce, L. J., Grove, W. M., Faust, D., & Lenzenweger, M. F. (Eds.). (2006). A Paul Meehl reader: Essays on the practice of scientific psychology. Mahwah, NJ: Erlbaum.

References

Abi-­Dargham, A., Kegeles, L. S., Zea-Ponce, Y., Mawlawi, O., Martinez, D., Mitropoulou, V., et al. (2004). Striatal amphetamine-­induced dopamine release in patients with schizotypal personality disorder studied with single photon emission computed tomography and [123l]iodobenzamide. Biological Psychiatry, 55(10), 1001–1006. Abrams, R., & Taylor, M. A. (1983). The genetics of schizophrenia: A reassessment using modern criteria. American Journal of Psychiatry, 140(2), 171–175. Addington, J., Cadenhead, K. S., Cannon, T. D., Cornblatt, B., McGlashan, T. H., Perkins, D. O., et al. (2007). North American prodrome longitudinal study: A collaborative multisite approach to prodromal schizophrenia research. Schizophrenia Bulletin, 33(3), 665–672. Allen, N. C., Bagade, S., McQueen, M. B., Ioannidis, J. P. A., Kavvoura, F. K., Khoury, J. J., et al. (2008). Systematic meta-­analyses and field synopsis of genetic association studies in schizophrenia: The SzGene database. Nature Genetics, 40(7), 827–834. American Psychiatric Association. (1968). Diagnostic and Statistical Manual of Mental Disorders (DSM-II) (2nd ed.). Washington, DC: Author. American Psychiatric Association. (1980). Diagnostic and statistical manual of mental disorders (3rd ed.). Washington, DC: Author. American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (3rd ed., rev.). Washington, DC: Author. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed). Washington, DC: Author. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author. Anders, S., Birbaumer, N., Sadowski, B., Erb, M., Mader, I., Grodd, W., et al. (2004). Parietal somatosensory association cortex mediates affective blindsight. Nature Neuroscience, 7, 339–340. Andreasen, N. C. (1985). Comprehensive Assessment of Symptoms and History. Iowa City: University of Iowa.

393

394 References Andreasen, N. C., & Grove, W. M. (1986). Thought, language, and communication in schizophrenia: Diagnosis and prognosis. Schizophrenia Bulletin, 12, 348–359. Andreasen, N. C. (1986). Scale for the assessment of thought, language, and communication (TLC). Schizophrenia Bulletin, 12, 473–482. Andreasen, N. C., Arndt, S., Alliger, R., Miller, D., & Flaum, M. (1995). Symptoms of schizophrenia: Methods, meanings, and mechanisms. Archives of General Psychiatry, 52, 341–351. Andreasen, N. C., Flaum, M., & Arndt, S. (1992). The comprehensive assessment of schizophrenia symptoms and history (CASH): An instrument for assessing psychopathology and diagnosis. Archives of General Psychiatry, 49, 615–623. Armstrong, J. S. (1985). Long-range forecasting: From crystal ball to computer (2nd ed). New York: Wiley. Arseneault, L., Cannon, M., Witton, J., & Murray, R. M. (2004). Causal association between cannabis and psychosis: Examination of the evidence. British Journal of Psychiatry, 184(2), 110–117. Asarnow, J. R. (2005). Childhood-onset schizotypal disorder: A follow-up study and comparison with childhood-onset schizophrenia. Journal of Child and Adolescent Psychopharmacology, 15(3), 395–402. Avramopoulos, D., Stefanis, N. C., Hantoumi, I., Smyrnis, N., Evdokimidis, I., & Stefanis, C. N. (2002). Higher scores of self-­reported schizotypy in healthy young males carrying the COMT high activity allele. Molecular Psychiatry, 7(7), 706–711. Ayers, M. R. (1981). Locke versus Aristotle on natural kinds. Journal of Philosophy, 78(5), 247–272. Badcock, J. C., & Dragovic, M. (2006). Schizotypal personality in mature adults. Personality and Individual Differences, 40, 77–85. Baddeley, A. D. (1986). Working memory. Oxford, UK: Oxford University Press. Bakan, D. (1966). The test of significance in psychological research. Psychological Bulletin, 66, 423–437. Ballard, J. (2000). Biobehavioral markers of liability to schizotypal psychopathology, verbal memory deficits, atypical patterns of manual performance lateralization, and schizotypal symptoms in relatives of individuals with schizophrenia. Unpublished undergraduate thesis, Harvard University. Bandettini, P. A. (2002). The spatial, temporal, and interpretive limits of functional MRI. In K. L. Davis, D. Charney, & J. T. Coyle (Eds.), Neuropsychopharmacology: The fifth generation of progress (pp. 344–357). Philadelphia: Lippincott Williams & Wilkins. Barch, D. M., Mitropoulou, V., Harvey, P. D., New, A. S., Silverman, J. M., & Siever, L. J. (2004). Context-­processing deficits in schizotypal personality disorder. Journal of Abnormal Psychology, 113(4), 556–568. Barkus, E., & Lewis, S. (2008). Schizotypy and psychosis-like experiences from recreational cannabis in a non-­clinical sample. Psychological Medicine, 38(9), 1267–1276. Baron, M., Asnis, L., & Gruen, R. (1981). The Schedule for Schizotypal Personalities (SSP): A diagnostic interview for schizotypal features. Psychiatry Research, 4, 213–228. Barrett, J. C., & Cardon, L. R. (2006). Evaluating coverage of genome-wide association studies. Nature Genetics, 38(6), 605–606. Beach, S. R. H., Amir, N., & Bau, J. J. (2005). Can sample-­specific simulations help detect low base-rate taxonicity? Psychological Assessment, 17, 446–461. Beauchaine, T. P. (2003). Taxometrics and developmental psychopathology. Development and Psychopathology, 15, 501–527.

References

395

Beauchaine, T. P. (2007). A brief taxometrics primer. Journal of Clinical Child and Adolescent Psychology, 36(4), 654–676. Beauchaine, T. P., Lenzenweger, M. F., & Waller, N. G. (2008). Schizotypy, taxometrics, and disconfirming theories in soft science: Comment on Rawlings, Williams, Haslam, and Claridge. Personality and Individual Differences, 44(8), 1652–1662. Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. Bem, S. L. (1974). The measurement of psychological androgyny. Journal of Consulting and Clinical Psychology, 47, 155–162. Bender, L. (1938). A visual motor Gestalt test and its clinical use. Research Monographs, American Orthopsychiatric Association, 3, xi, 176. Benishay, D. S., & Lencz, T. (1995). Semistructured interviews for the measurement of schizotypal personality. In A. Raine, T. Lencz, & S. Mednick (Eds.), Schizotypal personality (pp. 463–479). New York: Cambridge University Press. Benton, A., & Sivan, A. B. (1993). Disturbances of body schema. In K. M. Heilman & E. Valenstein (Eds.), Clinical neuropsychology (pp. 123–140). New York: Oxford University Press. Berg, E. A. (1948). A simple objective technique for measuring flexibility in thinking. Journal of General Psychology, 39, 15–22. Bergida, H., & Lenzenweger, M. F. (2006). Schizotypy and sustained attention: Confirming evidence from an adult community sample. Journal of Abnormal Psychology, 115, 545–551. Berkson, J. (1946). Limitations of the application of fourfold tables to hospital data. Biometrics Bulletin, 2(3), 47–53. Berner, E. S., & Graber, M. L. (2008). Overconfidence as a cause of diagnostic error in medicine. American Journal of Medicine, 121(Suppl. 5), s2–s23. Bernstein, I. H., & Teng, G. (1989). Factoring items and factoring scales are different: Spurious evidence for multidimensionality due to item categorization. Psychological Bulletin, 105, 467–477. Bickhard, M. H., & Campbell, D. T. (2000). Emergence. In P. B. Andersen, C. Emmeche, N. O. Finnemann, & P. V. Christiansen (Eds.), Downward causation: Minds, body, matter (pp. 322–348). Århus, Denmark: Århus University Press. Billingsley-­Marshall, R. L., Simos, P. G., & Papanicolaou, A. C. (2004). Reliability and validity of functional neuroimaging techniques for identifying language-­critical areas in children and adults. Developmental Neuropsychology, 26(2), 541–563. Blanchard, J. J., Gangestad, S. W., Brown, S. A., & Horan, W. P. (2000). Hedonic capacity and schizotypy revisited: A taxometric analysis of social anhedonia. Journal of Abnormal Psychology, 109(1), 87–95. Bleuler, E. (1950). Dementia praecox or the group of schizophrenias (J. Zinkin, Trans.). New York: International Universities Press. (Original work published 1911) Bleuler, M. (1978). The schizophrenic disorders: Long-term patient and family studies. New Haven: Yale. Blyler, C. R., Maher, B. A., Manschreck, T. C., & Fenton, W. S. (1997). Line drawing as a possible measure of lateralized motor performance in schizophrenia. Schizophrenia Research, 26, 15–23. Boisen, A. (1936). Exploration of the inner world: A study of mental disorder and religious experience. New York: Willett, Clark. Bolinskey, P. K., Gottesman, I. I., & Nichols, D. S. (2003). The schizophrenia proneness

396 References (SzP) scale: An MMPI-2 measure of schizophrenia liability. Journal of Clinical Psychology, 59(9), 1031–1044. Bolinskey, P. K., Trumbetta, S. L., Hanson, D. R., & Gottesman, I. I. (in press). Predicting adult psychopathology from adolescent MMPIs: Some victories. Personality and Individual Differences. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley. Bollen, K. A. (2001). Indicator: Methodology. In N. J. Smelser & P. B. Baltes (Eds.). International Encyclopedia of the Social and Behavioral Sciences (pp.  7282–7287). Oxford, UK: Elsevier Science. Bolles, R. C. (1962). The difference between statistical hypotheses and scientific hypotheses. Psychological Reports, 11, 639–645. Boomsma, D., Busjahn, A., & Peltonen, L. (2002). Classical twin studies and beyond. Nature Reviews (Genetics), 3, 872–882. Boring, E. G., Langfeld, H. S., & Weld, H. P. (1935). Psychology: A factual textbook. New York: Wiley. Botstein, D., & Risch, N. (2003). Discovering genotypes underlying human phenotypes: Past successes for Mendelian disease, future approaches for complex disease. Nature Genetics, 33(Suppl.), 228–237. Bowers, M. (1974). Retreat from sanity: The structure of emerging psychosis. New York: Human Sciences Press. Boyd, R. (1991). Realism, anti-­foundationalism and the enthusiasm for natural kinds. Philosophical Studies, 61(1–2), 127–148. Boyd, R. N. (1999a). Kinds, complexity and multiple realization: Comments on Millikan’s “Historical kinds and the special sciences.” Philosophical Studies, 95(1–2), 67–98. Boyd, R. N. (1999b). Homeostasis, species, and higher taxa. In R. A. Wilson (Ed.), Species: New interdisciplinary essays (pp. 141–185). Cambridge, MA: MIT Press. Bradbury, T. N., & Miller, G. A. (1985). Season of birth in schizophrenia: A review of evidence, methodology, and etiology. Psychological Bulletin, 98, 569–594. Braver, T. S., Barch, D. M., & Cohen, J. D. (1999). Cognition and control in schizophrenia: A computational model of dopamine and prefrontal function. Biological Psychiatry, 46, 312–328. Bridgman, P. W. (1927). The logic of modern physics. New York: Macmillan. Broekma, V., & Rosenbaum, G. (1975). Cutaneous sensitivity in schizophrenics and normals under two levels of proprioception arousal. Journal of Abnormal Psychology, 84, 30–35. Brown, A. S. (2006). Prenatal infection as a risk factor for schizophrenia. Schizophrenia Bulletin, 32(2), 200–202. Brown, A. S., Begg, M. D., Gravenstein, S., Schaefer, C. A., Wyatt, R. J., Bresnahan, M., et al. (2004). Serologic evidence of prenatal influenza in the etiology of schizophrenia. Archives of General Psychiatry, 61(8), 774–780. Bruder, C. E. G., Piotrowski, A., Gijsbers, A. A. C. J., Andersson, R., Erickson, S., de Stahl, T. D., et al. (2008). Phenotypically concordant and discordant monozygotic twins display different DNA copy-­number-variation profiles. American Journal of Human Genetics, 82, 763–771. Bryk, A. S., & Raudenbush, S. W. (1987). Application of hierarchical linear models to assessing change. Psychological Bulletin, 101, 147–158. Brzustowicz, L. M. (2007). Size matters: The unexpected challenge of detecting linkage in large cohorts. American Journal of Psychiatry, 164, 192–194.

References

397

Brzustowicz, L. M., & Bassett, A.S. (2008). Phenotype matters: The case for careful characterization of relevant traits. American Journal of Psychiatry, 165, 1096–1098. Brzustowicz, L. M., Honer, W. G., Chow, E. C., Hogan, J., Hodgkinson, K., & Bassett, A. S. (1997). Use of a quantitative trait to map a locus associated with severity of positive symptoms in familial schizophrenia to chromosome 6p. American Journal of Human Genetics, 61, 1388–1396. Buchsbaum, M. S., Coursey, R. D., & Murphy, D. L. (1976). The biochemical high-risk paradigm: Behavioral and familial correlates of low platelet monoamine oxidase activity. Science, 194(4262), 339–341. Buckholtz, J. W., Sust, S., Tan, H. Y., Mattay, V. S., Straub, R. E., Meyer-­Lindenberg, A., et al. (2007). fMRI evidence for functional epistasis between COMT and RGS4. Molecular Psychiatry, 12, 893–895.. Butzlaff, R. L., & Hooley, J. M. (1999). Expressed emotion and psychiatric relapse: A meta­analysis. Archives of General Psychiatry, 55, 547–552. Byrne, M., Agerbo, E., Bennedsen, B., Eaton, W. W., & Mortensen, P. B. (2007). Obstetric conditions and risk of first admission with schizophrenia: A Danish national registerbased study. Schizophrenia Research, 97(1–3), 51–59. Cacioppo, J. T., Berntson, G. G., Lorig, T. S., Norris, C. J., Rickett, E., & Nusbaum, H. (2003). Just because you’re imaging the brain doesn’t mean you can stop using your head: A primer and set of first principles. Journal of Personality and Social Psychology, 85, 650–661. Calkins, M. E., Curtis, C. E., Grove, W. M., & Iacono, W. G. (2004). Multiple dimensions of schizotypy in first degree biological relatives of schizophrenia patients. Schizophrenia Bulletin, 30(2), 317–325. Cannon, M., Jones, P. B., & Murray, R. M. (2002). Obstetric complications and schizophrenia: Historical and meta-­analytic review. American Journal of Psychiatry, 159, 1080–1092. Cannon, T. D. (1997). On the nature and mechanisms of obstetric influences in schizophrenia: A review and synthesis of epidemiologic studies. International Review of Psychiatry, 9(4), 387–397. Cannon, T. D., Cadenhead, K., Cornblatt, B., Woods, S. W., Addington, J., Walker, E., et al. (2008). Archives of General Psychiatry, 65(1), 28–37. Cannon, T. D., Cornblatt, B., & McGorry, P. (2007). Editor’s introduction: The empirical status of the ultra high-risk (prodromal) research paradigm. Schizophrenia Bulletin, 33(3), 661–664. Cardno, A. G., & Gottesman, I. I. (2000). Twin studies of schizophrenia: From bow-andarrow concordances to Star Wars Mx and functional genomics. American Journal of Medical Genetics: Part C. Seminars in Medical Genetics, 97(1), 12–17. Cardno, A. G., Rijsdijk, F. V., Murray, R. M., & McGuffin, P. (2008). Twin study refining psychotic symptom dimensions as phenotypes for genetic research. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics), 147B, 1213–1221. Cardno, A. G., Sham, P. C., Murray, R. M., & McGuffin, P. (2001). Twin study of symptom dimensions in psychoses. British Journal of Psychiatry, 179(1), 39–45. Cardon, L. R., & Bell, J. I. (2001). Association study designs for complex diseases. Nature Reviews Genetics, 2(2), 91–99. Carey, G. (2003). Human genetics for the social sciences. Thousand Oaks, CA: Sage. Carey, G., & Gottesman, I. I. (1978). Reliability and validity in binary ratings: Areas of

398 References common misunderstanding in diagnosis and symptom ratings. Archives of General Psychiatry, 35, 1454–1459. Carey, G., Gottesman, I. I., & Robins, E. (1980). Prevalence rates for the neuroses: Pitfalls in the evaluation of familiality. Psychological Medicine, 10, 437–443. Cascio, C. J., Gerig, G., & Piven, J. (2007). Diffusion tensor imaging: Application to the study of the developing brain. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 213–223. Casey, B. J., Cohen, J. D., O’Craven, K., Davidson, R. J., Irwin, W., Nelson, C. A., et al. (1998). Reproducibility of fMRI results across four institutions using a spatial working memory task. NeuroImage, 8(3), 249–261. Caspi, A., & Roberts, B. W. (1999). Personality continuity and change across the life course. In L. A. Pervin & O. P. John (Eds.), Handbook of personality: Theory and research (2nd ed, pp. 300–326). New York: Guilford Press. Caspi, A., Moffitt, T. E., Cannon, M., McClay, J., Murray, R., Harrington, H., et al. (2005). Moderation of the effect of adolescent-onset cannabis use in adult psychosis by a functional polymorphism in the catechol-O-methyltransferase gene: Longitudinal evidence of a gene x environment interaction. Biological Psychiatry, 57, 1117–1127. Chan, R. C., & Gottesman, I. I. (2008). Neurological soft signs as candidate endophenotypes for schizophrenia: A shooting star or a Northern star? Neuroscience and Biobehavioral Reviews, 32(5), 957–971. Chang, B. P., & Lenzenweger, M. F. (2001). Somatosensory processing in the biological relatives of schizophrenia patients: A signal detection analysis of two-point discrimination thresholds. Journal of Abnormal Psychology, 110, 433–442. Chang, B. P., & Lenzenweger, M. F. (2005). Somatosensory processing and schizophrenia liability: Proprioception, exteroceptive sensitivity, and graphesthesia performance in the biological relatives of schizophrenia patients. Journal of Abnormal Psychology, 114, 85–95. Chapman, J., Chapman, L. J., & Kwapil, T. R. (1994). Does the Eysenck psychoticism scale predict psychosis? A ten-year longitudinal study. Personality and Individual Differences, 17, 369–375. Chapman, L. J., & Chapman, J. P. (1973). Disordered thought in schizophrenia. New York: Appleton-­Century-­Crofts. Chapman, L. J., & Chapman, J. P. (1977). Selection of subjects in studies of schizophrenic cognition. Journal of Abnormal Psychology, 86, 10–15. Chapman, L. J., & Chapman, J. P. (1978). The measurement of differential deficit. Journal of Psychiatric Research, 14, 303–311. Chapman, L. J., & Chapman, J. P. (1985). Psychosis proneness. In M. Alpert (Ed.), Controversies in schizophrenia: Changes and constancies (pp. 157–172). New York: Guilford Press. Chapman, L. J., & Chapman, J. P. (1987). The search for symptoms predictive of schizophrenia. Schizophrenia Bulletin, 13, 497–503. Chapman, L. J., & Chapman, J. P. (1989). Strategies for resolving the heterogeneity of schizophrenics and their relatives using cognitive measures. Journal of Abnormal Psychology, 98, 357–366. Chapman, J., Chapman, L., & Kwapil, T. (1995). Scales for the measurement of schizotypy. In A. Raine, T. Lencz, & S. Mednick (Eds.), Schizotypal personality (pp. 79–106). New York: Cambridge University Press.

References

399

Chapman, L. J., Chapman, J. P., Kwapil, T. R., Eckblad, M., & Zinser, M. C. (1994). Putatively psychosis-prone subjects 10 years later. Journal of Abnormal Psychology, 103(2), 171–183. Chapman, L. J., Chapman, J. P., & Raulin, M. L. (1976). Scales for physical and social anhedonia. Journal of Abnormal Psychology, 85, 374–382. Chapman, L. J., Chapman, J. P., & Raulin, M. L. (1978). Body-image aberration in schizophrenia. Journal of Abnormal Psychology, 87, 399–407. Chen, E. Y., Wong, G. H., Hui, C. L., Tang, J. Y., Chiu, C. P., Lam, M. M., et al. (2009). Phenotyping psychosis: Room for neurocomputational and content-­dependent cognitive endophenotypes? Cognitive Neuropsychiatry, 14, 451–472. Chen, W. J., Liu, S. K., Chang, C.-J., Lien, Y.-J., Chang, Y.-H., & Hwu, H.-G. (1998). Sustained attention deficit and schizotypal personality features in nonpsychotic relatives of schizophreniapatients. American Journal of Psychiatry, 155, 1214–1220. Chen, Y., Bidwell, L. C., & Norton, D. (2006). Trait vs. state markers for schizophrenia: Identification and characterization through visual processes. Current Psychiatry Reviews, 2, 431–438. Cicchetti, D., & Cohen, D. J. (2006). Developmental psychopathology (2nd ed). New York: Wiley. Cicchetti, D., & Rogosch, F. A. (1996). Equifinality and multifinality in developmental psychopathology. Development & Psychopathology, 8, 597–600. Cicchetti, D., & Rogosch, F. A. (2002). A developmental psychopathology perspective on adolescence. Journal of Consulting and Clinical Psychology, 70, 6–20. Cimpean, D., Torrey, W. C., & Green, A. I. (2005). Schizophrenia and co-­occurring general medical illness. Psychiatric Annals, 35(1), 70–81. Claridge, G. (1997). Theoretical background and issues. In G. Claridge (Ed.), Schizotypy: Implications for illness and health (pp. 3–18). Oxford, UK: Oxford University Press. Claridge, G., & Beech, T. (1995). Fully and quasi-dimensional constructions of schizotypy. In A. Raine, T. Lencz, & S. A. Mednick (Eds.), Schizotypal personality (pp. 192–216). New York: Cambridge University Press. Claridge, G. S., & Broks, P. (1984). Schizotypy and hemisphere function: I. Theoretical considerations and the measurement of schizotypy. Personality and Individual Differences, 5, 633–648. Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319. Clarke, M. C., Harley, M., & Cannon, M. (2006). The role of obstetric events in schizophrenia. Schizophrenia Bulletin, 32(1), 3–8. Clarkin, J. F., Levy, K. N., Lenzenweger, M. F., & Kernberg, O. F. (2007). Evaluating three treatments for borderline personality disorder: A multiwave study. American Journal of Psychiatry, 164, 922–928. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49(12), 997–1003. Cohen, J., & Cohen, P. (1983). Applied multiple regression / correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Cohen, P., Crawford, T. N., Johnson, J. G., & Kasen, S. (2005). The Children in the Community study of developmental course of personality disorder. Journal of Personality Disorders, 19, 466–486.

400 References Coleman, M. J., Carpenter, J. T., Waternaux, C., Levy, D. K., Shenton, M. E., & Perry, J., et al. (1993). The Thought Disorder Index: A reliability study. Psychological Assessment, 5, 336–342. Coleman, M. J., Levy, D. L., Lenzenweger, M. F., & Holzman, P. S. (1996). Thought disorder, perceptual aberrations, and schizotypy. Journal of Abnormal Psychology, 105, 469–473. Collins, L. M., & Sayer, A. G. (Eds.). (2001). New methods for the analysis of change. Washington, DC: American Psychological Association. Condray, R., & Steinhauer, S. R. (1992). Schizotypal personality disorder in individuals with and without schizophrenic relatives: Similarities and contrasts in neurocognitive and clinical functioning. Schizophrenia Research, 7, 33–41. Corcoran, C., Malaspina, D., & Hercher, L. (2005). Prodromal interventions for schizophrenia vulnerability: The risks of being “at risk.” Schizophrenia Research, 73(2–3), 173–184. Corkin, S., Milner, B., & Rasmussen, T. (1970). Somatosensory thresholds: Contrasting effects of postcentral-gyrus and posterior parietal-lobe excisions. Archives of Neurology, 23, 41–58. Cornblatt, B. A., & Erlenmeyer-­Kimling, L. (1985). Global attentional deviance as a marker of risk for schizophrenia: Specificity and predictive validity. Journal of Abnormal Psychology, 94(4), 470–486. Cornblatt, B. A., Lencz, T., & Kane, J. M. (2001). Treatment of the schizophrenia prodrome: Is it presently ethical? Schizophrenia Research, 51(1), 31–38. Cornblatt, B. A., Lencz, T., & Obuchowski, M. (2002). The schizophrenia prodrome: Treatment and high-risk perspectives. Schizophrenia Research, 54(1–2), 177–186. Cornblatt, B. A., Lenzenweger, M. F., Dworkin, R. H., & Erlenmeyer-­Kimling, L. (1985). Positive and negative symptoms, attention, and information processing. Schizophrenia Bulletin, 11, 397–408. Cornblatt, B. A., Lenzenweger, M. F., Dworkin, R. H., & Erlenmeyer-­Kimling, L. (1992). Childhood attentional dysfunction predicts social isolation in adults at risk for schizophrenia. British Journal of Psychiatry, 161 (Suppl. 18), 59–68. Cornblatt, B. A., Lenzenweger, M. F., & Erlenmeyer-­Kimling, L. (1989). The continuous performance test, identical pairs version (CPT-IP): II. Contrasting attentional profiles in schizophrenic and depressed patients. Psychiatry Research, 29, 65–85. Cornblatt, B. A., & Keilp, J. G. (1994). Impaired attention, genetics, and the pathophysiology of schizophrenia. Schizophrenia Bulletin, 20, 31–46. Cornblatt, B. A., & Malhotra, A. K. (2001). Impaired attention as an endophenotype for molecular genetic studies of schizophrenia. American Journal of Medical Genetics (Neuropsychiatric Genetics), 105, 11–15. Cornblatt, B. A., Risch, N. J., Faris, G., Friedman, D., & Erlenmeyer-­Kimling, L. (1988). The Continuous Performance Test, Identical Pairs Version (CPT-IP): I. New findings about sustained attention in normal families. Psychiatry Research, 26, 223–238. Cornblatt, B. A., & Obuchowski, M. (1997). Update of high-risk research: 1987–1997. International Review of Psychiatry, 9(4), 437–447. Craig, J. C., & Johnson, K. O. (2000). The two-point threshold: Not a measure of tactile spatial resolution. Current Directions in Psychological Science, 9, 29–32. Cronbach, L. J. (1957). The two disciplines of scientific psychology. American Psychologist, 12(11), 671–684.

References

401

Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology. American Psychologist, 30(2), 116–127. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52, 281–302. Croskerry, P., & Norman, G. (2008). Overconfidence in clinical decision making. American Journal of Medicine, 121(Suppl. 5), s24–s29. Crow, T. J., Done. D. J., & Sacker, A. (1996). Cerebral lateralization is delayed in children who later develop schizophrenia. Schizophrenia Research, 22, 181–185. Culverhouse, R., Suarez, B. K., Lin, J., & Reich, T. (2002). A perspective on epistasis: Limits of models displaying no main effect. American Journal of Human Genetics, 70, 461–471. Dalman, C., Allebeck, P., Gunnell, D., Harrison, G., Kristensson, K., Lewis, G., et al. (2008). Infections in the CNS during childhood and the risk of subsequent psychotic illness: A cohort study of more than one million Swedish subjects. American Journal of Psychiatry, 165(1), 59–65. D’Amato, M. R. (1970). Experimental psychology: Methodology, psychophysics, and learning. New York: McGraw-Hill. Dana, J., & Dawes, R. M. (2004). The superiority of simple alternatives to regression for social science predictions. Journal of Educational and Behavioral Statistics, 29(3), 317– 331. Danckert, J., Saoud, M., & Maruff, P. (2004). Attention, motor control and motor imagery in schizophrenia: Implications for the role of the parietal cortex. Schizophrenia Research, 70, 241–261. Darlington, R. B. (1990). Regression and linear models. New York: McGraw-Hill. Davies, G., Welham, J., Chant, D., Torrey, E. F., & McGrath, J. (2003). A systematic review and meta-­analysis of northern hemisphere season of birth studies in schizophrenia. Schizophrenia Bulletin, 29(3), 587–593. Dawes, R. M. (1979). The robust beauty of improper linear models in decision making. American Psychologist, 34(7), 571–582. Dawes, R. M. (2000). Proper and improper linear models. In T. Connolly, H. R. Arkes, & K. R. Hammond (Eds.), Judgment and decision making: An interdisciplinary reader (2nd Ed., pp. 378–394). New York: Cambridge University Press. Dawkins, R. (1982). The extended phenotype: The gene as the unit of selection. San Francisco: Freeman. De Boeck, P., Wilson, M., & Acton, G. S. (2005). A conceptual and psychometric framework for distinguishing categories and dimensions. Psychological Review, 112(1), 129– 158. Delawalla, Z., Csernansky, J. G., & Barch, D. M. (2007). Prefrontal cortex function in nonpsychotic siblings of individuals with schizophrenia. Biological Psychiatry, 63(5), 490–497. DeLisi, L. E. (2008). The effect of cannabis on the brain: Can it cause brain anomalies that lead to increased risk for schizophrenia? Current Opinion in Psychiatry, 21(2), 140–150. Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B, 39, 1–38. Depue, R. A., & Lenzenweger, M. F. (2001). A neurobehavioral dimensional model of personality disorders In W. J. Livesley (Ed.), Handbook of personality disorders: Theory, research, and treatment(pp.136–176). New York: Guilford Press.

402 References Depue, R. A., & Lenzenweger, M. F. (2005). A neurobehavioral model of personality disturbance. In M. F. Lenzenweger & J. F. Clarkin (Eds.), Major theories of personality disorder (2nd ed., pp. 391–453). New York: Guilford Press. Depue, R. A., Slater, J. F., Wolfstetter-­Kausch, H., Klein, D., Goplerud, E., & Farr, D. (1981). A behavioral paradigm for identifying persons at risk for bipolar depressive disorder: A conceptual framework and five validation studies. Journal of Abnormal Psychology, 90, 381–437. Deutch, A. Y., Clark, W. A., & Roth, R. H. (1990). Prefrontal cortical dopamine depletion enhances the responsiveness of mesolimbic dopamine neurons to stress. Brain Research, 521, 311–315. Diefendorf, A.R., & Dodge, R. (1908). An experimental study of the ocular reactions of the insane from photographic records. Brain, 31, 451–489. Dingfelder, S. F. (2008). Do psychologists have “neuron envy”? APA Monitor on Psychology, 39(6), 26. Dror, V., Shamir, E., Ghanshani, S., Kimhi, R., Swartz, M., Barak, Y., et al. (1999). hKCa3/ KCNN3 potassium channel gene: Association of longer CAG repeats with schizophrenia in Israeli Ashkenazi Jews, expression in human tissues and localization to chromosome 1q21. Molecular Psychiatry, 4, 254–260. Dworkin, R. H., & Lenzenweger, M. F. (1983). DSM-III and the genetics of schizophrenia. American Journal of Psychiatry, 140, 646. Dworkin, R. H., & Lenzenweger, M. F. (1984). Symptoms and the genetics of schizophrenia: Implications for diagnosis. American Journal of Psychiatry, 141, 1541–1546. Dworkin, R. H., Lenzenweger, M. F., Moldin, S. O., Skillings, G. F., & Levick, S. E. (1988). A multidimensional approach to the genetics of schizophrenia. American Journal of Psychiatry, 145(9), 1077–1083. Dyson, G., Frikke-­Schmidt, R., Nordestgaard, B. G., Tybjærg-­Hansen, A., & Sing, C. F. (2007). An application of the patient rule-­induction method for evaluating the contribution of the apolipoprotein E and lipoprotein lipase genes to predicting ischemic heart disease. Genetic Epidemiology, 31(6), 515–527. Dyson, G., Frikke-­Schmidt, R., Nordestgaard, B. G., Tybjærg-­Hansen, A., & Sing, C. F. (2009). Modifications to the patient rule-­induction method that utilize non-­additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease. Genetic Epidemiology, 33 317–324. Eckblad, M., & Chapman, L. J. (1983). Magical ideation as an indicator of schizotypy. Journal of Consulting and Clinical Psychology, 51, 215–225. Eckblad, M. B., Chapman, L. J., Chapman, J. P., & Mishlove, M. (1982). The Revised Social Anhedonia Scale. Unpublished test. Madison, WI: University of Wisconsin at Madison. Edell, W. S. (1995). The psychometric measurement of schizotypy using the Wisconsin Scales of Psychosis Proneness. In G. A. Miller (Ed.), The behavioral high-risk paradigm in psychopathology (pp. 3–46). New York: Springer-­Verlag. Egan, M. F., Goldberg, T. E., Kolachana. B. S., Callicott, J. H., Mazzanti, C.M., Straub, R.E., et al. (2001). Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proceedings of the National Academy of Sciences, 98, 6917–6922. Embretson, S. E., & Reise, S. (2000). Item response theory for psychologists. Mahwah, NJ: Erlbaum.

References

403

Erlenmeyer-­Kimling, L., Adamo, U.H., Rock, D., Roberts, S. A., Bassett, A. S., & Squires­Wheeler, E., et al. (1997). The New York High Risk Project: Prevalence and comorbidity of Axis I disorders in offspring of schizophrenic parents at 25-year follow-up. Archives of General Psychiatry, 54, 1096–1102. Erlenmeyer-­Kimling, L., & Cornblatt, B.A., (1987). High-risk research in schizophrenia: A summary of what has been learned. Journal of Psychiatric Research, 21, 401–411. Erlenmeyer-­Kimling, L., Roberts, S. A., & Rock, D. (2004). Longitudinal prediction of schizophrenia in a prospective high-risk study. In L. F. DiLalla (Ed.). Behavior genetics principles: Perspectives in development, personality, and psychopathology (pp.  135–144). Washington, DC,: American Psychological Association. Erlenmeyer-­Kimling, L., Rock, D., Roberts, S. A., Janal, M., Kestenbaum, C., & Cornblatt, B. A., et al. (2000). Attention, memory, and motor skills as childhood predictors of schizophrenia-­related psychoses: The New York High-Risk Project. American Journal of Psychiatry, 157, 1416–1422. Erlenmeyer-­Kimling, L., Roberts, S. A., Rock, D., Adamo, U. H., Shapiro, B. M., & Pape, S. (1998). Prediction from longitudinal assessments of high-risk children. In M. F. Lenzenweger & R. H. Dworkin (Eds.). Origins and development of schizophrenia: Advances in experimental psychopathology (pp. 427–445).Washington, DC: American Psychological Association. Erwin, B. J., & Rosenbaum, G. (1979). Parietal lobe syndrome and schizophrenia: Comparison of neuropsychological deficits. Journal of Abnormal Psychology, 88, 234–241. Essen-Möller, Larsson, H., Uddenberg, C.-E., & White, G. (1956). Individual traits and morbidity in a Swedish rural population. Acta Psychiatrica et Neurologica Scandinavica (Suppl. 100). Estes, W. K. (1956). The problem of inference from curves based on group data. Psychological Bulletin, 53, 134–140. Evans, I. K., McGrath, J., & Milns, R. (2003). Searching for schizophrenia in ancient Greek and Roman literature: A systematic review. Acta Psychiatrica Scandinavica, 107(5), 323–330. Everitt, B. S., Landau, S., & Leese, M. (2001). Cluster analysis (4th ed.). Oxford, England: Oxford University Press. Eysenck, H. J. (1958). The continuity of abnormal and normal behavior. Psychological Bulletin, 55(6), 429–432. Eysenck, H. J. (1986). Can personality study ever be scientific? Journal of Social Behavior and Personality, 1, 3-19. Eysenck, H. J., & Eysenck, S. B. G. (1976). Psychoticism as a dimension of personality. London: Hodder and Stoughton. Falconer, D. S. (1989). Introduction to quantitative genetics (3rd ed.). New York: Wiley. Fanous, A., Gardner, C., Walsh, D., & Kendler, K. S. (2001). Relationship between positive and negative symptoms of schizophrenia and schizotypal symptoms in nonpsychotic relatives. Archives of General Psychiatry, 58(7), 669–673. Fanous, A. H., & Kendler, K. S. (2005). Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: Searching for a framework. Molecular Psychiatry, 10, 6–13. Fanous, A. H., Neale, M. C., Gardner, C. O., Webb, B. T., Straub, R. E., O’Neill, F. A., et al. (2007). Significant correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. Molecular Psychiatry, 12(10), 958–965.

404 References Feldt, L. S. (1961). The use of extreme groups to test for the presence of a relationship. Psychometrika, 26(3), 307–316. Fenton, W. S., & McGlashan, T. H. (1989). Risk of schizophrenia in character disordered patients. American Journal of Psychiatry, 146, 1280–1284. Fernandez-Duque, D., & Posner, M. I. (2001). Brain imaging of attentional networks in normal and pathological states. Journal of Clinical and Experimental Neuropsychology, 23, 74–93. Fisher, S. (1964). Body image and psychopathology. Archives of General Psychiatry, 10, 519–529. Fischer, M., Harvald, B., & Hauge, M. (1969). A Danish twin study of schizophrenia. British Journal of Psychiatry, 115, 981–990. Fish, B. (1977). Neurobiologic antecedents of schizophrenia in children: Evidence for an inherited, congenital neurointegrative defect. Archives of General Psychiatry, 34, 1297– 1313. Fish, B. (1987). Infant predictors of the longitudinal course of schizophrenia development. Schizophrenia Bulletin, 13, 395–409. Fish, B., Marcus, J., Hans, S. L., Auerbach, J. G., & Purdue, S. (1992). Infants at risk for schizophrenia: Sequelae of a genetic neurointegrative defect. Archives of General Psychiatry, 49, 221–235. Fitzpatrick, S. M., & Rothman, D. L. (2002). Meeting report: Choosing the right MR tools for the job. Journal of Cognitive Neuroscience, 14(5), 806–815. Forss, N., Hietanen, M., Salonen, O., & Hari, R. (1999). Modified activation of somatosensory cortical network in patients with right hemisphere stroke. Brain, 122(10), 1889–1899. Fossati, A., Raine, A., Borroni, S., & Maffei, C. (2007). Taxonic structure of schizotypal personality in nonclinical subjects: Issues of replicability and age consistency. Psychiatry Research, 152(2–3), 103–112. Fossati, A., Raine, A., Carretta, I., Leonardi, B., & Maffei, C. (2003). The three-­factor model of schizotypal personality: Invariance across age and gender. Personality and Individual Differences, 35, 1007–1019. Franke, P., Maier, W., Hardt, J., & Hain, C. (1993). Cognitive functioning and anhedonia in subjects at risk for schizophrenia. Schizophrenia Research, 10, 77–84. Freedman, R., Coon, H., Myles-­Worsley, M., Orr-­Urtreger, A., Olincy, A., Davis, A., et al. (1997). Linkage of a neurophysiological deficit in schizophrenia to a chromosome 15 locus. Proceedings of the National Academy of Sciences, 94, 587–592. Freedman, L. R., Rock, D., Roberts, S. A., Cornblatt, B. A., & Erlenmeyer-­Kimling, L. (1998). The New York high-risk project: Attention, anhedonia and social outcome. Schizophrenia Research, 30(1), 1–9. Freud, S. (1905). On psychotherapy. In J. Strachey (Ed. & Trans.), The standard edition of the complete psychological works of Sigmund Freud (Vol. 7, pp. 257–268). London: Hogarth Press. (Original work published 1905) Freud, S. (1914). On narcissism: An introduction. In J. Strachey (Ed. & Trans.), The standard edition of the complete psychological works of Sigmund Freud (Vol. 14, pp. 67–102). London: Hogarth Press. Funder, D. (2007). The personality puzzle (4th ed). New York: Norton. Gabbard, G. O. (2007). Do all roads lead to Rome? New findings on borderline personality disorder. American Journal of Psychiatry, 164(6), 853–855.

References

405

Gangestad, S., & Snyder, M. (1985). “To carve nature at its joints”: On the existence of discrete classes in personality. Psychological Review, 92, 317–349. Gates, E. J. (1915). The determination of the limens of single and dual impression by the method of constant stimuli. American Journal of Psychology, 26, 152–157. Gigerenzer, G. (2002). Calculated risks: How to know when numbers deceive you. New York: Simon & Schuster. Gold, J. M., & Harvey, P. D. (1993). Cognitive deficits in schizophrenia. Psychiatric Clinics of North America, 16, 295–312. Gold, J. M., Randolph, C., Carpenter, C. J., Goldberg, T. E., & Weinberger, D. R. (1992). Forms of memory failure in schizophrenia. Journal of Abnormal Psychology, 101, 487– 494. Golden, R. R. (1991). Bootstrapping taxometrics: On the development of a method for detection of a single major gene. In W. M. Grove & D. Cicchetti (Eds.). Thinking clearly about psychology: Vol. 2: Personality and psychopathology (Essays in honor of Paul E. Meehl (pp. 259–294). Minneapolis, MN: University of Minnesota Press. Golden, R., & Meehl, P. E. (1980). Detection of biological sex: An empirical test of cluster methods. Multivariate Behavioral Research, 15, 475–496. Goldman-Rakic, P. S. (1991). Prefrontal cortical dysfunction in schizophrenia: The relevance of working memory. In B. Carroll (Ed.), Psychopathology and the brain (pp. 1–23). New York: Raven Press. Goldman-Rakic, P. S. (1994). Working memory systems in schizophrenia. Journal of Neuropsychiatry and Clinical Neurosciences, 6, 348–357. Gooding, D. C., Kwapil, T. R., & Tallent, K. A. (1999). Wisconsin Card Sorting Test deficits in schizotypic individuals. Schizophrenia Research, 40, 201–209. Gooding, D. C., Matts, C. W., & Rollmann, E. A. (2006). Sustained attention deficits in relation to psychometrically identified schizotypy: Evaluating a potential endophenotypic marker. Schizophrenia Research, 82(1), 27–37. Gooding, D. C., Miller, M. D., & Kwapil, T. R. (2000). Smooth pursuit eye tracking and visual fixation in psychosis-prone individuals. Psychiatry Research, 93, 41–54. Gooding, D. C., Tallent, K. A., & Hegyi, J. V. (2001). Cognitive slippage in schizotypic individuals. Journal of Nervous and Mental Disease, 189, 750–756. Gooding, D. C., Tallent, K. A., & Matts, C. W. (2005). Clinical status of at-risk individuals 5 years later: Further validation of the psychometric high-risk strategy. Journal of Abnormal Psychology, 114(1), 170–175. Gooding, D. C., Tallent, K. A., & Matts, C. W. (2007). Rates of avoidant, schizotypal, schizoid and paranoid personality disorders in psychometric high-risk groups at 5-year follow-up. Schizophrenia Research, 94(1–3), 373–374. Goto, Y., & Grace, A. A. (2007). The dopamine system and the pathophysiology of schizophrenia: A basic science perspective. International Review of Neurobiology, 78, 41–68. Gottesman, I. I. (1963). Heritability of personality: A demonstration. Psychological Monographs: General and Applied, 77(9), 1–21. Gottesman, I. I. (1974). Developmental genetics and ontogenetic psychology: Overdue detente and propositions from a matchmaker. In A. Pick (Ed.), Minnesota Symposia on Child Psychology (Vol. 8, 55–80). Minneapolis: University of Minnesota Press. Gottesman, I. I. (1987). The psychotic hinterlands or the fringes of lunacy. British Medical Bulletin, 43(3), 557–569. Gottesman, I. I. (1991). Schizophrenia genesis: The origins of madness. New York: Freeman.

406 References Gottesman, I. I. (1997). Twins—en route to QTLs for cognition. Science, 276, 1522–1523. Gottesman, I. I., & Bertelsen, A. (1989). Confirming unexpressed genotypes for schizophrenia: Risks in the offspring of Fischer’s Danish identical and fraternal discordant twins. Archives of General Psychiatry, 46, 867–872. Gottesman, I., & Gould, T. (2003). The endophenotype concept in psychiatry: Etymology and strategic intentions. American Journal of Psychiatry, 160, 636–645. Gottesman, I. I., Laursen, T. M., Bertelsen, A, & Mortensen, P. B. (2010). Severe mental disorders in offspring of two psychiatrically ill parents. Archives of General Psychiatry, 67, 252–257. Gottesman, I. I., & Shields, J. (1967). A polygenic theory of schizophrenia. Proceedings of the National Academy of Sciences, USA, 58(1), 199–205. Gottesman, I. I., & Shields, J. (1972). Schizophrenia and genetics: A twin study vantage point. New York: Academic Press. Gottesman, I. I., & Shields, J. (1973). Genetic theorizing and schizophrenia. British Journal of Psychiatry, 122(566), 15–30. Gottesman, I. I., & Shields, J. (1982). Schizophrenia: The epigenetic puzzle. New York: Cambridge University Press. Gould, T. D., & Gottesman, I. I. (2006). Psychiatric endophenotypes and the development of valid animal models. Genes, Brain and Behavior, 5(2), 113–119. Grace, A. A. (1991). Phasic versus tonic dopamine release and the modulation of dopamine system responsivity: A hypothesis for the etiology of schizophrenia. Neuroscience, 41, 1–24. Grace, A. A. (2000). Gating of information flow within the limbic system and the pathophysiology of schizophrenia. Brain Research Reviews, 31, [Special issue: Nobel Symposium 111: Schizophrenia: Pathophysiological mechanisms], 330–341. Grace, A. A., & Moore, H. (1998). Regulation of information flow in the nucleus accumbens: A model for the pathophysiology of schizophrenia. In M. F. Lenzenweger & R. H. Dworkin (Eds.), Origins and development of schizophrenia: Advances in experimental psychopathology (pp. 123–157). Washington, DC: American Psychological Association. Grados, M. A., Riddle, M. A., Samuels, J. F., Liang, K-Y., Hoehn-Saric, R., Bienvenu, J. O., et al. (2001). The familial phenotype of obsessive–­compulsive disorder in relation to tic disorders: The Hopkins OCD family study. Biological Psychiatry, 50(8), 559–565. Grayson, D. A. (1987). Can categorical and dimensional views of psychiatric illness be distinguished? British Journal of Psychiatry, 151, 355–361. Graziano, M. S. A., Cooke, D. F., & Taylor, C. S. R. (2000). Coding the location of the arm by sight. Science, 290, 1782–1786. Green, C. D. (1992). Of immortal mythological beasts: Operationism in psychology. Theory and Psychology, 2(3), 291–320. Green, C. D. (2001). Operationism again: What did Bridgman say? What did Bridgman need? Theory and Psychology, 11(1), 45–51. Green, D. M., & Swets, J. A. (1966). Signal detection theory and psychophysics. New York: Wiley. Greenamyre, J. T. (2007). Huntington’s disease: Making connections. New England Journal of Medicine, 356(5), 518–520. Grinnell, F. (1987). The scientific attitude. Boulder, CO: Westview Press. Grove, W. M. (1982). Psychometric detection of schizotypy. Psychological Bulletin, 92, 27–38.

References

407

Grove, W. M. (2005). Clinical versus statistical prediction: The contribution of Paul E. Meehl. Journal of Clinical Psychology, 61(10), 1233–1243. Grove, W. M., Lebow, B. S., Clementz, B. A., Cerri, A., Medus, C., & Iacono, W. G. (1991). Familial prevalence and coaggregation of schizotypy indicators: A multitrait family study. Journal of Abnormal Psychology, 100, 115–121. Grove, W. M., & Lloyd, M. (2006). Meehl’s contribution to clinical versus statistical prediction. Journal of Abnormal Psychology, 115(2), 192–194. Grove, W. M., & Meehl, P. E. (1996). Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical–­statistical controversy. Psychology, Public Policy, and Law, 2, 293–323. Grove, W. M., Zald, D. H., Lebow, B. S., Snitz, B. E., & Nelson, C. (2000). Clinical versus mechanical prediction: A meta-­analysis. Psychological Assessment, 12(1), 19–30. Guttmacher, A. E., & Collins, F. S. (2002). Genomic medicine: A primer. New England Journal of Medicine, 347(19), 1512–1520. Hacking, I. (1991). A tradition of natural kinds. Philosophical Studies, 61(1–2), 109–126. Halbreich, U., Bakhai, Y., Bacon, K. B., Goldstein, S., Asnis, G. M., Endicott, J., et al. (1989). The normalcy of self-­proclaimed “normal volunteers.” American Journal of Psychiatry, 146(8), 1052–1055. Hamilton, E. (1940). Mythology: Timeless tales of gods and heroes. New York: New American Library. Hamon, S. C., Stengard, J. H., Clark, A. G., Salomaa, V., Boerwinkle, E., & Sing, C. F. (2004). Evidence for non-­additive influence of single nucleotide polymorphisms within the apolipoprotein E gene. Annals of Human Genetics, 68(6), 521–535. Hanh, T. N. (1987). Being peace. Berkeley, CA: Parallax Press. Hanna, G. L., Himle, J. A., Curtis, G. C., & Gillespie, B. W. (2005). A family study of obsessive–­compulsive disorder with pediatric probands. American Journal of Medical Genetics, 134B(1), 13–19. Hanson, D. R., Gottesman, I. I., & Meehl, P. E. (1977). Genetic theories and the validation of psychiatric diagnosis: Implications for the study of children of schizophrenics. Journal of Abnormal Psychology, 86, 575–588. Hardcastle, G. L. (1995). S. S. Stevens and the origins of operationism. Philosophy of Science, 62(3), 404–424. Harding, C. M., Brooks, G. W., Ashikaga, T., Strauss, J. S., & Breier, A. (1987). The Vermont longitudinal study of persons with severe mental illness: II. Long-term outcome of subjects who retrospectively met DSM-III criteria for schizophrenia. American Journal of Psychiatry, 144(6), 727–735. Harkness, A. R., McNulty, J. L., & Ben-­Porath, Y. (1995). The Personality Pathology Five (PSY-5): Constructs and MMPI-2 scales. Psychological Assessment, 7, 104–114. Haroun, N., Dunn, L., Haroun, A., & Cadenhead, K. S. (2006). Risk and protection in prodromal schizophrenia: Ethical implications for clinical practice and future research. Schizophrenia Bulletin, 32(1), 166–178. Harrison, P., & Owen, M. (2003). Genes for schizophrenia? Recent findings and their pathophysiological implications. Lancet, 361(9355), 417–419. Harvey, P. D., Keefe, R. S. E., Mitroupolou, V., DuPre, R., Roitman, S. L., Mohs, R., et al. (1996). Information-­processing markers of vulnerability to schizophrenia: Performance of patients with schizotypal and nonschizotypal personality disorders. Psychiatry Research, 60, 49–56.

408 References Haslam, N. (2003). The dimensional view of personality disorders: A review of the taxometric evidence. Clinical Psychology Review, 23(1), 75–93. Haslam, N. (2007). The latent structure of mental disorders: A taxometric update on the categorical vs. dimensional debate. Current Psychiatry Reviews, 3(3), 172–177. Heaton, R. K. (1981). Wisconsin Card Sorting Manual. Odessa, FL: Psychological Assessment Resources. Hecaen, H., & Albert, M. L. (1978). Human neuropsychology. New York: Wiley. Heinrichs, R. W., & Zakzanis, K. K. (1998). Neurocognitive deficit in schizophrenia: A quantitative review of the evidence. Neuropsychology, 12, 426–445. Henquet, C., Murray, R., Linszen, D., & van Os, J. (2005). The environment and schizophrenia: The role of cannabis use. Schizophrenia Bulletin, 31(3), 608–612. Holzman, P. S. (1969). Perceptual aspects of schizophrenia. In J. Zubin & C. Shagass (Eds.), Neurobiological aspects of psychopathology (pp.  144–178). New York: Grune & Stratton. Holzman, P. S. (1976). Theoretical models and the treatment of the schizophrenias. Psychological Issues, 9(4), 134–157. Holzman, P. S., Kringlen, E., Matthysse, S., Flanagan, S. D., Lipton, R. B., Cramer, G., et al. (1988). A single dominant gene can account for eye tracking dysfunctions and schizophrenia in offspring of discordant twins. Archives of General Psychiatry, 45, 641–647. Holzman, P. S., Proctor, L., & Hughes, D. W. (1973). Eye-­tracking patterns in schizophrenia. Science, 181, 179–181. Holzman, P. S., Proctor, L. R., Levy, D. L., Yasillo, N. J., Meltzer, H. Y., & Hurt, S. W. (1974). Eye-­tracking dysfunctions in schizophrenia patients and their relatives. 143–151. Holzman, P. S., Shenton, M. E., & Solovay, M. R. (1986). Quality of thought disorder in differential diagnosis. Schizophrenia Bulletin, 12, 360–372. Hon, L. E., Summerfelt, A., Mitchell, B. D., McMahon, R. P., Wonodi, I., Buchanan, R. W., et al. (2008). Sensory gating endophenotype based on its neural oscillatory pattern and heritability estimate. Archives of General Psychiatry, 65(9), 1008–1016. Hooley, J. M., & Parker, H. A. (2006). Measuring expressed emotion: An evaluation of the shortcuts. Journal of Family Psychology, 20(3), 386–396. Hooley, J. M., & Richters, J. E. (1991). Alternative measures of expressed emotion: A methodological and cautionary note. Journal of Abnormal Psychology, 100(1), 94–97. Horan, W. P., Blanchard, J. J., Gangestad, S. W., & Kwapil, T. R. (2004). The psychometric detection of schizotypy: Do putative schizotypy indicators identify the same latent class? Journal of Abnormal Psychology, 113(3), 339–357. Horan, W. P., Kring, A. M., & Blanchard, J. J. (2006). Anhedonia in schizophrenia: A review of assessment strategies. Schizophrenia Bulletin, 32(2), 259–273. Howes, O. D., Montgomery, A. J., Murray, R. M., Valli, I., Tabraham, P., and Asselin, M. C. (2009). Elevated striatal dopamine linked to prodromal signs of schizophrenia. Archives of General Psychiatry, 66, 13–20 Hunter, J. E. (1997). Needed: A ban on the significance test. Psychological Science, 8(1), 3–7. Hunter, J. E., Schmidt, F. L., & Jackson, G. B. (1982). Meta-­analysis: Cumulating research findings across studies. Beverly Hills, CA: Sage. Ingram, R. E., & Price, J. M. (Eds.). (2010). Vulnerability to psychopathology: Risks across the lifespan (2nd ed.). New York: Guilford Press. International Schizophrenia Consortium. (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460, 748–752.

References

409

Ismail, B., Cantor-Graae, E., & McNeil, T. F. (1998). Neurological abnormalities in schizophrenia patients and their siblings. American Journal of Psychiatry, 155, 84–89. Jackson, D. N. (1971). The dynamics of structured personality tests. Psychological Review, 78(3), 229–248. Jakobsson, M., Scholz, S. W., Scheet, P., Gibbs, J. R., VanLiere, J. M., Fung, H. C., et al. (2008). Genotype, haplotype and copy-­number variation in worldwide human populations. Nature, 451(7181), 998–1003. Javitt, D. C. (2007). Glutamate and schizophrenia: Phencyclidine, N-methyl-d-­aspartate receptors, and dopamine–­glutamate interactions. International Review of Neurobiology, 78, 69–108. Javitt, D. C. (2009). When doors of perception close: Bottom-up models of disrupted cognition in schizophrenia. Annual Review of Clinical Psychology, 5, 249–275. Javitt, D. C., Liederman, E., Cienfuegos, A., & Shelley, A. (1999). Panmodal processing imprecision as a basis for dysfunction of transient memory storage systems in schizophrenia. Schizophrenia Bulletin, 25, 763–775. Jensen, S. T., Lenzenweger, M. F., & Rubin, D. B. (2002). A Bayesian approach to reducing heterogeneity in laboratory performance measures: An illustration from schizophrenia research. Case Studies in Bayesian Statistics, 6, 255–266. John, B., & Lewis, K. R. (1966). Chromosome variability and geographical distribution in insects: Chromosome rather than gene variation provide the key to differences among populations. Science, 152, 711–721. Johnson, J. G., Cohen, P., Kasen, S., Skodol, A. E., Hamagami, F., & Brook, J. S. (2000). Age-­related change in personality disorder trait levels between early adolescence and adulthood: A community-based longitudinal investigation. Acta Psychiatrica Scandinavica, 102(4), 265–275. Johnson, K. O., & Phillips, J. R. (1981). Tactile spatial resolution: I. Two-point discrimination, gap detection, grating resolution, and letter recognition. Journal of Neurophysiology, 46, 1177–1191. Johnston, M. H., & Holzman, P. S. (1979). Assessing schizophrenia thinking. San Francisco, CA: Josey-Bass. Johnstone, E. C., Abukmeil, S. S., Byrne, M., Clafferty, R., Grant, E., Hodges, A., et al. (2000). Edinburgh High-Risk Study—­findings after four years: Demographic, attainment and psychopathological issues. Schizophrenia Research, 46(1), 1–15. Johnstone, E. C., Ebmeier, K. P., Miller, P., Owens, D. G. C., & Lawrie, S. M. (2005). Predicting schizophrenia: Findings from the Edinburgh High-Risk Study. British Journal of Psychiatry, 186(1), 18–25. Johnstone, E. C., Owens, D. G. C., Hoare, P., Gaur, S., Spencer, M. D., Harris, J., et al. (2007). Schizotypal cognitions as a predictor of psychopathology in adolescents with mild intellectual impairment. British Journal of Psychiatry, 191(6), 484–492. Jones, E. G. (2000). Cortical and subcortical contributions to activity dependent plasticity in primate somatosensory cortex. Annual Review of Neuroscience, 23,(1), 1–37. Jonides, J., & Nee, D. E. (2005). Assessing dysfunction using refined cognitive methods. Schizophrenia Bulletin, 31, 823–829. Jung, 1907. The psychology of dementia praecox. London: Routledge and Kegan Paul Ltd. Kagan, J. (1980). Perspectives on continuity. In O. Brim & J. Kagan (Eds.), Constancy and change in human development. Cambridge, MA: Harvard University Press. Kagan, J. (1984). Galen’s prophecy. New York: Basic Books. Kagan, J. (1994). Galen’s prophecy: Temperament in human nature. New York: Basic Books.

410 References Kagan, J. (2007). A trio of concerns. Perspectives on Psychological Science, 2(4), 361–376. Kaplan, B. (1974). The inner world of mental illness: A series of first-­person accounts of what it was like. New York: Harper & Row. Kay, R. (2004). An explanation of the hazard ratio. Pharmaceutical Statistics, 3(4), 295– 297. Keller, M. C., & Miller, G. (2006). Resolving the paradox of common, harmful, heritable mental disorders: Which evolutionary genetic models work best? Behavioral and Brain Sciences, 29, 385–452. Kendler, K. S. (1985). Diagnostic approaches to schizotypal personality disorder: A historical perspective. Schizophrenia Bulletin, 11, 538–553. Kendler, K. S. (2001). Twin studies of psychiatric illness: An update. Archives of General Psychiatry, 58, 1005–1014. Kendler, K. S. (2005). “A gene for . . . ”: The nature of gene action in psychiatric disorders. American Journal of Psychiatry, 162(7), 1243–1252. Kendler, K. S. (2006). Reflections on the relationship between psychiatric genetics and psychiatric nosology. American Journal of Psychiatry, 163(7), 1138–1146. Kendler, K. S. (2008). Explanatory models for psychiatric illness. American Journal of Psychiatry, 165(6), 695–702. Kendler, K. S., & Gardner, C. O. (1997). The risk for psychiatric disorders in relatives of schizophrenia and control probands: a comparison of three independent studies. Psychological Medicine, 27, 411–419. Kendler, K. S., Gruenberg, A. M., & Kinney, D. K. (1994). Independent diagnoses of adoptees and relatives as defined by DSM-III in the provincial and national samples of the Danish Adoption Study of Schizophrenia. Archives of General Psychiatry, 51, 456–468. Kendler, K. S., & Hewitt, J. (1992). The structure of self-­report schizotypy in twins. Journal of Personality Disorders, 6, 1–17. Kendler, K. S., Lieberman, J. A., & Walsh, D. (1989). The Structured Interview for Schizotypy (SIS): A preliminary report. Schizophrenia Bulletin, 15, 559–571. Kendler, K. S., McGuire, M., Gruenberg, A. M., O’Hare, A., Spellman, M., & Walsh, D. (1993). The Roscommon Family Study: III. Schizophrenia-­related personality disorders in relatives. Archives of General Psychiatry, 50, 781–788. Kendler, K. S., McGuire, M., Gruenberg, A. M., & Walsh, D. (1995). Schizotypal symptoms and signs in the Roscommon Family Study: Their factor structure and familial relationship with psychotic and affective disorders. Archives of General Psychiatry, 52, 296–303. Kendler, K. S., Myers, J., Torgersen, S., Neale, M. C., & Reichborn-­Kjennerud, T. (2007). The heritability of Cluster A personality disorders assessed by both personal interview and questionnaire. Psychological Medicine, 37(5), 655–665. Kendler, K. S., Neale, M. C., & Walsh, D. (1995). Evaluating the spectrum concept of schizophrenia in the Roscommon Family Study. American Journal of Psychiatry, 152, 749–754. Kendler, K. S., Ochs, A. L., Gorman, A. M., Hewitt, J. K., Ross, D. E., & Mirsky, A. F. (1991). The structure of schizotypy: A pilot multitrait twin study. Psychiatry Research, 36(1), 19–36. Kennedy, J., & Bai, J. (2002). Haptic pictures: Fit judgments predict identification, recognition memory, and confidence. Perception, 31(8), 1013–1026.

References

411

Kernberg, O. F. (1984). Severe personality disorders. New Haven, CT: Yale University Press. Kessler, R. C., Birnbaum, H., Demler, O., Falloon, I. R. H., Gagnon, E., Guyer, M., et al. (2005). The prevalence and correlates of nonaffective psychosis in the National Comorbidity Survey Replication (NCS-R). Biological Psychiatry, 58(8), 668–676. Kety, S. S., Rosenthal, D., Wender, P. H., & Schulsinger, F. (1968). The types and prevalence of mental illness in the biological and adoptive families of adopted schizophrenics. Journal of Psychiatric Research, 6, 345–362. Kety, S. S., Rosenthal, D., Wender, P. H., & Schulsinger, F. (1975). Mental illness in the biological and adoptive families of adopted individuals who have become schizophrenic: A preliminary report based on psychiatric interviews. In R. R. Fieve, D. Rosenthal, & H. Brill (Eds)., Genetic research in psychiatry. Baltimore: Johns Hopkins University Press. Kety, S. S., Wender, P. H., Jacobsen, B., Ingraham, L. J., Jansson, L., Faber, B., et al. (1994). Mental illness in the biological and adoptive relatives of schizophrenic adoptees: Replication of the Copenhagen Study in the rest of Denmark. Archives of General Psychiatry, 51, 442–455. Khaja, R., Junjun, Z., MacDonald, J. R., Yongshu, H., Joseph-­George, A. M., Wei, J., et al. (2006). Genome assembly comparison identifies structural variants in the human genome. Nature Genetics, 38(12), 1413–1418. Khouri, P. J., Haier, R. J., Rieder, R. O., & Rosenthal, D. (1980). A symptom schedule for the diagnosis of borderline schizophrenia: A first report. British Journal of Psychiatry, 137, 140–147. King, H. E. (1954). Psychomotor aspects of mental disease. Cambridge, MA: Harvard University Press. Klein, G. S. (1976). Psychoanalytic theory: An exploration of essentials. New York: International Universities Press. Klonsky, E. D., Oltmanns, T. F., & Turkheimer, E. (2002). Informant-­reports of personality disorder: Relation to self-­reports and future research directions. Clinical Psychology: Science and Practice, 9, 300–311. Knapp, M., Mangalore, R., & Simon, J. (2004). The global costs of schizophrenia. Schizophrenia Bulletin, 30(2), 279–293. Knecht, S., Kunesch, E., & Schnitzler, A. (1996). Parallel and serial processing of haptic information in man: Effects of parietal lesions on sensorimotor hand function. Neuropsychologia, 34, 669–687. Koch, S. (1992). Psychology’s Bridgman vs. Bridgman’s Bridgman: An essay in reconstruction. Theory and Psychology, 2(3), 261–290. Kolb, B., & Whishaw, I. Q. (1996). Fundamentals of human neuropsychology (4th ed.). New York: Freeman. Korfine, L. & Hooley, J. M. (2000). Directed forgetting of emotional stimuli in borderline personality disorder. Journal of Abnormal Psychology, 109, 214–221. Korfine, L., & Hooley, J. M. (2009). Detecting individuals with borderline personality disorder in the community: An ascertainment strategy and comparison with a hospital sample. Journal of Personality Disorders, 23, 62–75. Korfine, L., & Lenzenweger, M. F. (1995). The taxonicity of schizotypy: A replication. Journal of Abnormal Psychology, 104, 26–31. Kosslyn, S. M. (1999). If neuroimaging is the answer, what is the question? Philosophical Transactions of the Royal Society of London: B. Biological Sciences, 354, 1283–1294.

412 References Kosslyn, S. M., Cacioppo, J. T., Davidson, R. J., Hugdahl, K., Lovallo, W. R., Spiegal, D., et al. (2002). Bridging psychology and biology: The analysis of individuals in groups. American Psychologist, 57(5), 341–351. Kosslyn, S. M., & Rosenberg, R. S. (2005). The brain and your students: How to explain why neuroscience is relevant to psychology. In B. Perlman, L. I. McCann, & W. Buskist (Eds.), Voices of experience: Memorable talks from the National Institute on the Teaching of Psychology (Vol. 1, pp. 71–82). Washington, DC: American Psychological Society. Kraepelin, E. (1971). Dementia praecox and paraphrenia (R. M. Barclay, Trans., G. M. Robertson, Ed.). Huntington, NY: Krieger. (Original work published 1909–1913; original translation of selected portions published 1919) Kremer, B., Goldberg, P., Andrews, S. E., Theilmann, J., Telenius, H., Zeisler, J., et al. (1994). A worldwide study of the Huntington’s disease mutation: The sensitivity and specificity of measuring CAG repeats. New England Journal of Medicine, 330(20), 1401–1406. Kwapil, T. R. (1998). Social anhedonia as a predictor of the development of schizophrenia­spectrum disorders. Journal of Abnormal Psychology, 107(4), 558–565. Kwapil, T. R., Barrantes-Vidal, N., & Silva, P. J. (2008). The dimensional structure of the Wisconsin schizotypy scales: Factor identification and construct validity. Schizophrenia Bulletin, 34(3), 444–457. Kwapil, T. R., Chapman, L. J., & Chapman, J. (1999). Validity and usefulness of the Wisconsin manual for assessing psychotic-like experiences. Schizophrenia Bulletin, 25(2), 363–375. Kwapil, T. R., Chapman, J. P., Chapman, L. J., & Miller, M. B. (1996). Deviant experiences as indicators of risk for psychosis. Schizophrenia Bulletin, 22(2), 371–382. Kwapil, T. R., Mann, M. C., & Raulin, M. L. (2002). Psychometric properties and concurrent validity of the schizotypal ambivalence scale. Journal of Nervous and Mental Disease, 190(5), 290–295. Kwapil, T. R., Miller, M. B., Zinser, M. C., Chapman, J., & Chapman, L. J. (1997). Magical ideation and social anhedonia as predictors of psychosis proneness: A partial replication. Journal of Abnormal Psychology, 106(3), 491–495. Lalouel, J. M., Rao, D. C., Morton, N. E., & Elston, R. C. (1983). A unified model for complex segregation analysis. American Journal of Human Genetics, 35, 816–826. Lander, E. (1996). The new genomics: Global views of biology. Science, 274, 536–539. Lataster, T., Myin-­Germeys, I., Derom, C., Thiery, E., & Os, J. V. (in press). Evidence that self-­reported psychotic experiences represent the transitory developmental expression of genetic liability to psychosis in the general population. American Journal of Medical Genetics: Part B. Neuropsychiatric Genetics. Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. New York: Houghton Mifflin. Lee, J., & Park, S. (2005). The role of stimulus salience in CPT-A performance of schizophrenia patients. Schizophrenia Research, 81(2–3), 191–197. Leischenring, F., & Rabung, S. (2008). Effectiveness of long-term psychodynamic psychotherapy: A meta-­analysis. Journal of the American Medical Association, 300, 1551– 1565. Lencz, T., Raine, A., Scerbo, A., Redmon, M., Brodish, S., Holt, L., et al. (1993). Impaired eye tracking in undergraduates with schizotypal personality disorder. American Journal of Psychiatry, 150, 152–154. Lenzenweger, M. F. (1991). Confirming schizotypic personality configurations in hypothetically psychosis-prone university students. Psychiatry Research, 37, 81–96.

References

413

Lenzenweger, M. F. (1994). The psychometric high-risk paradigm, perceptual aberrations, and schizotypy: An update. Schizophrenia Bulletin, 20, 121–135. Lenzenweger, M. F. (1998). Schizotypy and schizotypic psychopathology: Mapping an alternative expression of schizophrenia liability. In M. F. Lenzenweger & R. H. Dworkin (Eds.), Origins and development of schizophrenia: Advances in experimental psychopathology (pp. 93–121).Washington, DC: American Psychological Association. Lenzenweger, M. F. (1999a). Deeper into the schizotypy taxon: On the robust nature of maximum covariance (MAXCOV) analysis. Journal of Abnormal Psychology, 108, 182–187. Lenzenweger, M. F. (1999b). Schizophrenia: Refining the phenotype, resolving endophenotypes. Behaviour Research and Therapy, 37, 281–295. Lenzenweger, M. F. (1999c). Stability and change in personality disorder features: The Longitudinal Study of Personality Disorders. Archives of General Psychiatry, 56, 1009– 1015. Lenzenweger, M. F. (2000). Two-point discrimination thresholds and schizotypy: Illuminating a somatosensory dysfunction. Schizophrenia Research, 42, 111–124. Lenzenweger, M. F. (2001). Reaction time slowing during high-load, sustained-­attention task performance in psychometrically identified schizotypy. Journal of Abnormal Psychology, 110, 290–296. Lenzenweger, M. F. (2003). On thinking clearly about taxometrics, schizotypy, and genetic influences: Correction to Widiger (2001). Clinical Psychology: Science and Practice, 10, 367–369. Lenzenweger, M. F. (2004). Consideration of the challenges, complications, and pitfalls of taxometric analysis. Journal of Abnormal Psychology, 113, 10–23. Lenzenweger, M. F. (2006a). The Longitudinal Study of Personality Disorders: History, design, and initial findings. Journal of Personality Disorders, 6, 645–670. Lenzenweger, M. F. (2006b). Schizotaxia, schizotypy and schizophrenia: Paul E. Meehl’s blueprint for experimental psychopathology and the genetics of schizophrenia. Journal of Abnormal Psychology, 115, 195–200. Lenzenweger, M. F. (2006c). Schizotypy: An organizing framework for schizophrenia research. Current Directions in Psychological Science, 15, 162–166. Lenzenweger, M. F. (2008). Epidemiology of personality disorders. Psychiatric Clinics of North America, 31, 395–403. Lenzenweger, M. F. (2009). Confirming the schizotypy and Wisconsin Card Sorting Test performance association in a community sample. (Unpublished Data). Lenzenweger, M. F. (2009). Schizotypic psychopathology: Theory, evidence, and future directions. In P. H. Blaney & T. Millon (Eds.), Oxford textbook of psychopathology, 2nd edition (pp. 692–722). New York: Oxford University Press. ©Lenzenweger, M. F. (2010a). Contemplations on Meehl (1986): The territory, Paul’s map, and our progress in psychopathology classification (or, the challenge of keeping up with a beacon 30 years ahead of the field). In T. Millon, R. F. Krueger, & E. Simonsen (Eds.). (2010). Contemporary directions in psychopathology: Scientific foundations of the DSM-V and ICD-11 (pp. 187–204). New York: Guilford Press. Lenzenweger, M. F. (2010b). Endophenotype, intermediate phenotype, and biomarker: A comparative conceptual analysis. Unpublished manuscript. Lenzenweger, M. F., Bennett, M. E., & Lilenfeld, L. R. (1997). Referential thinking as an indicator of schizotypy: Scale development and initial construct validation. Psychological Assessment, 9, 452–463.

414 References Lenzenweger, M. F., Clarkin, J. F., Yeomans, F. E., Kernberg, O. F., & Levy, K. N. (2008). Refining the borderline personality disorder phenotype through finite mixture modeling: Implications for classification. Journal of Personality Disorders, 22, 313–331. Lenzenweger, M. F., Cornblatt, B. A., & Putnick, M. E. (1991). Schizotypy and sustained attention. Journal of Abnormal Psychology, 100, 84–89. Lenzenweger, M. F., & Dworkin, R. H. (1996). The dimensions of schizophrenia phenomenology: Not one or two, at least three, perhaps four. British Journal of Psychiatry, 168, 432–440. Lenzenweger, M. F., & Hooley, J. M., (Eds.). (2003). Principles of experimental psychopathology: Essays in honor of Brendan A. Maher. Washington, DC: American Psychological Association. Lenzenweger, M. F., Jensen, S., & Rubin, D. B. (2003). Finding the “genuine” schizotype: A model and method for resolving heterogeneity in performance on laboratory measures in experimental psychopathology research. Journal of Abnormal Psychology, 112, 457–468. Lenzenweger, M. F., Johnson, M. D., & Willett, J. B. (2004). Individual growth curve analysis illuminates stability and change in personality disorder features: The Longitudinal Study of Personality Disorders. Archives of General Psychiatry, 61, 1015–1024. Lenzenweger, M. F., & Korfine, L. (1991, December). Schizotypy and Wisconsin Card Sorting Test performance. Paper presented at the sixth annual meeting of the Society for Research in Psychopathology, Harvard University, Cambridge, MA. Lenzenweger, M. F., & Korfine, L. (1992a). Confirming the latent structure and base rate of schizotypy: A taxometric analysis. Journal of Abnormal Psychology, 101, 567–571. Lenzenweger, M. F., & Korfine, L. (1992b). Identifying schizophrenia-­related personality disorder features in a nonclinical population using a psychometric approach. Journal of Personality Disorders, 6, 264–274. Lenzenweger, M. F., & Korfine, L. (1994). Perceptual aberrations, schizotypy and the Wisconsin Card Sorting Test. Schizophrenia Bulletin, 20, 345–357. Lenzenweger, M. F., & Korfine, L. (1995). Tracking the taxon: On the latent structure and base rate of schizotypy. In A. Raine, T. Lencz, & S. A. Mednick (Eds.), Schizotypal personality (pp. 135–167). New York: Cambridge University Press. Lenzenweger, M. F., Lane, M., Loranger, A. W., & Kessler, R. C. (2007). DSM-IV personality disorders in the National Comorbidity Survey Replication (NCS-R). Biological Psychiatry, 62, 553–564. Lenzenweger, M. F., & Loranger, A. W. (1989a). Detection of familial schizophrenia using a psychometric measure of schizotypy. Archives of General Psychiatry, 46, 902– 907. Lenzenweger, M. F., & Loranger, A. W. (1989b). Psychosis proneness and clinical psychopathology: Examination of the correlates of schizotypy. Journal of Abnormal Psychology, 98, 3–8. Lenzenweger, M. F., Loranger, A. W., Korfine, L., & Neff, C. (1997). Detecting personality disorders in a nonclinical population: Application of a two-stage procedure for case identification. Archives of General Psychiatry, 54, 345–351. Lenzenweger, M. F., & Maher, B. A. (2002). Psychometric schizotypy and motor performance. Journal of Abnormal Psychology, 111, 546–555. Lenzenweger, M. F., McLachlan, G., & Rubin, D. B. (2007). Resolving the latent structure of schizophrenia endophenotypes using expectation-­maximization-based finite mixture modeling. Journal of Abnormal Psychology, 116, 16–29.

References

415

Lenzenweger, M. F., Miller, A. B., Maher, B. A., & Manschreck, T. C. (2007). Schizotypy and individual differences in the frequency of normal associations in verbal utterances. Schizophrenia Research, 95, 96–102. Lenzenweger, M. F., Nakayama, K., & Chang, B. P. (2003). Methodological excursions in pursuit of a somatosensory dysfunction in schizotypy and schizophrenia. In M. F. Lenzenweger & J. M. Hooley (Eds.), Principles of experimental psychopathology: Essays in honor of Brendan A. Maher (pp. 135–155). Washington, DC: American Psychological Association. Lenzenweger, M. F., & O’Driscoll, G. A. (2006). Smooth pursuit eye movement dysfunction and schizotypy in an adult community sample. Journal of Abnormal Psychology, 115, 779–786. Lenzenweger, M. F., & Willett, J. B. (2007). Modeling individual change in personality disorder features as a function of simultaneous individual change in personality dimensions linked to neurobehavioral systems: The Longitudinal Study of Personality Disorders. Journal of Abnormal Psychology, 116, 684–700. Leventhal, D. B., Schuck, J. R., Clemons, T., & Cox, M. (1982). Proprioception in schizophrenia. Journal of Nervous and Mental Disease, 170, 21–26. Levin, S. (1984a). Frontal lobe dysfunctions in schizophrenia-I. Eye movement impairments. Journal of Psychiatric Research, 18, 27–55. Levin, S. (1984b). Frontal lobe dysfunctions in schizophrenia: II. Impairments of psychological brain functions. Journal of Psychiatric Research, 18, 57–72. Levy, D. L. (1996). Location, location, location: the pathway from behavior to brain locus in schizophrenia. In S. Matthysse, D. L. Levy, J. Kagan, & F. M. Benes (Eds.), Psychopathology: The evolving science of mental disorder (pp. 100–126). New York: Cambridge University Press. Levy, D. L., Bowman, E., Abel, L., Krastoshevsky, O., Krause, V., & Mendell, N. R. (2008). Does performance on the standard antisaccade task meet the co-­familiality criterion for an endophenotype? Brain and Cognition, 68, 462–475. Levy, D. L., Holzman, P. S., Matthysse, S., & Mendell, R. (1993). Eye-­tracking dysfunction and schizophrenia: A critical perspective. Schizophrenia Bulletin, 19, 461–536. Levy, D. L., Holzman, P. S., Matthysse, S., & Mendell, N. R. (1994). Eye tracking and schizophrenia: A selective review. Schizophrenia Bulletin, 20, 47–62. Levy, D. L., O’Driscoll, G., Matthysse, S., Cook, S. R., Holzman, P. S., & Mendell, N. R. (2004). Antisaccade performance in biological relatives of schizophrenia patients: A meta-­analysis. Schizophrenia Research, 71(1), 113–125. Levy, D. L., Bowman, E., Abel, L., Krastoshevsky, O., Krause, V., & Mendell, N. R. (2008). Does performance on the standard antisaccade task meet the co-­familiality criterion for an endophenotype? Brain and Cognition, 68, 462–475. Levy, D. L., & Sebat, J. (2010). Copy number variation and molecular genetic studies of schizophrenia. Unpublished manuscript. Lewis, C. M., Levinson, D. F., Wise, L. H., Delisi, L. E., Straub, R. E., Hovatta, L., et al. (2003). Genome scan meta-­analysis of schizophrenia and bipolar disorder: Part II. Schizophrenia. American Journal of Human Genetics, 73(1), 34–48. Lidz,T. (1990). The origin and treatment of schizophrenic disorders. Madison, CT: International Universities Press. Lidz, T., Blatt, S., & Cook, B. (1981). Critique of the Danish-­American studies of the adopted-away offspring of schizophrenic parents. American Journal of Psychiatry, 138(8), 1063–1068.

416 References Lilienfeld, S. O., Wood, J. M., & Garb, H. N. (2000). The scientific status of projective techniques. Psychological Science in the Public Interest, 1, 27–66. Limosin, F., Rouillon, F., Payan, C., Cohen, J-M., & Strub, N. (2003). Prenatal exposure to influenza as a risk factor for adult schizophrenia. Acta Psychiatrica Scandinavica, 107(5), 331–335. Lin, C. C., Su, C. H., Kuo, P. H., Hsiao, C. K., Soong, W. T., & Chen, W. J. (2007). Genetic and environmental influences on schizotypy among adolescents in Taiwan: A multivariate twin-­sibling analysis. Behavior Genetics, 37(2), 334–344. Lin, H-F., Liu, Y-L., Liu, C-M., Hung, S-I., Hwu, H-G., & Chen, W. J. (2005). Neuregulin 1 gene and variations in perceptual aberration of schizotypal personality in adolescents. Psychological Medicine, 35(11), 1589–1598. Link, B. G., Dohrenwend, B. P., & Skodol, A. E. (1986). Socio-economic status and schizophrenia: Noisome occupational characteristics as a risk factor. American Sociological Review, 51, 242–258. Linscott, R. J. (2007). The latent structure and coincidence of hypohedonia and schizotypy and their validity as indices of psychometric risk for schizophrenia. Journal of Personality Disorders, 21(3), 225–242. Linscott, R. J., Marie, D., Arnott, K. L., & Clarke, B. L. (2006). Overrepresentation of Maori New Zealanders among adolescents in a schizotypy taxon. Schizophrenia Research, 84(2–3), 289–296. Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: Wiley. Livesley, W. J., Jang, K. L., Jackson, D. N., & Vernon, P. A. (1993). Genetic and environmental contributions to dimensions of personality disorder. American Journal of Psychiatry, 150(12), 1826–1831. Livesley, W. J., Jang, K. L., & Vernon, P. A. (1998). Phenotypic and genetic structure of traits delineating personality disorder. Archives of General Psychiatry, 55(10), 941–948. Loevinger, J. (1954). The attenuation paradox in test theory. Psychological Bulletin, 51(5), 493–504. Loevinger, J. (1957). Objective tests as instruments of psychological theory. Psychological Reports, 3, 635–694. Loewy, R. L., Bearden, C. E., Johnson, J. K., Raine, A., & Cannon, T. D. (2005). The prodromal questionnaire (PQ): Preliminary validation of a self-­report screening measure for prodromal and psychotic syndromes. Schizophrenia Research, 79(1), 117–125. Loomis, J. M., & Lederman, S. J. (1986). Tactual perception. In K. R. Boff, L. Kaufman, & J. P. Thomas (Eds.), Handbook of perception and human performance: Vol. 2. Cognitive processes and performance (pp. 31–41). New York: Wiley. López-Muñoz, F., Alamo, C., Cuenca, E., Shen, W. W., Clervoy, P., Rubio, G. (2005). History of the discovery and clinical introduction of chlorpromazine. Annals of Clinical Psychiatry, 17 Special issue: The History of Antipsychotics.113–135. Loranger, A. (1990). The impact of DSM-III on diagnostic practice in a university hospital: A comparison of DSM-II and DSM-III in 10,914 patients. Archives of General Psychiatry, 47, 672–675. Loranger, A. W. (1999). International Personality Disorder Examination: DSM-IV and ICD10 interviews. Odessa, FL: Psychological Assessment Resources. Loranger, A. W., Lenzenweger, M. F., Gartner, A., Susman, V., Herzig, J., Zammit, G. K., et al. (1991). Trait–state artifacts and the diagnosis of personality disorders. Archives of General Psychiatry, 48, 720–728.

References

417

Loranger, A. W., Sartorius, N., Andreoli, A., Berger, P., Channabasavanna, S. M., Coid, B., et al. (1994). The International Personality Disorder Examination (IPDE): The World Health Organization / Alcohol, Drug Abuse, and Mental Health Administration International Pilot Study of Personality Disorders. Archives of General Psychiatry, 51, 215–224. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading, MA: Addison-­Wesley. Lubinski, D. (2000). Scientific and social significance of assessing individual differences: “Sinking shafts at a few critical points.” Annual Review of Psychology, 51, 405–444. Luck, S. J., & Gold, J. M. (2008). The translation of cognitive paradigms for patient research. Schizophrenia Bulletin, 34(4), 629–644. Lykken, D. T. (1968). Statistical significance in psychological research. Psychological Bulletin, 70, 151–159. Lykken, D. T. (1991). What’s wrong with psychology anyway? In D. Cicchetti & W. M. Grove (Eds.), Thinking clearly about psychology: Volume I: Matters of public interest (Essays in honor of Paul E. Meehl) (pp. 3–39). Minneapolis, MN: University of Minnesota Press. MacCorquodale, K., & Meehl, P. E. (1948). On a distinction between hypothetical constructs and intervening variables. Psychological Review, 55(2), 95–107. MacFarlane, R. (1996). Taxometric Analysis of Schizotypy (Unpublished doctoral dissertation). University of Iowa. MacMillan, N. A., & Creelman, C. D. (2005). Detection theory: A user’s guide. Mahwah, NJ: Erlbaum. Maher, B. A. (1966). Principles of psychopathology: An experimental approach. Oxford, UK: McGraw-Hill. Maher, B. A. (1972). The language of schizophrenia: A review and interpretation. British Journal of Psychiatry, 120, 3–17. Maher, B. A. (1974). Editorial. Journal of Consulting and Clinical Psychology, 42(1), (1–3. Maher, B. A. (1983). Towards a tentative theory of schizophrenic utterance. Progress in Experimental Personality Research (Vol. 12). New York: Academic Press. Maher, B. A. (1993). Manual for the measurement and interpretation of lateralization by line drawing. Cambridge, MA: Author. Maher, B. A. (2003). Psychopathology and delusions: Reflections on methods and models. In M. F. Lenzenweger & J. M. Hooley (Eds.), Principles of experimental psychopathology: Essays in honor of Brendan A. Maher (pp. 9–28). Washington, DC: American Psychological Association. Maher, B. A., & Gottesman, I. I. (2005). Deconstructing, reconstructing, preserving Paul E. Meehl’s legacy of construct validity. Psychological Assessment, 17(4), 415–422. Maher, B. A., & Lenzenweger, M. F. (2006, October). Research in psychopathology: Some paths for the next twenty years. Paper presented at the 20th annual meeting of the Society for Research in Psychopathology, University of California at San Diego. Maher, B. A. & Manschreck, T. C. (1998) Lateralization, memory and language in schizophrenia: Some facts and an artifact. In M.F.Lenzenweger and R.H.Dworkin (Eds.), Origins and development of schizophrenia: Advances in experimental psychopathology (pp. 211–233). Washington, D.C: American Psychological Association. Maier, W., Falkai, P., & Wagner, M. (1999). Schizophrenia-­spectrum disorders. In M. Maj (Ed.), World Psychiatric Association series: Evidence and experience in psychiatry. schizophrenia (Vol. 2, pp. 311–371). Chichester, UK: Wiley.

418 References Malamud, W., & Nygard, W. J. (1931). The role played by the cutaneous senses in spatial perceptions: II. Investigations with mental diseases. Journal of Nervous and Mental Disease, 73, 465–477. Mangalore, R., & Knapp, M. (2007). Cost of schizophrenia in England. Journal of Mental Health Policy and Economics, 10(1), 23–41. Manoach, D. S., Halpern, E. F., Kramer, T. S., Chang, Y., Goff, D. C., Rauch, S. L., et al. (2001). Test–­retest reliability of a functional MRI working memory paradigm in normal and schizophrenic subjects. American Journal of Psychiatry, 158(6), 955–958. Manschreck, T. (1986). Motor abnormalities in schizophrenia. In H. Nasrallah & D. R. Weinberger (Eds.), Handbook of schizophrenia: Volume 1. The neurology of schizophrenia (pp. 65–96). New York: Elsevier. Manschreck, T. C., Maher, B. A., Hoover, T. M., & Ames, D. (1984). The type-token ratio in schizophrenic disorders: Clinical and research value. Psychological Medicine, 14, 151–157. Manschreck, T. C., Maher, B. A., Winzig, L., Candela, S. F., Beaudette, S., & Boshes, R. (2000). Age disorientation in schizophrenia: An indication of progressive and severe psychopathology, not institutional isolation. Journal of Neuropsychiatry and Clinical Neurosciences, 12, 350–358. Manschreck, T. C., Redmond, D. A., Candela, S. F., & Maher, B. A. (1999). Deterioration in performance over time associated with non-­response to clozapine medication in schizophrenia patients. Journal of Neuropsychiatry and Clinical Neurosciences, 11, 481–489. Maraun, M. D., & Slaney, K. (2005). An analysis of Meehl’s MA COV-HITMA procedure for the case of continuous indicators. Multivariate Behavioral Research, 40(4), 489–518. Maric, N., Myin-­Germeys, I., Delespaul, P., de Graaf, R., Vollebergh, W., & van Os, J. (2004). Is our concept of schizophrenia influenced by Berkson’s bias? Social Psychiatry and Psychiatric Epidemiology, 39(8), 600–605. Marieb, E. L. (1998). Human anatomy and physiology (4th ed.). Menlo Park, CA. Benjamin/ Cummings Science. Martin, S. P. (1996). Neuroanatomy: Text and atlas (2nd ed.). New York: Appleton & Lange. Martini, F. R. (2001). Fundamentals of anatomy and physiology (5th ed). Upper Saddle River, NJ: Prentice-Hall Inc. Mason, O. (1995). A confirmatory factor analysis of the structure of schizotypy. European Journal of Personality, 9, 271–281. Mason, O., & Claridge, G. (2006). The Oxford–­Liverpool inventory of feelings and experiences (O-LIFE): Further description and extended norms. Schizophrenia Research, 82(2–3), 203–211. Matthysse, S. (1993). Genetics and the problem of causality in abnormal psychology. In P. B. Sutker & H. E. Adams (Eds.), Comprehensive handbook of psychopathology (2nd ed.), (pp. 47–56). New York: Plenum Press. Matthysse, S., & Holzman, P. S. (1987). Genetic latent structure models: Implication for research on schizophrenia. Psychological Medicine, 17, 271–274. Matthysse, S., Holzman, P., Gussela, J. F., Levy, D. L., Harte, C. B., Jorgensen, A., et al. (2004). Linkage of eye movement dysfunction to chromosome 6p in schizophrenia: Additional evidence. American Journal of Human Genetics, Part B. Neuropsychiatric Genetics, 128b, 30–36.

References

419

Matthysse, S., Holzman, P. S., & Lange, K. (1986). The genetic transmission of schizophrenia: Application of Mendelian latent structure analysis to eye tracking dysfunctions in schizophrenia and affective disorder. Journal of Psychiatric Research, 20(1), 57–76. Matthysse, S., Levy, D. L., Wu, Y., Rubin, D. B., & Holzman, P. (1999). Intermittent degradation in performance in schizophrenia. Schizophrenia Research, 40(2), 131–146. Matthysse, S., & Parnas, J. (1992). Extending the phenotype of schizophrenia: Implications for linkage analysis. Journal of Psychiatric Research, 26(4), 329–344. McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., et al. (2008). Genome-wide association studies for complex traits: Consensus, uncertainty and challenges. Nature Reviews Genetics, 9(5), 356–369. McClellan, J. M., Susser, E., & King, M.-C. (2007). Schizophrenia: A common disease caused by multiple rare alleles. British Journal of Psychiatry, 190(3), 194–199. McDavid, J. D., & Pilkonis, P. A. (1996). The stability of personality disorder diagnoses. Journal of Personality Disorders, 10, 1–15. McGhie, A. & Chapman, J. (1961). Disorders of attention and perception in early schizophrenia. British Journal of Medical Psychology, 34, 103–116. McGlashan, T. H., Addington, J., Cannon, T., Heinimaa, M., McGorry, P., O’Brien, M., et al. (2007). Recruitment and treatment practices for help-­seeking “prodromal” patients. Schizophrenia Bulletin, 33(3), 715–726. McGorry, P. D., Edwards, J., Mihalopoulos, C., Harrigan, S. M., & Jackson, H. J. (1996). EPPIC: An evolving system of early detection and optimal management. Schizophrenia Bulletin, 22, 305–326. McIntosh. A. M., Baig, B. J., Hall, J., Job, D., Whalley, H. C., Lymer, G. K. S., et al. (2007). Relationship of Catechol-O-Methyltransferase variants to brain structure and function in a population at high risk of psychosis. Biological Psychiatry, 61, 1127–1134. McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley. McLachlan, G. J., Do, K.-A., & Ambroise, C. (2004). Analyzing microarray gene expression data. Hoboken, NJ: Wiley. Meehl, P. E. (1945). The dynamics of “structured” personality tests. Journal of Clinical Psychology, 1, 296–303. Meehl, P. E. (1954). Clinical versus statistical prediction: A theoretical analysis and a review of the evidence. Minneapolis: University of Minnesota Press. [Reprinted with new Preface, 1996, by Jason Aronson, Northvale, NJ.] Meehl, P. E. (1956). Wanted: A good cookbook. American Psychologist, 11, 263–272. Meehl, P. E. (1962). Schizotaxia, schizotypy, schizophrenia. American Psychologist, 17, 827– 838. Meehl, P. E. (1964). Manual for use with Checklist of Schizotypic Signs. Minneapolis: University of Minnesota. Meehl, P. E. (1966). Memo to Lykken on schizophrenia research strategy. Unpublished manuscript. Meehl, P. E. (1967). Theory-­testing in psychology and physics: A methodological paradox. Philosophy of Science, 34, 103–115. Meehl, P. E. (1970). Nuisance variables and the ex post facto design. In M. Radner & S. Winokur (Eds.), Minnesota studies in the philosophy of science: Vol. IV. Analyses of theories and methods of physics and psychology (pp.  373–402). Minneapolis: University of Minnesota Press. Meehl, P. E. (1971). High school yearbooks: A reply to Schwarz. Journal of Abnormal Psychology, 77, 143–148.

420 References Meehl, P. E. (1972a). A critical afterword. In I. I. Gottesman & J. Shields (Eds.), Schizophrenia and genetics: A twin study vantage point (pp. 367–415). New York: Academic Press. Meehl, P. E. (1972b). Specific genetic etiology, psychodynamics and therapeutic nihilism. International Journal of Mental Health, 1, 10–27. Meehl. P. E. (1973). Psychodiagnosis: Selected papers. Minneapolis: University of Minnesota Press. Meehl, P. E. (1975). Hedonic capacity: Some conjectures. Bulletin of the Menninger Clinic, 39, 295–307. Meehl, P. E. (1977). Specific etiology and other forms of strong influence: Some quantitative meanings. Journal of Medicine and Philosophy, 2, 33–53. Meehl, P. E. (1978). Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology. Journal of Consulting and Clinical Psychology, 46, 806– 834. Meehl, P. E. (1979). A funny thing happened to us on the way to the latent entities. Journal of Personality Assessment, 43(6), 564–581. Meehl, P. E. (1986a). Causes and effects of my disturbing little book. Journal of Personality Assessment, 50(3), 370–375. Meehl, P. E. (1986b). Diagnostic taxa as open concepts: Metatheoretical and statistical questions about reliability and construct validity in the grand strategy of nosological revision. In T. Millon & G. L. Klerman (Eds.), Contemporary directions in psychopathology: Toward the DSM-IV (pp. 215–231). New York: Guilford Press. Meehl, P. E. (1987). “Hedonic capacity” ten years later: Some clarifications. In D. C. Clark & J. Fawcett (Eds.), Anhedonia and affect deficit states (pp. 47–50). New York: PMA. Meehl, P. E. (1989). Schizotaxia revisited. Archives of General Psychiatry, 46, 935–944. Meehl, P. E. (1990a). Toward an integrated theory of schizotaxia, schizotypy, and schizophrenia. Journal of Personality Disorders, 4, 1–99. Meehl, P. E. (1990b). Why summaries of research on psychological theories are often uninterpretable. Psychological Reports, 66, 195–244. Meehl, P. E. (1990c). Appraising and amending theories: The strategy of Lakatosian defense and two principles that warrant it. Psychological Inquiry, 1, 108–141; 173–180. Meehl, P. E. (1992). Factors and taxa, traits and types, differences of degree and differences of kind. Journal of Personality, 60(1), 117–174. Meehl, P. E. (1993). Philosophy of science: Help or hindrance? Psychological Reports, 72, 707–733. Meehl, P. E. (1995). Bootstraps taxometrics: Solving the classification problem in psychopathology. American Psychologist, 50, 266–275. Meehl, P. E. (1999). Clarifications about taxometric method. Applied and Preventive Psychology, 8(3), 165–174. Meehl, P. E. (2001). Primary and secondary hypohedonia. Journal of Abnormal Psychology, 110(1), 188–193. Meehl, P. E. (2004). What’s in a taxon? Journal of Abnormal Psychology, 113, 39–43. Meehl, P. E. (2006). The power of quantitative thinking. In N. G. Waller, L. J. Yonce, W. M. Grove, D. Faust, & M. F. Lenzenweger (Eds.), A Paul Meehl reader: Essays on the practice of scientific psychology (pp. 433–444). Mahwah, NJ: Erlbaum. (Original work published 1998) Meehl, P. E., & Sellars, W. (1956). The concept of emergence. In H. Feigl & M. Scriven (Eds.), Minnesota studies in the philosophy of science: Vol. I. The foundations of science and

References

421

the concepts of psychology and psychoanalysis (pp. 239–252). Minneapolis: University of Minnesota Press. Meehl, P. E., & Waller, N. G. (2002). The path analysis controversy: A new statistical approach to strong appraisal of verisimilitude. Psychological Methods, 7(3), 283–300. Meehl, P. E., & Yonce, L. J. (1994). Taxometric analysis: I. Detecting taxonicity with two quantitative indicators using means above and below a sliding cut (MAMBAC procedure). Psychological Reports, 74, 1059–1274. Meehl, P. E., & Yonce, L. J. (1996). Taxometric analysis: II. Detecting taxonicity using covariance of two quantitative indicators in successive intervals of a third indicator. Psychological Reports, 78, 1091–1227. Merikangas, K. R., & Risch, N. (2003). Will the genomics revolution revolutionize psychiatry? American Journal of Psychiatry, 160(4), 625–635. Meyer, G. J. (2002). Implications of information-­gathering methods for a refined taxonomy of psychopathology. In L. E. Beutler & M. Malik (Eds.). Rethinking the DSM: Psychological perspectives (pp. 69–105). Washington, DC: American Psychological Association. Meyer, T., & Keller, F. (2001). Exploring the latent structure of the perceptual aberration, magical ideation and physical anhedonia scales in a German sample: A partial replication. Journal of Personality Disorders, 15, 521–535. Meyer-­Lindenberg, A., & Weinberger, D. R. (2006). Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nature Reviews Neuroscience, 7(10), 818–827. Meyers, J. E., & Meyers, K. R. (1995). Rey complex figure test and recognition trial: Professional manual. Odessa, FL: Psychological Assessment Resources. Miers, T. C., & Raulin, M. L. (1987). Cognitive slippage scale (CSS). In K. J. Corcoran (Ed.), Measures of clinical practice: A sourcebook (pp. 125–127). New York: Free Press. Mijolla-­Mellor, S. (2002). The evolution of psychoanalytic practice with psychotic patients. Psychoanalysis and History, 4(1), 31–43. Miller, A. B., & Lenzenweger, M. F. (2010). Social-­interpersonal information processing and schizotypy. Manuscript in preparation. Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202. Miller, G. A. (1995). The behavioral high-risk paradigm in psychopathology. New York: Springer. Miller, G. A., & Chapman, J. P. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110, 40–48. Miller, M. B., & Chapman, J. P. (1993, October). A twin study of schizotypy in college-age males. Paper presented at the eighth annual meeting of the Society for Research in Psychopathology, Chicago. Milné, D. A., Roché, M. W., Ribb, K., Sloat, V. C., Maher, B. A., Manschreck, T. C., et al. (2008, September). Increased thought associations in verbal utterances of schizotypes: Replication and extension. Poster session presented at the 22nd annual meeting of the Society for Research in Psychopathology, University of Pittsburgh. Millon, T. (1987). Millon Clinical Multiaxial Inventory-II manual. Minneapolis, MN: National Computer Systems, Inc. Minzenberg, M. J., Laird, A. R., Thelen, S., Carter, C. S., & Glahn, D. C. (2009). Meta­analysis of 41 functional neuroimaging studies of executive function in schizophrenia. Archives of General Psychiatry, 66, 811–822. Mischel, W., Shoda, Y., & Rodriguez, M. L. (1989). Delay of gratification in children. Science, 244, 933–938.

422 References Mishlove, M., & Chapman, L. J. (1985). Social anhedonia in the prediction of psychosis proneness. Journal of Abnormal Psychology, 94, 384–396. Modstein, J., Huber, A., Satirli, E., Malti, T., & Hell, D. (2003). Long-term course of schizophrenic illness: Bleuler’s study reconsidered. American Journal of Psychiatry, 160(12), 2202–2208. Mohanty, A., Herrington, J. D., Koven, N. S., Fisher, J. E., Wenzel, E. A., Webb, A. G., et al. (2005). Neural mechanisms of affective interference in schizotypy. Journal of Abnormal Psychology, 114(1), 16–27. Morey, L. C., Waugh, M. H., & Blashfield, R. K. (1985). MMPI scales for DSM-III personality disorders: Their derivation and correlates. Journal of Personality Assessment, 49, 245–251. Mortimer, J. T., Finch, M. D., & Kumka, D. S. (1982). Persistence and change in development: The multidimensional self-­concept. In P. B. Baltes & O. Brim (Eds.), Life-span development and behaviors (Volume 4, pp. 263–313). New York: Academic Press. Murphy, E. A. (1964). One cause? Many causes? The argument from the bimodal distribution. Journal of Chronic Diseases, 17, 301–324. Nagin, D. S. (1999). Analyzing developmental trajectories: Semi-­parametric, group-based approach. Psychological Methods, 4, 39–77. Nagin, D. S. (2005). Group-based modeling of development. Cambridge, MA: Harvard University Press. National Institute of Drug Abuse. (2003). Marijuana Abuse. National Institute of Drug Abuse Report Series (NIH Pub. No. 05-3859). Washington, DC: U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Drug Abuse. Neale, J. M., & Oltmanns, T. F. (1980). Schizophrenia. New York: Wiley. Nesselroade, J., & Baltes, P. (1979). Longitudinal research in the study of behavior and development. New York: Academic Press. Nesselroade, J., Stigler, S., & Baltes, P. (1980). Regression toward the mean and the study of change. Psychological Bulletin, 88, 622–637. Nicodemus, K. K., Marenco, S., Batten, A. J., Vakkalanka, R., Eagan, M. F., Straub, R. E., et al. (2008). Serious obstetric complications interact with hypoxia-­regulated/vascular­expression genes to influence schizophrenia risk. Molecular Psychiatry, 13, 873–877. Niebuhr, D., Millikan, A. M., Cowan, D. N., Yolken, R., Li, Y., & Weber, N. S. (2008). Selected infectious agents and risk of schizophrenia among U.S. military personnel. American Journal of Psychiatry, 165(1), 99–106. Nordentoft, M., Thorup, A., Petersen, L., Øhlenschlæger, J., Melau, M., Christensen, T. Ø., et al. (2006). Transition rates from schizotypal disorder to psychotic disorder for first­contact patients included in the OPUS trial: A randomized clinical trial of integrated treatment and standard treatment. Schizophrenia Research, 83(1), 29–40. Norton, N., Williams, H. J., & Owen, M. J. (2006). An update on the genetics of schizophrenia. Current Opinion in Psychiatry, 19(2), 158–164. Nuechterlein, K. H. (1987). Vulnerability models for schizophrenia: State of the art. In H. Hafner, W. F. Gattaz, & W. Janzarik (Eds.), Search for the causes of schizophrenia (pp. 295–316). New York: Springer-­Verlag. Nuechterlein, K. H., Asarnow, R. F., Subotnik, K. L., Fogelson, D. L., Ventura, J., Torquato, R. D., et al. (1998). Neurocognitive vulnerability factors for schizophrenia: Convergence across genetic risk studies and longitudinal trait–state studies. In M. F. Lenzen-

References

423

weger & R. H. Dworkin (Eds.), Origins and development of schizophrenia: Advances in experimental psychopathology (pp. 299–327). Washington, DC: American Psychological Association. Nuechterlein, K. H., Barch, D. M., Gold, J. M., Goldberg, T. E., Green, M. F., & Heaton, R. K. (2004). Identification of separable cognitive factors in schizophrenia. Schizophrenia Research, 72(1), 29–39. Nuechterlein, K. H., & Dawson, M. E. (1984). Information processing and attentional functioning in the developmental course of schizophrenic disorders. Schizophrenia Bulletin, 10, 160–202. Nunnally, J., & Bernstein, I. H. (1994). Psychometric theory (3rd ed). New York: McGrawHill. Obiols, J. E., Garcia-­Domingo, M., de Trincheria, I., & Domenech, E. (1993). Psychometric schizotypy and sustained attention in young males. Personality and Individual Differences, 14, 381–384. Ochsner, K. N. (2008). The social–­emotional processing stream: Five core constructs and their translational potential for schizophrenia and beyond. Biological Psychiatry, 64, 48–61. O’Donovan, M. C., Craddock, N., Norton, N., Williams, H., Peirce, T., Moskvina, V., et al. (2008). Identification of loci associated with schizophrenia by genome-wide association and follow-up. Nature Genetics, 40(9), 1053–1055. O’Driscoll, G. A., & Callahan, B. L. (2008). Smooth pursuit in schizophrenia: A meta­analytic review of research since 1993. Brain and Cognition, 68, 359–370. O’Driscoll, G., Lenzenweger, M. F., & Holzman, P. S. (1998). Antisaccades and smooth pursuit eye tracking and schizotypy. Archives of General Psychiatry, 55, 837–843. OSS Assessment Staff. (1948). Assessment of men: Selection of personnel for the Office of Strategic Services. New York: Rinehart. Owen, M. J., Craddock, N., & O’Donovan, M. C. (2005). Schizophrenia: Genes at last? Trends in Genetics, 21(9), 518–525. Owens, D. G. C., & Johnstone, E. C. (2006). Precursors and prodromata of schizophrenia: Findings from the Edinburgh high-risk study and their literature context. Psychological Medicine, 36(11), 1–14. Parasuraman, R. (1984). The psychobiology of sustained attention. In J. S. Warm (Ed.), Sustained attention in human performance (pp. 61–101). New York: Wiley. Park, S., & Holzman, P. S. (1992). Schizophrenics show working memory deficits. Archives of General Psychiatry, 49, 975–982. Park, S., Holzman, P. S., & Goldman-Rakic, P. (1995). Spatial working memory deficits in the relatives of schizophrenic patients. Archives of General Psychiatry, 52, 821–828. Park, S., Holzman, P. S., & Lenzenweger, M. F. (1995). Individual differences in working memory in relation to schizotypy. Journal of Abnormal Psychology, 104, 355–363. Park, S., & McTigue, K. (1997). Working memory and the syndromes of schizotypal personality. Schizophrenia Research, 26, 213–220. Parnas, J. (2005). Clinical detection of schizophrenia-prone individuals. British Journal of Psychiatry, 187(Suppl. 48), s111–s112. Pause, M., Kunesch, E., Binkofski, F., & Freund, H.-J. (1989). Sensorimotor disturbances in patients with lesions of the parietal cortex. Brain, 112, 1599–1625. Pearl, J. (2009). Causality: Models, reasoning, and inference (2nd ed.). New York: Cambridge University Press.

424 References Pearson, J. S., & Kley, I. B. (1957). On the application of genetic expectancies as age­specific base rates in the study of human behavior disorders. Psychological Bulletin, 54(5), 406–420. Penney, D., & Stastny, P. (2008). The lives they left behind: Suitcases from a state hospital attic. New York: Bellevue Literary Press. Perry, J. W. (1976). Roots of renewal in myth and madness. San Francisco: Jossey-Bass. Peterson, S. E., & Fiez, J. A. (1993).The processing of single words studied with positron emission tomography. Annual Review of Neuroscience, 16, 509–530. Petronis, A. (2001). Human morbid genetics revisited: Relevance of epigenetics. Trends in Genetics, 17(3), 142–146. Petronis, A. (2004). The origin of schizophrenia: Genetic thesis, epigenetic antithesis, and resolving synthesis. Biological Psychiatry, 55(10), 965–970. Petronis, A. (2006). Epigenetics and twins: Three variations on the theme. Trends in Genetics, 22(7), 347–350. Piskulic, D., Olver, J. S., Norman, T. R., & Maruff, P. (2007). Behavioural studies of spatial working memory dysfunction in schizophrenia: A quantitative literature review. Psychiatry Research, 150(2), 111–121. Pope, H. G., Jr., Jonas, J. M., Cohen, B. M., & Lipinski, J. (1982). Failure to find evidence of schizophrenia in first-­degree relatives of schizophrenia probands. American Journal of Psychiatry, 139, 826–828. Posner, M. I. (Ed.). (2004). Cognitive neuroscience of attention. New York: Guilford Press. Post, S. G. (2001). Preventing schizophrenia and Alzheimer disease: Comparative ethics. Schizophrenia Research, 51, 103–108. Preacher, K. J., Rucker, D. D., MacCallum, R. C., & Nicewander, W. A. (2005). Use of the extreme groups approach: A critical reexamination and new recommendations. Psychological Methods, 10(2), 178–192. Prentice, K. J., Gold, J. M., & Buchanan, R. W. (2008). The Wisconsin Card Sorting impairment in schizophrenia is evident in the first four trials. Schizophrenia Research, 106, 81–87. Price, J. M., & Lento, J. (2001). The nature of child and adolescent vulnerability: History and definitions. In R. E. Ingram & J. M. Price (Eds.), Vulnerability to psychopathology: Risk across the lifespan (pp. 20–38). New York: Guilford Press. Putnam, H. (1983). Realism and reason. Cambridge, UK: Cambridge University Press. Quine, W. V. O. (1969). Natural kinds. In W. V. O. Quine, Ontological relativity and other essays (pp. 114–138). New York: Columbia University Press. Rado, S. (1953). Dynamics and classification of disordered behavior. American Journal of Psychiatry, 110, 406–416. Rado, S. (1960). Theory and therapy: The theory of schizotypal organization and its application to the treatment of decompensated schizotypal behavior. In S. C. Scher & H. R. Davis (Eds.), The outpatient treatment of schizophrenia (pp. 87–101). New York: Grune & Stratton. Raine, A. (1991). The SPQ: A scale for the assessment of schizotypal personality disorder based on DSM-III-R criteria. Schizophrenia Bulletin, 17, 555–564. Raine, A., Lencz, T., & Mednick, S. (1995). Schizotypal personality. New York: Cambridge University Press. Raine, A., Reynolds, C., Lencz, T., Scerbo, A., Triphon, N., & Kim, D. (1994). Cognitive­perceptual, interpersonal, and disorganized features of schizotypal personality. Schizophrenia Bulletin, 20, 191–201.

References

425

Raine, A., Sheard, C., Reynolds, G., & Lencz, T. (1992). Pre-­frontal structural and functional deficits associated with individual differences in schizotypal personality. Schizophrenia Research, 7, 237–247. Raskin, D. E. (1975). Bleuler and schizophrenia. British Journal of Psychiatry, 127(3), 231–234. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed). Thousand Oaks, CA: Sage. Raulin, M. L. (1986). Schizotypal ambivalence scale. Unpublished manuscript. Available from M. L. Raulin, Psychology Department, State University of New York at Buffalo, Buffalo, NY 14260. Raulin, M. L., Lowrie, G. S., & Brenner, V. (1994, October). Searching for the schizotypal taxonomy. Paper presented at the annual meeting of the Society for Research in Psychopathology, Coral Gables, FL. Raulin, M. L., & Wee, J. L. (1984). The development and initial validation of a scale to measure social fear. Journal of Clinical Psychology, 40, 780–784. Rawlings, D., & Goldberg, M. (2001). Correlating a measure of sustained attention with a multidimensional measure of schizotypal traits. Personality and Individual Differences, 31, 421–431. Rawlings, D., Williams, B., Haslam, N., & Claridge, G. (2008a). Is schizotypy taxonic? Response to Beauchaine, Lenzenweger, & Waller. Personality and Individual Differences, 44(8), 1663–1672. Rawlings, D., Williams, B., Haslam, N., & Claridge, G. (2008b). Taxometric analysis supports a dimensional latent structure for schizotypy. Personality and Individual Differences, 44(8), 1640–1651. Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., et al. (2006). Global variation in copy number in the human genome. Nature, 444(7118), 444–454. Reichenbach, H. (1938). Experience and prediction. Chicago: University of Chicago Press. Reichenbach, H. (1956). The rise of scientific discovery. Berkeley, CA: University of California Press. Ribes-Iñesta, E. (2003). What is defined in operational definitions? The case of operant psychology. Behavior and Philosophy, 31, 111–126. Riddihough, G., & Pennisi, E. (2001). The evolution of epigenetics. Science, 293(5532), 1063. Risch, N. J. (2000). Searching for genetic determinants in the new millennium. Nature, 405(6788), 847–856. Ritsner, M. S., & Gottesman, I. I. (2009). Where do we stand in the quest for neuropsychiatric biomarkers and endophenotypes and what next? In M. S. Ritsner (Ed.), Neuropsychiatric biomarkers, endophenotypes, and genes: Volume 1: Neuropsychological endophenotypes and biomarkers. (pp. 3–22). New York: Springer. Ritsner, M., Modai, I., Ziv, H., Amir, S., Halperin, T., Weizman, A., et al. (2002). An association of CAG repeats at the KCNN3 with symptom dimensions of schizophrenia. Biological Psychiatry, 51(10), 788–794. Ritzler, B. (1977). Proprioception and schizophrenia: A replication study with nonschizophrenic patient controls. Journal of Abnormal Psychology, 86, 501–509. Ritzler, B., & Rosenbaum, G. (1974). Proprioception in schizophrenia and normals: Effects of stimulus intensity and interstimulus interval. Journal of Abnormal Psychology, 83, 106–111. Robins, E., & Guze, S. B. (1970). Establishment of diagnostic validity in psychiatric illness: Its applications to schizophrenia. American Journal of Psychiatry, 126(7), 983–987.

426 References Robins, R. W., Fraley, R. C., Roberts, B. W., & Trzesniewski, K. H. (2001). A longitudinal study of personality change in young adulthood. Journal of Personality, 69, 617–640. Roberts, B. W., & DelVecchio, W. F. (2000). The rank-order consistency of personality traits from childhood to old age: A quantitative review of longitudinal studies. Psychological Bulletin, 126, 3–25. Roberts, B. W., Walton, K. E., & Viechtbauer, W. (2006). Patterns of mean-level change in personality traits across the life course: A meta-­analysis of longitudinal studies. Psychological Bulletin, 132, 1–25. Rogosa, D. (1988). Myths about longitudinal research. In K. Shaie, R. Campbell, W. Meredith, & S. Rawling (Eds.), Methodological issues in aging research (pp. 171–209). New York: Springer. Rogosa, D., Brandt, D., & Zimowski, M. (1982). A growth curve approach to the measurement of change. Psychological Bulletin, 90, 726–748. Rogosa, D. R., & Willett, J. B. (1985). Understanding correlates of change by modeling individual differences in growth. Psychometrika, 50, 203–228. Romo, R., Hernandez, A., Zainos, A., Lemus, L., & Brody, C. (2002). Neuronal correlates of decision making in secondary somatosensory cortex. Nature Neuroscience, 5(11), 1217–1225. Rosen, A. (1952). Development of some new MMPI scales for differentiation of psychiatric syndromes within an abnormal population. Dissertation Abstracts International: Section B. Sciences and Engineering, 12, 785A. Rosen, A. (1962). Development of the MMPI scales based on a reference group of psychiatric patients. Psychological Monographs, 76 (8, Whole No. 527). Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55. Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79(387), 516–524. Rosenthal, D., & Kety, S. S. (1968). The transmission of schizophrenia. New York: Pergamon. Rosenthal, D., Wender, P. H., Kety, S. S., Welner, J., & Schulsinger, F. (1971). The adoptedaway offspring of schizophrenics. American Journal of Psychiatry, 128, 307–311. Rosenthal, R. (1994). Interpersonal expectancy effects: A 30-year perspective. Current Directions in Psychological Science, 3(6), 176–179. Rosenthal, R. (2003). Covert communications in laboratories, classrooms, and the truly real world. Current Directions in Psychological Science, 12(5), 151–154. Rosenthal, R., & Rosnow, R.L. (1985). Contrast analysis in behavioral research: Focused comparisons in the analysis of variance. New York: Cambridge. Rosenthal, R., & Rosnow, R. (1991). Essentials of behavioral research (2nd ed.). New York: McGraw-Hill. Rosenthal, R., & Rosnow, R. L. (2008). Essentials of behavioral research: Methods and data. (3rd ed.). New York: McGraw-Hill. Rosenthal, R., Rosnow, R. L., & Rubin, D. B. (2000). Contrasts and effect sizes in behavioral research: A correlational approach. New York: Cambridge University Press. Rosenthal, R., & Rubin, D. B. (1982). A simple, general purpose display of magnitude of experimental effect. Journal of Educational Psychology, 74(2), 166–169. Rosnow, R. L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276–1284.

References

427

Rowe, D. C. (1994). The limits of family influence: Genes, experience, and behavior. New York: Guilford Press. Rozeboom, W. W. (1960). The fallacy of the null hypothesis significance test. Psychological Bulletin, 57, 416–428. Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688–701. Rubin, D. B. (1997). Estimating causal effects from large data sets using propensity scores. Annals of Internal Medicine, 127 (part 2), 757–763. Rubin, D. B (2006). Matched sampling for causal effects. New York: Cambridge. Rubin, D. B., & Wu, Y. N. (1997). Modeling schizophrenic behavior using general mixture components. Biometrics, 53, 243–261. Rumelhart, D. E. (1984). The emergence of cognitive phenomena from the sub-­symbolic processes. In Proceedings of the Sixth Annual Conference of the Cognitive Science Society (pp. 59–62). Boulder, CO: Cognitive Science Society. Ruscio, J., & Ruscio, A. M. (2004). Clarifying boundary issues in psychopathology: The role of taxometrics in a comprehensive program of structural research. Journal of Abnormal Psychology, 113, 24–38. Rust, J. (1988a). The Rust Inventory of Schizotypal Cognition (RISC). Schizophrenia Bulletin, 14, 317–322. Rust, J. (1998b). The Handbook of the Rust Inventory of Schizotypal Cognitions (RISC). London: The Psychological Corporation. Rutter, M., & Rutter, M. (1993). Developing minds: Challenge and continuity across the lifespan. New York: Basic Books. Salanova, V., Andermann, F., Rasmussen, T., Olivier, A., & Quesney, L. F. (1995). Tumoural parietal lobe epilepsy: Clinical manifestations and outcome in 34 patients treated between 1934 and 1988. Brain, 118, 1289–1304. Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press. Sawaguchi, T., & Goldman-Rakic, P. S. (1994).The role of D1-dopamine receptor in working memory: Local injections of dopamine antagonists into the prefrontal cortex of rhesus monkeys performing an oculomotor delayed-­response task. Journal of Neurophysiology, 71, 515–528. Scarone, S., Abbruzzese, M., & Gambini, O. (1993). The Wisconsin Card Sorting Test discriminates schizophrenic patients and their siblings. Schizophrenia Research, 10, 103–107. Schafer, J. L. (1999). Multiple imputation: A primer. Statistical Methods in Medical Research, 8(1), 3–15. Schultze-­Lutter, F., Ruhrmann, S., Berning, J., Maier, W., & Klosterkötter, J. (2010). Basic symptoms and ultrahigh risk criteria: Symptom development in the initial prodromal state. Schizophrenia Bulletin, 36, 182–191. Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-­Martin, C., Walsh, T., et al. (2007). Strong association of de novo copy number mutations with autism. Science, 316(5823), 445–449. Sellen, J. L., Oaksford, M., & Gray, N. S. (2005). Schizotypy and conditional reasoning. Schizophrenia Bulletin, 31(1), 105–116. Selten, J-P., & Cantor-Graae, E. (2005). Social defeat: Risk factor for schizophrenia? British Journal of Psychiatry, 187(2), 181–182.

428 References Semmes, J., Weinstein, L., Ghent, L., & Teuber, H. L. (1960). Somatosensory changes after penetrating brain wounds in man. Cambridge, MA: Harvard University Press. Shea, M. T., Stout, R., Gunderson, J., Morey, L. C., Grilo, C. M., McGlashan, T., et al. (2002). Short-term diagnostic stability of schizotypal, borderline, avoidant, and obsessive–­compulsive personality disorders. American Journal of Psychiatry, 159(12), 2036–2041. Shields, J., & Gottesman, I. I. (1973). Genetic studies of schizophrenia as signposts to biochemistry. Biochemical Society, Special Publication, 1, 165–174. Shrout, P. E. (1997). Should significance tests be banned? Introduction to a special section: Exploring the pros and cons. Psychological Science, 8(1), 1–2. Shtasel, D. L., Gur, R. E., Mozley, P. D., Richards, J., Taleff, M. M., Heimberg, C., et al. (1991). Volunteers for biomedical research: Recruitment and screening of normal controls. Archives of General Psychiatry, 48(11), 1022–1025. Siever, L. J., & Davis, K. L. (2004). The pathophysiology of schizophrenia disorders: Perspectives from the spectrum. American Journal of Psychiatry, 161(3), 398–413. Siever, L. J., Friedman, L., Moskowitz, J., Mitropoulou, V., Keefe, R., Roitman, S. L., et al. (1994). Eye movement impairment and schizotypal psychopathology. American Journal of Psychiatry, 151, 1209–1215. Siever, L. J., Keefe, R., Bernstein, D. P., Coccaro, E. F., Klar, H. M., Zemishlany, Z., et al. (1990). Eye tracking impairment in clinically identified patients with schizotypal personality disorder. American Journal of Psychiatry, 147, 740–745. Silbersweig, D., Clarkin, J. F., Goldstein, M., Kernberg, O., Tuescher, O., Levy, K., et al. (2007). Failure of the fronto-­limbic inhibitory function in the context of negative emotion in borderline personality disorder. American Journal of Psychiatry, 164, 1832–1841. Silbersweig, D. A., Stern, E., Frith, C., Cahill, C., Holmes, A., Grootoonk, S., et al. (1995). A functional neuroanatomy of hallucinations in schizophrenia. Nature, 378, 176–179. Silverstein, S. M. (2008). Measuring specific, rather than generalized, cognitive deficits and maximizing between-group effect size in studies of cognition and cognitive change. Schizophrenia Bulletin, 34(4), 645–655. Simons, R. F., & Katkin, W. (1985). Smooth pursuit eye movements in subjects reporting physical anhedonia and perceptual aberrations. Psychiatry Research, 14, 275–289. Sing, C. F., Haviland, M. B., & Reilly, S. L. (1996). Genetic architecture of common ­multifactorial diseases. In D. J. Chadwick and G. Cardew, (Eds.), Variation in the human genome (Ciba Foundation Symposium 197) (pp. 211–232). Chichester, UK: John Wiley. Sing, C. F., Stengard, J. H., & Kardia, S. L. R. (2003). Genes, environment, and cardiovascular disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 23(7), 1190–1196. Sing, C. F., Stengard, J. H., & Kardia, S. L. R. (2004). Dynamic relationships between the genome and exposures to environments as causes of common human disease. World Review of Nutrition and Dietetics, 93, 77–91. Sing, C. F., Zerba, K. E., & Reilly, S. L. (1994). Traversing the biological complexity in the hierarchy between genome and CAD endpoints in the population at large. Clinical Genetics, 46, 6–14. Singer, M. T., & Nievod, A. (2003). New age therapies. In S. O. Lilienfeld, S. J. Lynn, & J. M. Lohr (Eds.), Science and pseudoscience in clinical psychology (pp. 176–204). New York: Guilford Press. Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press.

References

429

Skelly, S. L., Goldberg, T. E., Egan, M. F., Weinberger, D. R., & Gold, J. M. (2008). Verbal and visual memory: Characterizing the clinical and intermediate phenotype in schizophrenia. Schizophrenia Research, 105, 78–85. Skodol, A. E., Gunderson, J. G., Shea, M. T., McGlashan, T. H., Morey, L. C., Sanislow, C. A., et al. (2005). The Collaborative Longitudinal Personality Disorders Study (CLPS): Overview and implications. Journal of Personality Disorders, 19, 487–504. Smith, G. N., & Iacono, W. G. (1986). Lateral ventricular size in schizophrenia and choice of control group. Lancet, i, 1450. Smith, C., & Mendell, N. R. (1974). Recurrence risks from family history and metric traits. Annals of Human Genetics, 37, 275–286. Smyrnis, N., Avramopoulos, D., Evdokimidis, I., Stefanis, C. N., Tsekou, H., & Stefanis, N. C. (2007). Effect of schizotypy on cognitive performance and its tuning by COMT val158 met genotype variations in a large population of young men. Biological Psychiatry, 61(7), 845–853. Snitz, B. E., MacDonald, A. W., III, & Carter, C. S. (2006). Cognitive deficits in unaffected first-­degree relatives of schizophrenia patients: A meta-­analytic review of putative endophenotypes. Schizophrenia Bulletin, 32(1), 179–194. Spauwen, J., Krabbendam, L., Lieb, R., Wittchen, H-U., & van Os, J. (2006). Evidence that the outcome of developmental expression of psychosis is worse for adolescents growing up in an urban environment. Psychological Medicine, 36(3), 407–415. Sponheim, S. R., McGuire, K. A., & Stanwyck, J. J. (2003). Neural anomalies during sustained attention in first-­degree biological relatives of schizophrenia patients. Biological Psychiatry, 60(3), 242–252. Squires-­Wheeler, E., Skodol, A. E., Bassett, A., & Erlenmeyer-­Kimling, L. (1989). DSM-IIIR schizotypal personality traits in offspring of schizophrenic disorder, affective disorder, and normal control parents. Journal of Psychiatric Research, 23(3–4), 229–239. Squitieri, F., Gellera, C., Cannella, M., Mariotti, C., Cislaghi, G., Rubinsztein, D. C., et al. (2003). Homozygosity for CAG mutation in Huntington disease is associated with a more severe clinical course. Brain, 126(4), 946–955. Stefanis, N., van Os, J., Avramopoulos, D., Smyrnis, N., Evdokimidis, I., Hantoumi, et al. (2004). Variation in catechol-­methyltransferase genotype associated with schizotypy but not cognition: A population study in 543 young men. Biological Psychiatry, 56(7), 510–515. Stefanis, N. C., Trikalinos, T. A., Avramopoulos, D., Smyrnis, N., Evdokimidis, I., Ntzani, E. E., et al. (2007). Impact of schizophrenia candidate genes on schizotypy and cognitive endophenotypes at the population level. Biological Psychiatry, 62(7), 784–792. Stefanis, N. C., Trikalinos, T. A., Avramopoulos, D., Smyrnis, N., Evdokimidis, I., Ntzani, E. E., et al. (2008). Association of RGS4 variants with schizotypy and cognitive endophenotypes at the population level. Behavioral and Brain Functions, 4, 1–9. Stefansson, H., Rujescu, D., Cichon, S., Pietiläinen, O. P., Ingason, A., Steinberg, S., et al. (2008). Large recurrent microdeletions associated with schizophrenia. Nature, 455(7210), 232–236. Stevens, S. S. (1935). The operational definition of psychological concepts. Psychological Review, 42, 517–527. Stevens, S. S. (1939). Psychology and the science of science. Psychological Bulletin, 36, 221–263. Stone, W. S., Faraone, S. V., Seidman, L. J., Olson, E. A., & Tsuang, M. T. (2005). Searching for the liability to schizophrenia: Concepts and methods underlying genetic high-

430 References risk studies of adolescents. Journal of Child and Adolescent Psychopharmacology, 15(3), 403–417. Straub, R. E., Lipska, B. K., Eagan, M. F., Goldberg, T. E., Callicott, J. H., Mayhew, M. B., et al. (2007). Allelic variation in GAD1 (GAD67) is associated with schizophrenia and influences cortical function and gene expression. Molecular Psychiatry, 12, 854–869. Straub, R. E., MacLean, C. J., Ma, Y., Webb, B. T., Myakishev, M. V., Harris-Kerr, C. et al. (2002). Genome-wide scans of three independent sets of 90 Irish multiplex schizophrenia families and follow-up of selected regions in all families provides evidence for multiple susceptibility genes. Molecular Psychiatry, 7, 542–559. Straub, R. E., & Weinberger, D. R. (2006). Schizophrenia genes: Famine to feast. Biological Psychiatry, 60(2), 81–83. Sung, H., Ji, F., Levy, D. L. Matthysse, S., & Mendell, N. R. (2009). The power of linkage analysis of a disease-­related endophenotype using asymmetrically ascertained sib pairs. Computational Statistics & Data Analysis, 53, 1829–1842. Sullivan, H. S. (1956). Clinical studies in psychiatry. New York: Norton. Sullivan, H. S. (1962). Schizophrenia as a human process. New York: Norton. Sung, H., Ji, F., Levy, D. L., Matthysse, S., & Mendell, N. R. (2009). The power of linkage analysis of a disease-­related endophenotype using asymmetrically ascertained sibpairs. Computational Statistics & Data Analysis, 53, 1829–1842. Swets, J. A., & Pickett, R. M. (1982). Evaluation of diagnostic systems: Methods from signal detection theory. New York: Academic Press. Talkowski, M. E., Bamne, M., Mansour, H., & Nimgaonkar, V. L. (2007). Dopamine genes and schizophrenia: Case closed or evidence pending? Schizophrenia Bulletin, 33, 1071– 1081. Tan, H-Y., Chen, Q., Sust, S., Buckholtz, J. W., Meyers, J. D., Eagan, M. F., et al. (2007). Epistasis between catechol-O-methytransferase and type II metabotropic glutamate receptor 3 genes on working memory brain function. Proceedings of the National Academy of Sciences USA, 104, 12536–12541. Thaker, G. K., Cassady, S., Adami, H., & Moran, M. (1996). Eye movements in spectrum personality disorder: Comparison of community subjects and relatives of schizophrenic patients. American Journal of Psychiatry, 153, 362–368. Thompson, J. L., Pogue-Geile, M. F., & Grace, A. A. (2004). Developmental pathology, dopamine, and stress: A model for the age of onset of schizophrenia symptoms. Schizophrenia Bulletin, 30(4), 875–900. Thurston-Snoha, B.-J., & Lewine, R. R. J. (2007). Intact Wisconsin Card Sorting Test performance: Implications for the role of executive function in schizophrenia. British Journal of Clinical Psychology, 46, 361–369. Tienari, P., Wynne, L. C., Läksy, K., Moring, J., Nieminen, P., Sorri, A., et al. (2003). Genetic boundaries of the schizophrenia spectrum: Evidence from the Finnish adoptive family study of schizophrenia. American Journal of Psychiatry, 160(9), 1587–1594. Tishler, C. L., Apseloff, G., Bartholomae, S., Reiss, N. S., Rhodes, A. R., & Singh, A. (2007). Are normal healthy research volunteers psychologically healthy? A pilot investigation. Experimental and Clinical Psychopharmacology, 15(6), 539–545. Titchener, E. B. (1905). Experimental psychology: A manual of laboratory practice. New York: Macmillan. Titchener, E. B. (1916). On ethnological tests of sensation and perception with special reference to the tests of color vision and tactile discrimination described in the reports of

References

431

the Cambridge Anthropological Expedition to Torres Straits. Proceedings of the American Philosophical Society, 55, 204–236. Titterington, D. M., Smith, A. F. M., & Makov, U. E. (1985). Statistical analysis of finite mixture distributions. New York: Wiley. Torgersen, S., Lygren, S., Øien, P. A., Skre, I., Onstad, S., Edvardsen, J., et al. (2000). A twin study of personality disorders. Comprehensive Psychiatry, 41(6), 416–425. Torrey, E. F. (2007). Schizophrenia and the inferior parietal lobule. Schizophrenia Research, 97(1–3), 215–225. Torrey, E. F., Bartko, J. J., Lun, Z-R., & Yolken, R. H. (2007). Antibodies to toxoplasma gondii in patients with schizophrenia: A meta-­analysis. Schizophrenia Bulletin, 33(3), 729–736. Trull, T. J. (1993). Temporal stability and validity of two personality disorder inventories. Psychological Assessment, 5, 11–18. Tsakanikos, E., & Claridge, G. (2005). More words, less words: Verbal fluency as a function of “positive” and “negative” schizotypy. Personality and Individual Differences, 39, 705–713. Tsankova, N., Renthal, W., Kumar, A., & Nestler, E. J. (2007). Epigenetic regulation in psychiatric disorders. Nature Reviews Neuroscience, 8(5), 355–367. Tsuang, M. T., Stone, W. S., Tarbo, S. I., & Faraone, S. V. (2002). An integration of schizophrenia with schizotypy: Identification of schizotaxia and implications for research on treatment and prevention. Schizophrenia Research, 54(1–2), 169–175. Tukey, J. W. (1977). Exploratory data analysis. Reading, MA: Addison-­Wesley. Tulving, E., & Craik, F. I. M. (Eds.). (2000). The Oxford handbook of memory. New York: Oxford University Press. Turetsky, B. I., Calkins, M. E., Light, G. A., Olincy, A., Radant, A. D., & Swerdlow, N. R. (2007). Neurophysiological endophenotypes of schizophrenia: The viability of selected candidate measures. Schizophrenia Bulletin, 33(1), 69–94. Tuulio-­Henriksson, A., Perälä, J., Gottesman, I. I., & Suvisaari, J. (2009). Neuropsychological endophenotypes in schizophrenia and bipolar I disorder: Yields from the Finnish family and twin studies. In M. S. Ritsner (Ed.), Neuropsychiatric biomarkers, endophenotypes, and genes: Promises, advances, and challenges (pp. 125–140). New York: Springer. Uhlhass, P. J., Silverstein, S. M., Phillips, W. A., & Lovell, P. G. (2004). Evidence for impaired visual context processing in schizotypy with thought disorder. Schizophrenia Research, 68, 249–260. Underwood, B. J. (1975). Individual differences as a crucible in theory construction. American Psychologist, 30(2), 128–134. Unsworth, N., & Engle, R. W. (2007a). On division of short-term and working memory: An examination of simple and complex span and their relation to higher order abilities. Psychological Bulletin, 133, 1038–1066. Unsworth, N., & Engle, R. W. (2007b). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review, 114, 104–132. Vallbo, A. B., & Johansson, R. S. (1978). Tactile sensory innervation of the glabrous skinn of the human hand. In G. Gordon (Ed.), Active touch: The mechanism of recognition of objects by manipulation (pp. 29–54). Oxford, England: Pergamon. Vanderweele, T. (2006). The use of propensity score methods in psychiatric research. International Journal of Methods in Psychiatric Research, 15, 95–103.

432 References Venables, P. H. (1990). The measurement of schizotypy in Mauritius. Personality and Individual Differences, 11, 965–971. Verdoux, H., Geddes, J. R., Takei, N., Lawrie, S. M., Bovet, P., Eagles, J. M., et al. (1997). Obstetric complications and age at onset in schizophrenia: An international collaborative meta-­analysis of individual patient data. American Journal of Psychiatry, 154, 1220–1227. Volkow, N. D., Gur, R. C., Wang, G.-J., Fowler, J. S., Moberg, P. J., Ding, Y-S., et al. (1998). Association between decline in brain dopamine activity with age and cognitive and motor impairment in healthy individuals. American Journal of Psychiatry, 155(3), 344– 349. Vollema, M., & Ormel, J. (2000). The reliability of the Structured Interview for Schizotypy—­ Revised. Schizophrenia Bulletin, 26, 619–629. Von Bertalanffy, K. L. (1968). General system theory: Foundations, development, applications, New York: George Braziller. Vonnegut, M. (1975). The Eden express. New York: Bantam Books. Vul, E., Harris, C., Winkielman, P., & Pashler, H. (2009). Puzzingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspectives on Psychological Science, 4, 274–290. Waddington, J. L., Brown, A. S., Lane, A., Schaefer, C. A., Goetz, R. R., Bresnahan, M., et al. (2008). Congenital anomalies and early functional impairments in a prospective birth cohort: Risk of schizophrenia-­spectrum disorder in adulthood. British Journal of Psychiatry, 192(4), 264–267. Walker, E., Lewis, N., Loewy, R., & Palyo, S. (1999). Motor dysfunction and risk for schizophrenia. Development and Psychopathology, 11, 509–523. Waller, N. G. (2006). Carving nature at its joints: Paul Meehl’s development of taxometrics. Journal of Abnormal Psychology, 115(2), 210–215. Waller, N. G. (2008). Commingled samples: A neglected source of bias in reliability analysis. Applied Psychological Measurement, 32, 211–223. Waller, N. G., & Meehl, P. E. (1998). Multivariate taxometric methods: Distinguishing types from continua. Thousand Oaks, CA: Sage. Waller, N. G., & Meehl, P. E. (2002). Risky tests, verisimilitude, and path analysis. Psychological Methods, 7, 323–337. Waller, N. G., Yonce, L. J., Grove, W. M., Faust, D. A., & Lenzenweger, M. F. (2006). A Paul Meehl reader: Essays on the practice of scientific psychology. Mahwah, NJ: Erlbaum. Walsh, T., McClellan, J. M., McCarthy, S. E., Addington, A. M., Pierce, S. B., Cooper, G. M., et al. (2008). Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia. Science, 320(5875), 539–543. Wang, K., Fan, J., Dong, Y., Wang, C., Lee, T. M. C., & Posner, M. I. (2005). Selective impairment of attentional networks of orienting and executive control in schizophrenia. Schizophrenia Research, 78, 235–241. Wang, Y. H., Li, W. Q., Huang, Z., Shi, Y. Z., Wang, X. Y., Huang, J. S. et al. (2008). 5-HT2A receptor gene polymorphism and negative symptoms in first-episode (drugnaïve) Chinese Han nationality individuals with schizophrenia. Journal of Central South University of Technology, 33, 293–298. Watt, N. F., Anthony, E. J., Wynne, L. C., & Rolf, J. E. (1984). Children at risk for schizophrenia: A longitudinal perspective. New York: Cambridge. Weinberger, D. R., Berman, K. F., & Zec, R. F. (1986). Physiologic dysfunction of dorso-

References

433

lateral prefrontal cortex in schizophrenics: I. Regional cerebral blood flow evidence. Archives of General Psychiatry, 43, 114–124. Weisberg, D. S., Keil, F. C., Goodstein, J., Rawson, E., & Gray, J. R. (2008). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20(3), 470–477. Weiser, M., Reichenberg, A., Rabinowitz, J., Kaplan, Z., Mark, M., Bodner, E., et al. (2001). Association between nonpsychotic psychiatric diagnoses in adolescent males and subsequent onset of schizophrenia. Archives of General Psychiatry, 58(10), 959– 964. Weiser, M., van Os, J., Reichenberg, A., Rabinowitz, J., Nahon, D., Kravitz, E., et al. (2007). Social and cognitive functioning, urbanicity and risk for schizophrenia. British Journal of Psychiatry, 191(4), 320–324. Weller, E. B., Weller, R. A., & Vo, D. (2004). Defining subtypes of childhood bipolar illness. Journal of the American Academy of Child and Adolescent Psychiatry, 43(1), 4–5. Wender, P. H., Rosenthal, Kety, S. S., Schulsinger, F., & Welner, J. (1974). Crossfostering: A research strategy for clarifying the role of genetic and experiential factors in the etiology of schizophrenia. Archives of General Psychiatry, 30, 121–128. West, S. G. (2009). Alternatives to randomized experiments. Current Directions in Psychological Science, 18, 299–304. Westen, D. (1998). The scientific legacy of Sigmund Freud: Toward a psychodynamically informed psychological science. Psychological Bulletin, 124, 333–371. Westen, D., & Weinberger, J. (2005). In praise of clinical judgment: Meehl’s forgotten legacy. Journal of Clinical Psychology, 61(10), 1257–1276. Wiggins, J. S. (1973). Personality and prediction. Reading, MA: Addison Wesley. Wickens, T. D. (2002). Elementary signal detection theory. New York: Oxford. Widiger, T. (2001). What can be learned from taxometric analyses? Clinical Psychology: Science and Practice, 8, 528–533. Wikström, H., Roine, R. O., Salonen, O., Lund, K. B., Salli, E., Ilmoniemi, R. J., et al. (1999). Somatosensory evoked magnetic fields from the primary somatosensory cortex (SI) in acute stroke. Clinical Neurophysiology, 110, 916–923. Wilcox, M. A., Faraone, S. V., Su, J., van Eerdewegh, P., & Tsuang, M. T. (2002). Genome scan of three quantitative traits in schizophrenia pedigrees. Biological Psychiatry, 52(9), 847–854. Willett, J. B. (1988). Questions and answers in the measurement of change. In E. Rothkopf (Ed.), Review of research in education (1988–1989) (pp.  345–422). Washington, DC: American Educational Research Association. Wing, L. (1981). Asperger’s syndrome: A clinical account. Psychological Medicine, 11, 115– 129. Wittgenstein, L. (1984). Culture and value. Chicago, IL: University of Chicago Press. Wolff, S. (1991a). “Schizoid” personality in childhood and adult life: I. The vagaries of diagnostic labeling. British Journal of Psychiatry, 159(5), 615–620. Wolff, S. (1991b). “Schizoid” personality in childhood and adult life: III. The childhood picture. British Journal of Psychiatry, 159(5), 629–635. Wolff, S. (1995). Loners: The life path of unusual children. London: Routledge. Wolff, S., Townshend, R., McGuire, R. J., & Weeks, D. J. (1991). “Schizoid” personality in childhood and adult life: II. Adult adjustment and the continuity with schizotypal personality disorder. British Journal of Psychiatry, 159(5), 620–629. Wong, A. H. C., Gottesman, I. I., & Petronis, A. (2005). Phenotypic differences in geneti-

434 References cally identical organisms: The epigenetic perspective. Human Molecular Genetics, 14(1), r11–r18. Woodward, S. A., Lenzenweger, M. F., Kagan., J., Snidman, N., & Arcus, D. (2000). Taxonic structure of infant reactivity: Evidence from a taxometric perspective. Psychological Science, 11(4), 296–301. Wu, E. Q., Birnbaum, H. G., Shi, L., Ball, D. E., Kessler, R. C., Moulis, M., et al. (2005). The economic burden of schizophrenia in the United States in 2002. Journal of Clinical Psychiatry, 66(9), 1122–1129. Wuthrich, V. M., & Bates, T. C. (2006). Confirmatory factor analysis of the three-­factor structure of the Schizotypal Personality Questionnaire and Chapman Schizotypy Scales. Journal of Personality Assessment, 87, 292–304. Yasuda, Y., Watanabe, T., & Ogura, A. (2000). Parietal cheiro-oral syndrome. Internal Medicine, 39(12), 1105–1107. Yoo, Y. J., Bull, S. B., Paterson, A. D., Waggot, D., The Diabetes Control and Complications Trial / Epidemiology of Diabetes Interventions and Complications Research Group, & Sun, L, (2010). Were genome-wide association studies a waste of time? Exploiting candidate regions within genome-wide association studies. Genetic Epidemiology, 34, 107–118. Young, E., & Mason, O. (2007). Psychosis-­proneness and socially relevant reasoning. Psychiatry Research, 150(2), 123–129. Zachar, P., & Kendler, K. S. (2007). Psychiatric disorders: A conceptual taxonomy. American Journal of Psychiatry, 164(4), 557–565. Zhou, S-Y., Suzuki, M., Takahashi, T., Hagino, H., Kawasaki, Y., Matsui, M., et al. (2007). Parietal lobe volume deficits in schizophrenia spectrum disorders. Schizophrenia Research, 89(1–3), 35–48. Zimmerman, M., & Coryell, W. (1990). Diagnosing personality disorders in the community: A comparison of self-­report and interview measures. Archives of General Psychiatry, 47, 527–531. Zimmerman, M., Rothschild, L., & Chelminski, I. (2005). The prevalence of DSM-IV personality disorders in psychiatric outpatients. American Journal of Psychiatry, 162, 1911–1918. Zubin, J., & Spring, B. (1977). Vulnerability: A new view of schizophrenia. Journal of Abnormal Psychology, 86(2), 103–126.

Index

Page numbers followed by an f or a t indicate figures or tables. Abstraction ability, 364–365 Adoption studies, 210–211 Affect expression, 10–11 Alogia, 261 Alternative phenotypic form, 342 Analysis of covariance (ANCOVA), 67–68 Analysis of variance (ANOVA) framework contrast analysis and, 59–61, 60f simplicity and, 268–269 stability of schizotypic features and, 324–326 statistical control and, 67–68 Anhedonia, 355–356 Animal studies, 55n Antisaccade task eye-tracking dysfunction, 260 overview, 364–365 Anxiety, 26–27 Assessment best approach to, 119–120 heterogeneity and, 132–140, 136f list of measures, 390 methodological issues to keep in mind in, 123–127 motor functions and, 292–296, 294f, 295t proprioception and, 286–289, 288t reliability and validity and, 29–30 tools for, 128–132 Atheoretical phenomenological observation mode, 141 Attentional impairments. see also Sustained attention data collection and, 48 development of schizophrenia and, 311



overview, 364–365 sustained attention, 237–245, 242f Attenuation paradox example of, 31–35 overview, 30–31 Behavior development of schizophrenia and, 311 disordered thinking and, 261 types of data collected and, 44–45 Bias Berkson’s bias, 97–99 discontinuity and, 331–333 latent mixtures and, 35–42, 36f, 37f, 38f, 41f reliability and, 35–38 sensitivity and, 280–282 Bimodal distribution discontinuity and, 334 overview, 36, 37f Binomial effect size display (BESD), 65–67, 66t Biological factors, 11–12, 308–310. see also Causes of schizophrenia Biological-relatives approach to defining the schizotype heterogeneity and, 138 overview, 121 Biomarker, 192–198, 193f Bipolar disorder, 213 Bleuler, Eugen, 177–178, 178f, 179 The blind exteroception and, 270n overview, 78–79, 240–241 Body image, disturbed, 271–272

435

436

Index

Borderline, 209n Borderline personality disorder (BPD) heterogeneity and, 139–140 schizophrenia liability and, 209n Case examples, 5–7 Causal attributions, 10 Causal modeling, 56n, 144 Causes of schizophrenia. see also Biological factors; Developmental factors; Environmental factors; Genetic factors; Neurobiological factors overview, 14–17 schizotypy model approach and, 17–18, 154–157, 156f Chapman Psychosis Proneness Scales, 130–131 Chapmans’ 10-year follow-up study, 314–319 Chapmans’ Perceptual Aberration Scale (PAS). see Perceptual Aberration Scale (PAS) Checklist for Schizotypic Signs, 128–129 Children in the Community Study (CIC), 323–324, 327–328 Chromosomal regions, 216–217 Claridge’s model of schizotypy, 173–175 Classic bimodality, 36, 37f Classification systems. see also Diagnostic and Statistical Manual of Mental Disorders expanded phenotype and, 101–103 heterogeneity and, 133–134 questioning and looking beyond, 103–106 schizotypy model approach and, 165 Clinical approach to defining the schizotype development of schizophrenia and, 301–308 heterogeneity and, 138 Clinical features of the schizotype, 10–11 Clinical heterogeneity, 133–134 Clinical interviews defining and conceptualizing the schizotype and, 119–120 tools for, 128–130 Clinical observation case example of, 25 compared to self-report assessments, 126– 127 importance of, 24–25 motor functions and, 290–291 overview, 236–237 Clinical outcome. see Outcomes of schizotypy Clinical psychology, 29–30 Clumsiness. see Motor dysfunction Cluster analysis, 333–334 Cognitive distortions, 208 Cognitive slippage disordered thinking and, 260, 261 sustained attention and, 239

Collaborative Longitudinal Personality Disorders Study (CLPS), 323–324, 328 Collinearity, 86–87 Communication skills, 262. see also Language use Compensation environmental factors and, 376 schizotypy model approach and, 159–160 Complex diseases assumption that schizophrenia is a single unit of analysis and, 184–186 biomarker, 192–198, 193f endophenotype, 187–192, 189t, 190f “genetalk” and, 183–184 intermediate phenotype, 192–198, 193f nature of, 181–183 overview, 180–181 Complex segregation analysis, 335 Comprehensive Assessment of Symptoms and History (CASH), 48 Computerized Assessment of Sequential Test (CAST) system, 265–266 Concentration impairments data collection and, 48 sustained attention, 237–245, 242f Concepts related to schizotypic psychopathology, 8–10 Conceptual models, 141–142 Conceptual tools, 23–24 Confidence intervals, 63–64 Constant stimuli method, 278–280, 280f Construct structure, 171–173 Construct validity, 27–29. see also Validity Continuity, 341 Continuous Performance Test (CPT) overview, 48, 224–225 sustained attention and, 240–243, 242f Continuous Performance Test-Identical Pairs Version (CPT-IP) sustained attention and, 240–243, 242f working memory and, 253 Continuum of compensation, 376 Contrast analysis, 58, 59–61, 60f Control tasks, 112 Copy number variations, 227 Correlation coefficient, 81–82, 82f Correlational nature of research, 49–56, 54f Counting in psychopathology research compared to rating types of data collection, 48–49 future progress and, 374 overview, 42–43 Covariance adjusted means, 67–68 Criterion validity, 29–30 Cronbach’s coefficient alpha, 35



Index

“Damn strange coincidence” view, 364–367 Danish Adoption Study environmental factors and, 375–378 latent liability constructs and, 340–341 schizophrenia liability and, 210–211 Data analysis dimensional latent structure of schizotypy and, 172 expanded phenotype, 101–103 levels of analysis, 93–97 missing data, 75–76 null hypothesis testing (NHT), 57–63, 60f post-hoc analysis of data, 68–75 psychopathology and, 100–101 statistical versus scientific significance and, 64–67, 66t staying close to your data and, 99–100 Data collection rating type of, 46–49 scaling and, 45–46 staying close to your data and, 99–100 types of data collected, 43–45 Defensiveness, 127 Definitions related to schizotypic psychopathology defining and conceptualizing the schizotype, 118–121 operational definitions, 145–146 overview, 8–10 Delusions connection of schizotypy to schizophrenia and, 11 overview, 8–9 Depression, 26–27 Derailment, 261 Descriptive psychopathology, 29 Detection, early, 278–280 Developmental factors. see also Causes of schizophrenia heterogeneity and, 135–137, 136f overview, 16–17 schizophrenia and, 300–320 schizotypy model approach and, 155, 162–163 Developmental model, 164–169, 166f Diagnosis, 202 Diagnostic and Statistical Manual of Mental Disorders defining and conceptualizing the schizotype and, 120–121 development of schizophrenia and, 301–302 epidemiology of the schizotypic psychopathology and, 122–123 example of the attenuation paradox and, 31–35 expanded phenotype and, 101–103

437

operational definitions and, 145–146 overview, 8 questioning and looking beyond, 103–106 reliability and validity and, 30 schizophrenia liability and, 206–207 schizotypy model approach and, 160, 165–166 Diagnostic criteria defining and conceptualizing the schizotype and, 120–121 heterogeneity and, 89–93, 92f questioning and looking beyond, 103–106 schizophrenia liability and, 206–207 schizotypy model approach and, 160, 165–166 Diagnostic interview defining and conceptualizing the schizotype and, 119–120 tools for, 128–130 Diagnostic systems heterogeneity and, 89–93, 92f reliability and validity and, 30 Diathesis-stressor model developmental model and, 166f overview, 151–152 Dimensional approach discontinuity and, 332–333 overview, 171–175 Dimensional latent structure of schizotypy, 171–175 Discontinuity dimensional latent structure of schizotypy and, 173 how to find, 333–335 overview, 331–333 Discovery, context of, 70–73 Disordered thinking. see Thought disorder Disorganized symptoms, 134 Distribution of scores, 35–38, 36f, 37f, 38f DNA, 181–182. see also Genetic factors Dopaminergic system, 377–378 DSM-III, 30, 31–35. see also Diagnostic and Statistical Manual of Mental Disorders Early intervention efforts development of schizophrenia and, 305–307 overview, 305n, 378–381 Eccentric personalities, 206 Economic impact of schizophrenia, 13–14 Edinburgh High-Risk Study (EHRS), 311–312 Effect size correlational versus the experimental nature of research, 50–51 null hypothesis testing and, 63–64 statistical versus scientific significance and, 64–67, 66t

438

Index

Emergence, 94n Empathy, 119–120 Empirical connections schizophrenia liability and, 204–227, 212t, 213t somatosensory system and, 273–275 Endophenotype. see also Genetic factors biomarker, 192–198, 193f disordered thinking, 260–266 executive functioning and, 245–254, 246f eye-tracking dysfunction, 255–260, 256f future progress and, 383–384 intermediate phenotype, 192–198, 193f intervention and, 379–380 latent structure and, 351 overview, 187–192, 189t, 190f sustained attention and, 237–245, 242f working memory and, 245–254, 246f Environmental factors. see also Causes of schizophrenia overview, 13, 375–378 schizophrenia liability and, 209–210 schizotypy model approach and, 168 Epidemiology of the schizotypic psychopathology, 122–123 Epigenetics epigenetic control, 227 future progress and, 382–383 overview, 227, 229–235, 229f, 234t Etiological factors, 95–97 Etiological heterogeneity, 90, 133, 135 Executive functioning, 245–255, 246f, 254f Expanded phenotype, 101–103 Expectation-maximization (EM) algorithm, 224 Experimental psychopathologist’s toolbox. see also Experimental psychopathology the blind, 78–79 clinical observation, 24–25 collinearity and, 86–87 correlational versus the experimental nature of research, 49–55, 54f heterogeneity and, 89–93, 92f latent mixtures and, 35–42, 36f, 37f, 38f, 41f levels of analysis, 93–97 linearity and, 79–81 null hypothesis testing and, 57–63, 60f overview, 23–24 quantitative thinking, 88–89 reliability and validity and, 26–31 suppressor variable, 82–86, 84f Experimental psychopathology. see also Experimental psychopathologist’s toolbox exteroception and, 280–282 marker versus indicator and, 197–198

outcomes of schizotypy and, 299–300 overview, 18–19, 363–364 simplicity and, 268–270 Experimental research, 49–55, 54f Expressed emotion (EE), 33–35 Exteroception, 270–285, 275f, 280f Extreme-groups approach design, 313–314 Eye-tracking dysfunction latent structure and, 350–352 overview, 255–260, 256f, 364–365 unexpressed liability and, 342 Factor analysis, 334 Family approach to defining the schizotype development of schizophrenia and, 308–310 epidemiology of the schizotypic psychopathology and, 123 heterogeneity and, 138 overview, 121 Finite mixture modeling, 226–227 Follow-up studies, 314–320 Freud, Sigmund, 178–179 Functional neuroimaging methods, 44–45. see also Neuroimaging Gene expression, 227. see also Genetic factors Gene-environment interaction, 182 “Genetalk”, 183–184 Genetic factors. see also Causes of schizophrenia biomarker, 192–198, 193f complex disease notion and, 180–198, 189t, 190f, 193f connection of schizotypy to schizophrenia and, 11–12 defining and conceptualizing the schizotype and, 121 development of schizophrenia and, 308–310 developmental model and, 166f endophenotypes and, 187–192, 189t, 190f epidemiology of the schizotypic psychopathology and, 123 epigenetics and, 229–235, 229f, 234t eye-tracking dysfunction, 259 future progress and, 374, 382–383 heterogeneity versus homogeneity and, 233–235, 234t history of research in, 177–180, 178f intermediate phenotype, 192–198, 193f liability and, 146–147 overview, 13, 14–17, 106–109 risk and, 149–150, 150f schizophrenia liability and, 207–209 schizotypy model approach and, 154–157, 156f, 160–162, 163–164, 168 structural variation and, 230–235, 234t



Index

sustained attention and, 238–239 tapestry analogy of, 198–201 Genetic heterogeneity, 182 Genetic marker, 197–198. see also Biomarker Genetic regulation, 227 Genome-wide approaches, 217–221 Genomic imprinting, 229 Genomic rearrangements, 230–231 Group-difference paradigm correlational nature of research and, 55 psychopathology and, 101 Habit strength, 27 Hallucinations case example of, 25 connection of schizotypy to schizophrenia and, 11 overview, 8–9 “Healthy psychosis”, 170–171 Hedonic capacity, 158–159 Heritability, 207–209. see also Genetic factors Heterogeneity assessment and, 132–140, 136f assumption that schizophrenia is a single unit of analysis and, 184–186 future progress and, 373–374 versus homogeneity, 233–235, 234t overview, 89–93, 92f schizophrenia liability and, 222–225 Heterogeneity in growth (or change), 133, 135–137, 136f History of the definition of schizophrenia, 9–10 Homogeneity, 233–235, 234t Hypohedonia latent constructs and, 352–356 overview, 158–159 Hypokrisia disordered thinking and, 260 overview, 158–159 Hypothetical constructs, 27–29, 175–176 Identifying the schizotype. see Recognizing the schizotype IGC analysis, 326–327 Improper linear models, 79–81 Individual difference correlational nature of research and, 55 future progress and, 384–386 outcomes of schizotypy and, 299 overview, 52n self-report assessments and, 126 Inference, 371 Informant (observer) rating data, 43–45 Innovation, 382–386 Insight, 127

439

Intelligence genetic factors and, 199–201 reliability and validity and, 26–27 Intermediate phenotype, 192–198, 193f International Classification of Diseases (ICD) development of schizophrenia and, 302 schizotypy model approach and, 160 International Personality Disorder Examination (IPDE), 119–120 International Personality Disorder Examination-Screen (IPDE-S), 345–346 Interpersonal aversiveness, 26–27 Interval scaling, 45–46 Intervening variable, 27–28 Interventions, 378–381 Interview method of assessment defining and conceptualizing the schizotype and, 119–120 tools for, 128–130 Irish Study of High-Density Schizophrenia Families (ISH-DSF), 221–222 Item-response theory (IRT), 339n–340n Jung, Carl G., 178–179 Justification, context of, 70–73 Kraepelin, Emil, 177–178, 178f, 179 Kuder-Richardson-20 value, 35 Laboratory approach to defining the schizotype development of schizophrenia and, 312–319 heterogeneity and, 138 latent liability constructs and, 340–348 neuroimaging and, 367–373 overview, 120–121 taxometrics and, 335–340, 338f Laboratory task performance heterogeneity, 90–91 Language use clinical features of the schizotype and, 10 disordered thinking and, 261n, 262 Latent class analysis, 335 Latent constructs eye-tracking dysfunction, 259 hypohedonia and, 352–356 overview, 146–151, 148f, 150f schizophrenia liability and, 204–227, 212t, 213t stability of schizotypic features and, 320–321 taxometrics and, 350–352 Latent liability constructs, 340–348 Latent mixtures reliability and, 35–38, 36f, 37f, 38f validity and, 38–42, 41f Latent structure, 171–173

440

Index

Latent-trait model of schizophrenia, 349–350 Lenzenweger 18-year follow-up study of schizotypy, 319–320 Levels of analysis overview, 93–97, 164–169, 166f phenomenology and, 202 schizophrenia liability and, 204–227, 212t, 213t Liability development of schizophrenia and, 300–320 eye-tracking dysfunction, 259 intervention and, 378–386 latent liability constructs, 340–348 models of psychopathology and, 146–151, 148f, 150f outcomes of schizotypy and, 299–300 overview, 199–201 stability of schizotypic features and, 320–328, 325f sustained attention and, 238–239 Life-record data, 43–45 Liger example, 228–229, 229f Line Drawing Task, 292–296, 294f, 295t Linearity, 79–81 Linkage analysis, 181–182 Longitudinal Study of Personality Disorders (LSPD), 323–327, 325f Magical abilities, 10. see also Causal attributions Magical Ideation Scale (MIS) latent liability constructs and, 347 overview, 130–131 Maher Line Drawing Task, 292–296, 294f, 295t Manual for Use with Checklist of Schizotypic Signs (Meehl, 1964), 387–389 Marker, 197–198. see also Biomarker Maximum-covariance analysis (MAXCOV) guidelines for research and, 358 latent liability constructs and, 344–347, 352 overview, 336–337, 336f, 338f Measurement list of measures, 390 overview, 42–43 Meehl’s Checklist for Schizotypic Signs, 128–129 Meehl’s model of schizotypy. see also Schizotypy model approach alternative views to, 169–175 future progress and, 374 misunderstandings of, 160–163, 161f overview, 151–164, 156f, 161f revisionist efforts, 164–169, 166f taxometrics and, 335–340, 336f, 338f Memory, 245–254, 246f, 254f, 364–365 Mendelian genetics, 181–182

Methodological approach, 262–264 Methods discontinuity and, 331–333 future progress and, 373–374 Minnesota Multiphasic Personality Inventory (MMPI), 132, 364–365 Missing data, 75–76 Mixed designs in research, 51–52 Mixed model overview, 157 quasi-dimensional view of Meehl’s model and, 174 schizotypy model approach and, 164 Mixture-based methods, 226–227 Models, 142–151, 148f, 150f, 175–176, 268–270. see also specific models Molecular considerations. see also Genetic factors schizophrenia liability and, 216–219 structural variation and, 230–235, 234t Monetary costs of schizophrenia, 13–14 Motor dysfunction, 267, 290–297, 294f, 295t, 364–365 Multidimensional Personality Questionnaire (MPQ), 54f Multifactorial polygenic model, 199–201 Multiple correlation, 80 Multivariate regression, 86–87 Mutagenic model, 182, 199–201 Negative symptoms data collection and, 48 heterogeneity and, 134 phenomenology and, 202–203 Neurobiological factors. see also Causes of schizophrenia endophenotypes and, 187–192, 189t, 190f executive functioning and, 245 overview, 13 parietal lobe, 289–290 Neurocognitive tasks eye-tracking dysfunction, 259–260 types of data collected and, 44–45 Neuroimaging executive functioning and, 245 functional neuroimaging methods, 44–45 future progress and, 382 levels of analysis and, 95 overview, 367–373 New York High-Risk Project (NYHRP) development of schizophrenia and, 310–311 sustained attention and, 243 Nominal scaling, 45–46 Nomological net, 29 Nomothetic research, 52n



Index

Nonpsychotic schizotype, 9–10 North American Prodrome Longitudinal Study (NAPLS), 306 Null hypothesis testing (NHT), 57–63, 60f Observable criterion, 28–29. see also Clinical observation Observation, clinical. see Clinical observation Office of Strategic Services (OSS), 28–29 Oligogenic model of inheritance, 182, 199–201 One-gene-one-disorder (OGOD) model of genetic influence, 199–201 One-tailed tests, 58 Operational definitions, 145–146 Ordinal scaling, 45–46 Outcomes of schizotypy development of schizophrenia, 300–320 overview, 298–300, 329 stability of schizotypic features and, 320–328, 325f Paradoxical properties, 30–31 Paranoia, 208 Paranoid personality disorder (PPD) epidemiology of the schizotypic psychopathology and, 122–123 overview, 120–121 stability of schizotypic features and, 323–327 Parietal connection, 272–273 Parietal lobe, 289–290 Path analysis, 56 Penetrance, 182 Perception clinical features of the schizotype and, 10 exteroception and, 271–272 Perceptual Aberration Scale and/or Magical Ideation Scales (Per-Mag), 314, 315, 316–318 Perceptual Aberration Scale (PAS) data analysis and, 73 development of schizophrenia research and, 319–320 latent liability constructs and, 343–344 Maher Line Drawing Task and, 295–297, 295t overview, 130–131 schizophrenia liability and, 212–213, 223– 224 Performance heterogeneity, 133, 134–135 Personality schizophrenia liability and, 205–206 schizotypy model approach and, 161–162, 170–171 Personalty Pathology Five (PSY-5), 132 Phenomenological heterogeneity, 90

441

Phenomenology. see also Genetic factors clinical observation and, 24–25 development of schizophrenia and, 306–307 future progress and, 374 genetic factors and, 201–204 Phenotype, expanded, 101–103 Pleiotropy, 182, 200n Point predictions, 63–64 Polygenic model of inheritance, 182, 199–201 Polygenic potentiators, 157, 174 Polymorphisms, 216–217 Polythetic diagnostic criteria set, 89–90 Positive symptoms. see also Symptoms example of the attenuation paradox and, 31–35 overview, 31–32 phenomenology and, 202–203 Post-hoc analysis of data, 68–75, 75n Poverty of content of thought, 261 Poverty of thought, 261 Practical tools, 23–24 Praecox pursuit, 257 Precision, null hypothesis and, 58 Predictions linearity and, 79–81 overview, 80n psychopathology and, 101 suppressor variable, 82–86, 84f Premorbid social functioning, 134 Prevalence of schizotypic psychopathology, 121–123 Prevention development of schizophrenia and, 305–307 overview, 378–381 Primary cognitive slippage, 158 Primary hypohedonia, 352–353. see also Hypohedonia Primary prevention, 307n Primary processes, 170–171 Primate research, 249–254, 254f Prodromal research paradigm, 303–308 Productive symptoms. see Positive symptoms Projections, 378–386 Proprioception, 272–273, 285–290, 288t Psychodynamic models, 141–142 Psychological constructs discontinuity and, 331–333 overview, 330–331 Psychological tests, 42–43 Psychometric approach to defining the schizotype heterogeneity and, 138 latent structure and, 350–352 taxometrics and, 358 Psychophysiological recording methods, 44–45 Psychosis, absence of, 8–9

442

Index

Qualitative meaning connection of schizotypy to schizophrenia and, 11–12 discontinuity and, 334 Quantitative meaning connection of schizotypy to schizophrenia and, 11–12 overview, 88–89 Quasi-dimensional view of Meehl’s model, 173–175 Questionnaires overview, 42–43 types of data collected and, 43–44 Rado, Sandor, 153–154 Rating type of data collection compared to counting, 48–49 overview, 42–43, 46–49 Ratio scaling, 45–46 Reality distortion heterogeneity and, 134 personality and, 170–171 Recognizing the schizotype defining and conceptualizing the schizotype and, 118–121 methodological issues to keep in mind in, 123–127 overview, 117–118 Referential Thinking Scale (REF) latent liability constructs and, 347 overview, 132 Regression coefficients, 82–86, 84f Regresssion, degree of, 170–171 Relations, social clinical features of the schizotype and, 10 overview, 8–9 Reliability example of the attenuation paradox and, 31–35 latent mixtures and, 35–38, 36f, 37f, 38f overview, 26–31 stability of schizotypic features and, 321–323 Research. see also Statistics basic science paradigms for use in, 111 clinical observation, 24–25 collinearity and, 86–87 constructs and, 42–43 control tasks and, 112 correlational versus the experimental nature of research, 49–55, 54f example of the attenuation paradox and, 31–35 genetic factors and, 106–109 large-scale projects, 109–110 latent mixtures and, 35–38, 35–42, 36f, 37f, 38f, 41f

linearity and, 79–81 prior to the use of electronic formats, 110–111 psychopathology and, 100–101 rating type of data collection, 46–49 reliability and validity, 26–31 scaling and, 42–43, 45–46 subjects of, 97–99 taxometrics and, 356, 358 time and, 76–77 types of data collected, 43–45 writing up results of, 112–113 Resilience, 148–149, 148f Revised Social Anhedonia Scale (RSAS), 353–355 Risk, 146–151, 148f, 150f Roscommon Family Study (RFS), 206 Rubin causal model, 56 Rust Inventory of Schizotypal Cognitions (RISC), 132 Sampling methods development of schizophrenia research and, 309n heterogeneity and, 137–140 latent liability constructs and, 348 Scaling, 42–43, 45–46 Schedule for Schizotypal Personalities (SSP), 129 Schizoid withdrawal, 353 Schizophrenia development of, 300–320 environmental factors and, 375–378 future progress and, 373–374 schizotypy model approach and, 162–163 Schizophrenia liability. see also Liability expressions of, 204–227, 212t, 213t “healthy psychosis” and, 171 Schizophrenia Proneness Scale, 132 Schizophrenism Scale, 132 “Schizotaxia, Schizotypy, Schizophrenia” (Meehl, 1962), 154–157, 156f Schizotypal Ambivalence Scale (SAS), 132 Schizotypal cognition, 208 Schizotypal personality disorder (SPD) development of schizophrenia and, 301–303 epidemiology of the schizotypic psychopathology and, 122–123 overview, 120–121 stability of schizotypic features and, 321–327, 325f Schizotypal Personality Questionnaire (SPQ), 131–132 Schizotypal Personality Scale (STA), 132 Schizotypic psychopathology overview



Index

assumption that schizophrenia is a single unit of analysis and, 184–186 cases to illustrated, 5–7 clinical features, 10–11 connection of schizotypy to schizophrenia, 11–12 defining and conceptualizing the schizotype, 118–121 environmental factors and, 375–378 future progress and, 373–374 heterogeneity and, 132–140, 136f, 233–235 heterogeneity versus homogeneity and, 234t latent liability constructs, 340–348 prevalence of schizotypic psychopathology, 121–123 recognizing the schizotype, 117–118 research and, 364–367 schizophrenia liability and, 204–227, 212t, 213t schizotypy model approach and, 159–160 stability of schizotypic features and, 320–328, 325f tapestry analogy of, 198–201 terminology and concepts, 8–10 Schizotypy model approach. see also Meehl’s model of schizotypy alternative views to, 169–175 environmental factors and, 375–378 misunderstandings of, 160–163, 161f overview, 17–18, 154–157, 156f, 364–367 revisionist efforts, 164–169, 166f stressors and, 377–378 Scientific significance, 64–67, 66t Secondary hypohedonia. see also Hypohedonia Secondary prevention, 307, 307n Self-rating data, 43–45 Self-report inventories issues related to, 125–127 overview, 42–43 tools for, 130–132 Sensitivity, 280–282 Severity connection of schizotypy to schizophrenia and, 11–12 personality and, 170–171 Short-term memory, 250. see also Memory Shotgun approach, 219n Significance, 64–67, 66t Simplicity, 268–270 Single major locus (SML) model future progress and, 374 overview, 199–201 Skewness, 348 Smooth pursuit eye movement, 364–365. see also Eye-tracking dysfunction

443

Social Fear Scale, 132 Social relations clinical features of the schizotype and, 10 overview, 8–9 Socialization models, 142n Socialization science, 231n Societal impact of schizophrenia, 12–14 Somatosensation exteroception, 270–285, 275f, 280f overview, 267, 364–365 proprioception, 285–290, 288t Spatial working memory, 250, 253–254, 254f. see also Working memory Spatial-kinesthetic-vestibular (SKV) system, 272 Speech clinical features of the schizotype and, 10 disordered thinking and, 261n, 262 State-trait issue, 123–125 Statistics. see also Research collinearity and, 86–87 correlation coefficient, 81–82, 82f linearity and, 79–81 missing data and, 75–76 null hypothesis testing and, 57–63, 60f post-hoc analysis of data, 68–75 proprioception and, 287–289, 288t significance and, 64–67, 66t statistical control, 67–68 statistical model, 143–144 suppressor variable, 82–86, 84f time and, 76–77 Stressors, 377–378. see also Environmental factors Structural equation modeling (SEM), 56n, 144 Structural variation, 230–235, 234t Structured Interview for Schizotypy (SIS), 129–130 Subject sampling methods, 137–140 Suppressor variable, 82–86, 84f Susceptibility, 146–151, 148f, 150f Suspiciousness clinical features of the schizotype and, 10–11 schizophrenia liability and, 208 Sustained attention. see also Attentional impairments latent structure and, 350–352 overview, 237–245, 242f, 364–365 Symptom Schedule for the Diagnosis of Borderline Schizophrenia (SSDBS), 129 Symptoms complex disease notion and, 180–181 example of the attenuation paradox and, 31–35 heterogeneity and, 134

444

Index

Symptoms (cont.) Manual for Use with Checklist of Schizotypic Signs (Meehl, 1964), 387–389 phenomenology and, 202–203 recognizing the schizotype, 117–118 stability of schizotypic features and, 320–328, 325f Synaptic slippage, 239 Tangentiality, 261 Task-based data, 43–45 Taxometrics guidelines for research and, 356, 358 latent liability constructs and, 346–348 latent structure and, 350–352 Meehl’s model of schizotypy and, 335–340, 336f, 338f overview, 349–350 Revised Social Anhedonia Scale (RSAS) and, 354–355 Taxa guidelines for research and, 356, 358 importance of, 337, 339–340 overview, 332 Terminology overview, 8–10 Tertiary prevention, 307n Test theory, 30–31 Test-retest studies, 321–323 Theory compared to models, 142–145 future progress and, 373–374 Theory of signal detection (TSD), 278n Thought, Language, and Communication Scales (TLC), 262 Thought disorder overview, 8–9, 260–266, 364–365 reliability and validity and, 26–27

Thought disorder index (TDI) approach, 262–264 Three-factor model, 118–121 Threshold effect, 174, 232n Touch sensitivity. see Exteroception Transitive property of equality, 354n Twin studies, 207–209. see also Genetic factors Two-point discrimination, 280–282 Two-point stimuli, 278–280, 280f Two-tailed tests, 58 Unexpressed liability, 342 Unimodal distribution discontinuity and, 334 latent liability constructs and, 343 overview, 36–37, 36f, 38f Validity example of the attenuation paradox and, 31–35 latent mixtures and, 38–42, 41f overview, 26–31 Variable expressivity discontinuity and, 334–335 overview, 182 Verisimilitude, 365n Vigilance decrement, 244 Vulnerability, 146–151, 148f, 150f Weight sensitivity. see Proprioception Wisconsin Card Sorting Test (WCST) executive functioning and, 246–249, 246f heterogeneity and, 92 schizophrenia liability and, 224 simplicity and, 268–269 working memory and, 253 Working memory, 245–254, 246f, 254f, 364–365