Vulnerability to Psychopathology: Risk across the Lifespan

VULNERABILITY TO PSYCHOPATHOLOGY

Vulnerability to Psychopathology Risk across the Lifespan Second Edition

Edited by Rick E. Ingram Joseph M. Price

THE GUILFORD PRESS New York   London

© 2010 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. 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 The authors have checked with sources believed to be reliable in their efforts to provide information that is complete and generally in accord with the standards of practice that are accepted at the time of publication. However, in view of the possibility of human error or changes in medical sciences, neither the authors, nor the editor and publisher, nor any other party who has been involved in the preparation or publication of this work warrants that the information contained herein is in every respect accurate or complete, and they are not responsible for any errors or omissions or the results obtained from the use of such information. Readers are encouraged to confirm the information contained in this book with other sources.

Library of Congress Cataloging-in-Publication Data Vulnerability to psychopathology risk across the lifespan / edited by Rick E. Ingram, Joseph M. Price. — 2nd ed. p. cm. Includes bibliographical references and index. ISBN 978-1-60623-347-4 (hardcover : alk. paper) 1.  Schizophrenia—Risk factors.  2.  Affective disorders—Risk factors.  3.  Child psychopathology—Longitudinal studies.  4.  Schizophrenia—Prevention— Longitudinal studies.  I.  Ingram, Rick E.  II.  Price, Joseph M. (Joseph Michael) RC455.4.R56V85 2010 362.2′6—dc22 2009028935

About the Editors

Rick E. Ingram, PhD, is Professor of Psychology at the University of Kansas. His research focuses on cognitive functioning in emotional disorders, with a particular emphasis on the cognitive features of individuals at risk for depression. This research examines the cognitive mechanisms of risk in adults, but also assesses processes linked to the possible developmental origins of cognitive risk. Dr. Ingram is the editor of the International Encyclopedia of Depression; coauthor (with Jeanne Miranda and Zindel V. Segal) of Cognitive Vulnerability to Depression; editor of Cognitive Therapy and Research; and associate editor of the Journal of Consulting and Clinical Psychology. He is a recipient of the New Researcher Award from the Association for Advancement of Behavior Therapy, the Distinguished Scientific Award for Early Career Contributions to Psychology from the American Psychological Association, as well as the John C. Wright Graduate Mentor Award from the University of Kansas. He was also elected as a Division 12 Fellow of the American Psychological Association. Joseph M. Price, PhD, is Professor in the Department of Psychology at San Diego State University and a member of the Joint Doctoral Training Program in Clinical Psychology at San Diego State University and the University of California, San Diego. He is also a Research Scientist at the Child and Adolescent Services Research Center at Rady Children’s Hospital in San Diego. Dr. Price’s recent research and publications focus on the developmental sequelae of the experiences associated with early maltreatment and the implementation of evidence-based interventions for child behavior problems in the child welfare systems of care.



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Contributors

Iris Beltran, MA, Department of Psychology, Arizona State University, Tempe, Arizona Steven L. Bistricky, MA, Department of Psychology, University of Kansas, Lawrence, Kansas Patricia A. Brennan, PhD, Department of Psychology, Emory University, Atlanta, Georgia Kelly D. Brownell, PhD, Rudd Center for Food Policy and Obesity, Yale University, New Haven, Connecticut Laurie Chassin, PhD, Department of Psychology, Arizona State University, Tempe, Arizona R. Lorraine Collins, PhD, School of Public Health and Health Professions, University at Buffalo, State University of New York, Buffalo, New York Michael T. Compton, MD, MPH, Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia Nicki R. Crick, PhD, Institute of Child Development, University of Minnesota, Minneapolis, Minnesota Kamryn T. Eddy, PhD, Harris Center, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts Matthew W. Gallagher, MA, Department of Psychology, University of Kansas, Lawrence, Kansas Judy Garber, PhD, Department of Psychology and Human Development, Vanderbilt University, Nashville, Tennessee Tasha C. Geiger, PhD, Bluegrass Regional Mental Health– Mental Retardation Board, Lexington, Kentucky Adam Gonzalez, BA, Department of Psychology, University of Vermont, Burlington, Vermont

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Contributors

Moira Haller, MA, Department of Psychology, Arizona State University, Tempe, Arizona Constance L. Hammen, PhD, Department of Psychology, University of California, Los Angeles, California Ingunn Hansdottir, PhD, SAA—National Center of Addiction Medicine, Reykjavik, Iceland Philip D. Harvey, PhD, Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia Julianna Hogan, MA, Department of Psychology, University of Vermont, Burlington, Vermont Rick E. Ingram, PhD, Department of Psychology, University of Kansas, Lawrence, Kansas Todd B. Kashdan, PhD, Department of Psychology, George Mason University, Fairfax, Virginia Pamela K. Keel, PhD, Department of Psychology, Florida State University, Tallahassee, Florida Matthew Lee, MA, Department of Psychology, Arizona State University, Tempe, Arizona Gloria R. Leon, PhD, Department of Psychology, University of Minnesota, Minneapolis, Minnesota Vanessa L. Malcarne, PhD, Department of Psychology, San Diego State University, San Diego, California Richard J. McNally, PhD, Department of Psychology, Harvard University, Cambridge, Massachusetts Erin L. Merz, MA, San Diego State University and University of California, San Diego, San Diego, California Sadia Najmi, PhD, Center for Understanding and Treating Anxiety, San Diego State University, San Diego, California Joseph M. Price, PhD, Department of Psychology, San Diego State University, San Diego, California Hannah E. Reese, MA, Department of Psychology, Harvard University, Cambridge, Massachusetts Jennifer Ritter, MS, Child Guidance Clinic, Winnipeg School Division, Winnipeg, Manitoba, Canada Marlene B. Schwartz, PhD, Rudd Center for Food Policy and Obesity, Yale University, New Haven, Connecticut Mariela C. Shirley, PhD, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland



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Jennifer J. Thomas, PhD, Massachusetts General Hospital/McLean Hospital, Eating Disorders Clinical/Research Program, Harvard Medical School, Boston, Massachusetts Ian Villalta, MA, Department of Psychology, Arizona State University, Tempe, Arizona Elaine F. Walker, PhD, Department of Psychology, Emory University, Atlanta, Georgia Michael J. Zvolensky, PhD, Department of Psychology, University of Vermont, Burlington, Vermont Jennifer Zwolinski, PhD, Department of Psychology, University of San Diego, San Diego, California

Preface

Since the publication of the first edition of this volume, theory and research related to identifying and understanding vulnerability processes in the development of psychopathology has flourished. Significant progress has been made in identifying biological, cognitive, and affective-based vulnerability processes, aided by advances in the biological and behavioral sciences. For example, progress in molecular genetics has led to the identification of specific genes that may play a causal role in the emergence of specific disorders and the contribution of specific gene–environment interactions. Additionally, single-factor models of vulnerability to psychopathology have been replaced by diathesis–stress and developmental models of psychopathology. Guided by these developmentally based models, progress has been made in understanding the interaction between vulnerability processes and environmental stressors over time and in determining the influence of this interaction on both the emergence and maintenance of psychopathology. It is within the context of this expanding knowledge base that we and our editorial partners at The Guilford Press believed it was time to work toward summarizing what has been learned since the publication of the first edition. Our goal with the second edition is to consolidate what is currently known about the vulnerability processes associated with various forms of psychopathology and propose directions for future research. It is our hope that the theory and research discussed here will contribute to the advancement of the research on the etiology, assessment, and treatment of psychopathology. Our first task in putting together the second edition was locating, contacting, and recruiting the stellar group of scholars who had worked with us to put together the successful original volume. Fortunately, we were able to convince an overwhelming majority of the original authors to rejoin us in this endeavor. We are grateful for being able to maintain such a high level of continuity in authors across these editions. With a team of eminent scholars reassembled, we began the process of constructing this edition. It was our desire to maintain the original structure that made this volume so unique. The original concept for the book was conceived together with

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Seymour Weingarten, Editor-in-Chief at Guilford, and with the aid of several thoughtful reviews of our initial prospectus. The outcome was to structure the volume according to each of the major disorders for which there is a significant research base. Accordingly, we invited one chapter on the childhood and adolescent form of a major disorder and also a chapter on the corresponding adult form of the disorder. This organizational scheme helped to ensure that the adult and childhood ends of lifespan vulnerability were covered. Moreover, we believed that the side-by-side appearance of chapters on adult and child vulnerability to a given disorder would help stimulate the integration of theory and research across the lifespan; our assumption was that those interested in adults would also learn from the corresponding childhood chapter and vice versa. Yet, organizing chapters side by side was not a completely satisfactory solution to the lack of theory and data across the lifespan. We therefore asked the respective authors of the childhood and adult chapters to collaborate on a brief summary chapter that would examine the points of contact and the points of departure between childhood and adulthood vulnerability and then point to future conceptual and research directions that might help bridge the gap between these different aspects of the lifespan. Thus, our hope was that each of these chapters—adult, child, and a summary—would help stimulate the eventual integration of knowledge of vulnerability across the lifespan. With these same goals in mind, we have retained this unique and informative structure in the second edition. We also chose to continue with the coverage of the same disorders that were included in the first edition. This allowed for continuity of coverage over the last decade of the literature associated with each of these disorders. We recognize that numerous disorders are examined in the scientific literature and that adequate coverage of each would be impossible in a single volume. Consequently, this volume covers the major families of disorders: alcohol/substance abuse, depression, anxiety, schizophrenia, and eating disorders. We acknowledge that some important conditions may not be included in this list, but we nevertheless believe that the list covers the bulk of psychopathological states that afflict people. We were also again faced with the challenge concerning the best approach for the coverage of personality disorders. This is a particularly thorny issue inasmuch as the precise diagnosis of these disorders in adulthood is difficult. Similarly, personality disorders for the most part lack childhood counterparts, even though they are recognized as having their roots in childhood through personality development. Moreover, even though the clinical and scientific literature identifies a range of personality disorders, differentiating among them is extremely difficult. It would have been easy to omit coverage of these disorders, yet we believe they are an extremely important set of disorders that, if nothing else, are frequently comorbid with other disorders. Therefore, as in the first edition, we again decided to include one chapter that examined possible childhood precursors to adult personality disorders. Although, of necessity, the format for this chapter differs from the others in the volume, our



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goals for this chapter are the same as our goals for the others: to stimulate theory and research to incorporate a lifespan approach to understanding vulnerability to psychopathology. This edition is organized into the same four parts as in the first edition: Part I includes three chapters that provide a broad introduction to the concepts of vulnerability as they pertain to both childhood and adulthood disorders. Chapter 1, by Ingram and Price, provides a general overview of the concept of vulnerability to psychopathology; Chapter 2, by Price and Zwolinski, examines child psychopathology vulnerability constructs and issues; and Chapter 3, by Ingram and Gallagher, explores these constructs and issues within the adult literature. In Part II, Geiger and Crick (Chapter 4) examine the overall idea of personality from the perspective of childhood and adolescent development, and then address the corresponding implications for adult personality disorders. In Part III we cover the major clinical syndromes mentioned earlier. Chassin, Beltran, Lee, Haller, and Villalta (Chapter 5) examine childhood vulnerability to alcohol and substance abuse, and Zvolensky, Kashdan, Gonzalez, and Hogan (Chapter 6) examine the adult counterpart. The next chapters examine depression, with the childhood and adolescence chapter by Garber (Chapter 8) and the adulthood chapter by Hammen, Bistricky, and Ingram (Chapter 9). Anxiety comes next, with Malcarne, Hansdottir, and Merz (Chapter 11) focusing on childhood and adolescence and Reese, Najmi, and McNally (Chapter 12) focusing on adulthood. These chapters are followed by vulnerability theory and research on schizophrenia. Here again we faced a challenge in organizing these chapters because schizophrenia typically emerges in late adolescence or early adulthood. Thankfully, we could rely on the expertise of our authors to determine how best to organize the vulnerability research in this area. Thus, Brennan and Walker (Chapter 14) discuss developmental approaches to understanding schizophrenia, and Compton and Harvey (Chapter 15) review research that have used other approaches. The final chapters in this part address eating disorders, first by Eddy, Keel, and Leon (Chapter 17) for children and adolescents and then by Thomas, Schwartz, and Brownell (Chapter 18) for adults. The final part contains one chapter (Chapter 20) by Price and Ingram that summarizes the previous chapters and provides some ideas on where the study of vulnerability is heading and where we believe it needs to proceed. The theme that occurs throughout this chapter is that integration of childhood and adult vulnerability is critical if we are to make genuine progress in understanding not only the genesis of disorders but also their treatment and prevention. Throughout the process of conceptualizing and editing both editions, we have become indebted to a number of individuals. We would like to express our thanks to Seymour Weingarten, who not only was supportive and encouraging of the project from the beginning but also freely shared his wisdom as we worked through the structure of the original edition. We also would like

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to thank Jim Nageotte, Senior Editor, for his guidance and insight, and most importantly, for his patience as we worked through putting together and editing the second edition. We also owe our gratitude to Jane Keislar, Assistant Editor, for helping us to remember, organize, and collect the numerous details that go into producing a quality product. It has been our pleasure to work with these talented and skilled professionals who have played no small part in helping us to put together both editions. Special thanks go as well to the contributing authors in this edition. In many cases we found ourselves to be voices from the past entering into their current realities to again request their assistance and expertise to help us compose a volume on vulnerability to psychopathology. With relatively little encouragement and begging, our esteemed colleagues agreed to again join us in this endeavor. To them we will always be grateful. Finally, we would like to thank our families, which have expanded since the publication of the first edition, for their patience and encouragement over the years as we have worked on both editions of this volume. As the research on resilience indicates, the various challenges of life, including putting together a quality edited volume, are overcome most successfully when surrounded by those who provide support and encouragement. Our personal experiences in completing this project have certainly found this to be true.

Contents

Part I. Foundations of the Vulnerability Approach to Psychopathology CHAPTER 1 Understanding Psychopathology: The Role of Vulnerability

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Rick E. Ingram and Joseph M. Price

CHAPTER 2 The Nature of Child and Adolescent Vulnerability: History and Definitions

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Joseph M. Price and Jennifer Zwolinski

CHAPTER 3 The Nature of Adult Vulnerability: History and Definitions

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Rick E. Ingram and Matthew W. Gallagher

Part II. Personality Disorders CHAPTER 4 Developmental Pathways to Personality Disorders

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Tasha C. Geiger and Nicki R. Crick

Part III. Clinical Syndromes Substance Use Disorders CHAPTER 5 Vulnerability to Substance Use Disorders in Childhood 113 and Adolescence Laurie Chassin, Iris Beltran, Matthew Lee, Moira Haller, and Ian Villalta

CHAPTER 6 Vulnerability to Substance Use Disorders in Adulthood 141 Michael J. Zvolensky, Todd B. Kashdan, Adam Gonzalez, and Julianna Hogan

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CHAPTER 7 Vulnerability to Substance Use Disorders across the Lifespan

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Laurie Chassin, R. Lorraine Collins, Jennifer Ritter, Mariela C. Shirley, Michael J. Zvolensky, amd Todd B. Kashdan

Depression CHAPTER 8 Vulnerability to Depression in Childhood and Adolescence

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Judy Garber

CHAPTER 9 Vulnerability to Depression in Adulthood

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Constance L. Hammen, Steven L. Bistricky, and Rick E. Ingram

CHAPTER 10 Vulnerability to Depression across the Lifespan

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Constance L. Hammen, Judy Garber, and Rick E. Ingram

Anxiety Disorders CHAPTER 11 Vulnerability to Anxiety Disorders in Childhood and Adolescence

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Vanessa L. Malcarne, Ingunn Hansdottir, and Erin L. Merz

CHAPTER 12 Vulnerability to Anxiety Disorders in Adulthood

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Hannah E. Reese, Sadia Najmi, and Richard J. McNally

CHAPTER 13 Vulnerability to Anxiety Disorders across the Lifespan

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Richard J. McNally, Vanessa L. Malcarne, Sadia Najmi, Ingunn Hansdottir, Hannah E. Reese, and Erin L. Merz

Schizophrenia CHAPTER 14 Vulnerability to Schizophrenia in Childhood and Adolescence

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Patricia A. Brennan and Elaine F. Walker

CHAPTER 15 Vulnerability to Schizophrenia in Adulthood

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Michael T. Compton and Philip D. Harvey

CHAPTER 16 Vulnerability to Schizophrenia across the Lifespan Patricia A. Brennan and Philip D. Harvey

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Eating Disorders CHAPTER 17 Vulnerability to Eating Disorders in Childhood and Adolescence

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Kamryn T. Eddy, Pamela K. Keel, and Gloria R. Leon

CHAPTER 18 Vulnerability to Eating Disorders in Adulthood

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Jennifer J. Thomas, Marlene B. Schwartz, and Kelly D. Brownell

CHAPTER 19 Vulnerability to Eating Disorders across the Lifespan

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Pamela K. Keel, Kamryn T. Eddy, Jennifer J. Thomas, and Marlene B. Schwartz

Part IV. Summary and Future Directions of the Vulnerability Approach CHAPTER 20 Future Directions in the Study of Vulnerability to Psychopathology

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Joseph M. Price and Rick E. Ingram



Index

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Part I

Foundations of the Vulnerability Approach to Psychopathology

Chapter 1

Understanding Psychopathology The Role of Vulnerability

Rick E. Ingram and Joseph M. Price

We believe there is no more important goal in psychopathology research than understanding the causes of psychopathology. Although there may be multiple pathways to such an understanding, theory and research on vulnerability are indispensable to this quest for causality. In a broad sense, it is difficult to envision an effective effort to understand the causes of disorder that does not include an examination of the processes that give rise to the disorder. Even more broadly, a case can be made that efforts to understand vulnerability to psychopathology underlie virtually all efforts to understand psychopathology itself. Theory and research related to a number of different psychopathological conditions are examined in the various chapters in this book. Each of these examinations focuses on the specific vulnerability theory and data that are relevant to particular disorders. We start here, however, with a broader examination of the idea of vulnerability that can serve as a foundation for understanding vulnerability in these more specific disorders. In this vein, we start by briefly examining what is arguably the single most important aspect of psychopathology, that is, the concept of causality in psychopathology. We follow with a discussion of the notion of vulnerability itself and then move to issues concerning the relationships among vulnerability, risk, and resilience, and then finally to issues concerning the distinction between childhood and adulthood.

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What Is Causality? In the most obvious sense, “causality” refers to the processes that create or facilitate the transition from a normal state of psychological functioning into an abnormal psychological state. Although this concept of causality is accurate, it is incomplete; causality does not refer simply to this onset phase but also to other important processes in the course of psychopathology. As such, a more complete examination of causality necessitates some discussion of both onset and maintenance processes.

Onset Causality Whether a first onset of a disorder or the occurrence of a subsequent episode of a disorder, understanding the processes involved in onset are critical to understanding the causes of psychopathology. From a vulnerability perspective, data on these processes inform researchers about the factors that place individuals at risk for experiencing a disorder. Similarly, data have also provided insights into how these risk processes in the nondisordered person are translated into a psychopathological state in that same person. Onset can be further understood in the context of distal and proximal vulnerability. Although investigators differ to some extent in drawing the temporal lines for these different risk processes, proximal factors are generally regarded as those that become apparent right before the onset of a disorder. Distal factors, however, occur before the disorder but more distant in time from its appearance. For example, a model of a psychopathological state that specified certain psychological or physiological responses to life events would be specifying a more proximal cause, whereas a model that focused on the creation of risk factors in childhood would be focusing on more distal variables.

Maintenance Causality Some researchers have differentiated between the onset and the maintenance of a disorder and have tacitly suggested that the onset or appearance of psychopathology is synonymous with causality. Correspondingly, maintenance processes are not viewed as causal, and hence relatively little importance is ascribed to these factors (Ingram, Miranda, & Segal, 1998). We argue, however, that causality is not synonymous solely with onset and that the factors that maintain a disorder can be legitimately seen as causal. We thus suggest that an exclusive focus on onset is too narrow a conception of the construct of causality. Consider the case of depression. A considerable amount of data shows that depression is a persistent disorder, with symptoms lasting months and in some cases years (e.g., dysthymia). Moreover, data also show that untreated depression lasts between 6 months to 1 year or, depending on the severity of the episode, possibly up to 2 years (Goodwin & Jamison, 1990). Unless a model argues that the factors that lead to the onset of a disorder are identical to the factors that maintain the disorder (and few



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even address this idea), the processes associated with the perpetuation of psychopathology can be considered to have real causal significance. Indeed, a case might be made that such factors are more meaningful than onset factors—that is, the psychological, interpersonal, occupational, academic, and perhaps biological damage associated with a disorder like depression arises not because it occurred but rather because it persists over weeks, months, and perhaps years. Although we focus on depression in this example, virtually all psychopathological states are problematic not only because they occur but also because they are maintained over time. We can therefore legitimately ask whether the causes of this occurrence over time are any less important than the causes of its initial appearance. Thus, we argue that fully understanding vulnerability requires investigating not only the factors that bring about a disordered state but also those that result in its continuation over time.

How Do We Define Vulnerability? It seems reasonable to assume that a volume on vulnerability to psychopathology should offer, at a minimum, some ideas on how to define the vulnerability construct. Although the vulnerability approach to psychopathology is at least several decades old, little consensus has been reached on what constitutes an adequate definition of “vulnerability” (Ingram et al., 1998). This definitional shortcoming persists even though ideas about vulnerability have generated a significant body of theory and data. Such a corpus of knowledge is possible because we arguably know vulnerability when we see it and because researchers can identify demonstrably vulnerable groups to study. For example, data show that people who have experienced a disorder are at greater likelihood of experiencing another disorder, and hence investigators can assemble such groups to study vulnerability. Yet, these operational definitions leave aside the broader question about what constitutes the vulnerability construct itself. Of course, simple definitions of “vulnerability” abound, and for the public at large such terms are quite appropriate. For example, those who are vulnerable are liable to, or susceptible to, psychopathology. From a scientific standpoint, however, exchanging one poorly defined term for another is an unsatisfactory means of appreciating the nature and complexity of the vulnerability construct. Although truly comprehensive definitions of vulnerability are rare, one can derive a conceptual understanding of this construct by examining its core features, that is, those features that have been examined in theory and research and that can therefore offer important clues about its nature (Ingram et al., 1998).

Core Features of Vulnerability Examination of the literature suggests that several themes appear repeatedly in discussions of vulnerability, which focus on vulnerability as a stable trait,

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the endogenous and latent nature of vulnerability, and the role of stress in actualizing vulnerability. We now turn to a brief examination of each theme.

Vulnerability as a Stable Trait Researchers frequently discuss vulnerability as an enduring trait. Zubin and Spring (1977) pioneered many of the ideas about vulnerability in their work on understanding causal processes in schizophrenia. Zubin and Spring were also the most specific about what they regarded as the trait-like nature of vulnerability: “We regard [vulnerability] as a relatively permanent, enduring trait” (p. 109); “the one feature that all schizophrenics have . . . is the everpresence of their vulnerability” (p. 122). They leave little doubt that “vulnerability” refers to processes that endure over time. Other investigators have tended to be not quite as specific, but the traitlike nature of vulnerability is nevertheless implicit in many of their discussions of vulnerability. Such assumptions of permanence are likely rooted in the genetic level of analysis employed by researchers who pioneered this concept. For example, many schizophrenia researchers emphasize the genetic endowment of individuals who are at risk for this disorder. Meehl’s (1962) pioneering concept of schizotaxia represents an inherited neural deficit, whereas other influential researchers such as Zubin and Spring (1977) and Nicholson and Neufeld (1992) are quite explicit that genetic factors determine the relative level of vulnerability (at least for schizophrenia). Permanence, however, need not be rooted in genetic factors. An example from the schizophrenia literature is again illustrative. Researchers have suggested that prenatal stress or trauma may lead to vulnerability to schizophrenia (Brennan & Walker, Chapter 14, this volume). For example, both maternal influenza and significant famine have been linked to a rise in the rate of schizophrenia. In regard to the latter example, a two-fold increase in schizophrenia was subsequently reported following a massive famine in China between 1959 and 1961 (St. Clair et al., 2005). Postnatal factors, such as exposure to environmental toxins, have also been implicated (Brown, 2007), which may interact with genetic liabilities to render the vulnerability even more permanent. Such conceptualizations tend to posit that no decrease in absolute vulnerability levels is possible. This is not to suggest, however, that functional vulnerability levels cannot be attenuated by several factors, such as those that affect neurochemistry. For instance, medications such as lithium carbonate, which alters the likelihood of developing the symptoms of a bipolar episode by presumably controlling the neurochemistry of the underlying vulnerability, may prove helpful. Similar diminishment of functional vulnerability may be seen in the actions of psychopharmacological treatments for depression with medications such as the various generations of tricyclic agents and the more recent selective serotonin reuptake inhibitors (Potter, Padich, Rudorfer, & Krishnan, 2006; Shelton & Lester, 2006). Even though functional vulner-



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ability may be altered and individuals are less likely to develop the disorder, the vulnerability persists; for example, in many cases the probability of experiencing a psychiatric episode is increased if the medication is discontinued. Thus, even though the vulnerability may be controlled, the vulnerability trait itself remains. The trait-like nature of vulnerability is perhaps most clearly seen in contrasting it to the episodic nature of psychological disorders. For instance, Zubin and Spring (1977) clearly distinguish between an enduring vulnerability trait and episodes of schizophrenia that “are waxing and waning states” (p. 109). Hollon, Evans, and DeRubeis (1990) and Hollon and Cobb (1993) also distinguish between (1) stable vulnerability traits that predispose individuals to the disorder but do not constitute the disorder and (2) state variables that represent the occurrence of the symptoms that reflect the onset of the disorder. Thus, while predisposing factors are enduring traits, virtually all investigators characterize the disorder itself as a state. Disordered states can therefore emerge and decline as episodes cycle between occurrence and remission, but the traits that give rise to vulnerability for the disordered state are typically thought to remain constant. Although vulnerability is assumed by many theorists, particularly those working within a genetic framework, to be permanent and enduring, this need not be the case. This is especially true when the level of vulnerability analysis is psychological rather than genetic or prenatal in nature. As we have noted, assumptions of genetic vulnerability offer little possibility for the modification of vulnerability characteristics. Many psychological approaches, however, rely on assumptions of dysfunctional learning as the genesis of vulnerability. Given these assumptions, not only functional but actual vulnerability levels may fluctuate as a function of new learning experiences that influence the particular vulnerability factor. For instance, Hollon, Stewart, and Strunk (2006) have summarized data showing that, compared to pharmacotherapy for depression, cognitive therapy is more effective in preventing relapse and recurrence, presumably because the underlying vulnerability has been at least partially altered. In this vein, Hollon et al. (1990) and Hollon and Cobb (1993) argue that the effects of pharmacological treatments may be largely symptomsuppressive but that psychological interventions such as cognitive therapy are designed to alter dysfunctional cognitive structures and, to the extent that genuine vulnerability is rooted in such structures, may lessen susceptibility to psychopathology. Fewer recurrences of the disorder over time may reflect decreased vulnerability. It is certainly possible that factors other than vulnerability reduction may be at the heart of cognitive therapy’s prophylactic effects, but this example does illustrate how, theoretically at least, actual vulnerability levels might be altered. Of course, from the viewpoint of a psychological level of analysis, vulnerability may decrease with certain corrective experiences, or, alternatively, it may increase over time. This latter possibility would be the case if continued exposure to aversive experiences and stressful life events served the function

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of enhancing the factors that contribute to vulnerability. Some perspectives have suggested that frequent experiences with the disorder itself may increase vulnerability for future onsets. For example, in describing the idea of kindling, Post (1992, 2007) has proposed such a process in the area of affective disorders. Post suggests that each episode of an affective disorder leaves a residual neurobiological trace that leads to the development of pathways by which increasingly minimal stress becomes sufficient to activate the mechanisms that result in a disorder. Such a process thus leads to increased vulnerability. The possibility that psychological vulnerability levels can be altered (up or down) suggests a subtle but potentially important distinction between stability and permanence. Stability and permanence are likely to be viewed as synonymous. However, even though the concept of stability clearly suggests a resistance to change, it does not presume that change is never possible. Under the right circumstances, changes in an otherwise stable variable may very well occur. Indeed, the entire concept of psychotherapy is based on precisely this premise. Without intervention or the introduction of other significant life experiences, however, little change in stable psychological variables should occur. On the other hand, variables that are considered to be enduring, particularly biological processes emanating from genetic or prenatal processes, imply a permanence or immutability that is not only resistant to change under ordinary circumstances but is assumed to offer virtually no possibility of change.

Vulnerability as Endogenous and Latent Another core feature that is possible to glean from vulnerability research is that vulnerability represents an endogenous variable. This is perhaps most clearly seen in genetic conceptualizations of vulnerability, but it is equally relevant for psychological conceptualizations. That is, whether stemming from inborn characteristics or acquired through learning processes, the vulnerability resides within the person. This aspect can be contrasted to other levels of analysis that might, for example, focus on environmental or external sources of stress that initiate a disorder, or perhaps a focus on interpersonal styles that may lead to aversive interactions (see Joiner & Coyne, 1999). We discuss this distinction more fully in the section differentiating vulnerability from risk. For now it is important to note that, although these “external” variables are clearly important, the locus of vulnerability processes is within the person. In line with the idea that vulnerability is an endogenous process, and that vulnerability remains stable even though observable states of psychopathology arise and then (in many cases) diminish, some investigators have suggested that vulnerability is not easily observable and can thus best be conceptualized as a latent process. From a research perspective, this feature can perhaps be seen most clearly in the empirical search for observable markers of vulnerability; numerous investigators have sought to find reliable empirical indicators of the presence of the vulnerability. There are a variety of research strategies for identifying markers, but in each case they operate with the assumptions



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that (1) vulnerability processes are present in individuals who have few or no outward signs of the disorder, (2) these processes are causally linked to the appearance of symptoms, and (3) they are not readily observable and are therefore difficult to assess. This sense of latency is particularly the case in investigations that rely on some kind of stressful or challenging event that makes detection of the vulnerability factor possible (see Shelton, Hollon, Purdon, & Loosen, 1991, for a discussion of the challenge paradigm as it pertains to the conceptualization of vulnerability and dysregulation). The search for vulnerability indicators is thus the search for predictors of the disorder in the absence of symptoms of the disorder, an empirical strategy reflecting a conceptual judgment that vulnerability is present and stable but not easily observable—that is, latent.

The Role of Stress We have alluded to the importance of stress in fully defining vulnerability, and it is therefore important to note that although stress may not be a core feature of vulnerability in the sense that it is stable and endogenous, it nevertheless is an important enough variable to be included within any discussion of the core features of vulnerability. To comprehensively examine definitions of “stress” would require an entire volume, and indeed while volumes have been devoted to this topic (for classic examples, see Brown & Harris, 1989, and Cohen, 1988). In general, however, stress can be understood as falling into several broad categories. A number of investigators (e.g., Luthar & Zigler, 1991; Monroe & Simons, 1991) note that a major category of stress is conceptualized as the occurrence of significant life events that, in the case of psychopathology, are interpreted by the person as undesirable or aversive. Another kind of stress can be seen as the accumulation of minor events, hassles, or challenges (Lazarus, 1990). Although the definitions of “stress” may be numerous, we can view stress generally as the life events (major or minor) that disrupt the mechanisms maintaining the stability of an individual’s physiology, emotions, and cognitions. Classic descriptions of stress suggest that such events represent a strain on the person’s adaptive capability that initiates an interruption of the person’s routine or habitual functioning. As such, stress interferes with the system’s physiological and psychological homeostasis and is thus seen as a critical variable in a multitude of models of psychopathology (Monroe & Harkness, 2005; Monroe & Simons, 1991), regardless of whether these models focus explicitly on (endogenous) vulnerability factors. The problems with conceptualizing and adequately assessing stress have been well documented, as have concerns about separating concepts of stress from concepts of psychopathology (e.g., Hammen, 1991; Monroe & Harkness, 2005; Monroe & Simons, 1991). Nevertheless, we argue that at a conceptual level it makes sense to separate stress from vulnerability and psychological disorder. Such a conceptual separation recognizes the possibility that

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stress can exist independently of appraisal processes and can be consensually defined and objectively measured; everyone would agree, for instance, that a car accident resulting in permanent confinement to a wheelchair will be stressful for everyone regardless of his or her appraisal processes. Moreover, separation of the stress and vulnerability constructs facilitates communication about the variables potentially operating in psychopathology; that is, it is possible to talk about stress without frequent qualifications attributable to appraisal processes.

The Diathesis–Stress Relationship By conceptually separating stress and vulnerability, we are better able to examine the diathesis–stress relationship. The diathesis concept has a long history in medical terminology. In tracing this history, Monroe and Simons (1991) note that the concept dates back to the ancient Greeks and as early as the late 1800s was well lodged in the psychiatric vernacular of the day. “Diathesis” signifies a predisposition to illness and has evolved from its original focus on constitutional, biological factors to presently also encompass psychological variables such as cognitive and interpersonal susceptibilities. Moreover, such diatheses are typically considered to be latent and, as we have noted, must be activated in some fashion before psychopathology can occur. In line with this concept, many models of psychopathology are explicitly diathesis–stress models. Thus, although there is general agreement that vulnerability constitutes an endogenous process, most models also recognize that events perceived as stressful act to trigger vulnerability processes that are linked to the onset of the disordered state. In many cases, psychopathology is therefore the interactive effect of the (latent and endogenous) diatheses and events perceived as stressful. Framed within the context of a diathesis–stress conceptualization, stress is integral to virtually all current conceptualizations of vulnerability.

Summary of the Core Features of Vulnerability In sum, a review of the existing literature suggests a number of essential features that characterize the construct of vulnerability. Perhaps its most fundamental core feature is that vulnerability is considered a trait (rooted in biological and/or psychological processes) as opposed to the kind of a state that more accurately characterizes the actual appearance of the disorder. Despite its trait-like qualities, vulnerability is not necessarily permanent or unalterable (though psychological vulnerability is relatively stable and resistant to change). Corrective experiences can occur that may attenuate the vulnerability, or, alternatively, certain experiences may increase vulnerability factors. In addition, vulnerability is viewed as an endogenous process that is typically conceptualized as latent. Finally, although conceptually distinct from vulnerability, stress is a critical “feature” of vulnerability in that many models postulate that vulnerability cannot be realized without stress. This last feature



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of vulnerability represents the essence of the diathesis–stress approach that is common among many current models of psychopathology.

The Relationships among Vulnerability, Risk, and Resilience Terms such as “vulnerability” and “risk” (and to a lesser degree “resilience”) tend to be used interchangeably. Such usage is understandable; clearly the ideas of vulnerability and risk refer to similar phenomena and share a number of features. Nevertheless, we believe that these terms, and the constructs they represent, are not interchangeable and should be clearly distinguished in any discussion of vulnerability. We therefore examine the associations between vulnerability and risk and vulnerability and resilience, respectively.

Vulnerability and Risk Vulnerability and risk are not synonymous. We argue, as have others (e.g., Cicchetti & Valentino, 2006), that the concept of risk refers to variables that are empirically associated with a greater likelihood of experiencing a disorder (e.g., poverty and stress as they relate to social injustice). Risk thus serves broadly to predict the likelihood of dysfunction. However, it is not informative about the actual mechanisms of a disorder. That is, risk tells us that someone may develop a disorder but not specifically how or why the disorder occurs. Thus, risk refers to descriptive variables rather than causal ones. Because risk factors are generally uninformative about the actual mechanisms that bring about a state of psychopathology, knowledge about risk factors is not particularly helpful with regard to specific psychosocial intervention strategies. Presumably the most effective treatment for a disorder targets not only the symptoms of the disorder but also the mechanisms that helped to bring it about, although it should be noted that some authors have argued that the only effective treatment is one that alters broadly defined risk factors. For example, Albee (2000) makes the case that until risk factors such as poverty and social injustice are changed, individual treatment is likely to be ineffectual—akin to using a band-aid to try to stop a hemorrhage. It should also be noted that, although risk and vulnerability are conceptually separate, these concepts are not necessarily empirically unrelated. In pointing out a similar distinction between vulnerability and risk, Rutter (1987) and Luthar and Zigler (1991) have argued that these variables interact with one another to produce the onset of a disorder. Thus, the person who is “at risk” because he or she lives, for example, in a particularly stressful environment is apt to see this risk realized in disorder if he or she also possesses the vulnerability mechanisms. This is the essence of the diathesis–stress interaction that characterizes numerous models of psychopathology. We have argued that risk represents a descriptive factor rather than a

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causal one, and that as an endogenous factor, only vulnerability can play a causal role. Yet, data have shown that risk variables both can predict the onset of psychopathology and are correlated with vulnerability. Such findings may make it tempting to suggest that risk variables might in fact have causal significance. Rutter et al. (1988), however, cautions against drawing causal inferences solely from risk variables that appear linked to a disorder. To illustrate this point, Rutter (1988) notes findings indicating that test results on a national examination were superior for schools where the children’s work was exhibited on the walls (Rutter, Maughan, Mortimore, & Ouston, 1979). This positive association constituted an empirical predictor of better test performance, but few would argue that putting children’s work on the wall “caused” the improvement in their test grades. Rather, such behavior was indicative of an enhanced school atmosphere that perhaps had some causal link to better performance. In sum, then, risk is an important predictive variable that tends to operate in concert with vulnerability, but it is uninformative, either theoretically or empirically, about mechanisms. “Vulnerability,” on the other hand, is a term that should be reserved for discussion of the mechanisms implicated in the onset or maintenance of a disorder.

Vulnerability and Resilience ”Invulnerability,” “competence,” “protective factors,” and “resilience” are terms used by various investigators to describe the opposite of vulnerability. Each of these terms suggests some level of invulnerability to psychopathology in the face of stress, and although they may reasonably be used interchangeably, some subtle distinctions do exist. For example, invulnerability suggests an absolute level of protection from psychopathology; to the extent that individuals are characterized as invulnerable, the implication is that they will never experience a disorder. “Resilience,” on the other hand, suggests that it is difficult but not impossible to experience psychopathology. We thus prefer the concept of resilience over others because it implies a diminished, but not zero, possibility of psychopathology. A working assumption is that resilience and vulnerability represent different ends of a vulnerability continuum. Such a continuum is seen as interacting with stress to produce the possibility that a disordered state will occur. Thus, at the most extreme vulnerability end of the range, little life stress is necessary to result in a disorder. At the resilient end of the range a great deal of stress will be needed before psychopathology develops. Figure 1.1 represents the vulnerability–resilience relationship. As this figure illustrates, with enough stress even the most resilient people will be at significant risk for the development of symptomatology, although these symptoms will probably be milder than those of the vulnerable person who experiences low to moderate stress and will almost certainly be milder than those of the vulnerable person under significant stress. Resilience thus suggests the opposite of vulnerability and implies a resistance to disorder but not an immunity.



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FIGURE 1.1.  Representation of a diathesis–stress continuum. When vulnerability is at its highest level, less stress is required to activate psychopathology.

Defining Childhood and Adulthood: Where Do We Draw the Line? An examination of vulnerability across the lifespan obviously encompasses vulnerability theory and research on both children/adolescents and adults. This begs the question, however, as to where to draw that line between childhood and adulthood. Although the distinction is clear in many cases (e.g., comparing a 5-year-old child to a 50-year-old adult), differentiating the actual line is significantly more difficult. There are several approaches to differentiating childhood from adulthood. Perhaps the most simple relies on legal definitions, although even here the distinction is not always clear. For example, in the United States adulthood is legally defined for most behaviors as beginning at age 18. At this age, individuals have virtually all the legal rights and responsibilities of all other adults. Yet, there is at least one notable exception—in most states the right to drink alcohol and to work in settings where alcohol is served is not granted until age 21. Legal definitions within the United States thus view adulthood as commencing for the most part at age 18 and completely by age 21. Another way to demarcate between childhood and adulthood, which is particularly relevant for any discussion of vulnerability to psychopathology, is to rely on the current North American psychiatric classification system, DSMIV-TR (American Psychiatric Association, 2000). In terms of explicit defini-

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tions, however, DSM-IV-TR generally sidesteps this issue and states that the provision of a separate section for disorders that are usually first diagnosed in childhood or adolescence is not meant to suggest that “there is any clear distinction between ‘childhood’ and ‘adult’ disorders” (p. 39). Nevertheless, when age is mentioned at all in diagnosing “Disorders Usually First Evident in Infancy, Childhood, or Adolescence” (the general category that covers all these disorders), the maximum age is 18 for disorders appearing in adolescence. Likewise, most assessment methods for children and adolescence (e.g., the Diagnostic Interview for Children and Adolescents) define their top range at around age 17, and corresponding assessment methods for adults typically define a minimum age of 18 (e.g., the Structured Clinical Interview for DSMIV Disorders [SCID]). The current diagnostic approach thus appears to have adopted an age demarcation between adolescence and adulthood similar to the U.S. legal standard, although for different reasons. Another and more comprehensive approach focuses on theory and research on developmental processes. Rather than relying on arbitrary ages and legal standards, a developmental approach considers the physiological, emotional, and psychological maturation processes that occur as individuals progress from childhood to adulthood. Not surprisingly, from this perspective no single age best represents when an individual transitions into adulthood. In terms of physical maturation (e.g., maximum height and the development of secondary sexual characteristics) girls typically reach maturity by roughly age 16, whereas boys typically do so by age 18. However, some physical change will continue (e.g., brain maturation and adding strength and muscle mass through the mid- to late 20s). But physical maturation alone is not sufficient to differentiate between adolescence and adulthood in a psychological or emotional sense. The determination of adulthood is also strongly influenced by the social context in which development occurs. For example, cultural differences can vary widely. In most non-Western cultures the transition from childhood to adulthood is socially defined and marked by a significant social event, such as marriage. In contrast, in the contemporary West, where there is a strong emphasis on individualism and independence and fewer and less well defined rituals of passage, the transition to adulthood is often determined by individual cognitive, emotional, and behavioral changes (Arnett & Taber, 1994). Nevertheless, from a developmental perspective, by approximately 18 years of age most individuals have experienced physiological, psychological, behavioral, and social changes that propel them to at least begin the transition into adulthood. It is clear that any approach to defining adulthood must take into account a wide range of psychological, physiological, and cultural factors. Certainly the boundary between adolescence and adulthood is best represented as a gradual transition rather than an abrupt change. In general, however, at least in Western societies, it seems safe to suggest that the ages of 18–20 are a



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reasonable time to begin to differentiate between adolescence and adulthood, recognizing that some individuals will not developmentally “fit” their age category. In fact, each of the approaches we briefly examined to determine the boundary between adolescence and adulthood (legal, psychiatric, and developmental) seems to converge on a similar time frame. Thus, somewhere between the ages of 18 and 20 appears to be a convenient place to mark the transition from adolescence to adulthood. Indeed, even a cursory review of the published research on child and adult psychopathology supports this age period as the typical line of demarcation between adolescence and adulthood.

Psychopathology and Vulnerability Foundations: A Brief Summary In this chapter we have noted two different facets of causality: causes of disorder and causes of the maintenance of disorder. We also examined certain core features that appear to characterize vulnerability constructs. In particular, we argued that vulnerability refers to the relatively stable causal mechanisms of psychopathology that are endogenous to the individual but that for many psychopathological states are actualized through a diathesis–stress relationship. We also noted distinctions between the concepts of vulnerability and risk and further suggested a preference for conceptualizing vulnerability and resilience as different ends of the vulnerability continuum, noting that resilience implies a resistance but not an immunity to disorder. We briefly reviewed some different perspectives on differentiating adolescence and adulthood and noted that they tend to converge on the ages of 18 to 20 as defining the transitional phase into adulthood. As should be at least implicit in this discussion, we believe that vulnerability research represents not only the current cutting edge of psychopathology research but also the future for psychopathology research. Not that psychopathology research that focuses on describing the operation of various processes in the disordered state will be unimportant, but rather the clearest advances in understanding the causes of psychopathology will come from research that focuses explicitly on vulnerability. Not only will this approach bring us closer to understanding causal processes, but also in so doing it will bring us closer to understanding the mechanisms that must be therapeutically addressed once a disorder has occurred. An adequate understanding of vulnerability can also aid in preventing the onset of psychopathology, or at the least attenuating the duration and intensity of disorders along with their damaging effects (e.g., deficits in interpersonal functioning). Moreover, although still separated by a gulf between childhood/adolescence and adulthood theory and research, we believe that the clearest road to understanding vulnerability and prevention will come from research that considers vulnerability from a lifespan perspective.

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References Albee, G. W. (2000). Critique of psychotherapy in American society. In C. R. Snyder & R. E. Ingram (Eds.), Handbook of psychological change: Psychotherapy processes and practices for the 21st century (pp. 689–706). New York: Wiley. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author. Arnett, J. J., & Taber, S. (1994). Adolescence terminable and interminable: When does adolescence end? Journal of Youth and Adolescence, 13, 517–537. Brown, G. W., & Harris, T. O. (Eds.). (1989). Life events and illness. New York: Guilford Press. Brown, J. (2007). Psychiatric issues in toxic exposure. Psychiatric Clinics of North America, 30, 837–854. Cicchetti, D., & Valentino, K. (2006). An ecological–transactional perspective on child maltreatment: Failure of the average expectable environment and its influence on child development. In D. Cicchetti & D. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (pp. 129–201). Hoboken, NJ: Wiley. Cohen, L. (Ed.). (1988). Research on stressful life events: Theoretical and methodological issues. Newbury Park, CA: Sage. Goodwin, F. K., & Jamison, K. R. (1990). Manic–depressive illness. New York: Oxford University Press. Hammen, C. (1991). The generation of stress in the course of unipolar depression. Journal of Abnormal Psychology, 100, 555–561. Hollon, S. D., & Cobb, R. (1993). Relapse and recurrence in psychopathological disorders. In C. G. Costello (Ed.), Basic issues in psychopathology (pp. 377–402). New York: Guilford Press. Hollon, S. D., Evans, M. D., & DeRubeis, R. J. (1990). Cognitive mediation of relapse prevention following treatment for depression: Implications of differential risk. In R. E. Ingram (Ed.), Contemporary psychological approaches to depression: Theory, research, and treatment (pp. 117–136). New York: Plenum Press. Hollon, S. D., Stewart, M. O., & Strunk, D. (2006). Enduring effects for cognitive behavior therapy in the treatment of depression and anxiety. Annual Review of Psychology, 57, 285–315. Ingram, R. E., Miranda, J., & Segal, Z. V. (1998). Cognitive vulnerability to depression. New York: Guilford Press. Joiner, T., & Coyne, J. C. (1999). (Eds.). The interactional nature of depression. Washington, DC: American Psychological Association. Lazarus, R. S. (1990). Theory-based stress management. Psychological Inquiry, 1, 3–13. Luthar, S. S., & Zigler, E. (1991). Vulnerability and competence: A review of research on resilience in childhood. American Journal of Orthopsychiatry, 61, 6–22. Meehl, P. E. (1962). Schizotaxia, schizotypy, schizophrenia. American Psychologist, 17, 827– 838. Monroe, S. M., & Harkness, K. L. (2005). Life stress, the “kindling” hypothesis, and the recurrence of depression: Considerations from a life stress perspective. Psychological Review, 112, 417–445. Monroe, S. M., & Simons, A. D. (1991). Diathesis–stress theories in the context of life stress research: Implications for the depressive disorders. Psychological Bulletin, 110, 406– 425. Nicholson, I. R., & Neufeld, R. W. J. (1992). A dynamic vulnerability perspective on stress and schizophrenia. American Journal of Orthopsychiatry, 62, 117–130. Post, R. M. (1992). Transduction of psychosocial stress into the neurobiology of affective disorder. American Journal of Psychiatry, 149, 999–1010. Post, R. M. (2007). Kindling and sensitization as models for affective episode recurrence, cyclicity, and tolerance phenomena. Neuroscience and Biobehavioral Review, 31, 851–873.



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Potter, W. Z., Padich, R. A., Rudorfer, M. V., & Krishnan, R. R. (2006). Tricyclics, tetracyclics, and monoamine oxidase inhibitors. In D. J. Stein, D. J. Kupfer, & A. F. Schatzberg (Eds.), Textbook of mood disorders (pp. 251–262). Washington, DC: American Psychiatric Association. Rutter, M. (1987). Psychosocial resilience and protective mechanisms. American Journal of Orthopsychiatry, 57, 316–331. Rutter, M. (1988). Longitudinal data in the study of causal processes: Some uses and some pitfalls. In M. Rutter (Ed.), Studies of psychosocial risk: The power of longitudinal data (pp. 1–28). Cambridge, UK: Cambridge University Press. Rutter, M., Maughan, B., Mortimore, P., & Ouston, J. (1979). Fifteen thousand hours: Secondary schools and their effects on children. London: Open Books. Shelton, R. C., Hollon, S. D., Purdon, S. E., & Loosen, P. T. (1991). Biological and psychological aspects of depression. Behavior Therapy, 22, 201–228. Shelton, R. C., & Lester, N. (2006). Selective serotonin reuptake inhibitors and newer antidepressants. In D. J. Stein, D. J. Kupfer, & A. F. Schatzberg (Eds.), Textbook of mood disorders (pp. 263–280). Washington, DC: American Psychiatric Association. St. Clair, D., Xu, M., Wang, P., Yu, T., Fang, Y., Zhang, F., et al. (2005). Rates of adult schizophrenia following prenatal exposure to the Chinese famine of 1959–1961. Journal of the American Medical Association, 294, 557–562. Zubin, J., & Spring, B. (1977). Vulnerability: A new view of schizophrenia. Journal of Abnormal Psychology, 86, 103–126.

Chapter 2

The Nature of Child and Adolescent Vulnerability History and Definitions

Joseph M. Price and Jennifer Zwolinski

Although the formal study of child psychopathology has had a shorter history than that of psychopathology in adulthood, the study of the vulnerability processes associated with psychopathology in children and adolescents has evidenced a dramatic increase in the past two decades and is now a well-established field of scientific inquiry. As is evident from the chapters in this volume, there now exists a substantial body of information on the vulnerability processes associated with specific forms of child and adolescent psychopathology. Evidence indicating that many childhood problems have lifelong consequences for individuals has contributed to the search for and study of vulnerability processes in children and adolescents. In addition, an increased realization of the resulting costs to the lives of individual children, their families, and society in general attributable to psychopathology has also contributed to the growing interest in the study of vulnerability to psychopathology in children and adolescents. In this chapter our goal is to accomplish two primary objectives: first, to provide a background on the study of vulnerability processes in children and adolescents by briefly reviewing some important issues related to the definition and prevalence of psychopathology during these important periods of development; and, second, to present a brief review of the history of the definitions, theories, and research methods that have been used to examine vulnerability factors related to child and adolescent psychopathology.

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Defining Psychopathology during Childhood and Adolescence Perhaps one of the greatest challenges to understanding vulnerability to psychopathology during childhood and adolescence is reaching consensus about how best to define psychopathology during these periods of development. Over the past several decades there has been a growing tendency to rely on definitions of psychopathology that are derived from standardized diagnostic systems such as the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000) and the International Classification of Diseases (ICD-10; World Health Organization, 1992). However, in spite of the increased acceptance and use of these diagnostic systems, there is still a lack of agreement on the exact nature of psychopathology during childhood and adolescence and the specific criteria that should be used to define psychopathology (Jensen, Knapp, & Mrazek, 2006). Mash and Dozois (2003) have identified several issues that are typically debated in discussions of the definition of psychopathology as it occurs during childhood and adolescence. Among the issues they mention are (1) whether child psychopathology is endogenous to the child, a reaction to environmental circumstances, or an interaction of both; (2) whether it is best to conceptualize psychopathology during childhood and adolescence as categorically distinct from normal functioning or as an extreme on a normally occurring dimension or trait, or both; (3) whether specific types of psychopathology can be identified during childhood and adolescence or whether it is best to view psychopathology as a configuration of co-occurring disorders or as a type of profile; and (4) whether psychopathology should be viewed as a static trait or as a dynamic and ongoing process that is influenced by both the developmental changes within the individual and changes in environmental contexts. In spite of the differences across researchers in their positions on these issues, there does seem to be some agreement that psychopathology represents difficulties or failures in negotiating developmental issues and tasks (e.g., Cicchetti, 2006; Jensen & Mrazek, 2006; Mash & Dozois, 2003; Sroufe, 1997). The essence of this perspective is that at each phase of development children are faced with the task of using both internal and external resources to adapt to developmental demands (e.g., developing language, learning to regulate emotions, and negotiating successful relationships with peers). If they are able to successfully adapt to these demands, their development is more likely to be oriented toward a normative trajectory. However, difficulties or failure in negotiating these demands can place a child on a trajectory toward psychopathology. Thus, psychopathology represents some form of maladaptation that results in the individual’s deviation from age-appropriate norms. Following from this perspective, it therefore becomes essential to identify and understand the specific developmental tasks that need to be accomplished at each phase of development (Mash & Dozois, 2003). Furthermore, because of the important influence of the context of development, it is also important to

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understand the contextual variables that can affect both the nature of the developmental tasks and the extent to which these tasks are successfully negotiated. Clearly, this particular view of psychopathology suggests that atypical development can only be understood in relation to normal development and within the relevant contexts of development. As becomes evident in a later section of this chapter, the increasing influence of a developmental psychopathology perspective on theory and research in child and adolescent psychopathology has played an instrumental role in the adaptation of this particular conceptualization of psychopathology.

Prevalence of Psychopathology in Childhood and Adolescence Despite the challenges to defining psychopathology in childhood and adolescence, over the past several decades a number of investigators have examined the prevalence of psychopathology in the developmental periods prior to adulthood. According to this research, about half of all Americans will meet diagnostic criteria for some psychiatric illness in their lives, with first onset during childhood or adolescence (Kessler, Berglund, Demler, Jin, & Watters, 2005). Current global epidemiological data consistently report that up to 20% of children and adolescents exhibit some form of disabling psychiatric illness (Belfer, 2008). Another consistent finding in these prevalence studies has been the high rates of comorbidity in clinical samples and, to a lesser extent—but beyond what one would expect from chance—in community samples (Knapp & Jensen, 2006). Not only was comorbidity found within the internalizing and externalizing clusters, but also overlap was found between these two clusters of symptoms (McConaughy & Achenbach, 1994). This consistent and striking degree of comorbidity presents challenges to understanding vulnerability processes in childhood and adolescence. As mentioned earlier, one of the unresolved issues in defining child and adolescent psychopathology is whether there are clearly identifiable categories of psychopathology or whether psychopathology represents a configuration of co-occurring disorders. If distinct homogeneous disorders do exist, then research on the vulnerability processes associated with these disorders could progress toward identifying and understanding the specific vulnerability processes associated with specific types of disorders. However, if psychopathology during childhood and adolescence is best represented by a constellation of comorbid conditions, then the task of identifying and understanding the vulnerability processes related to these conditions becomes a vastly more complex and challenging task.

Why Study Vulnerability Processes? As the prevalence estimates suggest, there is a clear need to identify and understand the causal factors underlying psychopathology that arise during child-



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hood and adolescence. The benefits from this line of research are numerous. First, the study of vulnerability processes contributes to understanding the nature of the development of psychopathology in children and adolescents. Through the study of vulnerability, the biological and psychological processes that make children susceptible to the development of psychopathology are identified and better understood, thus increasing our understanding of the potential causes of psychopathology in children and adolescents, Numerous studies of vulnerability in children from diverse cultural backgrounds have shown that there are similar risk and protective factors in the development of psychiatric disorders across cultures. What does vary, however, across cultures is the magnitude or intensity of these factors (Canino & Alegría, 2008). Through the investigation of vulnerability factors, we learn how these vulnerability processes interact with maturational processes within the child (e.g., dopaminergic dysfunction) and the environmental context (e.g., various forms of stress) to influence the onset and maintenance of disorder in children and adolescents. For example, over the past three decades the study of vulnerability to schizophrenia has revealed both genetically based and environmentally based (e.g., neurological deficits resulting from obstetrical complications) vulnerabilities associated with the development of schizophrenia. As Brennan and Walker point out (see Chapter 14, this volume), these vulnerability processes appear to interact with hormonal and neurological (i.e., neural pruning) changes in adolescence and with stress in adolescence and adulthood to contribute to the onset of the disorder. Now we have a much clearer picture (although far from complete) of the factors contributing to the emergence of schizophrenia than we did four decades ago when vulnerability research was still in its infancy. Second, in addition to enhancing our understanding of the processes contributing to atypical development, the study of vulnerability processes also contributes to our understanding of neurological, cognitive, and affective processes necessary for normal functioning and adjustment. In a review of the pathogenesis of childhood anxiety disorders, Muris (2006) reported a number of vulnerability and protective factors contributing to childhood anxiety, including recent empirical research support for Chorpita and Barlow’s (1998) model of anxiety and depression. According to this model, early life experiences with diminished control may foster the development of cognitions that certain events may be out of one’s personal control. Given that perceptions of a “lack of control” contribute to maladjustment and psychopathology, the converse is also true; that is, the development of a sense of control over one’s internal states and environmental events serves as a buffer to childhood anxiety (Muris, 2006). For example, children who report higher levels of perceived control also tend to display lower levels of anxiety (e.g., Muris, Schouten, Meesters, & Gijsbers, 2003; Weems, Silverman, Rapee, & Pina, 2003; Muris, 2006). Other protective factors similar to perceived control, such as self-esteem and self-efficacy, have also been shown to be inversely related to childhood anxiety (e.g., Muris, 2002; Muris, Meesters, & Fijen, 2003; Muris, 2006).

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Third, the study of the vulnerability factors and processes contributes to the development of efficacious treatment strategies for children who are experiencing some form of psychopathology. For example, theory and research on anxiety suggests that anxious children, like anxious adults, may have a biological vulnerability that takes the form of hypersensitivity to stress and challenge, along with a diffuse stress response involving a variety of neurobiological processes (see Malcarne, Hansdottir, & Merz, Chapter 11, and McNally et al., Chapter 13, this volume). These responses are associated with anxietyelevating cognitions (e.g., “I know I can’t do this”) and behavioral avoidance of the stressors. Because avoidance reduces distress and arousal, it becomes a reinforced behavioral tendency. Thus, dysfunctional anxiety results from a self-perpetuating cycle of biological arousal to stress, crippling cognitions, and avoidance of stressful situations. In an effort to alter this cycle, as revealed in vulnerability research, anxiety treatment researchers have developed a set of treatment strategies that involve helping children to recognize biological arousal associated with anxious feelings, to use relaxation techniques, to confront negative self-talk, and gradually to be exposed to stressful situations (Kendall, Aschenbrand, & Hudson, 2003). The research on vulnerability processes associated with other forms of psychopathology (e.g., depression and conduct disorders) has also contributed to the growing arsenal of efficacious treatment strategies for children and adolescents (see Kazdin & Weisz, 2003, for a review of this literature). Finally, research on vulnerability contributes to the development of preventative intervention programs for children and adolescents at risk for psychopathology. For example, Dodge and his colleagues (e.g., Dodge, 2006; Dodge, Bates, & Pettit, 1990; Landsford, Malone, & Dodge, 2006) have identified a number of social-cognitive processes associated with the development of aggressive behavior and conduct disorder. These processes include hostile attributions of others’ intentions, generation of aggressive solutions to social dilemmas, and the endorsement of aggressive responses as being effective solutions to conflicts (see Crick & Dodge, 1994). These cognitive orientations, which are hypothesized to develop in response to exposure to hostile home and community environments, in turn serve as vulnerability processes in the development of aggressive behavior. The findings from this line of research have contributed to the development of the “Fast Track” prevention program for conduct disorder. In this intervention program, as children begin kindergarten parents are taught to respond to and interact with their children in a manner that contributes to the formation of cognitions that support prosocial and competent forms of social behavior (see Conduct Problems Prevention Research Group, 1999a, 1999b, 2002). Another key component of this preventative intervention is to teach children within the context of interactions with peers how to identify the intentions of others, generate prosocial solutions to social dilemmas, and understand the value of nonaggressive behavior (Conduct Problems Prevention Research Group, 1999b). The initial results from this research indicated that at the end of first grade there were moderate posi-



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tive effects of the intervention on children’s social, emotional, and academic competencies and on children’s peer interactions and social status. There were also reductions in the rates of children’s aggressive behavior. Positive effects continued to be evident at the end of the third grade (Conduct Problems Prevention Research Group, 2002). More recent results have revealed effects of the intervention lasting into later elementary school and middle school (Conduct Problems Prevention Research Group, 2007). Although the study of vulnerability processes in children has potential benefits for understanding the development of psychopathology, for revealing essential processes for normal development and adjustment, and for the development of efficacious prevention and treatment strategies for children and adolescent psychopathology, several challenges still need to be addressed. One of these challenges is in reaching agreement on the definition and conceptualization of vulnerability in the child and adolescent literatures.

Defining Vulnerability Perhaps the greatest challenge in defining the concept of vulnerability within the child and adolescent literatures is distinguishing vulnerability from the concept of risk. As noted by several investigators (Ingram, Miranda, & Segal, 1998; Richters & Weintraub, 1990), these terms are often used interchangeably; thus, the statistical risk for a disorder is assumed to imply the presence of a vulnerability factor. However, there appears to be a growing consensus that, whereas risk describes a broad array of factors associated with an increased probability of the occurrence of a disorder, vulnerability represents a subset of risk that refers to factors endogenous to the individual that may serve as mechanisms in the development of the disorder. Aside from the confusion between the terms “risk” and “vulnerability,” there appears to be some agreement among those studying vulnerability to child and adolescent disorders as to the nature of vulnerability. First, vulnerability factors are generally viewed as characteristics that predispose an individual to develop a particular disorder. Thus, consistent with the definition of vulnerability used in this volume, vulnerability processes are viewed as playing some sort of causal role in the development of psychopathology (Albano, Chorpita, & Barlow, 2003; Richters & Weintraub, 1990). Second, vulnerability factors are typically conceptualized as characteristics residing within the individual that are either genetically or environmentally based. Hereditary factors include genetically determined neurobiological processes as well as various dimensions of temperament. Environmentally based factors are quite broad, ranging from central nervous system damage resulting from prenatal exposure to teratogens, obstetrical and birth complications to vulnerability factors acquired through exposure to early trauma (e.g., maltreatment), and socialization and learning processes (e.g., a lack of control that might result from overprotective parenting). The extent to which geneti-

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cally and environmentally based vulnerability processes have been examined in relation to a particular disorder is largely determined by the theoretical models guiding the research in that particular area. For example, research on vulnerability to schizophrenia has focused on both genetically based and environmentally based (e.g., obstetrical complications) vulnerability factors, which naturally follows the diathesis–stress models that have guided the research in this area for the past three decades (e.g., Asarnow & Asarnow, 2003). Similarly, in the mood disorders literature that often utilizes diathesis– stress models, both genetically based vulnerabilities (e.g., negative affect) and environmentally based vulnerabilities (e.g., learned helplessness) have been the focus of research. In contrast, research on conduct disorders has primarily focused on vulnerability processes acquired through socialization processes in early development (Dishion & Patterson, 2006; Dodge & Pettit, 2003). This is not surprising, given that the predominant theories guiding this research are rooted in behavioral (e.g., Patterson, 1993) and cognitive-social learning theories (e.g., Dodge, 1993). However, increasing attention has been directed toward understanding the biological and genetic bases of aggressive behavior (e.g., Jaffee et al., 2005; Dodge & Sherrill, 2007). Third, in general, vulnerability processes are viewed as being relatively stable and enduring. However, the extent to which a factor is seen as enduring depends on whether the factor is seen as a biological process that has its roots in hereditary processes, is the result of some sort of environmentally based trauma or injury, or has been acquired through learning processes (e.g., a negative self-schema). Whereas vulnerability processes rooted in hereditary processes or some sort of environmentally based injury are perceived as stable and enduring, vulnerability processes resulting from learning are seen as more malleable. Yet, even learning-based vulnerability processes are often viewed as being relatively stable and even enduring, especially if the environmental context in which the individual is developing consists of features that maintain the learning-based vulnerability process (e.g., persistent parental rejection).

History of Theory and Research on Vulnerability Factors Related to Child and Adolescent Psychopathology Theoretical Models Prior to the 20th century, there was a glaring absence of knowledge about child psychopathology and professional specialties that focused on child psychopathology (Rie, 1971). This was due, in part, to the general social philosophy that permeated mainstream culture that children were not valued persons but, rather, family possessions (Aries, 1962). During this period, child behavioral disorders were believed to be the result of either organic imbalances, inherent evil, or possession by supernatural forces. During the latter half of the 19th century, the philosophies of Locke



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(1690/1913), Rousseau (1762/1955), and others began to have an influence on societal conceptualizations of childhood (Colon & Colon, 2001). These philosophers asserted that the direction of children’s lives were not necessarily biologically determined and could be influenced by moral guidance and support. Consequently, concern for the needs of children in general began to increase across Europe and North America. By the turn of the century, specific concern for the welfare of children with mental and behavioral disorders was also increasing (Smuts, 2006). However, due to the heavy influence of the medical sciences and the organic disease model, mental disorders among children were often viewed as being biologically based. Although not discussed in terms of vulnerability processes, the causal mechanisms in the development of child disorders were seen as being rooted in the child’s physiological makeup. This perspective continued to dominate during the early part of the 20th century. However, over the next three decades, the role of environmental and social influences in the development of childhood disorders became more widely recognized and accepted as psychoanalytic and behavioral theories increased in influence and as three new child study models began to take hold in the United States (Smuts, 2006). The first of these models, labeled the “guidance movement,” introduced the clinical study of emotional and behavioral problems in children utilizing teams of psychiatrists, psychologists, and social workers who worked within community clinics rather than hospitals. The second model, based in the establishment of the United States Children’s Bureau, initiated the sociological study of children, pioneering survey techniques developed by urban social reformers during the Progressive era to the study of children and their families. The third model, the child development movement, with roots in the Iowa Child Welfare Research Station, institutionalized research on the physical, mental, and emotional development of normal children, with the goal of drawing insights from numerous disciplines, including psychology, psychiatry, pediatrics, nursing, anthropology, sociology, home economics, and education. The unifying goal of each of these models was the discovery of new knowledge, through science, about children in order to improve the lives of children and everyone in the nation (Smuts, 2006). Those within the child guidance movement hoped that the diagnosis and treatment of children’s problems would help to prevent later psychopathology. Staff members from the Children’s Bureau hoped to improve the living conditions of children and their families. Investigators and supporters of the child development movement hoped to improve child-rearing methods that would promote normal development and healthy adjustment through to adulthood. Each of these models would play an important role in helping to shape our understanding of children and the direction of research on childhood and adolescence through the remainder of the 20th century. Consequently, child guidance clinics were established throughout the United States; academic-based child development research institutes were established, such as the Institute for Child Development at the University of Minnesota; and the federal government became increasingly involved in funding basic and

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applied research aimed at improving the lives of children and their families. Unfortunately, the economic and personnel demands of World War II interrupted the initial momentum of these movements, which then resumed during the 1950s and 1960s. By 1962, Meehl (1962) introduced the diathesis–stress model of schizophrenia, which formally introduced the concept of vulnerability, along with the notion that psychopathology was a result of the interplay between both biological vulnerability processes and environmental stressors and influences. Meehl’s model helped to integrate the biological and environmental models of psychopathology. Since that time, the diathesis–stress model has been used to understand myriad childhood disorders, including childhood schizophrenia (e.g., Asarnow & Asarnow, 2003), anxiety (e.g., Albano et al., 2003), and depression (e.g., Hammen & Rudolph, 2003). The diathesis–stress model was also instrumental in launching research on the risks of psychopathology, which has expanded from an earlier focus on identifying risk factors associated with schizophrenia to the identification of risk factors associated with a wide range of child and adolescent disorders. With the advent of the field of developmental psychopathology, there has been a trend toward moving beyond diathesis–stress models to multidimensional models that reflect more of the dynamic nature of the interactions, or “transactions,” between the child and his or her environment, with particular importance given to developmental processes (e.g., Cicchetti, 2006; Hammen & Rudolph, 2003; Sroufe, 1997). Most of these developmental theories integrate the basic components of the general diathesis–stress model with developmental principles. The general characteristics of developmental models of psychopathology include several elements. First, vulnerability processes are viewed as being based in heredity, the environment, or the interaction of the two. Heredity-based vulnerability factors include neurological functioning and temperament. Environmentally based vulnerability factors include those arising from trauma or injury (e.g., attentional deficits or hostile attributional biases) or socialization processes (e.g., cognitions of self that emerge from parent–child interactions). Emergence of vulnerabilities resulting from the interaction between hereditary and environmental influences are also possible, such as when genes that contribute to early anxiety interact with overprotective parenting, resulting in heightened sensitivity and avoidance of stressful situations. Second, the developmental psychopathology perspective asserts that vulnerability factors can exist within any of the physiological, affective, cognitive, or social/behavioral systems. Table 2.1 lists several examples of vulnerability factors that have been found to be related to several different forms of psychopathology among children and adolescents. We have attempted to categorize each of these factors according to the type of developmental system it represents. As is evident from this table, for each of the forms of psychopathology listed, vulnerability factors have been found within each of the major



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TABLE 2.1.  Vulnerability Factors Related to Child Psychopathology

Anxiety

Cognitive Affective • Cognitions of • Difficulty diminished conregulating and trol over events monitoring or situations emotional • Excessive attenexpression tional allocation to threat

Social/ behavioral • Social evaluation fears • Insecure attachment

Biological • Heritability • Behavioral inhibition • Dysregulation of threat response

Depression

• Dysfunctional cognitive appraisals

Conduct disorder

• Automatic • Strong negative • Early antisocial • Neurological processing that affect and aggressive impairment includes aggres- • Impulsivity behavior • Heritability sive, hostile • Low fearfulness • Social • Problems with attributions withdrawal serotonergic • Low cognitive • Tendency to and stressability scores and respond to regulating verbal deficits threats with mechanisms • Disregard for frustration wishes and feelings of others

Attention• Cognitive deficit/ processing hyperactivity deficits disorder • Poor working memory • Executive functioning deficits

• Difficulty with emotional regulation

• Impaired emotional recognition • Impulsivity

Schizophrenia • Premorbid speech • Abnormal and language emotional impairments contact • Deficits in infor- • Emotional mation and atten- instability tional processes

• Anxious • Heritability attachment • Dysfunction of • Social impairhypothalamic– ments such as pituitary– withdrawal adrenal axis and social skill and other deficits hypothalamic– endocrine axes

• Social skills • Heritability deficits • Dysfunction in • Difficulties in frontosubcortimodulating cal pathways social • Imbalances in communication dopaminergic and noradrenergic systems • Reactive incentive response tendencies • Low birthweight • Problems with • Heritability social compe- • Altered tency neurohormonal • Social processes withdrawal • School problems

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domains or systems of development. According to the developmental psychopathology perspective, with age these systems become more integrated, thus enabling various vulnerability processes, as well as protective processes, to act in a synergistic fashion to influence the development of disorder (Cicchetti, 2006). Take, for example, the vulnerability processes associated with conduct disorders (CD). Biological vulnerability appears in the following areas: (1) neurological impairment (i.e., from disruption in the ontogenesis of the fetal brain such as exposure to toxic agents or child abuse and neglect; Craig & Pepler, 1997; Moffitt, 1993); (2) heritability (i.e., especially among children with CD who display callous and unemotional traits; Viding, Blair, Moffitt, & Plomin, 2005); and (3) biochemical influences (i.e., problems with the brain’s serotonergic and stress-regulating systems; VanGoozen, Fairchild, Snock, & Harold, 2007). Individuals with CD also tend to manifest certain social/behavioral vulnerabilities, including early onset of aggressive behavior and antisocial acts in multiple settings (Carr, 2006) as well as peer rejection (Snyder, Dishion, & Patterson, 1986). These social vulnerabilities interact with cognitive vulnerabilities such that the acquisition of knowledge and social information processing mediate the relation between life experiences and conduct problem outcomes (Dodge & Pettit, 2003). For example, memory structures and expectations can negatively affect the ability to form positive relationships and perpetuate the likelihood of negative social interactions (Cicchetti, 1990; Richters & Cicchetti, 1993). Additional cognitive vulnerabilities such as low verbal IQ and slow language development may interfere with parental attempts at socialization (Beitchman et al., 2001). These individuals display a variety of cognitive, perceptual, and attributional biases related to their CD problems (Dodge, Price, Bachorowski, & Newman, 1990), which are difficult to monitor and control. Individuals develop memory structures of the world as a hostile place that requires coercive behavior to achieve desired goals. Affective vulnerability such as emotional dysregulation can impair the development of social cognitive skills that allow the child to effectively process information (Dodge & Pettit, 2003). This vulnerability may manifest in a temperamental style marked by low fearfulness (Rothbart & Bates, 1998) and/or low behavioral inhibition (Kagan & Snidman, 1991), which can contribute to impulsivity (Moffitt, 2003) or a tendency to respond to threats with frustration (Gilliom & Shaw, 2004). Thus, individuals who are most vulnerable to CD are those who have a biological vulnerability for aggressive behavior as well as difficulty in controlling and managing negative affect. Further, they also tend to view the world and others as negative and hostile and demonstrate a variety of deficits in social competence. Conduct disorders then can be viewed as developing as a result of an interactional process among vulnerability processes from various developmental systems. Third, vulnerability processes within the individual are viewed as being in a dynamic interaction with environmental systems throughout the lifespan. This dynamic interaction, or transaction, is reciprocal in nature, allowing



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vulnerability processes both to influence and be influenced by environmental conditions (Cicchetti, 2006). Fourth, the degree to which an individual successfully negotiates the important developmental tasks at one phase of development (e.g., development of language skills in infancy and integration in the peer group in childhood) will have an impact on the degree to which developmental tasks are negotiated at subsequent phases of development (Sroufe, 1997). The development of various cognitive, affective, and social competencies acquired as a consequence of successful negotiation of developmental tasks will contribute to successful negotiation of the developmental requirements at the next phase of development and help to maintain a normative developmental trajectory. These competencies, in turn, can make the individual more resilient to the development of disorder, even in the presence of a vulnerability factor (see Masten, Burt, & Coatsworth, 2006, and Luthar, 2006, for reviews of this literature). Conversely, failure to develop necessary competencies becomes an obstacle to the negotiation of subsequent developmental tasks, thus contributing to the individual’s vulnerability to psychopathology later in development and increasing the possibility of an atypical developmental trajectory. Fifth, as might well be expected, developmental models emphasize the importance of understanding the particular pathway an individual takes in the development of a disorder. Even though two individuals may develop the same form of psychopathology (e.g., depression), the specific vulnerability factors and the dynamics of the interaction among these factors and the environment en route to the development of the disorder can differ (Pickles & Hill, 2006). Thus, a specific disorder may be reached from a variety of different initial conditions and through a variety of different processes. This phenomenon represents the construct referred to in general systems theory as epifinality. It is also recognized that the same vulnerabiity processes (e.g., inaccurate interpretations of others’ intentions) may lead to different types of disorders across different individuals, due to each person’s unique genotype and developmental history. This represents the complementary construct of multifinality. Thus, a particular vulnerability factor is not necessarily seen as leading to the same psychopathological outcome in every individual. Finally, unlike traditional disease models, developmental models do not assume discontinuity between dysfunctional behavior and normal behavior, where the former is viewed as being different in kind from normal behavior. Rather, developmental models of psychopathology make no prior assumptions about continuity or discontinuity between normal and pathological behavior (Cicchetti, 2006; Sameroff & Seifer, 1990). Furthermore, there is also no assumption as to whether vulnerabilities should be conceptualized as dichotomous or continuous variables. What clearly distinguishes the models emerging from the field of developmental psychopathology from the earlier diathesis–stress models are emphases on developmental processes and change and on the dynamic interactions between the individual and his or her experiences throughout the lifespan.

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From all appearances, current theory and research on vulnerability to child and adolescent psychopathology are becoming increasingly dominated by a developmental psychopathology perspective. As Garmezy (1991) notes, “Developmental psychopathology and risk research have now become inextricably linked in their common focus on those ontogenetic and environmental processes that influence the longitudinal evolution of adaptive and maladaptive behavior patterns extending from infancy to adulthood” (p. 32). As the developmental psychopathology perspective has become more influential in the study of vulnerability, changes have also occurred in both the methods used to study vulnerability and the direction of the research on vulnerability. These changes are reviewed briefly in the following section.

Research Methodology and Research Trends The 1960s saw the birth of a research tradition that focused on identifying the factors that put individuals at risk for psychopathology, which thus became the formal beginning of research on vulnerability processes. Initially those efforts used cross-sectional designs that focused almost exclusively on the characteristics of adults manifesting a disorder (e.g., schizophrenia). However, as Mednick and McNeil (1968) pointed out in reference to research on schizophrenia, there were serious weaknesses in studying etiological factors in individuals who had already been diagnosed with the disorder. Among the weaknesses cited were inaccurate and distorted retrospective reports, effects of psychiatric care, and, most seriously, the inability to separate the causes from the consequences of the disorder. In response to these shortcomings, Mednick and McNeil (1968) began advocating the use of prospective longitudinal designs to the study of the etiology of psychopathology. They argued that by studying a group of children, many of whom would later develop the disorder, the methodological shortcomings of cross-sectional designs could be avoided. One of the clear advantages of prospective designs is that, because the individuals in the study do not possess symptoms of the disorder, their responses on various measures taken during the course of the investigation, particularly early on, are unlikely to be influenced by features of the disorder or by any treatment. Likewise, the assessments provided by others during the course of development are also less likely to be influenced by manifested features of the disorder or by any expectations that might result from a prior diagnosis of a disorder. Another real advantage of the prospective design is that, because of the temporal sequencing of the assessment of risk factors and the emergence of the disorder, the causes, symptoms, and consequences of the disorder can be more easily separated and identified. Based on these considerations, researchers interested in understanding the etiology of schizophrenia began to examine the children of individuals diagnosed with schizophrenia. Given that children with one diagnosed parent are 10 to 15 times more likely to develop schizophrenia than the offspring of nondiagnosed parents, this represented a particularly high-risk group of



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individuals to study. Over the past 30 years, many researchers have studied samples of these high-risk children to examine the etiology of schizophrenia (e.g., Garmezy, 1974; Mednick & Schulsinger, 1968). To date, a wide range of personal and environmental characteristics of the children of parents diagnosed with schizophrenia has been assessed, resulting in an extensive literature on risk and vulnerability factors for both childhood-onset and later-onset schizophrenia (see Asarnow & Asarnow, 2003, and Compton & Harvey, Chapter 15, this volume, for reviews of this literature). Having proven useful for the study of the origins of schizophrenia, prospective longitudinal designs have been used to understand the etiology of child and adolescent disorders as well. For example, prospective longitudinal designs have been used extensively to understand the etiology of both mood disorders (e.g., NolenHoeksema, Girgu, & Seligman, 1986, 1992) and conduct disorders (see Lansford, Miller-Johnson, & Berlin, 2007; Loeber et al., 1993; Moffitt & Caspi, 2001; Patterson, 1993). Although the more formal and focused study of risk and vulnerability factors emerged from the study of schizophrenia during the 1960s, the use of longitudinal research to study developmental outcomes in children and adolescents actually has its roots in the 1920s. During that era, a number of “growth studies” of children were initiated. Perhaps the most well-known of these studies were conducted at the Institute of Human Development at the University of California, Berkeley (Jones, Bayley, MacFarlane, & Honzik, 1971). The first of these studies, the Guidance Study, was designed to reveal the frequency of behavior and personality problems displayed by a sample of children in therapeutic preschool clinics. As a precursor to the more formal study of risk that emerged several decades later, the aims of this study were to identify the “bioenvironmental” and family factors associated with the presence or absence of specific presenting problems. What began as a 5-year study eventually turned into a series of follow-up studies of the original cohort group when they were 30 and 40 years of age. The second study to have its genesis at the Institute was the Berkeley Growth Study (Jones et al., 1971), which began the same year as the Guidance Study. The major goal of this study was to examine physical, mental, physiological, and motor development during the first 15 months of life among a homogeneous sample of healthy Caucasian infants. However, as with the Guidance Study, a short-term longitudinal study turned into a follow-up investigation of the original cohort group from ages 3–18 and again at 21, 26, and 36 years of age. What began as a study of the growth and development of infants became a study of the linkages between child and adult personality patterns, predictors of adult relationships, and an evaluation of the offspring born to the members of the original cohort. Both of these investigations made early contributions to our understanding of risk for psychopathology and of the methodology that could be used to examine risk and vulnerability. So as not to leave the impression that longitudinal research should always be viewed as the “best” design for studying vulnerability processes, studies

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using cross-sectional designs still have an important place in vulnerability research, especially in the process of identifying potential vulnerability factors. For example, Garber (Chapter 8, this volume) points out how crosssectional methodology has proven fruitful in the identification of vulnerability factors in depression. Using this methodology, groups of individuals who are currently depressed are compared to those who have never been depressed and those who were formerly depressed. A stable vulnerability factor would be expected to be present in both the currently depressed individuals and the formerly depressed individuals. However, if this factor indeed represents some sort of vulnerability to depression, it would be less likely to be evident among the individuals who were never depressed. Over the course of the four decades since the formal study of risk research emerged, a number of changes have also occurred in the focus of risk and vulnerability research. Reflecting the transition from disease models to models based on a developmental psychopathology perspective, research on vulnerability to psychopathology in children and adolescents has shifted from the identification of single vulnerability processes to a more comprehensive analysis of the interaction between multiple vulnerability and protective processes, environmental stressors, and developmental change (e.g., Landsford et al., 2007) . Because the disease models guiding earlier research focused on identifying a single endogenous pathogen within the individual, initial vulnerability research was set up to determine linkages between a single endogenous factor (e.g., attentional deficits) and a specific type of disorder (e.g., schizophrenia). With the emergence of diathesis–stress models, the focus of research began to shift toward attempting to understand the interaction between the diathesis (the vulnerability factor) and stressful life experiences that might trigger the disorder. Theoretical, methodological, and statistical advancements have enabled researchers to investigate multiple vulnerability and protective factors interacting with myriad environmental experiences within the context of developmental change. Another recent trend has been to attempt to understand the nature of vulnerability processes and mechanisms rather than simply identifying a vulnerability factor via a correlational connection between the vulnerability factor and a specific form of psychopathology. Regardless of the form of psychopathology being investigated, researchers are attempting to understand the causal role of the vulnerability processes thought to contribute to the development of the disorder. For example, in this volume, Brennan and Walker (Chapter 14) outline a program of research that has attempted to shed light on how neurological and cognitive vulnerabilities interact with the neurological and hormonal changes of adolescence to contribute to the emergence of schizophrenia in adolescence and early adulthood. Similarly, in their review the literature on the development of substance use disorders, Chassin, Beltran, Lee, Haller, and Villalta (Chapter 5, this volume) describe research related to the deviance proneness model, where attempts have been made to understand the specific role and function of the personality dimensions of



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behavioral dysregulation and undercontrol in the development of substance use disorders. Advances in the study of behavioral and molecular genetics have made it possible for vulnerability research to examine the role of hereditary factors in increasing, or protecting against, vulnerability to psychopathology (Rende & Waldman, 2006). Complementing this research have been efforts to identify endophenotypic markers of vulnerability factors. Gottesman and Gould (2003, p. 636, emphasis added) define endophenotypes as “measureable components unseen by the unaided eye along the pathway between disease and distal genotype.” Endophenotypes represent biological and behavioral markers of latent vulnerabilities for psychopathology that can only be observed by careful measurement. Endophenotypic markers lie along the causal sequence between genotype and phenotype and therefore lie closer to the genetic vulnerabilities of disorders than do psychological processes or behavior (Lenzenweger, 2004). Examples of endophenotypes include peripheral serotonergic abnormalities in relation to emotional regulation in obsessive–compulsive disorder (Delorme et al., 2005) and signal detection indices of inattention and impulsivity in relation to attention-deficit/hyperactivity disorder (Loo et al., 2003). In addition to these trends, advances in statistical methodology allow for emphasis on person-oriented strategies (Bergman, von Eye, & Magnusson, 2006) as well as interpersonal processes (e.g., dyadic interactions) that facilitate an understanding of the links between social experiences and the development of psychopathology (Bukowski, Adams, & Santo, 2006). Some researchers promote ongoing interchanges between developmental theory and quantitative methodology through the use of a variety of trajectory models that can be used for hypotheses in developmental psychopathology (Curran & Willoughby, 2003). As a consequence of the research on vulnerability factors over the past four decades, a wide range of biological and psychological processes have been identified as being vulnerability factors that contribute to the development of child and adolescent psychopathology. Although the specifics on how these vulnerability factors are translated into a specific form of psychopathology are still being addressed, we at least have a starting point for understanding better the vulnerability processes that underlie child and adolescent psychopathology.

Conclusions Over the past four decades, research on vulnerability to child and adolescent disorders has clearly come into its own. New models for conceptualizing vulnerability have emerged, along with methodological approaches used to examine the processes described in these models. Also, as is evident from the chapters in this volume, a wide range of biologically and environmentally

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based vulnerability processes have been found to be linked to the development of psychopathology in children and adolescents. Whereas some vulnerability factors have been linked to specific types of psychopathology (e.g., dopaminergic hyperactivity in schizophrenia), other vulnerability factors have been linked to more than one type of disorder (e.g., attentional deficits). One of the major challenges remaining is uncovering the reasons why certain vulnerability factors may be associated with more than one form of psychopathology. One possibility is that during childhood, particularly early on in development, there may be a lack of differentiation between developmental systems such that vulnerability processes would naturally have an effect on a number of different domains of functioning. Another possibility is that, even though developmental systems will eventually differentiate, these systems are so well integrated that a single vulnerability process within one developmental system, such as deficits in sustained attention, could indeed be related to a variety of forms of psychopathology (attention-deficit/hyperactivity disorder and conduct disorders). Yet another possibility is that our measurement of vulnerability constructs still lacks the precision to detect subtle distinctions between vulnerability factors. For instance, although attention deficits have been found to be associated with several forms of psychopathology, it is possible that more subtle distinguishing forms of attention deficits are associated with different disorders. Relatedly, it is possible that a closer examination of the operational definitions of the same vulnerability process across studies will reveal subtle differences in measurements that reflect differences in the vulnerability processes. Finally, it is possible that the association between a particular vulnerability process with several types of disorders reflects overlap between the nature of the disorders. For example, in the model of anxiety proposed by Chorpita and Barlow (1998), anxiety and depression are hypothesized to lie on the same continuum in terms of perceived personal control. Thus, it should be no surprise to find that the two disorders share some of the same vulnerability processes. These and other challenges remain for those interested in understanding better the vulnerability processes associated with psychopathology during childhood and adolescence. If the progress that has been made over the past four decades is any indication of what can be accomplished over the next four, then we enter the new millennium with a renewed optimism for significantly increasing our understanding of vulnerability to psychopathology during childhood and adolescence.

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Dishion, T. J., & Patterson, G. R. (2006). The development and ecology of antisocial behavior in children and adolescents. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 503–541). New York: Wiley. Dodge, K. A. (1993). Social-cognitive mechanisms in the development of conduct disorder and depression. Annual Review of Psychology, 44, 559–584. Dodge, K. A. (2006). Translational science in action: Hostile attributional style and the development of aggressive behavior problems. Development and Psychopathology, 18, 791–814. Dodge, K. A., Bates, J. E., & Pettit, G. S. (1990). Mechanisms in the cycle of violence. Science, 250, 1678–1683. Dodge, K., & Pettit, G. (2003). A biopsychosocial model of the development of chronic conduct problems in adolescence. Developmental Psychology, 39, 349–371. Dodge, K., Price, J., Bachorowski, J., & Newman, J. (1990). Hostile attributional biases in severely aggressive adolescents. Journal of Abnormal Psychology, 99, 385–392. Dodge, K. A., & Sherrill, M. R. (2007). The interaction of nature and nurture in antisocial behavior. In D. Flannery, A. T. Vazsoni, & I. Waldman (Eds.), The Cambridge handbook of violent behavior and aggression (pp. 215–242). New York: Cambridge University Press. Garmezy, N. (1974). Children at risk: The search for the antecedents of schizophrenia. Part II: Ongoing research programs, issues, and interventions. Schizophrenia Bulletin, 9, 55–125. Garmezy, N. (1991). Longitudinal strategies, causal reasoning and risk research: A commentary. In M. Rutter (Ed.), Studies of psychosocial risk: The power of longitudinal data (pp. 29–44). New York: Cambridge University Press. Gilliom, M., & Shaw, D. S. (2004). Co-development of externalizing and internalizing problems in early childhood. Development and Psychopathology, 16, 313–334. Gottesman, I. I., & Gould, T. D. (2003). The endophenotype concept in psychiatry: Etymology and strategic intentions. American Journal of Psychiatry, 160, 636–645. Hammen, C., & Rudolph, K. D. (2003). Childhood depression. In E. J. Mash & R. A. Barkley (Eds.), Child psychopathology (2nd ed., pp. 233–278). New York: Guilford Press. Ingram, R. E., Miranda, J., & Segal, Z. V. (1998). Cognitive vulnerability to depression. New York: Guilford Press. Jaffee, S. R., Avshalom, C., Moffitt, R., Dodge, K. A., Rutter, M., Taylor, A., et al. (2005). Nature × nurture: Genetic vulnerabilities interact with physical maltreatment to promote conduct problems. Development and Psychopathology, 17, 67–84. Jensen, P. S., Knapp, P., & Mrazek, D. A. (Eds.). (2006). Toward a new diagnostic system for child psychopathology. New York: Guilford Press. Jensen, P. S., & Mrazek, D. A. (2006). Research and clinical perspectives in defining and assessing mental disorders in children and adolescents. In P. S. Jensen, P. Knapp, & D. A. Mrazek (Eds.), Toward a new diagnostic system for child psychopathology (pp. 11–37). New York: Guilford Press. Jones, M. C., Bayley, N., MacFarlane, J. W., & Honzik, M. P. (1971). The course of human development. Waltham, MA: Xerox. Kagan, J., & Snidman, N. (1991). Temperamental factors in human development. American Psychologist, 46, 856–862. Kazdin, A. E., & Weisz, J. R. (Eds.). (2003). Evidence-based psychotherapies for children and adolescents. New York: Guilford Press. Kendall, P. C., & Aschenbrand, S. G., & Hudson, J. L. (2003). In A. Kazdin & J. Weisz (Eds.), Evidence-based psychotherapies for children and adolescents (pp. 81–100). New York: Guilford Press. Kessler, R., Berglund, P., Demler, O., Jin, R., & Walters, E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey replication. Archives of General Psychiatry, 62, 593–602. Knapp, P., & Jensen, P. S. (2006). Recommendations for DSM-V. In P. S. Jensen, P. Knapp, &



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D. A. Mrazek (Eds.), Toward a new diagnostic system for child psychopathology (pp. 162–181). New York: Guilford Press. Landsford, J. E., Malone, P. S., & Dodge, K. A. (2006). A 12–year prospective study of patterns of social information processing problems and externalizing behaviors. Journal of Abnormal Child Psychology, 34, 715–724. Landsford, J. E., Miller-Johnson, S., & Berlin, L. J. (2007). Early physical abuse and later violent delinquency: A prospective longitudinal study. Child Maltreatment, 12, 233–245. Lenzenweger, M. F. (2004). Consideration of the challenges, complications, and pitfalls of taxometric analysis. Journal of Abnormal Psychology, 113, 10–13. Locke, J. (1913). Some thoughts concerning education (§§ 38 & 40). London: Cambridge University Press. (Original work published 1690) Loeber, R., Wung. P., Keenan, K., Girous, B., Stouthamer-Loeber, M., Van Kammen, W. B., et al. (1993). Developmental pathways in disruptive child behavior. Development and Psychopathology, 5, 103–133. Loo, S. L., Specter, E., Smolen, A., Hopfer, C., Teale, P. D., & Reite, M. L. (2003). Functional effects of the DATI polymorphism on EEG measures in ADHD. Journal of American Academy of Child and Adolescent Psychiatry, 42, 986–993. Luthar, S. S. (2006). Resilience in development: A synthesis of research across five decades. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 739–795). New York: Wiley. Mash, E. J., & Dozois, D. J. A. (2003). Child Psychopathology: A developmental-systems perspective. In E. J. Mash & R. A. Barkley (Eds.), Child psychopathology (2nd ed., pp. 3–71). New York: Guilford Press. Masten, A. S., Burt, K. B., & Coatsworth, D. J. (2006). Competence and psychopathology in development. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 696–738). New York: Wiley. McConaughy, S., & Achenbach, T. (1994). Comorbidities of empirically based syndromes in matched general population and clinical samples. Journal of Child Psychology and Psychiatry, 156, 557–563. Mednick, S. A., & McNeil, T. (1968). Current methodology in research on the etiology of schizophrenia. Psychological Bulletin, 70, 681–693. Mednick, S. A., & Schulsinger, F. (1968). Some premorbid characteristics related to breakdown in children with schizophrenic mothers. Journal of Psychiatric Research, 6(Suppl. 1), 354–362. Meehl, P. E. (1962). Schizotaxia, schizotypy, and schizophrenia. American Psychologist, 17, 827–838. Moffitt, T. E. (1993). The neuropsychology of conduct disorder. Development and Psychopathology, 5, 135–151. Moffitt, T. E. (2003). Life-course-persistent and adolescent-limited antisocial behaviour: A 10-year research review and a research agenda. In B. Lahey, T. E. Moffitt, & A. Caspi (Eds.). Causes of conduct disorder and serious juvenile delinquency (pp. 49–75). New York: Guilford Press. Muris, P. (2002). Relationships between self-efficacy and symptoms of anxiety disorders and depression in a normal adolescent sample. Personality and Individual Differences, 32(2), 337–348. Muris, P. (2006). The pathogenesis of childhood anxiety disorders: Considerations from a developmental psychopathology perspective. International Journal of Behavioral Development, 30, 5–11. Muris, P., Meesters, C., & Fijen, P. (2003). The Self-Perception Profile for Children: Further evidence for its factor structure, reliability, and validity. Personality and Individual Differences, 35, 1791–1802. Muris, P., Schouten, E., Meesters, C., & Gijsbers, H. (2003). Contingency-competence-controlrelated beliefs and symptoms of anxiety and depression in a young adolescent sample. Child Psychiatry and Human Development, 33(4), 325–339.

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Chapter 3

The Nature of Adult Vulnerability History and Definitions

Rick E. Ingram and Matthew W. Gallagher

As is evident from the organization of this volume, vulnerability theory and research can, at least for the sake of discussion, be partitioned into vulnerability to psychopathology in childhood and adolescence and vulnerability to psychopathology in adulthood. As previously noted (Ingram & Price, Chapter 1, this volume), such a distinction is in many respects artificial, but it nevertheless serves some important purposes. Perhaps most important, differentiating between child/adolescent and adult psychopathology renders more manageable the task of understanding vulnerability. Indeed, for all but the most extraordinary theorists and researchers, it is difficult to have a firm grasp on the most important vulnerability factors for either adults or children, let alone for both. Moreover, the sheer range and diversity of different forms of psychopathology in both adulthood and childhood/adolescence present formidable challenges for any attempt to adequately understand the factors that predispose to disorders. Partitioning theory and research on child and adult factors thus helps to make theory and research more manageable for both the producers and the consumers of this information. In pursuing this partition, Price and Zwolinski (Chapter 2, this volume) discuss a number of important issues that must be considered in understanding theory and research on childhood vulnerability. The current chapter explores some of the issues that surround conceptualizations of adult vulnerability. A variety of issues dictate that we confine our discussion to a limited number of psychological problems, and we thus start this exploration by briefly noting the disorders that are classified as adult psychopathology. We next address

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why we believe it is important to study vulnerability to disorders in adulthood and suggest three broad reasons that justify this approach. Next, we trace the history of the vulnerability approach to adult psychopathology.

The Disorders of Adulthood: A Brief Summary The number of disorders that exist in various classification schemes, and that are proposed by various schools of thought, is enormous. Deciding which disorders to examine therefore requires making some choices. Although some psychologists concentrate on extremely rare disorders (e.g., Franzini & Grossberg, 1995), the fact that they are so rare suggests that they affect few people, thus rendering discussion of them an inappropriate subject for serious psychology. On the other hand, some relatively rare disorders are quite serious (e.g., dissociative identity disorder), but because systematic empirical research on them is also rare, it is difficult to examine vulnerability factors with any degree of confidence. We will thus limit our discussion in this chapter to the major disorders of adulthood, as recognized by the current edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000) and which have been the subject of empirical research. Although the classification scheme offered by DSM-IV-TR is far from perfect (Ingram, Miranda, & Segal, 1998), it does tend to represent a consensus among researchers on a reasonable way to understand at least the descriptive features of psychopathology. We thus summarize here the descriptive features of several DSM-IV-TR Axis I (clinical syndrome) disorders that (1) are not extremely uncommon, (2) have been the subject of vulnerability theorizing and research, and (3) are not the clear result of organic causes (e.g., Alzheimer’s disease). Axis II disorders (personality disorders), of course, can also be disorders of adulthood, but we will leave an examination of these disorders to Geiger and Crick (Chapter 4, this volume). The disorders we examine make up the vast majority of psychopathological conditions experienced by adults (see Robins & Regier, 1991) and, correspondingly, are the disorders that are examined in more depth in the chapters throughout this volume.

Substance-Related Disorders Substance-related disorders may be the most detailed compilation of disorders that are included in DSM-IV-TR. They include the abuse of numerous substances as well as intoxication resulting from these substances. Intoxicated states are diagnosed as a disorder when they are associated with maladaptive functioning (e.g., cognitive impairment and interpersonal difficulty) that is the result of the ingestion of a psychoactive substance and occur in circumstances associated with significant risk (driving while intoxicated, behaviors that lead to legal problems, etc.). Although a convenient diagnostic category in some instances, substance intoxication generally falls outside the scope of our interest in psychopathology.



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A category that does fall within our view of psychopathology is that of substance abuse disorders. According to DSM-IV-TR, substance abuse disorders are defined as “a maladaptive pattern of substance use manifested by recurrent adverse consequences related to the repeated use of substances” (p. 198). DSM-IV-TR lists several criteria for an overall diagnosis of substance abuse, including (1) chronic use of a substance that results in the failure to fulfill one’s major life obligations; (2) recurrent use in situations that can be hazardous, such as driving; (3) legal problems that result from repeated substance use; and (4) recurrent use that occurs despite the problems caused by the abuse. Any one of these criteria can be sufficient for a diagnosis of substance abuse if it occurs for a period of 12 months. DSM-IV-TR also lists numerous substances whose chronic use can result in a diagnosis. A notable but not exhaustive list includes alcohol, amphetamines, cannabis, cocaine, hallucinogens, opioids, and phencyclidines (PCP). Also included in this list of substances that can form the basis of a disorder is caffeine, a legal and popular drug. For example, according to DSM-IV-TR, for those who ingest caffeine in the form of coffee, tea, soda, cold remedies, or chocolate, the average caffeine intake in the United States is around 200 mg per day (the equivalent of about two brewed cups of coffee, or about 50 oz. of soda). Excessive use of even these legal substances can result in a DSM-IV-TR diagnosis, although this is extremely rare. Each of these has criteria that are specific to the particular substance. Criteria for a diagnosis of alcohol intoxication, for example, include features such as slurred speech, lack of coordination, faulty memory, and attention impairment. On the other hand, cannabis intoxication includes primary features such as motor impairment, euphoria, and impaired judgment and peripheral features such as increased appetite and dry mouth. Continual use of such substances may be associated with a substance abuse diagnosis if this use results in the impairment noted in the general DSM-IV-TR criteria for substance abuse.

Eating Disorders Eating disorders, characterized by a significant disturbance in eating habits, are divided into two more specific disorders: anorexia nervosa and bulimia nervosa. Each of these disorders also has a specific subtype. DSM-IV-TR also includes a category for substance withdrawal, but inasmuch as this also falls outside the scope of our interest in psychological disorders, it is not discussed here.

Anorexia Nervosa DSM-IV-TR criteria suggest that this eating disorder is characterized by the refusal to maintain a minimally normal body weight for the individual’s age and height (i.e., less than 85% of the expected weight). The disorder is also characterized by a significant fear of becoming fat, unrelated to actual weight.

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Correspondingly, anorexia nervosa features a distorted body image in which individuals do not acknowledge the weight deficit. Prevalence rates for this disorder range from 0.5 to 1.0%. Onset typically occurs in late adolescence or early adulthood, with a mean onset of approximately 17 years of age. An enormous gender difference is widely acknowledged, with more than 90% of anorexia diagnoses being assigned to women (American Psychiatric Association, 1994). The disorder carries significant risk for illness and premature death through starvation or electrolyte imbalance. Suicide rates are also high for this disorder. Two specific subtypes of anorexia nervosa are recognized: the binge eating/purging type and the restricted type. The binge eating/purging subtype regularly engages in binge eating and then purges through the use of such methods as induced vomiting or laxative use. In contrast to this subtype, the restricted subtype does not binge eat and purge but, rather, severely restricts food intake (e.g., excessive dieting).

Bulimia Nervosa While anorexia nervosa is characterized by the refusal to maintain a normal weight, the primary features of bulimia nervosa are binge eating a large amount of food, relative to what most individuals would eat within a relatively limited amount of time, and feelings of a lack of control about eating. As with those with anorexia, the individual with bulimia uses an inappropriate way to compensate for the binge eating (e.g., vomiting). Also, as with anorexia, the onset of this disorder occurs in late adolescence or early adulthood and is far more often assigned to women than to men (by about the same 90% figure). This disorder is somewhat more commonly diagnosed than anorexia, with estimates ranging from 1 to 3%. The key difference between bulimia nervosa and anorexia is that individuals with bulimia are able to maintain a body weight at a normal level, or at a minimally normal level. Bulimia nervosa has two subtypes: the purging subtype and the nonpurging subtype. The purging subtype chronically uses inappropriate ways to avoid weight gain such as laxative overuse or self-induced vomiting. The nonpurging subtype compensates for bingeing through such methods as fasting or excessive physical exercise rather than through inappropriate use of laxatives, self-induced vomiting, and so on.

Mood or Affective Disorders The key feature of mood or affective disorders is a disturbance in, naturally enough, mood. Beyond this central feature, mood disorders generally fall into two broad categories: bipolar disorders and unipolar disorder. The key unipolar disorder is major depressive episode, while the key bipolar disorder can be either a depressive episode and a manic episode or the occurrence of a manic episode only. Mood disturbances of a less severe magnitude occur relatively



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frequently in the general population, and at present there is no consensus whether these states represent downward extensions of clinically severe states or fundamentally different phenomena (Ingram & Hamilton, 1999; Tennen, Hall, & Affleck, 1995).

Unipolar Disorder: Major Depressive Episode The core feature of a depressive episode is a minimum 2-week period in which the individual experiences either a significantly depressed mood or, alternatively, a loss of interest or pleasure in virtually all activities. Beyond these core symptoms, DSM-IV-TR specifies that at least four additional symptoms must be experienced. Although a minimum of 2 weeks is specified, untreated major depressive episode can last for up to 2 years (Goodwin & Jamison, 1990). Among the DSM-IV-TR criteria from which these four additional symptoms must be experienced are (1) a significant weight change (either loss or gain), (2) insomnia or hypersomnia, (3) motor retardation or agitation, (4) a continual sense of exhaustion or fatigue, (5) feelings of worthlessness or guilt, (6) cognitive impairment such as concentration difficulties or indecisiveness, and (7) suicidal ideation, a plan for committing suicide, or a suicide attempt. Other features, such as hopeless and negative or distorted information processing, are not included in DSM-IV-TR as specific criteria but are nonetheless widely recognized as characterizing many cases of depression. A first onset of depression can occur at any age but typically occurs in young adulthood. Because many individuals experience numerous depressive episodes over the course of their lifetime, depression is also widely recognized as a chronic disorder (Hammen, 1991; Lavori, Kessler, & Klerman, 1984). Prevalence estimates vary widely and can range from lifetime estimates of 5–20% (Ingram et al., 1998). Suicide rates are high in individuals with a depressive disorder; DSM-IV-TR reports that some 15% of individuals with a major depressive disorder commit suicide, and, even apart from suicide, overall mortality rates in depressed individuals are higher than average. There is a widely recognized gender difference in depression, with approximately twice as many women as men being diagnosed with the disorder. Such gender differences are observed worldwide and are unlikely to be accounted for such an artifact as diagnostic bias (Ingram, Miranda, & Segal, 1998).

Bipolar Disorder In DSM-IV-TR, bipolar disorders are separated into bipolar I and bipolar II types. Bipolar I is characterized by the occurrence of at least one manic episode. The occurrence of a major depressive episode at some point in the person’s life is not required for this diagnosis, but such episodes are nevertheless frequent, and when they have occurred, the disorder is classified as a mixed episode. Bipolar II is defined as the occurrence of at least one major depressive episode and the occurrence of at least one hypomanic (but not manic) episode.

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Like unipolar mood disorder, bipolar disorder usually occurs first in early adulthood and in many cases is chronic. For example, DSM-IV-TR reports that more than 90% of people who have experienced a manic episode will likely experience another episode in the future. Prevalence rates are lower for bipolar disorder than for unipolar disorder. For bipolar I disorder, lifetime prevalence rates range from 0.04 to 1.6%, with the large-scale Epidemiologic Catchment Area (ECA) study (Robins & Regier, 1991) finding a rate of 0.8%. Prevalence rates for bipolar II disorder tend to center around 0.5% (Robins & Regier, 1991). Gender differences are not significant in the incidence of bipolar disorder, unlike the case with major depression although the timing and onset of the disorder may differ somewhat between genders. For example, women are more likely to experience the onset of depression first, while men are more likely to experience a manic episode first (American Psychiatric Association, 1994).

Anxiety Disorders The category of anxiety disorders encompasses a number of specific anxiety states that are considered clinically problematic. For example, panic attacks, panic disorder, agoraphobia with and without panic, social phobia, specific phobia, obsessive–compulsive disorder, posttraumatic stress disorder, acute stress disorder, and generalized anxiety disorder all fall under the more general rubric of anxiety disorders. These specific disorders do not include the residual problems included in virtually all the DSM-IV-TR categories—anxiety disorder not otherwise specified. Rather than discussing each of these specific disorders here, instead we note the central features that characterize, and thus define, a condition as an anxiety disorder. Quite obviously, the core feature of anxiety disorders is anxiety, or fear or apprehensiveness. Although in some cases anxiety manifests itself only in certain situations (e.g., in social situations for social phobia), in other cases the anxiety is quite generalized and seems to pervade most of the individual’s functioning (e.g., generalized anxiety disorder). Although fear and apprehensiveness are the key emotional states involved in anxiety disorders, these disorders are also characterized by cognitive, behavioral, and somatic symptom patterns. Cognitive characteristics of many anxiety states include problems with effective task performance when the person is experiencing anxiety and the possible misinterpretation of situations as dangerous or threatening when the actual danger or threat is either limited or nonexistent. Behaviorally, many anxiety states are characterized by avoidance of perceived threatening situations (e.g., social situations). Somatic features involve physiological changes that occur in anxiety-provoking situations, such as dry mouth, shallow breathing, increased perspiration, and heart palpitations. The various characteristics that occur in the cognitive, behavioral, and somatic domains vary not only across individuals but also across the more specific anxiety disorders.



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Likewise, course, prevalence, and gender differences also vary considerably across the different disorders.

Schizophrenia Like anxiety and depression, the category of schizophrenia includes a number of different conditions and specific schizophrenic states. Unlike anxiety and depression, the defining feature of schizophrenia is psychosis—a condition that is typically defined as involving hallucinations, delusions, and psychological and behavioral disorganization (although not all these symptoms need be present in any given case of schizophrenia). Schizophrenia falls under the DSM-IV-TR category of “schizophrenia and other psychotic disorders.” Some of these other psychotic disorders include delusional disorder (previously labeled “paranoia”), brief psychotic disorder, shared psychotic disorder, and schizoaffective disorder, the last of which is defined as a combination of psychotic and affective features, making it difficult to diagnose as either schizophrenia or an affective (or mood) disorder. Clearly, schizophrenia is the most prevalent of the various psychotic disorders, although its overall prevalence in the general population is quite low in comparison to other psychiatric conditions. DSM-IV-TR estimates lifetime prevalence rates between 0.5 and 1%, whereas the ECA study estimates rates at 1.3% (Keith, Regier, & Rae, 1991). Estimates also vary by gender, with some studies indicating higher rates for males, others suggesting higher rates for females (possibly due to overlap between schizophrenia and mood disorders), and yet others suggesting no gender differences at all. Although it is still unclear whether there are gender differences in schizophrenia, if these differences do exist they are clearly much less pronounced than those seen in other disorders. Despite the lack of a consensus regarding gender differences in the incidence of schizophrenia, there is more of a consensus that gender differences exist during the course of the disorder. For example, the average age of onset of schizophrenia in men is earlier (typically in the early to mid-20s) than it is for women (in the late 20s). The symptom pattern for schizophrenia is quite varied but generally reflects the presentation of negative and positive symptoms. Positive symptoms refer to those reflected in the presence of abnormal behaviors such as hallucinations and delusions; negative symptoms are those that refer to the absence of normal behaviors (e.g., deficits in the expression of affect and speech deficits). Schizophrenia is also characterized by significant interpersonal and occupational dysfunction and, like other disorders, can be a chronic condition, although accurate data tend not to be available because of differences in the definition and assessment of schizophrenia (American Psychiatric Association, 1994). Nevertheless, it is commonly acknowledged that the majority of individuals who are diagnosed with schizophrenia will, if they do not remain continuously afflicted, experience chronic relapses and recurrences.

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Why Study Vulnerability to Disorders in Adulthood? It is unlikely that most of the precursors to psychopathology in adulthood arise solely with the onset of adulthood. Rather, most researchers acknowledge that in many if not most cases these precursors are rooted in experiences encountered early in life. The range of such early experiences is quite diverse. For example, such experiences can include a variety of prenatal insults, as has been suggested by some schizophrenia researchers (e.g., Zubin & Spring, 1977). Postnatal insults, such as those arising from obstetrical complications, can also occur and may produce vulnerability. And in many cases, especially those in which dysfunctional learning is involved, the development of vulnerability factors can occur throughout the childhood years. Why, then, focus on vulnerability in adulthood? We believe that there are several reasons why such a focus is both warranted and important.

Some Vulnerability Factors May Develop in Adulthood Although most vulnerability factors arise before adulthood, some of these processes do in fact occur during adulthood. For example, if we posit (from a psychopathological standpoint) that learning experiences can serve as the basis for vulnerability to psychopathology, then we cannot rule out that some of these learning experiences take place in adulthood. Take the example of anxiety states. Even though the root of many of these disorders is found in childhood or adolescent experiences, sufficient exposure to inescapable aversive circumstances as an adult should, in principle, also elicit the development of anxiety. In the case of posttraumatic stress disorder (PTSD), for instance, although it is known that some processes that appear in childhood (e.g., neuroticism) are linked to vulnerability to this disorder in adulthood (see Reese, Najmi, & McNally, Chapter 12, this volume), repeated exposure to traumatic events as an adult (e.g., rape experienced in prison or in wartime raids) may be sufficient to create lasting vulnerability to a variety of disorders that differ from the adulthood onset of PTSD (e.g., phobic states and depression may also develop). Hence, vulnerability to several disorders may be created by horrific experiences encountered as an adult. Although it is undoubtedly true that vulnerability to many psychopathological states arises prior to adulthood, in some cases vulnerability processes may indeed first appear in adulthood and thus justify both theoretical and empirical attention.

Factors That Actualize Vulnerability Occur in Adulthood Although the vulnerability roots of adult psychopathology may not develop in adulthood, an extremely important reason to examine vulnerability factors in adulthood is the activation or actualization of vulnerability factors that



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initiates the onset of adult psychopathology. As noted by Ingram et al. (1998) and Ingram and Price (Chapter 1, this volume), vulnerability variables are typically seen as stable traits. Psychological disorders, on the other hand, are considered to be states—that is, conditions that occur and then, in most cases, either disappear or enter at least a temporary state of remission. These trait and state distinctions underscore the fact that most vulnerability models are explicitly diathesis–stress models—models that locate the genesis of psychopathology in the combination of vulnerability traits and life stress. Thus, even though the vulnerability factors for a given disorder may have developed prior to adulthood, the variables that initiate the realization of these vulnerability traits into a psychopathological state (typically aversive life events) occur during adulthood. Indeed, the onset of all adult disorders is arguably a function of these triggering events, certainly according to those models that embrace a diathesis–stress approach. Understanding when, how, and why stress interacts with latent vulnerability factors to produce an active psychopathological state in adulthood is thus an extremely important goal for researchers.

Modification of Vulnerability Factors Can Occur in Adulthood It is possible to view vulnerability factors as static, unchanging, and unchangeable, and in some cases of vulnerability this may be an accurate conceptualization. For example, Zubin and Spring (1977) are clear about the impermeable nature of vulnerability: “We regard [vulnerability] as a relatively permanent, enduring trait” (p. 109). Such assumptions of permanence are likely rooted in the genetic level of analysis employed by researchers who examine such disorders as schizophrenia and the like (e.g., McGue & Gottesman, 1989; Nicholson & Neufeld, 1992) and clearly argue for a relatively static view of vulnerability mechanisms. Although these perspectives suggest that vulnerability mechanisms may not be modifiable, they do not necessarily posit that functional vulnerability levels cannot be attenuated by processes that affect neurochemistry. For instance, pharmacological agents such as lithium carbonate may alter the likelihood of developing the symptoms of a bipolar episode by presumably controlling the underlying neurochemistry of the vulnerability. Similar diminishment of functional vulnerability may be seen in the actions of psychopharmacological treatments for depression with medications such as selective serotonin reuptake inhibitors or the various generations of tricyclic agents. However, even though functional vulnerability may be altered and individuals are less likely to develop the disorder while on medication, the vulnerability persists; in the case of all the pharmacological agents we have mentioned, increased risk returns once the medication is discontinued (Hollon, 1999). Thus, even though the emergent vulnerability may be controlled, the vulnerability process itself remains.

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In other cases, vulnerability processes that arise before adulthood may in fact become modified during adulthood. For instance, changes may reflect variables that intensify the vulnerability. To illustrate, in the area of mood disorders, Post (1992, 2007) proposed a process he labeled kindling. Kindling is thought to be a neuronal process that intensifies vulnerability to affective disorders. In brief, Post suggests that each episode of an affective disorder leaves a residual neuronal trace. As these neurobiological traces become more distinct, they lead to the development of pathways by which increasingly minimal stress becomes sufficient to activate the affective mechanisms that result in the onset of a disorder. In the most extreme cases, disorder onsets become autonomous from the external triggering mechanisms that are acknowledged to occur in most disorders. From a somewhat different level of analysis, Segal, Williams, Teasdale, and Gemar (1996) argue that kindling may be associated with the likelihood that dysfunctional cognitive patterns are activated with increasingly minimal stimulation (e.g., aversive life events). Regardless of whether this process is viewed from a neurobiological or cognitive level of analysis, kindling intensifies the adult vulnerability processes that may have developed at an earlier time in life and thus serves to alter vulnerability levels. Changes in vulnerability processes do not always have to be in a negative direction; a lessening of vulnerability may also be possible. Whether or not a model specifies that decreases in vulnerability are possible depends on the disorder in question (e.g., schizophrenia as conceptualized by Zubin & Spring, 1977) and the level of vulnerability analysis (e.g., learning-based vs. neurobiological). For instance, psychological approaches typically rely on assumptions of maladaptive learning as the basis of vulnerability (Ingram et al., 1998). Given these learning assumptions, vulnerability may be affected by new learning experiences. The most obvious example of a new learning experience is that of psychotherapy, which in most cases is intended not only to treat the symptoms of a disorder but also to alter the underlying vulnerability. In addition, naturally occurring “corrective” learning experiences may also affect vulnerability. Although it is unlikely that new learning experiences will totally ameliorate vulnerability (see Mahoney, 2000), these conceptualizations nevertheless suggest that some modification of vulnerability is possible and, by extension, that vulnerability having its genesis in childhood or adolescence may be altered in adulthood. In sum, even though vulnerability to adulthood disorders may arise before adulthood, several circumstances suggest the importance of studying vulnerability in adulthood. These circumstances reflect the fact that some vulnerability processes do arise in adulthood, that the factors that actualize vulnerability to psychopathology occur in adulthood, and that vulnerability processes may be modified (both functionally and dysfunctionally) in adulthood. To fully appreciate the implications of these circumstances, it is helpful to understand the historical context for the study of vulnerability, a topic to which we now turn.



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A Brief History of Vulnerability Theory and Research Virtually all theories of psychopathology at least implicitly encompass notions of vulnerability. The history of vulnerability perspectives on adult psychopathology therefore depends to a large extent on the time frame one wants to cover. For example, as any abnormal psychology textbook tells us, many historical conceptualizations of psychopathology evidence the belief that individuals were possessed by demons and were presumably vulnerable to such possession by virtue of adopting immoral, or nonreligious, lifestyles. Somewhat more recent, and scientifically credible, origins of adult vulnerability theory can be seen in the work of the earliest psychiatrists. We refer most centrally to Freud, whose theory of trauma and fixation is every bit a vulnerability theory. Likewise, neo-Freudians such as Alder, who located vulnerability to psychopathology in fears of inferiority, also propose what can be considered to be theories of vulnerability. Our focus, however, is on the more contemporary origins of current vulnerability perspectives.

The Advent of Contemporary Approaches to Vulnerability Despite the various theories that imply vulnerability processes, explicit (and somewhat more contemporary) ideas of vulnerability as an explanatory concept for adult psychopathology most likely have their conceptual origins in theorizing about schizophrenia. In a classic paper, Meehl (1962) was probably the first to allude to a psychogenic vulnerability to schizophrenia when he proposed that the disorder is the result of a neural deficit (“schizotaxia”) that is combined with the individual’s learning history. Meehl (1962) referred to this as schizotypia and suggested that the confluence of these variables resulted in vulnerability to schizophrenia. Meehl also hypothesized, however, that schizotypia, although necessary for the development of schizophrenia, was not sufficient in and of itself for the development of schizophrenia. Rather, Meehl suggested that only certain schizotypic individuals would eventually develop clinical schizophrenia. Specifically, these were the individuals who were reared by a schizophrenogenic mother who would provide a developmental climate of ambivalent, unpredictable, and aversive mother–child interactions: “It seems likely that the most important causal influence pushing the schizotype toward schizophrenic decompensation is the schizophrenogenic mother” (p. 830). Meehl’s (1962) theory therefore argued that the onset of schizophrenia was a joint function of both biological (genetically determined schizotaxia) and psychological factors (e.g., the individual’s learning history and disturbed mother–child interactions). Despite the focus on childhood factors, which as we have noted underlie many approaches to adult psychopathology, Meehl’s theory represents, we believe, the inauguration of the vulnerability approach to understanding psychopathology in adults. The empirical origins of the vulnerability approach are again linked to

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schizophrenia and appear traceable to work reported by Kety, Rosenthal, Wender, and Schulsinger (1968), Mednick and Schulsinger (1968), and Rosenthal et al. (1968). Although interested in schizophrenia in adulthood, this work examined a variety of variables in the children of a parent (or parents) with a diagnosis of schizophrenia, with the idea that these variables may predict the eventual onset of schizophrenia in these children. To examine such individuals, these researchers used extensive registers in Denmark known as the National Psychiatric Register and the Folkeregister. The National Psychiatric Register documents all psychiatric hospitalizations in Denmark, while the Folkeregister contains the addresses of virtually all Danish residents. Using these databases, Mednick and Schulsinger (1968) located a sample of 207 children of schizophrenic mothers and a control group of more than 100 children whose mothers did not show evidence of psychopathology. These offspring were then tested on a number of variables and were followed longitudinally over time. The historical antecedents for disorders other than schizophrenia vary according to a number of factors. In the area of depression, for example, Beck (1967) was undoubtedly the first to articulate a cognitive theory of affective disorder and suggested that vulnerability to adult depression developed in childhood. In particular, he argued that problematic situations in childhood serve as the basis for the development of cognitive structures that place individuals at later risk. In childhood and adolescence, the depression-prone individual becomes sensitized to certain types of life situations. The traumatic situations initially responsible for embedding or reinforcing the negative attitudes that constitute the depressive constellation are the prototypes of the specific stresses that may later activate these constellations. When a person is subjected to situations reminiscent of the original situations, he may then become depressed (p. 278). Beck’s ideas clearly represent a vulnerability hypothesis that focuses on both vulnerability mechanisms and on how and under what circumstances these mechanisms developed and were later activated. Although the vulnerability approach had its earliest origins in schizophrenia, Beck’s theory appears to have developed independently of this vulnerability theory and research, as most likely did most of the vulnerability ideas discussed in the various chapters in this volume. More recently, researchers have begun to explore how genetic factors interact with cognitive and environmental factors to result in vulnerability to psychopathology. A diminished sense of control has been proposed to interact with genetically determined traits such as neuroticism to predict the development of anxiety disorders (Barlow, 2002). Similarly, recent work has demonstrated that a stressful early family environment interacts with the short allele of the serotonin-transported gene-linked polymorphic region (5-HTTLPR) to predict depressive symptoms (e.g., Taylor et al., 2006). Although preliminary, genetic–environmental interactions are a promising area for future vulnerability research. As this brief review demonstrates, the history of vulnerability theory



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and research in adult psychopathology is fairly short. Discounting the notion of possession by evil spirits, contemporary perspectives on vulnerability can probably be traced to Meehl’s (1962) pioneering work on schizophrenia and to some extent to Zubin and Spring’s (1977) suggestions that the only way to truly understand the development of schizophrenia itself is through understanding the processes that lead to the development of vulnerability factors. Although these perspectives originated with the study of schizophrenia, they nevertheless represent important influences on the study of vulnerability to a variety of disorders.

Conclusions: What Does the Future Hold for Adult Vulnerability Perspectives? Despite the reality that most vulnerability factors develop in childhood or adolescence, children and adolescents grow up to be adults. Hence, the history of the examination of vulnerability in adult psychopathology gives few indications of slowing down. This is due in large part to the three reasons we noted earlier. First, because some vulnerability factors may in fact develop in adulthood, it is important to continue to examine when and how these factors develop. Second, vulnerability to adult psychopathology will continue to be important because vulnerability factors for disorders that occur in adulthood, even if developed in childhood or adolescence, are actualized in adulthood. This perspective is captured most clearly in diathesis–stress models that focus on the interactive effects of stressful events and endogenous mechanisms (whether psychological or physiological), which together produce vulnerability. And third, vulnerability factors may be modified in adulthood. As we noted, sometimes vulnerability increases in adulthood, while in other cases, depending on the origins of the vulnerability, these factors may decrease in adulthood. Although there are numerous possible future directions for adult vulnerability theorizing and research, we end this chapter with a comment about one possible future direction. Ingram and Price (Chapter 1, this volume) suggested that the line between childhood/adolescence and adulthood can be difficult to find. From a conceptual standpoint it would be helpful if the line did not exist at all. That is, to truly understand vulnerability, theorists and researchers need to adopt a lifespan perspective. For childhood and adolescence researchers this means realizing that children and adolescents eventually become adults, and thus vulnerability factors, although developed in childhood or adolescence, may nevertheless affect individuals for a lifetime. Understanding the long-term trajectory of these vulnerability factors and their consequences is thus an extremely important quest. It will therefore be important for future vulnerability research to use appropriate longitudinal methods (Riskind & Alloy, 2006) and statistical analysis (Hertzog & Nesselroade, 2003) that permit the modeling of the trajectories of mental illness.

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From the adult psychopathologist’s perspective this means recognizing that adults were once children. Adult researchers tend to confine their investigations to variables that occur after childhood and adolescence, but it is becoming increasingly clear that in order to understand adult vulnerability we must begin with understanding children and adolescents. This dual recognition—that functioning continues after childhood and that adult processes must be understood in terms of earlier processes—suggests that vulnerability must be understood across the lifespan. With rare exceptions, this situation does not currently exist, as can be seen in the overarching organization of chapters within this volume. Nevertheless, only a lifespan perspective will move us closer to understanding the vulnerability processes that are linked to the devastating consequences of psychopathology in children and adults alike.

References 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. Barlow, D. H. (2002). Anxiety and its disorders: The nature and treatment of anxiety and panic (2nd ed.). New York: Guilford Press. Beck, A. T. (1967). Depression: Causes and treatment. Philadelphia: University of Pennsylvania Press. Franzini, L., & Grossberg, J. (1995). Eccentric and bizarre behaviors. New York: Wiley. Goodwin, F. K., & Jamison, K. R. (1990). Manic–depressive illness. New York: Oxford University Press. Hammen, C. (1991). Depression runs in families: The social context of risk and resilience in children of depressed mothers. New York: Springer-Verlag. Hertzog, C., & Nesselroade, J. R. (2003). Assessing psychological change in adulthood: An overview of methodological issues. Psychology and Aging, 18, 639–657. Hollon, S. D. (1999). Psychotherapy and pharmacotherapy: Efficacy, generalizability, and costeffectiveness. In N. E. Miller & K. M. Magruder, (Eds.), Cost-effectiveness of psychotherapy: A guide for practitioners, researchers, and policymakers (pp. 14–26). New York: Oxford University Press. Ingram, R. E., & Hamilton, N. A. (1999). Evaluating precision in the social psychological assessment of depression: Methodological considerations, issues, and recommendations. Journal of Social and Clinical Psychology, 18, 160–180. Ingram, R. E., Miranda, J., & Segal, Z. V. (1998). Cognitive vulnerability to depression. New York: Guilford Press. Keith, S. J., Regier, D. A., & Rae, D. S. (1991). Schizophrenia disorders. In L. N. Robins & D. A. Regier (Eds.), Psychiatric disorders in America: The Epidemiologic Catchment Area study (pp. 33–52). New York: Free Press. 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. In D. Rosenthal & S. S. Kety (Eds.), Transmission of schizophrenia (pp. 14–23). Oxford: Pergamon Press. Lavori, P. E., Kessler, M. B., & Klerman, G. L. (1984). Relapse in affective disorder: A reanalysis of the literature using life table methods. Journal of Psychiatric Research, 18, 13–25. Mahoney, M. J. (2000). A changing history of efforts to understand and control change: The



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case of psychotherapy. In C. R. Snyder & R. E. Ingram (Eds.), Handbook of psychological change: Psychotherapy processes and practices for the 21st century (pp. 2–18). New York: Wiley. McGue, M., & Gottesman, I. I. (1989). Genetic linkage in schizophrenia: Perspectives from genetic epidemiology. Schizophrenia Bulletin, 15, 453–464. Mednick, S. A., & Schulsinger, F. (1968). Some premorbid characteristics related to breakdown in children of with schizophrenic mothers. In D. Rosenthal & S. S. Kety (Eds.), Transmission of schizophrenia (pp. 41–57). Oxford: Pergamon. Meehl, P. E. (1962). Schizotaxia, schizotypy, schizophrenia. American Psychologist, 17, 827– 838. Nicholson, I. R., & Neufeld, R. W. J. (1992). A dynamic vulnerability perspective on stress and schizophrenia. American Journal of Orthopsychiatry, 62, 117–130. Post, R. M. (1992). Transduction of psychosocial stress into the neurobiology of affective disorder. American Journal of Psychiatry, 149, 999–1010. Post, R. M. (2007). Kindling and sensitization as models for affective recurrence, cyclicity, and tolerance phenomena. Neuroscience and Biobehavioral Review, 31, 851–873. Riskind, J. H., & Alloy, L. B. (2006). Cognitive vulnerability to psychological disorders: Overview of theory, design, and methods. Journal of Social and Clinical Psychology, 25, 705– 725. Robins, L. N., & Regier, D. A. (Eds.). (1991). Psychiatric disorders in America: The Epidemiologic Catchment Area study. New York: Free Press. Rosenthal, D., Wender, P. H., Kety, S. S., Schulsinger, F., Welner, J., & Ostergaard, L. (1968). Schizophrenics’ offspring reared in adoptive homes. In D. Rosenthal & S. S. Kety (Eds.), Transmission of schizophrenia (pp. 97–113). Oxford: Pergamon. Segal, Z. V., Williams, J. M., Teasdale, J. D., & Gemar, M. (1996). A cognitive science perspective on kindling and episode sensitization in recurrent affective disorder. Psychological Medicine, 26, 371–380. Taylor, S. E., Way, B. M., Welch, W. T., Hilmert, C. J., Lehman, B. J., & Eisenberger, N. I. (2006). Early family environment, current adversity, the serotonin transporter polymorphism, and depressive symptomatology. Biological Psychiatry, 60, 671–676. Tennen, H., Hall, J. A., & Affleck, G. (1995). Depression research methodologies in the Journal of Personality and Social Psychology: A review and critique. Journal of Personality and Social Psychology, 68, 870–884. Zubin, J., & Spring, B. (1977). Vulnerability: A new view of schizophrenia. Journal of Abnormal Psychology, 86, 103–126.

Part II

Personality Disorders

Chapter 4

Developmental Pathways to Personality Disorders Tasha C. Geiger and Nicki R. Crick

The dynamic and interactive process characterizing the unfolding of an individual’s personality—from newborn temperament, to the molding and shaping role of the early caregiving context, to the formation of new relationships with peers and teachers, to the development of attitudes, expectations of the motives of others, and ideas of self-potency—captivates the interest of developmental researchers and lay persons alike. How this normative process goes awry, resulting in a pervasive maladaptive pattern of interacting with others, is of utmost concern to clinicians who are charged with the task of helping these individuals adopt alternative ways of interacting with others, thus decreasing the harm they often inflict on themselves and others, the toll they can place on society and mental health resources, as well as the likelihood of maintaining the same difficulties in the next generation. Unfortunately, the study of personality disorders has been plagued by a number of difficulties. Numerous researchers have noted a number of difficulties with the current conceptualization and classification of personality disorders. These difficulties include the low reliability of personality disorder assessment, allowance for highly variable presentations of the same disorder, and limited support for the existence of clearly distinguishable types of personality disorders. Further, the current diagnostic system has been criticized for not including all aspects and types of personality pathology. In addition, there is also limited empirical evidence for a clear demarcation between normal and abnormal personality processes as well as an inadequate research base for several of the personality disorders (see Widiger, 2007). The difficulty in locating empirical research on the developmental precursors of such pathology may be one consequence of these systemic problems. In the mid-1990s, Millon and Davis (1995) com

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mented on the paucity of comprehensive prospective research on childhood risk for personality disorders despite extensive theories and clinical descriptions of personality pathology. Over a decade later, researchers continue to note the prominent lack of “a systematic study devoted to an understanding of the etiology, pathology, family history, or treatment of the histrionic, schizoid, paranoid, obsessive–compulsive, and other personality disorders despite the provision over 20 years ago of research diagnostic criteria within DSMIII” (Widiger, 2007, p. 25–26). Fortunately, some researchers are beginning to tackle these challenges in a comprehensive manner (e.g., Lenzenweger & Cicchetti, 2005). Despite these difficulties, the personality disorders especially lend themselves to examination according to developmental theory because personality is hypothesized to begin forming early in life—substrates of which are thought to be present even at birth (Hartup & van Lieshout, 1995). Our goal for this chapter is to examine possible childhood precursors to adult personality disorders. Although sparse, longitudinal research has indicated that behavioral characteristics associated with adult personality disorders can be observed in childhood (Bernstein, Cohen, Skodol, Bezirganian, & Brook, 1996; Rey, Morris-Yates, Singh, Andrews, & Stewart, 1995). These studies are limited, however, by the fact that the diagnoses were obtained during adolescence, a developmental period often marked by deviant behavior (Moffitt, 1993), increased stress, and emotional lability (Arnett, 1999). Such a pattern of adolescent behavior may result in a false inflation in the prevalence rate of personality disorders for that population. For example, one study found that, of the adolescents who were diagnosed with a personality disorder according to the revised third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R; American Psychiatric Association, 1987), less than half of them retained the diagnosis at a 2-year follow-up (Bernstein et al., 1993). Although some authors have methodologically addressed the instability of diagnoses during this transition period (e.g., Bernstein et al., 1996), it is not clear whether these adolescents would go on to obtain a personality disorder diagnosis during adulthood. The relative instability of personality disorder diagnoses from early adolescence to late adolescence or young adulthood has been acknowledged in both clinical (Mattanah, Becker, Levy, Edell, & McGlashan, 1995) and nonclinical samples (Korenblum, Marton, Golombek, & Stein, 1990). Given the limitations of the current personality disorder diagnostic system as delineated in the text revision of the fourth edition of the DSM (DSM-IVTR; American Psychiatric Association, 2000), and given the limited research on childhood precursors of personality pathology, we are approaching the examination of childhood vulnerability to personality disorder in two ways. First, we have chosen to address common themes that cut across diagnostic categories. For example, rather than focusing on precursors to paranoid personality disorder, we identify possible antecedents to core aspects of the disorder, such as a “hostile, paranoid world view,” a broader concept descriptive

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of not only paranoid personality disorder but schizotypal and borderline personality disorder as well. A similar approach has been used by Costello (1996) to describe personality characteristics of adults with personality disorders. Second, we have elected to explore childhood vulnerability to personality disorder by adopting a developmental psychopathology perspective. This two-pronged approach was taken for three reasons. First, this framework represents an attempt to address the inadequacy of the current diagnostic system (e.g., lack of discriminant validity). A review of the literature seems to indicate that researchers, although not explicitly acknowledging the difficulties of conducting research with the current personality disorder taxonomy use methods or data reduction techniques that compensate for the inadequacy of this classification system. For example, researchers have chosen to assess dimensions of personality pathology instead of, or in addition to, using the categorical approach of the DSM (e.g., Daley et al., 1999; Gibb, Wheeler, Alloy, & Abramson, 2001; Krischer, Sevecke, Lehmkuhl, & Pukrop, 2007; Lewinsohn, Rohde, Seeley, & Klein, 1997). Other researchers find it necessary to combine the personality disorders into clusters, groupings based on the personality clusters in the DSM (e.g., Bernstein et al., 1996; Crawford, Cohen, & Brook, 2001) or newly created groupings (e.g., Korenblum et al., 1990). Still others have resorted to combining all the personality disorder symptoms into one summary variable in order to locate predictors of personality pathology (e.g., Cohen, 1996). Thus, the approach taken in this chapter is an attempt to take into account the difficulties encountered in research concerned with the distinctiveness of the individual personality disorders and their precursors. Second, by not relying on the relatively nondevelopmental criteria of the DSM categories (e.g., Sroufe, Egeland, Carlson, & Collins, 2005) but rather by describing behavior relevant to a particular developmental stage, this approach may help to address some of the difficulties of assessing features of personality disorders during adolescence. Third, these common themes more readily map themselves onto skills and competencies addressed in the developmental psychology literature. When the diagnostic system is “abandoned” and common themes are considered, the result is often a dimensional system (van Praag, 1996, p. 131). Therefore, many of the themes listed here describe dimensions or continua of behaviors and characteristics, with an excess of one quality as one endpoint and a lack of that quality as the other endpoint (e.g., “intense, unstable, inappropriate emotion” to “constricted, flat affect”; see Table 4.1 for a list of the core behavioral areas to be discussed and the DSMIV-TR diagnostic criteria hypothesized to constitute each area). Thus, we adopt a developmental psychopathology model to examine how cognitive, behavioral, physiological, representational, and emotional systems may evolve over time, laying the foundation for features of maladaptive personality functioning in adulthood. It is important, therefore, to start with a description of some of the fundamental principles of developmental psychopathology. One guiding principle maintains that the study of normative behavior is essential to understanding deviant development (Cicchetti & Cohen, 1995).

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TABLE 4.1. A Developmental Approach to the Identification of Child and Adolescent Features of Personality Disorders Personality feature

Personality disorder Example DSM-IV-TR symptom

1.    Hostile, paranoid world view

PPD

Suspects, without sufficient basis, that others are exploiting, harming, or deceiving him or her

STPD

Suspiciousness or paranoid ideation

BPD

Transient, stress-related paranoid ideation or severe dissociative symptoms

2a.  Intense, BPD unstable, HPD inappropriate emotion

Affective instability due to a marked reactivity of mood

2b.  Restricted, flat affect

SZPD

Shows emotional coldness, detachment, or flattened affectivity

STPD

Inappropriate or constricted affect

APD

Impulsivity or failure to plan ahead

BPD

Impulsivity in at least two areas that are potentially selfdamaging (e.g., spending, sex, substance abuse)

OCPD

Shows perfectionism that interferes with task completion

AVPD

Is unusually reluctant to take personal risks or to engage in any new activities because they may prove embarrassing

BPD

A pattern of unstable or intense interpersonal relationships characterized by alternating between extremes of idealization and devaluation

HPD

Considers relationships to be more intimate than they actually are

DPD

Goes to excessive lengths to obtain nurturance and support from others, to the point of volunteering to do things that are unpleasant

OCPD

Is excessively devoted to work and productivity to the exclusion of leisure activities and friendships (not accounted for by obvious economic necessity)

PPD

Is reluctant to confide in others because of unwarranted fear that the information will be used maliciously against him or her

SZPD

Neither desires nor enjoys close relationships, including being part of a family

STPD

Lack of close friends or confidants other than firstdegree relatives

AVPD

Avoids occupational activities that involve significant interpersonal contact, because of fears of criticism, disapproval, or rejection

3a.  Impulsivity

3b.  Rigidity

4a.  Overly concerned with relationships

4b.  Avoids relationships

Displays rapidly shifting and shallow expression of emotions

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TABLE 4.1.  (continued) 5a.  Negative sense of self

NPD

Is often envious of others or believes that others are envious of him or her

AVPD

Views self as socially inept, personally unappealing, or inferior to others

DPD

Has difficulty initiating projects or doing things on his or her own (because of a lack of self-confidence in judgment or abilities rather than a lack of motivation or energy)

5b.  Lack of sense BPD of self

Identity disturbance: markedly and persistently unstable self-image or sense of self

5c.  Exaggerated sense of self

HPD

Is uncomfortable in situations in which he or she is not the center of attention

NPD

Has a grandiose sense of self-importance

6.    Peculiar STPD thought processes and behaviors

Behavior or appearance that is odd, eccentric, or peculiar

7.     Lack of APD concern for social norms and the needs NPD of others

Lack of remorse, as indicated by being indifferent to or rationalizing having hurt, mistreated, or stolen from another Lacks empathy: is unwilling to recognize or identify with the feelings and needs of others

Note. Reprinted with permission from the Diagnostic and Statistical Manual of Mental Disorders, Text Revision, Fourth Edition (copyright 2000). American Psychiatric Association. Abbreviations: PPD, paranoid personality disorder; SZPD, schizoid personality disorder; STPD, schizotypal personality disorder; APD, antisocial personality disorder; BPD, borderline personality disorder; HPD, histrionic personality disorder; NPD, narcissistic personality disorder; AVPD, avoidant personality disorder; DPD, dependent personality disorder; OCPD, obsessive–compulsive personality disorder.

One criticism of the classification system of personality disorders in the DSM is its lack of differentiation between normal personality and pathological personality processes (Widiger, 2007). Therefore, we often describe normal developmental processes before presenting deviations from this typical pattern that may be implicated as precursors to pathology. The developmental psychopathology model also embraces an organizational perspective in which attention is paid to cognitive, biological, social, and emotional processes and how these systems become integrated over time. More recently, additional emphasis has been placed on the interplay between brain development and social and environmental risk in the development of maladaptive outcomes generally (e.g., Cicchetti & Curtis, 2005, 2006) as well as specific personality disorders (Brendel, Stern, & Silbersweig, 2005; Minzenberg, Poole, & Vinogradov, 2005). Therefore, we include a discussion of vulnerability processes that may be implicated within each of these domains. Another important feature of the developmental psychopathology per-

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spective is a focus on a pattern of adaptation to significant tasks or requirements appropriate for a particular age group (Cicchetti & Cohen, 1995). For example, during infancy, an important task is the formation of an attachment relationship with the caregiver (Sroufe & Waters, 1977), whereas during middle childhood important accomplishments may include successful negotiation of peer relationships, academic endeavors, and appropriate behavior and conduct (Masten & Coatsworth, 1998). Throughout this chapter, we examine different developmental periods, and failure to deal effectively with pertinent developmental tasks is discussed as a possible indicator of future psychopathology. An additional aspect of the developmental psychopathology model is that pathways of development are emphasized such that the pattern of adaptation (both successful and maladaptive) to developmental tasks is examined over time. Thus, individuals confront future situations and challenges with the cognitive, social, biological, and emotional resources, skills, and knowledge they gained through their early negotiations with important developmental tasks (Sroufe et al., 2005). For example, an individual who was not successful at maintaining adequate relationships with peers during childhood may lack a solid foundation for the development of later positive, fulfilling adult friendships and romantic relationships (Masten et al., 1995). Failure at these important developmental tasks does not necessarily signify pathology but, rather, serves as an indicator that an individual may be on a deviant pathway and perhaps at an increased risk for further maladaptive behavior. The longer an individual remains on this deviant pathway, the more difficult it may be to return to a normal, typical developmental progression. Change, however, is still possible, but given the organizational structure of development, this change is constrained by the individual’s previous history and current circumstances (Sroufe, 1997). Within this focus on the organizational structure of development, such that the cognitive, emotional, biological, and social systems become integrated over time as the individual adapts to the environment and various experiences, it is possible to study the coherence of development. Coherence implies that there is a logical progression to this development. Emphasis, therefore, is not necessarily on the particular form of a behavior but, rather, on the function or meaning of a behavior and how it may change over time. Therefore, behaviors that are similar in appearance may have different meanings at different ages (Sroufe, 1997; Sroufe & Rutter, 1984). Coherence has two implications for this chapter. First, behaviors are examined for their appropriateness to a particular age group. Second, childhood behaviors are examined that are meaningfully related (but not necessarily phenotypically similar) to adult symptoms of personality disorder. In sum, this chapter illustrates how common concepts in developmental psychology that have functional or symptomatic similarity to features of personality disorders may represent vulnerabilities or liabilities that predispose children to developing a personality disorder in adulthood. However, given

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the paucity of empirical research on the antecedents of personality disorders, the developmental processes we select for discussion are not meant to provide a comprehensive review of the potential precursors of personality disorders. Rather, the concepts are chosen because a wide research base supports their validity in developmental psychology and because these concepts possess a conceptual or functional similarity linking them with the symptomatic picture of respective personality disorders of adulthood. We attempt to address vulnerability in several domains, including cognition, behavior, biology, emotion, and social interaction, and also to discuss vulnerability processes that may be occurring during infancy, childhood, and adolescence. Currently, the link between these processes and the development of a personality disorder is only speculative, but we hope they will serve as a springboard for future research endeavors. In keeping with the aims for this volume, we provide an overview of research on the assessment and stability of personality disorders before discussing childhood precursors of these disorders.

Assessment and Stability of Personality Disorders In their review, Mattia and Zimmerman (2001) found that the median prevalence estimate of any personality disorder among adults is quite high, specifically, 12.9%—a finding that likely contributes to the controversy surrounding personality disorder diagnosis (Fowler, O’Donohue, & Lilienfeld, 2007). The prevalence rate, however, varied for each specific personality disorder diagnosis. Narcissistic (0.2%) and schizoid personality disorder (0.6%) were the least common, and obsessive–compulsive personality disorder was the most prevalent (4%). Further contributing to the challenges of personality assessment, diagnostic decisions are likely influenced by gender bias. Whereas antisocial, narcissistic, obsessive–compulsive, schizoid, schizotypal, and paranoid personality disorders are more commonly diagnosed among men, women are more often diagnosed with borderline, histrionic, and dependent personality disorder (American Psychiatric Association, 2000; for a review of potential gender bias in the assessment of personality disorders, see Widiger & Spitzer, 1991). Among a community sample of adolescents (ages 9–19), Bernstein et al. (1993) found that 31.2% of adolescents met criteria for a personality disorder according to DSM-III-R at a moderate level (1 standard deviation above the mean on a continuous measure of personality disorder symptoms) and that 17.2% met criteria for a personality disorder at a severe level (2 standard deviations above the mean). Obsessive–compulsive personality disorder was the most prevalent type (16.3%), and schizotypal (3%) and schizoid personality disorders (6.2%) were the least prevalent. Regarding gender differences, dependent personality disorder was more common among boys than girls, although this disorder is more common among women in adult samples (American Psychiatric Association, 2000).

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Assessment “A Personality Disorder is an enduring pattern of inner experience and behavior that deviates markedly from the expectations of the individual’s culture, is pervasive and inflexible, has an onset in adolescence or early adulthood, is stable over time, and leads to distress or impairment” (American Psychiatric Association, 1994, p. 629). Assessment of these disorders, however, can be complicated. First, the Axis II diagnostic system, the one used to assess personality disorders, appears to lack adequate coverage of clinically significant character pathology (Widiger, 2007). In a survey of a random sample of psychiatrists and psychologists, Westen and Arkowitz-Westen (1998) found that almost 60% of the clients being treated for personality pathology did not fit into a personality disorder category and therefore remained undiagnosed on Axis II. A second concern regarding this diagnostic system is its relatively low discriminant validity (Westen, 1997). Comorbidity rates are very high among the personality disorders (for a review, see Widiger & Rogers, 1989) such that in some samples 80% of clients with a personality disorder qualified for another Axis II diagnosis (Oldham et al., 1992). Several measures exist for assessing normal and pathological personality functioning for adults (for reviews, see Butcher & Rouse, 1996; Clark & Harrison, 2001). The features vary among the instruments, and thus the goals of the researcher or clinician should be considered in choosing the appropriate measure. In selecting an appropriate instrument, several factors should be considered, including reliability, degree of structure, false-positive rates, correspondence to DSM criteria, coverage, administration procedures, content, and interviewer qualifications (for a review, see Zimmerman, 1994). Existing measures vary considerably with respect to these features. For example, the Personality Disorders Examination (PDE; Loranger, 1988) is structured to cover domains of functioning (e.g., work, interpersonal relationships), whereas the Structured Clinical Interview for the DSM-IV Axis II Disorders (SCID-II; First, Spitzer, Gibbon, & Williams, 1995) includes questions relating directly to each criterion for each personality disorder. Another commonly used instrument is the Millon Clinical Multiaxial Inventory (MCMI; Millon, 1994); however, the correspondence between the MCMI and the DSM-III or III-R has been questioned (Zimmerman, 1994). Further, the MCMI tends to overdiagnose personality disorders. This has also been shown to be true of another widely used instrument, the Personality Diagnostic Questionnaire (PDQ; Hyler et al., 1988), but to a lesser degree (Zimmerman, 1994). In comparison to adult measures, relatively few instruments have been developed to assess personality disorders during childhood or adolescence. Currently, little agreement or consistent discussion exists in the literature concerning the conceptualization of personality development in children (Shiner, 1998, 2005). Therefore, it may be difficult to determine not only which constructs assess normal personality but also which constructs measure deviant personality processes. The available instruments seem to represent two

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approaches: (1) standardizing versions of adult personality disorder measures with younger samples or (2) designing new instruments specifically for use with children but based on adult criteria. Concerning the former approach, the validity of the PDE for assessing personality disorders in a sample of psychiatric adolescents has been examined. Unfortunately, the internal consistency was lower and the overlap among the criteria for different disorders was greater for adolescents than for adults (Becker et al., 1999). In another example of this approach, an early version of the SCID, the Structured Interview for the DSM-III, was examined for a sample of adolescents, and convergent validity was demonstrated for the DSM-III Cluster B disorders (borderline, histrionic, and narcissistic personality disorders; Brent, Zelenak, Bukstein, & Brown, 1990). Corresponding to the second approach, several instruments have been designed specifically for the assessment of children and adolescents (for reviews, see Knoff, 1986; Martin, 1988; McCloskey, Kane, Morera, Gipe, & McLaughlin, 2007). The Coolidge Personality and Neuropsychological Inventory for Children (CPNI; Coolidge, 2005) is a parent report instrument used to assess DSM-IV Axis I and Axis II symptoms among individuals, ages 5–17. This measure has favorable psychometric properties (Coolidge, Thede, & Jang, 2001; Coolidge, Thede, Steward, & Segal, 2002). Other child or adolescent measures typically assess general personality functioning or behavioral and emotional difficulties but do not provide scales that correspond to the DSMIV personality disorders. For example, the Minnesota Multiphasic Personality Inventory—Adolescent (MMPI-A; Butcher et al., 1992) and the Millon Adolescent Clinical Inventory (MACI; Millon, Millon, Davis, & Grossman, 1997) are self-report measures of personality characteristics among adolescents (ages 12–18) with a wide research base to support their psychometric properties and clinical use (Butcher & Williams, 2000; Millon, 1997). For a thoughtful review on the current approaches and relevant concerns associated with the assessment of personality disturbance among youths, the reader is directed to Shiner’s (2007) chapter on personality disorders.

Stability Research concerning the stability of personality disorder diagnoses in adults (for a review, see Skodol et al., 2005; Zimmerman, 1994) has numerous methodological limitations, including follow-back designs, nonblind diagnoses, and unreliable diagnoses (for a review, see McDavid & Pilkonis, 1996). Little research has addressed the stability of these diagnoses in children or adolescents. One study has demonstrated that of the adolescents (age range, 9–19) who were diagnosed with a DSM-III-R personality disorder, less than half of them retained the diagnosis at a 2-year follow-up (Bernstein et al., 1993). These authors also found that, of their random community sample, approximately half of the adolescents were diagnosed with a personality disorder, a prevalence rate much higher than that for adults (American Psychi-

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atric Association, 2000). In addition, the older the adolescents, the less likely they were to receive a personality disorder diagnosis, another finding at odds with the DSM conceptualization of personality disorders as disorders that emerge in late adolescence and adulthood. Other investigations have generally reported limited stability of a specific personality disorder diagnosed in adolescence (e.g., Meijer, Goedhart, & Treffers, 1998). This instability of personality disorder diagnoses may be problematic for the diagnosis of these disorders during childhood or adolescence, given that general personality traits tend to be moderately stable during childhood and adolescence (Roberts & DelVecchio, 2000). Taken together, these findings suggest that the measures of personality disorders used to assess adolescents may not be tapping the same constructs as those designed for adults. Rather, these instruments may measure some normative behaviors of adolescence, including an increase in antisocial behaviors (Moffitt, 1993), narcissistic tendencies, and an immature sense of self (Harter, 1998). Accepting the limited discriminant validity of the personality disorders, it may be possible to demonstrate the stability of more broadly defined personality disturbance from childhood through adulthood. For example, two separate studies using different criteria and different ages of assessment both demonstrated that a borderline-related diagnosis during childhood is associated with the development of any personality disorder 10–15 years later (Lofgren, Bemporad, King, Lindem, & O’Driscoll, 1991; Thomsen, 1996). Neither study addressed, however, whether particular symptoms were associated with the later development of a specific personality disorder. Crawford et al. (2001), however, examined the 8-year stability of symptoms of the Cluster B (dramatic, emotional) personality disorders and found these symptoms to be highly stable during this period from adolescence (ages 10–14) to young adulthood (ages 18–22).

Childhood and Adolescent Precursors to Adult Personality Disorders To identify themes that cut across the personality disorders and have potential for increasing our understanding of the childhood precursors of adult personality disorders, we conducted a content analysis of the 79 personality disorder symptoms described in DSM-IV-TR. The authors separately examined a list of the symptoms and divided them into categories, based on their conceptual similarities. The content of the items within each category was then examined, and themes were created that seemed to encompass the variety of symptoms within each grouping. The authors then compared their categories and the symptoms that constituted those categories. Any differences were discussed, and the discrepancies were resolved by discussion and consultation with the literature. This analysis yielded seven themes, each of which is discussed in turn below. As described previously, most themes describe continua of behav-

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iors or characteristics, with an excess of a particular quality as one endpoint and a lack of that quality as the second endpoint. The seven themes are (1) hostile, paranoid world view; (2) intense, unstable, and inappropriate emotion, to restricted, flat affect; (3) impulsivity to rigidity; (4) overly concerned with relationships, to avoids relationships; (5) negative sense of self, or lack of self, to exaggerated sense of self; (6) peculiar thought processes and behaviors; and (7) lack of concern for social norms and the needs of others. Table 4.1 (see pp. 60–61) lists these themes, the personality disorders that are encompassed by each theme, and exemplary DSM-IV-TR symptoms for each theme–disorder pairing.

Hostile, Paranoid World View Individuals with paranoid, schizotypal, or borderline personality disorder tend to view the world in a hostile or paranoid manner. Persons with paranoid personality disorder believe that others are inherently persecutory, disloyal, and dishonest. Although these individuals lack sufficient proof of the malfeasance of others, they maintain that others are intentionally trying to harm them. These individuals may prematurely respond to social situations with aggressive outbursts. Persons with schizotypal or borderline personality disorder may also be suspicious and paranoid of others (American Psychiatric Association, 2000). The development of a hostile view of the world has been examined in childhood through a social information-processing model that describes the social and cognitive mechanisms related to children’s maladjustment (Dodge & Crick, 1990). According to this model, the cognitive steps of making sense of one’s environment and reacting to it include the following: (1) encoding important cues, (2) interpreting the information, (3) generating a set of possible responses, (4) choosing a response, and (5) performing the selected response. Dodge and Crick (1990) posit that “Skillful processing at each step will lead to competent performance within the situation, whereas biased or deficient processing will lead to deviant, possibly aggressive, social behavior” (p. 13). For example, aggressive children are more likely to encode negative stimuli and to interpret ambiguous situations as hostile. This inclination initiates a process where a bias toward attributing hostile intent to an ambiguous situation may lead to an aggressive response, which, in turn, may cause retaliation, an event that reinforces the child’s initially incorrect interpretation. Such a pattern may underlie the suspiciousness and the tendency to be “quick to react angrily or to counterattack” (American Psychiatric Association, 1994, p. 638) characteristic of persons with paranoid personality disorder. Poor social information-processing skills may serve as a risk factor for the development of later personality pathology that involves a paranoid or hostile view of others, but how might this pattern of interpreting the world develop, and what is the process by which this risk factor might play a role in making an individual vulnerable to the development of a personality disorder

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in adulthood? Cognitive deficits and biases have been associated with temperamental variables such as impulsivity (Dodge & Newman, 1981), childhood personality factors such as neuroticism and (low levels of) agreeableness (Shiner, 2005), and environmental factors including harsh parenting (Weiss, Dodge, Bates, & Pettit, 1992). Caspi (1998, p. 356) argues that these “early temperamental characteristics in combination with early social experiences can set up anticipatory attitudes that lead the individual to project particular interpretations onto new social relationships and situations.” An example of the processes involved in vulnerability may begin with an impulsive child who may be more likely to jump to conclusions without sufficient information. The difficulties for a child with such a tendency may be compounded if he or she lives in a chaotic household with harsh parenting or is exposed to aggressive peers. In such an antagonistic or unfriendly environment, a hostile attribution may be accurate in most cases, only becoming a “bias” when this tendency is carried into new contexts in which more positive social relationships may be available. At this point, there is no opposing endpoint such as “overly positive views” on a continuum with hostile views of the world. Although some research has been conducted on children who demonstrate a benign attributional bias, this behavior has not been considered pathological but, rather, has been associated with prosocial tendencies in a normative sample of children (Nelson & Crick, 1999). It is possible, however, that a pervasive and extreme benign attribution may lead to an inappropriate tolerance of negative behaviors, possibly making the child vulnerable to victimization by peers, an experience associated with the development of anxiety disorders in adulthood (Sourander et al., 2007).

Intense, Unstable, and Inappropriate Emotion, to Restricted, Flat Affect Intense, Unstable, and Inappropriate Emotion Intense, unstable, and inappropriate emotional expression is characteristic of both borderline and histrionic personality disorders. Symptoms of borderline personality disorder include “affective instability due to a marked reactivity of mood” and “inappropriate, intense anger,” whereas “exaggerated expression of emotion” and emotional lability are descriptive of histrionic personality disorder (American Psychiatric Association, 1994, pp. 654, 658). Such behavior may implicate difficulty with emotion regulation as a risk factor underlying the development of these particular disorders. Emotion regulation concerns individuals’ ability to control their arousal, and the foundation for such a skill begins forming in infancy. During infancy, a secure attachment style is one mechanism or process through which children learn to regulate their emotions. A secure attachment is one in which the caregiver has demonstrated that he or she is consistently available to the infant, even in times of stress. Within a secure relationship, negative emotions such

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as anger or fear are more easily managed by infants because such arousal has been associated with a soothing, effective response by the caregiver (Sroufe, 1996). Initially, the caregiver is responsible for regulating the emotional arousal of the infant by recognizing the infant’s distress and relieving the infant’s state of disorganization. The infant gradually plays a larger role in regulating his or her own arousal by, for example, seeking contact with the caregiver or displaying wariness at separation. Having success at returning to a settled state after high arousal teaches the infant that expressing intense emotion is not an extremely disorganizing experience. Therefore, he or she becomes able to experience more intense emotions and withstand greater arousal, at first with the assistance of the caregiver and gradually on his or her own (Sroufe, 1996). When this process is aberrant, for example, when the caregiver is not effective at providing responsive and consistent care, the infant may experience arousal as confusing and unsettling. The infant who has not experienced a pattern of intense arousal coupled with attentive care and soothing may not learn that emotion can be experienced and then quelled. As a result, a smooth transition from parent-guided regulation in infancy to self-regulation during childhood may not occur, laying the groundwork for an inability to cope with intense arousal and emotions experienced later in life (Sroufe, 1996). An adequate parent–child relationship also appears to be involved in the development of important biological systems involved in emotion regulation. For example, Schore (1994) describes how the development of the central nervous system is implicated in emotion regulation. Specifically, the development of the inhibitory processes of the limbic system can influence control over the earlier maturing excitatory processes of the limbic system. Importantly, however, it is the caregiver’s assistance in regulating the infant’s arousal that may influence the relative power of inhibitory/excitatory functions of the limbic system. In support of the role of early caregiving in the development of biological systems, inadequate caregiving during infancy has been found to influence the physiological underpinnings of emotion regulation. Dawson, Hessl, and Frey (1994) examined the effects of maternal depression on infants and have described how depressed mothers may not provide responsive care or be effective at soothing their infants’ distress. They hypothesized that these infants develop a lower threshold for the elicitation of negative emotion and have not learned how to regulate this negative arousal. The researchers suggest that “the infants of depressed mothers are experiencing negative emotions more frequently and intensely and that this results in selective amplification of those neural circuits involved in such emotion” (Dawson et al., 1994, p. 774). Other evidence suggests that a biological predisposition may influence the child’s response to environmental stressors, placing the child at risk for developing psychopathology in adulthood. Support for this view is found in the literature on temperament. Temperament styles consist of early emerging emotional and behavioral tendencies such as activity level, irritability, ability

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to regulate arousal (“soothability”), inhibition, and sociability (Goldsmith et al., 1987), and these styles are often considered a foundation for personality (Hartup & van Lieshout, 1995). Temperament researchers often maintain that individual differences in biological dispositions may underlie differences in emotional and behavioral responsivity among children. Kagan, Reznick, and Snidman (1988), for example, argue that inhibited infants, who are fearful of novel situations, may have a central nervous system that has a low threshold for arousal. Thus, stimuli that may cause no response or a positive response for some infants may elicit fear or anxiety in others. Research by Davidson (1991) is consistent with the perspective that biological vulnerability factors might play a role in emotion regulation. Davidson has studied the frontal and anterior temporal regions, two cortical zones associated with the limbic system that are involved in controlling emotion expression. Examination of electroencephalographic (EEG) measures of brain activation has indicated that activation in the left hemisphere is associated with approach behavior and positive emotion, whereas right-sided activation is associated with withdrawal and negative emotion. The relative balance of this activation pattern has been associated with stable trait-like tendencies toward either negative (relatively stronger right activation) or positive (relatively stronger left activation) emotional responses to eliciting situations. Thus, having a trait-like tendency toward negative emotional responding may make it more difficult to regulate that response. This hypersensitivity is important. For example, maltreatment or other chaotic family life experiences may have devastating consequences for the development of any child (e.g., Cicchetti & Valentino, 2006); however, the combination of a child physiologically predisposed to be overly sensitive to aversive stimuli and an extremely negative environment may be disastrous. Such a process may be implicated in the proneness to unprovoked episodes of extreme anxiety characteristic of individuals with borderline personality disorder (American Psychiatric Association, 1994; Cicchetti & Olsen, 1990). This combination of a biological predisposition exacerbating the impact of negative family experiences is consistent with current research demonstrating that a genetic factor, a polymorphism of the serotonin transporter gene, moderates the influence of life stress on the development of depression (Caspi et al., 2003). Poor emotion regulation skills begin forming during infancy, but, consistent with the organizational nature of development, this foundation is carried into the early childhood years, where it can have significant implications for adaptation. Having an insecure attachment history may place a child at risk for problematic behaviors associated with a lack of emotional control. There are important links between how an individual feels and how he or she acts. Emotions not only require regulation themselves but also serve as regulators of behavior. Coping behaviors are one example of how emotions regulate behavior. In a study of 4- to 6-year-olds, intense emotionality was related to ineffective coping, and this was hypothesized to be due to the high

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intensity of the children’s negative emotions, making them more “distractible” and less able to focus on the situation (Eisenberg et al., 1993; see the section on “Impulsivity” for behavioral manifestations of dysregulated emotion during childhood and adolescence). Poor emotion regulation skills in the context of chaotic, negative, critical, and neglectful home environments have been specifically implicated in the etiology of borderline personality disorder (Cicchetti & Olsen, 1990; Fruzzetti, Shenk, & Hoffman, 2005). One process that may be involved in the etiology of this disorder includes the impact of intense emotional arousal on cognitive processes. Although the social information-processing model described previously has most typically been applied to the study of aggression (Dodge & Crick, 1990), this model offers a broad framework for understanding cognitive processing that has proven useful in describing other types of maladjustment, including depression (Dodge, 1993). Therefore, this model may also be helpful in outlining a cognitive vulnerability toward developing borderline personality disorder. Individuals who come from families marked with violence, disorganization, or maltreatment are likely to become overly sensitive to negative emotional stimuli. This sensitivity is evident at both the behavioral (Pollak, Cicchetti, Hornung, & Reed, 2000) and neurofunctional levels of analysis (Cicchetti & Curtis, 2005; Pollak, Cicchetti, Klorman, & Brumaghim, 1997). Given that a hostile attribution bias is associated with a tendency toward encoding negative aspects of the social environment (Dodge & Crick, 1990), this heightened sensitivity to negative emotions may make these children particularly prone to interpreting potentially benign situations as hostile. Thus, they may respond to a benign social situation with anger, a hostile outburst, or anxiety, which may lead to a negative response from other family members. This negative response by others likely works to reinforce the individual’s misinterpretation of the benign event and may play a role in furthering inappropriate emotional arousal to events. Because children with borderline characteristics may view some events as traumatic that would not usually be experienced in such a manner by other children (Cicchetti & Olsen, 1990), the development of these types of biological, emotional, and cognitive systems may make particular individuals more sensitive to negative events and may explain this phenomenon. Further, these vulnerabilities may be linked to another defining feature of borderline personality disorder—that of being “prone to outbursts of anger and bouts of paralyzing anxiety, both of which happen seemingly without provocation” (American Psychiatric Association, 1994, p. 364). Fruzzetti and colleagues (2005) have suggested that it is the combination of emotion dysregulation and a particular type of family environment, one where the child’s feelings, emotions, and experiences are not validated by caregivers, that specifically places children on a trajectory toward developing borderline personality disorder. They argue that invalidating the child’s experiences leads to emotional sensitivity because the child learns to be vigilant to situations that might result in negative emotions. For example, a child may

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display reluctance to engage in a new activity, and the parent might invalidate the child’s feeling by telling the child the new activity is fun and the child will enjoy himself. If the child has an unpleasant time, he will be more sensitive in the future to new activities that might also elicit unpleasant feelings. This heightened arousal will likely lead to further invalidation. Invalidation of the child’s experiences may also lead to problems with labeling and modulating emotions. For example, the child might appear sad, and the caregiver might tell the child she is fine and should stop being angry. Thus, the child may not learn to accurately report and discriminate between different emotions experienced by herself and others. This ability to identify emotions and understand how one feels internally is necessary for adequate emotion regulation. In sum, a genetic vulnerability may exacerbate the impact of environmental stressors (e.g., Caspi et al., 2003). Environmental risk factors, however, play a role in shaping the developing brain and physiological arousal systems (e.g., Cicchetti & Curtis, 2005; Schore, 1994). Both of these perspectives, however, are consistent with a developmental psychopathology perspective and highlight the interdependence of social, emotional, and biological systems. The studies reviewed in this section suggest that emotion regulation skills may serve as one avenue for developmental research targeting personality disorders characterized by intense, unstable, and inappropriate affect. Recent research has supported the powerful role of early emotion regulation problems in the development of borderline-related pathology (Fruzzetti et al., 2005; Rogosch & Cicchetti, 2005). It appears as though the development of particular biological systems, the presence of specific patterns of cognitive processing, and an inability to effectively regulate emotion not only set the stage for intense emotional reactivity but may also play a role in the impulsive behaviors (see the section on “Impulsivity”) and in the tendency to overreact to personally important situations (see the section on “Overly Concerned with Relationships”) characteristic of particular personality disorders.

Restricted, Flat Affect At the other end of our emotion continuum is restricted or flat affect, a characteristic typical of individuals with schizoid or schizotypal personality disorder. Schizoid personality disorder involves “a restricted range of expression of emotions in interpersonal settings,” and schizotypal personality disorder is characterized by “inappropriate or constricted affect” (American Psychiatric Association, 1994, pp. 638, 642). Behavioral precursors of these two disorders have been identified; for example, children who were later diagnosed with schizotypal personality disorder were described as high on such characteristics as “seldom laughs or smiles with others,” “quiet and unengaged,” “passive,” and “shy, reserved, and silent” (Olin et al., 1997, p. 96). Depressive symptoms in childhood have also been predictive of the later development of Cluster A personality disorders (which include schizotypal and schizoid personality disorder), especially for boys (Bernstein et al., 1996).

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Both schizoid and schizotypal personality disorders have been linked with schizophrenia (Erlenmeyer-Kimling, Squires-Wheeler, Adamo, & Bassett, 1995; Maier, Lichtermann, Minges, & Heun, 1994); however, this link is particularly strong for schizotypal personality disorder (Miller, Useda, Trull, Burr, & Minks-Brown, 2001). Therefore, research on the development of schizophrenia may also be useful in identifying vulnerability processes for these personality disorders. Infants with a genetic risk for the development of schizophrenia have been found to be atypically quiet and underactive (Fish, 1977). Further, by examining home movies, children who later developed schizophrenia were found to demonstrate more negative affect than their healthy siblings, and preschizophrenic girls were found to exhibit fewer expressions of joy (Walker, Grimes, Davis, & Smith, 1993). From infancy through age 5, preschizophrenic children were found to be less responsive than their nonaffected siblings (Walker & Lewine, 1990). In adolescence, increased negative affect, disobedience, irritability, and social isolation are noted in individuals who go on to develop schizophrenia (Walker, Baum, & Diforio, 1998). It has been hypothesized that individuals with schizoid personality disorder may present with a physiological dysfunction present in infancy “favoring the cholinergic or parasympathetic system” that is thought to underlie a temperamental “emotional unresponsiveness” (Millon & Davis, 1995, p. 666). This reduced emotional expression may also have its roots in the attachment process of infancy. Some infants who have been exposed to a rejecting caregiver may learn to restrain the normative healthy proximity-seeking behavior toward a caregiver, as discussed earlier and develop an anxious–avoidant attachment relationship with their caregiver. An anxious–avoidant attachment is a type of insecure attachment that may result when the child experiences rejection when approaching the caregiver for comfort. Therefore, these infants may instead avoid and ignore the caregiver when distressed. In contrast to infants with secure attachments, arousal for these infants is associated with increased avoidance, because to exhibit intense emotions and approach a rejecting caregiver would likely exacerbate the distress rather than calm the infant. Thus, the infant may learn to inhibit the expression of distressing emotions (Sroufe, 1996). In keeping with the principles of developmental psychopathology, the formation of an attachment relationship is considered an ongoing process involving the behavior of both the caregiver and the infant, mutually influencing each other. From one perspective, the infant–caregiver attachment relationship may play a role in the young child’s learning to suppress emotion and engage in avoidance of social partners. From a complementary perspective, however, an especially emotionally unresponsive infant may elicit particular reactions from the environment (e.g., less involvement from a caregiver). Evidence indicates that an infant’s behavior may influence the type of caregiving that is received. For example, the mothers of “irritable” babies have been shown to engage in less face-to-face contact, physical contact, appropriate

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stimulation, soothing, and responsiveness as compared to the behavior of mothers of “nonirritable” babies (van den Boom & Hoeksma, 1994). Thus, the behavioral characteristics of children who later developed a schizophrenia spectrum disorder may be both the result of important processes (e.g., the development of an insecure attachment) and the instigators or facilitators of an aberrant process. Although a particular attachment style does not indicate that a disorder will develop, it does suggest that an individual may be on a deviant pathway and may therefore reflect a vulnerability to later psychopathology. An insecure attachment may influence how an individual relates to others, thus serving as a risk factor for a pervasive maladaptive pattern of social interaction later in life. The pattern of emotional unresponsiveness of the infant and toddler may play a role in the limited ability to form close relationships later in life, a fundamental characteristic of persons diagnosed with schizoid or schizotypal personality disorders (see the section on “Avoids Relationships”).

Impulsivity to Rigidity Impulsivity Impulsivity appears to be manifested in personality disorders in several ways. It is evident in the inability to inhibit excesses in behavior such as excessive spending or substance use characteristic of individuals with borderline personality disorder, or the inability to delay gratification characteristic of individuals with histrionic personality disorder. This characteristic is also present in the impulsive self-mutilating or suicidal behaviors of individuals with borderline personality disorder. Impulsivity is also manifest in behaviors related to aggressive outbursts and the lack of planning characteristic of antisocial personality disorder. Impulsivity related to aggression also includes the “reckless disregard for safety of self or others” prominent among individuals with antisocial personality disorder and the “physical fights” commonly exhibited by persons with either antisocial or borderline personality disorder (American Psychiatric Association, 1994, pp. 650, 654). The display of intense, unstable, and inappropriate emotion characteristic of individuals with borderline or histrionic personality disorder described in the section above may be considered an emotional component of impulsivity. For example, it has been found that relatively low levels of negative emotionality and high levels of emotion regulation predict competent and appropriate social behavior (Eisenberg et al., 1995). Because an inability to regulate emotional arousal may interfere with the ability to inhibit behavior (Eisenberg & Fabes, 1998), emotion regulation difficulties may be predictive of later personality pathology involving impulsivity. In fact, the combination of both emotional vulnerability factors and a specific cognitive profile associated with impulsivity has been implicated in borderline personality disorder. Specifically, adults with borderline personality disorder have both executive

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functioning deficits (difficulties with impulsivity, attention, planning, organization, and cognitive flexibility) as well as high levels of negative affect (Posner et al., 2003). Rogosch and Cicchetti (2005) have extended these findings to children, discovering similar correlates among children at high risk for developing borderline personality disorder. The individual with antisocial personality disorder demonstrates behavioral impulsivity and repeated aggressive outbursts. In childhood, aggressive behavior and impulsivity often present together. One example concerns reactive aggression, a form of aggression in which anger and/or negative affect due to the perceived thwarting of a goal or other provocation plays a role in children’s hurting others (Dodge & Coie, 1987). The display of aggression, therefore, is linked with an inability to regulate emotional arousal. Second, emotional arousal can interfere with the information-processing steps of encoding and interpreting events and also with selecting, evaluating, and enacting possible responses. When children experience negative emotions, adequate regulation can often result in inhibiting impulses to behave inappropriately (Eisenberg & Fabes, 1998). Thus, emotion regulation is an important component of an individual’s ability to regulate his or her behavior. Therefore, these studies suggest that the personality factors of low levels of conscientiousness (low effortful control; Rogosch & Cicchetti, 2005) and agreeableness may offer another avenue for research on the development of impulsivity in adult character pathology. Children who exhibit low levels of conscientiousness have problems with attention and self-control. They are not planful or responsible (Shiner, 2005). Further, impulsivity is often found among children who are both low in conscientiousness and agreeableness. Individuals who are low in the trait of agreeableness are aggressive, disrespectful, and manipulative. Children low on this trait are particularly difficult for parents to handle (Shiner, 2005). Self-regulatory skills may offer another avenue for research on the development of impulsivity in adult character pathology (e.g., Calkins & Fox, 2002). An inability to inhibit behavior, hyperactivity, and attention problems form the syndrome of attention-deficit/hyperactivity disorder (ADHD; American Psychiatric Association, 2000). Conduct disorder during childhood, a necessary precursor to diagnosing antisocial personality disorder in adulthood, is often found to co-occur with ADHD (Hinshaw, 1987). In addition, individuals with borderline personality disorder also exhibit marked impulsivity, anger-control problems, and the recurrent expression of “inappropriate, intense anger” (American Psychiatric Association, 1994, p. 651), and these individuals may have a history of ADHD (Rey et al., 1995) as well as exhibit problems with cognitive measures of attention and impulsivity (inhibitory control; Posner et al., 2003). In fact, a review of the literature on borderline personality disorder found that this disorder is characterized by two general factors—impulsive aggression and emotion regulation problems (Skodol et al., 2002). Consistent with the developmental psychopathology model, attention

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problems may be a risk factor that interacts with other variables, placing a child on the pathway toward aggressive behavior. For example, parents may use more harsh discipline with an impulsive child (Hinshaw & Simmel, 1994), and harsh discipline has been associated with later aggressive behavior (Weiss et al., 1992). It has also been demonstrated that children’s ability to exhibit self-restraint mediates the relation between parenting measures and later antisocial behavior (Feldman & Weinberger, 1994). Another pathway toward aggressive behavior may include ADHD and academic failure. Attention problems may cause academic difficulties, which can increase the risk for aggressive behavior (Maughan, Gray, & Rutter, 1985). It is not clear, however, whether attention and impulsivity difficulties precede or antecede academic problems (Coie & Dodge, 1998; Dishion, French, & Patterson, 1995). Attention difficulties and academic problems likely serve as risk factors that may interact with other biological, social, or cognitive systems to increase the child’s tendency to engage in aggressive behavior. Several processes have been implicated in the development of antisocial behavior (for reviews, see Coie & Dodge, 1998; Dishion & Patterson, 2006), and future research will need to determine which of these processes is linked to impulsivity in adult personality pathology. For example, lack of empathy for others is a defining feature of antisocial personality disorder (see the section on “Lack of Concern for Social Norms and the Needs of Others”) that may be associated with biological or cognitive processes not implicated in other impulse-control disorders such as intermittent explosive disorder, in which the individual may feel regretful after an aggressive episode.

Rigidity At the other end of the continuum from impulsivity, lack of planning, and lack of emotion regulation and self-regulation is the inflexibility and rigidity characteristic of individuals with obsessive–compulsive personality disorder or avoidant personality disorder. The rigidity observed in individuals with avoidant personality disorder refers to their excessive unwillingness “to take personal risks or to engage in any new activities because they may prove embarrassing” (American Psychiatric Association, 1994, p. 665). One potential vulnerability to this extreme inhibition has been identified by Kagan (Kagan, 1992; Kagan & Snidman, 1991). As described previously, infants exhibiting behavioral inhibition are fearful of novel situations, and this behavior has been argued to reflect a physiological sensitivity to stimuli (i.e., a low threshold for arousal; Kagan et al., 1988). Similarly, Gray (1982) has posited a behavioral inhibition system (BIS) that is thought to underlie temperamental differences. An overly active BIS may be associated with feelings of anxiety that lead to the inhibition of behavior. Over time, an overly active BIS might predispose an individual to experience generalized feelings of anxiety leading to extreme inhibition in both negative circumstances and potentially positive situations.

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On the other hand, individuals with obsessive–compulsive personality disorder demonstrate rigidity in that they exhibit “perfectionism that interferes with task completion,” “stubborness,” and “inflexibility about matters of morality, ethics, or values” (American Psychiatric Association, 1994, pp. 672–673). The empirical information on obsessive–compulsive personality disorder, particularly on etiological factors, is extremely limited (Blashfield & Intoccia, 2000; Widiger, 2007). Although an abundance of research exists concerning childhood obsessive–compulsive disorder (OCD), and some research points toward a linkage between OCD and obsessive–compulsive personality disorder (e.g., Pollak, 1987), studies have shown that these two disorders are not necessarily related (Thomsen & Mikkelsen, 1993). Therefore, it may not be fruitful to draw on the extensive childhood OCD literature to examine precursors to obsessive–compulsive personality disorder. Because individuals with obsessive–compulsive personality disorder are excessively perfectionist, organized, detail-oriented, and concerned about making errors, the study of perfectionism in children and adolescents may provide a viable research avenue for understanding the development of a rigid personality style. Perfectionism has been found to predict obsessive–compulsive features such as excessive checking in a nonclinical sample of adolescents and adults (Wade, Kyrios, & Henry, 1998). Further, it has been found that a negative form of perfectionism, “maladaptive evaluation concerns” rather than “positive striving,” is associated with obsessive–compulsive features in a psychiatric sample of adolescents and adults (Norman, Davies, Nicholson, Cortese, & Malla, 1998). Interestingly, perfectionism has also been considered an important component of anorexia nervosa in female adolescents and young adults (Attie & Brooks-Gunn, 1995), and an association between anorexia nervosa and obsessive–compulsive personality disorder has been observed in adolescents (Gillberg & Rastam, 1992). In fact, some researchers support an obsessive– compulsive spectrum of disorders including obsessive–compulsive personality disorder, eating disorders, and related problems (Allen, King, & Hollander, 2003). These findings point toward excessive perfectionism as a risk factor that may place a child on a deviant pathway for psychopathological outcomes. How this risk factor interacts with other biological and social systems may determine whether it manifests itself in obsessive–compulsive personality traits, disordered eating, or related disorders. Beck and colleagues (Beck, Freeman, Davis, & Associates, 2004) point toward cognitive processes likely to be involved in obsessive–compulsive personality disorder such as catastrophic thinking (e.g., excessive concern about the consequences of imperfection). Future research could examine the processes that may be involved in an association between childhood strivings for perfection, cognitive distortions, and obsessive–compulsive features during adulthood. Individuals with obsessive–compulsive personality disorder are also preoccupied with control, and many of their problematic behaviors, including excessive organization and unwillingness to trust others to complete tasks satisfactorily, reflect attempts

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to “maintain a sense of control” (American Psychiatric Association, 1994, p. 669). Thus, the strivings for perfection that may be associated with later personality pathology may be related to an excessive need to maintain control. The examination of the personality factor agreeableness in childhood may therefore benefit research in this area. Low levels of agreeableness are associated with stubbornness, and in children low levels of this personality factor include indices of control, such as forcing others to go along with their objectives and wishes (Shiner, 2005).

Overly Concerned with Relationships, to Avoids Relationships Overly Concerned with Relationships Anxiety about close relationships as typified by excessive dependency, a preoccupation with relationship concerns, and heightened emotionality about relationship matters are characteristic of individuals with borderline, histrionic, or dependent personality disorder. For example, persons with borderline personality disorder demonstrate “a pattern of unstable or intense interpersonal relationships” and are preoccupied with fears of abandonment, individuals with histrionic personality disorder may engage in “inappropriate sexually seductive . . . behavior,” and those with dependent personality disorder may rely on others to the point that they feel helpless to function on their own (American Psychiatric Association, 1994, pp. 654, 657). These adults appear to demonstrate a pattern of excessive apprehension and concern about the quality and stability of their relationships while using these same relationships to manipulate or control others. One possible precursor to the development of disorders characterized by relationship insecurity may be found in children who engage in a similar pattern of excessive concern about and manipulation of relationships. This pattern of behavior has been observed in children who engage in relatively high rates of relationally aggressive behavior (Crick, Werner, Casas, et al., 1999). Evidence has demonstrated an association between relationally aggressive behaviors and borderline personality features in both children’s (Crick, Murray-Close, & Woods, 2005) and adolescents’ peer relationships (Werner & Crick, 1999) and adolescents’ romantic relationships (Morales & CullertonSen, 2000). Relational aggression has at its core a focus on relationships such that these children harm others by manipulating or damaging social relationships (e.g., spreading rumors in retaliation to damage a child’s reputation and withdrawing friendship in order to control a peer; Crick & Grotpeter, 1995). Similar to adults with borderline, histrionic, or dependent personality disorder, despite their manipulative behaviors within relationships, relationally aggressive children also appear to lack confidence in their ability to maintain meaningful, close relationships with others and therefore demonstrate heightened sensitivity to relational events. For example, relationally aggressive

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children tend to maintain friendships that are overly exclusive and marked with jealousy. These children also manipulate their friends in order to obtain control within the friendship (Grotpeter & Crick, 1996). Further, adolescents who are relationally aggressive have been found to exhibit this relational event sensitivity and an elevated level of desire for exclusivity in their close relationships (Morales & Crick, 1999). Relationally aggressive children also report feeling more anger than do nonrelationally aggressive children when faced with relational conflicts (Crick, 1995; Crick, Grotpeter, & Bigbee, 1998). Thus, the intense emotionality discussed in the section “Intense, Unstable, and Inappropriate Emotion” may be activated in situations that threaten the integrity of important relationships. Given their preoccupation with maintaining close relationships and their sensitivity to relational slights, children who are successful at achieving their goals and controlling others through this form of social manipulation may continue this pattern in adult relationships. The social information-processing model described previously may also highlight social and cognitive aspects of the oversensitivity to relationship events. For example, individuals with borderline personality disorder worry about abandonment, and these individuals may be more alert to cues signaling potential loss or may misinterpret temporary separation as possible abandonment. Their intense reaction may ultimately push others away, beginning a process that reinforces the initial incorrect interpretation of the event. This sensitivity to interpersonal events may be compounded by the intense, uncontrolled emotion often experienced by these individuals. Such a cognitive pattern may explain why neutral events, such as a friend’s being a few minutes late, is so easily misinterpreted and related to feelings of “panic or fury” (American Psychiatric Association, 1994, p. 650). A recent investigation provides preliminary support for aspects of this pathway to the development of borderline personality disorder (Crick et al., 2005). Changes in features of borderline personality disorder in a community sample of fourth through sixth graders was found to be predicted by cognitive sensitivity to relational slights (hostile attribution bias), a heightened emotional response to relational events, the degree of exclusivity sought within a close friendship, and the child’s level of relationally aggressive behavior. The role of these childhood variables as precursors to adult borderline personality disorder, however, has not yet been explored. As discussed previously, these cognitive processes likely interact with environmental events to produce vulnerability to the development of disorders characterized by anxiety about close relationships. For example, a chaotic family life may be related to a heightened sensitivity to negative stimuli. Further, individuals from this family environment may misinterpret situations and react with an angry outburst that may lead to a negative response from other family members, thereby reinforcing the initial misinterpretation. Whereas chaotic home environments may be a risk factor for the development of borderline personality disorder, the possible contribution of overinvolved

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parenting in children’s low self-esteem may be more relevant for the individual who later goes on to develop dependent personality disorder (see the section on “Negative Sense of Self”).

Avoids Relationships A pathological absence of adequate nurturing and fulfilling social relationships is a shared feature of obsessive–compulsive, paranoid, schizoid, schizotypal, and avoidant personality disorders. The emotional unresponsiveness discussed in the earlier section “Restricted, Flat Affect” may play an important role in the inability to maintain adequate social relationships. Children with schizoid features have been described as having “an acutely constricted and underdeveloped affective life, with emotional distance in human relations” (Cicchetti & Olsen, 1990, p. 359). As mentioned earlier, the relation between schizoid and schizotypal personality disorders and schizophrenia, a disorder associated with several neurological impairments, may indicate a biological risk factor that is involved in the emotional unresponsiveness and social withdrawal observed in children who later develop these disorders. An important risk factor therefore may be a biological predisposition toward emotional unresponsiveness, and the processes involved in creating a vulnerability to the development of a personality disorder marked by distant relationships may begin as early as infancy. If the infant–caregiver bond is characterized by a secure attachment, the infant can learn to trust the caregiver, and this first relationship serves as a model for future relationships. As mentioned previously, it is plausible that an emotionally unresponsive infant may elicit less involvement from a caregiver and may make appropriate caregiving more difficult. A history marked by a series of insecure attachments may instill an inability to trust others, and this inherent distrust is a primary feature of paranoid personality disorder. On the other hand, a series of insecure attachments and a tendency to distrust others may develop instead into the ambivalence toward maintaining close interpersonal relationships that is characteristic of the individual with schizoid or schizotypal personality disorder. Thus, an insecure attachment may influence how an individual interacts with others, resulting in a deviant pattern of social interacting that worsens over time. Some infants have been identified as having an anxious–resistant attachment relationship with their caregivers. This type of relationship emerges when the caregiver is responsive to the child on some occasions but not others. In addition, the caregiver often disturbs or interferes with the child’s activity, such as playing with him when he is tired or hungry. This inconsistent noncontingent responding of the caregiver causes the child to exhibit anger and anxiety when distressed, such as seeking the caregiver for comfort but not being able to settle easily. The infant is thought to experience anxiety about the responsiveness of the caregiver. This pattern of interaction over time also teaches the child that his or her attempts to engage the environment

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are not effective. Thus, this insecure relationship can cause difficulties with both emotion regulation (experiencing prolonged anxiety or hypervigilance and difficulty calming when distressed) and a sense of self as unable to carry out meaningful behaviors in the environment that have the intended outcome (Bowlby, 1973; Cassidy, 1995; Sroufe, 1996). The development of this anxiety within the context of relationships is quite important for understanding avoidant personality disorder, which shares many similarities with social phobia/social anxiety disorder and is often conceptualized as a more severe form of this disorder (Liebowitz et al., 1998; Reich, 2001). Egeland, Sroufe, and colleagues (Warren, Huston, Egeland, & Sroufe, 1997) found that an anxious–resistant attachment at age 1 predicted the development of an anxiety disorder, including social phobia, at age 17. The relation between infant attachment and anxiety remained significant even after accounting for possible genetic contributions indexed by newborn temperament and maternal anxiety. This evidence supports the conclusion that an insecure attachment in infancy is a risk factor for the later development of avoidant personality disorder. Recall that within a developmental psychopathology model pathways of development are emphasized such that knowledge, resources, and skills gained in early negotiations with important tasks assist in the completion of future tasks. The child whose early caregiving experience is characterized by an anxious–resistant attachment with the caregiver will likely experience anxiety in his relationships but also in his approach to the major developmental tasks he encounters (Cassidy, 1995), such as negotiating peer relationships in school and developing autonomy as an adolescent and young adult. If the child continues on a pathway marked by failure in accomplishing these tasks, the child is at greater risk for psychopathology, particularly in the area of personality pathology (Shiner, Masten, & Tellegen, 2002). Although each of the personality disorders addressed in this section is characterized by a lack of fulfilling social relationships, the reasons underlying this social withdrawal differ among the disorders. Although persons with avoidant personality disorder long to form lasting relationships with others, they are plagued by feelings of inadequacy and fear of rejection (American Psychiatric Association, 1994). A possible developmental pathway associated with avoidant personality disorder in adulthood may begin with an infant with an anxious–resistant attachment history. This child is at risk for exhibiting a pattern of “passive withdrawal” with peers during childhood, including shyness, avoiding interactions, not participating, and needing direction from others (Renken, Egeland, Marvinney, Mangelsdorf, & Sroufe, 1989). Research on social withdrawal in children has identified a subtype of children, passive–anxious children, who exhibit this type of behavior with peers (Harrist, Zaia, Bates, Dodge, & Pettit, 1997). Passive–anxious children refrain from playing with other children because they are afraid of the social interchange (Rubin & Mills, 1988). These children tend to be easily aroused by unfamiliar situations (Harrist et al., 1997). This type of withdrawn behavior

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may be similar to the behavior of adults with avoidant personality disorder because these children would like to play with others but are too inhibited to engage in social activities. It is interesting to speculate whether the subtypes of social withdrawal among children also parallel the social reticence and avoidance descriptive of schizoid, schizotypal, or paranoid personality disorder. Whereas individuals with avoidant personality disorder are distressed by their lack of close relationships with others, those with schizoid or schizotypal personality disorder have no interest in maintaining social relationships. Further, the individual with paranoid personality disorder avoids relationships because of pervasive feelings of distrust and suspicion toward others. A second subtype of withdrawn children that has been identified is referred to as unsociable. In contrast to passive–anxious children described previously, unsociable children prefer playing by themselves (Harrist et al., 1997). These withdrawn children may demonstrate behaviors similar in function and appearance to adults with schizoid or schizotypal personality disorder who exhibit little desire to engage in social activities. This hypothesis is consistent with the finding that children who later developed schizophrenia were described by their kindergarten through 12th-grade teachers as being low in interpersonal competence (e.g., maturity level, group participation, popularity, and sociability; Lewine, Watt, Prentky, & Fryer, 1980). Poor social maladjustment and a reduced number of friends in childhood and adolescence appear to be common childhood precursors among adults with schizophrenia (Done, Crow, Johnstone, & Sacker, 1994). The third subtype of withdrawn children, active isolates, includes those who want to play with others but are rejected as play partners because of their aggressive behavior and/or lack of social skills (Harrist et al., 1997). In accordance with the social information-processing model described earlier, aggressive children may exhibit poor social skills, including the maintenance of a hostile attribution bias. For some individuals, it is possible that these negative peer interactions accumulate over time and contribute to the negative and hostile view of others that is prominent in individuals with paranoid personality disorder. Thus, the risk factor may be poor social skills and/or aggressive behavior; however, the mechanisms by which the individual becomes vulnerable to the development of paranoid personality disorder may involve the process by which this risk factor influences the child’s social system (e.g., peer rejection) and cognitive system (e.g., an intensification of a hostile attribution bias). In contrast to the anxious–resistant attachment history posited to serve as a risk factor for the anxiety characteristic of avoidant personality disorder, a different type of early attachment relationship, an anxious–avoidant attachment, may place a child at risk for this type of “active isolate” social avoidance in childhood. An anxious–avoidant attachment develops between an infant and the caregiver when the caregiver is rejecting or punitive in response to the infant’s signals that he or she is in need of care, attention, or soothing. A

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pattern of rejection by the caregiver when contact is sought leads the child to avoid others when distressed, instilling a view of others as unavailable, threatening, or even hostile (Sroufe et al., 2005). Children with this attachment history go on to exhibit aggressive behavior during preschool (Troy & Sroufe, 1987) and childhood, perhaps because they have learned that relationships with others are not rewarding and supportive but rather that “the vulnerable are exploited or pushed aside” (Renken et al., 1989, p. 277). These aggressive children go on to experience rejection by their peers (Coie, Dodge, & Kupersmidt, 1990). Considering peer rejection from a developmental psychopathology framework, it is important to examine the implications of failure at effective peer relationships in childhood. Children who are rejected by their peers do not have a setting in which to learn appropriate social skills and relationship-building skills such as sharing, trusting, cooperating, and generating intimacy. In fact, children who are not accepted by their peers have been found to be at an increased risk for future maladjustment (Parker & Asher, 1987). Early social withdrawal, therefore, may begin a process by which children become increasingly incapable of maintaining successful relationships with peers and ultimately with romantic partners. The vulnerability process may continue with increasing age because with better cognitive skills the manner in which individuals perceive the environment may play a larger role in the preference for social detachment. Whereas the interaction between children’s social context and neurological impairments pertaining to emotional unresponsiveness may be an especially important factor in the development of schizoid personality disorder, the formation of selfdefeating cognitive schemes may be particularly significant for the development of avoidant personality disorder. Early experience such as overly critical parenting and experiences of humiliation or rejection, in combination with a hypersensitivity to aversive stimuli, may cause these children to learn that they are ineffectual, impotent, and inconsequential (Millon & Davis, 1995). These individuals may develop cognitive schemes concerning their ineffectiveness to maintain relationships that, in turn, might lead to biased encoding of the unfavorable aspects of relationships and negative misinterpretations of benign interpersonal events. For example, it is likely that individuals with avoidant personality disorder develop social-cognitive biases, selectively encoding negative information and interpreting ambiguous information in a self-defeating manner. They may interpret an acquaintance’s failure to show up at a meeting as a direct indication that the acquaintance does not accept or approve of them. Further, biased comparisons of personal qualities and accomplishments with those of others may reinforce low self-esteem and feelings of worthlessness. With increasing age and independence, individuals also have more control over their environment such that persons uncomfortable with social situations may choose to remain in settings that suit their fear or ambivalence toward personal relationships (e.g., an isolated occupational setting). Such personal choices may exacerbate the lack of interpersonal skills of these individuals.

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Negative Sense of Self, or Lack of Self, to Exaggerated Sense of Self A core symptom of several of the personality disorders is a disturbed sense of self. A negative self-view is a key aspect of both avoidant and dependent personality disorders, an unstable self-image or lack of self is characteristic of borderline personality disorder (American Psychiatric Association, 1994), and an inflated self-image is an element of both narcissistic and histrionic personality disorders (American Psychiatric Association, 1994; Kernberg, 1989). Whereas an exaggerated sense of self represents one end of the continuum, the other end may be conceptualized as either a negative sense of self or a lack of a coherent sense of self. In congruence with a developmental psychopathology model, an exploration of the normative development of self-representations may offer clues to aberrant processes underlying the distorted view of the self that is inherent in certain types of maladaptive personality functioning in adulthood. Harter (1998) describes the typical pattern of the developing sense of self. Due to increasing cognitive skills that allow children to perceive the distinction between what they hope to achieve and what they actually can achieve (Crain, 1996), it is normal for children’s self-concepts to become more negative (less unrealistically positive) during middle childhood (Harter, 1982). In early adolescence, there may be a second decrease in self-esteem, followed by a slow increase over the later adolescent years (Marsh, 1989). Deviations in this normal pattern may be indicative of an increased potential for the development of one of the patterns of distorted self-concept characteristic of an adult personality disorder. For example, during the middle childhood years, a child who maintains the unrealistically high self-view characteristic of early childhood may be on a pathway toward developing narcissistic personality features (see Millon, 1981). Similarly, an adolescent who maintains the typically low self-esteem characteristic of early adolescence without undergoing the gradual increase in self-concept generally experienced by older adolescents may be on a pathway toward developing the chronic negative self-concept characteristic of persons with avoidant or dependent personality disorder. Thus, the question arises as to what mechanisms might be responsible for these deviations in the development of self-representations. Many normal processes in children appear to mirror symptoms of personality disorders in adults, suggesting that personality-disordered adults have adopted immature ways of dealing with the environment. This theory is consistent with the notion that some features of personality disorder represent immature patterns of behavior (Ryglewicz & Pepper, 1996). It is possible that overlearned behavioral patterns of childhood were maintained because they were effective, reinforced, or because the learning of new, more effective, behavior was somehow hindered. Thus, the following are possible processes in the development of the self that may serve as markers or liabilities for the development of the distorted self-representations characteristic of particular personality disorders.

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Negative Sense of Self Beginning in infancy, the development of a negative self-view may be fostered by internalization of the experience of the caregivers’ pattern of responsiveness. A consistent and responsive caregiver teaches the infant that he or she can elicit desirable events in the environment and more generally that the infant is effectual, worthy of care, and lovable. A caregiver who is rejecting or a caregiver who is inconsistent in responding to an infant’s attempts to garner attention, however, may set the stage for the child to learn that he or she is ineffectual and not worthy of attention. Sroufe (1990) has demonstrated that children with an insecure attachment history are rated as lower on self-esteem than those with secure attachment histories. With increasing age, cognitive processes may play an important role in creating a vulnerability toward personality disorders characterized by low self-esteem. Specifically, the child may be more sensitive to social cues that undermine his or her confidence or ability to be successful. The child may misinterpret ambiguous social information as indicative of his or her inferiority. This tendency to interpret an ambiguous situation negatively may lead to feelings of inadequacy, which, in turn, could result in a failure to complete a task. This failure may serve to reinforce the child’s initially incorrect interpretation of his or her ability. These reinforced processes involve the development and maintenance of a general sense of negative self-worth, characterized by inferiority and fear of negative evaluation, that may make the child vulnerable to a personality disorder such as avoidant personality disorder. The following processes involved in negative self-concept, however, may be more associated with dependent personality disorder because of their relation to helplessness and overreliance on others. Because it is generally during middle childhood that children more clearly realize the kind of individual that others might want them to become (Higgins, 1991), this period may be where the foundation is laid for excessive concern with the desires of others. It is in adolescence, however, that the opinions of others appear to have an overwhelming influence on an individual’s sense of self (Elkind, 1967; Lapsley & Rice, 1988). To deal with the perceived demands or opinions of others, many adolescents have reported engaging in “false-self behavior,” which includes “not saying what you think,” “expressing things you don’t really believe or feel,” and “changing yourself to be something that someone else wants you to be” (Harter, 1998, p. 581). Harter has suggested that some adolescents believe that they receive little support from important others and that they will only be able to obtain this limited support by meeting exceptionally high demands. These adolescents may “feel hopeless about pleasing others, which in turn causes them to suppress their true self as a potential means of garnering the desired support” (Harter, 1998, p. 581). Given the similarity between examples of “false-self behavior” and the symptoms of dependent personality disorder such as “has difficulty expressing disagreement with others because of

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fear of loss of support or approval” (American Psychiatric Association, 1994, p. 668), it makes sense that such behaviors may function as precursors to the development of this disorder. In addition, the proposed link between negative self-concept and the “fear of loss of support” typical of individuals with dependent personality disorder (American Psychiatric Association, 1994, p. 668) is mirrored in Gilligan’s (1982) argument that false-self behavior may be related to an individual’s notion that to reveal his or her particular opinions may damage close relationships. Individuals with dependent personality disorder also have “difficulty initiating projects or doing things on their own (because of a lack of selfconfidence in judgment or abilities rather than a lack of motivation or energy)” (American Psychiatric Association, 1994, p. 668). Another possible source of the negative self-concept related to an overreliance on others may involve the type of parenting a child receives. Although maltreatment has a direct negative impact on several domains of a child’s development (Cicchetti & Valentino, 2006), it has been specifically linked to the formation of a negative self-view. Fischer and Ayoub (1994) posit that maltreatment can lead children to believe that they are unimportant and useless, instilling within them the notion that they are generally “bad.” Maltreatment is an extreme example of negative parenting; however, more normative types of parenting may also influence a child’s sense of self. Caregivers who are sensitive to and helpful with their child’s efforts at achievement generally aid in the development of a positive self-image. For children with a negative sense of self, however, such outside involvement may indicate to the child that he or she is not capable of independent success (Harter, 1998). For example, Shell and Eisenberg (1992) have found that children who have already developed a notion that they are not smart tend to perceive assistance as a sign that they are incapable of accomplishing tasks on their own. This perception may lead to negative views of the self and to feelings of inadequacy. This example also highlights the role of the child’s subjective interpretation of social events in the maintenance of a negative self-image, as discussed previously.

Lack of Sense of Self The characteristics of borderline personality disorder such as “identity disturbance,” “unstable self-image or sense of self,” and “chronic feelings of emptiness” (American Psychiatric Association, 1994, p. 654) suggest that the individual with this disorder suffers from a lack of an integrated, coherent sense of self. This state is to be distinguished from a negative self-image because individuals with borderline personality disorder “at times have feelings that they do not exist at all” (American Psychiatric Association, 1994, p. 651). The changing self-image of individuals with borderline personality disorder involves shifting between viewing the self as all good or all bad (Ryglewicz & Pepper, 1996). This inability to integrate different facets of individuals, par-

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ticularly characteristics that are opposites, is common in normally developing children (Fischer, 1980). During early and middle childhood, children often separate these opposing qualities to such an extent that the idea that individuals may have aspects of both characteristics is difficult to comprehend. As mentioned earlier, it is normal for children to view themselves in an overly positive manner. Because children have difficulty integrating opposite characteristics, this overdistinction between “good” and “bad” tends to result in a “unidimensional or all-or-none thinking that typically leads to selfdescriptions that remain laden with virtuosity” (Harter, 1998, p. 570). Under adverse circumstances, however, this “all-or-none thinking” may have the opposite effect, leading a child to think that he or she is all bad (Harter, 1986). Thus, it seems logical that if individuals with borderline personality disorder partially maintain this earlier “unidimensional” thinking such that they view the self as all positive or all negative, it may result in both an unstable switching between positive and negative self-views and a general lack of a cohesive self-representation. Further, for most children, it is normal for the “all good” or “all bad” view of the self to be associated with specific external events. For example, if a teacher scolds a child, the child may think that he or she is a “bad” child. Between 7 and 8 years of age, however, children undergo a cognitive shift marked by moving away from associating negative feelings with absolute events that can change from situation to situation and also by an increasing tendency to compare oneself to peers. This process can affect self-evaluation by the formation of global attributions rather than event-related attributions (Cicchetti & Toth, 1995). The individual with borderline personality disorder, for example, may demonstrate an inability to make these global attributions but instead will rely on the more immature view of the self—that which is tied to absolute events and therefore fluctuates depending on the nature of the eliciting occurrence. For instance, events of perceived abandonment common in persons with borderline personality disorder may imply for these individuals that they are generally “bad.” Those individuals who continue to attribute their self-image to external events during adolescence may be especially at risk for identity problems. Damon and Hart (1988, cited in Harter, 1998) argue that “adolescents who do not move to the stage of internalized standards but continue to rely on external social standards and feedback will be at risk because they will not have developed an internalized, relatively stable sense of self that will form the basis for subsequent identity development” (p. 586). Adolescents are capable of thinking of themselves in a more abstract manner, for example by combining similar concepts into broader categories. An example might include conceptualizing oneself as “trustworthy,” a category that encompasses other notions of the self such as “responsible” and “honest” (Fischer, 1980; Harter, 1998). Adolescents, however, are still cognitively limited in their ability to integrate the abstract concepts that are opposite in nature (Harter & Monsour, 1992). In fact, self-constructs in middle adolescence are characterized by “an immature form of relating . . . abstract con-

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cepts to one another because one cannot yet integrate such self-representations in a manner that would resolve the apparent contradiction” (Harter, 1998, p. 573). This inability to meaningfully integrate abstract traits that are opposite in nature during adolescence has been linked directly with an unstable self-image that fluctuates between the two extremes (e.g., viewing oneself as extremely productive and creative at times but feeling inadequate and like a complete failure at another time; Harter, 1990). As stated previously, one experiential factor that may influence the continuation of this less well developed conceptualization of the self, and therefore may make an individual vulnerable to the development of borderline personality disorder, is child maltreatment. Physical and sexual abuse have often been identified as risk factors associated with the development of this disorder (Cicchetti & Olsen, 1990; Zanarini et al., 2002; Zelkowitz, Paris, Guzder, & Feldman, 2001). In an excellent example of a developmental approach to the examination of personality disorders, Rogosch and Cicchetti (2005) found that, in fact, maltreated children were more likely than nonmaltreated controls to exhibit a number of childhood precursors to adult borderline personality disorder. This maltreatment may encourage an immature conceptualization of the self. For example, Harter (1998) argues that in an abusive home “family members typically offer and continue to reinforce negative evaluations of the child that are then incorporated into the self-portrait. As a result, there may be little scaffolding for the kind of self structure that would allow the child to develop as well as integrate both positive and negative self-evaluations” (p. 571). This maltreatment at the hands of a caregiver is especially confusing for the child’s developing sense of self because the child’s abuser at times also fulfills the role of nurturer. It has been hypothesized that exposure to these opposing, contradictory roles of the caregiver may result in the child’s receiving conflicting messages about his or her self-worth. This contradictory view of the caregiver and the self may lead to a “disorganized” attachment style between the infant and caregiver. This attachment style is characterized by unusual, atypical behavior exhibited by the infant who cannot determine whether to turn to or retreat from the caregiver when distressed (Liotti, 1992; Main & Hesse, 1990; Sroufe et al., 2005). Child maltreatment (Briere & Runtz, 1988; Chu & Dill, 1990) and other trauma in general (Irwin, 1994) have been found to be related to dissociation, a symptom of borderline personality disorder that is associated with a lack of sense of self. Dissociation refers to the inability to integrate aspects of the self including “consciousness,” “memory,” and “identity” (American Psychiatric Association, 1994, p. 766) and can include amnesic or depersonalization experiences (Waller, Putnam, & Carlson, 1996). Dissociation is thought to be a defense mechanism enacted in response to trauma in order to protect the self (Putnam, 1994). “Self, in fact, refers to the integration and organization of diverse aspects of experience, and dissociation can be defined as the failure to integrate experience” (Ogawa, Sroufe, Weinfield, Carlson, & Egeland, 1997, p. 855).

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There are several ways in which dissociation, a lack of sense of self, trauma, and insecure attachment may be related. Ogawa et al. (1997) have demonstrated that having a weak sense of self during infancy and toddlerhood predicts dissociation during adolescence, suggesting that a less well developed sense of self may serve as a vulnerability factor for later dissociation. Further, anxious–avoidant attachment during infancy as well as disorganized attachment were associated with increased adolescent dissociative behaviors for individuals who had undergone substantial trauma. Thus, an insecure or disorganized attachment may serve as a vulnerability factor for later dissociation in the context of traumatic experiences. Ogawa et al. (1997) speculated that “the vulnerable self will be more likely to adopt dissociation as a coping mechanism because it does not have either the belief in worthiness gained from a loving and responsive early relationship or the normal level of defenses and integration that such a belief affords” (p. 15). This incoherent sense of self appears to be a highly important component of borderline personality disorder. A poor self-concept emerged among a host of other cognitive and affective variables (e.g., anger, depression, and locus of control) as the only variable that distinguished female adolescents who were comorbid for depression and borderline personality disorder from those suffering from depression only (Pinto, Grapentine, Francis, & Picariello, 1996). Thus, disturbances in self-concept during childhood and adolescence and how this risk factor may interfere with social, emotional, and cognitive processes may indicate vulnerability processes associated with the later development of borderline personality disorder.

Exaggerated Sense of Self On the other end of the continuum from negative sense of self or lack of self is an inflated self-view, another distorted view of the self that characterizes aspects of both narcissistic and histrionic personality disorders. Childhood precursors of such a self-concept are difficult to identify because most children typically boast excessively about their accomplishments, indulge in grandiose fantasies (Kernberg, 1989), and maintain an unrealistically positive view of the self (Harter, 1998). It is possible that individuals with narcissistic or histrionic personality disorder have carried this early pattern of grandiose selfappraisal into adulthood. This pattern of behavior may have been reinforced, or the child may have failed to develop appropriate skills that might have later served as a foundation for a more mature and realistic assessment of the self. In addition, although children generally describe themselves positively, many of them do not endorse purely virtuous attributes but also acknowledge that they are less than perfect (Cassidy, 1988). Thus, it may be that those children who do not acknowledge even minor faults may be on an early pathway toward developing a maladaptive overevaluation of their attributes and accomplishments. This grandiose view of the self may function to mask a negative self-

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concept. For example, individuals with narcissistic personality disorder demonstrate “a grandiose sense of self-importance,” “a sense of entitlement,” and arrogance (American Psychiatric Association, 1994, p. 661). Despite this aggrandizement, the inflated self-esteem and boasting behavior appears to belie an “invariably very fragile” self-esteem such that these individuals may become excessively distressed by criticism (American Psychiatric Association, 1994, p. 658). One process that may have predisposed the individual to adopt this pattern of masking feelings of inferiority with grandiosity may have been the early attachment process with the primary caregiver discussed previously. It appears that children with a history of an anxious–avoidant attachment may present with a pattern of self-representation that strikingly resembles that of the narcissistic personality. Specifically, despite observer, teacher, or counselor ratings of low self-esteem (Sroufe, 1990), some children with insecure attachment histories have been reported to describe themselves rather positively, suggesting that these children report high self-esteem to hide their feelings of worthlessness (Cassidy, 1988).

Peculiar Thought Processes and Behaviors In general, individuals with a personality disorder maintain thoughts and beliefs about events, people, or behaviors that most would consider maladaptive and are often unsubstantiated. For example, individuals with borderline, histrionic, or dependent personality disorder exhibit distorted beliefs concerning relationships, whereas persons with paranoid personality disorder may demonstrate untenable beliefs about the hostility of others. These individuals may behave in a manner that seems to perpetuate and reinforce these maladaptive thoughts, such that these beliefs appear to be understandable given the particular circumstances of the individual. Another category of eccentric thought processes—psychotic thoughts—includes those that are extremely unusual and not likely to be justified, given most circumstances. These thoughts and their associated behaviors include the “ideas of reference,” “unusual perceptual experiences,” “odd beliefs or magical thinking,” “belief[s] in clairvoyance, [or] telepathy,” and “odd thinking and speech” that characterize the individual with schizotypal personality disorder (American Psychiatric Association, 1994, p. 645). Persons with borderline personality disorder may also exhibit hallucinations, ideas of reference, and hypnagogic episodes (American Psychiatric Association, 1994). Psychotic processes include hallucinations, delusions, and formal thought disorder. Research on the development of these phenomena is limited (for a review, see Volkmar, Becker, King, & McGlashan, 1995). Hallucinations are perceptual experiences that lack an appropriate stimulus (American Psychiatric Association, 1994). Individual differences in vulnerability to hallucinations have been identified such that persons more vulnerable to hallucinatory experiences tend to be highly suggestible. Also, vulnerability to hallucinating has been associated with individuals who are overconfident in judging the

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source of experimentally produced perceptual events (e.g., determining the location of a sound; Bentall, 1990). Further, the experience of hallucinations has been related to difficulties distinguishing reality from imagination (Slade & Bentall, 1988). Delusions are beliefs that cannot possibly be true, given an individual’s social and cultural context. Delusions are not symptomatic of the personality disorders; however, a related phenomenon, ideas of reference, is characteristic of schizotypal personality disorder. Ideas of reference are notions that everyday occurrences, such as newspaper articles or television programs, have special importance—usually negative—for the individual (American Psychiatric Association, 1994). The individual does not exhibit the delusional intensity of such phenomenon but, rather, maintains some insight that the occurrence may not be real. In children and adolescents, symptoms of schizotypal personality disorder may include “bizarre fantasies or preoccupations” (American Psychiatric Association, 1994, p. 645). Possible precursors of ideas of reference and related unusual behavior may be identified during childhood. Children who later developed schizotypal personality disorder were rated by a psychiatrist interviewer as more “peculiar” (e.g., eccentric, queer, and awkward) than psychiatric and nonpsychiatric controls (Parnas & Jorgensen, 1989). Patterns of “odd thinking and speech” have also been detected in a highrisk sample of children (mean age, 15) who later developed schizotypal personality disorder. In this longitudinal prospective study, evidence of formal thought disorder was observed in these children (Parnas, Schulsinger, Schulsinger, Mednick, & Teasdale, 1982). Formal thought disorder refers to deviance in the form of thinking as demonstrated by vague, tangential, or incoherent speech as opposed to deviance in thought content (e.g., delusions or hallucinations). Assessing psychotic processes in children can be a daunting task, which makes research in this area difficult. Knowledge of normal development and abilities for particular age groups may be beneficial. For example, it may be difficult to determine the presence of psychotic processes in young children because of their limited language ability. Children may not be able to articulate their hallucinatory experiences (Volkmar et al., 1995). Also, it is normal for young children to have difficulty distinguishing what is real from fantasy (e.g., Ceci & Huffman, 1997), and this normative behavior must not be confused with hallucinatory experiences. Further, hallucinations have been observed to occur in normal but anxious children of preschool age (Volkmar et al., 1995). Behavior resembling loose associations and irrational thinking, two examples of formal thought disorder, are observed in normal children before the age of 7 (Caplan, Foy, Asarnow, & Sherman, 1990). Further, psychosis must be distinguished from normal behaviors that are similar in appearance (e.g., imaginary friends; Volkmar et al., 1995). For all of these reasons, identifying and researching antecedents to peculiar thought processes and behaviors may be difficult, and the ideas posited

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here should be considered speculative. It seems likely, however, that given the numerous biological correlates of the schizophrenia spectrum disorders, physiological risk factors may also play an important role in psychotic thought processes. Perhaps the combination of psychological vulnerability, such as an increased tendency to withdraw into fantasy, and a family history significant for a schizophrenia spectrum disorder is characteristic of children who later display personality pathology marked by eccentric thoughts and behavior.

Lack of Concern for Social Norms and the Needs of Others A lack of concern for the needs of others, as demonstrated by an inability to experience remorse or empathy, is characteristic of individuals with antisocial or narcissistic personality disorder. For individuals with antisocial personality disorder, this lack of concern for others may also be manifested in lying, cheating, and criminal behavior (American Psychiatric Association, 1994). Research on the cognitive, emotional, biological, and social interaction processes associated with empathy and the development of a conscience may offer insight into vulnerability to these disorders. One pathway toward a lack of concern for others might include an early avoidant attachment relationship, instilling a view of others as threatening or hostile. These children go on to exhibit aggressive behavior, as described previously. In families with a high level of coercive exchanges between parents and children, the child’s aggressive behavior is reinforced and encouraged (Patterson, 1982). These coercive exchanges include the caregiver giving in when the child’s problem behavior intensifies or to avoid the child’s aggressive outbursts (Dishion & Patterson, 2006). These coercive family interactions marked by hostility, anger, yelling, and aggression become the mainstay of the family environment such that children do not gain experience with self-regulatory and prosocial skills (Eisenberg & Fabes, 1998). Dishion and Patterson (2006) argue that this pattern of coercion, avoidance, and manipulation to the exclusion of effective training in self-regulation leads to deficits in empathic understanding. Research on adult psychopathy (Cleckley, 1976; Hare, 1993) also provides information on the development of a deficit in empathy and concern for others. Psychopathy is a syndrome involving behavioral deviance that is related to antisocial personality disorder. It is also characterized by a lack of remorse as well as related interpersonal difficulties such as insincerity, deceitfulness, and an inability to maintain meaningful, loving interpersonal relationships (Cleckley, 1976). Psychopathy has been associated with diminished autonomic and reflex responses to fearful and startling stimuli (for a review, see Patrick, 2007). This research suggests that individual differences in emotional reactivity, particularly in the fear response, may be one risk factor for the development of a lack of concern for others. As mentioned earlier in the discussion of impulsivity, emotions can regulate behavior in that varying intensities of different emotional responses are

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often associated with different actions. In general, children who display emotional indicators of sympathy often behave in a prosocial manner (Eisenberg & Fabes, 1998). Eisenberg and Fabes (1998) described a series of studies conducted with their colleagues in which children were exposed to videos designed to bring about an empathic response. Children’s demonstration of physiological indicators of empathy (e.g., measures of heart rate, facial expressions, and skin conductance) was associated with their tendency to engage in prosocial behavior toward others. When discussing rigidity, an overactive BIS was implicated in the expression of anxiety or negative affect (Gray, 1982). An underactive BIS, however, has been hypothesized to predispose an individual to remain relatively unaffected by punishment, setting the stage for later antisocial behavior (Quay, 1993). Thus, individuals with a reduced emotional response to empathy-inducing events may be at risk for the development of antisocial or narcissistic personality disorder. These risk factors must be examined within a social context to understand the processes relevant to the development of impaired empathy-related behaviors. Parents often assume initial responsibility for instructing their children about appropriate emotional and behavioral responses to events that children should “internalize” into standards for behavior. In her review on the development of conscience, Kochanska (1993) states that “the gradual developmental shift from external to internal regulation that results in a child’s ability to conform to societal standards of conduct and to restrain antisocial or destructive impulses, even in the absence of surveillance, is the essence and hallmark of successful socialization” (pp. 325–326). Harsh parenting may interact with cognitive and emotional risk factors in predisposing a child to developing an impaired sense of empathy. One example is offered by Dienstbier (1984), who argues that when children break a rule they become distressed and attempt to understand the cause of this discomfort. If parents are excessively negative, angry, and punishing, the child may attribute his or her negative feelings to external reasons (i.e., being discovered misbehaving by the parents). In contrast, parents who use a calm approach to discipline may be more effective in teaching the child to internalize standards of behavior because the child may be more likely to attribute the negative emotion to internal reasons. In another example of the role of parenting on empathy-related behavior, Kochanska (1993) proposes that the development of conscience involves meaningful interactions between the individual characteristics of the child and the parenting style used. Kochanska (1995) found that compliance in children is most likely to occur when the parent’s disciplinary style matches the child’s individual characteristics. Gentle discipline was effective in obtaining compliance in children who tend to be fearful; however, the subtlety of this parenting style did not elicit compliance in fearless children. For fearless children, compliance was instead related to maternal sensitivity and mutual engagement between the child and caregiver. Kochanska’s research is especially important, given the role of trait fearlessness in the development of psychopathy described previously.

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Conclusions Individual Differences The preceding discussion of vulnerability factors offers an account of meaningful individual differences in children that may be related to the future development of personality disorders. For example, it is hypothesized that individuals with a negative sense of self may be at an increased risk for avoidant or dependent personality disorder as compared to individuals with a positive self-concept. Nonspecific individual differences including age or gender also may be related to the previously discussed vulnerability factors and processes. First, vulnerability processes are related to the age of the child; for example, the development of an aberrant attachment relationship begins during infancy, whereas cognitive processes are not likely primary vulnerabilities until later in childhood. Further, it has been found that, in general, behavioral excess tends to decline, whereas solitary, isolated behavior tends to increase with age. With respect to gender, research has found that during childhood and adolescence males are more likely to exhibit impulsivity problems, physical aggression, and avoidant behaviors (McDermott, 1996). Nonspecific individual differences may also be related to personality disorders directly. In a sample of psychiatric adolescents, gender differences were generally not related to personality disorder diagnosis (assessed by DSMIII-R criteria), with the exceptions that females were more often diagnosed with borderline personality disorder whereas narcissistic personality disorder was found only among the males (Grilo et al., 1996). Age effects have also been noted in a separate clinical sample that included both adolescents and adults, such that individuals with a diagnosis of dependent personality disorder tended to be older as compared with individuals with other personality disorders. In addition, females constituted approximately 70% of individuals diagnosed with this disorder, in contrast with the approximately 60% female prevalence in other personality disorder categories (Loranger, 1996). Nonspecific individual differences have also been found to be associated with the measurement of personality disorders. In a prospective study of childhood risk factors associated with later personality pathology, Cohen (1996) has found that prediction was more precise among girls, particularly younger girls.

Implications for Intervention In this chapter, we have attempted to identify possible vulnerabilities to the development of personality disorders by conceptualizing the process within a developmental psychopathology framework. This perspective also has implications for intervention research and treatment. Proponents of the diagnostic system adopted in the DSM attempt to identify therapeutic interventions that benefit most individuals with the same diagnosis. A developmental perspective, however, suggests that treatment should not necessarily be dictated by

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how an individual’s behavior patterns are classified but, rather, by attention to the developmental pathway of each individual. Thus, persons who manifest similar behaviors (e.g., borderline features) may have arrived at this outcome from very different histories and patterns of success and failure throughout childhood and adolescence (Sroufe, 1997; Sroufe et al., 2005). Addressing the processes involved in particular outcomes may assist clinicians in creating treatment plans that take into account the development of a disorder rather than primarily addressing the similar behavioral outcome among a group of possibly heterogeneous individuals. Further, by identifying well-researched broad areas of functioning that may be antecedents or important components of adult personality disorders, it may be possible to direct preventative efforts at these personality dimensions. Such an approach would prevent the delay of treatment until maladaptive patterns of behavior become deeply ingrained and interact with one another to produce a full-blown psychiatric disorder. For example, whereas individuals with antisocial personality disorder may be highly resistant to psychotherapy, research on the developmental manifestations of empathy may be informative for interventionists and preventionists interested in targeting children who demonstrate deficits in empathy. In their review of empathic responding, Eisenberg, Wentzel, and Harris (1998) identify two processes, emotionality and regulation, that may be involved in children’s empathy, describe how to measure empathic feelings and behavior, and review several intervention programs designed to enhance empathy. By focusing on the processes of emotionality and regulation rather than on a similar behavioral manifestation (i.e., empathic responding), these researchers concluded that different types of interventions would be indicated for children who differ on these characteristics. Whereas children who become too emotionally distressed to be helpful to others might need assistance in regulation, those children who are generally less emotional may need help in identifying and understanding the emotions of others. Another treatment implication of the dimensional model used in this chapter involves a search for therapeutic intervention beyond the individual child. Traditionally, researchers develop treatment programs that are thought to benefit individuals who “have” a psychiatric disorder. General maladaptation during childhood, as described by extremes on the dimensions discussed earlier, does not necessarily reflect a disorder that a child has or does not have but, rather, implies problematic functioning within a particular domain. Thus, difficulties such as impulsivity or behaviors related to low self-esteem may be addressed by examining the context in which these negative behaviors are exhibited. For example, some researchers intervene to reduce aggressive behavior in children by altering family interaction patterns of negative reinforcement and coercion (Patterson, DeBaryshe, & Ramsey, 1989). Rather than emphasizing treatment research that conceptualizes these problems as a disorder endogenous to the child, a child’s treatment needs could be considered within his or her context (Sroufe, 1997).

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A developmental model allows researchers and clinicians to identify maladaptive behaviors that are not necessarily pathological in themselves but increase an individual’s risk for serious psychopathology. For example, substantial progress in exploring the developmental precursors of borderline personality disorder point to areas to target preventative efforts including family interactions (Fruzzetti et al., 2005; Ryan, 2005), children who exhibit low levels of the trait conscientiousness, and children with heightened sensitivity to relational conflicts and relationally aggressive behavior (Crick et al., 2005; Gunderson & Lyons-Ruth, 2008). Using normal developmental accomplishments as a guide, one can identify children who fail at important developmental milestones. Such an approach may bring more success to the commonly pessimistic prognosis of therapeutic intervention for individuals with personality disorders.

Future Directions Throughout the chapter, we have attempted to describe how several risk factors and vulnerability processes within different domains of developmental psychology might serve as fruitful avenues for the study of the antecedents of personality disorders. Longitudinal studies are necessary to test whether these processes in childhood predispose an individual to the later development of a personality disorder and whether these hypothesized precursors differentially predict the personality disorders as conceptualized in DSM. In addition to pointing toward the benefits of longitudinal research, the developmental psychopathology perspective adopted in this chapter has implications for the type of research that is conducted. A developmental approach would call for research that begins before the onset of a disorder. Despite similar symptom expression (and similar diagnostic labels), two individuals may have arrived at the disorder from different pathways. This information may shed light on heterogeneity within a particular disorder. For example, these individuals may have different prognoses or may be amenable to different types of treatment, given their unique developmental history (Sroufe, 1997). Future researchers should also consider normal developmental processes in their hypotheses and models of psychopathology. By studying the development of normal emotion regulation, strivings for perfection, sense of self, and other processes, researchers will better be able to identify when these processes are aberrant and indicative of increased risk for pathology. Throughout the chapter we examined childhood behaviors that were functionally or conceptually similar to symptoms of adult personality disorders. The developmental psychopathology perspective, however, reminds researchers that childhood symptoms need not be phenotypically similar to adult behaviors; rather, the hypothesized links between childhood and adult problems should appear logical, given what is known about normal development. For example, aggressive behavior in a preschool boy may not necessarily predict adult aggression because such behavior is more typical at this age. Similarly, apparently dependent behavior during toddlerhood is considered a healthy, developmentally

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appropriate behavior associated with future independence rather than pathological dependency. Thus, researchers should not limit their search for vulnerability factors by seeking out childhood symptoms that are identical to adult symptoms of disorder. Rather, researchers should strive to examine general patterns of adaptation in important developmental periods in order to identify childhood predictors of adult disorders that may appear, on the surface, to be quite distinct patterns of behavior (Sroufe & Rutter, 1984). Further, attention should be paid to normative personality processes during childhood. The difficulty in finding empirical research on childhood antecedents of personality disorders is understandable, given the lack of agreement concerning what constitutes normal personality development in children and how it should be measured. Grove and Tellegen (1991) suggest that the classification problems of the personality disorders may be partially addressed by considering the research on normal personality. They draw parallels between factor models of normal personality and personality disorder clusters in DSM. Further, by examining normal personality dimensions, they speculate that it would be possible to determine to what extent personality disorders represent problematic interactions among normal personality traits. In addition, research should address how various risk and protective factors influence one another to produce an outcome rather than studying any hypothesized variable in isolation (Masten, 1999). As mentioned earlier, not only do the social, cognitive, biological, and emotional systems influence one another, but also each of these systems is developing within an environmental context that plays an important role in the vulnerability process. Perhaps this attention to vulnerability processes within a particular context, as opposed to an emphasis on isolated risk factors, might pave the way for answering questions of specificity, for example, how a pattern of withdrawal or poor social adjustment during childhood may play a role in the development of schizoid personality disorder for one individual, avoidant personality disorder for yet another, and antisocial personality disorder for another individual. The answer may lie in how a particular risk factor interacts with other risk and protective factors within a given context. Current approaches examining the development of personality disorders are beginning to address these questions. For example, a recent review on the etiology of borderline personality disorder addressed the role of physiological reactivity, attachment relationships, and parenting styles (Gunderson & Lyons-Ruth, 2008). Although such a comprehensive approach to identifying the numerous variables and processes playing a role in the development of a particular disorder may appear daunting, by examining basic patterns of maladaptation within essential developmental tasks, patterns may appear that reliably predict psychopathology (Sroufe & Rutter, 1984). Further, data-analytic techniques have been developed to examine pathways of individuals by identifying both common and infrequent patterns in complex data sets (Bergman & Magnusson, 1997). Researchers, however, may be called on to address another challenging issue. Perhaps reliable antecedent processes will not be predictive of one particular personality disorder versus another because these disorders do not rep-

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resent coherent syndromes. As discussed previously, the current personality disorder taxonomy is problematic, as demonstrated by its low discriminant validity, the high rates of comorbidity, and insufficient coverage of general personality pathology. Sroufe (1997) challenges researchers to consider “classification schemes centered on patterns of adaptation and developmental trajectories” (p. 257) rather than using diagnoses as a “starting point for studying problem behaviors over time” (p. 255). Fortunately, research is beginning to move in this direction. A pioneering study by Shiner, Masten, and Tellegen (2002) found that successful completion of developmental tasks in childhood predicted personality in adulthood above and beyond consistency in personality traits across time. These researchers found that poor childhood adaptation was particularly associated with higher adult levels of the trait of negative emotionality (e.g., anxiety, anger, resentment, negative relationships, difficulty managing stress, hostile and untrusting of others), suggesting that examining a pattern of adaptation over time would be particularly important in the study of personality pathology. An investigation applying this developmental approach to the study of adult personality disorders, however, has yet to be conducted, but it would likely provide invaluable information about precursors to personality pathology. Thus, understanding the etiology of personality disorders will benefit from the exploration of normative and maladaptive development across biological, social, and emotional domains. Rather than examining adult personality disorders in younger and younger populations as an effort to understand etiology, the developmental perspective and the research outlined in this chapter support exploring the role of attachment as well as, for example, childhood self-concept, aggressive behavior, social competence, emotion regulation, and conscientiousness in the etiology of personality disorders in adulthood. In this manner, we are able to use our knowledge of normative development rather than a clinical diagnosis (of, at times, questionable validity) as our “starting point” for understanding vulnerability processes indicative of later psychopathology.

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Werner, N. E., & Crick, N. R. (1999). Relational aggression and social-psychological adjustment in a college sample. Journal of Abnormal Psychology, 108, 615–623. Westen, D. (1997). Divergence between clinical and research methods for assessing personality disorders: Implications for research and the evolution of Axis II. American Journal of Psychiatry, 154, 895–903. Westen, D., & Arkowitz-Westen, L. (1998). Limitations of Axis II in diagnosing personality pathology in clinical practice. American Journal of Psychiatry, 155, 1767–1771. Widiger, T. A. (2007). Alternatives to DSM-IV: Axis II. In W. O’Donohue, K. A. Fowler, & S. O. Lilienfeld (Eds.), Personality disorders: Toward the DSM-V (pp. 21–40). Los Angeles: Sage. Widiger, T. A., & Rogers, J. H. (1989). Prevalence and comorbidity of personality disorders. Psychiatric Annuals, 19, 132–136. Widiger, T. A., & Spitzer, R. L. (1991). Sex bias in the diagnosis of personality disorders: Conceptual and methodological issues. Clinical Psychology Review, 11, 1–22. Zanarini, M. C., Yong, L., Frankenburg, F. R., Hennen, J., Reich, D., Marino, M. F., et al. (2002). Severity of reported childhood sexual abuse and its relationship to severity of borderline psychopathology and psychosocial impairment among borderline inpatients. Journal of Nervous and Mental Disease, 190, 381–387. Zelkowitz, P., Paris, J., Guzder, J., & Feldman, R. (2001). Diathesis and stressors in borderline pathology of childhood: The role of neuropsychological risk and trauma. Journal of the American Academy of Child and Adolescent Psychiatry, 40, 100–105. Zimmerman, M. (1994). Diagnosing personality disorders: A review of issues and research methods. Archives of General Psychiatry, 51, 225–245.

Part III

Clinical Syndromes

Substance Use Disorders

Chapter 5

Vulnerability to Substance Use Disorders in Childhood and Adolescence L aurie Chassin, Iris Beltran, Matthew Lee, Moira Haller, and Ian Villalta

Substance use disorders (SUDs) have been considered “developmental” disorders because they show characteristic age patterns of onset and offset and because vulnerability may manifest differently at different ages (Sher & Gotham, 1999). Current taxonomy, as represented in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000), distinguishes between two major SUDs: substance abuse and dependence. Substance abuse is a maladaptive pattern of use accompanied by significant negative consequences (e.g., legal and social problems). Substance dependence, which is considered to be more severe, is a maladaptive pattern of use involving either psychological or physical dependence, including symptoms such as tolerance and withdrawal. However, recent findings have called into question the validity of the distinction between substance abuse and dependence and suggested that there is a single continuum of problems for both adults (Langenbucher et al., 2004) and adolescents (Hartman et al., 2008). Further, some substance abuse symptoms have been found to indicate a greater severity of the disorder than some of the dependence symptoms. These findings have led to proposed changes for the upcoming DSM-V (e.g., Martin, Chung, Kirisci, & Langenbucher, 2006). Current practice is to diagnose adolescents and adults with the same criteria. However, the developmental appropriateness of adult diagnostic criteria for adolescents has been questioned (Chung, Martin, & Winters, 2005). Compared to adults, adolescents have been reported to be more frequent “diag

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nostic orphans” whose symptoms are just below the diagnostic threshold for SUDs (Pollock & Martin, 1999), and this may reflect the developmental inappropriateness of adult criteria as applied to adolescents. For example, tolerance in adolescents may be overestimated because it is confused with normal patterns of learning to use substances among novice users (Caetano & Babor, 2006; Harford, Grant, Yi, & Chen, 2005). Similarly, adolescent withdrawal may be overestimated because of short-term physiological consequences of “binge” patterns of use (which are more common among adolescents than adults; Zeigler et al., 2005). The possible developmental inappropriateness of SUD criteria may explain why adolescents are more likely than adults to be diagnosed with substance dependence at low levels of use (Kandel et al., 2005; Langenbucher et al., 2000). Alternatively, adolescents may actually be more susceptible to substance dependence at lower levels of use because of their unique neurobiological characteristics (Hiller-Sturmhöfel & Swartzwelder, 2004–2005).

Epidemiology: Prevalence Rates of Adolescent Substance Use and SUDs National epidemiological data from the Monitoring the Future (MTF) project (Johnston, O’Malley, Bachman, & Schulenberg, 2007a) show that substance use is somewhat common by the end of high school. For instance, in 2006 past month rates of use among 12th graders were 45.3% for alcohol, 21.6% for cigarettes, 18.3% for marijuana, and 9.8% for other illicit drugs. However, adolescent SUDs are infrequent, especially before age 15. Rohde and Andrews (2006) reviewed the prevalence of SUDs in studies of representative samples and reported that among 16-year-olds the prevalence of nicotine dependence was approximately 15%, whereas the prevalence of alcohol and marijuana dependence was less than 5%. In emerging adulthood (ages 18–25), SUD rates reach approximately 25% for nicotine dependence and 15–30% for alcohol dependence, whereas rates of marijuana (5%) and other illegal drug dependence remain low (less than 5%). The prevalence of adolescent substance use has also changed over time. Since the early 2000s, overall adolescent substance use has been declining. However, declines in the popularity of certain drugs are often accompanied by rises in the popularity of new ones (Johnston et al., 2007a). For example, at the time of this writing (2008) there is concern about increases in adolescent use of ecstasy (MDMA), inhalants, steroids, and over-the counter medications containing dextromethorphan (DXM) such as cough syrup and cold remedies, and misuse of prescription drugs including sedatives/barbiturates, tranquilizers, and narcotics other than heroin (Johnston et al., 2007a; McCabe, Boyd, & Young, 2007; Substance Abuse and Mental Health Services Administration [SAMHSA], 2008). Substance use rates also vary as a function of demographic character-



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istics. Beginning in mid- to late adolescence, males report more substance use than do females (Johnston et al., 2007a). However, once substance use has been initiated, females reportedly progress to substance-related problems faster than do males (Ridenour, Lanza, Donny, & Clark, 2006). Substance use also differs across ethnic groups, such that lifetime substance use is highest among American Indians, followed (in order of decreasing lifetime use) by non-Hispanic Caucasians, Hispanics, African Americans, and Asian Americans (Kandel, 1995). Finally, there are conflicting data concerning socioeconomic status (SES). Some have found greater adolescent substance use among those low on SES indicators such as parental education (Chassin, Presson, Sherman, & Edwards, 1992) and parental occupation (Droomers, Schrijvers, Casswell, & Mackenbach, 2003), whereas others have found higher adolescent substance use in affluent suburban settings (Ennett, Flewelling, Lindrooth, & Norton, 1997; Hanson & Chen, 2007). Together, these studies might suggest a curvilinear effect of socioeconomic status on adolescent substance use, with higher rates of adolescent substance use found with both low and high SES. In low-SES neighborhoods, decreased social cohesion (Duncan, Duncan, & Strycker, 2002), greater acceptance of substance use, lower perceived harm (Lambert, Brown, Phillips, & Ialongo, 2004), and decreased after-school supervision (Luthar & Latendresse, 2005) have been found to mediate the effect of socioeconomic disadvantage on adolescent substance use. In highSES neighborhoods, popularity with peers, decreased availability/supervision from parents (Luthar & Latendresse, 2005), increased availability of family financial resources (Hanson & Chen, 2007), and increased achievement pressures (Luthar & Becker, 2002) have been found to mediate the effect of affluence on adolescent substance use.

Age-Related Trajectories of Adolescent Substance Use and SUDs Despite some variation across substances, there are characteristic age-related patterns of substance use, including onset during adolescence and peak rates of use (and SUDs) in emerging adulthood (ages 18–25). Declines in substance use typically begin in the mid-20s (Chen & Kandel, 1995; Johnston et al., 2007a, 2007b; Rohde & Andrews, 2006). However, these patterns represent normative age-related trends, and studies using mixture modeling have empirically identified multiple trajectories that capture developmental heterogeneity. These studies have often identified, in addition to abstainers, an earlyonset group (i.e., onset before 15), a late-onset group (around the end of high school), and a developmentally limited group (i.e., increasing use during the teens, which then declines during young adulthood). These groups have been identified for outcomes including cigarette smoking (Chassin, Presson, Pitts, & Sherman, 2000), binge drinking (Windle, Mun, & Windle, 2005), marijuana use (Ellickson, Martino, & Collins, 2004), and SUD symptoms (Clark, Jones, Wood, & Cornelius, 2006). Moreover, membership in the early-onset

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group has been associated with poorer outcomes on a variety of measures including SUDs (Chassin, Pitts, & Prost, 2002; Flory, Lynam, Milich, Leukefeld, & Clayton, 2004).

Mechanisms Underlying Age-Related Patterns The characteristic age patterns of adolescent onset, late adolescent escalation, and early adult declines in substance use and SUDs have often been interpreted as reflecting changes in social context. For example, it has been suggested that adolescent substance use initiation and escalation are related to the drive for independence and adult status (Jessor & Jessor, 1977) and the increasing freedom and peer exploration that typically characterizes adolescence (Bachman, Wadsworth, O’Malley, & Johnston, 1997; Bachman et al., 2002). Similarly, increases in substance use during late adolescence have been linked to departures from the parental home and parental supervision and the move to living situations and social environments (such as college) that are less restrictive and more tolerant of substance use (Bachman et al., 1997; Bachman et al., 2002). Finally, declines in substance use that occur during the mid- to late 20s have been linked to the assumption of adult roles such as marriage, work, and parenthood (Bachman et al., 1997; Bachman et al., 2002). An alternative (but not mutually exclusive) explanation has focused on maturational changes and the neurobiology of adolescent brain development. Research has suggested important developmental changes in brain systems that influence both reward sensitivity and cognitive control. Specifically, changes in dopaminergic systems (including changes in cortical and subcortical areas) occur early in adolescence and are thought to produce changes in sensation seeking and the salience of rewards, including increases in the reward value of peer social interactions (Chambers, Taylor, & Potenza, 2003; Gardner & Steinberg, 2005; Spear, 2000). In contrast, developmental changes in cognitive control systems continue until the mid-20s. These changes include synaptic pruning in prefrontal regions, increases in white matter, which occur with myelination, and increased connections among cortical areas as well as between cortical and subcortical areas (Paus, 2005). The differing developmental age courses in systems governing reward and motivation as compared to systems governing cognitive control and self-regulation are theorized to create a gap that places adolescents at an elevated risk for risky behavior in general and substance use in particular (Steinberg, 2007). Thus, the typical ages of substance use initiation occur during times of biologically based increases in sensation seeking and reward salience (particularly the salience of social and peer rewards) coupled with a less than fully mature cognitive control system. In the mid-20s, age-related declines in substance use occur during a time of maturation of the cognitive control system. In addition to developmental changes in neural systems governing selfregulation and reward, adolescents may also be particularly biologically vulnerable to substance use effects (Spear, 2000; Levin, Rezvani, Montoya, Rose,



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& Swartzwelder, 2003). These theories posit not only that adolescence will be a period of substance use onset but also that, because adolescents may derive more positive physiological effects (and/or less negative effects) from the use of tobacco, alcohol, or other drugs, initiation of substance use during adolescence (compared to adulthood) will also be associated with more rapid increases in consumption. Indeed, animal studies have shown that initial exposure to substances (e.g., nicotine) during adolescence produces greater subsequent self-administration than does initial exposure during adulthood (Slotkin, 2002). Another psychobiological explanation of the timing of adolescent onset of substance use notes that adolescent substance use is associated with the pubertal transition—specifically, with early puberty among adolescent girls (Ge et al., 2006; Lanza & Collins, 2002). These findings have been replicated in a sample of adolescent twin girls who were discordant for pubertal timing (Dick, Rose, Viken, & Kaprio, 2000) even after controlling for confounding between-family factors that are associated with early maturation. Findings for boys have been more mixed, with studies of European youth suggesting greater risk for substance use among early maturers (Dick & Mustanski, 2006) and those of American youth finding effects for both early (Costello, Sung, Worthman, & Angold, 2007) and late maturers (Ge et al., 2006).

Research Approaches and Methodological Issues There is a large empirical literature studying child and adolescent populations that focuses on describing trajectories of substance use as well as identifying correlates and prospective predictors of use. These include longitudinal studies of school-based samples (e.g., Bentler, 1992; Chassin, Presson, & Sherman, 1984; Jessor & Jessor, 1977; Johnston et al., 2007a; Kandel, Yamaguchi, & Chen, 1992), and community samples (e.g., Brook, Whiteman, Cohen, Shapiro, & Balka, 1995; Bates & Labouvie, 1997; Costello et al., 2007), birth cohort samples (e.g., Fergusson, Horwood, & Ridder, 2007), and samples who have received preventative interventions aimed at deterring substance use (e.g., Botvin, Baker, Dusenbery, Botvin, & Diaz, 1995; Bricker, Anderson, Rajan, Sarason, & Peterson, 2007; Hawkins, Kosterman, Catalano, Hill, & Abbot, 2005). Studies that follow large samples for long time periods make important contributions to describing the natural history of substance use and its vulnerability factors. However, they are often limited by small representations of clinical substance disorders, and the large sample sizes often preclude in-depth multilevel, multimethod assessments. Another approach has been to focus on high-risk samples, most typically on offspring of alcoholic or drug-abusing parents (Chassin, Curran, Hussong, & Colder, 1996; Sher, Walitzer, Wood, & Brent, 1991; Tarter, Kirisci, & Clark, 1997; Zucker, Ellis, Bingham, &

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Fitzgerald, 1996) but also on other risk groups such as those with externalizing disorders (e.g., Molina, Pelham, Gnagy, Thompson, & Marshal, 2007). Many of these studies have been able to use more intensive assessment methods, including psychophysiological assessment (e.g., Harden & Pihl, 1995) and neuropsychological assessment (Ozkaragoz & Noble, 1995; Tarter, Jacob, & Bremer, 1989), but are often restricted to smaller samples than are the general population or school-based studies. Finally, a small but rapidly growing number of studies have focused on clinical populations of adolescents with SUDs (e.g., Brown, 1993a; Brown, Myers, Mott, & Vik, 1994; Chan, Dennis, & Funk, 2008; Martin, Kaczynski, Maisto, & Tarter, 1996). Although these studies are the most clinically relevant, it is difficult to draw inferences about vulnerability factors because researchers are unable to separate the antecedents of SUDs from the effects of those disorders. One challenge for longitudinal research is to determine an appropriate time lag between measurements, and studies are often limited by long time intervals in between assessments, which cannot capture the “real-time” dynamic processes and contextual influences underlying adolescent substance use. To better address these questions, some studies use experience sampling—that is, employing diaries or hand-held electronic devices that participants access multiple times per day while they are in the natural environment (e.g., Hussong, Gould, & Hersh, 2008; Whalen, Jamner, Henker, Delfino, & Lozano, 2002). Experience sampling studies are better suited to capturing etiological processes that have short-term lags of effect. However, they also have limitations in terms of relatively brief assessment, short-term follow-up, and smaller sample sizes. Finally, recent interest in gene–environment interplay has produced a rapidly expanding literature using molecular and behavioral genetic methods to study adolescent substance use (see, e.g., Hopfer, Crowley, & Hewitt, 2003 for a review) and greater use of genetically informative samples (e.g., Iacono, Carlson, Taylor, Elkins, & McGue, 1999; Dick et al., 2007). For the current chapter, summarizing and interpreting the empirical literature on vulnerability to SUDs present several challenges. First, much of the child and adolescent literature is restricted to substance use rather than problem use, or disorders. Thus, our review includes vulnerability to substance use as well as abuse/dependence. Second, vulnerability for SUDs includes both factors that are common across multiple drugs and those that are drug-specific. For example, children who are prone to conduct problems are at heightened risk for a range of substance use and SUDs. Thus, conduct problems are a common vulnerability factor for the use and abuse of different types of drugs. In contrast, other risk factors are drug-specific. For example, the influence of advertising may increase risk for alcohol or cigarette use but not for the use of illegal drugs. Because a single chapter cannot do justice to the complexity of substance-specific pathways of vulnerability, we will focus on common vulnerabilities. Moreover, it is necessary to choose some operational definition of childhood and adolescence in order to focus our discussion. Given the age-related epidemiological patterns of substance use and SUDs, the current



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chapter will focus on populations from childhood up to the early 20s. Finally, to organize the large number of vulnerability factors that have been proposed, we draw on three multivariate, biopsychosocial models of risk (Sher, 1991). These pathways, which are not mutually exclusive, are “deviance proneness” (focusing on substance use as part of a broader disposition to disinhibited behavior), stress and negative affect pathways (focusing on substance use as a way of coping with stress and negative affect), and substance use effects pathways (focusing on individual differences in the experience of substance use effects). Each of these pathways considers multiple biopsychosocial factors influenced by interactions of genetic and environmental factors (for reviews, see Chassin, Hussong, & Beltran, 2009; Sher, 1991).

Genetic Influences Although a complete review is beyond the scope of this chapter, Hopfer et al. (2003) reviewed the behavioral genetic literature and reported that both genetic and environmental influences (shared and nonshared) were important for adolescent substance use. Shared environment influences are those that are common to siblings within families, such as family environment. Hopfer et al. (2003) found some variation across substances, and heritability was stronger for tobacco use than for alcohol or marijuana use. Similarly, heritabilities appear to differ, depending on the “stage” of substance use. For example, Rhee and colleagues (2003) found that “problem substance use” showed greater heritability and weaker shared environment effects than did substance use initiation (see also Pagan et al., 2006). Given that adolescence is the period of substance use initiation, these shared environment effects on initiation are consistent with the finding that the adolescent literature (compared with the adult literature) also shows more shared environment effects (Han, McGue, & Iacono, 1999; Pagan et al., 2006). Finally, some studies of gene–environment interaction have suggested that religiousness (Koopmans, Slutske, van Baal, & Boomsma, 1999; Timberlake et al., 2006) and family functioning (Dick et al., 2007; Nilsson et al., 2005; Nilsson, Wargelius, Sjoberg, Leppert, & Oreland, 2008) moderate the effects of genetic influence. In terms of candidate genes, studies have focused on factors from the multiple pathways that are hypothesized to underlie substance use effects (recognizing that substance use is a complex phenotype that will be influenced by multiple interacting genes and gene–environment interactions). For example, the deviance proneness pathway is reflected in studies of candidate genes that are related to disinhibition and behavioral undercontrol such as the MAO-A gene (Nilsson et al., 2008), genes involving the serotonin transporter (Nilsson et al., 2005), and variants of the GABRA2 gene (although these effects may not appear in childhood, Dick & Mustanski, 2006). The deviance proneness pathway may be particularly important for genetic investigation because behavioral undercontrol has been viewed as the common heritable characteristic that underlies the use of different substances either individually or in com-

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bination as polysubstance use, which is common among adolescents (Iacono, Malone, & McGue, 2008; McGue, Iacono, & Krueger, 2006; Zucker, 2006). The stress and negative affect regulation pathway is reflected in studies of genes that involve affect regulation and reward salience, including the dopamine pathway (Audrain-McGovern, Lerman, Wileyto, Rodriguez, & Shields, 2004; Laucht, Becker, El-Faddagh, Holm, & Schmidt, 2005) and CHRM2, which is linked to the combination of alcohol dependence and depression (Nurnberger & Bierut, 2007). Finally, the substance use effects pathway focuses on genes that influence the metabolism of substances, which might influence the experience of substance use effects. Examples include studies of CYP2A6, which inactivates nicotine to cotinine (Audrain-McGovern et al., 2007; O’Loughlin et al., 2004), and studies of genes influencing alcohol metabolism (Nurnberger & Bierut, 2007). In general, findings from genetic studies of adolescent substance use echo the conclusions of Lessov and colleagues (Lessov, Swan, Ring, Khroyan, & Lerman, 2004) from the adult data: although heritable factors are important, there are also important environmental influences (particularly on substance use initiation). SUDs are the result of complex interactions among multiple genes and likely also interactions between genetic and environmental factors. Moreover, inconsistencies in findings may reflect variations in study designs, sample ascertainment, and the phenotypes that are studied.

Prenatal Exposure Family history risk can also exert influence through fetal exposure (see Glantz & Chambers, 2006, for a review). In human studies, it is difficult to isolate the effects of prenatal exposure from genetic risk and postnatal environmental risk. However, animal models have found effects of prenatal exposure to alcohol on subsequent alcohol intake (Chotro, Arias, & Laviola, 2007). Baer, Barr, Bookstein, Sampson, and Streissguth (1998) found that prenatal exposure to alcohol raised risk for adolescent drinking above and beyond a family history of alcoholism. However, Cornelius, Leech, Goldschmidt, and Day (2005) showed that the effects of prenatal exposure on tobacco use were no longer significant, once co-occurring risk factors were considered. Glantz and Chambers’s (2006) review concluded that prenatal exposure was best viewed as a modest direct contribution to vulnerability to drug abuse.

Deviance Proneness Models Sher’s (1991) deviance proneness model analyzes the development of SUDs within the broader context of antisocial behavior, and consequently its theoretical bases are similar to those that attempt to explain the etiology of conduct problems and antisociality (e.g., Patterson, 1986). This model posits that parenting behavior, temperament, peer influence, and cognitive characteristics interact to produce drug and alcohol outcomes. That is, ineffective parenting,



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in combination with a child’s difficult temperament and high impulsivity, is hypothesized to lead to poor academic performance, which leads to affiliation with substance-using peers. Data support the association between adolescent substance use and traits that reflect behavioral undercontrol, including unconventionality, novelty/sensation seeking, aggression, impulsivity, and an inability to delay gratification (Bates, 1993; Hawkins, Catalano, & Miller, 1992). These traits in early childhood are longitudinally predictive of later substance use (Block, Block, & Keyes, 1988) and problems (Caspi, Moffitt, Newman, & Silva, 1996). Interestingly, these characteristics are also found more frequently among children of alcoholics (COAs), who are at elevated risk for substance-related problems (Carbonneau et al., 1998). Researchers have identified several biobehavioral markers of behavioral undercontrol and risk for adolescent substance use. For instance, reduced P3 amplitude predicts drinking onset (Iacono et al., 1999) and is seen in COAs even before the onset of drinking (Begleiter & Porjesz, 1999). P300 is heritable and may represent an endophenotype underlying the genetic vulnerability to externalizing disorders (Hicks et al., 2007). Other biobehavioral markers of behavioral undercontrol and risk for substance use are neurochemical and neuroendocrine reactivity (Tarter et al., 1999) and ability to modulate autonomic nervous system activity (Iacono et al., 1999). The effects of temperamental characteristics on substance use may be modified by environmental factors such as parental control and support (Wills, Sandy, Yaeger, & Shinar, 2001). King and Chassin (2004) found a “protective but reactive” interaction in which parent support buffered the effects of behavioral undercontrol, but these protective effects were lost at the highest levels of behavioral undercontrol. Deficits in executive functioning have been suggested as vulnerability factors for adolescent SUDs. Sons of substance-abusing fathers perform more poorly than do controls on tests of executive functioning (Harden & Pihl, 1995) and show deficits on sustained attention, motor restraint, and abstract reasoning in problem solving (e.g., Aytaclar, Tarter, Kirisci, & Lu, 1999). Cognitive deficits have also been found among adolescents with SUDs (e.g., Sher, Martin, Wood, & Rutledge, 1997). For example, relative to youth without alcohol problems, alcohol-dependent adolescents had poorer retention of verbal and nonverbal information, poorer attentional capacity, deficits in visual–spatial planning (Tapert & Brown, 1999), and poorer executive functioning (Giancola, Mezzich, & Tarter, 1998). Similarly, risky decision making on laboratory tasks such as the IOWA gambling task (Bechara et al., 2001; Stout, Rock, Campbell, Busemeyer, & Finn, 2005) has been related to adolescent substance use and to college student binge drinking (Goudriaan, Grekin, & Sher, 2007). However, decision-making performance on laboratory tasks is not necessarily correlated with measures of impulsivity (Goudriaan et al., 2007) and can be influenced by factors other than a focus on immediate reward (Stout et al., 2005) so that the factors driving performance on these

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tasks are complex. Moreover, cognitive deficits among those with SUDs may reflect either preexisting vulnerability factors or the effects of substance use, or both. Ineffective parenting is hypothesized to moderate the relation between deficits in self-regulation and the development of substance use problems by increasing the likelihood of school failure and affiliation with deviant peers. Longitudinal studies have found that high levels of parental monitoring, discipline, and social support are associated with a lower likelihood of adolescent substance use (Nowlin & Colder, 2007; Van der Vorst, Engels, Meeus, & Dekovic, 2006). Deficits in these aspects of parenting are found in alcoholic and drug-abusing families (Chassin et al., 1996; Zucker et al., 1996). Data also suggest that adolescent substance use may be related to parents’ specific socialization about the use of substances (e.g., discussions about substance use, rules about use; Chassin et al., 2005; Van der Vorst et al., 2006). Children who are temperamentally underregulated, receive ineffective parenting, and have cognitive deficits are at heightened risk for school failure (Patterson, 1986). School failure may elevate risk for the onset of adolescent substance use through several mechanisms (Townsend, Fisher, & King, 2007). Adolescents with poor grades (Cox, Zhang, Johnson, & Bender, 2007), low educational aspirations (Paulson, Combs, & Richardson, 1990), poor school connectedness (Bond et al., 2007), and low expectations for achieving academic success (Jessor & Jessor, 1977) are more likely to use alcohol or drugs. Moreover, low school achievement prospectively predicts substance use across ethnic groups (Bryant, Schulenberg, Bachman, O’Malley, & Johnston, 2000). Adolescents who experience school failure are also more likely to affiliate with peers who themselves use substances. Numerous studies have found that adolescent substance use can be predicted from that of their friends (Hawkins et al., 1992; Kandel, 1978), and the correlations between friends’ use and adolescent substance use are still significant when peers are surveyed directly (Kandel, 1978). Moreover, longitudinal studies suggest that both peer influence (in which drug-using peers influence adolescents’ behavior) and peer selection (in which drug-using adolescents seek out similar friends) contribute to the prediction of adolescent substance use (Curran, Stice, & Chassin, 1997; Kandel, 1978). Fowler et al. (2007) found that a significant amount of the variation in twin reports of peers’ substance use was explained by genetic influences, thereby suggesting that peer selection is genetically influenced. Interestingly, the presence of non-drug-using peers in one peer context (e.g., within a close friendship group) can offset the risk in another context (e.g., within larger peer groups, Hussong & Hicks, 2003). Finally, Sussman, Dent, and McCullar (2000) found that adolescent drug use was related to membership in adolescent cliques and may serve to communicate particular social images that are characteristic of certain peer groups (Barton, Chassin, Presson, & Sherman, 1982). Finally, the deviance proneness model suggests that adolescent SUDs are



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part of a broader pattern of conduct problems, and the link between adolescent SUDs and conduct problems has received consistent empirical support (Hawkins et al., 1992; Zucker, 2006). For instance, conduct problems and aggression predict adolescent substance use (Henry et al., 1993; Kellam, Brown, Rubin, & Ensminger, 1983), escalations in use over time (Hill, White, Chung, Hawkins, & Catalano, 2000; Hussong, Curran, & Chassin, 1998), shorter trajectories from drinking onset to alcohol disorder (Hussong, Bauer, & Chassin, 2008), and later substance diagnoses (Fergusson et al., 2007; Pardini, White, & Stouthamer-Loeber, 2007) among both male and females (Chassin, Pitts, De Lucia, & Todd, 1999; Costello, Erkanli, Federman, & Angold, 1999; Disney, Elkins, McGue, & Iacono, 1999). The association with conduct problems is strongest for illicit drug use and SUDs, as opposed to licit substance use (Disney et al., 1999). Moreover, Markon and Krueger (2005) examined models of a common externalizing liability to antisociality and SUDs and found that the best-fitting model was graded and continuous, as opposed to categorical and class-like. Attention-deficit/hyperactivity disorder (ADHD ) has been related to adolescent substance use in clinic-referred (Molina & Pelham, 2003) and nonclinic samples (Disney et al., 1999) but not all samples (Costello et al., 1999). The effects of ADHD are magnified when conduct disorder is present (Flory, Milich, Lynam, Leukefeld, & Clayton, 2003) and sometimes becomes nonsignificant once conduct disorder or problems are controlled (Fergusson et al., 2007; Pardini et al., 2007). These findings suggest that the relation between ADHD and substance use may be spurious or that ADHD symptoms contribute to later conduct problems, which, in turn, increase the likelihood of adolescent substance use. Inconsistencies across studies may also be due to age specificity of ADHD effects on later substance use (Molina et al., 2007) or differing effects of ADHD across substances (Burke, Loeber, & Lahey, 2001).

Vulnerability to SUDs through Negative Affect Pathway The negative affect pathway hypothesizes that individuals use or abuse substances in order to regulate or cope with negative affect (Colder, Chassin, Villalta, & Lee, 2009). According to negative affect models, children and adolescents who are temperamentally prone to experience high negative affect (e.g., high neuroticism) and/or experience high levels of environmental stress that result in negative affect may be at risk for substance use and SUDs. Numerous cross-sectional studies have shown that high negative affect and depression commonly co-occur with adolescent alcohol use (e.g., Costello et al., 1999), heavy drinking (e.g., Rohde et al., 1996), drug use (e.g., Waller et al., 2006), and nicotine use/dependence (see Kassel, Stroud, & Paronis, 2003, for a review). In community samples, adolescent SUDs and depression cooccur about 20–30% of the time, although studies on the association between

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SUDs and adolescent anxiety disorders generally show weak and inconsistent results (Armstrong & Costello, 2002). In addition, stressful life events have been found to correlate with adolescent substance use and with increased use over time (Dube et al., 2006; Hussong & Chassin, 2004). Moreover, adolescents with heightened reactivity to stress (Conrod, Petersen, & Pihl, 1997), poor modulation of stress responses (Moss, Vanyukov, Yao, & Irillova, 1999), and deficient coping skills (Kassel, Jackson, & Unrod, 2000) may be at high risk for substance use/abuse, particularly if they are also low in self-regulation (Eisenberg, 2000). Prospective effects of stress and negative affect on adolescent substance use have been less consistently obtained. Moreover, because adolescent substance use/abuse is frequently associated with conduct problems, which covary with negative affect, it is unclear whether negative affect has a unique effect on adolescent substance use/abuse beyond conduct problems. Although several studies suggest that internalizing symptoms prospectively predict early substance use initiation (King, Iacono, & McGue, 2004), marijuana use and dependence (Wittchen et al., 2007), alcohol use/abuse (Mason, Hitchings, & Spoth, 2007; Sung, Erkanli, Angold, & Costello, 2004), and smoking (Dierker, Vesel, Sledjeski, Costello, & Perrine, 2007), the effect is weak, compared to the effects of externalizing symptoms. Other studies have failed to find a unique effect of negative affect beyond externalizing symptoms (e.g., Hallfors, Waller, Bauer, Ford, & Halpern, 2005). Interestingly, adolescents with high levels of both depressive symptoms and conduct problems are at particularly high risk for heavy alcohol use (Pardini et al., 2007). These inconsistent findings suggest that the relation between negative affect and substance use may be quite complex, with many factors influencing the strength of the relation and the temporal ordering. For instance, various components of negative affect (e.g., depression, anxiety, anger) may differentially relate to substance use (Swaim, Oetting, Edwards, & Beauvais, 1989). Moreover, although few studies have considered low positive affect separate from negative affect, some have found that low positive affect predicts escalation of use (Wills, Sandy, Shinars, & Yaeger, 1999) and interacts with poor self-regulation to predict substance use problems (Colder & Chassin, 1997). In addition to differing types of negative affectivity, inconsistent results may be due to an inappropriate time lag between measurements of stress/ affect and drinking behavior. Recent studies using experience sampling reveal that adolescents and young adults tend to drink immediately after experiencing a stressful event (Park, Armeli, & Tennen, 2004). Thus, typical self-report measures that aggregate reports of negative affect and substance use behavior over long periods of time may not accurately capture their relations. Experience sampling methods also indicate a relation between high positive affect and substance use (e.g., Park et al., 2004; Rankin & Maggs, 2006), suggesting that adolescents and young adults use substances not only for self-medicating purposes but also for celebratory purposes. The relation between negative affect and substance use may also vary



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depending upon the presence of moderator variables. Several studies have indicated that positive expectancies about the effectiveness of substance use as a coping mechanism exacerbate the influence of negative affect on substance use (Hussong, Galloway, & Feagans, 2005; Kassel et al., 2007). AudrainMcGovern et al. (2004) found that the DRD2 A1 allele interacted with depressive symptoms to predict the progression of smoking among experimenters. Finally, gender may moderate the relation between negative affect and substance use such that the relation may be stronger for females than for males (e.g., Armstrong & Costello, 2002; Poulin, Hand, Bandreau, & Santor, 2005). For instance, after controlling for the greater prevalence of SUDs among boys, girls who are depressed and use substances are significantly more likely to develop SUDs than are boys (Hallfors et al., 2005; Poulin et al., 2005).

Vulnerability to SUDs through Sensitivity to Reinforcing Effects The enhanced reinforcement model focuses on individual differences in the pharmacological effects of substances. Individuals who are relatively more sensitive to the reinforcing effects of substances and/or less sensitive to their adverse effects will be likely to use substances more frequently and in larger amounts, thus placing them at increased risk for SUDs. Studies that administer substances to participants provide the most direct test of this hypothesis. However, given ethical and legal considerations, these studies have been largely limited to participants who are over age 21, and most have been done with alcohol. Consistent with the enhanced reinforcement hypothesis, several studies have found that a moderate dose of alcohol dampens psychophysiological response to laboratory stressors in nonalcoholic Caucasian college-age subjects, particularly for those whose personality profiles and/or family histories place them at high risk for alcoholism (Finn, Zeitouni, & Pihl, 1990; Levenson, Oyama, & Meek, 1987; Sher & Levenson, 1982). In addition, other studies have found that sons of male alcoholics are less sensitive to the negative effects of alcohol. A series of studies by Schuckit and colleagues (e.g., Schuckit & Smith, 1996) found that sons of male alcoholics who had particularly low levels of negative responses to an alcohol challenge (measured subjectively by feelings of intoxication and objectively by body sway) were more likely to receive SUD diagnoses over the subsequent decade. In addition, adolescents’ lower levels of self-reported response to alcohol were related to their serotonin transporter genotype (Hinkers et al., 2006). Although alcohol challenge studies are typically not conducted using children and adolescents, animal data have suggested that adolescent animals may show heightened sensitivity to positive effects and lessened sensitivity to aversive effects as compared to adult animals (Slotkin, 2002; Spear, 2000). Relevant human data focus on perceptions of substance use effects. For instance, Zucker, Kincaid, Fitzgerald, and Bingham (1995) found that

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preschool-age children of alcoholics possessed more knowledge about, and were better able to identify, alcoholic beverages relative to controls, suggesting that alcohol-related cognitive schemas are detectable early in development and prior to the ingestion of alcohol. Because these subjects were too young to drink, it is unclear whether these early schemas truly reflect vulnerability for alcohol use. However, other longitudinal studies have found that adolescents who have positive expectancies about the effects of alcohol (e.g., social facilitation, increased arousal, improvement of cognitive/motor functioning) are more likely to initiate drinking (Christiansen, Smith, Roehling, & Goldman, 1989) and to continue their use of alcohol over time (Smith, Goldman, Greenbaum, & Christiansen, 1995). Continued affirmation of positive alcohol expectancies in late adolescence may be prognostic for the development of alcohol abuse and/or dependence in adulthood (Brown, Creamer, & Stetson, 1987). Similarly, individual differences in reported effects of initial tobacco use are predictive of adolescent nicotine dependence (Kandel, Hu, Griesler, & Schaffran, 2007), and affirmation of drug-specific expectancies for marijuana and cocaine distinguish between college students who do and do not use each of these drugs (Brown, 1993b; Schafer & Brown, 1991). Some studies suggest that cognitions and perceptions about the pharmacological effects of alcohol and drugs are implicitly represented in semantic memory networks whose activation influences the decision to use. Stacy, Ames, Sussman, and Dent (1996) found that substance-specific measures of memory association were correlated with alcohol and drug use in adolescents, and longitudinal research with college students showed prospective prediction (Stacy, 1997). More recently, researchers have expanded on this work to use a variety of indirect measures of implicit attitudes toward substance use. For example, studies have found that implicit attitude measures add significant explained variance (over and above direct measures of beliefs) in predicting adolescent alcohol use (Thush et al., 2007) and marijuana use (Ames et al., 2007). Thus, individual differences in the reinforcement value of substance use may also be represented in implicit attitudes toward substances as well as in more traditional explicit measures.

Implications of These Models for Prevention of Adolescent SUDs Research on the numerous vulnerability factors for adolescent substance use has implications for the design of successful prevention programs. For example, prevention programs have had some success by focusing on family influences (e.g., Hawkins et al., 1992; Spoth, Redmond, Shin, & Azevedo, 2004). Programs such as Strengthening Families (Kumpfer, Molgaard, & Spoth, 1996) and Focus on Families (Catalano, Gainey, Fleming, Haggerty, & Johnson, 1999) attempt to reduce parental drug use and improve parents’ coping and family management skills. In addition, given the importance of parental SUDs, programs aimed at treating parental substance abuse might function as



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a form of targeted prevention for the next generation (Kelley & Fals-Stewart, 2007). In terms of peer influences, school-based programs have focused on social influence and the development of social skills including skills to resist peer influence (Botvin, 2000). These school-based programs have shown shortterm preventative effects, although they tend to fade over time. These programs may not be powerful enough to combat family and intrapersonal factors that are associated with risk for SUDs. For example, factors such as parental SUDs, childhood conduct problems, aggression, difficulties in regulating emotional arousal, impulsivity, poor school achievement, and difficulty coping may not be easily amenable to modification within typical school-based social influence programs. Tiered programs attempt to reach adolescents across the whole spectrum of risk by varying the intervention content and intensity with the needs and motivation of the family. Using a tiered program, Dishion, Kavanagh, Schneiger, Nelson, and Kaufman (2002) have shown some preventative effects on substance use among at-risk and typically developing middle school students across gender, ethnicity, and risk status. Finally, other programs focus on macro-level influences and use public policy interventions. For example, increasing taxes/price has been an effective policy deterrent against youth smoking (Bonnie, Stratton, & Wallace, 2007). Similarly, increasing taxes on alcohol, raising the legal drinking age, and lowering the allowable blood alcohol concentration for drivers under the age of 21 have been effective in decreasing alcohol-related problems, such as DUIs (Chaloupka, Grossman, & Saffer, 2002; Wagenaar, O’Malley, & LaFond, 2001). These programs have been recommended as particularly developmentally appropriate, given the neuroscience findings that adolescent cognitive control networks are not yet strong enough to withstand social pressures in adolescence (Steinberg, 2007).

Implications of These Models for Treatment of Adolescent SUDs The literature on adolescent vulnerability for SUDs also has treatment implications. Although there have been fewer studies of adolescent treatment than of adult treatment (Vaughn & Howard, 2004), this field is rapidly expanding. Moreover, there has been concern that adolescent interventions merely mirror those for adults and that professional certification requirements for substance use therapists do not include specific training in adolescent development (McLellan & Meyers, 2004). However, there has been growing recognition that treatment should be better tailored to the developmental context of adolescent SUDs (Brown & Abrantes, 2006; Wagner, 2008), and this recognition is reflected in recent guidelines for “quality” adolescent treatment (American Academy of Child and Adolescent Psychiatry, 2005). Developmentally appropriate treatments should recognize distinctions between adolescents and adults in neurological and cognitive development, developmental transitions,

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tasks, and social contexts (Colby, Lee, Lewis-Esquerre, Esposito-Smythers, & Monti, 2004; Wagner, 2008). For example, as discussed above, research suggests that parents play an important role in the development and maintenance of adolescent SUDs. Accordingly, family-based interventions have been developed that focus on modifying family systems (Liddle, 2004), and these interventions have shown some success (Diamond & Josephson, 2005; Vaughn & Howard, 2004; Williams, Chang, Foothills Addiction Center Adolescent Research Group, 2000). Better treatment outcomes have been found for adolescents with more parental social support, more parental alliance with the clinician, and less parental substance use (Brown, D’Amico, McCarthy, & Tapert, 2001; Hogue, Dauber, Stambaugh, Cecero, & Liddle, 2006; Williams et al., 2000). Peer contexts are also important to adolescent SUDs, and better treatment outcomes have been found for adolescents with more peer social support and less peer substance use (Brown et al., 2001; Williams et al., 2000). The importance of peer influence might also suggest that group treatment holds benefits over individual treatment (Kaminer, 2005). However, some evidence suggests that group treatment with deviant peers can unintentionally increase adolescents’ problem behaviors (under certain specific circumstances; Gifford-Smith, Dodge, Dishion, & McCord, 2005). Although some research has found group interventions to be at least as effective as individual adolescent treatment (e.g., Marques & Formigoni, 2001; see Weiss et al., 2005, for a review), vigilance for iatrogenic effects of peer influence is warranted. Finally, as noted earlier, adolescents with learning problems and low school achievement are vulnerable to developing SUDs, suggesting that educational deficits and the school context are important to address when treating adolescent SUDs (Wagner, Swenson, & Henggeler, 2000). School-based treatments are rare but show some preliminary evidence of success and are potentially useful in avoiding typical barriers to treatment that can be especially salient for adolescents (e.g., awareness of treatment options, transportation, ability to pay, D’Amico & Edelen, 2007; Wagner, Tubman, & Gil, 2004). Moreover, multisystemic therapy (MST) that is designed to address the multiple social systems within which adolescents are embedded (family, peer, school, and neighborhoods) has also shown some effectiveness (Henggeler, Clingempeel, Brondino, & Pickrel, 2002).

Conclusions and Future Research Directions Theory and research concerning child and adolescent vulnerability for substance use has substantially advanced our knowledge, and the field continues to grow in size and sophistication. Accumulating evidence suggests that there are multiple pathways to substance use and SUDs and that these pathways are biopsychosocial in nature. In terms of early-onset SUDs, there is clear evidence in support of deviance-proneness pathways, more controversy about negative affect regulation pathways, and indirect evidence for enhanced reinforce-



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ment pathways. Research with genetically informative samples suggests that genetic vulnerabilities are significant influences but that there are important environmental influences as well as likely gene–environment covariations and interactions. Moreover, research on neighborhoods suggests that macro-level social variables may also be important. The current literature also suggests important directions for future research. Exciting recent findings concerning the neurodevelopment of reward/incentive systems and cognitive control systems over the course of adolescent development remind us of the importance of taking a developmental approach. These findings should be mapped onto studies of the development of adolescent substance use, and the potentially bidirectional relation between substance use and adolescent neurodevelopment should be examined. Both animal and human studies will be important in this area, and the findings will have important implications for prevention and treatment programs. Research on the heterogeneity of substance use trajectories, including implications of variability in age of onset and speed of transition from onset to dependence, will be important in defining phenotypes for these studies. In addition, future research should continue to link multiple levels of analysis (from micro-level factors to macro-societal factors). These studies will provide richer theoretical explanations for epidemiological phenomena such as gender, SES, and race/ethnicity differences in adolescent substance use. In terms of clinical application, the research directions described above should help to improve the design of prevention interventions, which should be based on a firm understanding of underlying developmental processes of vulnerability and resilience. For diagnosis, more needs to be known about the developmental appropriateness of SUD diagnostic criteria and the potential for considering both dimensional and categorical approaches to the diagnosis and study of SUDs. Research on treatment of adolescent disorders is rapidly growing, and a continued focus on tailoring treatment to adolescent populations would be useful. Moreover, in common with adult SUD treatment, research on maximizing treatment engagement, management of SUDs as relapsing/remitting disorders, and treatment availability and funding are all also needed. Importantly, intervention research itself (either prevention or treatment) can be designed to provide information on the mediating and moderating mechanisms underlying intervention effects. Thus, these studies can provide experimental tests of both the underlying vulnerability processes and the factors that promote resilience to SUDs.

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for young drivers: Effects on drinking, driving, and driving-after-drinking behaviors in 30 states. American Journal of Public Health, 91(5), 801–804. Wagner, E. F. (2008). Developmentally informed research on the effectiveness of clinical trials: A primer for assessing how developmental issues may influence treatment responses among adolescents with alcohol problems. Pediatrics, 121, 337–347. Wagner, E. F., Swenson, C. C., & Henggeler, S. W. (2000). Practical and methodological challenges in validating community-based interventions. Children’s Services: Social Policy, Research, and Practice, 3, 211–231. Wagner, E., Tubman, J., & Gil, A. (2004). Implementing school-based substance abuse interventions: Methodological dilemmas and recommended solutions. Addiction, 99(Suppl. 2), 106–119. Waller, M. W., Hallfors, D. D., Halpern, C. T., Iritani, B. J., Ford, C. A., & Guo, G. (2006). Gender differences in associations between depressive symptoms and patterns of substance use and risky sexual behavior among a nationally representative sample of U.S. adolescents. Archives of Women’s Mental Health, 9, 139–150. Weiss, B., Caron, A., Ball, S., Tapp, J., Johnson, M., & Weisz, J. (2005). Iatrogenic effects of group treatment for antisocial youths. Journal of Consulting and Clinical Psychology, 73(6), 1036–1044. Whalen, C., Jamner, L., Henker, B., Delfino, R., & Lozano, J. (2002). The ADHD spectrum and everyday life: Experience sampling of adolescent moods, activities, smoking, and drinking. Child Development, 73, 209–227. Williams, R. J., Chang, S. Y., & Foothills Addiction Center Adolescent Research Group. (2000). A comprehensive and comparative review of adolescent substance abuse treatment outcome. Clinical Psychology: Science and Practice, 7(2), 138–166. Wills, T. A., Sandy, J. M., Shinar, O., & Yaeger, A. (1999). Contributions of positive and negative affect to adolescent substance use: Test of a bidimensional model in a longitudinal study. Psychology of Addictive Behaviors, 13, 327–338. Wills, T. A., Sandy, J., Yaeger, A., & Shinar, O. (2001). Family risk factors and adolescent substance use: Moderation effects for temperament dimensions. Developmental Psychology, 37, 283–297. Windle, M., Mun, E. Y., & Windle, R. C. (2005). Adolescent-to-young adulthood heavy drinking trajectories and their prospective predictors. Journal of Studies on Alcohol, 66(3), 313–322. Wittchen, H.-U., Frohlich, C., Behrendt, S., Gunther, A., Rehm, J., Zimmermann, P., et al. (2007). Cannabis use and cannabis disorders and their relationship to mental disorders: A 10–year prospective-longitudinal community study in adolescents. Drug and Alcohol Dependence, 88S, S60–S70. Zeigler, D. W., Wang, C. C., Yoast, R. A., Dickinson, B. D., McCaffree, M. A., & Robinowitz, C. B. (2005). The neurocognitive effects of alcohol on adolescents and college students. Preventive Medicine, 40, 23–32. Zucker, R. (2006). Alcohol use and the alcohol use disorders: A developmental biopsychosocial systems formulation covering the life course. In D. Cicchetti & D. Cohen (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder, and adaptation (2nd ed., pp. 620–656). Hoboken, NJ: Wiley. Zucker, R. A., Ellis, D. A., Bingham, C. R., & Fitzgerald, H. E. (1996). The development of alcoholic subtypes: Risk variation among alcoholic families during the early childhood years. Alcohol Health and Research World, 20(1), 46–55. Zucker, R. A., Kincaid, S. B., Fitzgerald, J. E., & Bingham, C. R. (1995). Alcohol schema acquisition in preschoolers: Differences between children of alcoholics and children of nonalcoholics. Alcoholism: Clinical and Experimental Research, 19, 1011–1017.

Chapter 6

Vulnerability to Substance Use Disorders in Adulthood Michael J. Zvolensky, Todd B. K ashdan, Adam Gonzalez, and Julianna Hogan

Substance use and its disorders represent a major public health priority. Most people have tried, or know someone who has tried, tobacco, alcohol, or a recreational drug of one type or another at some point in his or her life. Any single occasion of such use or “experimentation” may represent a one-timeevent related to curiosity, mood enhancement, impaired judgment, or related types of factors. Yet, for a substantial subset of those using alcohol or drugs, substance use behavior can become more frequent, lead to negative personal consequences, and ultimately a pattern of persistent abuse. Substance use disorders are a major public health issue both in the United States and in all major regions of the world due to their high prevalence rates, negative personal consequences across several life domains (e.g., family, occupational, educational responsibilities), and financial cost to society. As one example, estimates indicate that the costs to society of illicit drug abuse in the United States are approximately $181 billion, and when combined with alcohol and tobacco costs, the total exceeds $500 billion annually (National Institute on Drug Abuse [NIDA]), 2004). Perhaps relatively more than many other psychiatric disorders, substance use disorders (SUDs) also are controversial from the perspective of the general public. Some people tend to perceive these problems as being primarily related to certain social conditions (e.g., low socioeconomic status) or individual characteristics (e.g., moral weakness, criminal tendencies). Such perspectives often lead to the erroneous viewpoint that people with SUDs should be able to stop using drugs or alcohol if they “really wanted to do so.” As a result of this type of faulty perception, certain aspects of SUDs and treatment

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for them may unfortunately be missed or ignored in the public sphere. For instance, persons suffering from an SUD experience recurrent craving and other withdrawal symptoms, engage in compulsive use despite clear negative consequences for their behavior, and often cannot quit on their own. These types of issues, along with other evidence, such as a neuronal basis underlying the core features of addictive behavior, indicate that this class of problems is a disorder (or set of disorders) that requires formal treatment to successfully end ongoing use and prevent relapse. Although evidence-based substance use treatment can have a meaningful positive effect on the individual and society, widespread access to such care is unfortunately rare (McLellan, O’Brien, Lewis, & Kleber, 2000). The present chapter is focused on vulnerability for substance use disorders among adults. Although myriad biopsychosocial factors can influence the onset, maintenance, and relapse of substance use disorders across the lifespan, substance use and its disorders can be highly ingrained. In this chapter, we provide an overview of the nature of substance use disorders among adults. We begin by providing a definition of substance use disorders and their clinical characteristics and then discuss their prevalence in society. Here, we use tobacco, marijuana, and alcohol as prototypical examples. We then provide a brief description of different conceptualizations of vulnerability for substance use disorders among adults. In the next section, we describe some illustrative examples of vulnerability factors for adult substance use disorders from a biopsychosocial framework. In the final section of the chapter, we present treatment approaches for such substance use problems and highlight promising areas of research and practice.

SUDs: Conceptualization and Clinical Characteristics General Conceptualizations Definitions of substance use disorders have evolved, particularly over the past two decades. Today, definitions of substance use disorders have achieved a certain degree of cross-national recognition and acceptance within (at least) the scientific and medical communities. These perspectives recognize common clinical features across different types of substance use disorders. That is, the symptoms and “classic signs” of impairment related to problematic substance use behavior. In general, these characteristics include the following: (1) impaired psychological functioning that focuses on substance use (e.g., craving for drugs or drug-related experiences); (2) frequent drug use behavior that occurs despite negative consequences related to it; (3) the development of tolerance (biological adaptation to drug exposure); and (4) withdrawal symptoms upon discontinuation of use. Across these characteristics, most clinicians and scholars have observed that people with substance use disorders often “lose control” over their ability to manage their substance use behavior, par-



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ticularly during periods of escalated positive as well as negative affect (e.g., feeling happy or stressed). The fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) employs three separate labels of severity: use, abuse, and dependence. Substance use reflects nonproblematic consumption of drugs or alcohol. Substance abuse denotes use when there is evidence of limited negative consequences. And, finally, substance dependence refers to a more severe form of use whereby there is a clear pattern of “loss of control” of drug use behavior as well as evidence of clinical features of tolerance and withdrawal. Interestingly, among those who work day to day with substance use disorders in real-world settings (e.g., hospitals), it is more likely to use the label addiction than dependence (e.g., Addiction Treatment Centers). The reason for this choice of language is related to the technical meaning of the word dependence. Many people equate dependence with a purely pharmacological effect of a specific drug agent—for example, bodily adaptation to greater exposure to a substance—and therefore to avoid confusion with such a meaning, the term “addiction” is conveniently applied (Vaillant, 1990). The term “addiction” reflects the same feature of substance use dependence as indexed by the DSM-IV but can be applied broadly to numerous substances and thereby maintains a more general meaning (American Psychiatric Association, 1994). Although the DSM has offered a useful perspective on classifying substance use behavior, researchers have frequently questioned whether it is too narrow of a perspective, failing to adequately capture the intricate nature of substance use problems (Shaffer & Neuhaus, 1985). For this reason, researchers and clinicians often find it necessary to describe other clinical features common to substance use and its disorders. Specifically, they have a broader meaning in the sense of how they manifest and affect a person’s day-to-day functioning. Beyond the general descriptive features of substance use behavior, definitions of disorders attempt to specify their severity (degrees of how problematic use may be at a particular point in time). Such classification of severity is necessary for making judgments about how best to manage and understand the disorder. As one illustrative example, a clinician working with a person suffering from an alcohol use disorder might decide a more intensive treatment program (e.g., inpatient care instead of outpatient care) is necessary for one person as compared to another because the severity of the disorder in the former case is greater. In discussing etiology, phenomenology, and course, researchers continue to find evidence for divergence among various substance use disorders and heterogeneity across (different) people for the same substance. For instance, some people might show a steady incremental progression in the severity of their substance use behavior, whereas others might stabilize in their severity and impairment for an extensive time period. There are a number of factors that could theoretically affect such developmental trajectories. With an appreciation of shared and common features across disorders, we offer

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an elaborated view of substance use behavior that helps clarify how it may “look” in the lives of people.

Common Clinical Features and Processes One classic aspect of substance use behavior, and presumably a cornerstone reason for persistent use, pertains to its effects on the brain. This effect of substance use typically is referred to as drug-induced euphoria, although there are numerous labels for it in everyday life (e.g., high, buzzed, drunk, stoned, gassed). From a scientific perspective, clarifying the nature of substance use effects on the brain has helped researchers gain a clearer understanding of the underlying processes involved in drug addiction. One of the more recent and influential findings, across substances, is that substance-induced euphoria effects are systematically related to brain regions that are typically involved in naturally occurring reward-oriented activities such as satisfying cravings for food, drink, and sexual activity (Dackis & O’Brien, 2003). Some scholars believe that these neural reward circuits may become negatively impacted by chronic or even time-limited persistent drug use (e.g., excessive binge drinking during college years). This account converges with clinical reports from people with substance use disorders that frequently report craving, loss of control, and an impaired ability to regulate short- and long-term consequences (American Psychiatric Association, 1994). The clinical manifestation of tolerance is another hallmark characteristic of substance use disorders. Tolerance reflects the process whereby there is an escalation in drug dose needed to achieve a specific drug-induced effect. Accounting for more recent scientific findings, we now generally recognize that tolerance can exist prior to an extended history of excessive substance use. Research also suggests that tolerance effects for certain aspects of drug use can affect people in markedly different ways. For instance, some cigarette smokers show evidence of the tolerance effects of nicotine after even years of abstinence (Perkins, Grobe, Fonte, & Goettler, 1994), whereas for others abstinence from nicotine for just a few hours may restore nicotine’s tolerance effects (Benowitz, Shoshana, & Jacobs, 1998). A related process is sensitization. Sensitization, sometimes called “reverse tolerance,” reflects an increase in drug responses after repeated administration. Tolerance and sensitization can develop more slowly or rapidly for different types of drugs and for different people (Hughes, 2007). Although it may be tempting to assume that these differences in tolerance or sensitization are solely a function of drug type (e.g., alcohol versus marijuana), such a conclusion would be inaccurate. Indeed, there are a wide variety of individual difference factors related to tolerance and sensitization levels for given substances, with genetic sources often accounting for substantial variability (Dackis & O’Brien, 2003). Thus, both the substance being used and the person using the substance influence the nature of tolerance and sensitization processes, presumably in a synergistic manner across time.



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Withdrawal symptoms related to drug discontinuation (stopping the use of a substance) are another cardinal feature of substance use disorders in the day-to-day life of many people with these problems. Withdrawal symptoms generally occur after repeated drug-related activity rather than after just one or a few occurrences. The onset, duration, and severity of withdrawal symptoms may vary by type of substance used as well as within a drug class across individuals. Despite such symptom-based heterogeneity, there is a growing appreciation that one common aspect of withdrawal that cuts across all substance use disorders is the presence of negative affect—an often aversive emotional state characterized by feelings of agitation, anxiety, depressive mood, anger, irritability, and the like (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004). Additionally, it is evident that substance use can effectively alleviate the withdrawal syndrome emerging from drug abstinence, a finding that is evident in both human and animal research literature (e.g., Cheeta, Irvine, Kenny, & File, 2001; Jorenby, Hatsukami, Smith, & Fiore, 1996). From a clinical perspective, it is useful to think of withdrawal symptoms as a “compensatory reaction” to return a user’s brain state to the condition of abusing substances. In this sense, withdrawal symptoms are believed to have a motivational significance; that is, they prompt or signal the person to use the substance again to alleviate aversive subjective experiences. This withdrawal state is functionally important, often related to a “return” to drug use among those trying to quit. For instance, withdrawal symptoms reflecting increased negative affect often are a clinically significant predictor of relapse among persons trying to quit cigarette usage (Piasecki, Kenford, Smith, & Fiore, 1997). More importantly, withdrawal symptoms arising from alcohol dependence or sedative addiction (e.g., barbiturates) can be lethal. In fact, the early phase of treatment for such problems typically involves administrating smaller and smaller doses of a psychoactive substance that serves a similar function as the drug itself. It is important to point out here that, although detoxification may be an important and even necessary element of drug treatment for certain disorders, it is rarely sufficient for successful treatment (Marlatt & Gordon, 1985). Psychological interventions to alter problematic thinking and emotional styles as well as other types of more global lifestyle changes (e.g., creating nondrug-using social networks) are often necessary to maintain therapeutic gains (McClelland & Teplin, 2001; Vaillant, 1983). An emerging, potentially clinically significant, finding is that withdrawal symptoms often lack a pharmacological basis. Many users report withdrawal symptoms well beyond the time that the drug can possibly have a direct effect on the body. This observation is coupled with the recognition that many users, particularly those with preexisting psychological vulnerability such as anxiety or depressive symptoms, use drugs to manage their mood states (Zvolensky & Bernstein, 2005). Baker and colleagues (Baker, Japuntich, Hogle, McCarthy, & Curtin, 2006) suggest that prolonged symptom dysregulation following drug discontinuation may be due to the fact that users not only stop using

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a drug (e.g., alcohol) but also stop their drug-using routine or “rituals,” a phenomenon called behavioral withdrawal. Evidence in favor of this contemporary multidimensional view of withdrawal includes such findings as heroin withdrawal being diminished by injections of saline (Butschky, Bailey, Henningfield, & Pickworth, 1995). A final clinical process that is helpful in understanding the presentation of substance use disorders pertains to initial and maintaining motivations for substance use. Here, clinicians and scholars have increasingly found merit in applying motivational models to substance use behavior. This work builds from the motivational study of alcohol (Cooper, Frone, Russell, & Mudar, 1995; Cox & Klinger, 1988; Stewart, Zeitlin, & Samoluk, 1996; Stewart, Zvolensky, & Eifert, 2001) and tobacco use (Ikard, Green, & Horn, 1969; Piper et al., 2004; Russell, Peto, & Patel, 1974; Zvolensky et al., 2004). Such an approach recognizes that there are a number of distinct motives for using drugs that can vary both between and within individuals (Cooper, 1994). That is, two individuals may use a specific drug for different reasons, and one person may use for multiple types of reasons. Theoretically, distinct motives may be related to particular problems (Cooper, 1994). For instance, specific motives may play unique roles in various aspects of use (e.g., addictive use, withdrawal symptoms, craving) or problems related to use (e.g., psychological disturbances, risk-taking behavior).

Prevalence The popularity of psychoactive substances is readily apparent in society from almost any vantage point. Within this social context, scholars suggest that illicit substance use behavior in the United States changed from being restricted to a relatively narrow band of people often on the fringe of society to being a “normative” and “mainstream” activity (Johnston, O’Malley, & Bachman, 2002). For instance, approximately 66% of youth during the mid- to late 1970s had used illicit substances by the time they completed high school, a percentage that was substantially greater than prior time periods (Johnston et al., 2002). Higher rates of illicit substance use did not show stability or a notable decrease over time until the mid- to late 1980s, possibly due to increased awareness of drug-related problems and federal efforts to prevent substance use (Bachman, Johnston, & O’Malley, 1990). With other societal events under way such as the Gulf War, federal resources were redirected from drug use prevention toward military efforts during the early to mid-1990s. Interestingly, there was an appreciable increase in illicit substance use behavior during this same time frame (Johnston, O’Malley, & Bachman, 2003). During the late 1990s, illicit substance use behavior decreased for certain drugs among specific segments of the population (e.g., lysergic acid diethylamide



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[LSD]) and increased for others (e.g., MDMA, or “ecstasy”; Johnston et al., 2003). The examination of drug use trends generally indicates that, across circumscribed time periods an increase in the use of a particular drug type often coincides with a decrease in the use of another (Johnston et al., 2003). Thus, inconsistent attitudes toward the use of drugs across substances suggest various societal (e.g., degree of law enforcement focused on a specific class of drugs) and personal (e.g., perceived risks associated with using a drug) factors that play a role in determining usage rates at any time point. Although prevalence rates vary as a function of drug class and historical period, it is useful to highlight rates for the most common types of substances.

Tobacco Use Cigarette smoking is widely recognized as the most popular form of tobacco use and a major public health problem. Indeed, cigarette smoking remains a leading preventable cause of death and disability in the United States (Centers for Disease Control and Prevention [CDC], 1994). Smoking is considered a key factor in various medical illnesses, including heart disease, pulmonary diseases (e.g., chronic obstructive pulmonary disease), and certain forms of cancer (CDC, 1994, 2002). Despite a reduction in smoking prevalence over the past 25 years, approximately 45–48 million adults (some 22–25%) in the United States currently smoke (CDC, 1996). Although nearly 70% of these smokers are motivated to quit (CDC, 2002), about 90–95% of them who try to quit smoking on their own (Cohen et al., 1989)—and 60–80% who attend treatment programs—relapse (CDC, 2002). Thus, there is evidence that not only is smoking a major source of death and disability but also, once started, it is extremely difficult to stop. Additionally, there is a significant population of smokeless tobacco users in the United States and other regions of the world (e.g., India, China; American Cancer Society [ACS], 1999). At the end of the 20th century, an estimated 3% of the population used some form of smokeless tobacco—either snuff (finely ground, shredded tobacco) or chewing tobacco—during the preceding month (ACS, 1999). Domestically, these rates were most elevated among young Caucasian males, as compared with females, and among those in southeastern and northcentral states and rural (vs. urban) settings (Hatsukami & Severson, 1999). Earlier research suggests that the highest rates of chewing tobacco use (16.6%) are among Caucasian males 18–25 years of age (CDC, 1994).

Alcohol Use and Disorders Alcohol (ethyl alcohol or ethanol) is a central nervous system sedative and therefore similar to other sedative drugs such as barbiturates and benzodiazepines. Alcohol use disorders (alcohol abuse or dependence) are among the most prevalent forms of psychopathology worldwide and rank high as a

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cause of disability in most regions of the world (World Health Organization, 2001). Alcohol use disorders are among the most prevalent mental disorders in the United States. According to the National Institute on Alcohol Abuse and Alcoholism’s (NIAAA) 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; Grant et al., 2003), the 12-month prevalence of DSM-IV alcohol abuse and dependence is approximately 8% (Grant et al., 2006). Such problems are associated with impairment across numerous life spheres. For instance, chronic heavy drinking is an etiological factor for certain cancers, liver cirrhosis, immune system disorders, and brain damage. Additionally, family members and friends of the person with an alcohol use disorder may be adversely affected by the problem (Sanderson & Andrews, 2002). Given such findings, it is indeed striking that more than 50% of American adults have a first-degree family member with (or who once met) criteria for alcohol dependence (Dawson & Grant, 1998). The estimated economic cost of alcohol abuse and dependence in the United States is $184.6 billion annually (Harwood, 1998).

Marijuana Use and Disorders Marijuana has been the most widely used illicit substance for 30 consecutive years in the United States (Johnston et al., 2003), with approximately 25 million users during the preceding year (8.6% of the population; Johnston, O’Malley, Bachman, & Schulenberg, 2004). An estimated 10% of persons who ever used marijuana become daily users (Johnston, O’Malley, & Bachman, 1995). Lifetime marijuana dependence is estimated at 4% of the general population, a higher figure than for any other illicit drug (Anthony & Helzer, 1991; Anthony, Warner, & Kessler, 1994). For those using marijuana during the preceding 12 months, the relative risk of experiencing marijuana dependence is estimated to be 7% among adults, which is only slightly lower than that for cocaine (12%) and greater than that observed for alcohol (5%; Kandel, Johnson, Bird, & Canino, 1997). Furthermore, greater levels of use increase the risk for dependence. Studies suggest that the rate of dependence is 20–30% among persons using marijuana on a regular (weekly) basis (Hall, Johnston, & Donnelly, 1999). Moreover, marijuana use problems have increased, with 35% of adult marijuana users in the United States currently meeting the criteria for marijuana abuse or dependence, compared to 30% a decade earlier, representing an increase of approximately 730,000 individuals (Compton, Grant, Colliver, Glantz, & Stinson, 2004).

Vulnerability Perspectives for SUDs A variety of perspectives continue to be used to understand vulnerability processes for substance use disorders. In this section of the chapter, we provide a brief overview of some of the most influential perspectives.



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The Disease Model A historically and clinically important model of vulnerability for substance use disorders has been the disease model (Peele, 1996). In this model, substance use disorders represent an illness of bodily systems with a recognizable set of etiological factors, and a reliable group of symptoms that typically produces a range of anatomical alterations. There have been numerous intellectual challenges to the disease model that are based upon scientific evidence (e.g., Vaillant, 1990). Yet, this model of substance use disorders has had a far-reaching impact, including directing public policy and informing certain treatment approaches (e.g., Alcoholics Anonymous [AA]; Peele, 1996). The shortcomings of a disease model are most apparent in its inadequate ability to predict the onset and maintenance of substance use disorders (e.g., Marlatt & Gordon, 1985).

The Social Deviance Model It also is worth noting that societal viewpoints and diversion from normality also have informed efforts to understand vulnerability for substance use disorders. The basic premise of the social deviance model is that substance use behaviors and its disorders are conceived as problematic when they significantly deviate from the socially acceptable standards in a given community. This approach to vulnerability has helped to integrate social-based perspectives, understanding a person within his or her natural environment (Kuhn, 1962). At the same time, this approach to problematic substance use behavior is, by definition, not simply a product of empirical evidence but also influenced by societal values and beliefs. Intervention strategies are designed to “pull” the individual back to a normal or relatively more normal range of functioning in a given community. There have been a variety of interesting consequences of the utilization of a social deviance model. Some scholars have argued, for example, that because substance use problems have been historically related to men, the vast majority of research has been disproportionately focused on men as compared to women (Blume, 1998). As another example, expectations about the nature of alcohol use often differ by gender (e.g., with women expected to consume less alcohol than men). Some research suggests that such social expectations regarding substance use can, at times, serve as protective factors against the development of certain substance use disorders (Kubicka, Csemy, & Kozeny, 1995).

The Biopsychosocial Model The dominant contemporary approach to understanding vulnerability for substance use disorders is a biopsychosocial one wherein multiple factors from distinct domains can influence the onset and maintenance of these clinical problems (Zucker & Gomberg, 1986). There is a rich history to the biopsy-

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chosocial framework of vulnerability, and it is not specific to substance use disorders (Engel, 1977). Moreover, the biopsychosocial conceptualization now represents a philosophy of clinical care (Engel, 1980). In its most basic form, this conceptual framework suggests that to understand and respond in a maximally effective manner to a particular disorder, including enlisting those affected into treatment (when applicable), it is necessary to attend simultaneously to biological, psychological, and social factors related to the disorder (Engel, 1977). As applied to substance use disorders, this type of approach posits that substance use disorders are not a monolithic disease but rather a combination of genetic (e.g., biological predispositions), psychological (e.g., belief sets, coping strategies), emotional (e.g., emotional dysregulation patterns), learning (e.g., acquired behavior learned in one way or another), and life context (e.g., high levels of stress) factors. There is an obvious complexity involved in studying and integrating the range of factors in this domain. As one illustrative example, the biopsychosocial model has indicated that the relation between mental and physical aspects of a disorder is complex, and they are not reducible or isomorphic with one another. Despite the challenge to comprehensively integrate works across these domains of study, the biopsychosocial model is important, at a minimum, for calling explicit attention to the need to recognize distinct levels of explanation and not reduce one level to another. In the next section of the chapter, we turn to an illustration of the range of factors studied in biopsychosocial models and how they may result in risk for the pathogenesis or maintenance of specific types of substance use problems. Here, we continue to use tobacco, alcohol, and marijuana as substance use problems to illustrate such vulnerability work.

Research on Vulnerability for SUDs Prior to turning to an overview of exemplar vulnerability processes for substance use disorders among adults, it is necessary to first clarify some of the broad-based terms relevant to the current study of putative vulnerability factors that may be involved in the onset or maintenance of such disorders.

Vulnerability Terminology Perspectives Kraemer and her colleagues’ groundbreaking conceptual strides attempted to standardize operational definitions for risk processes so that communication about such factors is more clearly and consistently presented across studies (Kazdin, Kraemer, Kessler, Kupfer, & Offord, 1997; Kraemer et al., 1997; Kraemer, Lowe, & Kupfer, 2005; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001). A risk factor is a variable that is related to, and temporally precedes, an unwanted outcome. Although it is perhaps most common for the outcome of interest to be a discrete diagnostic factor (e.g., psychiatric disorder), risk fac-



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tors also are applicable to continuously defined process variables (e.g., change over time). Causal risk factors reflect variables that, when modified in some way (e.g., through an intervention), produce systematic change (increase or decrease) in the dependent variable of interest among persons who did not previously manifest such problems. Controlled research designs are necessary to document causal effects because they can serve to rule out other competing alternative explanations (e.g., “third variables”). Proxy risk factors are variables that are related to an outcome of interest, but this association is due to the proxy risk factor’s relationship with a causal risk factor (Kraemer et al., 2001). Thus, change in a proxy risk factor would not yield corresponding systematic change in an outcome variable; accordingly, a proxy risk factor may “mark” risk but not explain or account for such risk. Due to the importance—theoretically and clinically—of the ability to change a risk factor, both causal and proxy factors often are further categorized on the basis of whether or not they are malleable. When a risk factor cannot be changed, it can be classified as a fixed marker, whereas when it can be changed, it can be classified as a variable risk factor (Kraemer et al., 2005). These terms clarify whether a variable that is related to an outcome over time can be changed; if it can be changed, it can be considered a “risk factor,” and when it cannot it is better characterized as a “risk marker.” Both markers and causal risk factors may be important for identifying vulnerable individuals, but only causal risk factors will be the ultimate direct target (typically) of the preventative intervention. It also is important to note that a risk factor may be contrasted with a maintenance factor. A maintenance factor reflects a variable that predicts the persistence of an existing outcome over time among people already demonstrating the outcome of interest (Stice, 2002). In theory, the same categorization scheme could be applied to maintenance factors in terms of whether or not they are causal or proxy maintenance factors (Kazdin et al., 1997). Moreover, a risk factor also may subsequently function as a maintenance factor (Stice, 2002).

Biological Aspects of Vulnerability There has been a long-standing appreciation of the biologically based underpinnings of certain substance use disorders. This research has been apparent in both human and nonhuman (animal) literature. There are different branches of study within this domain, including the study of genetic risk, physiological mechanisms, and neurobiological substrates. It is worth noting from the outset that one overarching challenge to research focused on the physiological or biological underpinnings of substance use disorders (and other psychiatric problems) is the wide-ranging heterogeneity of psychiatric conditions (Krueger, 1999; Krueger, McGue, & Iacono, 2001; Krueger & Piasecki, 2002). In biological studies, in particular, this heterogeneity can be a source of error and may hinder efforts to identify biological risk candidates and their neurobiological substrates. Although there have been research strategies devised to

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help mitigate against this challenge (e.g., selecting persons with a “pure” substance use disorder history uncomplicated by co-occurring psychopathology), it does not fully remove the problem. One promising biological factor in the study of substance use disorders, particularly alcohol use disorders, is the P300 component of the event-related potential (ERP). The P300 is a positive (scalp) potential that typically follows the occurrence of infrequent attended targets in a stimulus presentation. Here, reduced amplitude of the P300 response has been related to alcohol use abuse and dependence (Porjesz, Begleiter, & Garozzo, 1980). Whereas early work in this domain indicated that P300 was related to concurrent expression of alcohol use disorders (Porjesz et al., 1980), subsequent research extended this linkage to future risk for the development of alcohol use problems (Berman, Whipple, Fitch, & Noble, 1993; Polich, Pollock, & Bloom, 1994). The P300– alcohol use disorder linkage has been evident across generations, perhaps suggesting a genetic or shared environmental or combination theory of etiology. For instance, children with a paternal history of an alcohol use disorder have evidenced reduced P300 as compared to children without such a history (Begleiter, Porjesz, Bihari, & Kissin, 1984; Hill & Shen, 2002). Specifically, reduced P300 response may indicate a physiological impairment in executive functioning that is related to risk for alcohol abuse and dependence. Although compelling in many respects, reduced P300 is related to a wide range of psychopathologies, especially those in the externalizing spectrum (Attou, Figiel, & Timsit-Berthier, 2001; Branchey, Buydens-Branchey, & Horvath, 1993). In total, this corpus of work suggests, at a minimum, that P300 is a physiological marker of risk for alcohol use disorder and possibly may represent a causal risk factor for such problems. Yet, due to its general association with externalizing problems, it may be a general, as opposed to specific, risk marker or factor. It is unclear how malleable P300 is in response to intervention. For the purposes of the present chapter, what is perhaps most interesting about reduced P300 responding is that it represents an example of a physiological marker of a potential vulnerability process for alcohol use disorder. Future work is needed to explicate what precisely reduced P300 represents in terms of underlying brain functioning. As another example of a biologically oriented vulnerability, research work has addressed genetic vulnerability for certain substance use disorders. For instance, a large number of studies have focused on understanding the heritability of cigarette smoking. Sullivan and Kendler (1999), specifically, in a review of the twin literatures suggested that genetic effects accounted for approximately 50% of the variance in smoking initiation and an even greater amount of variance among those who ultimately developed nicotine dependence. One set of genes that has received empirical support in this domain is that involved with dopaminergic activity. Here, it is theorized that persons with genetic variants linked to less physical activity may be at risk for experiencing greater reinforcement from nicotine because of its dopaminestimulating effects (Comings, Muhleman, & Gysin, 1996). Related types of



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genetic findings have been evident for other substance use problems. Tsuang and colleagues (2001) have reported heritability estimates ranging from .30 to .45 for various types of substance use behavior, indicating relatively consistent and strong heritability. It is important to keep in mind that, although genetic factors are related to various substance use problems, there does not appear to be any single gene responsible for such effects. That is, genes are involved in complex activities and interact with environmental factors to influence substance use disorder outcomes. Some work suggests that genetic effects for substance use problems are mediated through certain personality traits such as impulsivity or sensation seeking (McGue, 1994; Zuckerman, 2007). Additionally, although genetic factors are certainly part of the larger explanatory context for substance use disorders, they are not easily modifiable, and therefore their ultimate utility as a causal risk factor may be less than that for other risk candidates. A final example of biologically oriented research has focused on sensitivity to specific types of substances (Schuckit & Gold, 1988). This domain of study has been largely concerned with identifying patterns of physiological responding that mark a risk process for substance use problems. Some work in this area has found that greater heart rate reactivity is associated with heavier patterns of alcohol use (e.g., binge drinking; Pihl & Peterson, 1991). There have been a wide variety of approaches taken in this domain of inquiry, including body movement and other peripheral indices of somatic reactivity. In general, this area of work has most clearly indicated the intricacies of identifying a specific and reliable physiological marker of reactivity to a pharmacological substance. That is, there has been a relatively inconsistent pattern of findings. In some respects, this work illustrates the importance of integrating neurobiological factors with psychological and social factors to more comprehensively account for etiology and maintenance processes.

Psychological Aspects of Vulnerability The study of psychological vulnerability to substance use disorders has addressed a wide range of factors, such as personality, information processing biases, and cognitive beliefs and expectancies. This work has been fruitful, much like that on biological processes, in providing new insights into the nature of the cognitive styles and self-regulatory strategies involved in substance use disorders. Perhaps the most long-standing area of research on psychological vulnerability has focused on personality. This work is historically related to the popular lay notion that there are “addictive personalities.” Although much early work in the personality–substance use disorder arena has been controversial for theoretical reasons and not empirically consistent (Nathan, 1988), contemporary approaches are yielding arguably relatively more success. This work has been guided by the influential five-factor model of personality (Costa & McCrae, 1989), the five factors representing neuroticism, extraversion, open-

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ness, agreeableness, and conscientiousness. Some work in this domain points to the explanatory relevance of certain personality dimensions over others in terms of specific substance use disorders. For example, higher levels of neuroticism and lower levels of conscientiousness have been related to alcohol use disorders (Martin & Sher, 1994). Sher and Trull (1994) offered the perspective that it is often advisable to focus on broad rather than specific personality dimensions in understanding vulnerability to substance use disorders due in large part to the heterogeneity of this population. The other key personality dimension routinely explored in substance use disorders is impulsivity/disinhibition (Sher, 1991; Zuckerman, 1999); this trait reflects tendencies to seek out intense and novel sensations, impulsivity, and proneness to deviance. It is generally unclear whether a personality dimension such as impulsivity/disinhibition is uniquely related to a specific type of substance use disorder or, rather, represents a more broad-based marker of risk for substance use problems. Despite inconsistencies and ongoing debate, it appears that considering the role of personality in terms of understanding substance use disorders remains an important task. Another body of work indicates that people’s expectations of substance use effects are meaningful. Outcome expectancies reflect the anticipated consequences of substance use (Brandon, 1994; Cohen, McCarthy, Brown, & Myers, 2002; Cox & Klinger, 1988; Niaura, Goldstein, & Abrams, 1991). Due to distinct pharmacological, learning, and sociocultural effects, the expected consequences of substance use may vary by type of drug. In terms of cigarette smoking, outcome expectancies reflect beliefs about positive reinforcement (e.g., “I enjoy the taste sensations while smoking”), negative reinforcement/negative affect reduction (e.g., “Smoking helps me calm down when I feel nervous”), negative consequences (e.g., “The more I smoke, the more I risk my health”), and appetite control (e.g., “Smoking helps me control my weight”) (Brandon & Baker, 1991). Studies have documented the clinical relevance of outcome expectancies in terms of explaining various aspects of smoking behavior (Keleman & Kaighobadi, 2007). For example, studies have indicated that smokers who smoke at higher rates endorse more positive expectancies about the effects of smoking (Ahijevych & Wewers, 1993; Copeland, Brandon, & Quinn, 1995; Downey & Kilbey, 1995), whereas other work has found that expectancies for negative reinforcement/negative affect reduction and negative consequences predict lack of cessation success (Wetter et al., 1994). This body of work has implicated certain types of outcome expectancies as a putative maintenance factor for cigarette smoking among adults. It is noteworthy that these findings generally parallel results for alcohol outcome expectancies and drug use behavior more generally (Abrams & Niaura, 1987; Cooper, Russell, & George, 1988). Another area of work integrates insights from work on the anxiety disorders. Here, research has found merit in a cognitive-based individual difference factor called anxiety sensitivity—reflecting the fear of anxiety and arousalrelated sensations (McNally, 2002; Taylor, 1999). When anxious, people high



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in anxiety sensitivity become acutely fearful due to beliefs that anxious feelings have harmful physical, psychological, or social consequences (Bernstein & Zvolensky, 2007). Intervention tactics, including psychosocial and pharmacological protocols, can change anxiety sensitivity (Otto & Reilly-Harrington, 1999; Smits, Berry, Tart, & Powers, 2008; Wald & Taylor, 2005). Anxiety sensitivity has increasingly been linked to a variety of substance use disorders (Lejuez, Paulson, Daughters, Bornovalova, & Zvolensky, 2006; Norton, Rockman, Luy, & Marion, 1993; Stewart, Karp, Pihl, & Peterson, 1997; Stewart & Kushner, 2001). In fact, a growing corpus of empirical work indicates that anxiety sensitivity is associated with numerous aspects of cigarette smoking. Some of the earliest and now the most well documented studies in this domain, for example, have found that adult cigarette smokers high, but not low, in anxiety sensitivity were more apt to report smoking because they believe that smoking serves the function of down-regulating negative affective states (e.g., Brown, Kahler, Zvolensky, Lejuez, & Ramsey, 2001; Zvolensky, Bonn-Miller, Feldner, et al., 2006). More recent scientific study has found that such anxiety sensitivity-smoking motive relations underscore habitual and addictive smoking behavior more so than other motives (Leyro, Zvolensky, Vujanovic, & Bernstein, 2008). Anxiety sensitivity also is related to problems in quitting and therefore may represent a maintenance factor for cigarette smoking. One study found anxiety sensitivity to be associated with an increased rate of smoking lapse during the first week of a quit attempt (Brown, Kahler, Zyolensky, Lejuez, & Ramsey, 2001). Additionally, daily smokers with higher levels of anxiety sensitivity reported their longest (lifetime) quit attempts as consisting of relapse within 1 week postcessation (Zvolensky et al., 2007; Zvolensky, Bonn-Miller, Bernstein, & Marshall, 2006). As a final example, there have been a variety of psychological problems associated with marijuana use and its disorders. There are numerous lines of evidence for an association between marijuana use and psychotic-spectrum disorders. Indeed, case reports have documented that marijuana use can precede the onset of certain psychotic-spectrum disorders such as schizophrenia at higher rates than expected by chance among “regular” marijuana users (Bowers, Boutros, D’Souza, & Madonick, 2001). Although the directional nature of the marijuana psychotic-spectrum problem association has been the subject of debate (e.g., Hambrecht & Hafner, 2000), one position has been that the use of marijuana may increase the risk of psychotic-spectrum disorders (Bowers et al., 2001). Consistent with this marijuana-to-psychotic symptoms/disorders perspective, the acute effects of marijuana use contributes to the elicitation of psychotic episodes and the recurrence of psychotic symptoms among previously afflicted persons (Mathers & Ghodse, 1992). Other work has found that intravenous tetrahydrocannabinol (THC) administered to antipsychotic-treated patients with schizophrenia and nonpsychiatric controls exacerbated positive schizophrenic symptoms in the patient sample and induced positive symptoms in controls (D’Souza et al., 2000). Neuroimaging studies also have found similarities between neural networks impaired by

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marijuana use and those known to be implicated in the etiology of schizophrenia (Loeber & Yurgelun-Todd, 1999). Finally, in a meta-analytic review of the existing empirical literature, Semple, McIntosh, and Lawrie (2005) concluded that early use of marijuana increased the risk of schizophrenia or a schizophrenia-like psychotic illness by approximately three-fold. Although a model indicating that marijuana may lead to psychotic-spectrum disorders provides only one possible way in which these factors may be related, it documents the importance of understanding marijuana in the context of severe cognitivebased mental illness.

Affective Aspects of Vulnerability Beyond cognitive factors, there is growing evidence that emotional states and disorders are related to certain aspects of vulnerability to substance use disorders. There are numerous theories as to how best to describe emotional states (Izard, 1992; Ekman, 1992; Lang, 1994). Most contemporary integrative accounts of emotion such as the work of Ekman (1992) posit that emotions are biologically selected reactions that coordinate adaptive responding to environmental events and challenges (Lang, 1994). Thus, emotional states like fear, sadness, or anger presumably “coordinate” specific responses to particular eliciting cues and, by extension, serve a unique function. As emotions presumably serve unique functions, they naturally experientially possess an imperative quality; that is, they “prioritize” responding and can disrupt ongoing behavioral responses. The abrupt nature of emotional states often means that they can operate, especially early in the generative process, beyond conscious awareness (Lang, 1994). At the same time, emotional response tendencies can be modulated to varying degrees (e.g., enhanced or diminished)—an area of work often referred to as emotion regulation (Izard, 1990). In research and practice, there are emerging lines of evidence consistent with the perspective that negative affect is an important factor in smoking cessation relapse and may therefore represent a risk factor for relapse. First, studies indicate smokers consistently self-report that smoking is associated with negative emotional states, most commonly anxiety, depression, and anger (Gilbert & Spielberger, 1987). Moreover, negative affect processes are a particularly common antecedent to smoking (Shiffman, 1982). In one study, 75% of subjects in a smoking cessation trial reported that negative affect precipitated their temptation to smoke, with anxiety being the most frequently reported negative emotion (Shiffman, 1985); others found similar results (Hughes, Hatsukami, & Skoog, 1986). Second, prospective studies have shown that negative affect after quitting predicts poorer cessation outcomes (Ginsberg, Hall, Reus, & Ricardo, 1995; West, Hajek, & Belcher, 1989). Third, relapse to smoking often occurs in situations involving negative moods such as anxiety and depression (Bliss, Garvey, Heinold, & Hitchcock, 1989; Brandon, Tiffany, Obremski, & Baker, 1990; Shiffman, 1982). Fourth, lapses in negative affect situations are more likely than lapses in other situa-



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tions to lead to complete relapses (O’Connell & Martin, 1987). Fifth, smokers who attribute their smoking to negative affect reduction may have a particularly difficult time quitting (Pomerleau, Adkins, & Pertschuk, 1978). For instance, O’Connell and Shiffman (1988) found that smoking to reduce negative affect significantly predicted relapse at 1-year follow-up. Finally, affectrelated withdrawal symptoms are superior to measures of physical dependence and physical withdrawal symptom severity in predicting relapse (Piasecki et al., 1997). Taken together, negative emotional states are a central component to understanding relapse for cigarette smoking. Beyond negative emotional states, specific emotional disorders are similarly linked to substance use disorders. One line of inquiry regarding tobacco anxiety associations has focused on clarifying the link between posttraumatic stress disorder (PTSD) and smoking. PTSD is characterized by an inability to recover from a stress reaction to a traumatic event (Kessler, Sonnega, Bromet, & Hughes, 1995). Persons with this emotional disorder experience distinct sets of symptoms: reexperiencing (e.g., intrusive thoughts, nightmares), avoidance (e.g., trying to not think about a traumatic event), and hyperarousal (e.g., easily startled) symptoms (Lyons, Gerardi, Wolfe, & Keane, 1988). There are at least four interrelated streams of empirical work that suggest linkages between smoking and PTSD. First, both lifetime and current smoking rates are significantly higher among persons with PTSD as compared to persons without this disorder (Acierno, Kilpatrick, Resnick, & Saunders, 1996; Beckham, Roodman, Shipley, & Hertzberg, 1995; Buckley, Mozley, Bedard, Dewulf, & Grief, 2004; Hapke et al., 2005; Lasser et al., 2000). Second, smokers with PTSD, compared to those without the disorder, smoke more cigarettes per day and are more dependent on nicotine (Babson, Feldner, Sachs-Ericsson, Schmidt, & Zvolensky, 2008; Beckham et al., 1997; Lipschitz et al., 2003). Third, persons who develop PTSD after exposure to a traumatic event report increased smoking behavior as compared to people not developing such symptoms subsequent to the traumatic event (Breslau, Davis, & Schultz, 2003; Pfefferbaum et al., 2002; Vlahov et al., 2004). Finally, PTSD is associated with lower overall success in quitting smoking (Hapke et al., 2005; Lasser et al., 2000; Zvolensky et al., 2008). These data on PTSD and smoking highlight that this particular emotional disorder may play a role in various facets of cigarette smoking behavior, including possibly operating as both a risk and, possibly, a maintenance factor.

Behavioral Aspects of Vulnerability Behavioral aspects of vulnerability for substance use disorders have a longstanding history. Some of the earliest accounts emphasized, in the most basic sense, that substance use behavior and disorders are learned behaviors that are reinforced because they reduce distressing (aversive) experiential states. Although few would challenge the importance of learning in the context of substance use behavior, straightforward tension-reduction perspectives have

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proven to be more challenging and less convincing explanatory accounts. As one example, prolonged drinking can be associated with increases rather than decreases in negative experiential states (McNamee, Mello, & Mendelson, 1968). Perhaps a more promising contribution of the behaviorally oriented perspective has focused on coping processes. In brief, coping processes are a subordinate category within the construct of affect regulation (Compas, Connor-Smith, Saltzman, Thomsen, & Wadsworth, 2001; Gross, 1998). Although the construct of coping has been defined in many ways, the vast majority of research has been based on work suggesting coping reflects conscious voluntary attempts to manage internal or external stressors that an individual perceives as exceeding personal resources. In recent years, researchers expanded upon this conceptualization by suggesting that coping processes are contextspecific, ongoing, and dynamic (e.g., Compas et al., 2001). Perhaps the most well known influence of the coping perspective of substance use disorder vulnerability is broadly focused on cognitive-behavioral models. Cognitive-behavioral approaches are founded on the assumption that persons with substance use disorder have a deficit in skills needed to effectively deal with cognitive, affective, and environmental challenges related to substance use (Marlatt & Gordon, 1985). Thus, these persons lack the skills to maintain abstinence or regulate ongoing use of a specific drug. From this perspective, the goal of an intervention would be to identify skill deficits and provide corrective learning experiences that could facilitate skill development and corresponding changes in self-efficacy for remaining abstinent. Among marijuana-dependent individuals, coping skills often are related to an increased ability to maintain long-term abstinence from marijuana (Litt, Kadden, Cooney, & Kabela, 2003). These data suggest that coping skills may be a mechanism of behavior change in the treatment of marijuana use disorders. Another promising behavioral perspective has focused on distress tolerance and relapse in cigarette smoking behavior. This scientific work has been stimulated, at least in part, by the observation that a significant percentage of smokers attempting cessation lapse to smoking within a matter of days, and few of these individuals recover to achieve abstinence (Cook, Gerovich, O’Connell, & Potockym, 1995). In this literature, distress tolerance is defined as individual differences in the (in)ability to tolerate aversive experiential states (Brown, Lejuez, Kahler, Strong, & Zvolensky, 2005). It reflects the behavioral tendency to continue to pursue a goal despite encountering various states of affective discomfort, which may be in response to perceived physical and/or psychological distress (Brown et al., 2005). There are a number of studies that have provided data consistent with a distress tolerance perspective on early lapse. In some of the earliest studies within this domain, Hajek and colleagues (Hajek, 1991; Hajek, Belcher, & Stapleton, 1987; West et al., 1989) found consistent positive associations between duration of breath holding, as an index of tolerance for physical discomfort, and duration of abstinence from smoking among daily smokers. Other work used laboratory tasks that tapped distress



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tolerance, defined as persistence on psychologically distressing (Paced Auditory Serial Addition Task (PASAT; Lejuez, Kahler, & Brown, 2003) and physical (carbon dioxide enriched air inhalation [CO2] and breath-holding duration) challenge provocation tests. These tests are designed to generate physical symptoms of interoceptive distress. Smokers who are immediate relapsers are more likely to terminate the CO2 and PASAT challenges and show a shorter duration of breath holding than delayed relapsers (Brown, Lejuez, Kahler, & Strong, 2002). These findings are noteworthy in that the two groups did not differ in terms of their smoking history or nicotine dependence level. A subsequent investigation by Brandon and colleagues (Brandon et al., 2003) evaluated the predictive utility of persistence on behavioral tasks to relapse following treatment for smoking (n = 144). Prior to treatment, participants completed a variety of behavioral persistence tasks including an anagram test (AT) and a mirror tracing persistence task (MTPT). Participants were divided into three groups: (1) treatment noncompleters, (2) lapsers (those who completed treatment but relapsed back to smoking), and (3) abstainers (those who sustained abstinence until follow-up). Results indicated that MTPT was found to be a significant predictor of sustained abstinence, while the AT was not; this effect was apparent after controlling for level of nicotine dependence and gender. Additionally, MTPT persistence increased monotonically across treatment noncompleters, lapsers, and continuous abstainers. Collectively, numerous studies are consistent with the emerging perspective that distress tolerance is a possible maintenance factor for early smoking lapse.

Interpersonal Aspects of Vulnerability Social processes also are related to substance use disorders. There is a long, although not necessarily systematic, literature in this domain. In general, it highlights that social expectations and interactions can influence substance use behavior among adults. Sometimes these social-based effects are reflections of community-based acceptance of substance use behavior. For example, during the late 1800s people in the United States consumed approximately three times more alcohol than they do today (Levine, 1978). As is clear from this illustration, it is likely the relative degree of problematic alcohol use would be expected to differ quite drastically across time in the United States. Newcomb (1997) has reported that there are a wide array of geographical and community differences in alcohol attitudes. In some U.S. communities, for example, while underage drinking may technically be illegal, that law is rarely enforced (Newcomb, 1997); in this situation, the community may be implicitly transmitting the message to youth that it is “reasonable” to drink alcohol. Other socially based attitudes may be evident in certain religious communities (e.g., among Muslims vs. Irish Catholics), where substance use behavior may be viewed as either consistent with or diametrically opposed to core religious beliefs (Lawson & Lawson, 1998). Although these cited examples are pertinent to alcohol use problems, social influences may be equally apparent for

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other substance use problems. Indeed, social and interpersonal factors have been evident for many substance use problems. As one illustrative example, peer group cigarette smoking is consistently a predictor of smoking among youth (Chassin, Presson, Steven, & Sherman, 2000). Social norms also can influence the nature of expressed substance use behavior. Lindman and Lang (1994), for instance, examined alcohol consumption behavior cross-nationally. Here, participants reliably reported that aggression was often believed to follow alcohol intake. Yet, there were marked differences across countries in the extent to which respondents believed alcohol would contribute to aggressive behavior (Lindman & Lang, 1994). These types of findings illustrate that some of the learning processes that govern substance use behavior, and by extension vulnerability for substance use disorders, often are influenced by social factors. Beyond social beliefs, norms, and expectations, the sociocultural environment can influence vulnerability for substance use disorders. Perhaps the most well known factor in this domain has been socioeconomic status (SES). Numerous studies have linked SES in cross-sectional and prospective work to greater risk for substance use disorders (Abbey, Scott, Oliansky, Quinn, & Andreski, 1990). Other research has indicated that neighborhood features may have an impact on the relative risk for substance use and its disorders. Environments rich in substance use behavior can make access to specific types of substances relatively easy (Abbey et al., 1990). These same environments also can decrease the likelihood of opportunities to learn more adaptive selfregulatory strategies. At present, it is generally unclear whether such social conditions are a causal factor in substance use behavior and problems. After all, there is likely an intricate web of interconnections between the loss of social resources and substance use behavior. As individuals engage in higher rates of substance use behavior, they may have fewer opportunities to attain financial and social resources and thus find themselves drifting toward increasingly deviant social networks, reinforcing their own destructive behavioral tendencies. Social support is yet another social factor that can influence substance use behavior. Forms of social support may be representative of positive relations with family, partners, children, friends, and others (e.g., coworkers). In many cases, social support acts as a buffer to substance use behavior, such that increases in social support are related to lower levels of substance use. For example, among cocaine and heroin users and nonusers, social support and relations with employed persons served as protective factors in regard to using these substances (Williams & Latkin, 2007). It also is particularly important to note that nonenabling (discouraging substance use) social support is beneficial in reducing and quitting substance use behavior (Havassy, Wasserman, & Hall, 1995; Wasserman, Stewart, & Delucchi, 2001). Other work in this area has consistently supported a social support–substance use relation (Kim, Davis, Jason, & Ferrari, 2006; Oetzel, Duran, Jiang, & Lucero, 2007).



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Intervention Programs for SUDs Although not every person who uses substances will experience problems related to such use, a substantial minority of people will develop problems and, moreover, require some sort of treatment to help alleviate such disturbances. For example, one recent survey in the United States found that approximately 22.5 million Americans ages 12 or older, needed treatment for substance (alcohol or illicit drug) abuse and addiction (Substance Abuse and Mental Health Service Administration, 2005). Unfortunately, this same survey indicated that, of the 22.5 million people who needed treatment, only 3.8 million received it (Substance Abuse and Mental Health Service Administration, 2005). Researchers and others have therefore worked to develop intervention strategies that can help treat or even prevent substance use problems. Of the substance use disorders, alcohol or alcohol in combination with another substance tends to be the most common type of problem for which publicly funded treatment is sought, with marijuana and heroin use following close behind (National Institute of Drug Abuse, 2004). There has been much progress made in terms of developing and disseminating evidence-based therapies for substance use disorders. A general aim of such treatment is to help the individual achieve abstinence in the long term. To achieve this aim, many therapies work with the individual first to achieve smaller, more proximate, successes such as reducing drug abuse and developing healthier behavior patterns. Additionally, it is not uncommon for individuals seeking treatment to relapse, even when they receive optimal care. As a result of this and related factors, scholars tend to view substance use disorders as “chronic problems.” Not surprisingly, recovery from substance use disorders, then, is frequently a long-term process that requires multiple iterations of treatment before “success.” In this section of the chapter, we describe the nature of substance use treatment and provide an overview of some of the cutting-edge treatments in this domain. Evidence-based intervention programs for substance use disorders generally follow a predictable course, typically beginning with some form of detoxification, followed by formal intervention (either inpatient or outpatient) and then relapse prevention. In most cases, the active elements of the intervention include a pharmacological element, a psychosocial or behavioral element, or a combination of the two. Throughout there is a working assumption that continuity of care is needed for successful behavior change and the maintenance of such changes. That is, the intervention is not a “quick fix” that can be administered once, like a shot, from which unending benefits then ensue. Rather, treatment for substance use disorders requires a commitment from the individual as well as the treatment team to work together, adapt and tailor the intervention, and implement it with close monitoring over relatively long periods of time. Sometimes this care, although primarily focused on substance use as the primary presenting problem, also requires the integration of services in other domains of life functioning. For example, to the extent that an

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individual’s physical health is in poor condition or in need of formal medical care, these services may need to be integrated with substance use treatment. As another example, to the extent that an individual needs help in locating social services (e.g., gaining care for children, finding an occupation), social workers may be involved in therapy. Thus, there often is a trandisciplinary focus in substance use treatment, involving various professionals, each with his or her own expertise. Given this background, a number of specific types of substance use treatments that have been advanced with varying degrees of success.

Family and Multisystem Therapy Family and multisystem therapy for SUDs is an example of a psychosocial treatment approach. In this therapy, the underlying approach recognizes that the individual seeking treatment operates in a social context, typically involving family, friends, coworkers, and so on. This social system is the context in which substance use problems develop and are maintained, and therefore successful treatment for such problems needs to address these social factors. This approach has the benefit, in theory, of offering high levels of social support to the individual seeking care. Thus, this treatment approach generally includes such people as family members, significant others, and friends in treatment. This type of therapy has been particularly popular among youth with substance use problems and has generally been well studied. Psychosocial approaches to substance use treatment are diverse, so it is not possible to capture them all in a brief description; suffice it to say that they can involve a variety of theoretical approaches, treatment tactics or strategies, and type of focus (e.g., individual vs. group format). Among the substance use treatment programs that follow this approach are multisystemic therapy (Henggeler & Borduin, 1990) and multidimensional family therapy (Liddle et al., 2001). These treatments are not focused on any one type of substance use problem but, rather, seek to modify underlying individual and social factors related to substance use problems more generally. Controlled clinical trials evaluating these therapies have indicated that they generally outperform therapies that do not involve multisystem approaches. For example, Liddle and colleagues (2001) found that multidimensional family therapy outperformed group therapy that did not involve outside family members or family education in regard to producing statistically significant reductions in substance use problems. It is noteworthy that, due to the focus on the family unit and responsibility of care for minors, this type of approach is used more frequently among youth than among adult populations.

Behavioral Therapies Behavioral therapy applications have been widely recognized as being very successful for treating a wide variety of behavioral problems. The application of these therapies across conditions is built on a number of key elements,



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including the following: (1) utilization of learning principles (operant and classical conditioning) to change behavior; (2) a focus upon the function rather than the structure of behavior (i.e., in the most general sense, structural analyses focus on how people behave [e.g., the form of a particular response], whereas functional analyses focus on why people behave [e.g., the purpose of a particular response]); and (3) idiographic [i.e., individual] rather than nomothetic [i.e., group] approaches to assessing and changing behavior. Despite the uniformity among behavioral therapies commonly perceived by the public, it is important to note that not all behavioral therapies are the same. Indeed, behavioral approaches differ in the specific aspects of their clinical approach and the focus of treatment. This diversity is reflected in the numerous terms that have been employed to describe this general therapeutic approach (e.g., applied behavior analysis, behavior modification, cognitive-behavioral therapy). Although these various terminologies capture relative differences in one’s specific approach, behaviorally oriented therapies are committed to changing maladaptive behavior through a functional idiographic-based assessment of specified target behaviors. Thus, even in the case of standardized treatment manuals that identify the major processes functionally related to a particular disorder, treatments are tailored to the individual—at least at the level of practical implementation. To achieve these goals, behavioral therapists attempt to provide their patients with a new set of learning experiences that accord with positive behavior change within the patients’ value systems. Using these approaches, behavioral therapies have made important inroads into the treatment of substance use disorders. Indeed, there are numerous efficacious therapies developed for a wide range of substance use problems, including alcohol, marijuana, cocaine, and tobacco use disorders (DeRubeis & Crits-Christoph, 1998). As one illustrative behavioral treatment example, contingency management has been effective in reducing drug use behavior and promoting abstinence. This treatment approach is based on operant conditioning behavioral principles by which individuals receive rewards and incentives for reducing and eliminating their drug use. For example, a number of studies have shown that providing individuals with vouchers for redeemable goods in return for drug-free urine specimens is effective in reducing drug use behavior and retaining patients for treatment (Higgins, Wong, Badger, Ogden, & Dantona, 2000; Higgins, Badger, & Budney, 2000). Although this form of treatment appears to be effective in drug use reduction and abstinence, in isolation it may not be a cost-efficient and long-term successful treatment for abstinence. This is because individuals often relapse once contingencies are reduced or removed, and the treatment can be costly to provide (Crowley, 1999).

Motivational Therapies Another treatment approach has been to use motivational strategies to prompt internally motivated change in problematic behavior (Miller & Rollnick,

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1991). The general idea behind this approach is that the individual can and should decide to make a concerted effort to change his or her behavior. To systematically encourage such change, therapists can be empathetic, facilitate the identification of a discrepancy between beliefs and lifestyle patterns, be flexible in managing resistance, and support the individual as the agent of change. The motivational approach is nonconfrontational at its core; it seeks to adapt flexibly to a person’s current point of view and to help them consider other possibilities such as changing substance use patterns if they are willing to do so. Controlled research has indicated that this approach to changing substance use behavior and promoting healthy lifestyle change more generally has been found to be beneficial across a wide range of substance use problems (Carroll, Ball, & Martino, 2004). As an example, marijuana-dependent individuals undergoing motivational interviewing treatment significantly decreased their marijuana use as compared to a delayed treatment control group (Stephens, Roffman, & Curtin, 2000). These treatment effects also held true for problematic alcohol use (Burke, Arkowitz, & Menchola, 2003; Dunn, Deroo, & Rivara, 2001).

12-Step Programs Although many of the above mentioned treatments are delivered in addiction centers, hospitals, or other medically or psychologically oriented centers, other SUDs treatments are rooted in the community at large. These programs are therefore not affiliated with a care system and often are free of charge. The mission of such programs in general is to help individuals learn to live a sober life. Perhaps the most popular and well known of these programs are such 12-step programs as Alcoholics Anonymous (AA) and Narcotics Anonymous (NA). These programs, specifically, provide a social context that enables people to work together to solve their common problem, helping them to recover from alcoholism or substance use problems. The only requirement for membership is a desire to stop drinking or using. There are no dues or fees for AA or NA membership, and the programs are not allied with any denomination, sect, politic group, organization, or institution. A core assumption of both AA and NA approaches is that these substance use disorders are a disease and the primary route for health is abstinence. Individuals in these programs therefore work through a series of 12 steps, each having a particular goal or aim. For example, Step 1 in AA states that people must admit that “we are powerless over alcohol—that our lives had become unmanageable.” Although AA and NA groups are both widespread and numerous, data relating to their overall efficacy is currently limited. However, research that focuses on treatments based on 12-step principles has suggested that such approaches may indeed be helpful. For example, a number of randomized clinical trials evaluating 12-step manuals (not AA or NA, per se, but, rather, principles used in such treatments) have found that this type of treatment outperforms standard care (Carroll et al., 1998).



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Pharmacotherapy Outside of psychosocial strategies for substance use disorder treatment, a number of pharmacological therapies have been developed and are commonly used in the treatment of drug and alcohol addiction. These treatments can be useful for facilitating detoxification, preventing future drug use, and helping to manage challenging symptoms more generally. For example, detoxification for alcohol use disorders typically involves the use of benzodiazepines or barbiturates and anticonvulsants to decrease withdrawal symptoms and help prevent seizures. As another example, for heroin and opioid dependence, methadone is prescribed to decrease withdrawal symptoms. Another example of a commonly used pharmacotherapy is naltrexone; this drug is employed to block opioid receptors, reducing the rewards that alcohol and other substances can offer. Thus, theoretically, substance use may become less rewarding to an individual. Though the efficacy of pharmacotherapy depends on the specific drug being used and the type of substance use disorder for which it is being employed, many of these drugs are commonly employed in substance use disorder treatment. Typically, these drugs are administered as part of a larger therapeutic effort, as described earlier in this chapter, rather than being the only element of treatment. To illustrate some key aspects of pharmacotherapy, we now present some work on drug-based treatments for smoking cessation in which pharmacological agents are employed for maintaining abstinence and preventing relapse. In brief, these approaches provide nicotine to the body to help ease withdrawal symptoms and facilitate the maintenance of abstinence in a relatively safe and controlled manner. First-line pharmacotherapy has consistently demonstrated beneficial effects for smoking cessation, including the ability to nearly double successful quit rates (Fiore et al., 2000). Currently there are numerous medications that facilitate smoking cessation efforts, though the mechanisms underlying these effects may differ according to the specific drug. Due to the wide variety of pharmacotherapy options, we are unable to review all these medications and their relative efficacy in detail (see Hughes, Shiffman, Callas, & Zhang, 2003). However, the most popular types of pharmacological agents are those that rely on a safer (i.e., nonsmoking) nicotine delivery system that can be stepped down gradually as needed by the individual. These nicotine replacement therapies (NRTs) include nicotine gum, inhalers, nasal sprays, and patches. All of these agents are focused principally on maintaining blood nicotine levels to decrease adverse withdrawal symptoms upon smoking abstinence (Hughes et al., 2003). It is possible these NRT strategies also may promote an enhanced expectation of success in quitting (placebo effect), although relatively little scientific work has been focused on addressing this matter. Overall, the exact dosing of these NRT-related drugs varies across individuals, as does the relative degree of efficacy (Fiore et al., 2000). Clinically, therapists may work with clients to isolate the best “match” of pharmacotherapy for their individual clients. For example, some smokers

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may prefer nicotine gum, whereas others may prefer the patch for a variety of personal reasons. Another drug that has proven efficacious in facilitating smoking cessation is bupropion (Zyban). This drug blocks neural reuptake of dopamine and nor-epinephrine; it is a prescription-only pharmacological agent. Although bupropion is not appropriate for all patients (e.g., individuals with seizure disorders), it may help decrease the aversive experience of quitting (e.g., decreasing negative affect prior to, or during, a quit attempt). Bupropion also can be used in conjunction with NRT strategies, possibly enhancing clinical benefit for certain individuals by targeting different mechanisms of action. It should be noted that there are a variety of other pharmacological drugs that may be helpful to smokers trying to quit that are not discussed as extensively in this chapter, such as clondidine and nortriptyline; their efficacy for smoking cessation is less well known than NRTs and bupropion.

Summary This chapter has focused on vulnerability for substance use disorders among adults. Examination of the research and clinical literature in this area makes clear that a wide range of biopsychosocial factors can influence the onset, maintenance, and relapse of substance use disorders. Significant advances in understanding these disabling and costly conditions will likely continued to be made when integrative approaches addressing their multiple sources of influence are utilized.

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Chapter 7

Vulnerability to Substance Use Disorders across the Lifespan L aurie Chassin, R. Lorraine Collins, Jennifer Ritter, Mariela C. Shirley, Michael J. Zvolensky, and Todd B. K ashdan

Establishing Common Ground: Similar Themes and Issues across the Lifespan Models of vulnerability to substance use and abuse in adolescence and adulthood that encompass biopsychosocial factors suggest several areas of overlap and continuity. We highlight four common areas of vulnerability across the lifespan: genetic and biological factors, temperament and personality factors, social environmental influences, and cognitive influences. Thus, the major categories of etiological and maintenance factors are similar across the lifespan, but the specific manifestations may vary at different ages (e.g., parental influences versus peer influences) and the importance of particular factors also may differ at specific ages. While the same variables may predict vulnerability across the lifespan, questions remain (Masten, Faden, Zucker, & Spear, 2008; Zucker, Donovan, Masten, Mattson, & Moss, 2008) regarding what disengages these at different points in time, and the type of vulnerability that is being predicted (e.g., initiation, age of onset, use, abuse vs. dependence, who is more likely to mature out or never develop problematic use). For example, it is well known that age is highly correlated with “stage” of use. Genetic vulnerability is one type of influence that operates across the lifespan, although recent data suggest that early substance use is more strongly influenced by social and family environment factors and that the strength of genetic influences increases with age (Kendler, Schmitt, Aggen, & Prescott, 2008). Some hypothesized mechanisms underlying genetic influence are likely evident at all ages. For instance, it has been hypothesized that genetically

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vulnerable individuals experience different psychopharmacological effects of substances, and these differential sensitivities might be expected to be present in childhood, adolescence, and adulthood. However, the effects of these heritable individual differences would be expressed only when the person has access to psychoactive substances and begins to experiment with their use, usually in adolescence or young adulthood. Temperament and personality influences include a variety of characteristics, ranging from deficits in self-regulation to levels of emotional responsivity, and behavioral undercontrol; behavioral undercontrol has been identified as a risk factor for both adolescent and adult vulnerability to substance use disorders (SUDs). Adolescent and adult substance abusers, who are characterized by high levels of neuroticism (negative affectivity) and low levels of conscientiousness, generally manifest low behavioral control and regulation (Gollnisch, 1997; McGue, Slutske, & Iacono, 1999). Other research suggests that deficits in the ability to tolerate aversive internal states and life stressors may play a formative role in the maintenance of certain types of substance use (e.g., cigarette smoking) across the lifespan (Brown, Lejuez, Kahler, Strong, & Zvolensky, 2005). Thus, although specific indicators or measures of temperament and personality vary across different age groups, there seems to be substantial continuity in their underlying contribution to vulnerability for substance abuse. Social and cultural influences play important roles in both adolescence and adulthood. Social networks (e.g., family and peers) that approve, tolerate, or model substance use encourage use, thereby increasing vulnerability for substance use disorders. The specific sources of influence may vary at different stages of development. Initially parents/family may serve as models and important socializing agents, whereas peers become important during adolescence and partners/spouses become more important during adulthood. Of course, because some substances are legal for adults but illegal for adolescents (i.e., tobacco and alcohol), there may be differential social access across age that affects consumption patterns. The role of the neighborhood environment is less well studied, although work on alcohol outlet density is an exception (Gruenewald, 2008; Paschall, Grube, Black, & Ringwalt, 2007; Treno, Ponicki, Remer, & Gruenewald, 2008). However, risks related to poverty, deteriorated neighborhoods, high crime, and easy access to drugs are likely to play a role in substance use in both adolescence and adulthood. For adolescents, risk also has been associated with affluent neighborhoods, in which high stress and psychologically absent parents may create similar risk factors to those in impoverished neighborhoods (Luthar & Latendresse, 2005). Similarly, the norms and values of the individual’s social context (including advertising and policies related to access and use of licit substances) remain constant influences on substance use and abuse across the lifespan. Socialization effects also point to similarities across the lifespan. That is, in both adolescence and adulthood, the demands of successful role performance can inhibit substance use. The content of the roles may be different in

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adolescence and adulthood. During adolescence, school and athletic performance might be important inhibitors of substance use, whereas during adulthood, work, marriage, and parental roles may become important. Disruption of social roles can increase vulnerability for substance use, and substance use can impair the successful acquisition of social roles. Despite substantial similarities across the lifespan, however, there is also some evidence that the developmental timing of social roles can influence vulnerability. For example, the transition to parenthood during adolescence does not have the same effect in reducing substance use as a later transition to parenthood (Little, Handley, Leuthe, & Chasin, 2009). Finally, data from both adolescence and adulthood suggest that individuals who have more positive beliefs about the effects of substance use (i.e., positive expectancies) are more likely to use and abuse substances. Likewise, expectancies that substances will reduce negative affect are often related to individual differences in affective vulnerability (Brandon & Baker, 1991). The specific content and organization of expectancies vary with age and experience such that adolescents report more diffuse and generally positive beliefs, whereas with greater age and substance use experience these beliefs become more homogeneous and “crystallized” (Christiansen, Goldman, & Inn, 1982). Yet, beliefs about the effects of alcohol and drugs are related to substance use in similar ways for adolescents and adults. Overall, there are important commonalities in vulnerability factors for alcohol and drug abuse/dependence for adolescents and adults. Although specific manifestations of the vulnerability factors, as well as their relative importance, may vary in adolescence versus adulthood, several of the underlying sources of vulnerability are indeed similar across the lifespan.

Points of Departure: Issues at Different Developmental Periods Despite substantial common ground, there also are points of departure in vulnerability for substance use problems where it is necessary to consider the features typifying adolescents as distinct from those of adults. First, although current practice is to use the same diagnostic criteria across the lifespan, some of these criteria appear to be inappropriate for capturing adolescent substance abuse and dependence. For example, it may be difficult to distinguish the symptom of tolerance from adolescents’ “learning” to use substances, and social role impairment criteria may be inappropriate for adolescents who do not occupy occupational and marital roles. The differing consumption patterns, greater polydrug use, and different role occupancies of adolescents versus adults create challenges in using a single set of diagnostic criteria across the lifespan. Thus, future research might usefully focus on creating diagnostic criteria that better reflect the unique nature of adolescent substance abuse and dependence. Of particular need are diagnostic criteria that incorporate



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developmental transitions and consider the interplay between these and risk/ resiliency factors (Chung & Martin, 2005; Chung, Martin, & Winters, 2005; Martin, Chung, Kirisci, & Langenbucher, 2006). Moreover, the fact that adolescents have been reported to meet dependence criteria at lower levels of consumption may reflect either age variations in the appropriateness of the criteria or age differences in vulnerability to dependence (or both). Given recent animal research data (reviewed by Chassin, Beltran, Lee, Haller, & Villalta, Chapter 5, in this volume), which show age differences in sensitivity to some substance use effects, it is possible that adolescents have a unique vulnerability to the effects of substance use that make them more likely to develop clinical substance use disorders as compared to adults who use substances at the same level of quantity and frequency. For example, heavy alcohol use during adolescence affects learning and self-regulation (see Windle et al., 2008, for a review). An important future research direction is to understand the generalizability of these animal models to human adolescents. Moreover, the significance of recent findings regarding adolescent neurobiological development (particularly the disjunction in the developmental time courses of appetitive versus self-regulatory systems) requires further study as it relates to vulnerability for substance use disorders. Other important distinctions between substance use in adolescence and adulthood are social context and relative social acceptance. This point is particularly salient for alcohol consumption and cigarette smoking, which are illegal behaviors for adolescents but legal ones for adults. Theoretical models of “problem behaviors” (including alcohol and drug use) note the age-graded nature of these behaviors: use at younger ages is considered more socially deviant and associated with other forms of deviant behavior than is use at older ages (Jessor & Jessor, 1977; Donovan & Jessor, 1985). The implication of these models is that antisocial behavior and other forms of deviance are more strongly predictive of alcohol use, cigarette smoking, and other drug use for adolescents than for adults. Consistent with this type of conceptualization, Carlson, McLarnon, and Iacono (2007) found that early-onset substance disorders were more strongly associated with externalizing disorders than were late-onset substance disorders. An important area for theory and empirical research is the exploration of heterogeneity among substance abusers. A substantial body of research on subtypes of alcoholics already exists (e.g., distinctions between Type A and B alcoholism [Babor, 1994]; Type 1 and Type 2 alcoholism [Cloninger, 1987]). Babor’s Type B and Cloninger’s Type II alcoholism are characterized by early onset, substantial heritability, and significant levels of antisocial behavior. Babor’s Type A alcoholism and Cloninger’s Type I alcoholism are characterized by later (adult) ages of onset, fewer use-related social consequences, and less antisocial behavior but more affective symptomatology (Babor, 1994; Babor et al., 1992; Cloninger, 1987; Cloninger, Bohman, & Sigvardsson, 1981). In contrast, less research has been devoted to subtyping adolescent substance abuse and dependence, with most researchers assuming that adolescent

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problems reflect Type II or Type B disorders. Research to explore the heterogeneity of adolescent substance abuse/dependence is harder to conduct because of the lower base rates of clinical disorders. However, in some notable exceptions (Mezzich et al., 1993; Tarter, Kirisci, Hegedus, Mezzich, & Vanyukov, 1994; Tarter, Kirisci, & Mezzich, 1997), subtypes of adolescent alcoholism have been identified, and these subtypes seem to parallel the adult distinctions between antisocial alcoholism and negative affect-related alcoholism. These data suggest that more research on the potential heterogeneity of adolescent substance use disorders is warranted. Reports of a negative affect subtype of adolescent substance abuse/dependence also raises a somewhat controversial question regarding the relative importance of negative affect as a vulnerability factor in substance abuse/ dependence across the lifespan. In the adult literature, this controversy may be somewhat resolved by the notion of primary versus secondary alcoholism, in which secondary alcoholism is seen as motivated by self-medication of depression or anxiety (Schuckit, 1985). Similarly, Zucker (1994) has described negative affect alcoholism as one of four different subtypes of alcoholism, and others have suggested that depression in particular might be particularly important for alcoholism in women (Fillmore et al., 1997). Thus, among adults, the role of negative affect in vulnerability to substance abuse may be important for a subtype of the disorder and might vary with such factors as gender. Although not directly linked to the diagnosis of alcoholism and substance use disorders, models of the failure to self-regulate highlight the etiological role of negative affect in assessing risk for excessive alcohol use and alcoholism, once the individual has become a social drinker. Two such models focus on (1) drinking restraint and the limit violation effect (Collins, 1993) and (2) self-control strength (Muraven & Baumeister, 2000). The drinking restraint model posits that a preoccupation with controlling alcohol intake paradoxically may increase the risk of excessive use, which occurs as a function of experiencing the limit violation effect (LVE). In the LVE, restrained drinkers who both fail to regulate their alcohol intake and attribute the failure to themselves experience negative mood effects. To alleviate the negative mood, they continue to drink, thereby drinking to excess. Over time, restrained drinkers experience multiple cycles of excessive drinking in which limit setting leads to failures to regulate alcohol intake. Support for aspects of this model has come from cross-sectional surveys (e.g., Collins, Koutsky, Morsheimer, & Maclean, 2001; Collins & Lapp, 1991), experiments (Collins, Gollnisch, & Izzo, 1996; Collins, Lapp, & Izzo, 1994), and more recently intensive self-monitoring using ecological momentary assessment (EMA) techniques (Stone, Shiffman, Atienza, & Nebeling, 2007). EMA has been used to examine the relationship between negative mood and drinking at both the episode level (i.e., how mood at the end of a drinking episode is related to subsequent drinking; Muraven, Collins, Morsheimer, Shiffman, & Paty, 2005a; Swendsen et al., 2000) and the day



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level (i.e., how drinking during the whole day affected drinking the next day; Muraven, Collins, Morsheimer, Shiffman, & Paty, 2005b). Consistent with the model of drinking restraint and the LVE, experiencing negative affective states after drinking resulted in deregulating, leading to greater subsequent alcohol intake, especially for heavier drinkers. Of note, using similar technologies, this conceptual model also has the potential for better understanding excessive, uncontrollable smoking behavior (Shiffman et al., 2007) and perhaps behavior relating to other licit and illicit substances. EMA also has been used to examine the self-control strength approach to explaining excessive drinking, which posits that the exertion of self-control in daily life undermines individuals’ subsequent ability to use self-control to regulate their alcohol intake (see Muraven, Collins, & Nienhaus, 2002). Consistent with self-control strength theory, participants who experienced greater self-control demands during the day were more likely to drink to excess that night (Muraven, Collins, Shiffman, & Paty, 2005). In addition, experiencing greater-than-average self-control demands led to more drinking on occasions when the individual planned to limit alcohol intake, suggesting that restraint also played a role in this failure to regulate intake. Both the restraint and selfcontrol strength models suggest ways in which negative affect and states such as being depleted can enhance the progression to more problematic drinking and alcoholism. In adolescence, the importance of negative affect has been questioned repeatedly. Some researchers have argued that adolescent substance abuse/ dependence may be motivated by a need to cope with negative emotions, and adolescent substance abuse has been linked with both depression and anxiety (Clark et al., 1997; Deykin, Levy, & Wells, 1987). However, the role of negative affect in adolescent substance abuse/dependence remains controversial (Swaim, Oetting, & Beauvais, 1989), and some researchers suggest that negative affect results from rather than causes substance use (Hansell & White, 1991). It may be that, for adolescent forms of substance use and substance disorders, negative affect alone is not a vulnerability factor. For example, adolescents who cope with negative affect through social withdrawal and isolation may be less likely to participate in a peer culture that promotes substance use and thus may be at lower risk for alcohol problems. However, negative affectivity may operate in combination with other risk factors. For example, adolescents who both experience negative affect and show poor self-regulation are more likely to engage in antisocial behaviors in general and substance use in particular (Miller, Lochman, Coie, Terry, & Hyman, 1998). There may be some emerging parallel to adult findings in this domain, where some research has found that negative affectivity and low tolerance for distress are related to more persistent and ingrained patterns of substance use (Abrantes et al., 2008). Prospective research with appropriate measures of negative affect and sufficient base rates of substance use/abuse will be needed to further test and comprehensively evaluate these hypotheses with adolescents and other populations. Moreover, because early stress and adversity can have long-term

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effects on the stress response system, and because stress exposure at different ages can have different effects (Andersen & Teicher, 2009), a lifespan developmental perspective is particularly important for understanding the effects of negative affectivity on the development of substance disorders.

Learning from Each Other: Improving Future Research through Cross-Fertilization Our description of commonalities and points of departure suggests fruitful areas for a lifespan approach to understanding vulnerability to substance abuse. Zucker (2006) has presented such a perspective for understanding alcoholism that could easily be applied to understanding the use and abuse of a variety of substances. His framework incorporates a developmental biopsychosocial perspective for evaluating multiple etiologies and courses of alcohol disorders. Within this perspective, sources of influence include biological, psychological, peer, familial, and sociocultural factors, and life stages range from the prenatal through late adulthood. Over the lifespan, sources of influence interact with risk and protective factors to characterize levels of vulnerability. There are many ways in which investigators of adolescents and investigators of adults can learn from each other. For example, for obvious ethical reasons research that calls for administering substances to study participants are conducted solely with adult rather than adolescent samples, but researchers can use these studies to draw hypotheses about adolescents to test with more indirect measures. In addition, subtyping research can more easily be done with adult samples who have a higher prevalence of clinical disorder (at least in early adulthood). Research on adolescents could benefit from considering the adult literature on subtyping and by looking for heterogeneity in vulnerability to substance abuse disorders. In addition, there is a need to better integrate translational work from animal studies into human models. On the other hand, research on vulnerability factors is easier to conduct with younger populations, for whom it is easier to separate the antecedents of substance disorders from their consequences. Longitudinal studies provide powerful tests of developmental issues in vulnerability to substance abuse. They can link child and adolescent vulnerability factors to both adolescent-onset and adult-onset forms of substance use disorders. They also can help to establish the continuity of constructs across developmental stages; for example, such studies can elucidate the ways in which early temperament links to later adult personality. The combination of both designs to study age cohorts (cross-sectional) through an entire lifespan (longitudinal) may be useful. Finally, biopsychosocial models are informed in important ways by animal studies in which researchers manipulate exposure to vulnerability factors and to substance use at different ages to more directly examine age-related differences in vulnerability.



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The research described in the two preceding chapters on substance abuse illustrates clearly that substance use disorders are developmental in character. Comprehensive models that explicitly incorporate a developmental perspective already exist (e.g., Tarter & Vanyukov, 1994; Sher, 1991; Zucker, 2006). Although complex, these models provide useful starting points for conceptualizing vulnerability, designing meaningful research, and developing effective intervention strategies.

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comes: Exploring the contributions of beverage instructions, beverage content, and selfmonitoring. Journal of Studies on Alcohol, 57, 563–571. Collins, R. L., Koutsky, J. R., Morsheimer, E. T., & Maclean, M. G. (2001). Binge drinking among underage college students: A test of a restraint-based conceptualization of risk for alcohol abuse. Psychology of Addictive Behaviors, 15, 333–340. Collins, R. L., & Lapp, W. M. (1991). Restraint and attributions: Evidence of the abstinence violation effect in alcohol consumption. Cognitive Therapy and Research, 15, 69–84. Collins, R. L., Lapp, W. M., & Izzo, C. V. (1994). Affective and behavioral reactions to the violation of limits on alcohol consumption. Journal of Studies on Alcohol, 55, 475– 486. Deykin, E., Levy, J., & Wells, V. (1987). Adolescent depression, alcohol, and drug abuse. American Journal of Public Health, 77, 178–182. Donovan, J. E., & Jessor, R. (1985). Structure of problem behavior in adolescence and young adulthood. Journal of Consulting and Clinical Psychology, 53, 890–904. Fillmore, K. M., Golding, J. M., Leino, E. V., Motoyoshi, M., Shoemaker, C., Terry, H., et al. (1997). Pattern and trends in women’s and men’s drinking. In R. W. Wilsnack & S. C. Wilsnack (Eds.), Gender and alcohol (pp. 21–48). New Brunswick, NJ: Rutgers Center of Alcohol Studies. Gollnisch, G. (1997). Multiple predictors of illicit drug use in methadone maintenance clients. Addictive Behaviors, 22, 353–366. Gruenewald, P. (2008). Why do alcohol outlets matter anyway?: A look into the future. Addiction, 103, 1585–1587. Hansell, S., & White, H. R. (1991). Adolescent drug use, psychological distress and physical symptoms. Journal of Health and Social Behavior, 32, 288–301. Jessor, R., & Jessor, S. L. (1977). Problem behavior and psychosocial development: A longitudinal study of youth. New York: Academic Press. Kendler, K. S., Schmitt, E., Aggen, S. H., & Prescott, C. A. (2008). Genetic and environmental influences on alcohol, caffeine, cannabis, and nicotine use from early adolescence to middle adulthood. Archives of General Psychiatry, 65, 674–682. Little, M., Handley, E., Leuthe, E., & Chasin, L. (2009). The impact of parenthood on alcohol consumption trajectories: Variations as a function of timing of parenthood, familial alcoholism and gender. Development and Psychopathology, 21, 661–682. Luthar, S. S., & Latendresse, S. J. (2005). Children of the affluent: Challenges to well-being. Current Directions in Psychological Science, 14, 49–53. Martin, C. S., Chung, T., Kirisci, L., & Langenbucher, J. W. (2006). Item response theory analysis of diagnostic criteria for alcohol and cannabis use disorders in adolescents: Implications for DSM-V. Journal of Abnormal Psychology, 115, 807–814. Masten, A. S., Faden, V. B., Zucker, R. A., & Spear, L. P. (2008). Underage drinking: A developmental framework. Pediatrics, 121, 235–251. McGue, M. K., Slutske, W., & Iacono, W. G. (1999). Personality and substance use disorders: II. Alcoholism versus drug use disorders. Journal of Consulting and Clinical Psychology, 67, 394–404. Mezzich, A., Tarter, R., Kirisci, L., Clark, D., Buckstein, O., & Martin, C. (1993). Subtypes of early age onset alcoholism. Alcoholism: Clinical and Experimental Research, 17, 767– 770. Miller, S., Lochman, J., Coie, J., Terry, R., & Hyman, C. (1998). Comorbidity of conduct and depressive problems at 6th grade: Substance use outcomes across adolescence. Journal of Abnormal Child Psychology, 26, 221–232. Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion of limited resources: Does self-control resemble a muscle? Psychological Bulletin, 126, 247–259. Muraven, M., Collins, R. L., Morsheimer, E. T., Shiffman, S., & Paty, J. A. (2005a). One too many: Predicting future alcohol consumption following excessive drinking. Experimental and Clinical Psychopharmacology, 13, 127–136. Muraven, M., Collins, R. L., Morsheimer, E. T., Shiffman, S., & Paty, J. A. (2005b). The morn-



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Depression

Chapter 8

Vulnerability to Depression in Childhood and Adolescence Judy Garber

Considerable progress has been made toward describing the construct of depression in children and adolescents and understanding the processes underlying it (Birmaher et al., 1996). This chapter complements the next one (Hammen, Bistricky, & Ingram, Chapter 9, this volume) on depression in adults and focuses on issues of vulnerability to depression particularly relevant to youth. Many of the definitions, characteristics, and theories are similar for child and adult depression. This chapter highlights the features and empirical findings for depression in childhood and adolescence.

Definitions and Characteristics of Depression in Children and Adolescents Phenomenology Hammen, Bistricky, and Ingram (Chapter 9, this volume) describe the affective, behavioral, cognitive, and somatic symptoms that define the diagnosable syndrome of depression. The criteria outlined in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) that currently define depressive disorders are essentially the same, regardless of developmental level. Two minor differences are that, for children and adolescents, irritability is considered a manifestation of dysphoric mood, and dysthymia is defined as lasting a minimum of 1 rather than 2 years. Functional impairment is particularly important in distinguishing depressive disorders from normal mood variability in children as well as adults. Thus, according to DSM-IV there are few real developmental differ

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ences in the symptoms that constitute the syndromes of major depression or dysthymia. Infants have been observed to experience symptoms that characterize depression, including sadness, irritability, sleep and eating problems, fatigue, withdrawal, apathy, fussiness, and tantrums (Guedeney, 2007). The age of the emergence of other symptoms of depressive disorder (e.g., anhedonia, psychomotor changes, low self-worth, guilt, concentration problems, hopelessness, suicidality) is less clear. The five-axis classification system (Diagnostic Classification [DC]: 0–3) for mental health and developmental disorders in infancy includes infant depression as an Axis I mood disorder (Zero to Three, 2005) and is considered reliable and valid (Cordeiro, Caldeira Da Silva, & Goldschmidt, 2003; Guedeney et al., 2003). Failure to thrive (FTT) in infants has several similarities to depression in terms of psychomotor delay, behavioral difficulties, and feeding problems (Raynor & Rudolf, 1996) and may be one manifestation of a mood disorder in babies. The extent to which such depressive symptoms in very young children have continuity with adolescent- and adult-onset mood disorders, however, is still a matter of debate. In preschool-age children, a specific constellation of depressive symptoms characterized by developmentally modified symptoms of major depressive disorder (MDD) has been identified (Luby, Heffelfinger, Mrakotsky, et al., 2002). Whereas anhedonia was found to be a specific indicator, mood symptoms (i.e., sadness and irritability) were found to be sensitive indicators of depression in preschoolers. Although the most severely impaired preschoolers were diagnosed by using unmodified DSM criteria, and a subgroup even showed melancholic-like symptoms (Luby, Mrakotsky, Heffelfinger, Brown, & Spitznagel, 2004), the modified criteria identified a large number of seriously impaired children that would have been missed by the existing DSM-IV criteria (Luby, Mrakotsky, Heffelfinger, et al., 2003). Developmental psychopathologists (Cicchetti & Toth, 1998; Weiss & Garber, 2003) have suggested that manifestations of depression likely depend on the individual’s level of cognitive, social, and physiological development, and therefore the symptoms of depression might not be isomorphic across the lifespan. The broad criteria that define depression in adults may “need to be translated into age-appropriate guidelines for children, sensitive to developmental changes in the children’s experience and expression of depression” (Cicchetti & Schneider-Rosen, 1984, p. 7). Although there may be a core set of common depressive symptoms across all ages, other symptoms might be uniquely associated with the syndrome at different developmental levels (Avenevoli & Steinberg, 2001; Kovacs, Obrosky, & Sherrill, 2003). Developmental differences in depressive symptoms may occur in at least two ways. First, children and adults might have the same symptom but differ in how it is expressed. For example, dysphoric mood might be excessive crying in very young children, nonverbal sadness in school-age children, irritability in adolescents, and sadness in adults, but the core mood symptom is essentially the same across these age-specific expressions. Second, symptoms that

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constitute the syndrome could differ developmentally; that is, different combinations of symptoms would define the syndrome at different ages; appearing as developmental differences in the rates of particular symptoms and in the composition of the syndrome. A meta-analysis of 16 empirical studies comparing the rates of depressive symptoms in different age groups found developmental effects for 18 of the 29 (62%) core and associated depressive symptoms (Weiss & Garber, 2003). More developmentally advanced youth had higher levels of anhedonia, hopelessness, hypersomnia, weight gain, and social withdrawal, and lower levels of energy (see also Sorensen, Nissen, Mors, & Thomsen, 2005). Overall, adolescents tend to experience more vegetative symptoms (i.e., lack of energy, hypersomnia, weight loss), hopelessness/helplessness, and suicidality than do preadolescents (Yorbik, Birmaher, Axelson, Williamson, & Ryan, 2004). Thus, there appear to be developmental differences in the rates of at least some depressive symptoms in children versus adolescents. Weiss and Garber (2003) also reviewed studies comparing the structure of depression at different age levels and found that two studies reported a similar factor structure across ages, two found developmental differences, and one found mixed results. Thus, although some researchers have argued against the existence of developmental differences in depressive symptoms (e.g., Kashani, Rosenberg, & Reid, 1989; Ryan et al., 1987), the evidence does not support this conclusion. “The suggestion that the clinical presentation of major depression varies with age is far from resolved and more developmentally sensitive studies are required” (Goodyer, 1996, p. 407). Developmental differences in the phenomenology of depression are relevant to the issue of vulnerability because they might reflect differences in the causal processes that underlie the disorder at different ages. For example, Wickramaratne and Weissman (1998) found that, whereas childhood-onset depressive disorder was associated with early onset of mood disorders in parents, adolescent-onset depression was not, and therefore they suggested that childhood- and adolescent-onset mood disorders might be etiologically distinct. Thus, different causal processes could result in a different configuration of symptoms. Even if children were developmentally capable of experiencing the same symptoms of depression as adults, certain symptoms that are tied more closely to one causal mechanism or another could be more or less a part of depression in children as compared to adults. Differences in causal processes might arise in several ways. First, both a specific symptom and the full syndrome of depression may be caused by a common third variable; that is, they may share a mutual causal agent. Second, an individual symptom might be related to the broader syndrome of depression because the symptom itself may be part of the causal mechanisms producing the depression. For example, the strong correlation of pessimism and depression in both adults (e.g., Beck, Steer, Beck, & Newman, 1993) and children (e.g., Abela & Hankin, 2008) might be because such hopelessness is part of the causal process underlying the disorder (Abramson, Metalsky, & Alloy,

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1989). Third, a specific symptom could be related to the disorder because it is a consequence of other symptoms of the depressive syndrome. For instance, concentration problems might be a result of other symptoms of depression (e.g., distracting negative cognitions or fatigue). Thus, developmental differences in the causal processes or consequences of depression could produce differences in the relations among depressive symptoms at different ages. For example, if the etiology of depression is less biological in children than in adults (e.g., Post, 1992), then the relations among symptoms resulting from these biological processes and the rest of the syndrome of depression would be greater for adults. This would occur because the causal processes underlying depression would be more responsible (both in absolute terms and relative to the nondepressive causes of the symptom) for interindividual variability in the symptoms. That is, compared to children, in adults a greater proportion of the variance in a particular symptom (e.g., sleep disturbance) may be accounted for by the causal processes underlying depression. Developmental factors unrelated to depression also could cause age differences in the relations among depressive symptoms. Even if the causal processes underlying depression were the same in children and adults, some symptoms (e.g., fatigue) could be more a part of depression at one developmental period than another because the normative causal processes producing that symptom change developmentally. For example, hormones associated with puberty but not with depression could become increasingly responsible for the fatigue and sleepiness often observed in adolescents (Carskadon, Keenan, & Dement, 1987). Therefore, the causal processes underlying depression would be less of a factor proportionally for interindividual variability in fatigue, thereby making the relation between depression and fatigue smaller for children than for adults (Weiss & Garber, 2003). Thus, important theoretical and empirical factors likely explain why symptoms of depression differ across development.

Comorbidity Identifying comorbidity is particularly important in studies of vulnerability because some factors considered to be risks for depression could be causes of the comorbid condition instead. Moreover, some comorbid conditions may exacerbate or trigger depression. Thus, comorbidity may be attributable to shared vulnerability between two disorders, or one disorder may be a cause or a consequence of the other. Comorbidity with depression is very common in children and adolescents, with rates ranging from about 42% in community samples (e.g., Rohde, Lewinsohn, & Seeley, 1991) to as high as 75% in clinical samples (e.g., Kovacs, 1996b; Sorensen et al., 2005). Dysthymia is the most common comorbid disorder with MDD (Kovacs, 1994). Children with double depression have more severe and longer depressive episodes, a higher rate of other comorbid disorders (e.g., generalized anxiety disorder), more suicidality, less social com-

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petence, and experience less parental monitoring (Goodman, Schwab-Stone, Lahey, Shaffer, & Jensen, 2000). Other common comorbid diagnoses with MDD in children include anxiety disorders, oppositional defiant disorder (ODD), conduct disorder (CD), attention-deficit/hyperactivity disorder (ADHD), and substance abuse (Angold, Costello, & Erkanli, 1999; Wagner, 2003). Anxiety and depression are so highly comorbid in youth that some researchers have argued that the two disorders are not distinct (e.g., Patterson, Greising, Hyland, & Burger, 1994), share a single underlying process referred to as negative affectivity (e.g., Watson & Clark, 1984), or share a genetic diathesis (e.g., Hudziak, Rudiger, Neale, Heath, & Todd, 2000; Middeldorp, Cath, van Dyck, & Boomsma, 2005). Patterns of comorbidity with depression vary across age and gender. In younger children anxiety and depression form a unified indistinguishable construct, whereas in older children a dual-factor or tripartite model is more common (Cole, Truglio, & Peeke, 1997). In preadolescents, depression often co-occurs with separation anxiety, ADHD (Yorbik et al., 2004), and conduct problems (Harrington, Fudge, Rutter, Pickles, & Hill, 2000), whereas in adolescents common comorbid conditions include ODD and substance use disorders (SUDs), particularly in males, and eating disorders, particularly in females (Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993). Concurrent comorbidity as well as homotypic and heterotypic continuity are more common in girls than in boys (Costello, Mustillo, Erkanli, Keeler, & Angold, 2003). Comorbidity with depression is associated with higher risk of recurrence, longer duration, suicide attempts, functional impairment, less favorable response to treatment, and greater utilization of mental health services (Birmaher et al., 1996; Ezpeleta, Domenech, & Angold, 2006; Rudolph & Clark, 2001). Comorbidity adds to the complexity and severity of depressive disorders in children and is not simply the result of methodological problems, arbitrary groupings of symptoms into diagnoses, or recruitment bias (Angold et al., 1999). Comorbidity also might reflect different processes underlying certain disorders. For example, depressed adolescents with comorbid anxiety show different patterns of brain functioning as compared to those without comorbid anxiety (Kentgen et al., 2000). Comorbidity may stem from common etiological influences such as shared genetic liability or overlapping risk factors. For example, heritability estimates of the liability to depression cotransmitted with anxiety is about 60% (Hudziak et al., 2000; Thapar & McGuffin, 1997). The co-occurrence of depression with disruptive disorders and SUDs may result from shared risk such as abuse, family violence and discord, deviant peers, and parental psychopathology (Fergusson, Wanner, Vitaro, Horwood, & Swain-Campbell, 2003; Nomura, Wickramaratne, Warner, Mufson, & Weissman, 2002). Comorbidity also may be explained by the developmental progression of one disorder into another (e.g., Cole, Peeke, Martin, Truglio, & Seroczynski,

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1998; Kim-Cohen et al., 2003). Kovacs and Devlin (1998) proposed that the move from anxiety to depression reflects a “readiness” (p. 54) to show certain physiological aspects of anxiety (e.g., agitation and hyperarousal) earlier in development and certain other physiological (e.g., vegetative symptoms) and cognitive (e.g., rumination) aspects of depression later in development. Others (Eaves, Silberg, & Erkanli, 2003) have proposed that a shared genetic liability may be differentially expressed as anxiety earlier and depression later in development. Eaves et al. (2003) have further suggested that genes that affect liability to anxiety also may lead to an increased likelihood of exposure to depression-generating life events. Alternatively, disorders may unfold sequentially wherein one disorder actually serves as a vulnerability factor for another. The dual failure model (Patterson & Stoolmiller, 1991) proposes that disruptive behavior disorders create academic and social problems that heighten risk for depression. Peer rejection and school failure often associated with impulsivity and hyperactivity in children with ADHD may be precursors to depression (Jaffee et al., 2002). Finally, longitudinal studies have found a bidirectional relation between other problems and depression in youth, with substance use (alcohol, drug, and tobacco) both preceding and following the onset of depression (Rohde, Kahler, Lewinsohn, & Brown, 2004a, 2004b; Rohde, Lewinsohn, Brown, Gau, & Kahler, 2003). Discovering the causes and consequences of comorbidity has implications for understanding vulnerability to depression across development. Testing among the various alternative explanations of comorbidity could help identify both shared and specific risk factors for depressive disorders, which then would increase our ability to predict how and when one disorder precedes or follows the onset of depression. Such knowledge is crucial in formulating interventions aimed at disrupting this sequence across development. Other important questions relevant to comorbidity and vulnerability include: What is the temporal relation between depression and comorbid disorders? What explains concurrent versus sequential comorbidity? What is the trajectory of different comorbid conditions across development, and what accounts for these changes? How can interventions effectively reduce comorbidity?

Continuity The continuity of depression across symptoms, syndrome, and disorder also is relevant to discussions about vulnerability. Do the same mechanisms that lead to depressive mood also produce depressive syndromes and disorders? How and why does depressive mood develop into a more severe and sustained depressive syndrome for some people but not others? Do some individuals simply have more of the causal agent, or do qualitatively different processes lead to the full depressive syndrome and disorder in those who are vulnerable? Compas, Ey, and Grant (1993) suggested that the three levels of depression are hierarchical and depressive disorders are a subset of depressive syndrome,

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which is a subset of depressed mood. Furthermore, the transition from one level to the next is the result of “dysregulation or dysfunction in biological, stress, and/or coping processes” (Compas et al., 1993, p. 336), and there likely are important developmental changes in all three processes that make adolescence a time of particularly increased vulnerability. The issue of continuity also can be affected by how the construct is measured. Much of the research on depression in youth has used questionnaires to assess depressive symptoms. The most commonly used measures are selfreport (e.g., Children’s Depression Inventory; Kovacs, 1981) and parent report (e.g., Child Behavior Checklist [CBCL]; Achenbach & Edelbrock, 1991). Such measures not only evaluate levels of distress but also assess other symptoms of psychopathology. Typically studies that use such questionnaires focus on community (school) samples, which generally have lower levels of severity. It is not clear whether the same etiological correlates characterize depression across various levels of severity. Additionally, measures such as the CBCL include other internalizing symptoms, particularly anxiety; therefore, it is difficult to know whether the correlated vulnerability factors are specific to depression or characteristic of internalizing symptoms in general. Overall, the issues of continuity, stability, and change in depressive symptoms and disorders in individuals with varying ages of onset from infancy through adulthood need further study (Avenevoli & Steinberg, 2001).

Course and Outcome Early-onset MDD is a chronic and recurrent illness associated with significant impairment in interpersonal relationships, school and work settings, and overall quality of life (Birmaher et al., 2004; Geller, Zimerman, Williams, Bolhofner, & Craney, 2001b). In children 8–13 years old major depressive episodes (MDEs) tend to be acute and have an average duration of 7–9 months and a maximal recovery rate at about 18 months from onset (Kovacs, 1996a). Among children with dysthymia, 91% eventually recover, and the median episode length is 4 years. Among outpatient and inpatient youth with MDD, approximately 90% recover within 1.5–2 years (Birmaher, Arbelaez, & Brent, 2002); the duration of MDEs in nonreferred community samples of adolescents (Lewinsohn, Clarke, Seeley, & Rohde, 1994) tends to be shorter (i.e., about 26 weeks). Recurrence, defined as the onset of a new depressive episode, is high in children and adolescents (Kennard, Emslie, Mayes, & Hughes, 2006). Younger age of onset significantly predicts relapse (e.g., Birmaher et al., 1996). MDD has a cumulative probability of recurrence of 40% by 2 years and 70% by 5 years (Emslie, Rush, Weinberg, Guillion, et al., 1997a). A 9-year follow-up study found that 80% of children with prior dysthymia and 50% of children with prior MDD had subsequent episodes of depression (Kovacs, 1996a). Results of investigations of the long-term course of early-onset mood disorders have been inconsistent. Some studies have found that prepubertal-onset

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depression did not show continuity into adulthood but was sometimes followed by behavioral problems and impaired functioning (e.g., Harrington et al., 1990; Weissman et al., 1999b). Other studies (e.g., Dunn & Goodyer, 2006; Geller, Zimerman, Williams, Bolhofner, & Craney, 2001a; Kovacs, 1996b; Weissman et al., 1999a) have shown that depression during childhood recurs into adulthood. Still other studies (e.g., Weissman et al., 1999) have reported that early-onset depression has a bipolar course, emerging over time. One predictor of the recurrence and continuity of childhood depression into adulthood is a positive family history of MDD. Weissman and colleagues (1999) reported that patients with prepubertal-onset MDD who experienced a recurrence had higher rates of depressive disorders in their first-degree relatives. Depression at the symptom level also has been found to be relatively stable in children (e.g., Cole, Martin, Powers, & Truglio, 1996; Hofstra, van der Ende, & Verhulst, 2000). Cole and colleagues (1996) reported high stability of depressive symptoms assessed by self-, teacher, parent, and peer report over a 6-month period for children in both grades 3 and 6. In contrast, a prospective study of 3- to 12-year-old children showed a lack of stability from very early childhood to preadolescence in depressive symptoms based on self- and parent report (Pihlakoski et al., 2006). An important question with respect to the issue of vulnerability is what accounts for the stability and recurrence of depression from childhood to adulthood. Factors associated with the onset, duration, and recurrence of early-onset depression include demographic (e.g., age, gender), individual (e.g., preexisting diagnosis, negative cognitive style), family (e.g., parental psychopathology), biological (e.g., neurobiological dysregulation), and psychosocial (e.g., poor support, stressful life events) (Birmaher et al., 2004; Garber, 2007; Timbremont & Braet, 2004). For example, Birmaher and colleagues (2004) showed that for girls higher levels of guilt, more prior depressive episodes, and greater parental psychopathology predicted a more severe clinical course of depression. Although the same underlying processes may cause depression across the lifespan, depressions that recur in the same individuals at different ages may be the result of correlated, yet different, risk factors (e.g., parental depression and parental marital discord). Another possibility is that earlier episodes of depression create biological and/or psychological scars that sensitize individuals to later exposures to even low levels of the etiological agent(s). That is, recurrence of depression may result from kindling, sensitization, or scarring (Lewinsohn, Steinmetz, Larson, & Franklin, 1981; Monroe & Harkness, 2005; Post, 1992). Prior MDEs may increase vulnerability to subsequent episodes, and as the number of past depressive episodes increases, so does the probability of future episodes. Teasdale’s (1983, 1988) differential activation hypothesis posited that vulnerability to subsequent, more severe, depressive episodes is influenced by patterns of information processing that occur during earlier milder depressions. Depressed mood presumably activates negatively biased interpretations of experiences, which then maintain and exacerbate

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the dysphoria into further clinical depression. The kindling hypothesis asserts that prior episodes of depression “leave behind neurobiological residues that make a patient more vulnerable to subsequent episodes” (Post, 1992, p. 1006). A related explanation is that earlier depressions change individuals in some ways, which then lead to their generating the kinds of stressful environments that are likely to precipitate future episodes (Hammen, 1991). Finally, the important distinction between relapse of symptoms within the same episode versus recurrence of a totally new episode is relevant to discussions about vulnerability (Prien & Kupfer, 1986). The same processes may not underlie these different kinds of return of depressive symptoms (Hollon, Evans, & DeRubeis, 1990). Therefore, studies of vulnerability need to identify what factors maintain depressive symptoms within an episode, account for relapse of the same episode once it has remitted, and underlie the recurrence of depression over time.

Prevalence of Depression in Childhood and Adolescence The prevalence of mood disorders increases from childhood to adolescence. MDD is rarely assessed in infants, uncommon in preschool-age children, relatively infrequent during middle childhood, and increases significantly during adolescence. A meta-analysis (Costello, Foley, & Angold, 2006) showed that the overall prevalence estimate of depression in children is 2.8%, although the rate varies by age, informant, and type of depression (i.e., MDD, dysthymia). Among very young children (i.e., ages 2–5), prevalence rates have been found to be 1.4% for MDD, 0.6% for dysthymic disorder (DD), and 0.7% for depression not otherwise specified (NOS)/minor depression, with rates significantly higher in older preschoolers (3.0%) than in toddlers (0.3%; Egger & Angold, 2006). In children ages 9, 11, and 13, 3-month prevalence was found to be 0.03% for MDD, 13% for DD, and 1.45% for depression NOS (Costello et al., 1996). Thus, the rates of diagnosed depressive disorders in preadolescents are relatively low, although they are higher when based on children’s as compared to parents’ report (Rubio-Stipec, Fitzmaurice, Murphy, & Walker, 2003). When impairment criteria are included, as required in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994), lower rates of depression (3.4%) are found as compared to when impairment is not included (4.1%; Canino et al., 2004). The rates of clinical depression rise sharply from childhood through late adolescence (Costello et al., 2003). By mid- to late adolescence, rates of MDD are comparable to those found in adults. Adolescence is a particularly vulnerable period for first episodes of MDD (Hankin et al., 1998) and likely is the time when many depressed adults experience their first serious mood problems (Kessler et al., 1993). Lifetime prevalence rates of MDD in adolescents have ranged from 9 to 24% (Lewinsohn & Essau, 2002; Avenevoli, Knight, Kessler, & Merikangas,

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2008). An epidemiological survey in the United States, the National Comorbidity Study, reported a lifetime prevalence rate of 15% for MDD in adolescents (Kessler & Walters, 1998). Similar rates have been found in other community samples of adolescents (Lewinsohn, Rohde, Seeley, Klein, & Gotlib, 2000; Rao, Hammen, & Daley, 1999). Subclinical depression also is quite high in adolescents, with about 10–20% of youth experiencing subsyndromal or minor depression (Kessler & Walters, 1998). An even greater percentage of youth (20–50%) endorse significant levels of depressive symptoms on self-report measures (Kessler, Avenevoli, & Merikangas, 2001). Increases in depressive symptoms during adolescence are associated with significant functional impairment (Gotlib, Lewinsohn, & Seeley, 1995) and the onset of subsequent clinical disorders (Angst, Sellaro, & Merikangas, 2000). Epidemiological data concerning age trends in prevalence rates can serve as a guide to inquiries about mechanisms underlying the disorder (Costello et al., 2006; Rutter, 1988). For example, why is MDD less common during childhood than adolescence? What about childhood prevents depression from occurring or what happens during adolescence that increases risk for depression? What accounts for the change in the sex ratio of depression from childhood to adolescence?

Gender Differences Across cultures, epidemiological studies repeatedly have found approximately twice the rate of depression in women as compared to men (Weissman & Olfson, 1995). This 2-to-l sex ratio, however, does not appear until adolescence. Whereas some researchers have found the rates of MDD to be about equal in preadolescent girls and boys (e.g., Angold & Rutter, 1992; Fleming & Offord, 1990), others have reported higher rates among preadolescent boys than girls (e.g., Angold, Costello, & Worthman, 1998; Steinhausen & Winkler, 2003). Angold and colleagues (1998) showed that girls had higher rates of depressive disorders after Tanner Stage III, whereas boys had higher rates before this stage. Findings of sex differences in minor depression or depressive symptoms have been more mixed (e.g., Gonzalez-Tejera et al., 2005). A meta-analysis of 310 studies using the Children’s Depression Inventory (CDI) found no significant sex differences in self-reported depressive symptoms for children ages 8–12, although boys in this age range reported slightly higher scores than girls (Twenge & Nolen-Hoeksema, 2002). In early adolescence (about 12–14 years of age), girls begin to show higher levels of depressive symptoms and disorders than boys (Angold, Erkanli, Silberg, Eaves, & Costello, 2002; Costello et al., 2003; Hankin et al., 1998). This sex difference increases throughout adolescence until it reaches the 2:1 female-to-male ratio seen throughout adulthood. Sex differences in the manifestation of depression also have been noted. Young depressed females are more likely than males to experience appetite and weight problems, worth-

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lessness or guilt (Lewinsohn, Rohde, & Seeley, 1998), and suicidality (Yorbik et al., 2004). MDD tends to be more recurrent and insidious in adolescent females than males (Lewinsohn & Essau, 2002). Theoretical models proposed to explain the increasing rates of depression in females during adolescence (Cyranowski, Frank, Young, & Shear, 2000; Hankin & Abramson, 2001; Nolen-Hoeksema & Girgus, 1994; Rudolph, 2009) emphasize the contributions of biological, psychological, interpersonal, and contextual factors and their interactions during the transition to adolescence. Hormonal changes during puberty may be one explanation of emerging sex differences in depression during adolescence (Angold, Costello, Erkanli, & Worthman, 1999; Susman et al., 1985). Angold, Worthman, and Costello (2003) reported that higher levels of androgen and estradiol were associated with depression in girls at puberty; when sex steroid levels (combined testosterone and estradiol) reached the upper 30th percentile, girls were five times more likely to be depressed than those with lower levels, and reaching the upper 10% further quadrupled the rates of depression.

Methods for Studying Vulnerability to Depression Several different methods have been used to examine vulnerability to depression in children and adolescents, including cross-sectional, prospective, offspring, and intervention studies (Ingram, Miranda, & Segal, 1998). Crosssectional studies can identify factors that characterize depressed versus nondepressed youth, although they cannot address the temporal and causal relations between such factors and depression. A particularly interesting crosssectional comparison is among never depressed, currently depressed, and formerly depressed individuals. If a stable vulnerability marker exists, it should characterize both currently and formerly depressed individuals as compared to never depressed controls (although see Just, Abramson, & Alloy, 2001). Prospective designs can show that a variable temporally precedes an increase in depressive symptoms or the onset of depressive disorder, but such studies also are not conclusive with regard to causality because some unmeasured third variable could account for the link between the vulnerability factor and subsequent depressive outcome. Studies of the offspring of depressed parents can provide evidence of potential risk factors before the children ever experience depression (Goodman & Gotlib, 1999) and can help rule out the problem of reverse causality, that is, that the experience of depression produced the vulnerability rather than the reverse. If a particular risk factor contributes to the development of a mood disorder, then high-risk children would be expected to have the vulnerability as compared to children of parents who have not had a mood disorder. Once such a vulnerability is identified, the next step is to show that it predicts the onset of depression in high-risk offspring.

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Intervention trials also can be used to study vulnerability. If individuals who receive an intervention aimed at changing an identified vulnerability factor show lower rates of depression as compared to individuals in the untreated group, then this would be consistent with the view that this vulnerability variable might be a risk factor for depression. Of course, treatment designs can only show a reduction in symptoms and cannot confirm that the identified variable contributed to the original onset of the symptoms. Prevention studies can be used to demonstrate that changing a hypothesized vulnerability reduces the risk of the onset of a depressive episode or an increase in depressive symptoms (Horowitz & Garber, 2006). Combining these different research strategies could provide even more informative tests of vulnerability. Studies could compare currently depressed, remitted, high-risk, and never depressed children with regard to different multivariate models and then follow them over time to examine the temporal precedence of the vulnerability factors to depressive outcomes. Additionally, designs that randomly assign currently depressed, remitted, high-risk, and never depressed individuals to various kinds of interventions can address questions of onset and change over time. Finally, laboratory analogue studies that experimentally manipulate specific processes also can be used to test causal mechanisms.

Theory and Research on Vulnerability to Depression in Children and Adolescents Several fundamental questions are relevant in addressing vulnerability to depression from a developmental perspective. First, are the processes underlying depression the same in children and adults? How and why might vulnerabilities change across time? How do vulnerabilities to mood disorders develop? Most theories of depression have focused on adults and typically have been extended downward to explain depression in children and adolescents. If depression is essentially the same construct at any age, then shouldn’t similar causal processes underlie the disorder across the lifespan? Rather than having different theories of child and adult depression, theories need to explain developmental variation in the characteristics of depression (e.g., prevalence, course). Conversely, if child and adult depression are not the same, then different theories may be needed (e.g., Cole, 1991). As with juvenile- and adult-onset types of diabetes, which share some commonalities but also have important differences in course, correlates, and treatment, child- and adult-onset types of depression may exist that have different causal processes. Many different theories of depression have been articulated. This chapter focuses on the factors with the most empirical support, including genes, neurobiology, temperament, negative cognitions, self-regulation, stressful life events, and interpersonal relationships as well as the interactions among these variables.

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Genes Family, twin, and adoption studies have yielded varying results regarding genetic contributions to individual differences in depression (Lau & Eley, 2008). Family studies of childhood depression indicate that the likelihood of a first-degree relative having MDD is 2.3 times higher among children with MDD as compared to those without it and 1.85 times higher than in children with other psychiatric disorders (Rice, Harold, & Thapar, 2002a). Parents of prepubertal depressed children also have high rates of criminality, abuse, antisocial disorder, and mania (Harrington et al., 1997; Wickramaratne, Warner, & Weissman, 2000), whereas first-degree relatives of depressed adolescents have an increased rate of mood disorders (Harrington et al., 1997; Wickramaratne et al., 2000; Williamson et al., 1995). Offspring of depressed parents are about four times more likely than normal controls and 1.7 times more likely than psychiatric controls to have MDD, have longer episodes, and tend to have earlier onsets and worse associated impairment (Klein, Lewinsohn, Rohde, Seeley, & Olino, 2005; Weissman et al., 1987). A high family loading for MDD also is linked with higher rates of recurrence, particularly from childhood-onset MDD, and an increased risk of anxiety disorders (Warner, Weissman, Mufson, & Wickramaratne, 1999; Weissman et al., 2005; Wickramaratne, Greenwald, & Weissman, 2000; Williamson, Birmaher, Axelson, Ryan, & Dahl, 2004). Family studies, however, provide only limited information about the relative contribution of genes and environment. Cross-generational transmission of depression could be due to psychosocial factors such as maladaptive parenting, marital dysfunction, and stress, which also are associated with parental depression (Goodman & Gotlib, 1999). Children exposed to severe environmental stressors or trauma early in development might be especially vulnerable to developing mood disorders (Nolen-Hoeksema, Girgus, & Seligman, 1992; Post, 1992; Rice, Harold, & Thapar, 2002b). Early-onset (i.e., < 20 years old) depression is associated with greater genetic risk (Gjone, Stevenson, Sundet, & Eilertsen, 1996; Weissman, Warner, Wickramaratne, & Prusoff, 1988; Weissman et al., 1987). Adolescent-onset depression has been reported to have a greater heritable component as compared to child-onset depression (Scourfield et al., 2003), although this may be due to the relatively low number of young children in twin samples or to the higher number of behavior-dependent life events during adolescence (Rice, Harold, & Thapar, 2003). It is unclear whether earlier-onset depression is due to greater genetic influence or factors within the shared environment of families with a depressed proband (Rutter, MacDonald, et al., 1990). Twin studies with children report heritability estimates of about 40–65% (Glowinski, Madden, Bucholz, Lynskey, & Heath, 2003; O’Connor, Neiderhiser, Reiss, Hetherington, & Plomin, 1998; Todd & Botteron, 2001); estimates differ, however, as a function of sex, age, and informant. Genetic effects have been found to be larger in girls than boys (Happonen et al., 2002; Scour-

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field et al., 2003), although some studies have not replicated this (Hewitt et al., 1997; van der Valk, van den Oord, Verhulst, & Boomsma, 2003), and still other studies have found no sex differences in the heritability of depression in children (Bartels et al., 2004; Gjone & Stevenson, 1997). In a study of pre- and postpubertal twins, Silberg and colleagues (1999) found evidence of genetic heritability only for postpubertal girls. In contrast, Eley and Stevenson (1999) reported that genetic effects decreased with age in females but increased with age in males. Genes also appear to play a larger role in the relation between negative life events and depression in adolescents, ages 12–17, than in children, ages 8–11 (Rice et al., 2003). Age-related changes in heritability estimates can result from different gene effects at different ages, from the same genes impacting the phenotypical expression of a trait at different ages, or from environmental influences that vary with development (Lau & Eley, 2008). Heritability estimates based on children’s self-report tend to be lower than those based on parents’ reports of children’s depressive symptoms (Eaves et al., 1997). Heritability estimates also vary as a function of symptom heterogeneity. Adult studies generally have found that environmental factors make a greater contribution to mild depressions and genes play a larger role in more severe depressions (Rutter, MacDonald, et al., 1990). In children, studies evaluating severity differences in genetic and environmental effects have reported mixed results (Eley, 1997; Rende, Plomin, Reiss, & Hetherington; 1993). In a sample of 9- to 18-year-olds, Rende et al. (1993) found smaller genetic effects and significant shared-environment effects in children with greater severity of depressive symptoms. In contrast, in a sample of 8- to 16-year-olds, Eley (1997) reported similar heritability estimates for different levels of severity but less influence of shared environmental factors in the more severely depressed groups. Adoption studies of childhood depression have tended to yield different results than twin studies. Whereas twin studies suggest a moderate role for genetic influences on individual differences in depression, adoption studies (e.g., Eley, Deater-Deckard, Fombonne, Fulker, & Plomin, 1998; van den Oord, Boomsma, & Verhulst, 1994) typically have reported small to negligible genetic effects. In general, twin studies report nonsignificant effects of shared environment, whereas adoption studies suggest a small but significant effect of shared environment. Both designs indicate moderate to large nonshared environmental influences. Evidence that genetic risk interacts with negative life events to predict depression is growing (Lotrich & Pollock, 2004). Caspi and colleagues (2003) showed that the relation between childhood maltreatment and adult depression is moderated by the serotonin transporter (5-HTTLPR) gene for individuals possessing one or two copies of the short allele(s) as compared to individuals homozygous for the long allele. Kaufman and colleagues (2004) reported that maltreated children with the s/s genotype had significantly higher depression scores than children with the same genotype who had not been maltreated. In

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another study, Kaufman and colleagues (2006) reported that an interaction among the s/s allele of the 5-HTTLPR gene, the MET allele of the brainderived neurotropic factor (BDNF) val66met polymorphism, and child history of maltreatment predicted the highest depression scores. Finally, in a candidate gene study, Strauss et al. (2005) reported an association between six polymorphic markers within the BDNF locus and early-onset depression. In summary, estimates of heritability tend to be moderate, shared-environment effects tend to be small, and nonshared environmental effects emerge as the largest environmental influence on individual differences in childhood depression. Vulnerability to depression clearly has a genetic component, but the exact genetic mechanisms underlying depression still need to be identified. Genes likely influence risk for depression through endophenotypes such as temperament, cognitive style, stress reactivity, and/or hormone and neurotransmitter levels (Thapar & Rice, 2006), and these vulnerabilities then interact with the environment to produce depressive disorders. Moreover, multiple genetic loci likely contribute to the risk for depression (e.g., Holmans et al., 2007). Recent genetic research has focused on identifying specific candidate genes associated with systems involved in depression and on using genetic linkage studies to identify common genes in families at high risk for depression (Levinson, 2006).

Neurobiological Vulnerability Psychobiological studies of depression in children (e.g., Kaufman & Charney, 2003; Zalsman et al., 2006) have focused on dysregulation in neuroendocrine and neurochemical systems, biological rhythm abnormalities, and disturbances in sleep architecture. In addition, structural and functional brain differences in depressed and high-risk children increasingly have been investigated (e.g., Field, Fox, Pickens, & Nawrocki, 1995; Thomas et al., 2001). Although some similarities exist in the biological correlates of depression in adults and children, salient developmental differences also have been noted, which highlight the importance of studying how the maturation of biological systems affects the nature, timing, and expression of depression and its correlates across development (Kaufman, Martin, King, & Charney, 2001).

Psychoneuroendocrinology Depressed individuals show dysregulation of the human stress response in the limbic–hypothalamic–pituitary–adrenocortical (LHPA) system, including higher levels of basal cortisol, abnormal responses to the dexamethasone suppression test (DST), and abnormalities in corticotrophin-releasing factor (Thase, 2009). The LHPA axis is active from birth (Gunnar, 1989). Even during infancy, increases in cortisol levels are correlated with stress, although there is considerable variability in the magnitude of infants’ cortisol responses to stress. Some neuroendocrine changes in infants have been associated with

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depression-like symptoms such as prolonged crying, withdrawal, and apathy in response to stress, particularly separation (Trad, 1994). Psychobiological studies of depression in children and adolescents typically have attempted to replicate the results of studies with adults. Depressed and nondepressed children do not appear to differ, however, in basal cortisol secretion or post corticotropin-releasing hormone (CRH) levels of cortisol or adrenocorticotropic hormone (ACTH) (Birmaher et al., 1996; Feder et al., 2004; Kaufman et al., 2001). Some studies have shown elevated cortisol around sleep onset in suicidal or inpatient depressed adolescents (Dahl et al., 1991; Forbes, Williamson, et al., 2006). Other studies have found evening cortisol hypersecretion and morning dehydroepiandrosterone (DHEA) hyposecretion (Goodyer et al., 1996), which predicted subsequent major depressive episodes and suicidality a year later (Goodyer, Herbert, & Altham, 1998; Goodyer, Herbert, Tamplin, & Altham, 2000; Mathew et al., 2003). Another approach to studying neuroendocrine dysfunction has been to examine reactivity to a pharmacological or psychological challenge. In one study, adolescents who responded to a social challenge with heightened cortisol reactivity had higher levels of depressive symptoms 1 year later (Susman, Dorn, Inoff-Germain, Nottleman, & Chrousos, 1997). Similarly, daughters of depressed mothers have been found to have heightened cortisol reactivity to stress as compared to low-risk offspring (Gotlib, Joormann, Minor, & Cooney, 2006). Studies of the DST as an indicator of abnormalities in LHPA response have found some evidence of nonsuppression in children. Greater sensitivity has been reported in inpatient as compared to outpatient youth (61 vs. 29%) and in children as compared to adolescents (58 vs. 44%), although comparisons with psychiatric controls were stronger in adolescent samples (85%) than in child samples (60%; Dahl et al., 1992; Dahl & Ryan, 1996). Another neuroendocrine marker is a blunted growth hormone (GH) response to pharmacologic challenge. Regulation of GH may be a biological indicator of central noradrenergic and serotoninergic processes (Birmaher et al., 2000). GH is normally secreted by the pituitary gland, functions as a growth-promoting agent throughout the body, and is mostly secreted during sleep in children (Ryan & Dahl, 1993). Some studies report an increase in unstimulated GH secretion at night in depressed children (e.g., Kutcher et al., 1991), whereas others report blunted GH secretion throughout the day (e.g., Meyer et al., 1991). Compared to nondepressed controls, children with MDD have a blunted GH response to stimulation with insulin-induced hypoglycemia and growth hormone-releasing hormone (GHRH; e.g., Ryan et al., 1994), which continues even after remission (Dahl et al., 2000). Blunted GH response to GHRH also has been found in at-risk children with no personal history of depression but with high rates of affective illness in their families (Birmaher et al., 2000). Bonari and colleagues (2004) demonstrated that children of depressed mothers had increased stress hormone levels at baseline and in response to laboratory stressors. Thus, GH system dysregu-

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lation may be a trait vulnerability marker for depression (Dinan, 1998). Such at-risk children need to be followed to determine whether their blunted GH response predicts onset of depressive episodes.

Neurotransmitters Biological dysregulation has been found in the neurochemistry of depressed individuals. Serotonin, norepinephrine, and acetylcholine are especially implicated in the pathophysiology of mood disorders (Thase, 2009). Serotonergic system dysregulation, in particular, is consistent with molecular genetic research showing a polymorphism in the serotonin transporter gene as a marker of depression vulnerability (Eley et al., 2004). Never-depressed children with high familial loading for depression as well as currently depressed girls show a blunted cortisol response and an increased prolactin response after administration of L-5-hydroxytryptophan (L-5-HTP; Birmaher et al., 1997; Ryan et al., 1992; for a review, see Kaufman et al., 2001). Also paralleling results in adults, children with recurrent depression secrete significantly less prolactin than children with a single episode of depression, suggesting changes over time in neurobiological functioning. Depressed children who have been abused have a greater prolactin response after administration of L-5-HTP as compared to depressed nonabused children and nonabused nondepressed controls, thus highlighting the possible role of early childhood adversity on neurobiological functioning (Kaufman et al., 1998b). Treatment studies of the effectiveness of selective serotonin reuptake inhibitors (SSRIs) in reducing depressive symptoms in children also suggest serotoninergic system dysregulation (Emslie, Rush, Weinberg, Kowatch, et al., 1997b). Overall, children, adolescents, and adults exhibit serotoninergic system dysregulation, although the nature of the abnormalities varies depending on age, gender, and history of trauma. The effect of SSRIs on the developing brain is a particularly important issue for future research.

Functional and Anatomical Brain Differences Structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) studies of depressed adults have shown various anatomical and functional abnormalities in the brain, including reduced amygdala volume, hippocampal abnormalities, and reduced blood flow and metabolism in the prefrontal cortex (Davidson, Pizzagalli, & Nitschke, 2002). Studies using sMRI in depressed children have revealed a smaller left subgenual prefrontal cortext (PFC), lower frontal lobe volumes, and greater ventricular volumes as compared to nondepressed psychiatric controls (Botteron, Raichle, Drevets, Heath, & Todd, 2002; Nolan et al., 2002; Steingard et al., 2002). Smaller left subgenual PFC has been reported in depressed female adolescent twins, suggesting possible genetic transmission of structural abnormalities (Todd & Botteron,

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2001). Reduced amygdalar, but not hippocampal, volume has been found in depressed youth as compared to nondepressed controls; no significant association was found, however, between amygdalar volume reduction and severity, duration, or age of onset of depression (Rosso et al., 2005). Depressed youth also show reductions in white frontal matter volume (Steingard et al., 2002), reduced blood flow in the prefrontal cortex (Clerc, Noury, & Gittos, 1986), and decreased activity in the occipital region (Bonte et al., 2001). Ladouceur and colleagues (2005) suggested that depressed children process emotional information differently than do nondepressed controls, and recommended examining the neural mechanisms behind these processing differences. Brain-imaging research in children, particularly of the nucleus accumbens, amygdala, and medial and ventral PFC regions, is being used to examine the neural correlates of early-onset depression (Ernst, Pine, & Hardin, 2006). Studies of depressed children and adolescents (ages 8–16) using fMRI have found a blunted amygdalar response to fearful faces as compared to nondepressed controls and anxious youth (Thomas et al., 2001). Another study, however, found increased amygdalar activity during successful memory encoding of evocative faces in depressed youth as compared to nondepressed controls and anxious youth (Roberson-Nay et al., 2006). Depressive symptoms in adolescents also have been linked to increased activity in the ventromedial prefrontal cortex and anterior cingulate gyrus during the processing of fearful faces (Killgore & Yurgelun-Todd, 2006), and youth with a history of MDD show deficits in memory for fearful faces (Pine et al., 2004), indicating possible amygdala dysfunction. Additionally, never-depressed daughters of depressed mothers show deviant processing of facial emotions, such as selective attention to sad facial expressions (Joormann, Talbot, & Gotlib, 2007). Thus, disturbances in the processing and memory of emotional facial expressions may be one marker of vulnerability to depression. Studies of brain asymmetry have revealed relative hypoactivation of the left frontal region of the brain in infant (Dawson, Frey, Panagiotides, Osterling, & Hessl, 1997; Field et al., 1995) and young adolescent (Tomarken, Dichter, Garber, & Simien, 2004) offspring of depressed mothers as compared to the offspring of nondepressed mothers. Such asymmetry may represent another biological marker of vulnerability to depression. Davidson, Pizzagalli, Nitschke, and Putman (2002) proposed that decreased left frontal activation reflects an underactivation of the approach system and reduced positive emotionality. Neuroimaging studies of depressed adults indicate disruption in the structure and function of several reward-related areas that may contribute to the reduced positive affect found in many depressed patients (Drevets, 2001). Similarly, depressed youth (ages 9–17) show more disrupted neural responses to rewarding events than do nondepressed youth (Forbes, May, et al., 2006b); abnormalities occurred in both reward decision/anticipation and reward outcome phases of processing. Depressed children and adolescents also show atypical patterns of reduced right posterior brain activity. Evidence of right parietotemporal hypoactiva-

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tion, but not left frontal hypoactivation, in depressed female adolescents has been reported (Kentgen et al., 2000). Another study (Flynn & Rudolph, 2007) found that reduced posterior right hemisphere bias (PRHB) was associated with depressive symptoms in youth exposed to high levels of interpersonal stress. Less adaptive (e.g., involuntary, dysregulated) responses to stress partially mediated the link between reduced PRHB and depressive symptoms Such neuropsychological deficits presumably heighten stress reactivity by interfering with effective coping and emotion regulation (Flynn & Rudolph, 2007).

Sleep Architecture Abnormalities Depressed youth subjectively report sleep disturbances, but sleep electroencephalographic (EEG) results are less consistent in children than adults (Ryan & Dahl, 1993). Prolonged sleep latencies have been found across several studies of depressed children and adolescents (Birmaher & Heydl, 2001, Dahl et al., 1996). Results are less clear regarding reduced rapid eye movement (REM) latencies (especially in more severely depressed patients), increased REM density, and decreased sleep efficiency (Wolfson & Armitage, 2009), and some studies (e.g., Armitage et al., 2002; Bertocci et al., 2005) have failed to find differences between depressed and nondepressed children in EEG sleep patterns. Sleep polysomnography measures have been found to predict recurrence of depression in children, particularly in boys (Armitage et al., 2002; Emslie et al., 2001). The absence of consistent patterns of sleep abnormalities in depressed youth has been attributed to maturational changes in the nature and function of sleep across development (Kaufman et al., 2001). Sleep disturbances that characterize depression may not become evident until adolescence or young adulthood. In summary, there is evidence of neuroendocrine and neurochemical dysregulation in depressed children and adolescents. Basal cortisol levels do not consistently discriminate between depressed and normal children, whereas HPA axis responses to stress, seen in the DST, do appear to differ between depressed and nondepressed children. The strongest neuroendocrinological evidence is for dysregulation of the growth hormone system. Hyposecretion of GH in response to pharmacological challenge also has been found in high-risk children (Birmaher et al., 1999), suggesting a possible vulnerability marker. Neurochemical dysregulation has been implicated in childhood depression, and serotonergic system dysregulation has been demonstrated in highrisk children (Birmaher et al., 1997), again suggesting a vulnerability for depression. There also is evidence of functional and anatomical brain differences in depressed youth as compared to normal controls, and in offspring of depressed mothers. Sleep studies of depressed children and adolescents have not consistently found disturbances similar to those found in adults. Thus, the neurobiological literature in children and adolescents is more variable but not inconsistent with adult findings (Kaufman & Charney, 2003; Zalsman et al., 2006). Such differences underscore the importance of taking a developmental

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perspective when studying the neurobiology of psychopathology across the lifespan (Cicchetti & Posner, 2005). A greater understanding is needed of the maturational differences in brain structure and function as well as the role of hormonal changes associated with puberty and how they affect the onset, course, and expression of depression at different ages in males and females.

Temperament Temperament is a relatively stable and consistent behavioral, emotional, and/ or cognitive style (Rothbart & Bates, 1998; Shiner, 1998). Temperament is thought to have a genetic or biological basis (e.g., Gray, 1987), although social experience also can affect its development (Caspi, Henry, McGee, Moffitt, & Silva, 1995; Hartup & van Lieshout, 1995). Personality traits linked particularly with depression in children are negative and positive emotionality and constraint and attentional control (Compas, Connor-Smith, & Jaser, 2004). Negative emotionality (NE) is the propensity to experience negative emotions (e.g., anxiety, fear, sadness, anger) and is characterized by sensitivity to negative stimuli, increased wariness, vigilance, physiological arousal, and emotional distress. Positive emotionality (PE), or surgency, is characterized by sensitivity to reward cues, approach, energy, involvement, sociability, and adventurousness. NE and PE, respectively, are conceptually related to negative (NA) and positive affectivity (PA; Clark & Watson, 1991), neuroticism and extraversion (Eysenck & Eysenck, 1985), the behavioral inhibition and activation systems (Gray, 1991), difficult temperament and activity/approach (Thomas & Chess, 1977), and harm avoidance and novelty seeking (Cloninger, 1987). Although different terms are used, these constructs share much conceptual and empirical overlap (Klein, Durbin, Shankman, & Santiago, 2002). According to the tripartite model of anxiety and depression (Clark & Watson, 1991), high levels of NA are associated with both depression and anxiety, whereas low levels of PA are uniquely related to depression, particularly anhedonia. Evidence consistent with this model has been found in children (e.g., Lonigan, Phillips, & Hooe, 2003; Phillips, Lonigan, Driscoll, & Hooe, 2002). Low PA is a significant risk factor for depression, and low extraversion and low emotional stability predict internalizing problems in both clinical and nonclinical samples of children (van Leeuwen, Mervielde, De Clercq, & De Fruyt, 2007). Vulnerability models suggest that certain temperaments may be a risk for depression. (e.g., Caspi, Moffitt, Newman, & Silva, 1996; Goodwin, Fergusson, & Horwood, 2004; Nigg, 2006). Caspi and colleagues (1996) reported that children rated as inhibited, socially reticent, and easily upset at age 3 had elevated rates of depressive disorders at age 21. Moreover, the association between temperament and mood disorders differs by gender. Gjerde (1995) reported that shy and withdrawn behavior in girls and higher levels of undercontrolled behaviors in boys at ages 3 and 4 predicted chronic depression during adulthood.

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Parenting behaviors, such as rejection or inconsistent discipline, also moderate the relation between temperament and depression. The link between fearful temperament and depressive symptoms in girls was stronger for those whose parents were rejecting, whereas parental warmth buffered the relation of child frustration to internalizing problems (Oldehinkel, Veenstra, Ormel, de Winter, & Verhulst, 2006). Similarly, in a study of families undergoing divorce, low PE predicted higher levels of depressive symptoms among children experiencing high levels of parental rejection, and impulsivity and depression were significantly associated in children receiving inconsistent parental discipline (Lengua, Wolchik, Sandler, & West, 2000). High levels of PE in children, however, tended to buffer against the adverse effects of parental rejection on depression. The relation between child temperament and parenting likely is bidirectional such that parental rejection and inconsistent discipline each predict increases in children’s NE (fear and irritability), child irritability predicts increases in inconsistent discipline by parents, higher effortful control predicts decreases in parental rejection (Lengua, 2006; Lengua & Kovacs, 2005), and high withdrawal predicts more negative interactions with parents and peers (Finch & Graziano, 2001). Lengua (2006) concluded that child temperament and parenting predict changes in each other and in subsequent adjustment. Temperament itself can be a diathesis that moderates the effect of other risk factors (e.g., stress) on depression. Under conditions of stress, negative affectivity has been shown to lead to greater emotional arousal, more difficulty modulating emotional reactivity to stress, and a greater likelihood of using avoidance coping (Compas et al., 2004). For example, among girls with a more reactive temperament, peer rejection significantly predicted an increasing trajectory of depressed mood (Brendgen, Wanner, Morin, & Vitaro, 2005). Temperament also may contribute to the development of the cognitive vulnerability to depression (e.g., Garber, 2007; Hankin & Abramson, 2001). For example, higher levels of withdrawal measured at ages 1 and 4 were found to interact with recent life events to predict more negative cognitions in children at age 11 (Mezulis, Hyde, & Abramson, 2006). Similarly, low PE in early childhood predicted depressive cognitions in middle childhood (Hayden, Klein, & Durbin, 2005). In summary, temperament may be both a direct vulnerability and a diathesis that interacts with other variables (e.g., stress), to predict depression in youth. No single model can capture the complexity of the interplay between temperament and depression. Moreover, the various dimensions of temperament (e.g., frustration, fear, shyness) likely are linked differently to depression, depending on age, sex, and family characteristics (Ormel et al., 2005).

Negative Cognitions Cognitive stress models of depression (Abramson et al., 1989; Beck, 1967) assert that negative beliefs and maladaptive information processing serve as

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vulnerabilities that become active in the context of stress. Beck (1967) suggested that negative cognitive schemas (i.e., beliefs about loss, failure, worthlessness) and dysfunctional attitudes cause biased interpretations of stress and negative views of the self, world, and future, and result in depression. Hopelessness theory (Abramson et al., 1989) asserts that maladaptive beliefs interact with stressful events to produce negative inferences about the causes, consequences, and self-implications of the events, which then result in hopelessness and depression. Consistent with these models, depressed children and adolescents have been found to report more hopelessness, cognitive distortions, cognitive errors, negative views of self and future, and more negative attributional styles compared to nondepressed children (Abela & Hankin, 2008). Concurrent covariation between negative cognitions and depression, however, does not indicate whether such cognitions are a concomitant, cause, and/or consequence of depression. Prospective studies have shown that in nondepressed youth and in those at risk for depression these cognitive vulnerabilities predict depressive symptoms when exposed to stressful life events (e.g., Garber, Keiley, & Martin, 2002; Lewinsohn, Joiner, & Rohde, 2001; Rudolph, Kurlakowsky, & Conley, 2001; Schwartz, Kaslow, Seeley, & Lewinsohn, 2000). Reviews of over 30 prospective studies (Abela & Hankin, 2008; Lakdawalla, Hankin, & Mermelstein, 2007) have found a small effect size for the relation between the cognitive vulnerability–stress interaction and elevations in depression among children (ages 8–12; partial correlation = .15) and a somewhat larger effect (partial correlation = .22) among adolescents (ages 13–19). Thus, the cognition by stress interaction may be a stronger predictor of depression in adolescents than in children. This finding is consistent with the developmental hypothesis that depressive cognitions do not emerge and consolidate until late childhood/early adolescence, when abstract reasoning and formal operational thought are developing, and that the relation of the cognitive vulnerability to depression becomes stronger with increasing age (e.g., Abela, 2001; Cole et al., 2008; Turner & Cole, 1994; Weisz, SouthamGerow, & McCarty, 2001). In addition, some of the mixed findings from studies testing cognitive diathesis–stress models of depression to children likely are due to the use of measures that do not sufficiently address the cognitive developmental level of the children being studied. For example, questionnaires that require metacognitive skills, self-reflection, or perspective taking may not be appropriate for young children. Evidence also is inconsistent regarding the stability of negative cognitions, particularly after recovery from a depressive episode (Just et al., 2001). Whereas some studies have not found differences in the cognitive styles of remitted versus nondepressed children (Asarnow & Bates, 1988; McCauley, Mitchell, Burke, & Moss, 1988), other studies have reported a stable cognitive vulnerability in children when priming techniques were used (e.g., Scher, Ingram, & Segal, 2005; Timbremont & Braet, 2004). Priming negative affect

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may be needed to access latent maladaptive cognitive structures that serve as vulnerabilities to depression. The relation of cognitive vulnerability to depression also may depend on the specific type of cognitions. Abela (2001) suggested that inferential styles about consequences and the self may develop earlier than causal attributions, which require more abstract, higher-order thinking. In addition, Abela and colleagues (Abela & Payne, 2003; Abela & Sarin, 2002) proposed the weakest link hypothesis, which asserts that individuals are as vulnerable to depression as their most negative inferential style makes them. Indeed, Abela and Payne (2003) showed that children’s most depressive inferential style—about causes, consequences, or the self—interacts with negative events to predict increases in depressive symptoms. The weakest link approach may explain some of the inconsistencies in past research on cognitive stress models of depression in children. In another study testing the weakest link hypothesis, Morris, Ciesla, and Garber (2008) found evidence consistent with the cognitive diathesis– stress model for boys, whereas for girls the pattern of relations reflected a dual vulnerability model. That is, all girls showed high levels of depressive symptoms except for those with more positive cognitive styles and low stress levels. Cognitive vulnerability also has been found in the offspring of depressed parents. Children of depressed mothers report significantly lower self-worth and a more negative attributional style than do children of nondepressed mothers (e.g., Garber & Robinson, 1997; Gotlib et al., 2006; Murray, Woolgar, Cooper, & Hipwell, 2001). Garber and Robinson (1997) showed that the offspring of mothers with more chronic depression reported significantly more negative cognitions than did the children of mothers with no history of psychiatric disorders, even when children’s current level of depressive symptoms was controlled. Information-processing biases following a negative mood induction procedure have been found in never-depressed adolescent daughters of depressed mothers (Gotlib et al., 2006). Thus, children who have not yet experienced depression themselves, but who are at risk, show negative cognitions and processing biases that likely serve as vulnerabilities to depression. Possible mechanisms through which negative cognitions develop include the modeling of parents’ negative beliefs, dysfunctional parent–child relationships, exposure to stressful life events, family adversity, feedback from others, and temperament (Garber & Martin, 2002; Hankin, 2005; Rudolph et al., 2001). Emotional abuse, in particular, has been linked with depressive cognitive styles (Gibb, 2002). Several studies (Bruce et al., 2006; Garber & Flynn, 2001; Gibb & Alloy, 2006; Mezulis et al., 2006) have found that negative life events, as well as interpersonal difficulties, predict depressive cognitions. For example, in a study of children followed from infancy through fifth grade, peer harassment predicted negative cognitions, and a significant interaction between mothers’ negative attributions and negative life events predicted children’s negative cognitions (Mezulis et al., 2006).

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The experience of depression itself also may lead to depressive cognitions (Haines, Metalsky, Cardamone, & Joiner, 1999; Nolen-Hoeksema et al., 1992; Pomerantz & Rudolph, 2001). Nolen-Hoeksema and colleagues (1992) suggested that depression during childhood contributes to the development of a pessimistic explanatory style that persists even after the depression has remitted. Others have shown bidirectional relations between depressive symptoms and perceived competence (Cole, Martin, Peeke, Seroczynski, & Hoffman, 1998; Hoffman, Cole, Martin, Tram, & Seroczynski, 2000) and between negative mood and self-critical cognitions in youth (Kelvin, Goodyer, Teasdale, & Brechin, 1999; Rudolph, Hammen, & Burge, 1997; Park, Goodyer, & Teasdale, 2005; Stewart et al., 2004). Identification of the specific types of cognitive vulnerabilities that contribute to the onset, maintenance, and recurrence of depressive episodes in children and adolescents requires further study. Studies also are needed that map out the origins of cognitive vulnerability and the developmental trajectories of various negative cognitions and their relation to depression over the life course.

Self-Regulation and Coping Self-regulation has been defined as the way individuals stimulate, modify, or manage their thoughts, affects, and behaviors through biological, cognitive, social, and/or behavioral means (Calkins, 1994; Thomson, 1994). During infancy, caregivers provide initial regulation until babies learn self-soothing behaviors (e.g., sucking, head turning). As children develop, they acquire gross motor skills and cognitive abilities that improve self-regulation by facilitating their ability to monitor and exert control over their behaviors (Cole, Martin, & Dennis, 2004). Coping is a subcategory of self-regulation activated in times of stress (Compas, Connor-Smith, Saltzman, Thomsen, & Wadsworth, 2001; Eisenberg, Fabes, & Guthrie, 1997). Eisenberg and colleagues (1997) suggested three coping categories: emotion regulation, problem-focused coping, and behavioral regulation. Emotion regulation refers to direct attempts to manage affect; problem-focused coping involves attempts to regulate the situation; and behavioral regulation is the management of behaviors resulting from emotional arousal. Eisenberg and colleagues (Eisenberg, Fabes, Guthrie, & Reiser, 2000; Eisenberg et al., 2004) showed that (1) behavior regulation predicted socially appropriate behavior, (2) this relation was moderated by negative emotionality, and (3) two dimensions of self-regulation—effortful control and impulsivity—predicted resiliency 2 years later in children, ages 4–8. Moreover, low attention regulation and low impulsivity were associated with internalizing symptoms, whereas high impulsivity, low attention focusing, and low inhibitory control were associated with externalizing symptoms (Eisenberg et al., 2001). Similarly, Lengua and Sandler (1996) found that attention regulation and inhibitory control were related to higher social

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competence. Children with stronger self-regulation skills may be better able to delay maladaptive responses and to use active coping strategies in response to stressful situations. Compas and colleagues (2001) suggested a broader definition of coping that incorporates attempts to intentionally regulate emotions, cognitions, behaviors, physiology, and the environment. They emphasized that coping involves volitional responses to stress, whereas involuntary or automatic reactions reflect individual differences in temperament. Compas and colleagues also distinguished between engagement coping (i.e., problem solving, cognitive restructuring, positive reappraisal, distraction) and disengagement coping (i.e., avoidance, self-blame, emotional discharge, rumination). Whereas engagement coping is associated with lower internalizing and externalizing symptoms, disengagement coping is associated with higher symptom levels (Compas et al., 2001). For example, in a sample of children, ages 9–12, active coping predicted fewer depressive symptoms, whereas avoidant coping predicted higher levels of depressive symptoms (Lengua, Sandler, West, Wolchik, & Curran, 1999). Another study (Flynn & Rudolph, 2007) found that maladaptive responses to stress (i.e., fewer effortful responses and more involuntary, dysregulated responses) accounted for the contribution of reduced posterior right hemisphere bias (PRHB) to depressive symptoms in adolescents, suggesting that PRHB heightens stress reactivity by interfering with effective coping and emotion regulation. Studies of self-regulation and depression in children have found differences as a function of gender and context. Garber, Braafladt, and Weiss (1995) showed that in interpersonal situations, depressed girls reported using problem solving less than nondepressed girls. In achievement situations, depressed girls and boys reported using fewer support-seeking, cognitive, and affectchange strategies than did nondepressed children. Children at risk for depression show greater difficulty inhibiting negative affect, selectively attend to sad facial expressions, use active distraction less, and are less able to generate positive affect in the face of distraction as compared to low-risk youth (Forbes, Fox, Cohn, Galles, & Kovacs, 2006a; Goodyer, 2002; Joormann, Talbot, & Gotlib, 2007; Ladoucer et al., 2005; Silk, Shaw, Forbes, Lane, & Kovacs, 2006; Silk, Shaw, Skuban, Oland, & Kovacs, 2006). For example, in a sample of 4- to 7-year-old children, Silk, Shaw, Forbes, and colleagues (2006) showed that positive reward anticipation in the context of a negative-emotion inducing task was associated with lower internalizing problems, and this link was stronger for children of depressed as compared to nondepressed mothers. Thus, in children at risk for depression, positive self-regulatory behavior may be protective against the negative effects of stress, whereas problems in self-regulation may be a marker of vulnerability. In summary, deficiencies in self-regulatory skills have been associated with a range of adverse outcomes in children. Many studies have been crosssectional, however, limiting our conclusions about the direction of the coping–

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depression relation. Just as coping can reduce emotional distress, emotional distress can affect coping. Children who are less depressed may be better at generating solutions to problems and maintaining a positive outlook when faced with stress. Therefore, prospective studies are needed to characterize the direction of the relation between self-regulation and depression and to identify deficits in self-regulation that are specific to different outcomes.

Stressful Life Events and Trauma Stress has a prominent role in most theories of depression. Depressive symptoms and disorders in children and adolescents are significantly associated with both major and minor undesirable life events, particularly cumulative or chronic stressors (Grant et al., 2006). Depressed youth experience significantly more negative life events as compared to nondepressed children (e.g., Goodyer et al., 2000; Williamson et al., 1998). The link between stress and depression emerges even before birth. Animal studies show that both antenatal and prepartum stress impact the developing physiology of the fetus and later physiological and behavioral outcomes in the offspring of stressed animals (e.g., Kay, Tarcic, Poltyrev, & Weinstock, 1998; Schneider, Moore, & Kraemer, 2003). In human infants, stress in the fetal environment can affect birth weight and the development of the LHPA axis, both of which may be vulnerabilities for depression (Austin, Leader, & Reilly, 2005; Gale & Martyn, 2004). Infants born to prenatally depressed mothers tend to show excessive crying and irritability (Lundy et al., 1999). Stress-induced hormonal changes in mothers such as elevated levels of corticotropins releasing hormone (CRH) and cortisol may lead to increased LHPA fetal activity, difficulty in habituating to stimuli, temperamental difficulties, reduced birth weight, and slowed growth (Kapoor, Dunn, Kostaki, Andrews, & Matthews, 2006; Weinstock, 2005), resulting in increased sensitivity to stress and greater vulnerability to depression as they mature. Infants exposed to high levels of maternal stress (e.g., maternal depression) show elevated cortisol levels when they encounter current maternal stress as preschoolers (Essex, Klein, & Kalin, 2002). Moreover, the relation between depression in preschoolers and a family history of mood disorders has been found to be mediated by stress (Luby, Belden, & Spitznagel, 2006). A particularly salient stressor during infancy is separation from caregivers between the ages of 6 and 8 months (Moreau, 1996). Infants respond to separation with negative changes in sleep, heart rate, activity, temperature, monoamine systems, and immune and endocrine function (Kalin & Carnes, 1984). Hospitalism, which involves long and frequent hospital stays, and earlier age of entering the hospital have been associated with depressive symptoms in infants (Moreau, 1996). Childhood-onset depression has been linked with more perinatal insults, parental criminal convictions, parental psychopathology, caregiver changes, and peer problems (Jaffee et al., 2002). Stressful life events increase from

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childhood through adolescence (Rudolph & Hammen, 1999), with girls reporting greater increases than boys (Garber, 2007; Ge, Lorenz, Conger, Elder, & Simons, 1994), paralleling increases in rates of depression during adolescence (Hankin et al., 1998). This increasing trajectory of stressful life events predicts growth in depressive symptoms for girls but not for boys (Ge et al., 1994), particularly stressful interpersonal events (Hankin, Mermelstein, & Roesch, 2007; Rudolph & Hammen, 1999; Shih, Eberhart, Hammer, & Brennan, 2006). Stress also predicts the onset of depressive symptoms in previously asymptomatic adolescents (Aseltine, Gore, & Colton, 1994) and the onset of clinically significant depressive episodes, controlling for prior symptom levels in children and adolescents (Garber, Martin, & Keiley, 2002; Goodyer et al., 2000; McFarlane, Bellissimo, Norman, & Lange, 1994; Monroe, Rohde, Seeley, & Lewinsohn, 1999). Only three of these studies (Aseltine et al., 1994; Garber et al., 2002; Monroe et al., 1999), however, controlled for lifetime history of MDD to rule out the possibility that earlier depressive disorder contributed to the onset of subsequent episodes. Although no specific stressful event invariably leads to depression, events occurring during childhood and adolescence such as loss, disappointment, separation, interpersonal conflict, relationship break-ups, and rejection (Goodyer et al., 2000; Monroe et al., 1999; Rueter, Scaramella, Wallace, & Conger, 1999), as well as parents’ marital conflict and divorce, family violence, maltreatment, and economic disadvantage, are particularly likely to predict depression in youth (Eley & Stevenson, 2000; Gilman, Kawachi, Fitzmaurice, & Buka, 2003; Hankin, 2005; Reinherz, Paradis, Giaconia, Stashwick, & Fitzmaurice, 2003; Uhrlass & Gibb, 2007). Physical and/or sexual abuse, especially when the trauma is chronic and severe, are among the most damaging stressors linked with the onset and recurrence of depression (Harkness & Lumley, 2008; Trad, 1994), as well as with comorbid PTSD, substance abuse, conduct disorder, and suicide (Barbe, Bridge, Birmaher, Kolko, & Brent, 2004; Brown, Cohen, Johnson, & Smailes, 1999; Fergusson & Lynskey, 1996; Fergusson, Lynskey, & Horwood, 1996; Molnar, Berkman, & Buka, 2001). Maltreatment leads to avoidant or resistant attachments and withdrawal behaviors in infants, self-esteem deficits in children, higher levels of depression in adolescents, and increased risk of subsequent abuse (e.g., Lamb, Gaensbauer, Malkin, & Schultz, 1985; Silverman, Reinherz, & Giaconia, 1996). The relation between depression and maltreatment is particularly strong in the presence of high familial loading of depression and polymorphisms in SLCGA4 and BNDF genes (Caspi et al., 2003; Kaufman et al., 2004; Kaufman et al., 2006; Kaufman et al., 1998a). Moreover, experience of such early adversity may make children more vulnerable or sensitized to depression when exposed to new stressors later in development (Hammen, Henry, & Daley, 2000; Harkness, Bruce, & Lumley, 2006; Monroe & Harkness, 2005), although this may vary by age and gender (Rudolph & Flynn, 2007). Cumulative and multiple stressors are particular risks for depression in

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youth. For example, children living in poverty are likely to witness violence and to be the victims of abuse themselves (Buka, Stichick, Birdthistle, & Earls, 2001). Possible mediators between economic disadvantage and depression include lack of access to adequate health care and educational opportunities, fewer social resources, and greater exposure to violence. Another life event often associated with multiple other stressors is the loss of a loved one. Approximately 30% of children who experience a death become clinically depressed during the year following the loss. Additional stressors moderate and mediate this relation. For example, a personal or family history of depression increases risk for a mood disorder after a death (Brent et al., 1993; Weller, Weller, Fristad, & Bowes, 1991). Moreover, loss may be followed by other stressors such as a decline in economic resources, moving, school transitions, and distress in other family members (Rutter, 1966; Tremblay & Israel, 1998). Interpersonal stressors (e.g., rejection) are especially likely to predict depression in individuals who are more socially dependent. According to the specific vulnerability hypothesis (e.g., Beck, 1983), individuals who derive their self-esteem predominantly from interpersonal relationships are at increased risk for depression when they experience social stressors. Evidence consistent with this hypothesis has been found in children (e.g., Hammen & GoodmanBrown, 1990; Little & Garber, 2000, 2005). Little and Garber (2005) showed that youth for whom interpersonal relationships were especially important were more susceptible to depressive symptoms following the experience of dependent social stressors than were those for whom interpersonal issues were less salient. Social support also may affect the relation between stress and depression in youth. For example, among children with low as compared to high social support, the interaction between genes and childhood maltreatment significantly predicts higher levels of depressive symptoms (Kaufman, Yang, Douglas-Palumberi, Grasso, et al., 2004; Kaufman, Yang, Douglas-Palumberi, Houshyar, et al., 2004). Additionally, among youth living in highly disordered neighborhoods (i.e., exposure to gangs, harassment, drug dealing), supportive parenting (i.e., use of inductive reasoning) serves as a buffer against depressive symptoms (Natsuaki et al., 2007). The relation between stress and depression likely is bidirectional. According to the stress exposure model, stress precedes the onset of depression (Brown, 1993), whereas the stress generation model asserts that depressed individuals’ own behaviors create many of the stressors they encounter, which then further exacerbate their depressive symptoms (Hammen, 1991, 2006). Depressed youth (Hankin et al., 2007; Rudolph et al., 2000; Shih et al., 2006) as well as those with maladaptive interpersonal problem-solving styles (Davila, Hammen, Burge, Paley, & Daley, 1995) tend to generate more stress in their lives. Additionally, several studies (Carter, Garber, Ciesla, & Cole, 2006; Cole, Nolen-Hoeksema, Girgus, & Paul, 2006; Gibb & Alloy, 2006)

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have found a reciprocal relation between stress and depression, thus highlighting the “vicious cycle” between them. Thus, stress often is both a precipitant and consequence of depression. Not all individuals exposed to the same stressors become depressed, however. Rather, individual vulnerabilities such as genetic liability, neurobiological dysregulation, negative appraisals, and maladaptive responses to stress affect the likelihood of becoming depressed (Abela & Hankin, 2008; Caspi et al., 2003; Hankin & Abramson, 2001; Kaufman et al., 2006; Kaufman et al., 2004). Therefore, integrative diathesis–stress models that propose interactions between individual vulnerabilities and contextual factors likely best explain the onset of depression in youth.

Interpersonal Relationships Interpersonal perspectives on depression emphasize the importance of transactions between individuals and their social environment (Gotlib & Hammen, 1992; Hammen, 2006; Joiner, Coyne, & Blalock, 1999). The social context can be both a source of support and a source of stress. Depressed individuals are often the recipient as well as the elicitor of interpersonal difficulties. Depression in children and adolescents is associated with considerable family adversity, peer problems, and interpersonal rejection (Nolan, Flynn, & Garber, 2003; Rudolph, Flynn, & Abaied, 2008). At the same time, depressed youth may have distorted perceptions of their social world, engage in behaviors that elicit negative responses and conflict with others, and generate additional stressors in their relationships (e.g., Hankin et al., 2007; Rudolph et al., 2000).

Family Family adversity often is associated with depression in youth, particularly insecure parent–child attachment, parental depression, maltreatment, and dysfunctional parenting. The processes through which these factors lead to depression involve many of the neurobiological, cognitive, and self-regulatory skills described earlier. Attachment theory (Bowlby, 1980) asserts that children with consistently accessible and supportive caregivers develop cognitive representations, or working models, of the self and others as positive and trustworthy. Conversely, unresponsive or inconsistent caregivers produce insecure attachments and working models of abandonment, self-criticism, and dependency. Such insecure attachments increase children’s vulnerability to depression, particularly when exposed to new interpersonal stressors. Securely attached toddlers tend to be more cooperative, persistent, enthusiastic, and higher-functioning (Matas, Arend, & Sroufe, 1978) and show lower levels of depressive symptoms when exposed to stress (Abela et al., 2005). Insecurely attached youth

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have social-behavioral and emotion regulation deficits that can increase their vulnerability to depression (Rudolph et al., 2008). Maladaptive parenting behaviors also are associated with depression in youth. Currently depressed children describe their parents as controlling, rejecting, and unavailable (e.g., Stein et al., 2000) and perceive their families to be low in cohesion and high in conflict (e.g., Garrison, Jackson, Marsteller, McKeown, & Addy, 1990). Children’s ratings of parents’ psychologically controlling behavior predict children’s depressive symptoms over and above prior depression levels (Barber, 1996). Similarly, mothers of depressed children describe themselves as more rejecting, less communicative, and less affectionate than do mothers of nondepressed or psychiatric controls (e.g., Puig-Antich et al., 1985a), and maternal hostile child-rearing attitudes predict increases in children’s depression (Katainen, Raikkonen, Keskivaara, & KeltikangasJarvinen, 1999). Conversely, a positive parent–child relationship in terms of good communication, parental supervision, clear and consistent expectations, and shared positive activities has been linked with less depression in youth (Borowsky, Ireland, & Resnick, 2001; Fergusson & Lynsky, 1996; Resnick et al., 1997). Observational studies have shown that low parental warmth, high parental hostility, harsh discipline, and family conflict predict internalizing symptoms in youth (Ge, Best, Conger, & Simons, 1996; Sheeber, Hops, Alpert, Davis, & Andrews, 1997), and escalating parent–child conflict predicts increases in adolescents’ internalizing symptoms (Rueter et al., 1999). Mothers of depressed children also have been observed to be less rewarding and more dominant and controlling than mothers of nondepressed children (Cole & Rehm, 1986; Sheeber, Hops, & Davis, 2001). Levels of maternal criticism of children are higher in mothers of depressed children as compared to mothers of children with ADHD or healthy controls (Asarnow, Tompson, Woo, & Cantwell, 2001). Convergence among children’s, parents’, and observers’ ratings indicates that depression in children and adolescents is characterized by considerable family dysfunction (Park, Garber, Ciesla, & Ellis, 2008). Family dysfunction and conflict may be particularly relevant to depression during adolescence (Sheeber, Hops, Alpert, Davis, & Andrews, 1997; Sheeber & Sorensen, 1998). Adolescents’ responses to the normative challenges of this transition period may be influenced and exacerbated by vulnerabilities developed as a result of earlier family adversity (Rudolph et al., 2006). When the parent–child relationship is already turbulent, negotiating normal autonomy demands can place even greater burden on the family and may lead to depression in vulnerable adolescents. Thus, the family environment may be an important contributor to the increasing rates of depression during adolescence. Although the parent–child relationship shows some improvement with remission of children’s depression, interpersonal problems persist, particularly with siblings (Puig-Antich et al., 1985b). Continued social adversities such as poor peer relationships, high family stress, and inadequate parental discipline

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increase the likelihood of children’s depressive symptoms continuing (e.g., McCauley et al., 1993), and negative attitudes of family members expressed toward depressed children predict relapse (Asarnow, Goldstein, Tompson, & Guthrie, 1993). The relation between parenting and children’s depression may be best characterized as transactional. That is, children’s and parents’ behaviors influence each other reciprocally over time (Elgar, Curtis, McGrath, Waschbusch, & Stewart, 2003; Sagrestano, Paikoff, Holmbeck, & Fendrich, 2003). For example, in a 4-year, cross-lagged panel study of children, ages 0–14, Elgar and colleagues (2003) showed that, whereas maternal depressive symptoms preceded child aggression and hyperactivity, child emotional problems preceded maternal depressive symptoms. Parental depression, which consistently has been linked with depression and other psychopathology in offspring, also is characterized by dysfunctional parenting (e.g., Garber, 2005; Hammen, Shih, & Brennan, 2004). Such difficulties likely are one important and possibly malleable mechanism of the intergenerational transmission of depression (Goodman & Gotlib, 1999). Hammen and colleagues (Hammen & Brennan, 2001; Hammen et al., 2004) showed that depressed mothers had high levels of interpersonal stress that contributed to poor parenting as well as interpersonal deficits, stress, and depression in their children. Bifulco and colleagues (2002) reported that the relation between maternal and child depression was mediated by childreported neglect and abuse (see also Hammen et al., 2004; Leinonen, Solantaus, & Punamaki, 2003). Other studies (Jones, Forehand, & Neary, 2001; Kim, Capaldi, & Stoolmiller, 2003), however, have not found that parenting attitudes or behaviors significantly explain the relation between parent and child depression. Less positive parenting has been found to partially mediate the link between parental depression and children’s externalizing symptoms (Foster, Garber, & Durlak, 2008; Frye & Garber, 2005). One possible mediator of the relation between dysfunctional parenting behaviors and offspring depression is children’s negative cognitions (Abela, Skitch, Adams, & Hankin, 2006; Garber, Robinson, & Valentiner, 1997; Gibb & Alloy, 2006; Gibb et al., 2001; McGinn, Cukor, & Sanderson, 2005). For example, negative cognitive style has been found to partially mediate the relation between parental abuse and neglect during childhood and subsequent depressive symptoms (McGinn et al., 2005), and between emotional maltreatment in childhood and depressive episodes during young adulthood (Gibb et al., 2001).

Peers Depressed children and adolescents have both real and perceived peer problems. In actuality, depressed youth have social skills deficits (e.g., Altmann & Gotlib, 1988), poorer quality friendships (Goodyer, Wright, & Altham, 1990; Prinstein, Borelli, Cheah, Simons, & Aikins, 2005), higher teacher-rated peer

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rejection (Rudolph, Hammen, & Burge, 1994), and more negative peer ratings (Peterson, Mullins, & Ridley-Johnson, 1985). Rejection by peers predicts higher levels of self-reported depressive symptoms among antisocial, although not among nonantisocial, youth (French, Conrad, & Turner, 1995). Depressed youth also view themselves as less socially competent (Rudolph et al., 1997) and perceive themselves to be less socially accepted than their nondepressed peers (Cole, Martin, et al., 1998). Moreover, perceived rejection, even more than actual peer rejection, predicts increases in depressive symptoms in children (e.g., Kistner, Balthazor, Risi, & Burton, 1999; Panak & Garber, 1992). Regardless of how well a child is actually liked by peers, those with high levels of rejection sensitivity (Rizzo, Daley, & Gunderson, 2006; Sandstrom, Cillessen, & Eisenhower, 2003) or social-evaluative concerns (Rudolph & Conley, 2005) are especially prone to experiencing depression and other internalizing problems. Thus, consistent with cognitive models of mood disorders, depressed children often perceive themselves and their peer relationships more negatively than the actual situation warrants. Depressed children not only think that they are less accepted by their peers and have a lower-quality relationship with their best friends, but they also have a more negative view of their social acceptance and friendship quality as compared to their peers (Brendgen, Vitaro, Turgeon, & Poulin, 2002). Indeed, depressed children and adolescents have both actual social skills deficits and overly negative views of their social status (Rudolph & Clark, 2001). Perceiving rejection from others may lead to acting withdrawn or hostile (Renouf & Harter, 1990), which then may elicit actual negative reactions from peers, thereby reinforcing the depressed child’s negative perceptions. Thus, a self-perpetuating cycle of cognitive distortions, negative social interactions, and depression may develop. Studies of the transactional hypothesis that depressive symptoms generate interpersonal rejection indicate that depressed adolescents elicit negative responses from unfamiliar peers (Connolly, Geller, Marton, & Kutcher, 1992) and create stress in their relationships (Daley et al., 1997; Krackow & Rudolph, 2008). Additionally, adolescent depression is associated with persistent relationship difficulties such as negative feedback seeking (Borelli & Prinstein, 2006) and greater stress in their romantic relationships (Hankin et al., 2007). Longitudinal studies have found that interpersonal difficulties such as excessive reassurance seeking (Prinstein et al., 2005), negative feedback seeking (Borelli & Prinstein, 2006), rejection (Nolan et al., 2003), and romantic breakups (Monroe et al., 1999) significantly predict increases in depressive symptoms. Moreover, social-behavioral deficits interact with some of these relationship disturbances to predict depression in youth (Gazelle & Rudolph, 2004; Rizzo et al., 2006). For example, girls with high levels of interpersonal sensitivity were particularly vulnerable to depression when experiencing problems in their romantic relationships (Rizzo et al., 2006). The types of friends with whom children associate also may contribute to the development and course of depression. Interestingly, both bulliers and the

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bullied have high rates of depression (Ivarsson, Broberg, Arvidsson, & Gillberg, 2005; Kaltiala-Heino, Rimpela, Rantanen, & Rimpela, 2000). Children who reported being friends with highly aggressive children had high levels of depressive symptoms across 2 years, controlling for initial depression levels (Mrug, Hoza, & Bukowski, 2004). Moreover, spending time with delinquent peers predicted high levels of self-reported depressive symptoms assessed monthly (Connell & Dishion, 2006). Depressed children might select delinquent peers as a way of “fitting in” and obtaining a sense of belonging not otherwise provided by their broader social networks, although deviant peer groups typically do not give much positive feedback, which then may further exacerbate their depression (Brendgen, Vitaro, & Bukowksi, 2000). Overall, interpersonal relationships play a key role in the development and maintenance of depression in children and adolescents. Family adversity and peer problems are stressors that can precipitate a depressive episode in vulnerable individuals. Social interactions also can play a role in the development of individual diatheses such as negative cognitive schema about self and others. Additionally, depressed children often are themselves more interpersonally difficult, which can exacerbate problems in their social network. Thus, the relation between depression and interpersonal dysfunction is reciprocal and bidirectional. For example, a prospective study of children ages 11–15 showed that deficits in perceived parental support, but not peer support, predicted increases in depressive symptoms, and depressive symptoms, in turn, predicted decreases in peer, but not parental, support (Stice, Ragan, & Randall, 2004). Depressed children’s reactions to their environments can exacerbate and perpetuate negative social exchanges, which further the interpersonal vicious cycle, thereby resulting in more rejection and depression. Thus, a transactional model of mutual influence probably best characterizes the association between depressed individuals and their social context.

Conclusions and Future Directions Depression is a heterogeneous condition in which no single factor is either necessary or sufficient. Rather, multiple risk factors and processes interact to contribute to its development. The etiology of depressive disorders involves the integration of various vulnerabilities into a complex multifactorial model spanning all levels of analysis of individual and contextual factors (Cicchetti & Dawson, 2002). The different vulnerability factors described here (e.g., genes, neurobiological dysregulation, reactive temperament, negative cognitions, poor self-regulation, stress, interpersonal problems) not only underlie depression but also are part of the causal chain underlying other disorders. The particular amalgamation of these vulnerabilities with one another or with additional variables, as well as their dose and timing, is what uniquely results in one condition or another. Rather than simply examining the independent contribution of individual risk factors, we need to develop and test multivari-

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ate models, explore how various vulnerability and contextual factors synergistically combine to explain the onset of depression, and address questions of specificity. If a particular risk factor (e.g., stress) predicts several disorders (e.g., anxiety and depression), this does not mean that the risk factor cannot be part of a more complex and specific causal model (Garber & Hollon, 1991). Several integrated models of depression have been formulated that include additive and interactive effects of multiple risk factors (e.g., Akiskal & McKinney, 1975; Kendler, Gardner, & Prescott, 2002). Akiskal and McKinney (1975) suggested that most distal causal processes (e.g., stress, low rates of positive reinforcement) go through a common final neuroanatomical pathway to depression. Diathesis–stress models highlight that person characteristics, such as genetic or cognitive vulnerability, interact with environmental stressors to produce depression (Abramson et al., 1989; Beck, 1967; Caspi et al., 2003; Kendler et al., 1995; Monroe & Simons, 1991). Interpersonal cognitive approaches (e.g., Gotlib & Hammen, 1992; Rudolph et al., 2008) suggest that cognitions about important social relationships may be a risk for depression when negative interpersonal events occur. Negative cognitive schemas about the self and others may be the result of earlier insecure attachment and interpersonal difficulties. Conversely, Ingram et al. (1998) posited that cognitive processes are the common final pathway through which all social and nonsocial information is processed and linked to depression. A broad, reciprocal, and dynamic biopsychosocial model of depression that incorporates the various etiological processes discussed here needs to be tested further. Figure 8.1 presents a conceptual framework showing that depression occurs in individuals with preexisting vulnerabilities, or diatheses, who are exposed to stress (Garber, 2007). Individual biological and psychological predispositions affect how individuals respond to various contextual factors, particularly stressful life events and interpersonal difficulties. The relations among these variables are reciprocal and dynamic. Individual vulnerabilities and contextual factors directly, indirectly (i.e., through mediation), and interactively (i.e., through moderation) affect depression. The diatheses are more distal and relatively stable (although some are potentially malleable) and influence how individuals’ respond to specific stressors. According to this perspective, some individuals are born with certain biological propensities, such as stress reactivity or an irritable temperament, that make them more vulnerable to the effects of negative life events and less able to respond effectively (e.g., solicit help from others). As children grow, they learn, in part through interactions with others, about their ability to cope effectively with stressors and whether others can be counted on for support. Children also learn through social encounters whether they are worthy of others’ love and support. Exposure to stressful life events can activate negative affective structures that connect with developing schemas about the self and others (Ingram et al., 1998). A cycle begins in which children develop some symptoms of depression (e.g., irritability, low self-esteem, anhedonia), which

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FIGURE 8.1.  Biopsychosocial model of depression.

then can lead to their being exposed to further stressors, such as interpersonal rejection and academic failure. Experience with chronic or severe stressors can produce neurobiological changes that further maintain or exacerbate the depressive symptoms. Thus, in this mediated moderation model (Baron & Kenny, 1986), individual diatheses moderate the relation between stress and depression and contribute to the manner in which the child responds to negative events; such specific responses to stress mediate the effect of the individual diatheses on subsequent depression. Individuals with particular biological and/or psychological “depressogenic” vulnerabilities who encounter stressful events and respond ineffectively (e.g., involuntary disengagement), so that the stressor is not adequately managed, will then develop depression. For example, individuals with a neurotic personality tend to respond to stress with maladaptive strategies such as emotional expression, escape avoidance, self-blame, confrontation, and poor problem solving (Lee-Baggley, Preece, & DeLongis, 2004; Newth & DeLongis, 2004; O’Brien & DeLongis, 1996), which then exacerbate the stressful situation with which they are trying to cope. Such escalating stressful circumstances can alter their biochemistry, self-schema, and information processing, leading to further maladaptive behaviors, thereby generating more negative events, particularly within the social domain (Coyne, 1976; Hammen, 2002), and so the cycle continues. This scarring (Lewinsohn, Allen, Seeley, & Gotlib, 1999) or kindling (Post, 1992) results in dynamic changes in these biopsychosocial systems over time. The exact mechanisms that explain how this complex interweaving of these multiple levels of vulnerability actually operates and interacts to produce

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the syndrome of depression are not well understood. That is, the precise combination of genes and the neural pathways that produce endophenotypes (e.g., temperament, negative cognitions) that then interact with specific contextual factors (e.g., exposure to in utero and early, severe, and/or chronic stress) to elicit the specific symptoms of depressive disorders have yet to be discovered. Further research is needed to identify specific genetic risk markers, to elucidate the pathophysiology from the genetic polymorphisms to neuroendocrine and neurochemical dysregulation, to describe how these biological processes then affect individuals’ appraisals and behavior in response to environmental events, and to determine how these processes affect the onset and course of the specific symptoms of depressive disorder. Research also needs to investigate the dynamic relations among the various individual vulnerabilities with one another and with the larger context. How do genes affect the neurobiological dysregulation that underlies depression? How are temperament, negative cognitive styles, and self-regulation strategies linked with one another and with genetic and biological vulnerabilities? How does early exposure to adversity impact an individual’s biological, cognitive, and self-regulatory pathways to depression? What mechanisms explain the cross-generational transmission of depression? How do contextual factors feed back to individuals’ biological and cognitive vulnerabilities? Why and how do individuals generate stress in their lives? The identification of the risk factors and processes that underlie vulnerability to depressive disorders can guide the formulation of appropriate interventions for treating and preventing depression as well as the determination of who is most likely to benefit from which intervention(s). Several important developmental questions remain regarding vulnerability to depression. Theories of depression need to account for differences in the phenomenology of depression in children, adolescents, and adults and changes in the rates of depression from childhood to adolescence, particularly in girls. Are the processes that underlie childhood-onset depressions different from those that explain the first onset of depression during adolescence or adulthood? Are vulnerabilities different for first versus recurrent episodes of depression? How do we account for the recurrences of depression across the lifespan? Do depressive vulnerabilities change with development, and, if so, how? When and how do depressive vulnerabilities develop and unfold? Finally, are the various vulnerabilities to depression described here permanent characteristics of individuals, and by what internal and external mechanisms are they turned on and off. What biopsychosocial processes set off latent vulnerabilities, and, conversely, how is spontaneous remission of depressive symptoms explained? Do vulnerable individuals no longer have the risk factor(s), or do they develop new skills for compensating for them? If the latter, can we learn from these naturalistic processes to develop more effective interventions?

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Acknowledgments Judy Garber was supported in part by grants (Nos. R01 MH57822 and R01 MH64735) and an Independent Research Scientist Development Award (No. K02 MH66249) from the National Institute of Mental Health, and by a grant from the William T. Grant Foundation (No. 173096).

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Chapter 9

Vulnerability to Depression in Adulthood Constance L. Hammen, Steven L. Bistricky, and Rick E. Ingram

This chapter highlights research on adult depression, presenting definitions and features of depression in adults, assessment methods, historical trends in vulnerability research, and current models and findings. It should be noted at the outset, however, that vulnerability is assumed to arise in childhood in most cases of depression. Thus, the major distinction between this chapter and the chapter on vulnerability to depression in childhood and adolescence (Garber, Chapter 8, this volume) is the age of the research populations studied. It may be assumed that the vulnerability factors are the same, although the child and adult literatures differ in emphasis and methods. The current chapter will focus on research conducted with adults—of whom many actually may have experienced their first depressive experiences as children or adolescents.

Definitions and Characteristics of Depression Most research on vulnerability to adult depression has focused on conditions that are marked by four features that we consider essential to a working definition: a constellation of symptoms defining a depressive syndrome rather than single symptom such as mood; a sustained period of symptoms over days, weeks, or months; some degree of impaired functioning; and a nonbipolar course. The specific methods of defining depression, such as self-reports on questionnaires or systematic interviews, as well as different samples surveyed such as patients or community members, may yield important differences that have implications for our understanding of vulnerability.

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Many investigators have held that the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000) definition of “major depressive disorder” is the gold standard for inclusion in research samples. According to the DSM-IV-TR, diagnosable syndromes of depression include affective, behavioral, somatic, and cognitive symptoms. Affective symptoms may include depressed mood or sadness, and feelings of loss of pleasure in typically enjoyable activities; irritability and anger may also be apparent. Behavioral symptoms include decreased activity such as withdrawal from typical pursuits and social interactions, and may include changes in movement such as slowed talking and reduced gestures, slumped posture, and sad facial expressions. The DSM-IV-TR criteria require a 2-week minimum and five of nine symptoms, at least one of which is depressed mood or loss of pleasure, plus clinically significant distress or impairment in important roles. Although there is much to be said for use of standardized criteria for defining research samples, several limitations must be acknowledged. One is that depression is highly heterogeneous in its presentation and course, and the uniformity myth that major depression is a single entity may obscure differences among as-yet unknown etiological subtypes. Although beyond the scope of this chapter, it is noted that various clinical profiles have been proposed as distinctive subtypes: atypical, melancholic, anxious, hopeless, psychotic, and early-onset recurrent depression, for example. It has been suggested also that research on particular symptoms, such as psychomotor change, anhedonia, or sleep disturbances, among others, might provide useful insights into etiological issues. Another related difficulty is that the diagnostic criteria are themselves somewhat arbitrary, having varied in diagnostic manuals over the past few decades as to the requirements of symptoms, duration, and impairment. Furthermore, meeting diagnostic criteria, or not, carries the implication that someone is either depressed or not depressed, whereas recent studies strongly imply that the course of major depression is markedly dynamic, changing between major depressive disorder and subsyndromal levels, suggesting a single underlying process with a highly varying continuum of severity (Judd et al., 1998). Judd and colleagues (1998) studied the weekly symptom course over a period of up to 12 years in a population seeking treatment for major depression. They found that patients overall were entirely symptom-free an average of only 41% of weeks of follow-up, and even those with first-episode depression were symptom-free only about half of the time. Most individuals reported highly fluctuating courses over time, in and out of periods varying in symptom severity—typically below diagnostic threshold but nonetheless associated with debilitation in functioning. The presence of subsyndromal symptoms in the absence of categorical diagnosis indicates a significant challenge to etiological vulnerability models because symptoms may exert influence on measures of vulnerability that obscure the direction of effects. Furthermore, categorical approaches to depression diagnosis (and etiological and treatment models) draw an arbitrary

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boundary because research indicates that substantial psychosocial impairment may accompany “subsyndromal” forms of depression (e.g., Judd et al., 2000). Subclinical depressive symptoms predict the onsets of major depression (e.g., Fogel, Eaton, & Ford, 2006) as well as other forms of psychological disorders (Zonderman, Herbst, Schmidt, Costa, & McCrae, 1993). Thus, it appears that a full understanding of the vulnerability to depressive experiences should include samples and definitions not constrained by DSM categories but perhaps supplemented by studies of samples selected by course features, including subsyndromal symptoms (e.g., Flett, Vredenberg, & Krames, 1997) and symptom profiles (e.g., Clark, Cook, & Snow, 1998) or even individual symptoms. Recently Klein (2008) called for modifications to the diagnostic system for depression that base classification on two dimensions, severity (mild, defined by subclinical, minor, or dysthymic depression vs. moderate/severe, defined by major depressive disorder) and chronicity (see below).

The Comorbidity Issue An additional diagnostic issue that affects the conduct and interpretation of vulnerability research in depression concerns the high rates of co-occurrence with other disorders. It is now well established that major depression relatively infrequently occurs alone. In both the original U.S. National Comorbidity Survey (NCS) and the recent NCS Replication, of all the community residents who met the criteria for lifetime and/or 12-month major depression, approximately 75% had at least one other diagnosis, with only a minority having “pure” cases of depression (Kessler, Chiu, Demler, & Walters, 2005; Kessler et al., 2003). For patients with a diagnosis of current major depression, only 40–45% had depression in isolation, with 60–65% having at least one comorbid Axis I diagnosis and with similar rates consistently found across different countries (e.g., Zimmerman, Chelminski, & McDermut, 2002). The most common comorbid Axis I diagnoses are anxiety and substance use disorders, but comorbidity is also frequent for impulse control disorders and eating disorders. For example, Hasin, Goodwin, Stinson, and Grant (2005) in the National Epidemiologic Survey on Alcoholism and Related Disorders found that lifetime major depression was associated with 40% rates of alcohol use disorder and with 41% anxiety disorder (and even higher rates were reported in the National Comorbidity Survey). The Hasin et al. (2005) study is also the largest community survey of Axis II disorders, and the investigators reported that major depression was associated with 31% rates of any personality disorder. Clinically ascertained samples may show even higher rates of Axis II comorbidity; Shea, Widiger, and Klein (1992) reported rates ranging from 23 to 87% across the studies they reviewed. Comorbidity raises various conceptual and methodological issues, not the least of which is whether studies of vulnerability to depression are really about “depression” or about comorbid conditions that are all too infrequently reported in articles. High rates of comorbidity may result in part from meth-



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odological artifacts, such as overlapping symptoms and changes in diagnostic systems, that increase the number of diagnoses and limit exclusion criteria (Kessler & Wang, 2008). Comorbid depression also may be a consequence of other disorders. Kessler and Wang (2008) report that only about 12% of cases of major depression temporally precede another disorder, suggesting that depression commonly may be a consequence of other disorders and their sequelae—although temporal patterns differ by disorder, with anxiety disorder especially likely to precede depression. It is also likely that some comorbid patterns result from shared etiological factors. Generalized anxiety disorder (GAD), for example, appears highly likely to predict eventual major depressive disorder, suggesting a shared etiological origin for a severe form of major depressive disorder that is comorbid with GAD (see Moffitt et al., 2007). A central issue that affects the future of vulnerability research in depression, therefore, is what we mean by “depression” and how we disentangle its unique attributes from those contributed merely by severity of symptoms or by coexisting psychopathology. Moreover, conceptualizing depression as a disease entity—or as an empirically defined construct—will likely lead in different directions.

Course of Depression Studies of vulnerability to depression need to be designed and interpreted in light of the features of the course of depression. Beyond symptom patterns and severity, two features of the course of depression have particular implications for research on vulnerability, age of onset and recurrence.

Age of First Onset Limited but growing evidence points to somewhat different etiological implications of depression that first appears in childhood, in adolescence, or in adulthood—particularly older adulthood. Typical research samples, whether a college student sample, an epidemiological sample, a twin registry, or a clinical trial, will commonly include individuals who vary considerably in age of first onset of depression, but without evaluation of whether the different onset ages have different outcomes and correlates of depression. There is ample evidence that in general an earlier age of onset of depression is associated with a worse course of depression, with greater chances of recurrence, chronicity, and impairment in role functioning (e.g., Hollon et al., 2006). Whether it reflects a more severe form of the disorder with specific etiological mechanisms or whether onset in childhood and adolescence interferes with the accomplishment of important developmental achievements that impair coping, adaptation to life transitions, and effective social problem solving, one’s age at first onset of depression is a variable that may introduce considerable heterogeneity into research on vulnerability to depression. Some have speculated that childhood, adolescent, adult, and older adult onsets may reflect different etiologi-

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cal or vulnerability processes—although further study is needed. Thus, at the very least, studies need to report age of first onset, and refinements in vulnerability models and processes should be conditional on differences in age of first onset. Late-life first onset depression may often reflect the effects of vascular changes in the brain or other older-age dementing disorders such as Alzheimer’s disease or Parkinson’s (e.g., Blazer, 2003; Blazer & Hybels, 2008), or result from biological changes associated with certain diseases, such as stroke. For instance, Van den Berg and colleagues (2001) found that late-onset depressed Dutch elders had higher vascular risk factors than elderly depressed with earlier onset. The latter had depressions that were best predicted by stressful life events (e.g., loss of spouse, medical problems), familial history of depression, and neuroticism. Depression symptoms in older adults may in fact sometimes mark the early warning signs of dementia (Blazer, 2003). Depression in older adults, both first and recurrent onsets, is an expanding topic of research, and readers are referred to a review chapter by Blazer and Hybels (2008) and a book, Late-Life Depression, edited by Roose and Sackheim (2004), among many excellent resources.

Chronicity and Recurrence of Depression More than 80% of people with major depression experience at least one recurrence, and the median number of major depressive episodes is four (see review in Judd, 1997). As noted earlier, Judd et al. (1998) found that depression symptomatology is frequent and persistent even in the absence of major depression episodes. Furthermore, there is evidence that the risk for recurrence progressively increases with each episode of major depression and decreases as the period of recovery becomes longer. Solomon et al. (2000) reported that among depressed patients followed over a 10-year period the probability of recurrence increased 16% with each successive episode; they also found that episodes come closer together over time. In a 23-year community follow-up study, major depression was unremitting in 15% of cases and recurrent in 35% (Eaton et al., 2008). Two implications of an intermittent course of depression are important. First, it means that most studies of depression are about recurrences rather than first onsets, particularly with adult samples, given the relative infrequency of new first cases as compared to recurrent cases of depression (Kessler, 1997). Vulnerability factors and processes may be different for predicting first versus later episodes (e.g., Daley, Hammen, & Rao, 2000), and increasingly models of depression must attempt to capture the dynamic, progressive processes (e.g., Post, 1992). Studies that do not identify, and ideally test for, differences in course features may obscure important information. Second, as reviewed by Klein (2008; see also Mondimore et al., 2006), there are important vulnerability/etiological, course/comorbidity, and treatment outcome differences between those who have relatively chronic courses of depression as



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compared with those with nonchronic depression. Klein notes that chronic major depressive disorder as compared with nonchronic major depressive disorder is generally associated with earlier onset, more family loading, neuroticism, suicidality, anxiety comorbidity, and poorer response to pharmacotherapy and psychotherapy. Klein (2008) argues that the current DSM system of diagnostic specifiers is complicated and not particularly valid for capturing continuing symptoms and incomplete remission of major depressive disorder, and he urges using a dimensional approach to chronicity (as well as severity, as noted earlier).

Epidemiology and Demographics of Depression Epidemiological surveys indicate that major depressive disorder is common. The 12-month prevalence is 5.3%, according to the National Epidemiologic Survey of Alcoholism and Related Conditions, the largest such study in the United States (Hasin et al., 2005), and 6.6% in the National Comorbidity Survey Replication (Kessler et al., 2003), with lifetime prevalences of 13.2 and 16.2%, respectively, in the two studies. Two of the key demographic correlates of major depression have substantial implications for vulnerability research: gender and socioeconomic disadvantage. Any model of depression must account for the significantly higher rates of diagnosis of depression in women as compared to men, running about 2:1 in the United States, with nearly universally higher rates throughout the world (Hasin et al., 2005; Kessler et al., 2003). Although no segment of the population is immune to depressive disorders, generally speaking, lower income, lower education, and social status variables likely associated with economic disadvantage such as unemployment and being divorced or widowed are also typically associated with higher rates of depression (Hasin et al., 2005; Kessler et al., 2003). Thus, conditions of social context also appear to play an important role in depression, as discussed more fully later.

Theory and Research on Vulnerability Biological Vulnerability Historically, the study of depression reveals a long-standing belief that, among the various forms of depression, some are biologically caused while others are psychogenic in origin. In the modern research milieu, however, no clear support has arisen for a distinction between types of depression based on biological or nonbiological etiology, although there are many in biological psychiatry—and the general community—that appear to view all clinically significant depressions as biologically based disease processes. Supported in part by the knowledge that certain medical illnesses and medications cause depressive symptoms, the somatic symptoms of the depression syndrome itself, and the apparent effectiveness of antidepressant medications, many are

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convinced that the origin of depression is fundamentally biological, a “disease of the brain” (e.g., Judd, 1997). On the other hand, we argue that the evidence for biological factors in depression better supports a vulnerability model—for some forms of depression—in which certain factors constitute diatheses requiring additional, largely psychosocial stress, factors in the classic diathesis-stress model. However, given that research is mostly based on crosssectional correlational designs, many observed differences between depressed and comparison groups may be consequences of depression or markers of other processes not yet clarified. Having noted these qualifications, it is also important to suggest that several areas of biological research are extremely intriguing and promise to promote further understanding of human behavior generally and are not limited just to depressive syndromes.

Genetic Vulnerability to Depression It has been known for some time now that depression runs in families. Gershon (1990) reviewed 10 studies of families of adult unipolar depressed probands and found rates of depression in first-degree relatives ranging between 7 and 30% across the studies, all considerably higher than in the general population. A later meta-analysis of five family depression studies conducted by Sullivan, Neale, and Kendler (2000) indicated that depressed individuals were nearly three times more likely than nondepressed controls to have a first-degree relative with a history of depression. In fact, having a depressed parent is one of the strongest predictors of depression in youth (Beardslee, Versage, & Gladstone, 1998). Family studies are poorly suited to sort out genetic and environmental factors, but alternative genetic strategies that are less confounded with environmental factors are also suggestive of genetic risk. For instance, twin studies using biometric model-testing analyses have proven to be informative. Reviews of studies that have drawn from large twin registries report consistent higher monozygotic (MZ) concordance than dizygotic (DZ) concordance in twin pairs (Levinson, 2006; Sullivan et al., 2000). Further, these reviews propose that the genetic liability accounts for 35–50% of the risk for major depressive episode among twin pairs, with the remaining variance attributable to individual-specific environmental factors such as stressful events. Interestingly, despite the consistently reported gender disparity in depression incidence, twin studies have typically reported similar heritability rates for males and females (e.g., Agrawal, Jacobson, Gardner, Prescott, & Kendler, 2004; McGuffin, Katz, Watkins, & Rutherford, 1996). However, Kendler, Gatz, Gardner, and Pedersen’s (2006) findings, derived from the massive Swedish Twin Registry, suggest that the heritability of depression liability may be significantly higher in women than men, an idea also supported by a smaller twin study (e.g., Bierut et al., 1999). Thus, while it is possible that females and males may not share all of the same genetic liability for depression, twin stud-



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ies suggest that common genetic factors play at least a moderate role in family patterns of major depression. Regarding the issue of whether particular subtypes or clinical courses of depression mark a particularly heritable form, the data are mixed. Sullivan and colleagues’ (2000) meta-analysis indicates that increased heritability is reliably and strongly associated with recurrent depressions, with episodes characterized by greater duration, symptom severity, and life impairment (e.g., McGuffin, Katz, & Watkins, 1996). Related to this, Kendler, Thornton, and Gardner (2001) found that female twin pairs who were at high genetic risk for depression showed an elevated but unchanging association between stressful life events and depressive onsets, unlike low genetic risk individuals who fit the “kindling” pattern, where each new episode tends to be less influenced by external stressors. Given the aforementioned heterogeneity of depression, linkage and association (i.e., candidate gene) studies have begun by targeting for study the recurrent early-onset depression phenotype, which represents high genetic risk. Genome-wide linkage scans have been conducted, and several studies have reported possible genetic linkage at particular chromosomal locations with depression susceptibility (e.g., Holmans et al., 2007; McGuffin et al. 2005). Recent candidate gene research has focused significant attention on hypothesized associations between a regional variant in the serotonin transporter gene (5-HTTLPR) and stress reactivity, possibly mediated by amygdala activity (Munafò, Brown, & Hariri, 2008). Caspi et al. (2003) first reported a gene-by-environment (G x E) interaction in which carriers of short alleles were significantly more likely than carriers of two long alleles to develop adult depression if they experienced significant childhood or adult stressors. Subsequent research has generally supported that 5-HTTLPR G x E interactions may be linked to increased depression incidence. However, as Uher and McGuffin (2008) and Zammit and Owen (2006) note in their recent reviews, this literature also includes null findings in two large studies and inconsistent and sometimes contradictory findings based on participant sex or the study’s use of episodic or chronic stress assessment. Additional vulnerability research is examining G x E interactions and multiple gene interactions, targeting genes that affect functioning of the hypothalamic–pituitary–adrenal (HPA) axis or dopaminergic, serotonergic, or noradrenergic systems. Although interesting results are being reported (e.g., Bradley et al., 2008), clear and consistent patterns in findings have yet to emerge. Because recent advances allow for the rapid genotyping of multitudes of individuals, research exploring candidate genes in specific phenotypes of depression will likely produce a surge of new findings in the years to come. However, current best evidence suggests that depression risk is mediated by various permutations of genes that may be expressed in conjunction with environmental stressors.

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Psychoneuroendocrinology of Depression Considerable evidence implicates dysregulation of the human stress response of the HPA axis in depressive disorders. Numerous studies have found elevated levels of cortisol, a hormone resulting in various forms of physical arousal and activation, in acutely depressed people as compared to nondepressed ones. Similarly elevated cortisol levels have been reported in recovered formerly depressed individuals, suggesting a possible mechanism influencing this group’s greater risk for future episodes (Bhagwagar, Hafizi, & Cowen, 2003). In addition to hypersecretion of cortisol, abnormal regulation of cortisol has been implicated in depression susceptibility and has been linked to impaired function or expression of glucocorticoid receptors thought to attenuate HPA axis activity following a stressor (Pariante & Lightman, 2008). Specifically, when the HPA axis is “challenged” by administration of a synthetic cortisol called dexamethasone and corticotropin-releasing hormone (i.e., a dex/CRH test), many depressed and depression-vulnerable individuals fail to engage healthy suppression of cortisol, resulting in higher cortisol levels than those of healthy never-depressed persons. HPA axis challenge tests held initial promise as an assessment tool for diagnosis or risk detection of a particular biological form of depression. However, it became apparent that abnormal HPA challenge reactions do not occur in all cases of depression and may only occur during the depressive syndrome for some. Nor is HPA dysregulation specific to depressive disorders; these reactions also occur in schizophrenia and posttraumatic stress disorder. Whether challenge-related nonsuppression predicts future depressive status has been addressed in various studies. Findings tend to show that when formerly depressed persons continue to show abnormal reactions to challenge even after remission, they are more likely to relapse in the weeks or months to follow (e.g., Rossier, Bertschy, & Bondolfi, 2007). These patterns may suggest that depressed persons with abnormal cortisol mechanisms are “sicker” and thus less responsive to treatment—or that there may be a subset of patients whose underlying disorder stems from dysregulation of the HPA axis. Interestingly, studies have revealed evidence of HPA axis dysregulation in people who have experienced insecure attachment, childhood maltreatment, or parental loss (e.g., Tyrka, Wier, Price, Ross, & Anderson, 2008), suggesting a link between neuroendocrine processes and early childhood adversity (possibly interacting with genetic predisposition). In a review of the effects of stress and HPA-related hormones on the brain, Plotsky, Owens, and Nemeroff (1998; see also Benes, 1994; Sapolsky, 1996) speculated that early stress experiences sensitize specific neural circuits, resulting in depressive reactions in later life in response to stressful life events. On the other hand, van Rossum and colleagues (2006) have reported evidence of a genetic link to a specific glucocorticoid receptor that is associated with greater susceptibility to depression.



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Consensus is lacking as to whether HPA axis dysregulation is a mechanism of risk for depression and how it arises. Some have suggested that HPA dysregulation might mediate the relationship between early adverse life experiences and elevated risk for depression (de Mello, de Mello, Carpenter, & Price, 2003) and that it might emerge from interactions between genetic susceptibility and the environment (Pariante & Lightman, 2008). Other investigators have regarded dysregulated HPA functioning as a trait vulnerability marker resulting from long-term affective disturbance (e.g., Ising, Lauer, Holsboer, & Modell, 2005). If HPA axis dysregulation proves to be a vulnerability factor, the development of effective early psychosocial or pharmacological interventions to ameliorate this risk may become important.

Neurotransmitters and Depression Vulnerability Historically, there has been considerable interest in the role of monoamine neurotransmitters (serotonin, norepinephrine, and dopamine) in mood disorders. These neurotransmitters are especially important in the limbic system of the brain, areas affecting drives and emotions, and pathways to other parts of the brain. The original catecholamine hypothesis of depression (Schildkraut, 1965) emphasizing relative deficits of the substances has proven to be far too simplistic, yielding to a greater focus on amine receptor systems (McNeal & Cimbolic, 1986) and models of dysregulation of neurotransmitters (e.g., Siever & Davis, 1985). Attention turned to serotonin (5-HT) models of depression (reviewed in Maes & Meltzer, 1995), suggesting that vulnerability to depression may arise from alterations in presynaptic 5-HT activity and postsynaptic serotonin receptor functioning. Experimental reduction of the availability of monoamines (through tryptophan depletion or alpha-methyl-para-tyrosine administration) has provided intriguing evidence of these neurotransmitters’ associations with depressive risk. Specifically, acute tryptophan depletion induces temporary but significant symptoms of depression in many remitted depressed patients (see Booij, Van der Does, & Riedel, 2003, for a review) but not in nondepressed persons. Similarly, reducing dopamine and norepinephrine availability via alphamethyl-para-tyrosine (AMPT) administration has been shown to induce relapse in individuals who have recovered from depression (Booij et al., 2003). Interestingly, several studies have reported that acute tryptophan depletion induces significantly greater depressive symptoms in females than males (e.g., Moreno, McGahuey, Freeman, & Delgado, 2006), but no such sex difference has been found following AMPT administration. In addition, recent findings have supported stress–neurotransmitter interactive conceptualizations. Initial exposure to a mild stressor may evoke a sensitizing monoamine response that increases monoamine release following subsequent stressors (Anisman, Hayley, & Merali, 2003). Given long-term exposure to stressful situations, monoamine demands might outpace synthesis, leading to depleted stores (Hayley, Poulter, Merali, & Anisman, 2005).

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Research has also examined various subtypes of neurotransmitter receptors (5-HT1A , 5-HT1B , 5-HT2A , 5-HT2C) and alternative neurotransmitters, such as glutamate and gamma aminobutyric acid (GABA; Oswald, Souery, & Mendlewicz, 2003), in relation to the onset and presentation of depression. In addition, evidence has been mounting that depression is associated with stress-related reductions in the expression of brain-derived neurotrophic factor (BDNF) and elevated serum levels of the neuropeptide substance P—although these phenomena may not be exclusively associated with depression (e.g., Geracioti et al., 2006). Reduced BDNF may lead to the hippocampal atrophy often found in depression (MacQueen et al., 2003), and a dysregulated substance P-neurokinin-1 receptor pathway might compromise normal functioning of brain regions involved in emotion regulation (Krishnan, 2002).

Functional and Structural Brain Changes in Depression A clinical neuroscience perspective suggests that depression vulnerability is a manifestation of focal brain dysfunction. In support of this model, neuroimaging studies have reported evidence of morphological and functional abnormalities in particular brain regions of depressed individuals. Depression has been associated with reduced prefrontal cortex, striatum, and hippocampal volumes (e.g., Fossati, Radtchenko, & Boyer, 2005) and with abnormal activity in brain regions such as the dorsomedial prefrontal cortex (PFC), the dorsolateral PFC, ventrolateral PFC, orbitofrontal cortex, anterior cingulate, amygdala, and hippocampus—areas that are important in emotional evaluation, reactivity, regulation, and memory (Drevets, 2000). A smaller set of studies has examined relevant brain function and depression vulnerability. In studies using mood inductions, remitted depressed individuals have shown reduced medial orbitofrontal cortical and anterior cingulate activity (Liotti, Mayberg, McGinnis, Brannon, & Jerabek, 2002) and elevated amygdala activity (Ramel et al., 2007) in response to emotional material. Even without mood induction, Hooley and colleagues (Hooley, Gruber, Scott, Hiller, & Yurgelun-Todd, 2005) found that remitted individuals showed lesser dorsolateral PFC activity than controls in response to maternal criticism, which they speculated could result in insufficient strategic responses to psychosocial threats. Additionally, studies in which tryptophan depletion induced a relapse in remitted individuals have reported related metabolism changes in medial frontal, orbitofrontal, cingulate, and thalamic areas of the brain (Neumeister et al., 2004). Although individual structural areas have been implicated in the etiology and maintenance of depression, theory and research have moved more toward connectivity analyses that attempt to understand the interactive functioning of structures linked to depressotypic emotion processing (Mayberg, 2007). Based on electroencephalographic (EEG) research on frontal brain activity, Davidson (1993, 1994) developed a model of emotional reactivity that described a tendency toward negative emotional states such as depression. His



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and other labs have observed that depressed patients, previously depressed but remitted patients, and even toddlers and adolescents of depressed mothers showed relative left frontal hypoactivation (e.g., Tomarken, Dichter, Garber, & Simien, 2004). Davidson (1993) proposed that this represents an underactivation of an approach system, reducing the person’s propensity to experience pleasure and develop positive engagement with the environment, which increases the likelihood of developing depressive symptoms. Although the predisposition toward left frontal hypoactivation and the concomitant experience of negative affect may be genetically transmitted, this tendency could also arise from the effects of early stressors on the functional development of affective brain structures (Jones, Field, Fox, Lunday, & Davalos, 1997). EEG research has also revealed resting state right posterior hypoactivation relative to left activation in depression. A model by Heller, Nitschke, and Miller (1998) proposed that reduced right posterior/parietal activity is associated with diminished arousal to emotionally salient information, which can result in the blunted affect and limited recognition of social and affective cues commonly seen in depression. With respect to depression risk, Bruder and colleagues (2005, 2007) found evidence of right parietal hypoactivation in never-depressed children and adult offspring from families with a history of depression. Additionally, subclinically depressed individuals have been found to exhibit attenuated task-evoked EEG activity in right relative to left parietal areas (Sumich, Kumari, Heasman, Gordon, & Brammer, 2006). Current EEGderived models of depression and risk will be refined as signal source localization techniques improve and as findings of resting state and task-related EEG activity become integrated conceptually and empirically. Further work will likely clarify whether particular neural abnormalities have significance for risk for depression or mostly describe depressive processes.

Cognitive Vulnerability Cognitive Models of Depression The idea that cognitive processes play a role in depression, and by extension that some of these processes play a role in vulnerability, originated with Beck’s (1967) cognitive model of depression. Beck’s model was the first to illuminate the characteristically negative thinking of depressed people and to assign causal significance to self-critical, pessimistic, helpless, and hopeless interpretations of the self and the world, and support for Beck’s model is considerable. For example, the descriptive aspects of depression noted by the model have been confirmed by numerous studies (Haaga, Dyck, & Ernst, 1991), research has shown that thinking styles in depression are dysfunctional (e.g., reviewed in Hammen, 1997; Ingram, Miranda, & Segal, 1998), and proposals regarding the emergence of negative schemas during stress have also received consistent support (Scher, Ingram, & Segal, 2005). Beck’s model focuses on cognitive structures, while other models empha-

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size specific kinds of cognitions. Attributional models fall into this category in that they focus on the self-related and potentially depression-inducing conclusions that individuals draw about the causes of events (Abramson, Metalsky, & Alloy, 1989). More specifically, Abramson et al. (1989) hypothesized that individuals whose cognitive styles lead them to make negative inferences about the causes, consequences, and self-implications of negative life events will face an increased likelihood that they will develop hopelessness and, in turn, the symptoms of depression, particularly a hopelessness type of depression (Abramson et al., 1999). Because of different conceptual traditions and theoretical emphases, attributional approaches have emerged as the second major cognitive approach to Beck’s schema-based models.

Vulnerability Hypotheses in Beck’s Models The essence of vulnerability in Beck’s model lies in a diathesis-stress conceptualization that argues that depression is the result of the interaction between negative self-schema diatheses and environmental stressors. This idea posits that, under ordinary conditions, people who are vulnerable to the onset of depression are indistinguishable from nonvulnerable people (Ingram et al., 1998; Scher et al., 2005). Beck’s model proposes, however, that when stressful life events are encountered by vulnerable people, these events activate the otherwise dormant negative self-schemas which then bring about the negatively biased self-referent information processing that initiates a downward spin into depression (Segal & Shaw, 1986). In describing this diathesis–stress process, Beck (1967) also hypothesizes its developmental origins: In childhood and adolescence, the depression-prone individual becomes sensitized to certain types of life situations. The traumatic situations initially responsible for embedding or reinforcing the negative attitudes that comprise the depressive constellation are the prototypes of the specific stresses that may later activate these constellations. When a person is subjected to situations reminiscent of the original traumatic experiences, he may then become depressed. (p. 278)

Hence, Beck’s theory locates the nexus of vulnerability, even for adults, in childhood experiences, and suggests that these experiences play a critical role in the formulation of depressogenic schemas, which are subsequently activated by life events that are both difficult and personally meaningful for the individual.

Vulnerability Hypotheses in the Hopelessness Model The hopelessness model of depression suggests a diathesis–stress relationship similar to Beck’s model, although important differences are apparent. The similarity resides in the idea that dysfunctional cognitive processes serve as



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a diathesis, processes that Alloy, Abramson, Safford, and Gibb (2006) have termed a “depressogenic” inferential style. This style consists of a tendency to attribute the causes of stressful events to stable (persistent) and global (generalized) personal attributes, and because of these attributions the negative events signify substantial personal deficiencies. The diathesis–stress difference lies in whether such a style needs to be activated; whereas such activation processes are now widely recognized as fundamental aspects of schema models, attribution theorists suggest that such a style is either always consciously available or possibly that questionnaires used to assess the style activate the process (e.g., Haeffel et al., 2005). Like Beck’s model, attributional models also locate the origins of cognitive vulnerability in early experiences. In the earliest statement of this process, Rose and Abramson (1992) suggested that, much like adults, children who experience negative events (such as maltreatment) attempt to ascertain the causes, consequences, and meaning of these events. Children, however, evince a tendency to make internal attributions for all events and thus blame themselves as causing the maltreatment. As the causes of such negative events are internalized, the child begins to incorporate a generalized tendency to see him- or herself as responsible for negative events. To the extent that negative events are repetitive and occur in the context of relationships with significant others and/or caretakers, these events undermine the need to maintain a positive self-image as well as optimism about future positive events. Moreover, the persistent occurrence of these events produces a pattern of attributions for negative events that, over time, becomes both stable and global and thus becomes traitlike.

Empirical Evidence of Cognitive Vulnerability To test cognitive vulnerability hypotheses, researchers must explore these ideas in samples whose members are vulnerable but not depressed (Ingram et al., 1998). Investigators must also consider the diathesis–stress context in which depressogenic cognitions, at least in Beck’s model, are predicted to arise. The model hypothesizes that stress is needed to activate otherwise dormant depressogenic schemas, a hypothesis that early studies attempting to test cognition in remitted depressed people failed to heed (e.g., Lewinsohn, Steinmetz, Larson, & Franklin, 1981). However, employing a diathesis–stress design, more recent studies have provided support for this hypothesized cognitive reactivity process. Although these studies vary in some respects, the general idea is to employ a laboratory analogue of stress, generally the use of a sad mood induction, and then examine the emergence of negative cognitions in nondepressed but vulnerable people. Such cognitions are otherwise difficult to detect in vulnerable individuals’ nondepressed state. As reviewed by Scher et al. (2005) and Ingram et al. (1998), a substantial body of research, across a variety of cognitive measures, has developed that suggests strong support for the diathesis–stress proposals of cognitive models. It is worth noting, as well,

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that evidence is accumulating to support the hypothesized developmental origins of cognitive vulnerability. Although it has been demonstrated that cognitive reactivity in vulnerable individuals is consistent with cognitive models, such demonstrations in and of themselves do not prove causality. That is, research needs to go beyond these demonstrations and show that reactivity is actually linked to causality. Two relatively recent studies, however, have indicated that this may be the case. In the first, Segal, Gemar, and Williams (1999) used a diathesis–stress test to examine depressed patients who were treated into remission and then examined relapse rates approximately 2½ years later. They found that reactivity (i.e., the endorsement of dysfunctional attitudes in response to negative mood), consistent with cognitive vulnerability proposals, predicted later depression, suggesting a causal link for the processes uncovered in diathesis– stress studies. In a second study, Segal et al. (2006) followed treated patients over an 18-month period and again found that cognitive reactivity was a significant predictor of relapse. The available research thus consistently suggests a cognitive diathesis in at least some individuals, and also supports the model’s validity in identifying vulnerability for the onset of depression. However, because these studies tested relapse rather than first onsets, conclusions are limited to subsequent episodes rather than initial onset of depression. This distinction is meaningful if different processes are responsible for subsequent episodes, such as the possibility that having a depressive episode may induce changes in the processes that give rise to cognitive functioning. Such is the proposal of the kindling hypothesis, which suggests that depressive episodes alter the underlying biology of the disorder, thus making the processes that trigger first episodes potentially different from those that trigger ensuing episodes (Post, 1992; see the later section on stressors). To date, there has been one test of depressive cognition as a vulnerability factor for first episodes. Using a behavioral high-risk paradigm, Abramson et al. (1999) identified, and followed longitudinally, university undergraduates who were not currently depressed but had high or low scores on a version of the Attribution Style Questionnaire and Beck’s Dysfunctional Attitude Scale (Weissman & Beck, 1978). Abramson et al. (1999) reported that the high-risk students had a 17% rate of first onset major depressive episode as compared to 1% for the low-risk students, and among those with prior depressive episodes the high-risk group also was more likely to have recurrences than was the lowrisk group. These results held true even when initial subsyndromal symptom levels of depression were controlled. The argument may be made (e.g., Hammen, 1992) that the cognitive models have overly focused on internal processes to the relative neglect of developmental and contextual factors that contribute to depression. While emergent negative cognitions may indeed be proximal triggers of depressive reactions, the Abramson et al. study in relative isolation contributes only a modest amount to our understanding of vulnerability processes. Accordingly,



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integrative models that include, but are not largely limited to, thinking styles may mark the contributions of this approach in the future. Indeed, such integrative efforts can be seen in some recent research examining the association between cognitive vulnerability and the serotonin transporter gene, the latter of which emerging data have suggested is associated with depression following life stress (e.g., Caspi et al., 2003). For example, Beevers, Bigg, McGeary, and Miller (2007) documented the effects of the serotonin transporter genotype (5-HTTLPR) on a factor that is typically thought of as a cognitive vulnerability mechanism, specifically, biased attention for emotional information. Similarly, Hayden et al. (2008) demonstrated a link between negative information processing and the 5-HTTLPR genotype in children who were induced into a negative mood. Given the evidence to date that appears to validate key aspects of cognitive models, it is not surprising that investigators are using this as a starting point in efforts to integrate cognitive approaches to vulnerability with other perspectives and hence to broaden understanding of vulnerability to depression.

Life Stress Approaches to Depression Vulnerability Depression generally occurs in response to negative life circumstances, and its mechanisms are increasingly viewed as maladaptive psychobiological responses to stress. Thus, etiological models are largely diathesis–stress perspectives, in which diatheses are risk factors or vulnerability processes such as biological, personality, or cognitive characteristics of the person, accounting for individual differences in how people respond to stressful challenges. Some of these topics are covered in other sections, such as neural circuits or cortisol and neuroendocrine differences in stress reactions, gene–environment interactions, and cognitive and interpersonal mediators and moderators of depressive reactions to stress. In this section we first review the empirical evidence linking stress and depression and then consider several specific topics of current conceptual and empirical interest.

Acute Life Events A major risk factor for depression is the experience of undesirable, or negative, life events. Indeed, a negative event is one of the most powerful risk factors for depression; Kendler, Karkowski, and Prescott (1998) noted that the experience of a high-threat life event increases the odds of major depression 5- to 16-fold in the next month or so, and generally there is a linear relationship between the severity and number of negative events and the probability of depression onset (Kendler et al., 1998). There is ample evidence that most major depressive episodes are triggered by stressful life events (see reviews by Hammen, 2005; Kessler, 1997). Mazure (1998) summarized the findings of her review as follows: recent stressors were 2.5 times more likely in depressed patients as compared to controls, and in community samples 80%

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of depressed cases were preceded by major life events. Cognitive appraisals, of course, may be an important moderator of the effects of stressors on depression, as the “severity” of the impact of an acute life event depends not only on the actual circumstances of the event but also its subjective meaning to the individual. It has been generally observed throughout the ages that depression is most likely to occur following the loss of something important to the sense of self, such as the loss of significant others or relationships, or of a sense of worth and competence. Interpersonal losses or “exits” have been shown to be more associated with depression than with other forms of disorder (Tennant, 2002; see also Kendler et al., 1995)—perhaps especially for women. Due to both biological and socialization processes, women are likely more attuned to and concerned about others’ reactions to them as well as more reactive to the needs of others (e.g., Cyranowski, Frank, Young, & Shear, 2000). Thus, women may be especially likely to be depressed in response to stressful social “loss” experiences and even to the negative experiences of others in their social networks. Gender differences in depression may be accounted for in part by both women’s greater exposure to interpersonal life events and also their greater likelihood, as compared to men, of reacting to such events with depression. Studies of adults have been mixed with regard to whether or not women experience more overall recent stressors (e.g., Kendler, Thornton, & Prescott, 2001), but studies have reliably found that adolescent females have higher levels of exposure to recent stressors than do males (Shih, Eberhart, Hammen, & Brennan, 2006). Moreover, several studies have shown that at comparable levels of acute stressors females had higher levels of depressive symptoms than did males (Maciejewski, Prigerson, & Mazure, 2001; Shih et al., 2006). Gender differences in exposure and reactivity may also reflect women’s higher levels of certain diatheses such as neuroticism or ruminative response styles, as well as meaning attached to interpersonal circumstances. In general, however, the risk factors for depression in men are likely very similar to those of women, involving complex interactions among environmental and neurobiological factors at different developmental stages (Kendler, Gardner, & Prescott, 2002, 2006). However, examination of gender differences in mechanisms underlying depressive responses to stress is sparse.

Chronic Stress Acute episodic life events tell only part of the depression story, however, and another source of depression is exposure to enduring long-term stressful circumstances. Many studies of stress–depression associations have not adequately distinguished between the effects of ongoing and acute stressors (e.g., Brown & Harris, 1978; Caspi et al., 2003), and failure to appreciate the distinction makes it difficult to fully explicate the mechanisms by which stressors have their effects on depression.



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Ongoing adverse sociodemographic conditions are significant predictors of depression as revealed in epidemiological studies. Hasin et al. (2005), in the National Epidemiologic Survey on Alcoholism and Related Conditions, found that major depressive disorder was associated with the female gender, low incomes, and being widowed, divorced, or separated. Similar results, and additionally low educational attainment and unemployed/disabled/homemaker occupational status, were also associated with major depressive disorder in the National Comorbidity Survey Replication (e.g., Kessler et al., 2003). Unfortunately, many of these conditions co-occur, with low educational attainment, low income, and disadvantaged work status related to one another and being a widowed/divorced/separated woman likely to be associated with lower income. A specific example of a chronically stressful condition amplified by cooccurring adverse conditions is single-mother status, and such women have higher rates of major depression than married mothers (e.g., Wang, 2004), especially for separated/divorced as compared to never-married mothers (Afifi, Cox, & Enns, 2006). Two large-scale studies have shown that the association between single-parent status and depression is entirely or largely mediated by higher chronic and acute stress and low social support (Cairney, Boyle, Offord, & Racine, 2003). Given that racial and ethnic minorities are overrepresented among low-income populations, another chronic stressor that has been examined extensively in relation to depression is racial discrimination (Gee, Spencer, Chen, Yip, & Takenchi, 2007). Residential neighborhoods also have been shown to be the source of multiple stressors including physical incivilities and high levels of noise, traffic, crime, and delinquency, to name a few (O’Campo, Salmon, & Burke, 2009; Rajaratnam, O’Campo, Caughy, & Muntaner, 2008). These stressors should be considered to contribute to the risk of depression independently of, or interact with, family or individual stressors that may place individuals at risk (Cutrona, Wallace, & Wesner, 2006; Rajaratnam et al., 2008). Chronically stressful relationships, such as marital and parenting roles, also contribute to depression and will be discussed in a separate section later on interpersonal vulnerabilities for depression.

Exposure to Early Adversity In addition to recent negative events and chronically stressful conditions, increasing evidence focuses on the link between childhood exposure to adversity and development of depression in adolescence or adulthood. One research strategy focuses on associations between a single specific experience, such as sexual abuse or physical or emotional maltreatment, and depression. There is ample evidence from mostly retrospective community and clinical studies of a significant association between childhood sexual or physical abuse and adult depression (e.g., Kendler et al., 2000; MacMillan et al., 2001) and similar results from prospective studies (e.g., Bifulco, Brown, Moran, Ball, &

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Campbell, 1998). Some studies suggest that abuse experiences are especially predictive of chronic or recurrent depression (Bifulco, Moran, Baines, Bunn, & Stanford, 2002). However, several studies suggest that physical and sexual abuse are related to diverse adult psychological disorders, not specifically to depression. Many of the studies have not distinguished among the specific types of abuse, nor have they controlled for factors in the environment that are correlated with the abuse, which could themselves influence the likelihood of depression (such as parental psychopathology). In a large study of psychiatric outpatients, Gibb, Butler, and Beck (2003) found that childhood emotional abuse was most specifically related to depression as compared with sexual or physical abuse (see also Alloy, Abramson, Smith, Gibb, & Neeren, 2006). Using a different research strategy, Kessler and Magee (1993) examined associations among one or more stressors from a diverse list of adverse experiences and depression. Their large-scale retrospective epidemiological study of community residents who met the criteria for major depression found that several childhood adversities (parental drinking, parental mental illness, family violence, parental marital problems, the death of the mother or father, and lack of a close relationship with an adult) were predictive of later onset of depression. Three early adversities—parental mental illness, violence, and parental divorce—were significantly predictive of the recurrence of depression. In a later similar study, Kessler, Davis, and Kendler (1997) examined 26 adversities occurring by age 16 and found that, although many of the events were associated with adult major depressive disorder, the adversities were also related to a broad array of psychological disorders besides depression. The investigators also noted that exposure to one or more adversities is common, occurring among three-fourths of the respondents, and that the adversities tend to overlap or cluster with one another. Further, they noted that no claim to causal relationships between the adversity and disorders is possible since there may be unmeasured common variables responsible for both the adversity exposure and the later disorder. Thus, while childhood traumas and early stressful conditions may contribute to depression, more study of the complex pathways is needed. The mechanisms by which specific childhood stressors such as physical or sexual abuse have their effects on later depression are not known directly. However, such experiences are highly likely to occur in the context of parental lack of care plus exposure to high levels of chronic and episodic stressors. Such environments contribute to dysfunctional attachment, cognitions, and coping skills that increase vulnerability to depression. Neurobiological mechanisms are also implicated, with the speculation, noted previously in the chapter, that severe stress early in life alters the brain’s neuroregulatory processes that promote susceptibility to depression (e.g., Heim & Nemeroff, 2001).

Sensitization and Kindling Exposure to adverse conditions in childhood may sensitize the youth to stress through both neuroendocrine and psychological processes, such that it may



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take less exposure to later stressful life events to precipitate depression as compared to those with no childhood adversity (e.g., demonstrated by Hammen, Henry, & Daley, 2000; Harkness, Bruce, & Lumley, 2006). Such processes represent an example of the emergence of the view that vulnerability to depression results from dynamic rather than static processes, in which, for example, progressive and developmental experiences alter the individual’s susceptibility to depression over time. Early adverse exposure (which could include perinatal experiences) and subsequent depression and life events alter the likelihood of responding to stress with depression and the threshold at which stressors trigger depression. As noted earlier, one approach emphasizes the effects of early adversity on the HPA axis system and its ability to regulate neuroendocrine functioning in response to stress. Another approach emphasizes the effects of prior stress and depression on the likelihood of a triggering association between stress and depression (e.g., Post, 1992). Observing the apparent tendency of depressive experiences to initially occur in response to stressors but over multiple episodes to become more independent of stressors, Post speculated that the underlying effects on the human brain in patients with recurrent mood disorders resembled the kindling and sensitization processes evident in the animal studies of progressive brain changes attributable to electrical stimulation or stimulant exposure. Although a full discussion of the meaning and mechanisms of his model is beyond the scope of this chapter, a few studies have demonstrated support for versions of the model in which depression episodes later in the course of disorder are associated less with stressors than are the first or earliest episodes (e.g., Monroe & Harkness, 2005; Kendler et al., 2000; Stroud, Davila, & Moyer, 2008).

Stress Generation In addition to the importance of viewing the stress–depression association as a dynamic one that changes with circumstances, that association also needs to be viewed as bidirectional and transactional. Hammen (1991) called attention to the tendency of women with histories of depression, compared with other-disorder and non-ill groups, to experience elevated rates of life events to which they had at least in part contributed. Such events, judged “dependent” on the person (in contrast to independent, or fateful, life events beyond the person’s control) were especially likely to have interpersonal content, and occurred even when the women were not depressed. Subsequently, this “stress generation” effect of higher stress among those with histories of depression has been widely replicated in adult, adolescent, and child samples, with men and women, and in community and patient samples (see reviews in Hammen, 2006; Hammen & Shih, 2008). Two implications are noteworthy. One is that increased rates of stress occurrence portend higher rates of recurrence or chronicity of depression, a vicious cycle with crucial practical and treatment implications. Second, the patterns suggest that vulnerability to depression recurrence may incorporate vulnerability to experience interpersonal stressors, a topic discussed in the following section.

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Interpersonal Approaches to Depression Vulnerability Problems in social relationships certainly may result from depressed mood, lack of enjoyment, irritability, low energy, and other syndrome features, leading to a downward spiral in which depression may be intensified or maintained by avoidance, hostility, or rejection by others. However, in this chapter we focus not on the consequences but rather on the possible interpersonal vulnerabilities that give rise to depression and also characterize the relationships of depressed people that portend depression onset or chronicity/recurrence. Several topics are selectively reviewed that suggest that for many individuals vulnerability to depression is uniquely tied to dysfunctional cognitions, behaviors, and traits that affect their interpersonal worlds and contribute to depressive outcomes.

Dysfunctional Parenting Depressed Adults’ Negative Experiences with Their Parents. As previously noted, early childhood abuse has commonly, although not uniquely, been associated with depression outcomes in adulthood. Gibb et al. (2003) found that childhood emotional abuse (rather than sexual or physical abuse) was most specifically related to depression. Similarly, retrospective studies of depressed patients have found that depressed adults report that their relations with their parents were marked by lack of caring, warmth, and acceptance, as well as stricter control (e.g., reviewed in Parker & Gladstone, 1996). Including studies of depressed community residents as well as patients in treatment for depression, Gerlsma, Emmelkamp, and Arrindell (1990) and a review by Alloy, Abramson, Smith, et al. (2006) concluded that reports of parental child-rearing styles that included low affection and more control (overprotection) were especially consistently related to depression. The mechanisms by which negative parent–child relations give rise to depression are not fully known and, as previously noted, are likely to include genetic and neurobiological stress processes (e.g., Caspi et al., 2003; Hooley et al., 2005). Dysfunctional parenting likely also occurs in the context of poor social problem solving, leaving children with poor models for learning how to resolve interpersonal disputes—or simply overwhelming their coping skills. Studies also have indicated that the association between negative parenting style and offspring depression is partly accounted for by negative cognitions such as low self-esteem, negative explanatory style, and other dysfunctional cognitions (e.g., Liu, 2003; review by Alloy, Abramson, Smith, et al., 2006). A further likely mechanism is insecure attachment, which according to Bowlby’s (1981) model likely results from caretaker rejection, unresponsiveness, or inconsistency. Failure to develop secure attachment results in negative representations of the self and others, leading to self-criticism, feelings of abandonment, hopelessness and helplessness, and related depressive symptoms, as well as expectations of loss and rejection. Although the great major-



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ity of attachment research has been conducted with children and adolescents, several studies with adults have supported the role of attachment as a vulnerability factor. Kobak, Sudler, and Gamble (1991) and Hammen et al. (1995) showed that young adults were more likely to become depressed following stressful life events if they had more insecure attachment representations of their parents or close figures. Bifulco, Moran, Ball, and Bernazzani (2002) found that insecure attachment representations predicted the onset of depressive episodes over a 1-year follow-up period. A retrospective study of clinically depressed women patients found that they reported significantly less attachment to their mothers than did nonpsychiatric controls (Rosenfarb, Becker, & Khan, 1994). Depressed Adults’ Parenting Difficulties. Considerable research indicates that depression in parents is associated with problematic parenting, which is considered an important mechanism by which the offspring of depressed parents have increased risk for depression and other disorders (e.g., reviewed in Goodman & Gotlib, 1999; Lovejoy, Graczyk, O’Hare, & Neuman, 2000). Parenting and other interpersonal difficulties may be exacerbated by current depressive symptoms but nonetheless may be evident even when the person is not depressed (e.g., Hammen & Brennan, 2002). It may be speculated that contributors to maladaptive parenting among depressed adults are histories of parenting dysfunction or abuse in their own families of origin, having “difficult” children who elicit conflict or ineffectual monitoring, stressful life circumstances including marital discord, as well as personality traits and styles that are risk factors both for depression and for nonoptimal parenting (e.g., neuroticism). Depression and Marital Discord. There is fairly strong evidence from longitudinal studies that earlier relationship dissatisfaction predicts depressive symptoms or episodes (e.g., Fincham, Beach, Harold, & Osborne, 1997). Whisman and Bruce (1999) examined marital dissatisfaction in over 900 nondepressed married adults in an epidemiological sample. They found that dissatisfied spouses were nearly three times more likely than satisfied spouses to develop a depressive episode in the subsequent 12 months, and the effects were similar for men and women. Relationship difficulties affect the course of depression as well. Spousal expressions of criticism and negative attitudes toward the depressed person (sometimes termed “expressed emotion”) have been shown to predict relapse following treatment or hospitalization (Butzlaff & Hooley, 1998). Studies of family functioning of hospitalized depressed patients indicate that those with poorer family functioning were less likely to recover within 12 months and to have a worse long-term course of depression (Keitner, Ryan, Miller, & Kohn, 1995; Keitner, Ryan, Miller, & Zlotnick, 1997). Overall, therefore, conflict and dissatisfaction in marital and family relationships may contribute to the onset and continuing course of depressive disorders.

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Depression also contributes to marital unhappiness, including effects on the spouse. Whisman, Uebelacker, and Weinstock (2004) attempted to tease apart the influence of mood state and marital dissatisfaction in subjects and their partners, and found that not only did current depressed mood predict marital dissatisfaction for the self, but also the spouse’s depressed mood predicted the partner’s dissatisfaction. Coyne, Thompson, and Palmer (2002) studied attitudes of female depressed patients and their spouses and found that both partners reported more marital distress, poor conflict resolution tactics, and less positive expressions of affection as compared to nondepressed couples. The romantic relationships of young women assessed over a 5-year period indicated that lower quality of the relationships at the end of the follow-up and the boyfriends’ dissatisfaction were significantly correlated with the amount of time the women had spent in major depressive episodes (Rao, Hammen, & Daley, 1999). Zlotnick, Kohn, Keitner, and Della Grotta (2000) used a large epidemiological database to compare people who were currently depressed, nondepressed, and those with other psychiatric disorders on ratings of the quality of relationships with their spouses/partners. The depressed individuals—both men and women—reported significantly fewer positive and more negative interactions with their partners than did the other two groups. Thus, there may be something specific about depression and dissatisfaction in intimate relationships that is not as marked among those who have nondepressive disorders. Vulnerability Factors for Interpersonal Discord. It may be speculated that one mechanism of depression is the creation of dysfunctional (stressful) relationships that trigger depression. We noted earlier in the chapter that people with histories of depression appear to generate elevated rates of interpersonal life events and chronic stress. One ingredient of stressful relationships is the selection of partners who are themselves disordered, presumably heightening the prospects of disrupted lives and dysfunctional interpersonal problem solving. Depressed people tend to marry other people with psychological problems, according to a review and meta-analysis by Mathews and Reus (2001). Depressed women patients have also been found to have higher rates of marriage to men with antisocial and substance use disorders (e.g., Hammen, 1991). Research on nonpatient samples also shows a similarity between spouses as it relates to depressive disorders (e.g., Galbaud du Fort, Bland, Newman, & Boothroyd, 1998; Hammen & Brennan, 2002), and a wife’s major depression is positively correlated with the husband’s antisocial personality disorder (Galbaud du Fort et al., 1998). While the possible reasons for “nonrandom mating” are beyond the scope of this chapter, they raise intriguing issues. Besides partner characteristics, are there other interpersonal traits and behaviors likely to contribute to relationship dysfunction? Several mechanisms likely underlie the association between depression and difficulties in intimate relationships, including maladaptive cognitions, attachment insecu-



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rities leading to dependency and distrust, excessive reassurance seeking, and other behaviors that provoke conflict. One well-studied trait is neuroticism, a higher-order heritable personality dimension defined by negative emotionality and high reactivity to real and perceived stress. Neuroticism is a powerful predictor of depressive episodes, according to a review by Enns and Cox (1997; see also Schmitz, Kugler, & Rollnik, 2003). One mechanism may be the role of neuroticism in stress generation. Kendler, Gardner, and Prescott (2003), for example, found that neuroticism was a strong predictor of stressful life events, particularly those related to interpersonal relationships—as well as a determinant of emotional responses to stress. Kendler, Kuhn, and Prescott (2004) found that neuroticism moderated the effects of stress on depression, particularly potentiating its effects at the highest levels of stress exposure. There is a long history of studies showing that depressed people have relatively more dependency beliefs (emotional reliance on others, the belief that the affection, acceptance, and support of other people are essential to personal worth) than do the nondepressed (reviewed by Nietzel & Harris, 1990). A review by Zuroff, Mongrain, and Santor (2004) concluded that levels of dependency may be affected by current mood but are relatively stable over time. High levels of dependency predict future onset or relapse of major depression (e.g., Sanathara, Gardner, Prescott, & Kendler, 2003). Clark, Watson, and Mineka (1994) examined correlates of dependency and reported that it appears to be a characterological dimension of inhibited expression, particularly of difficulty expressing hostility and anger. Dependency traits are generally more elevated in women than men (Bornstein, 1992). Dependency and neediness may lead individuals to seek reassurance of their worthiness from others, but that neediness or reassurance seeking may actually provoke negative reactions. Reassurance seeking may be annoying to others because depressed people may appear to be unreasonable and irrational in their worries, insecurities, and lack of apparent motivation and energy—so that their “inconsolability” is irritating and burdensome to those trying to help. The depressed person may appear to be unable or unwilling to accept the reassurance or take the steps the nondepressed partners think are needed to overcome depression. Several studies have shown that excessive reassurance seeking may result in increased levels of depression over time, presumably due to the negative reactions and perceived rejection it elicits in others (e.g., Joiner & Schmidt, 1998). Deficiencies in Social Support. In addition to difficulties in intimate family relationships, depressed people and those at risk for depression also appear to have problems with the availability—or the perception of availability—of supportive relationships with others, including friends and associates. Perceived support helps to reduce depression and its likelihood of recurrence (Sherbourne, Hays, & Wells, 1995). However, depression appears to be associated with low levels of perceived support (Burton, Stice, & Seeley, 2004; Dalgard et al., 2006). Reduced availability of supportive relations with others

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may be “real” in terms of actual social isolation due to behaviors and traits that discourage sustained and helpful relations with others (e.g., introversion and behavioral inhibition—Gladstone & Parker, 2006; poor social skills— Tse & Bond, 2004). Also, of course, depressive states may result in negative and distorted cognitions about one’s worthiness and likelihood of receiving effective help from others. Such perceptions may cause failure to seek help and support even if it does exist.

Future Directions for Research Throughout the chapter a number of issues have been highlighted for further research and analysis. Starting with the fundamental issue of what is depression, considerable work remains to be done to determine the unique and specific effects and origins of depression, given its common co-occurrence with other Axis I and Axis II disorders. Basic questions about the potential effects of different degrees of severity and course, as well as the potential subtypes of depression with different causes and consequences, remain. Depression heterogeneity continues to pose a conceptual and methodological challenge, and in practical terms it may limit the scope of research accomplishments if they can be generalized only to certain forms and levels of depression. Moreover, depression is increasingly viewed as a chronic or intermittent disorder, raising crucial challenges to the nature of treatment. There is an overarching need for integrative models of vulnerability that link biological and psychosocial processes, so that theories are not artificially in competition. As we have noted, some recent advances have begun to explore these links, but much more remains to be done before we see truly integrative models. Similarly, despite increased numbers of longitudinal studies in recent years, insufficient numbers of studies have tested their etiological elements in longitudinal designs—with the vast majority of studies describing current features. Specific tests of vulnerability models in a diathesis–stress design are increasing but are still relatively rare. Models also need to capture the potentially dynamic nature of vulnerability processes, based on the supposition that depression and other personal experiences alter the neurobiological and psychosocial environments and change the relationships among stress and diathesis factors over time. The content of psychological vulnerability models continues to emphasize cognitive and interpersonal factors, and exciting developments in the ways in which these processes are measured and understood have evolved. Nevertheless, critical questions remain about the etiological significance of such factors. Even at the level of understanding cognitive and social processes, comparatively little is known about their acquisition and operation in normal individuals as well as in those suffering from susceptibility to mood disorders. Increasingly also, developments in understanding genetics and neurobiology, along with advances in such methods, have raised expectations for etiological discoveries, but questions about etiological signifi-



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cance also arise in such studies. Truly integrative, developmentally informed, and longitudinal studies will be needed to address issues of etiology and vulnerability. Finally, it is worth repeating that further attention needs to be given to the three most robust findings to date in the depression field: it is most common in women, past depression is the strongest predictor of future depression, and depression runs in families. There is much to be extracted from these realities, and future theoretical and practical developments in vulnerability theory and research will profit from setting our sights on providing explication.

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Chapter 10

Vulnerability to Depression across the Lifespan Constance L. Hammen, Judy Garber, and Rick E. Ingram

This chapter in the first edition of Vulnerability to Psychopathology: Risk across the Lifespan noted that, for the most part, investigators of child/adolescent depression and adult depression have pursued separate paths. This observation remains largely accurate today, with research on childhood depression commonly guided by models and definitions of adult depression and with relatively little independent development of theories unique to children. It seems apparent in reading Chapters 8 (Garber, this volume) and 9 (Hammen, Bistricky, & Ingram, this volume) that there are critical gaps in both fields that are in part attributable to this typical age-related division of labor and its usual designs and methods. In this brief chapter, we explore several of these issues and make recommendations for further study.

Diagnostic and Definitional Issues An important concern is whether common diagnostic criteria identify the same underlying disorder and the same vulnerability factors in childhood, adolescent, and adult depression. As complex as this issue sounds on the surface, it becomes even more complicated because of the difficulties in knowing exactly where to draw the boundaries separating childhood from adolescence and then from adulthood. Further complicating issues of diagnosis and definitions are implicit assumptions about the nature of depression. As Hammen et al. (Chapter 9, this volume) note, simply meeting the diagnostic criteria for adult depression does not reflect the reality that depression is a dynamic

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process with potentially numerous underlying etiological factors. To implicitly assume that “depression” is the same disorder across the lifespan ignores that fact that depression may not be the same disorder even within a particular age group or developmental stage. At a minimum, however, within existent diagnostic criteria, research focused on identifying risk factors needs to examine these variables across developmental stages. Another important developmental issue concerns the age of onset of depression in adult samples, which is rarely identified. This leaves the impression that they had their onset during adulthood, although it is likely in many cases that the first episodes or significant symptoms began in adolescence or even earlier. It is likely that important differences exist in the features and correlates of depressive disorder as a function of age of onset and therefore should be studied further. Several important questions remain regarding the age of onset of depression. First, earlier age of onset of depression is associated with a worse course of depression, greater chances of recurrence, chronicity, and impairment in role functioning (e.g., Hollon et al., 2006), but does early onset reflect a distinct “type” of depression? Second, is there a commonality among depressions that commence at different ages? If not, are the differences due to developmental factors shaping the same underlying disorder, or are they actually different forms of depression? Third, what developmental factors influence the differential experience and expression of depressive symptoms and disorders over time? Finally, do the same processes underlie first-onset, maintenance, and recurrence of depression across the lifespan? These and related definitional issues remain unresolved and require developmentally informed models to be hypothesized and tested in longitudinal designs.

Models of Vulnerability The problems of defining depression across development stages not only are critical in their own right but also affect our ability to evaluate the evidence for vulnerability factors and etiological processes over time. These latter issues are further obscured by the relative neglect of developmental perspectives in the models themselves, as noted in the following topics.

Genetic Studies The rapidly developing technologies for identifying appropriate samples and testing biometric models have resulted in studies that are far superior to family pedigree studies in partitioning the relative contributions of heritability and environmental factors. Hammen et al. (Chapter 9, this volume) indicated that adult studies consistently find moderate genetic factors, although females and males may have different genetic liabilities for depression (Kendler, Gatz, Gardner, & Pedersen, 2006). Garber (Chapter 8, this volume) noted, however,

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that, depending on the age of the child and the source of the information, both twin and adoption studies present a more inconsistent picture in childhood. Methodological limitations make it difficult to know whether age and gender differences in genetic patterns are in fact unknown or simply muddled by the lack of clear definitional and developmental considerations.

Studies of Neurobiology Adult studies implicating disordered markers of neuroendocrine functioning such as sleep architecture and cortisol regulation have not translated well to youth samples (Dahl & Ryan, 1996). Several inconsistent findings in child or adolescent samples seemed eventually to prod investigators to consider that such parameters might not be appropriately measured in youth in the same ways as in adults due to the developmental differences (Dahl et al., 1992). On the positive side, research considering the influence of negative experiences on the developing brain represents an exciting and potentially significant focus for future work on vulnerability. Several intriguing findings highlight important directions for future research on biological vulnerability, including that the children of depressed mothers show relative left frontal hypoactivation of the type seen in adult depressive episodes (Tomarken, Dichter, Garber, & Simien, 2004), the influence of maternal depression on the quality of infant–parent relationships potentially affecting brain functioning, genetically transmitted patterns of electrophysiological emotion-related responding (Dawson, Frey, Panagiotides, Osterling, & Hessl, 1997; Dawson, Klinger, Panagiotides, Hill, & Spieker, 1992), and the role of traumatic exposure in childhood sensitizing individuals to how they experience stressors in the future. These studies may increasingly provide an understanding of how depression vulnerabilities operate and how they may affect the further development of at-risk youth. Such information also may provide fruitful glimpses into potential mechanisms behind recurrent depression in adults and the processes by which critical experiences alter the person’s vulnerability to react with depression to provoking situations and stressors.

Cognitive and Social Factors The cognitive perspective posits that individuals become depressed following life events if they interpret the events to reflect badly on their current or future worth or competence. This process can occur in both children (e.g., Joormann, 2009) and adults (e.g., Segal et al., 2006), although the variables that mediate such information processing may differ across development stages. As Chapter 9 points out, support for the vulnerability portion of this model for adults has been increasing (Scher, Ingram, & Segal, 2005), based largely on paradigms using methods to activate the proposed negative schemas (Ingram, Miranda, & Segal, 1998). Some parallels in research with children have been found (e.g., Joormann, 2009; Taylor & Ingram, 1999), although we need to

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learn more about depressed children’s information processing of schematic information. Within the cognitive perspective, one proposition that serves as a clear link between childhood and adulthood is the idea that the tendencies to interpret events negatively may be acquired in childhood and serve as a latent vulnerability for depression later in life (Beck, 1967). Several studies (e.g., Alloy et al., 2004; Garber & Flynn, 2001) have identified processes by which negative cognitions may be acquired, although it would be fruitful both for depression models specifically and social cognition research in general to learn more about children’s formation and use of schemas about the self and others, and how these schemas change over the course of development. Ample evidence attests to the role of stressful life events as triggers for depressive reactions among those who may be vulnerable to respond with significant and enduring depression. Chapters 8 and 9, respectively, note that the evidence for the stress–depression link is strong in both child and adult samples. Developmental issues profoundly affect children’s exposure to stressors as well as their resources for coping with them. The problem-solving techniques and coping strategies that children use may greatly affect their reactions to negative events as well as predict their capacity to deal with challenges and stressors as adults. One of the most important predictors of depressive reactions appears to be negative social events, especially if they match underlying interpersonal needs and vulnerabilities. The interpersonal perspective is attracting increasing attention with regard to depression in both adults (Gotlib & Hammen, 1992) and children (e.g., Rudolph, Hammen, & Burge, 1997). Moreover, the role of negative social interactions that often follow from depression is becoming increasingly recognized (Hammen, 2006). Studies are needed that directly examine the social skills and schemas of depressed youth, especially those behaviors and cognitions that may affect the quality of their interpersonal relationships both within and outside the family. At the same time, studies of family processes among high-risk families in which a parent suffers from depression have been increasingly informative about potential vulnerabilities for depression (reviewed in Goodman & Gotlib, 1999). Such investigations have been innovative in the methods of studying dysfunctional transactions between depressed parents and their children and the role of such interactions in the transmission of depression from parents to children. Further studies of the continuities across different development stages of dysfunctional interpersonal styles may help to shed light on an important mechanism of depression and its intergenerational transmission.

Conclusions Chapters 8 and 9 noted the burgeoning research on depression that contributes to a much richer understanding of mood disorders across the lifespan. We expect that this level of research activity will continue to address the many

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unresolved questions, although we caution that new paradigms are needed for the more mature state of this field. Although cross-sectional studies and single-construct approaches were appropriate to early investigations, there is a need for more integrative, longitudinal, and intervention studies to address the complexities of the construct. Integration of biological and psychosocial perspectives is clearly called for but difficult to accomplish. Yet, research on depression is becoming more and more multidisciplinary. Static linear models must yield to more complex models involving transactions among variables. The influence of earlier experiences on later behavior and the mutual influences of the person and environment on each other are some of the obvious dynamic processes that must be captured by a developmental psychopathology perspective of depression. We look forward to many more achievements in the field of depression and predict that the barriers between child and adult research will continue to diminish in order to address some of the unresolved issues noted here.

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Ingram, R. E., Miranda, J., & Segal, Z. V. (1998). Cognitive vulnerability to depression. New York: Guilford Press. Joormann, J. (2009). Cognitive aspects of depression. In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression (2nd ed., pp. 298–321). New York: Guilford Press. Kendler, K. S., Gatz, M., Gardner, C. O., & Pedersen, N. L. (2006). A Swedish national twin study of lifetime major depression. American Journal of Psychiatry, 163, 109–114. Rudolph, K. D., Hammen, C., & Burge, D. (1997). A cognitive-interpersonal approach to depressive symptoms in preadolescent children. Journal of Abnormal Child Psychology, 25, 33–45. Scher, C. D., Ingram, R. E., & Segal, Z. V. (2005). Cognitive reactivity and vulnerability: Empirical evaluation of construct activation and cognitive diathesis in unipolar depression. Clinical Psychology Review, 25, 487–510. Segal, Z. V., Kennedy, M. D., Gemar, M., Hood, K., Pedersen, R., & Buis, T. (2006). Cognitive reactivity to sad mood provocation and the prediction of depressive relapse. Archives of General Psychiatry, 63, 749–755. Taylor, L., & Ingram, R. E. (1999). Cognitive reactivity and depressotypic information processing in the children of depressed mothers. Journal of Abnormal Psychology, 108, 202– 210. Tomarken, A. J., Dichter, G. S., Garber, J., & Simien, C. (2004). Resting frontal brain activity: Linkages to maternal depression and socio-economic status among adolescents. Biological Psychology, 67, 77–102.

Anxiety Disorders

Chapter 11

Vulnerability to Anxiety Disorders in Childhood and Adolescence Vanessa L. Malcarne, Ingunn Hansdottir, and Erin L. Merz

The experience of anxiety is part of a normal course of development for children. Although distinctions have been made between fears and anxiety, with the former seen as more specific and the latter as more anticipatory and diffuse, both share similar cognitive, affective, and physiological response patterns (Campbell, 1986), and both are experienced by virtually all children. An important challenge is to distinguish developmentally appropriate fears/ anxiety from those that are inappropriate and/or pathological at different ages and developmental stages. Although the conceptualization of childhood anxiety disorders has its roots in the 1800s, it was not until much more recently, in the taxonomy of the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III; American Psychiatric Association, 1980), that child and adolescent anxiety disorders were systematically described and differentiated (Hooper & March, 1995). At that time, several anxiety disorders were categorized in a separate section of DSM-III for disorders usually first diagnosed in infancy, childhood, and adolescence, including separation anxiety disorder (SAD), overanxious disorder (OAD), and avoidant disorder of childhood (AVD). Subsequent revisions of the DSM have eliminated most of the distinctions between child and adult anxiety. In DSM-IV and IV-TR (American Psychiatric Association, 1994, 2000), only SAD is still considered a children’s disorder. OAD is subsumed under generalized anxiety disorder (GAD), with only one of the central symptoms being required for diagnosis in children. AVD is subsumed by social phobia (SOC), with special considerations included for diagnosis in children. All other variants of anxiety are listed as adult syndromes, in some cases with developmental features delineated (American Psychiatric Associa

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tion, 1994).1 For example, for specific phobia (SP; previously called simple phobia and renamed for compatibility with the 10th edition of the International Classification of Diseases [ICD-10; World Health Organization, 1988]), SOC, and obsessive–compulsive disorder (OCD), it is not required that children see their fears as excessive or unreasonable (Craske, 1997). The constant revision of DSM criteria for anxiety disorders has made it difficult to establish definitive prevalence and incidence data, and the results of research conducted using now outdated criteria may have limited applicability (Majcher & Pollack, 1996). More data are needed, particularly for children 5 and younger (Costello & Angold, 1995). However, evidence to date does point clearly to one general conclusion: considered broadly, anxiety disorders are common in childhood.

Epidemiology As a group, anxiety disorders represent the most prevalent form of childhood psychopathology (Cartwright-Hatton, McNicol, & Doubleday, 2006; Costello, Egger, & Angold, 2005; Pollock, Rosenbaum, Marrs, Miller, & Biederman, 1995; Roberts, Roberts, & Xing, 2007). In young children and adolescents, anxiety disorders are more common than depressive disorders (Cartwright-Hatton et al., 2006; Roberts et al., 2007) and are twice as common as attention deficit disorder (ADD; Popper, 1993; Roberts et al., 2007). In reviews of the epidemiological literature, Costello et al. (2005) reported that 2–33% of children between ages 5 and 17 may have an anxiety disorder; while Cartwright-Hatton et al. (2006) reported rates between 3.05 and 23.9%. Lower estimates typically reflect studies in which more stringent diagnostic criteria are applied (Bell-Dolan, Last, & Strauss, 1990; Bernstein & Borchardt, 1991; Cartwright-Hatton et al., 2006). Compared to other clinical diagnoses, anxiety disorders are especially susceptible to impairment thresholds; rates are lowered when higher thresholds are required (Masi, Mucci, & Millepiedi, 2001). For example, in a sample of adolescents between 11 to 17 years old, 6.89% had an anxiety disorder; however, when different levels of clinical impairment were required for classification, rates decreased to ranges between 1.36 and 3.42% (Roberts et al., 2007). In another adolescent sample, Kashani and Orvaschel (1988) found that 17.3% met criteria for at least one

1Because overanxious disorder and avoidant disorder of childhood were considered separate disorders of childhood until they were subsumed under adult disorders in DSM-IV, much of the research on childhood anxiety disorders has used these diagnostic categories. Also, although there is a recent movement toward using the term “social anxiety disorder” instead of “social phobia” (Ollendick & Hirshfeld-Becker, 2002), “social phobia” is still the formal name of the disorder in DSM-IV-TR. In this review, the original category names are used when appropriate to reflect the categories employed in research studies.



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anxiety disorder; this dropped to 8.7% with a stricter requirement of clinical impairment (Bernstein & Borchardt, 1991). Studies that used DSM III-R diagnostic criteria, in which symptom-related distress and impairment are not required for a diagnosis, reported greater prevalence of all anxiety disorders (Cartwright-Hatton et al., 2006; Roberts et al., 2007; Zahn-Waxler, KlimesDougan, & Slattery, 2000). The importance of impairment is uncertain, particularly in early diagnoses. Anxiety symptoms that are not impairing in early childhood may become so as a child develops and experiences novel settings apart from the family environment; thus stringent thresholds potentially underestimate prevalence and individual clinical needs (Cartwright-Hatton et al., 2006). Prevalence rates vary for specific anxiety disorders in children and adolescents. SAD, SP, and OAD appear to be the most common. Prevalence estimates of SAD in nonpsychiatric child samples have been reported from 0.5 to 20.2% (Cartwright-Hatton et al., 2006) but more commonly range from 3 to 5% (Anderson, Williams, McGee, & Silva, 1987; Benjamin, Costello, & Warren, 1990; Bird et al., 1988; Canino et al., 2004; Costello et al., 1996; Lewinsohn, Holm-Denoma, Small, Seeley, & Joiner, 2008; Masi, Mucci, et al., 2001; McGee et al., 1990; Roberts et al., 2007). However, some estimates are much higher (Gurley, Cohen, Pine, & Brook, 1996). Prevalence estimates for SP can vary from 0.7 to 21.6%, depending on impairment criteria (Costello, Egger, & Angold, 2005), but burden is generally 6% or less (Anderson et al., 1987; Bird et al., 1988; Cartwright-Hatton et al., 2006; Fergusson, Horwood, & Lynskey, 1993; McGee et al., 1990); although some studies have shown rates above 9% (Benjamin et al., 1990; Costello et al., 1988; Gurley et al., 1996; Kessler et al., 1994). OAD prevalence estimates range from 0.16 to 14.3% across studies (Anderson et al., 1987; Benjamin et al., 1990; Cartwright-Hatton et al., 2006; Costello et al., 1996; Fergusson et al., 1993; Gurley et al., 1996; McGee et al., 1990; Whitaker et al., 1990). Other anxiety disorders appear to be less common in children. Estimates of prevalence rates for AVD are low, ranging from 1 to 2% (Anderson et al., 1987; Benjamin et al., 1990; Costello et al., 1996; Fergusson et al., 1993; Gurley et al., 1996; McGee et al., 1990). OCD estimates fall mostly in the 0–2.6% range (Benjamin et al., 1990; Cartwright-Hatton et al., 2006; Costello et al., 1996; Douglass, Moffitt, Dar, McGee, & Silva, 1995; Flament et al., 1988; Whitaker et al., 1990). There are few epidemiological studies of other anxiety disorders in children. Panic disorder (PD) and agoraphobia (AG) are both rare in children (Bernstein & Borchardt, 1991; Cartwright-Hatton et al., 2006; Pine, 1997). Posttraumatic stress disorder (PTSD) has not been assessed in many of the epidemiological studies of anxiety disorders in children (Bernstein & Borchardt, 1991; Pine, 1997), and its prevalence is unknown, although it may be common in abused children (McLeer, Deblinger, Hendry, & Orvaschel, 1992).

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Developmental Course and Stability Infancy–Preschool Anxiety disorders are rarely diagnosed in children at very young ages, perhaps in part because the diagnostic criteria are not designed to reflect the developmental, and in particular verbal, characteristics of infants and toddlers (Warren, Umylny, Aron, & Simmens, 2006). However, the experience of anxiety related to specific objects and situations is common in young children. In a review of developmental aspects of children’s fears, Campbell (1986) reported that during infancy children show developmentally appropriate fears of loud and sudden stimuli, loss of support, and heights. By the second half of their first year of life they display fear of strangers and novel objects. Similarly, Morris and Kratochwill (1983) listed loss of support and loud noises as common fears of infants in their first 6 months of life; infants ages 7–12 months feared strangers and sudden, unexpected, and looming objects. Children who are 1–4 years old commonly fear separation from parents. This separation anxiety usually appears during the latter 6 months of the first year of life, peaks at around 18 months or after, and is fairly common through age 4 (Dashiff, 1995; Popper, 1993). Animals, darkness, and monsters also constitute common fears of toddlers and preschoolers (Campbell, 1986). Whether or not very young children can validly be diagnosed with anxiety disorders will require modification of DSM criteria to integrate developmental considerations. Warren et al. (2006) described efforts to revise diagnostic criteria for SOC and GAD and apply these via semistructured interviews to children ages 18 months to 5 years. Preliminary results supported the validity of the SOC criteria, but children identified as GAD did not show higher anxious characteristics than nonanxious children.

Middle Childhood Anxiety is a common experience of middle childhood, especially at subclinical levels and when individual symptoms rather than syndromes are assessed. In a national survey, Kessler and colleagues (2005) found that the median age of onset for any anxiety disorder was 11 years. Bell-Dolan et al. (1990) found that 9.8–30.6% of 62 nonreferred children reported subclinical levels of individual OAD symptoms, while 10.7–22.6% endorsed subclinical phobias. The most common symptoms were excessive concern about competence, excessive need for reassurance, fear of the dark, fear of harm to an attachment figure, and somatic complaints. The anxiety disorder most commonly diagnosed in middle childhood is SAD, with age of onset at around 7 years (Anderson et al., 1987; Bernstein & Borchardt, 1991; Kessler et al., 2005; Last, Perrin, Hersen, & Kazdin, 1992; Zahn-Waxler et al., 2000). Francis, Last, and Strauss (1987) found developmental changes in SAD symptom expression, with younger children (ages 5–8) more likely to be concerned about harm to attachment figures, to engage in school refusal, and to report nightmares about separation.



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In contrast, older children (ages 9–12) were mainly distressed at the time of separation and rarely reported nightmares. SP is also diagnosed in middle childhood (Bernstein & Borchardt, 1991; Kessler et al., 2005; Zahn-Waxler et al., 2000). Last et al. (1992) found an average age at onset of 8.4 years in a clinical sample. Unfortunately, little description of childhood SP exists (Silverman & Ginsburg, 1995), although there is literature on childhood fears, which are quite common in normal children (Ollendick & Francis, 1988; Silverman & Nelles, 1990). Ollendick, King, and Frary (1989), in a study exploring the psychometric properties of the Fear Survey Scale for Children—Revised in large samples of normal children from the United States and Australia, found that specific fears varied little by age, sex, or nationality for children ages 7–16. For all ages, the most commonly endorsed fears were “being hit by a car/truck” and “not being able to breathe.” As noted previously, OAD has now been subsumed under GAD as a result of problems with the OAD category (notably the lack of specificity; Werry, 1991). Thus, there is limited information on GAD in children. Previous evidence suggested that OAD first appears in middle childhood, although perhaps in a less severe form; Last et al. (1992) found an average age at onset of 8.8 years.

Adolescence The same anxiety disorders seen in middle childhood are also seen in adolescence (Bernstein, Borchardt, & Perwien, 1996; Cartwright-Hatton et al., 2006). While SAD appears to become less common (Dashiff, 1995; Francis et al., 1987), anxiety disorders are more prevalent in this age cohort than any other mental disorder (Roberts et al., 2007). As noted previously, adolescents diagnosed with SAD appear to show different patterns of symptom expression than younger children; they also report fewer symptoms (Francis et al., 1987). The opposite pattern is seen for OAD, with older children endorsing a greater number of symptoms, especially worries about the future (Strauss, Lease, Last, & Francis, 1988). For SP, prevalence rates are stable from childhood to adolescence. Although it has been suggested that there may be age variations in the focus of specific phobias, this has not been addressed empirically. OCD is most commonly diagnosed in early to mid-adolescence. Last et al. (1992) reported mean age at onset of 10.8 years; Flament et al. (1988) reported a mean age at onset of 12.8 years, with the most common obsessions being fear of contamination (35%) and thoughts of harm to self and familiar figures (30%) and the most common compulsions being washing and cleaning (75%). Adolescents also begin to show vulnerability to other anxiety disorders that are rarely seen at earlier ages, such as AVD and PD (Bernstein et al., 1996; Zahn-Waxler et al., 2000). AVD (SOC in DSM-IV) does occur before adolescence (e.g., Last et al., 1992, found the age of onset to be 8.2 years), but

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the most common age of onset is early to mid-adolescence (e.g., Kessler et al., 2005, found the median age of onset to be 13 years).

Stability A growing number of prospective studies have examined the stability of anxiety disorders in children (for an excellent recent review, see Hirshfeld-Becker, Micco, Simoes, & Henin, 2008). Such studies typically follow children who have demonstrated symptoms of anxiety at early ages, or follow large cohorts of community children, linking early characteristics to later anxiety outcomes. Evidence from both types of studies suggests that early indication of anxiety is associated with increased risk of anxiety disorders later in childhood or in adulthood; however, only a subset of anxious children continues to have problems with anxiety at older ages. In one of the first methodologically strong prospective studies, Last et al. (1996) followed children with anxiety disorders, ADHD, or no diagnosis for 3–4 years and found that 82% of referred children and adolescents diagnosed with anxiety disorders no longer met criteria for their disorder at the final follow-up, and two-thirds went into remission within the first year. At follow-up, one-third of the children had developed new disorders, mostly new anxiety disorders. A later follow-up of a smaller subset of the same original sample found that young adults diagnosed with anxiety disorders as children looked similar to those who had not had childhood clinical diagnoses; however, young adults earlier diagnosed with comorbid anxiety and depression had poorer outcomes (Last, Hansen, & Franco, 1997). Since Last et al.’s (1996, 1997) studies, several other prospective studies have been completed in which children diagnosed with anxiety disorders using structured interviews were followed over a period of years, in some cases up to a decade or more and/or into adulthood. Community-based and clinical studies, from the United States or New Zealand and with generally large samples, have found that having a diagnosis of an anxiety disorder in childhood significantly increases the odds of meeting criteria as an adult (in the United States: Biederman et al., 2007; Costello et al., 2003; Lewinsohn et al., 2008; Pine, Cohen, Gurley, Brook, & Ma, 1998; in New Zealand: Gregory et al., 2007, Kim-Cohen et al., 2003; Moffitt et al., 2007; Newman et al., 1996; Woodward & Fergusson, 2001). The overall pattern was for childhood diagnoses of anxiety to yield about a three-fold increase in risk for later anxiety disorders, suggesting substantial stability. There was also evidence that comorbidity during childhood, particularly of depression and anxiety, was associated with even higher risk of later diagnoses (e.g., Costello et al., 2003; Gregory et al., 2007; Kim-Cohen et al., 2003; Last et al., 1997; Moffitt et al., 2007; Pine et al., 1998). Some prospective studies have focused on anxiety symptoms and/or subclinical levels of anxiety rather than on actual diagnoses of disorders. These studies have generally found evidence of stability throughout childhood and



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adolescence. For example, lalongo and colleagues found that self-reported anxiety symptoms were moderately stable over a 4-month period in first grade (lalongo, Edelsohn, Werthamer-Larsson, Crockett, & Kellam, 1994) and that anxiety in first grade predicted anxiety and functioning in fifth grade (lalongo, Edelsohn, Werthamer-Larsson, Crockett, & Kellam, 1995). In a large representative Australian sample, Sanson, Pedlow, Cann, Prior, and Oberklaid (1996) found evidence of moderate stability for maternal reports of shyness from infancy to age 6, with children at the extremes (very low or high shyness) to be most stable over time. In another study by the same research team, Prior, Smart, Sanson, and Oberklaid (2000) found that parental reports of high shyness at ages 3–4 predicted increased risk of anxiety disorders in adolescence. In an American study, Bosquet and Egeland (2006) found modest stability in anxiety between infancy and adolescence in children born to at-risk mothers, considered so due to characteristics such as poverty and/or high life stress. Interestingly, they found that heightened reactivity and poor emotion regulation in very early infancy were associated with anxiety in childhood, although the relationship became nonsignificant by adolescence. Feng, Shaw, and Silk (2008) followed an ethnically diverse low-income sample of boys from infancy to early adolescence and identified four groups with varying trajectories: (1) stable low levels of anxiety, (2) high anxiety at age 2 but declining over time (approximately one-third of the sample), (3) low anxiety at age 2 but increasing over time, and (4) high anxiety at age 2 and increasing over time. Early shyness characterized boys in the high-declining and high-increasing groups; the low-increasing and high-increasing groups were more likely to have negatively controlling mothers. Evidence for the continuity of specific anxiety disorders is mixed. Studies using clinical interviews and/or anxiety checklists have found that specific anxiety diagnoses or symptoms in childhood are associated with the same problems in adolescence or adulthood. However, there is also substantial evidence of cross-anxiety disorder predictive relationships; often evidence both for and against specificity is found in the same studies (e.g., Ferdinand, Dieleman, Ormel, & Verhulst, 2007; Gregory et al., 2007; Lewinsohn et al., 2008; Pine et al., 1998). Childhood anxiety is also predictive of later depression or of internalizing disorders in general (Biederman et al., 2007; Gregory et al., 2007; Last et al., 1996; Moffitt et al., 2007; Pine et al., 1998). For example, Pine et al. found, in their prospective study following a large sample of adolescents into early adulthood, that simple phobia and SOC showed specific relationships over time. In contrast, OAD and GAD were associated with depression as well as anxiety. A recent 5-year prospective study of a community sample of junior high and high school students in the Netherlands found interesting results regarding possible gender differences in stability (Hale, Raaijmakers, Muris, van Hoof, & Meeus, 2008). All adolescents showed slight decreases in PD, school anxiety, and SAD symptoms, while SOC symptoms stayed generally stable. However, girls showed an increase in GAD symptoms over time, in contrast to boys, who showed a decrease. Hale

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et al. (2008) note that Pine et al. (1998) found that OAD (equivalent to GAD) in adolescence was predictive of diagnosed depression in adulthood, which suggests that Hale et al.’s findings may help to explain girls’ greater risk for depression.

Comorbidity Comorbidity is common for childhood anxiety disorders. In reviews of the epidemiological literature, Costello and Angold (1995) and Angold, Costello, and Erkanli (1999) report that many children meet criteria for multiple DSM anxiety diagnoses. Which anxiety disorders are most likely to co-occur is not yet clear, although some patterns are emerging. For example, Costello and colleagues found that phobic disorders were neither positively nor negatively associated with other anxiety disorders (Costello & Angold, 1995; Costello et al., 1988). Last et al. (1992) found evidence of extensive comorbidity, with most referred children in their sample meeting current or lifetime criteria for at least two anxiety disorders. In particular, children with OAD were most likely to show a pattern of comorbidity; almost 100% of these children met criteria for an additional current or past anxiety disorder. Masi and colleagues have reported evidence of extensive comorbidity of GAD with other anxiety disorders (Masi, Mucci, Favilla, Romano, & Poli, 1999; Masi et al., 2004). However, Last et al. (1992) and Masi et al. (2004) caution that their findings of extensive “overlap” among anxiety disorders may be a function of the referred nature of their sample; that is, it may be that having a history of multiple anxiety disorders is related to severity of disturbance and thus referral status. Depression is commonly comorbid with anxiety diagnoses, in both clinic (e.g., Strauss, Last, Hersen, & Kazdin, 1988; Masi et al., 1999, 2004) and nonclinic samples (e.g., Anderson et al., 1987; Kashani & Orvaschel, 1988). Anxiety and depression comorbidity is estimated to be from 20 to 75% among children (Kessler, Avenevoli, & Merikangas, 2001; Zahn-Waxler et al., 2000). Especially in adolescence, anxiety-depression comorbidity is more common than multiple anxiety diagnoses (Zahn-Waxler et al., 2000). Comorbidity may be higher in more severely disturbed samples (Bernstein & Borchardt, 1991; Kendall, Kortlander, Chansky, & Brady, 1992). Anxiety disorders have also been found to be comorbid with ADD (Anderson et al., 1987; Bird et al., 1988; Last, Strauss, & Francis, 1987; McClellan, Rubert, Reichler, & Sylvester, 1990; Strauss, Last, et al., 1988), bipolar disorder (Masi, Toni, et al., 2001) and oppositional disorder (Last et al., 1987; Masi et al., 1999) although these comorbidities are less common. Thus, evidence to date suggests that comorbidity is widespread, which complicates the identification of anxietyspecific risk factors, versus those that are general to other forms of child psychopathology.



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General Risk Factors A number of risk factors have been identified as putting children at risk for anxiety problems. It is unlikely that any one risk factor accounts for the development of anxiety; rather, anxiety likely is the end result of multiple pathways and interactions among causal influences. We begin here by examining demographic variables that have been identified as general risk factors and then follow with a presentation of biological, cognitive, affective, and social/ environmental processes that may leave children vulnerable to anxiety.

Demographics Age Age may not be particularly important as a risk factor. Although, as noted earlier, the prevalence of some anxiety disorders appears to decrease or increase with age, these changes are relatively modest and may be accounted for by different impairment thresholds (Roberts et al., 2007). The decrease of SAD with increasing age of the child is perhaps the most well documented (Costello & Angold, 1995; Bernstein & Borchardt, 1991); however, even this finding is inconsistent across studies, and the reasons for any age-related changes are unclear. Perhaps the most interesting age trend concerns the rarity of certain anxiety disorders (e.g., PD and AG) prior to adolescence. Changes associated with puberty may represent risk factors for the development of these disorders (Hayward et al., 1992; Last & Strauss, 1989). Bernstein and Borchardt (1991) have hypothesized that structural and neuroendocrine changes in the brain at puberty may account for changes in prevalence rates for some anxiety disorders, but as yet the nature of these changes and associated mechanisms have not been identified. Developmental changes in cognitions have also been implicated (see the section on “Cognitive and Affective Processes”).

Gender It has been generally accepted that girls have higher rates of anxiety disorders than boys (Zahn-Waxler et al., 2000), but gender differences generally diminish when considering the level of impairment (Roberts et al., 2007). In their earlier review of epidemiological studies of community samples, Costello and Angold (1995) reported little evidence of gender differences, with the exception of OAD, which appeared to be more common in girls. Several studies of clinical or high-risk samples have found relatively equal gender ratios across a variety of different anxiety disorders (Beidel & Turner, 1997; Masi et al., 1999; Last et al., 1992). However, other studies of referred and nonreferred children have found a higher prevalence of anxiety disorders

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in girls (Anderson et al., 1987; Prior et al., 2000; Silverman & Nelles, 1990). For example, Prior et al. (2000) found prevalence rates of 20.5% in girls and 12.9% in boys in a large community sample. Other studies found higher rates of anxiety-depression comorbidity among girls (Kessler et al., 2001; ZahnWaxler et al., 2000). Some studies have found equal prevalence across genders but differences in symptom expression or developmental progression (Flament et al., 1988, 1990; Swedo, Rapoport, Leonard, Lenane, & Cheslow, 1989). For example, Flament and colleagues (1988) found no gender differences in proportions of boys and girls diagnosed with OCD but reported that boys may have an earlier age of onset and suffer more severe symptoms. In sum, at present the most that can be stated is that gender may be a risk factor for the presence of some types of anxiety, with girls more at risk than boys.

Ethnicity Few studies have examined the relationship between ethnicity and anxiety in children; of the studies that exist, many have methodological shortcomings that make conclusions difficult. Most of the earlier studies considered only clinical samples and focused on Caucasian and African American children only; also, findings have been mixed (Beidel, Turner, & Trager, 1994; Kashani & Orvaschel, 1988; Last & Perrin, 1993; Last et al., 1987; Neal, Lilly, & Zakis, 1993; Perrin & Last, 1993; Strauss & Last, 1993), perhaps due to selection biases that affect results (Beidel et al., 1994). More recently, in a large sample (n = 3,812) of youth, ages 11–17, from a health maintenance organization, Caucasian youth were found to be at significantly less risk for anxiety than Mexican American and African American youth (Roberts & Roberts, 2007). However, after adjusting for SES, group differences became nonsignificant. In another large urban sample of low-SES adolescents, McLaughlin, Hilt, and Nolen-Hoeksema (2007) found separation anxiety to be most common among Hispanic adolescents, with Hispanic girls in particular experiencing the most symptoms. African American boys in this sample experienced greater separation anxiety than any other group (McLaughlin et al., 2007). This is consistent with a study by Pina and Silverman (2004) that found that Hispanic children had higher rates of SAD as compared to Caucasian children. Clearly, more research is needed on the role of ethnicity in childhood anxiety disorders. Also, given the potential confound, studies are needed that simultaneously consider ethnic and socioeconomic factors.

Socioeconomic Status Adverse socioeconomic conditions may put children at risk for certain anxiety disorders and also will likely influence who seeks treatment. Last et al. (1992) found that most of the clinic-referred children with anxiety disorders



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in their sample were from middle- to upper-middle-class backgrounds, with the exception of children diagnosed with SAD, who were more commonly from single-parent homes and of low SES. This is consistent with Beidel and Turner (1997), who found that children with anxiety or comorbid anxiety/ depression were from lower SES backgrounds than the comparison group, and with Velez, Johnson, and Cohen (1989) and Bird et al. (1988), who found that lower SES was a risk factor for development of SAD. Differences in anxiety disorder prevalence among Caucasian, African American, and Mexican American youth are diminished when controlling for SES, implying that social factors explain group disparities (Roberts & Roberts, 2007). Roberts et al. (2007) found that, although low-SES adolescents were more likely to develop an anxiety disorder, the discrepancy receded after adjusting for impairment. Although no clear conclusions can be drawn, there is at least some evidence that disadvantaged SES may put children at risk for anxiety.

Vulnerability Processes Biological Processes Temperament Kagan and colleagues (Kagan, 1989, 1994; Kagan, Reznick, & Snidman, 1988) defined the temperamental construct of “behavioral inhibition to the unfamiliar” (BI). BI is characterized by an initial reaction to encounters with unfamiliar stimuli that includes tension, withdrawal, inhibition, and seeking the comfort of a parent or caretaker. Developmentally, BI is expressed as irritability in infancy; shy, fearful behavior in early childhood; and cautious introversion in middle childhood (Pollock et al., 1995). BI is hypothesized to be a heritable trait. Findings from studies conducted by Kagan and colleagues on a sample of Caucasian children recruited through birth registries suggest that approximately 10–15% of these children can be classified as BI. In contrast, as many as 30% of these children may show an opposite profile, termed “behaviorally uninhibited” (BUI) and characterized by a sociable, minimally fearful approach to novel situations, people, and objects (Kagan, 1989, 1994; Kagan et al., 1988). Kagan’s research group followed two independent cohorts of infants from age 21 or 31 months who were categorized as either BI or BUI, based on their responses when exposed to unfamiliar rooms, people, or objects. A majority of children in both categories maintained their behavioral style from infancy to later assessments at 4, 5, 7.5, and 13 years, suggesting that the tendency to approach or withdraw from novelty is relatively stable (Kagan, 1989, 1994; Kagan et al., 1988; Kagan & Snidman, 1999; Schwartz, Snidman, & Kagan, 1999). Interestingly, when studying children not at the extreme on either of the two behavioral profiles, inhibition at 14 or 20 months

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did not predict differences in behavior at 4 years of age (Kagan, 1989). This suggests that the constructs of BI and BUI may refer to qualitatively distinct categories of children. BI has been hypothesized as a risk factor for the later development of anxiety disorders in children, especially SAD (Biederman et al., 2001; Hirshfeld-Becker et al., 2007; Hirshfeld-Becker, Micco, Henin, et al., 2008; Kagan & Snidman, 1999). Caspi, Henry, McGee, Moffitt, and Silva (1995), studying more than 800 children over a 12-year period, found that boys (but not girls) who were engaged in more “approach behavior” at ages 3 and 5 were less likely to be anxious in later childhood and adolescence but not to show other problems. For girls (but less so for boys), the tendency to withdraw from novelty at ages 3 and 5 was predictive of anxiety problems in adolescence. Biederman and colleagues (Biederman et al., 1990, 1993), following two independent samples of children, found that BI was associated with higher risk for anxiety disorders in children of parents both with and without psychiatric disorders. One sample was derived from Kagan’s cohort (described previously) and had been classified as BI or BUI; the other consisted of children of outpatient parents treated at Massachusetts General Hospital (MGH) for PD and AG who were classified as either BI or not inhibited (NI). At follow-up, BI children had significantly higher rates of multiple anxiety disorders, AD, and SAD (but not phobic disorders) as compared to children who were not BI. Also, the rates of anxiety disorders increased significantly from baseline to follow-up among the behaviorally inhibited children. Hirshfeld et al. (1992) classified children from Kagan’s sample according to the stability of their BI from infancy through young childhood, hypothesizing that children with more stable BI should be more vulnerable to anxiety disorders. At the 7.5-year follow-up, the stable BI children were significantly more likely than unstable BI children, as well as stable and unstable BUI children, to be diagnosed with any anxiety disorder, multiple (two or more) anxiety disorders, or phobic disorders. In a follow-up of the same children 12 years later, Schwartz et al. (1999) found that, of those whose temperament had remained stable, 61% of BI children experienced social anxiety, compared to 27% of BUI children. Other studies have found similar results, with consistent inhibition in childhood, rather than inhibition at any given time, being associated with higher risk for later anxiety disorders (Gladstone & Parker, 2005; Prior et al., 2000). An inhibited temperament is specifically hypothesized to influence SAD, and this has been supported by several studies (Biederman et al., 2001; Hirshfeld-Becker et al., 2007; Rosenbaum et al., 2000; Schwartz et al., 1999). The research on BI does not support the possibility that BI and anxiety disorders are simply variations on a theme. BI is an associated risk factor for—but does not determine—dysfunction. For example, approximately one-half to twothirds of inhibited children in studies do not develop anxiety disorders (e.g., Biederman et al., 1990; Prior et al., 2000; Schwartz et al., 1999). Indeed, BI is much more prevalent than anxiety disorders, suggesting that only a subgroup of inhibited children will develop disorders.



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Genetics Indirect evidence of a genetic contribution has been provided by findings that children of parents with anxiety disorders are at higher risk than children of parents without such disorders (see the later section on “Parent–Child Relationships” for a review of this literature), but of course such findings do not rule out environmental explanations of etiology. Family, twin, genetic linkage, and association studies more directly examine the role of genetics in childhood anxiety disorders. Unfortunately, only a small number of studies using these methods have been conducted. Much of the genetic literature relevant to children’s anxiety has focused on the transmission of a BI temperament. BI has been hypothesized to be an expression of a familial anxiety diathesis (Biederman, Rosenbaum, Chaloff, & Kagan, 1995; Merikangas, Avenevoli, Dierker, & Grillon, 1999; Smoller, Gardner-Schuster, & Covino, 2008; Zahn-Waxler et al., 2000). Studies of children with BI have found increased likelihood of anxiety disorders in their parents (Hirshfeld et al., 1992; Rosenbaum et al., 1991). Correspondingly, studies of parents with anxiety disorders have shown increased risk for BI in their children (Biederman et al., 2001; Rosenbaum et al., 1988). Interestingly, there is also evidence of an association between parental depression and BI (Hirshfeld-Becker et al., 2007; Rosenbaum et al., 2000). Twin studies have also demonstrated stronger BI concordance among monozygotic twins as compared to dizygotic twins, indicating a genetic influence for inhibition (Robinson, Kagan, Reznick, & Corley, 1992). Animal models have implicated specific genes that influence anxious temperament. Specifically, RGS2 (the regulator of G-protein signaling 2) has been shown to influence BI in mice (Smoller, Gardner-Schuster, et al., 2008) and humans (Smoller, Paulus, et al., 2008). Taken together, these findings suggest the possibility of genetic transmission of BI. Torgersen (1993) reviewed the role of genetic factors in the transmission of anxiety disorders and concluded that early evidence supported a genetic role for some disorders (e.g., PD) but not others (e.g., PTSD). Some family studies suggest that social anxiety, in particular, may be heritable (Ollendick & Hirshfeld-Becker, 2002). In a recent review, Smoller, Gardner-Schuster, et al. (2008) indicated that panic and phobic disorders may have a genetic basis. Six family studies were identified that indicate an increased risk of phobic disorders among relatives, particularly if onset occurs during the childhood or adolescence of first-degree relatives. In a prospective longitudinal study, Johnson, Cohen, Kasen, and Brook (2008) found that if both parents, rather than one, had a lifetime history of anxiety disorders, their offspring were significantly more likely to also develop an anxiety disorder. Twin studies have also indicated that anxiety disorders may be heritable (Smoller, Gardner-Schuster, et al., 2008). However, genetic linkage studies have failed to yield strong results unless phenotype definitions were expanded beyond DSM criteria, and association studies examining gene–phenotype cor-

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relations have been inconsistent. One potential explanation for the lack of findings is that sample sizes are typically small, and thus low statistical power limits detection of these small effects (Smoller, Gardner-Schuster, et al., 2008). It may be that genetic heritability is best understood as a predisposition to anxiety disorders in general rather than to a specific disorder (Turner, Beidel, & Costello, 1987). Eley and Stevenson (2000) found that, among 69 proband twin sets, 37 were disconcordant on anxiety diagnoses, 18 of which were monozygotic. Among both monozygotic and dizygotic twin pairs, threatening events affected each individual differently, suggesting that genetic predisposition is not necessarily a strong indicator of an eventual diagnosis. These findings suggest that general expression may result from genetic risk and specific expression may result from environmental exposure.

Neurobiology/Neuropsychology Little is understood about neurobiology of anxiety disorders (Smoller, Gardner-Schuster, et al., 2008). In an earlier review, Sallee and Greenawald (1995) described progress made in identifying possible neurobiological bases of childhood anxiety, noting that most of the progress to date derives from studies of adults. They argue that if childhood anxiety exists as a risk factor or prodromal condition for adult anxiety, then drawing conclusions from the adult literature may be warranted. However, because the relationship of child to adult anxiety is not well understood, as was pointed out earlier, it remains unclear how relevant studies of adults are to the understanding of children’s anxiety. A number of studies have attempted to explicate the neural structures and pathways underlying behavioral inhibition. Focus has been on the locus ceruleus/sympathetic system and the hypothalamic–pituitary–adrenal (HPA) axis. Studies have shown elevated cortisol levels in normal children under stress (Tennes, Downey, & Vernadakis, 1977; Tennes & Kreye, 1985), BI versus uninhibited children (Kagan et al., 1988), and children with anxiety disorders (Zahn-Waxler et al., 2000), suggesting that the HPA axis is at a high level of activity. Children with anxiety also have higher levels of resting cortisol and increased cortisol sensitivity (Zahn-Waxler et al., 2000). Interestingly, Nachmias, Gunnar, Mangelsdorf, Parritz, and Buss (1996) found that only insecurely attached BI children showed elevated cortisol change when exposed to novel stimuli; securely attached children responded in a manner similar to that of non-BI children. This finding underscores the importance of considering the interplay among psychosocial and biological variables. High-heart-rate and low-heart-rate variability have both been found to correlate with BI (Zahn-Waxler et al., 2000); also, heart rates of anxious children appear to habituate less to stress (Kagan et al., 1988). BI children’s consistent tendency to show cardiac acceleration in response to mild cognitive stress may suggest greater sympathetic influence on cardiovascular function. Rosenberg and Kagan (1987) and Kagan and Snidman (1999) have suggested



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that these differences may reflect lower reactivity thresholds in the limbic system, with the likely involvement of the amygdala and hypothalamus. Schwartz and Rauch (2004) also suggest that the amygdala may be partially responsible for the development of an anxiety disorder. In a sample of adults who had been classified as BI at age 2, fMRI scans indicated greater amygdala activation during exposure to pictures of novel faces. They also suggest that temperamental brain variation may remain stable through the lifespan. Hooper and March (1995) and Zahn-Waxler et al. (2000), in their reviews of the neuropsychology of childhood anxiety disorders, also note that there has been insufficient research on children. However, they describe several comprehensive and potentially important etiological models for anxiety that have been proposed. Zahn-Waxler et al. (2000) posit that abnormalities of the serotonin, noradrenaline, and GABA systems may be implicated in anxiety. Gray (1982) has hypothesized a separate subsystem in the brain for mediation of anxiety. This subsystem consists of two behavioral systems. The first mediates behavioral inhibition and is tied to the limbic system, with emphasis on the septohippocampal neural connections. The second mediates fight–flight responses; Gray has emphasized the roles of the amygdala, ventromedial hypothalamus, and midbrain central gray matter. Abnormalities in the septohippocampal and brain stem–hypothalamic circuits have also been confirmed, using fMRI (Zahn-Waxler et al., 2000). In another model, Tucker (1989) implicates the cognitive functional systems of the right hemisphere as providing control for perceptual arousal, and deemphasizes the role of the left hemisphere. This model proposes a complex interplay of several systems (including the cortex, subcortex, and neurotransmitters) in the regulation of arousal. Fox et al. (1996) have also implicated the activation of the right frontal lobe among inhibited children. Finally, Rourke’s (1989) nonverbal learning disability model hypothesizes that abnormalities in the white matter of the right hemisphere, in interaction with developmental experiences, produce a distinct pattern of learning disabilities. Associated with these difficulties are social, emotional, and behavioral deficits, including difficulties in adapting to novel situations and poor social interaction skills, which over time can put children at risk for internalizing problems (e.g., anxiety). However, experience and therapies during periods of rapid change, such as early childhood and adolescence, may impact neural plasticity, potentially reducing these deficits and possibly even BI (Zahn-Waxler et al., 2000). Further research is needed to understand the applicability of these models to childhood anxiety disorders.

Cognitive and Affective Processes Cognitive Developmental Changes The low prevalence of AVD and PD prior to adolescence may be explained by the development in adolescence of cognitive abilities necessary for the presence of the disorders. For example, Beidel and Morris (1995) have argued that the AVD’s later onset does not mean that social and performance anxiety

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are not experienced by preadolescents, and indeed there is evidence that shyness may be quite stable. They suggest instead that preadolescents “may lack the metacognitive and verbal skills to ground description of their fears in a social context” (Beidel & Morris, 1995, p. 187). Similar factors may explain why PD is rarely seen before adolescence (Bernstein & Borchardt, 1991; Black & Robbins, 1990; Craske, 1997; Ollendick, Mattis, & King, 1994). Barlow and colleagues (Chorpita, Albano, & Barlow, 1996; Nelles & Barlow, 1988) have suggested that prepubertal children may attribute panic symptoms to external events, because they lack sufficient abstract abilities to understand internal causation. Due to their concrete-operational level of cognitive development, these younger children are unable to associate internal sensations with abstract threat cognitions such as fears of going crazy. In contrast, adolescents may be able to make internal attributions necessary to experience spontaneous, uncued panic. Similarly, Vasey (1993) has argued that, as children age, the development of relevant cognitive structures, processes, and operations allows them to experience increasingly generalized anxiety. For example, the maladaptive cognitions that have been associated with anxiety may appear and/or change with age and cognitive developmental level. There have been surprisingly few studies that have directly tied the development of anxiety to cognitive development, however, with most studies only examining age as a correlate. Muris, Merckelbach, Meesters, and Van den Brand (2002) assessed the cognitive developmental level of children via Piagetian tasks and also interviewed them about personal worries and challenged them to identify negative outcomes associated with various topics. They found that the cognitive developmental level was associated with the ability to identify negative outcomes, which in turn was associated with personal worries. A recent longitudinal study specifically examined the development of language as a precursor to the development of SOC (Voci, Beitchman, Brownlie, & Wilson, 2006). Children identified as having impaired language at age 5 and a matched control sample of children with unimpaired language were followed prospectively to age 19. Children with language impairment were almost three times more likely to be diagnosed with SOC at age 19. Interestingly, maternal anxiety only predicted SOC among the control children, suggesting that language problems may be a particularly important pathway to SOC.

Emotion Regulation More recently, emotion regulation has been identified as potentially important to the development and maintenance of anxiety in children (Southam-Gerow & Kendall, 2002; Zahn-Waxler et al., 2000). Achievement of the ability to regulate emotional experience is an early developmental challenge, and dysfunctions and/or delays in the mastery of emotion regulation may be related to anxiety problems. Suveg and Zeman (2004) identified difficulties in emotion regulation in a small sample of children (ages 8 to 12) diagnosed with anxiety



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disorders, compared to normal controls. The anxious children reported more difficulties regulating and coping with distressing emotions, particularly with worry, and reported experiencing emotions more intensely. In another study of similar-aged nonreferred children by the same research group, the children who experienced more anxiety were less likely to be able to identify emotional states, more likely to rely on inhibition of emotions, and less likely to use adaptive means of regulation to manage their emotions (Zeman, Shipman, & Suveg, 2002). Some research supports the notion that parents may socialize children in (mal)adaptive emotional functioning. For example, children (ages 8–12) with anxiety disorders and their mothers were compared to nonclinical child–mother pairs on emotion interaction tasks that focused on situations in which the child felt worry, sadness, and anger (Suveg, Zeman, FlannerySchroeder, & Cassano, 2005). Mothers of anxious children discouraged discussion of emotions, conversed less with their child, and used fewer positive emotion words than mothers of nonanxious children.

Processing Bias Threat attention and interpretation biases have been shown to be associated with anxiety in children. Attentional bias occurs when threat or negative information receives greater allocation of attention. Problems can occur in the allocation of attention to distressing stimuli or in difficulties in regulating or shifting attention (for a review, see Lonigan, Vasey, Phillips, & Hazen, 2004). This phenomenon has been studied in adults and children, using probe detection and modified Stroop tasks (Dalgleish et al., 2003; Schippell, Vasey, Cravens-Brown, & Bretveld, 2003; Taghavi, Dalgleish, Moradi, Neshat-Doost, & Yule, 2003; Taghavi, Neshat-Doost, Moradi, Yule, & Dalgliesh, 1999; Vasey, Daleiden, Williams, & Brown, 1994). For example, Taghavi et al. (2003), using a modified Stroop paradigm to compare 19 children with GAD to nonanxious controls, found an interference effect specifically for threatrelated (versus depression-related) material. Dalgleish et al. (2003) compared clinically depressed or anxious (GAD or PTSD) children and adolescents to healthy controls on dot probe and modified Stroop measures of processing of both threat- and depression-related stimuli. Anxious children (in particular, the children with GAD) showed attention bias for the threat-related (but not the depression-related) stimuli, but only on the dot probe, underscoring the influence of the methodology, and raising questions about what is measured by dot probe versus Stroop tasks. A related construct, threat interpretation bias is the tendency to process ambiguous events as negative or threatening. This bias has been widely shown to be associated with anxiety in adults (for a review, see Mathews & MacLeod, 2005). Studies have suggested this association also applies to children (e.g., Barrett, Rapee, Dadds, & Ryan, 1996; Bögels, van Dongen, & Muris, 2003; Bögels & Zigterman, 2000; Creswell, Schniering, & Rapee, 2005; Muris, 2003; Muris, Jacques, & Mayer, 2004; Muris et al., 2000; Waters, Craske,

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Bergman, & Treanor, 2008; for a review, see Hadwin, Garner, & Perez-Olivas, 2006). For example, Waters et al. (2008) found that children diagnosed with an anxiety disorder made more threat interpretations of mildly threatening ambiguous stories than did children without anxiety disorders, or children who were considered at-risk for anxiety due to one of their parents being diagnosed with an anxiety disorder. Muris and colleagues (Muris, Merckelbach, Schepers, & Meesters, 2003; Muris, Rapee, Meesters, Schouten, & Geers, 2003) have described a Reduced Evidence for Danger (RED) bias in which anxious youth more quickly determine that stimuli are dangerous, relying sometimes on only minor cues. In their studies, anxious children needed to hear only a few sentences of a story before identifying it as threatening, significantly fewer sentences than less anxious children. Lonigan et al. (2004) posit that biased processing of threat-relevant stimuli may bridge temperament and the expression of anxiety problems. They focus on effortful control of attention, an ability not seen in very young infants but that, in the latter part of the first year of life, is associated with reduced distress in response to novel and/or aversive stimuli. In a series of studies, Lonigan and colleagues have shown that effortful control of attention forms a separate dimension from negative and positive affect and is uniquely predictive of anxiety. Also, they have found that effortful control may moderate the relationship between negative affect and biased processing of threat-relevant stimuli. Children high in negative affect but able to exert effortful control did not show a bias, while children also high in negative affect but low in effortful control did. Muris and colleagues have also demonstrated that low effortful control is associated with higher anxiety in nondiagnosed children and adolescents (Meesters, Muris, & van Rooijen, 2006; Muris, De Jong, & Engelen, 2004; Muris, Meesters, & Rompelberg, 2007).

Perceived Control Chorpita and Barlow (1998) have proposed a complex model that hypothesizes a pivotal role of control in the development of anxiety in children. Specifically, they propose a model in which early experiences with uncontrollable and/or unpredictable stimuli generate perceptions of low perceived control. These experiences lead to increases in the activity of the behavioral inhibition system (BIS), a functional brain system described by Gray (1982; Gray & McNaughton, 1996), and ultimately to the perceptual and somatic experiences described by Kagan and colleagues in their research on behavioral inhibition. As development proceeds and an individual accumulates a history of low-control experiences, cognitive schemas may become rigid and resist new information such as evidence of control; also, they may bias processing of later input. Chorpita and Barlow (1998) suggest that the long-term influence of perceptions of low control would be to intensify BIS activation, which would ultimately lead to the experience of generalized anxiety. Costanzo, Miller-Johnson, and Wencel (1995), in their review of social



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development and childhood anxiety, also suggested that low self-perceived control and self-efficacy in children may constitute risk factors for both anxiety and depression. They proposed a central etiological role of excessive caregiver control, suggesting that such control will undermine independence and intrinsic motivation in the child while increasing dependence on others for control and mastery. Ultimately, perceptions of personal control and self-efficacy fail to develop fully, and anxiety and depression will result as children encounter life situations for which they feel unprepared and helpless (for a further discussion of this issue, see the section on “Parent–Child Relationships”). Studies have found support for a relationship between low levels of perceived control and high levels of anxiety (Muris, Schouten, Meesters, & Gijsbers, 2003; Weems, Silverman, Rapee, & Pina, 2003) as well as for an inverse relationship between self-efficacy and anxiety (Matsuo & Arai, 1998; Muris, 2002; Yue, 1996). For example, in Muris’s study of a large sample of nondiagnosed adolescents, self-reported self-efficacy was concurrently related to anxiety symptoms, even when anxiety traits were controlled. Evidence was found supporting specificity: social self-efficacy correlated with SOC symptoms, emotional self-efficacy correlated with GAD and panic/somatic symptoms, and academic self-efficacy correlated with school phobia symptoms.

Negative Cognitions In addition to control, other cognitions may be relevant to children’s anxiety. Overall, studies have found that anxious children engage in more negative self-statements, more negative cognitive errors, and more off-task thoughts than do nonanxious children. For example, Zatz and Chassin (1983, 1985) found that highly test-anxious children endorsed more negative evaluations and off-task thoughts and less positive evaluations than did children who were less test-anxious. However, whether or not particular cognitions are specific to anxiety is unclear. Beck and colleagues have hypothesized that depression is characterized by cognitions that are more past-focused and concerned with perceived loss and failure, whereas anxiety is characterized by threat cognitions based on fear of future loss (e.g., Beck, Brown, Steer, Eidelson, & Riskind, 1987; Beck, Epstein, & Harrison, 1983). Unfortunately, only a few studies of cognitive content have used clinical samples or have compared anxious children to other relevant comparison groups, such as depressed children or normal controls. In one such study, Leitenberg, Yost, and Carroll-Wilson (1986) found that negative cognitive errors in children with evaluation anxiety were similar in type and frequency to those found in depressed children and children with low self-esteem. Similarly, Laurent and Stark (1993) found similar frequencies of anxious self-talk in anxious, anxious-depressed, and depressed children. In a study examining the ratios of positive to negative cognitions (statesof-mind [SOM] ratios), Treadwell and Kendall (1996) compared the negative

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self-statements of children (ages 8 to 13) with anxiety disorders versus those of normal controls. Negative self-statements were related to level of anxiety and, for children with anxiety disorders, response to a CBT intervention. However, both anxious and depressive self-talk were present at higher rates in anxious children than in normal controls, suggesting a more general negative affectivity rather than content-specific cognitions. Ronan and Kendall (1997) extended this study, examining SOM ratios and specificity of cognitions in anxious-only, depressed-only, mixed anxious-depressed, and normal children. Again, while distressed children’s SOM ratios suggested an emphasis on negative cognitions, relative to nondistressed children, there was limited support for content specificity of cognitions between anxious-only and depressed-only children. Ambrose and Rholes (1993), in a study of a nonclinical sample of 5th, 8th, and 11th graders, found some support for content specificity of loss versus threat cognitions, but only at lower levels of perceived threat; as perceptions of threat increased, so did the relationship of these cognitions to depression. Lerner et al. (1999) factor-analyzed data from children’s responses to the Negative Affect Self-Statement Questionnaire. All 306 children in the sample had been referred to an anxiety disorders clinic, and 252 met criteria for a primary diagnosis of an anxiety disorder. The factor analysis yielded distinct anxious and depressive factors as well as general negative and positive affect factors, consistent with Beck’s conceptualization and Clark and Watson’s (1991) tripartite model. There was stronger support for a specific relationship between depressive cognitive content and depression and less clear findings for cognitive content specific to anxiety. Most recently, in a study comparing anxious children and adolescents (GAD or PTSD) to depressed and healthy youth, Dalgleish et al. (2003) asked participants to estimate the probabilities of common negative events happening to themselves or to another child. The anxious children (both GAD and PTSD) judged negative events as more likely to happen to others, while the depressed children judged negative events as more likely to happen to themselves. In a longitudinal study of a large sample of New Zealand children (the Dunedin study), Craske, Poulton, Tsao, and Plotkin (2001) found evidence that youth’s personal or parental experiences with respiratory disturbance increased risk for PD at ages 18 or 21. Although these findings are consistent with the notion of a biological vulnerability, other research has not supported respiratory differences in adult PD patients. The authors suggest that the findings are consistent with a cognitive explanation, i.e., the children’s experience with respiratory problems may have led to a tendency to catastrophize about bodily sensations such as shortness of breath, resulting in panic. Overall, findings to date have provided somewhat mixed support for specific cognitions as a risk factor for anxiety. Additional studies making direct comparisons between anxious and nonanxious children in order to reveal common versus specific cognitive factors are needed. In addition, the relative absence of prospective studies makes it impossible to draw firm conclusions



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about the role of specific cognitions in the development of anxiety disorders in children.

Social Processes and Environmental Factors Parent–Child Relationships While Kagan and colleagues have emphasized temperament in the development of childhood anxiety disorders, others have pointed out that BI cannot be a complete explanation, because not all BI children share similar outcomes (Manassis & Bradley, 1994). It is essential to consider interactions between the child and the environment, and most efforts in this area have focused on interpersonal aspects of the parent–child relationship. Studies examining the quality of parent–child relationships as a risk factor for childhood anxiety have generally taken either a top-down or bottomup approach. In the bottom-up approach, studies have investigated whether psychopathology is present in parents of children with known anxiety disorders (Klein & Last, 1989). For example, Last, Hersen, Kazdin, Orvaschel, and Perrin (1991) compared mothers, fathers, and siblings of children with anxiety disorders to those of children with ADHD and normal controls. Relatives of anxious children showed a very high morbidity risk for anxiety disorders, compared to relatives of children in the other two groups, and this was particularly true for first-degree male relatives. Results of other bottomup studies that have examined psychopathology in parents of children with anxiety disorders are mixed in their support of parental disturbance as a risk factor for childhood anxiety (see Klein & Last, 1989, for a review). Although some studies have found that parents (primarily mothers have been studied) of children diagnosed with anxiety disorders are themselves more likely to meet criteria for anxiety disorders, other studies have not found this relationship or have provided mixed support. In contrast to the bottom-up approach, top-down studies have focused on children whose parents have anxiety (or other) disorders. An assumption of these studies is that the presence of psychopathology in parents can serve as a proxy for disturbance in parenting behavior and attachment relationships. Turner et al. (1987) found that children of anxious parents were seven times more likely than children of nondiagnosed parents to meet criteria for anxiety disorders and twice as likely to meet criteria as compared to children of dysthymic parents. More recently, in a large community sample, Schreier, Wittchen, Höfler, and Lieb (2008) found that children whose mothers had been diagnosed with anxiety disorders showed increased likelihood of developing any type of anxiety disorder, but only when mothers’ anxiety disorders were severe and of early onset and when two or more anxiety disorders were present. Also, presence of maternal SOC and GAD appeared to present the highest risk. A series of cross-sectional and prospective studies by Biederman and col-

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leagues (Biederman, Rosenbaum, Bolduc, Faraone, & Hirshfeld, 1991; Biederman, Petty, Faraone, et al., 2006; Biederman, Petty, Hirshfeld-Becker, et al., 2006; Biederman et al., 1991, 2001, 2005, 2007) has attempted to address this issue, examining children whose parents were diagnosed with either PD or major depression as compared to children of parents with neither disorder. Children of parents with PD were at increased risk for PD, but also for other anxiety disorders, including GAD, SAD, OCD, and AG. Comparison of children of anxious versus depressed parents suggested that risk appeared to be selective, in that parental PD increased the risk for children’s anxiety disorders and parental depression increased the risk for child depression and behavior disorders (Biederman, Petty, Hirshfeld-Becker, et al., 2006). There was even evidence supporting specificity within anxiety disorders. Although the presence of parental PD generally increased the risk of any anxiety disorder in the child, specific anxiety disorders in the parent predicted increased risk for that same disorder in the child for GAD, SOC, OCD, SAD, and simple phobia (Biederman, Petty, Faraone et al., 2006). Other studies have also found evidence supporting some degree of specificity. Beidel and Turner (1997) found that anxious parents were more likely to have children with anxiety disorders, in contrast to the children of depressed or depressed/anxious parents, who displayed a wider range of disturbance and more comorbidity. Wickramaratne and Weissman (1998) found that parental MDD was associated with increased risk of depression, anxiety, and conduct disorders in the children, but increased risk was highest for depression (10fold) and lower for conduct disorder (five-fold) and anxiety disorder (threefold), also supporting some degree of specificity. In their large community sample, Schreier et al. (2008) identified specific risk patterns in that maternal GAD was associated with increased risk for PD in children and PD in mothers was associated with an elevated risk for SAD in children. Taken together, these studies suggest that parental anxiety and/or depression are risk factors for childhood anxiety and may provide support for a genetic contribution; however, questions about the actual mechanisms of transmission remain unanswered. More recently, a great deal of attention has focused on parenting and the quality of the parent–child attachment. Two major reviews by Wood, McLeod, and colleagues (the more recent one a metaanalysis) provide comprehensive overviews of the research relating parenting to childhood anxiety (McLeod, Wood, & Weisz, 2007; Wood, McLeod, Sigman, Hwang, & Chu, 2003). In their first review, Wood et al. (2003) examined a decade of research linking parenting characteristics (i.e., parental acceptance, control, and modeling of anxious behaviors) to child anxiety. Parental acceptance refers to a parenting style “characterized by interactional warmth and responsiveness (including acceptance of children’s feelings and behaviors, active listening, praise, use of reflection, etc.) as well as emotional and behavioral involvement in children’s lives and activities” (pp. 134–135). A number of cross-sectional studies have examined parental acceptance, or lack of acceptance, generally



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conceptualized as criticism. Overall, findings linking acceptance to child anxiety are mixed. Observational studies that have coded parental acceptance behavior have been more likely to support an inverse relationship of acceptance to child anxiety, although the strongest findings have been for the relationship of explicit criticism to anxiety (Hudson & Rapee, 2001; Moore, Whaley, & Sigman, 2004; Sigueland, Kendall, & Steinberg, 1996; Whaley, Pinto, & Sigman, 1999). Hudson and Rapee (2001) found that mothers of anxious children were more negative than mothers of nondiagnosed children during interactions in which their child performed difficult cognitive tasks; however, they did not differ in negativity from mothers of oppositional defiant children. Interestingly, Ginsburg and colleagues (Ginsburg, Grover, Cord, & Ialongo, 2006) found that criticism varied by type of task. Both anxious and nonanxious mothers were more critical toward their children when participating in a structured task than when engaged in child-directed free play. Criticism was correlated across the two tasks only for the anxious mothers, who tended toward higher levels of criticism than nonanxious mothers. Ginsburg et al. (2006) suggest that attention to type of task used in observational studies may help to explain contradictory findings in the literature. Overcontrol by parents, in which autonomy is discouraged and reliance on parents is encouraged, may also put children at risk for anxiety disorders. In two studies by much the same research team, Whaley et al. (1999) and Moore et al. (2004) found that anxious mothers of anxious children exerted more control during interactions with their children than did anxious or nonanxious mothers of nonanxious children. Several other observational studies have found that parents of anxious children are likely to engage in overcontrolling behavior (Dumas, LaFremere, & Serketich, 1995; Hudson & Rapee, 2001; Mills & Rubin, 1998, Rubin, Cheah, & Fox, 2001; Wood, 2006). Ginsburg et al. (2006) found that parental overcontrol was greater in structured versus unstructured tasks, but, as with criticism, this finding applied to both anxious and nonanxious mothers. Interestingly, in a study that examined overcontrol in nonclinical children from different ethnic groups, Luis, Varela, and Moore (2008) found that overall control (conceptualized as frequent use of commands in family discussions) was associated with higher anxiety in children from European American families and Mexican families but not for children from Mexican American families. The authors suggest that parental commands may be more adaptive for children who are from an ethnic minority group, but not for children from the dominant majority group. Taken together, these findings underscore the potential complexity of the relationship between overcontrol and childhood anxiety. Another contributor to children’s anxiety may be modeling of anxious behaviors by parents. In a community sample of children (ages 7–18) and their parents, Drake and Kearney (2008) found that the relationship between parental psychopathology (essentially, mixed depression/anxiety) and child anxiety was mediated by family conflict /control and child anxiety sensitivity. They suggest that parents might communicate risk to their children or model

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anxiety-based reactions for anxious-sensitive children. Gerull and Rapee (2002) studied how parental modeling influenced fear responses and avoidance of rubber snakes and spiders in a small community sample of nonanxious toddlers. In this experimental manipulation, the children were shown the fearful stimuli in conjunction with either positive or negative maternal facial expressions; repeated presentations of stimuli were accompanied by neutral expressions. Toddlers showed the most anxious responses to stimuli if they had previously observed negative maternal facial expressions. McLeod et al.’s (2007) meta-analysis examining the association between parenting and childhood anxiety reviewed 47 cross-sectional studies from 1960 to 2002, all of which included measures of parenting behavior in addition to measures of child anxiety or established diagnosis in the child. From these studies, two patterns of parenting behavior were classified: rejection (withdrawal, aversiveness/hostility, and warmth) and control (overinvolvement and autonomy granting). Overall, the relationship between parenting and childhood anxiety was small, with parenting explaining only approximately 4% of the variance in childhood anxiety. Both rejection and control were associated with childhood anxiety, with a stronger relationship for control (and specifically for autonomy granting). Larger effects were found in methodologically stronger studies in which observers reported upon parenting, when parenting was measured with higher-quality techniques, and when diagnosed children were compared to nondiagnosed children. McLeod et al. concluded that their review provides support for a significant role of parenting in childhood anxiety—but that the role may be a very modest one. Finally, the quality of the parent–child attachment has been implicated as a possible influence on childhood anxiety (for a recent review, see Bögels & Brechman-Toussaint, 2006). Early experiences with caregivers are believed to influence children’s development of secure versus maladaptive attachment to caregivers, and ultimately to others as well. Two styles of anxious attachment were originally described (Ainsworth, Blehan, Waters, & Wall, 1978). The first, anxious-avoidant attachment, describes children whose attachment difficulties lead them to avoid relationships with others, while the second, anxious-ambivalent attachment, describes children who become overinvolved with relationships to reduce discomfort. A third type, disorganized attachment, has been added; this describes children who wish to have relationships with others but are mistrusting and lack organized strategies for forming attachments (Main & Solomon, 1990). There is insufficient research to date to permit firm conclusions about the importance of insecure attachment as a vulnerability factor for childhood anxiety. In a top-down study, Manassis, Bradley, Goldberg, Hood, and Swinson (1994, 1995) studied quality of attachment in mothers with anxiety disorders and their preschool children (ages 18 months to 5 years). They found that two-thirds of the children were classified as BI, based on Kagan’s assessment procedures, and 80% were insecurely attached. Other studies have examined whether attachment problems in children have been associated with current or



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later anxiety problems. Several studies have shown relationships between insecure attachment to the mother at around age 1 and later anxiety symptoms or disorders (Barnett, Schaafsma, Guzman, & Parker, 1991; Shaw, Keenan, Vondra, Delliquadri, & Giovannelli, 1997; Warren, Huston, Egeland, & Sroufe, 1997). Some evidence of specificity was found; insecure maternal attachment was associated with anxiety disorders in children, while dismissive maternal behavior was associated with children’s oppositional disorders (Crowell, O’Connor, Wollmers, Sprafkin, & Rao, 1991). In their review, Bögels and Brechman-Toussaint (2006) suggest that paternal attachment may also be influential, but they note that little is known about the relationship of paternal attachment to anxiety in children. Manassis and Bradley (1994) have proposed a model for vulnerability to anxiety disorders in children that integrates the constructs of temperament (specifically BI) and the quality of parent–child attachments. In their model, extremes of either BI or insecure attachment may constitute sufficient conditions for the development of certain forms of anxiety. However, they assert that an interaction between BI and insecure attachment would put children at greatest risk. Some research has offered support for their model; for example, Warren et al. (1997) found that BI children who are insecurely attached were more likely to develop anxiety disorders than BI children with secure attachments.

Life Events Stressful life events have been clearly implicated as a risk factor for anxiety disorders in adults (Monroe & Wade, 1988) but have been less studied in children. In his review, Muris (2006) concluded that research suggests that these events may also play an important role as risk factors for childhood anxiety. For example, Rapee and Szollos (2002), using maternal retrospective reports regarding children ages 7–16, found that anxious children were more likely than nonanxious children to have experienced severe stressors such as parental separation, violence, drug abuse, or death. This particularly characterized children with SAD. Boer et al. (2002) found that parents of children with anxiety disorders reported greater numbers of lifetime and prereferral year stressful events than did parents of healthy children. Interestingly, parents reported significantly more negative life events for their anxious children than for their nonreferred offspring. In a longitudinal study following children from low-income families from infancy through preschool, Shaw et al. (1997) found that negative life events (at 15 months) as well as exposure to parental conflict (at 24 months) were significant predictors of scores of mixed anxiety/depression at age 5. Interestingly, the interaction of parental conflict and ratings of “infant difficulty” was a significant predictor, suggesting that vulnerable children may be particularly at risk to stress and conflict. In another longitudinal study with a mainly African American sample, Grover, Ginsburg, and Iaolongo (2005) examined a number of stressors in first grade

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and found mixed results for predicting children’s anxiety levels in seventh grade. Academic difficulties and negative family environment were predictive of later anxiety symptoms, as was the total number of risk factors, but loss of a parent or other relative through separation or death and social adversity (e.g., parental unemployment, eviction) were not. Life events may constitute general risk factors for anxiety or may represent specific risk factors for certain types of anxiety and not others. In their Pittsburgh study, Costello et al. (1988) found that in adolescents stressful life events and ongoing adversity predicted a variety of anxiety disorders but not phobias. These findings suggest that environmental events may influence the development of some types of anxiety disorders more than others. Obviously, children’s experience of very traumatic life events puts them at high risk for a specific diagnosis of PTSD. However, some studies have shown that children meeting criteria for PTSD, or showing high levels of PTSD symptoms, also show increased likelihood for diagnosis with other anxiety disorders (Bolton, O’Ryan, Udwin, Boyle, & Yule, 2000; Carrion, Weems, Ray, & Reiss, 2002; Giaconia et al., 1995). Cortes et al. (2005) studied children who, at baseline, had experienced significant interpersonal trauma(s) during the preceding 6 months. Children who at baseline either met criteria for PTSD or showed higher levels of PTSD symptoms were more likely to develop a non-PTSD anxiety disorder 12–18 months later. This suggests that the experience of trauma put children at immediate risk for PTSD symptoms and at future risk for other anxiety disorders. There is also evidence that children with more anxiety report more stressful life events (e.g., Bernstein & Hoberman, 1989; Kashani & Orvaschel, 1990). More research is needed to fully understand the contribution of stressful life events to the development of anxiety in children. It is possible that stressful life events create a sense of lack of personal control, and, as described previously, low perceptions of control have been postulated to constitute a risk factor for anxiety disorders.

Implications for Prevention and Treatment Controlled empirical investigations of primary prevention efforts to decrease the incidence of anxiety disorders in children are scarce in the literature. However, a growing literature is addressing the efficacy and effectiveness of intervention efforts to ameliorate or diminish the impact of such disorders when they exist in children.

Prevention In reviews, Spence and Donovan (Donovan & Spence, 2000; Spence, 2001) have lamented the dearth of large-scale controlled studies of strategies or programs designed to prevent anxiety disorders in children, especially because



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the burgeoning research in risk factors for childhood anxiety has identified numerous targets for prevention efforts. No controlled studies of primary prevention programs for childhood anxiety can currently be found in the literature. Dadds, Spence, Holland, Barrett, and Laurens (1997), through their Queensland (Australia) Early Intervention and Prevention of Anxiety Project, have published results of what may be the only controlled trial of a secondary prevention program completed to date. Close to 2,000 nonreferred schoolchildren (7–14 years old) were screened for anxiety problems based on teacher report and self-report, resulting in a final sample of 128 children, approximately three-quarters of whom met criteria for at least one DSM-IV anxiety disorder. The children were then randomly assigned to a 10-week schoolbased group intervention based on Kendall’s (1990; Kendall, Kane, Howard, & Siqueland, 1990) CBT Coping Cat intervention, or to an assessment-only group. Parents of children in the intervention group also participated in group sessions, focusing on management of their child’s and their own anxiety. At posttreatment both groups had improved, but by 2-year follow-up the intervention group reported better outcomes such as parent and clinician ratings of change and percentage of children meeting criteria for an anxiety disorder (Dadds et al., 1999). Initial level of anxiety predicted both short- and longterm response to the intervention. Dadds et al. (1999) interpret their results as suggesting natural improvement over time in anxious children but that children who are initially more anxious are less likely to improve over both the short and long term.

Intervention The existing literature points to a variety of potential targets for intervention, including parenting behavior (especially overcontrol, modeling, acceptance, and attachment) and children’s cognitions and emotions (including processing bias, emotion regulation, perceptions of control, and negative thoughts/selfstatements). All of these have been targeted in interventions that have been developed and tested in recent years. The number of controlled trials of interventions for anxious children has expanded rapidly over the past two decades (see reviews by In-Albon & Schneider, 2007; Compton et al., 2004; McClellan & Werry, 2003). The recent meta-analytic review by In-Albon and Schneider (2007) identified two dozen psychotherapy studies as of 2005 that met basic CONSORT criteria. To be included, studies needed to have investigated the efficacy of a specific intervention for anxiety disorders in children against a control or alternative treatment, random assignment must have been used, and children had to have met diagnostic criteria for an anxiety disorder. Most of the studies examined interventions for children with a variety of anxiety disorders, although a few focused specifically on children with SOC. Almost all of the studies used exposure techniques, two-thirds used cognitive restructuring, half used relaxation, and one-third used positive self-talk; some interventions included

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family components. The overall effect size was 0.86 for treatment, versus 0.13 for controls. Follow-up data were available for most studies, with a few following participants over several years; these found continued evidence of treatment effect. There were no differences between group and individual therapy, or between individual child versus family therapy. Across all interventions, approximately two-thirds of children no longer met criteria for their presenting anxiety disorder after completing treatment. Interestingly, in two studies the control condition was psychoeducation, which was as efficacious as CBT; In-Albon and Schneider suggest that this finding is provocative and worthy of future investigation. A recent randomized controlled trial of parent bibliotherapy for children with anxiety disorders found evidence that it was more efficacious than no treatment although not as efficacious as an empirically supported CBT group treatment (Rapee, Abbott, & Lyneham, 2006). However, even with reduced impact, bibliotherapy may be more readily and cheaply available to anxious children and their families. Compton et al.’s (2004) comprehensive evidence-based review covered many of the same clinical trials as the In-Albon and Schneider (2007) metaanalysis, identifying 21 randomized clinical trials between 1990 and 2002 that investigated CBT interventions for child and adolescent anxiety. They also reported evidence of efficacy for CBT with maintenance over time. Research on pharmacological treatment for anxiety disorders in children has also expanded in recent years. Typically, medications found to be effective in the treatment of adult anxiety disorders are then tested on children in controlled studies. Medications that have attracted recent interest for treating children include tricyclic antidepressants (e.g., chlomipramine) and benzodiazepines (e.g., fluvoxamine, paroxetine). A recent review of the pharmacological management of childhood anxiety disorders by Reinblatt and Riddle (2007) concluded that there was support for the efficacy of SSRIs for pediatric anxiety and some support for tricyclic antidepressants (especially for pediatric OCD), although there are more questions than answers. There are still very few studies of medication efficacy for several of the specific anxiety disorders, and overall there are still few controlled trials, few large studies, and little short- or long-term follow-up. Safety issues also continue to be a concern (Jureidini et al., 2004). While it is useful to know that treatments of various types can help children with anxiety disorders, intervention research can also help to identify vulnerability factors if the mechanisms for the reduction in anxiety are identified and measured. Barrett, Dadds, and Rapee (1996), in a randomized clinical trial examining the importance of family involvement, compared CBT alone and CBT plus family anxiety management training to a waiting-list control condition. Subjects were 79 children, ages 7–14, who met diagnostic criteria for SAD, OAD, or SOC. The combination of CBT plus family therapy seemed to yield the greatest benefits; this was especially true for younger children. Unfortunately, the family intervention evaluated by Barrett, Dadds, et al. (1996) was multicomponent, and it is unclear which specific compo-



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nents were most important. Also, it is unclear whether the family focus of the intervention was essential; as Barrett, Dadds, et al. suggest, it is possible that the additional benefits found in the combined condition were simply due to any adjunctive treatment. In a follow-up study, Cobham, Dadds, and Spence (1998) narrowed the focus of their family intervention to a single component (parental anxiety management [PAM]) and compared child-focused CBT plus PAM to child-focused CBT alone. Further, they investigated whether differential response to treatment would be found in anxious children with at least one anxious parent versus anxious children whose parents were not anxious. They found that anxious children with nonanxious parents responded equally well to either treatment condition, but anxious children with anxious parents responded more positively to CBT plus PAM. On a related note, it is important to understand which treatments work, or work best, for which children. Unfortunately, moderators of treatment response are often not examined in studies. Southam-Gerow, Kendall, and Weersing (2001) examined correlates of treatment response in children with anxiety disorders receiving CBT. Focusing on children who received a complete course of treatment, they divided children into poor and good treatment response groups based on the presence/absence of an anxiety disorder at posttreatment and 1-year follow-up. Higher levels of internalizing symptoms at pretreatment predicted less favorable response to CBT, as did greater maternal depression and older age of child. Other variables such as parent–teacher reports of child externalizing symptoms, demographics, family structure, child reports of symptoms, and the child’s perception of the therapeutic relationship did not predict treatment response. Weersing and Weisz (2002) have argued that it is important to examine and identify mechanisms of action in therapeutic approaches, and they recently reviewed the psychotherapy outcomes literature for children and adolescents receiving treatment for anxiety, depression, and disruptive behavior. Of clinical trials finding empirical support for the efficacy of treatments for anxiety disorders, many failed to assess possible mediators; when mediators were evaluated, they tended to be measured at posttreatment, using similar methods to those used to evaluate the outcomes. Increased attention to the identification and timely assessment of potential mediators of treatment response, as well as explicit analysis of mediational effects, would help to identify key mechanisms of change.

Future Directions for Research on Vulnerability Sound epidemiological data are needed on both referred and nonreferred children. The profound changes in the classification of childhood anxiety as represented by DSM-IV necessitate a new wave of studies of prevalence and incidence rates of these disorders in children. Fortunately, Kendall and Warman’s (1996) study of diagnostic consistency between DSM-III-R and DSM-

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IV found a high level of agreement for referred children diagnosed under both systems, suggesting that generalizations from past research can continue to be made. However, many studies of anxiety symptoms in nonreferred children are decades old and should be updated, using improved assessment technologies available today. An up-to-date, comprehensive, and detailed picture of the presence and natural history of anxiety in nonreferred children will serve as the cornerstone for efforts to more fully understand clinically relevant deviations and disturbances in anxiety during childhood. It is important to continue to improve methodologies employed in studies of childhood anxiety. Studies must include children at a variety of ages, of both genders, and from different cultural backgrounds. To date, most studies have included samples that are predominantly Caucasian. The demographic characteristics of samples should be carefully measured, described, and considered. Also, anxiety parameters need to be carefully assessed and described. Children have been identified as anxious based on meeting full DSM criteria for a particular disorder and based on the self-reported presence of a single symptom of anxiety. It is likely that there is no single “best” approach to identifying anxiety in children; rather, different assessment approaches are needed for different purposes. For investigations and trials intending to target children who have an identifiable anxiety disorder, well-validated structured interviews, updated to reflect DSM-IV criteria, should be employed. The practice of grouping children with different anxiety disorders together is generally ill advised because the literature suggests that vulnerability factors and effective intervention agents differ among disorders and these distinctions might be obfuscated. For studies concerned with subclinical anxiety, myriad ways exist to assess symptoms of anxiety, ranging from self-report to teacher nomination to objective evaluation. Multi-modal assessment, using the most psychometrically sound and well-established instruments and approaches, is essential to the identification and quantification of symptoms and syndromes of anxiety in children. In addition, the identification of specific vulnerability processes contributing to the origination and/or maintenance of childhood anxiety disorders is essential to the development of efficacious prevention and intervention approaches. Recent prospective studies are a welcome addition to the literature, and more are needed. Large-scale longitudinal investigations should follow children identified as “at risk” for anxiety disorders, based on biological, cognitive, and/or social vulnerabilities suggested, theoretically or empirically, in the current literature. Comparison groups of non-“at-risk” children should be included. Descriptive studies are an important first step in identifying vulnerability factors, but cross-sectional and retrospective studies cannot reveal information on cause–effect relationships, which is necessary for understanding the etiology and maintenance of anxiety disorders as well as prevention and intervention efforts. Finally, as noted previously, controlled clinical trials of both prevention and intervention approaches are essential. In addition to establishing the



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most efficacious approaches, controlled investigations systematically manipulate vulnerability factors identified through descriptive research. Though not definitive, studies reporting positive outcomes provide further evidence for the importance of the targeted variables. In-Albon and Schneider (2007) have noted the importance of examining prevention and intervention efforts for specific anxiety disorders because to date much of the treatment research has included mixed samples. Also, research is needed with very young children, given evidence that anxiety problems begin very early. Hirshfeld-Becker, Masek, et al. (2008) recently reported success with a manualized CBT intervention piloted in a small sample of families with children ages 4–7, each with multiple risk factors for developing anxiety disorders and most of whom already displayed evidence of anxiety. These findings offer encouragement that early intervention may prove effective in resolving, reducing, or even preventing anxiety problems in childhood.

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Chapter 12

Vulnerability to Anxiety Disorders in Adulthood Hannah E. Reese, Sadia Najmi, and Richard J. McNally

Most clinicians believe that people vary in their proneness for developing anxiety disorders. Certain psychobiological characteristics presumably render some individuals more likely than others to fall ill. Despite widespread endorsement of such bromidic assumptions, knowledge about vulnerability is still relatively scarce. There are several reasons for this. First, the base rate for many risk factors is so high relative to disorder prevalence that their presence is not especially informative. For example, being female is associated with increased risk—relative to being male—for panic disorder. Because few women develop panic disorder, however, knowing that someone is female affords little in the way of predictive power. Second, many risk factors only indirectly reflect the causal processes underlying disorder emergence. Because not all statistical risk factors are causal vulnerability factors, identifying what predicts the development of a disorder need not reveal what causes it (Ingram & Price, Chapter 1, this volume). Predicting disorder emergence does not necessarily mean that the predictor variable participates in the causal chain. Firm inferences about causation require experimental manipulation of the putative vulnerability factor. For obvious reasons, this type of manipulation is generally neither feasible nor ethical. Prospective longitudinal studies may be the best we can do with regard to identifying vulnerabilities. Unfortunately, conducting prospective longitudinal studies is both expensive and difficult. One must have some sense about what populations are at risk and some sense about what variables ought to be measured over time. These limitations notwithstanding, researchers at least have some clues about the factors that render people prone to developing pathological anxiety.

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The purpose of this chapter is to review what is known about vulnerability for developing anxiety disorders in adulthood. Restricting coverage to adulthood eliminated from consideration several syndromes that usually emerge in childhood and adolescence. For example, most specific phobias have their origins in childhood (Öst, 1987), and social phobia rarely begins after adolescence (Rapee, 1995). Likewise, many people who suffer from generalized anxiety disorder claim that they have been anxious throughout their entire life (Rapee, 1991). Accordingly, these disorders are discussed elsewhere in this volume. Panic disorder, posttraumatic stress disorder (PTSD), and obsessive– compulsive disorder (OCD) are the foci of this chapter. Panic disorder rarely begins before puberty, PTSD can occur at any age, and many people develop OCD in adulthood.

Historical Prologue Clinicians have long speculated about vulnerability factors for what are now called panic disorder, OCD, and PTSD. Although two-factor learning theorists emphasized Pavlovian and instrumental conditioning episodes as etiologically significant events, they also assumed that not all people were equally conditionable (Eysenck & Rachman, 1965). Eysenck and Rachman (1965) cited laboratory studies showing that individuals scoring high on self-reported measures of introversion developed more robust and reliable conditioned eyeblink responses to air puffs than did those scoring high on measures of extraversion. Extrapolating from these experiments, they assumed that neurotic problems would be acquired as easily as conditioned responses in the laboratory. They also hypothesized that people scoring high on questionnaires of neuroticism were characterized by a labile autonomic nervous system that enhanced susceptibility for developing anxiety problems. Behavior theorists, such as Eysenck and Rachman, were disinclined to interpret these problems in terms of risk for specific syndromes; they favored a dimensional approach wherein people scoring high on introversion and neuroticism were rendered vulnerable to develop a range of conditioned anxiety reactions (e.g., fears, obsessions, and panic). The notion that there might be risk factors for specific nosological entities was not part of this framework. Yet, ever since DSM-III, researchers have increasingly studied risk for specific disorders.

Panic Disorder and Agoraphobia A panic attack is characterized by the sudden onset of intense fear accompanied by physiological symptoms and thoughts that one is about to die, go crazy, or lose self-control. Common symptoms include rapid heart rate, difficulty breathing, dizziness, and trembling. Classic unexpected panic attacks seem to emerge “out of the blue,” triggered by no obvious precipitant. Although

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panic attacks rarely last for more than a few minutes, people can develop disabling dread of their recurrence. Individuals who experience repeated unexpected attacks and report at least 1 month of persistent concern about their recurrence qualify for a diagnosis of panic disorder. They may begin to avoid activities and situations in which panic attacks would be especially unwelcome (e.g., driving a car, shopping). If avoidance becomes widespread, panic disorder with agoraphobia is diagnosed. According to the National Comorbidity Survey Replication (NCS-R), 28.3% of adults have experienced a panic attack at some point in their lives, and the lifetime prevalence rate of panic disorder and panic disorder with agoraphobia are 3.7 and 1.1%, respectively (Kessler et al., 2006). Women are about twice as likely as men to have panic disorder. The diagnosis of panic disorder jointly requires recurrent unexpected attacks and persistent dread of their recurrence. Therefore, vulnerability for panic may consist of proneness to experience eruptions of intense physiological sensations, a fear of these sensations, or both.

Anxiety Sensitivity One psychological variable that has received considerable attention as a possible vulnerability factor for panic disorder is anxiety sensitivity. Anxiety sensitivity refers to fears of anxiety symptoms that are based on beliefs about their possible harmfulness (Reiss & McNally, 1985). Thus, a person with high anxiety sensitivity may fear that heart palpitations signify an impending heart attack, whereas a person with low anxiety sensitivity is likely to regard these sensations as merely unpleasant. Thus, just as people vary in their proneness to experience anxiety symptoms (i.e., trait anxiety), so do they vary in their proneness to react fearfully to these symptoms (i.e., anxiety sensitivity). People with high anxiety sensitivity are likely to report episodes of anticipatory anxiety about the possible recurrence of panic attacks. Several lines of evidence point to anxiety sensitivity as a vulnerability factor for panic disorder. Patients with panic disorder score higher than do either those with other anxiety disorders or no disorder on the Anxiety Sensitivity Index (ASI), a 16-item self-report measure tapping concerns about anxiety symptoms (McNally & Lorenz, 1987; Reiss, Peterson, Gursky, & McNally, 1986; Taylor, Koch, & McNally, 1992). Moreover, elevated ASI scores have been observed in individuals who have never experienced a panic attack (Asmundson & Norton, 1993; Cox, Endler, Norton, & Swinson, 1991; Donnell & McNally, 1990), suggesting that concerns about the harmful implications of anxiety symptoms can emerge prior to the eruption of panic attacks. Also relevant to determining anxiety sensitivity’s status as a vulnerability factor are biological challenge studies involving provocation of feared sensations in people varying in levels of anxiety sensitivity. Rapee, Brown, Antony, and Barlow (1992) found that the ASI was the only significant predictor of fear triggered by either inhalation of 5.5% carbon dioxide or voluntary hyper-



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ventilation in patients with a range of anxiety disorders. If anxiety sensitivity is crucial for challenge-induced anxiety and panic, then psychiatrically healthy people who score high on the ASI should respond like panic patients to challenges that provoke intense bodily sensations. Indeed, several studies have found this to be the case. Individuals who score high on the ASI report more intense physical symptoms and more subjective anxiety in response to hyperventilation than individuals with low anxiety sensitivity (Holloway & McNally, 1987). Similar findings have been reported with carbon dioxide (Eke & McNally, 1996; McNally & Eke, 1996) and caffeine challenge (Telch, Silverman, & Schmidt, 1996). Moreover, ASI is a better predictor of response to challenge than is a history of spontaneous panic (Donnell & McNally, 1989) and general trait anxiety (Carter, Suchday, & Gore, 2001; Eke & McNally, 1996; Rapee & Medoro, 1994). That is, knowing that someone has a specific tendency to fear bodily sensations is more valuable in predicting his or her response to challenge than is knowing that he or she has a general proneness to experience anxiety (McNally, 1989). To truly test the claim that anxiety sensitivity is a vulnerability factor for panic attacks, however, prospective longitudinal studies are necessary. In an early study, Maller and Reiss (1992) interviewed college graduates who had scored either high (n = 23) or low (n = 25) on the ASI 3 years previously. Three of the four participants who experienced panic attacks for the first time during the follow-up period were from the high-ASI group. Subsequent prospective studies have provided results consistent with those of Maller and Reiss (1992). The German translation of the ASI predicted the emergence of spontaneous panic among a group of nonclinical participants and patients with simple phobias in a 1-year follow-up study, whereas a measure of trait anxiety did not (Ehlers, 1995). In another study, four of six students who experienced spontaneous panic during the year following their participation in a challenge experiment had preexisting high ASI scores (Harrington, Schmidt, & Telch, 1996). In a landmark study in psychopathology, Schmidt, Lerew, and Jackson (1997) assessed more than 1,000 cadets at the U.S. Air Force Academy before and after their highly stressful 5-week basic training program. Approximately 6% (n = 74) of the cadets reported a spontaneous panic during basic training, and of these cases 34 had never experienced panic before. Schmidt et al. (1997) found that the ASI predicted panic even after controlling for trait anxiety and history of panic. Those individuals who scored in the upper quartile of the ASI were twice as likely to experience a panic attack during basic training than were all other subjects. This same research team replicated these findings in another cohort of 1,000 cadets (Schmidt, Lerew, & Jackson, 1999). Plehn and Peterson (2002) also observed a relationship between anxiety sensitivity and panic in the longest prospective study to date. At time 1, 505 undergraduates were assessed for anxiety sensitivity, trait anxiety, and history of panic attacks and panic symptoms. Eleven years later, 178 of the original cohort were able to be recontacted. ASI scores at time 1 significantly predicted panic symptoms

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and panic attacks at time 2 even after Plehn and Peterson controlled for trait anxiety and history of panic. Collectively, these studies suggest that anxiety sensitivity is a vulnerability factor for the development of spontaneous panic attacks. It is less clear, however, whether elevated ASI scores predict the development of panic disorder as well. The results from Plehn and Peterson (2002) would suggest that it does not. Although ASI score did predict later panic attacks and panic symptoms, it did not predict later panic disorder. Trait anxiety was the only significant predictor of panic disorder at time 2. In another 2-year prospective longitudinal study of 404 young adults (Schmidt, Zvolensky, & Maner, 2006), baseline anxiety sensitivity predicted the emergence of panic attacks at follow-up but not panic disorder specifically. Rather, elevated ASI scores predicted the onset of a broad range of Axis I diagnoses including alcohol abuse/dependence, social anxiety disorder, panic disorder, major depressive disorder, generalized anxiety disorder, and specific phobia, suggesting that anxiety sensitivity may be a more general risk factor and not specific to panic disorder. A subsequent 2-year prospective study by Schmidt and Zvolensky (2007) demonstrated that anxiety sensitivity at baseline interacted with the degree of anxiety experienced during CO2 challenge at baseline to predict the onset of panic attacks 2 years later. Those individuals with high ASI scores and high challenge-induced anxiety at time 1 were at the greatest risk of experiencing panic attacks by time 2. However, only anxiety sensitivity significantly predicted the emergence of panic disorder and other anxiety disorders at time 2. Unfortunately, the authors did not present data on the incidence of any other Axis I disorders in this study, thus preventing us from making any conclusions about specificity. In summary, there is substantial evidence to suggest that anxiety sensitivity is a vulnerability factor for the emergence of spontaneous panic attacks. Whether anxiety sensitivity also predicts the later onset of panic disorder specifically or rather is a more general risk factor remains to be seen. Evidence from two cross-sectional studies suggests that anxiety sensitivity may be a unique vulnerability factor to the development of anxiety disorders rather than depression after one controls for the influence of higher-order variables such as neuroticism (McWilliams, Becker, Margraf, Clara, & Vriends, 2007), extraversion, and anxious arousal (Cox, Enns, Walker, Kjernisted, & Pidlubny, 2001). Future prospective studies should include a broader range of measures to allow for examination of this possibility.

Information-Processing Biases In addition to studying aberrant cognition via self-report questionnaires, such as the ASI, researchers have applied the methods of cognitive psychology to elucidate information-processing abnormalities in panic and other anxiety disorders (McNally, 1994, pp. 123–136; McNally, 1996; Williams, Watts,



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MacLeod, & Mathews, 1997). Most experiments identifying attentional, memory, and interpretive biases favoring the processing of threatening information in panic have been done in people who already meet criteria for the disorder (McNally, 1999). Thus, it is impossible to determine from these studies whether any observed biases predated the onset of the disorder and so may have contributed to the development of the disorder or rather are a consequence of the disorder itself. To address this issue, researchers have examined whether individuals at risk for panic disorder by virtue of having elevated anxiety sensitivity exhibit such biases. Overall, the results are mixed. One initial study did observe an attentional bias for threat among nonclinical subjects scoring high on the ASI (Stewart, Conrod, Gignac, & Phil, 1998). However, two subsequent studies failed to observe an attentional bias for threat on the emotional Stroop paradigm among individuals with elevated anxiety sensitivity (McNally, Hornig, Hoffman, & Han, 1999; Teachman, 2005). Additionally, many of Stewart et al.’s (1998) high-ASI subjects had experienced panic attacks before, and therefore it is unclear whether they would have obtained similar results with high-ASI subjects with no experience of panic. The results with regard to interpretive and memory biases are also mixed. Richards, Austin, and Alvarenga (2001) observed a relationship between anxiety sensitivity and a bias for threatening interpretations of internal cues among nonpanic controls, while McNally et al. (1999) observed that ASI scores predicted a bias for threatening interpretations of external but not internal cues. Teachman (2005) did observe an association between anxiety sensitivity and interpretive bias as measured by the Brief Body Sensations Interpretation Questionnaire (BBSIQ; Clark et al., 1997). High-ASI subjects endorsed more threatening interpretations of both internal and external cues relative to the low-ASI subjects. Within the high-ASI group, however, the bias was significantly more pronounced for external stimuli. McCabe (1999) observed an explicit memory bias for general threat words but not anxiety words. No implicit memory bias was observed. McNally et al. (1999) found no evidence for a memory bias for threatening stimuli. Teachman (2005) administered the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) to assess the strength of panic-related associations in memory. Relative to the low-ASI group, high-ASI subjects did demonstrate significantly stronger automatic associations in memory between the terms “self” and “panic.” However, both groups demonstrated stronger associations between the terms “self” and “calm” relative to “panic,” indicating that both groups more strongly associated themselves with being calm than panicked. Taken together, the evidence to suggest that information-processing biases characteristic of panic disorder exist prior to the onset of panic attacks and panic disorder is unconvincing. Evidence is perhaps strongest to suggest that interpretive biases may predate the emergence of panic. Future work and, in particular, prospective longitudinal studies are necessary to clarify whether such biases actually predict the emergence of panic attacks

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and panic disorder. Of particular relevance to this question is work examining the effect of experimentally modifying attentional and interpretive biases for threat among nonclinical participants (e.g. Mathews & MacLeod, 2002). Although this work has not focused on panic disorder per se, it may clarify the causal role of threat-related information-processing biases across the anxiety disorders.

Smoking A growing literature suggests that cigarette smoking may be a vulnerability factor for the development of panic attacks and panic disorder (for reviews see Zvolensky & Bernstein, 2005; Zvolensky, Feldner, Leen-Feldner, & McLeish, 2005). Zvolensky and Bernstein (2005) report that, relative to individuals with other psychiatric disorders and healthy controls, the rate of daily smoking among individuals with panic disorder is generally elevated. Approximately 40% of individuals who have been diagnosed with a panic-spectrum disorder smoke on a daily basis (Zvolensky et al., 2005). Conversely, approximately 5% of smokers report panic-related problems, compared to 2% of nonsmokers. To date, three large prospective studies have been conducted that allow for the examination of the relationship between smoking and vulnerability to panic attacks and panic disorder. In an analysis of the Epidemiologic Study of Young Adults, Breslau and Klein (1999) found evidence to suggest that daily smoking was associated with an increased risk for later developing panic disorder. Specifically, after controlling for gender and major depression, individuals who smoked had a nearly four times greater risk of developing panic disorder than nonsmokers. The converse relationship was not supported, however: individuals with prior panic attacks or panic disorder were not at an increased risk for initiating smoking. Similarly, Johnson et al. (2000) found an increased risk for panic disorder among individuals who smoked more than 20 cigarettes per day, as compared to nonsmokers, in a sample of 688 young adults. Again, panic did not increase the risk for smoking. The third prospective study also observed that dependent regular smokers were significantly more likely to have developed panic disorder 2 years later than were nonsmokers. However, this effect disappeared once the authors controlled for baseline comorbid psychopathology (Isensee, Wittchen, Stein, Höfler, & Lieb, 2003). In summary, there is a small but consistent literature suggesting that smoking may render individuals more vulnerable to later developing panic attacks or panic disorder. However, as Zvolensky et al. (2005) discuss, a number of interesting questions remain. Future work hopefully will focus on teasing apart the effect of cigarette smoking from other potentially relevant variables such as comorbid substance or alcohol use and medical illness. Additionally, experimental work may help elucidate causal mechanisms that could mediate a relationship between smoking and panic vulnerability.



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Genetics Several lines of evidence suggest a genetic vulnerability for panic disorder. In a review and meta-analysis of this literature, Hettema, Neale, and Kendler (2001) cite five studies indicating that panic disorder runs in families (Fyer et al., 1996; Horwath et al., 1995; Maier, Lichtermann, Minges, Oehrlein, & Franke, 1993; Mendlewicz, Papdimitriou, & Wilmotte, 1993; Noyes et al., 1986) First-degree relatives of a proband with panic disorder are approximately five times more likely to develop the disorder than are first-degree relatives of healthy probands (Hettema et al., 2001). Twin studies provide further evidence of genetic influence in the development of panic disorder. By directly comparing the concordance rates for panic disorder in monozygotic twins, who share 100% of their genes, to concordance rates in dyzygotic twins, who share 50% of their genes, investigators can approximate the relative contributions of genes and environment to the expression of the disorder. Hettema and colleagues (2001) cite five twin studies (Kendler, Neale, Kessler, Heath, & Eaves, 1993; Perna, Caldirola, Arancio, & Bellodi, 1997; Scherrer et al., 2000; Skre, Onstad, Torgersen, Lygren, & Kringlen, 1993; Torgersen, 1983), three of which met the authors’ criteria for inclusion in the meta-analysis (Kendler et al., 1993; Perna et al., 1997; Scherrer et al., 2000). In every study, concordance rates were elevated among monzygotic twins relative to dizygotic twins. When the authors combined the family and twin studies to perform structural equation modeling, the model of best fit revealed that variance in panic disorder liability could be best accounted by additive genetic factors and nonshared environmental factors (i.e., specific environmental events experienced by one twin but not by his or her co-twin). Genetic factors accounted for approximately 48% of the variance in panic disorder liability. Given the evidence to support a genetic contribution to the development of panic disorder, investigators have turned their attention to identifying the specific genes that put individuals at risk (for a review, see Gratacos et al., 2007). One approach has been to focus on genes that influence various neurotransmitter systems (e.g., serotonergic, dopaminergic, noradrenergic systems). Although some promising results have been reported (e.g., Maron et al., 2005), there have also been many failures to replicate. Thus, no consistent findings have emerged from the literature. As evinced by the sheer number of studies cited by Gratacos and colleagues (2007), the search for candidate genes that play a role in the development of panic and other anxiety disorders is a tremendously active area of research. With new advances in technology and a better understanding of the neural substrates underlying the development of panic attacks and panic disorder, our search should become more focused and consistent findings may emerge. In summary, there is strong evidence to support a role for genes in the development of panic disorder. Future work will hopefully identify the specific

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genes that render an individual more vulnerable to developing panic attacks and panic disorder.

Summary Research on vulnerability for panic disorder suggests several conclusions. First, studies on anxiety sensitivity implicate fear of bodily sensations as a risk factor for panic attacks and perhaps panic disorder, although the specificity of this latter point remains to be determined. Evidence for information-processing biases as vulnerability factors for panic is minimal and inconclusive. Existing data suggest that smoking may prove to be a vulnerability factor for panic disorder, although more research clearly is needed. And finally, there is strong evidence that panic disorder is heritable, although the specific genes that contribute to an increased risk for panic are unknown.

Posttraumatic Stress Disorder PTSD was recognized as a formal diagnosis in DSM-III (American Psychiatric Association, 1980). Its characteristic symptoms comprise reexperiencing the traumatic event (rather than merely remembering it) in the form of nightmares, intrusive thoughts, and physiological reaction to reminders of the trauma. PTSD sufferers report avoidance of stimuli associated with the event and also emotional numbing. Additionally they experience symptoms of hyperarousal, such as enhanced startle, irritability, and sleep disturbance. For many years, researchers were extremely wary of studying risk factors for PTSD. Psychiatric advocates for Vietnam veterans claimed that PTSD was caused by war and that investigating vulnerability for PTSD amounted to blaming the victim for his plight (e.g., Blank, 1985). Yet, as Shephard (2004) observed, once the disorder was firmly ensconced in the DSM, it became politically safer to ask why only a minority of people exposed to trauma developed PTSD (e.g., Breslau, Davis, Andreski, & Peterson, 1991). Indeed, much work solely concerning risk factors for PTSD has since appeared (Yehuda, 1999). Epidemiologic studies continue to confirm that only a minority of people exposed to trauma develop the illness. Although some studies show that nearly 90% of Americans are exposed to at least one trauma in their lives (Breslau & Kessler, 2001), the most recent general population survey revealed a lifetime prevalence rate for PTSD of 6.8% (9.7% in women and 3.6% in men) in the United States (Kessler, Berglund, et al., 2005; www.hcp.med.harvard.edu/ncs/ftpdir/table_ncsr_by_gender_and_age.pdf). The wars in Iraq and Afghanistan have yielded similar data. PTSD estimates of those exposed to combat indicate that about 8% have developed PTSD (Smith et al., 2008). The rates of PTSD among those serving in a noncombat capacity and among those deployed elsewhere were approximately 2 and 2.5%, respectively. Traumatologists often say that exposure to trauma is the most important



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risk factor for PTSD. But this claim is confused. Trauma is not a risk factor for PTSD but, rather, a necessary precondition. More precisely, the victim encodes a memory of the trauma, and in some cases the memory becomes pathogenic, thereby mediating the emergence of PTSD symptoms (McNally, 2003; Rubin, Berntsen, & Bohni, 2008; Young, 1995). Certain events, however, are more likely than others to result in these pathogenic memories. For example, in one epidemiologic study, 1.6% of the women had been raped at some point in their lives, and among these rape victims 80% developed PTSD (Breslau et al., 1991). In fact, assaultive violence (e.g., rape, being badly beaten) tends to produce PTSD in a larger proportion of victims than do other kinds of potentially traumatic events such as serious car accidents (e.g., Breslau, Chilcoat, Kessler, Peterson, & Lucia, 1999). Studying risk factors for PTSD differs from studying risk factors for other anxiety disorders. One can investigate the variables that increase a person’s risk for exposure to trauma and, separately, those that increase risk for PTSD among people who experience trauma.

Risk Factors for Exposure to Trauma Prospective longitudinal studies of risk for trauma exposure are rare. In one study, extraversion and neuroticism predicted exposure to trauma, and African American individuals experienced trauma more than did Caucasians (Breslau, Davis, & Andreski, 1995). In another study, both children with low and average intelligence later encountered more trauma than did children whose intelligence was above-average (Breslau, Lucia, & Alvarado, 2006).

Risk Factors for PTSD among People Exposed to Trauma Studies on risk for PTSD among those exposed to trauma fall into one of three categories. In the first type, researchers assess for certain features among trauma-exposed people who either developed or did not develop PTSD. Unfortunately, these studies are often difficult to interpret. If a certain feature is present more often in the PTSD group than in the non-PTSD group, it is difficult to tell whether it is a risk factor for PTSD or a consequence of PTSD. For example, Vietnam veterans with PTSD often report low levels of social support (e.g., Boscarino, 1995). Does this mean that minimal support makes it difficult for veterans to recover from acute stress symptoms, thereby placing them at risk for chronic PTSD? Or do symptoms such as irritability and withdrawal from others alienate potential sources of social support? Or do both processes occur? Moreover, people with PTSD may selectively recall adverse events from their childhood more than positive events, inadvertently creating the impression that the childhood experiences heightened their risk for PTSD. Retrospective ascertainment of possible risk factors among people who already have PTSD is not a pointless exercise, but it does come with its cave-

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ats. Keeping these in mind, researchers have reported that a history of psychiatric illness, especially anxiety and mood disorders, and a family history of anxiety, mood, or substance abuse disorders are positively associated with later PTSD (Breslau et al., 1991). Some correlates of PTSD are less likely than others to be consequences of the disorder and may therefore constitute antecedent risk factors. Neurological soft signs indicating nonspecific abnormalities in the central nervous system are more common in combat veterans and adult survivors of childhood sexual abuse (CSA) with PTSD than in healthy combat veterans and CSA survivors (Gurvits et al., 2000). These deficits in perception, language, and motor coordination usually originate in early childhood and are unlikely to result from PTSD itself. Another study from this group was able to confirm this conclusion by examining monozygotic twin pairs who constituted four groups: men who had developed PTSD following combat in Vietnam; their identical twins who had neither been exposed to combat nor had PTSD; Vietnam combat veterans who had not developed PTSD; and their identical twins who had neither been exposed to combat nor had PTSD (Gurvits et al., 2006). The findings revealed that neurological soft sign scores were higher in Vietnam combat veterans with PTSD than among those without PTSD. Moreover, the non-trauma-exposed identical co-twins of the PTSD group had higher neurological soft sign scores than did the identical co-twins of the healthy combat veterans, thereby implying that subtle neurological deficits are related to genetic (or at least constitutional) factors, not to PTSD itself. Using a similar design, Gilbertson et al. (2006) examined the role of IQ and neurocognitive abilities in the development of PTSD. The results were strikingly consistent: on nearly every test, combat veterans with PTSD and their identical twins performed very similarly, and both groups performed in the normal range; but they performed worse than did the healthy combat veterans and their co-twins. This study suggests several conclusions. First, trauma exposure has little or no effect on measures of IQ or on other tests of neurocognitive functioning. Second, the striking similarity in the test scores between co-twins strongly implicates genetic influence on performance. Third, because the PTSD group scored within the normal range on all but one test, above-average cognitive ability appears to confer protection against the disorder. Indeed, the mean IQ of the healthy combat veteran group was 118, with more than 40% of this group scoring in the superior range (over 120), whereas the mean IQ of the PTSD group was 105. Early research suggested that people with PTSD had smaller hippocampi than did people without PTSD (Bremner et al., 1995), including those who had been exposed to trauma yet who had remained psychiatrically healthy (Gurvits et al., 1996). These studies implied that the stress of suffering from PTSD might produce atrophy in this brain structure integral to autobiographical memory. Subsequent work, however, has shown that small hippocampi are a constitutional, probably genetic, vulnerability factor for PTSD among those



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exposed to trauma and not a consequence of trauma exposure or PTSD itself (Gilbertson et al., 2002). Other studies also implicate genetic variance in risk for PTSD. Studying 4,042 Vietnam era monozygotic and dizygotic twin pairs, True et al. (1993) found that heritabilities ranged from 13 to 30% for symptoms in the reexperiencing cluster (e.g., nightmares), from 30 to 34% for those in the avoidance/ numbing cluster, and from 28 to 32% in the arousal cluster (e.g., startle). They found no evidence that environments shared by co-twins accounted for variance in PTSD symptoms. Finally, the rate of PTSD is more than twice as great among women versus men, even though the latter are more often exposed to traumatic events (Tolin & Foa, 2006). The explanation for this remains unclear. One hypothesis is that women tend to be exposed to certain kinds of events that are inherently more traumatic than the ones that men usually encounter. However, even when one controls for type of trauma (e.g., rape), sex differences in the severity and prevalence of PTSD remain (Tolin & Foa, 2006). The second type of study concerning risk for PTSD involves assessing how a person responds during the trauma itself as a means of predicting who is most likely to develop the disorder. These assessments, of course, are always retrospective; researchers are seldom present when the trauma is occurring. But researchers endeavor to assess how victims responded during the trauma as soon as possible after it has occurred. Some studies suggest that peritraumatic dissociation predicts PTSD (e.g., Shalev, Peri, Canetti, & Schreiber, 1996); that is, victims who reported feeling disconnected from their body and feeling that time was moving very slowly during the trauma were especially likely to develop PTSD. How victims interpret their acute symptoms may affect whether they develop PTSD (Dunmore, Clark, & Ehlers, 2001; Ehring, Ehlers, & Glucksman, 2006; Halligan, Michael, Clark, & Ehlers, 2003). For example, if heightened startle responses and nightmares are construed as signs of personal weakness or if flashbacks are interpreted as signs of impending psychosis, trauma victims are at heightened risk for failing to recover from the acute effects of trauma. There is a potential interpretive problem with studies concerning peritraumatic responses and appraisal of acute symptoms as predictors of PTSD. Although researchers have isolated these phenomena and measured them as if they were independent variables influencing the dependent variable of PTSD, peritraumatic reactions are themselves aspects of the outcome we are trying to explain. Peritraumatic dissociation, negative appraisal of acute symptoms, and PTSD itself may all be variant manifestations of the same pathological process. Accordingly, the predictive capacity of these variables may be an artifact of how researchers parse the phenomenon, spuriously distinguishing responses during the trauma from those occurring somewhat later as if they were distinct phenomena.

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Prospective studies of risk for PTSD constitute the third type of study. These are informative but rare. To conduct this research properly, investigators must collect data on individuals prior to their exposure to trauma and thus prior to their development of PTSD. One study of Vietnam veterans indicated that lower predeployment intelligence predicted PTSD decades later even when researchers controlled statistically for degree of combat exposure (Macklin et al., 1998). The mean level of intelligence in the PTSD group was in the average range, whereas the mean level of intelligence in the non-PTSD group was above-average. Similarly, studying Vietnam veteran twins, Kremen et al. (2007) also found that higher predeployment cognitive ability buffers veterans against subsequent PTSD. Veterans scoring in the highest quartile on the cognitive ability measure had a 48% lower risk for PTSD than did those scoring in the lowest quartile. Further analyses indicated that variance in cognitive ability was entirely attributable to variance in genes. Taken together, these data imply that higher intelligence is protective against PTSD rather than lower intelligence being a risk factor. This interpretation was confirmed in a prospective longitudinal study of children (Breslau et al., 2006). Children of above-average intelligence were not only exposed to trauma less often than both those with average and below-average intelligence, but they were also less likely to develop PTSD when they were exposed to trauma. Hence, aboveaverage intelligence seems to buffer children against the pathogenic effects of trauma rather than lower intelligence increasing risk for PTSD. Many traumatologists have reported data suggesting that previous exposure to trauma is a risk factor for developing PTSD in response to exposure to subsequent trauma (e.g., King, King, Foy, & Gudanowski, 1996). That is, people who develop PTSD in response to later stressors report having experienced more trauma earlier in their lives than do people who do not develop PTSD in response to later stressors. These researchers, however, did not assess (even retrospectively) whether victims developed PTSD in response to the earlier trauma. Accordingly, one cannot tell whether exposure to prior trauma per se increases risk for subsequent PTSD in response to later trauma or whether PTSD in response to early trauma predicts PTSD in response to later trauma. Addressing this issue in a prospective longitudinal study of children, Breslau, Peterson, and Schultz (2008) found that only if children experienced PTSD in response to the earlier trauma did they have increased risk for PTSD in response to the later trauma. Accordingly, prior trauma per se does not appear to be a risk factor for PTSD in response to later trauma. Rather, a previous episode of PTSD in response to an earlier trauma increases risk for PTSD in response to a subsequent trauma.

Summary Vulnerability research on PTSD points to two major conclusions. First, researchers have separately identified risk factors for exposure to trauma and risk factors for developing PTSD among those exposed to trauma. Second,



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researchers have increasingly either identified risk factors prospectively or have designed studies that can ascertain whether a variable assessed nonprospectively can plausibly be confirmed as a risk factor rather than a consequence of PTSD. Finally, almost all research on risk factors for PTSD involves variables characterized at the level of the person (e.g., intelligence, neuroticism). This emphasis differs strikingly from the nearly forgotten work on risk for psychiatric breakdown during World War II (Jones & Wessely, 2007). In that work, group cohesion, morale, and leadership were identified as variables that buffered against battlefield psychiatric casualties.

Obsessive–Compulsive Disorder People with OCD experience recurrent intrusive thoughts, images, or impulses that increase anxiety or distress (i.e., obsessions), and they perform repetitive thoughts or actions to attenuate the distress associated with the obsessions (i.e., compulsions). The disorder usually begins gradually, with modal age of onset between the ages of 6 and 15 years for males and between 20 and 29 for females (American Psychiatric Association, 2000, p. 460). Men and women are affected equally. Estimates of prevalence vary. The NCS-R revealed a lifetime prevalence rate of 1.6% (Kessler, Berglund, et al., 2005). The 12-month prevalence rate was 1% (Kessler, Chiu, Demler, & Walters, 2005). Some data exist to suggest that there are potential genetic, neurobiological, and cognitive vulnerability factors for the development of OCD.

Genetics OCD is often familial (Jonnal, Gardner, Prescott, & Kendler, 2000; Nestadt et al., 2000) with risk to first-degree relatives reported as 3–12 times greater than in the general population (Grados, Walkup, & Walford, 2003; Hanna, Himle, Curtis, & Gillespie, 2005). Reviewing the literature on twins with OCD, Tallis (1995) concluded that concordance rates for monozygotic twins are higher than for dyzygotic twins. For example, Carey and Gottesman (1981) reported concordance rates of 87 and 47% for monozygotic and dyzygotic twin pairs, respectively, drawn from the Maudsley twin register. It is unclear, however, whether a specific vulnerability for OCD is transmitted or whether a general proneness for anxiety disorders constitutes the vulnerability. Black and his colleagues blindly interviewed first-degree relatives of 33 healthy controls (Black, Noyes, Goldstein, & Blum, 1992). They found that the morbidity risk for anxiety disorders in general was elevated among the relatives of OCD probands relative to the relatives of control probands; the specific risk for OCD was that parents of OCD probands were more likely than parents of controls (16 vs. 3%) to exhibit either OCD or subclinical OCD. Finally, although there are intriguing findings in the research on genetic markers for OCD that implicate the serotonin transporter gene (SERT; e.g., Hu et

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al., 2006), candidate gene association studies have not yet yielded sufficiently consistent evidence to confirm specific gene involvement in OCD (Menzies, Chamberlain, & Laird, 2008).

Neuroanatomical Findings Neuroanatomical studies are consistent with the idea that structural and functional aberrations may represent vulnerability factors for OCD. For instance, increased cortical gray–white matter ratios have been observed in OCD patients (Breiter et al., 1994; Jenike et al., 1996), and this may reflect a deviation in prenatal programmed cell death or a postnatal abnormality in myelination (Jenike et al., 1996; MacMaster, Dick, Keshavan, & Rosenberg, 1999). Furthermore, neurobiological models have consistently implicated irregularities in anterior cingulated–basal ganglia–thalamocortical circuitry in the pathogenesis of OCD (Baxter, 1994; Graybiel & Rauch, 2000; Jenike et al., 1996; Pujol et al., 2004; Saxena & Rauch, 2000). One hypothesis is that a developmentally mediated dysplasia involving this circuitry is a vulnerability factor for the development of OCD (Rosenberg & Keshavan, 1998). However, until prospective longitudinal studies are conducted, it remains unclear whether these neurobiological abnormalities reflect vulnerability to OCD or are correlates of OCD symptoms.

Cognitive Factors Clinicians have speculated about possible psychological vulnerability factors for OCD. Rachman (1997), for example, has suggested that premorbid high moral standards, tendencies to misinterpret the significance of one’s thoughts as in thought–action fusion (i.e., thinking a bad thought is morally equivalent to bad action), depressed mood (e.g., Abramowitz, Storch, & Keeley, 2007; Ricciardi & McNally, 1995), and exaggerated sense of personal responsibility (e.g., Salkovskis, 1985, 1999) may render people vulnerable to OCD. Cognitive theories of OCD (e.g., Rachman, 1997; Salkovskis, 1996) are based on the premise that the experience of unwanted intrusive thoughts is a normative experience (Rachman & de Silva, 1978; Salkovskis & Harrison, 1984), that the process that turns an intrusive thought into a clinically significant obsession is a faulty appraisal of the thought, and that these dysfunctional appraisals are based on certain enduring, dysfunctional core beliefs. The Obsessive Compulsive Cognitions Working Group (OCCWG; 1997, 2001, 2003, 2005) has identified six domains of obsessive beliefs that underlie the enduring tendency in individuals with OCD to appraise intrusive thoughts in particularly negative ways: an inflated sense of responsibility; an exaggerated importance attached to thoughts; faulty beliefs about the control of thoughts; perfectionism; overestimation of threat; and intolerance of uncertainty. With few exceptions, most of this theorizing has been based on observations of people who already have the disorder. However, Abramowitz, Khandker, Nelson, Deacon,



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and Rygwall (2006) conducted a prospective longitudinal study on the development of OCD in adulthood. Given that childbirth and postpartum are associated with the increased onset of OCD symptoms, the authors recruited pregnant women and men living with their pregnant partners and followed them prospectively for 3 months after childbirth. The results of the study revealed that the majority of new parents experienced intrusive thoughts related to the infant and performed some neutralizing behaviors. Importantly, scores on a measure of dysfunctional obsessive beliefs (OBQ; OCCWG, 2005) predicted the development and severity of certain types of OCD symptoms. Similarly, in a study with undergraduate participants, Coles and Horng (2006) showed that preexisting obsessive beliefs predicted change in OCD symptoms in a 6-week follow-up. Thus, some evidence is emerging to suggest that dysfunctional beliefs act as vulnerability factors in the pathogenesis of certain types of OCD.

Summary Few firm conclusions can be culled from OCD vulnerability research. First, it is unclear whether genetic factors increase specific risk for OCD or whether they predispose people to develop anxiety syndromes in general. Second, it is unclear whether the neurobiological aberrations seen in OCD are preexisting vulnerability factors or correlates of OCD symptoms. On a more promising note, an upsurge in theoretical and, more recently, empirical work on pathogenic obsessional beliefs provides important clues to the existence of cognitive vulnerability factors for OCD.

Conclusions The search for vulnerability factors for adult anxiety disorders is likely to continue to occur at multiple levels of analysis: genetic, cognitive, and social. Students of panic disorder, OCD, and PTSD will further explore the possibility that certain cognitive factors, especially pathogenic beliefs, may predispose people to develop specific syndromes. The chief challenge will be to identify relevant participants premorbidly and to test hypotheses about risk prospectively. In addition to deepening our understanding regarding causation and satisfying our scientific curiosity, identifying vulnerability factors may allow us to identify people at risk for developing particular disorders and to take steps to prevent the full-blown emergence of these syndromes. Although the search for vulnerability factors is clearly ongoing, some investigators have begun to use the information we already have to design preventative measures. For example, Schmidt et al. (2007) recently reported findings from a brief prevention program aimed at reducing anxiety sensitivity in hopes of reducing vulnerability to later Axis I disorders. At 24-month follow-up, those participants

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who had received the anxiety sensitivity amelioration training demonstrated greater reduction in anxiety sensitivity and reduced fear in response to a biological challenge relative to the control group. Moreover, the incidence of any anxiety disorder at 24-month follow-up was 3.8% in the treatment group, compared to 7.6% in the control group. Although this difference was not statistically significant, it is promising and suggests that future work is warranted. As our understanding of the factors involved in the development of anxiety disorders evolves, we should see more research of this kind.

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Chapter 13

Vulnerability to Anxiety Disorders across the Lifespan Richard J. McNally, Vanessa L. Malcarne, Sadia Najmi, Ingunn Hansdottir, Hannah E. Reese, and Erin L. Merz

Establishing Common Ground In this brief chapter, we underscore several points that occurred to us after having read each other’s chapters. First, vulnerability issues differ drastically across the anxiety disorders. Some conditions rarely emerge in childhood (e.g., panic disorder), others rarely emerge in adulthood (e.g., animal phobia), and still others can emerge in childhood, adolescence, or adulthood (e.g., obsessive–compulsive disorder). Therefore, questions about vulnerability partly depend on the syndrome in question. Second, suggestions that genetic heritability may represent a general diathesis for anxiety, with environmental risk factors (such as life events) representing the stressors that activate a specific anxiety disorder, are sensible and suggest greater applicability to understanding anxiety disorders across the lifespan. However, scientists have not clearly identified these environmental risk factors and their interaction with genetic risk factors. Moreover, genetically influenced personality variables may themselves affect exposure to these environmental stressors. Third, some childhood syndromes may themselves constitute vulnerable conditions for adult syndromes. The suggestion that separation anxiety disorder increases risk for later panic disorder and agoraphobia would constitute such an example. Moreover, some childhood syndromes may be developmental variants of adult syndromes, as exemplified by the subsuming of overanxious disorder of childhood under the “generalized anxiety disorder” rubric. Alternatively, some syndromes in adults, such as blood or animal phobia, may

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merely constitute a chronic condition that has never waned as the patient has grown into adulthood. Therefore, perhaps the most important lesson is that the childhood– adulthood distinction is arbitrary and unhelpful for understanding vulnerability for most anxiety disorders. Although there is tremendous overlap in many of the vulnerability processes considered in the adult and child anxiety literatures, these literatures seem to exist quite separately. This separation is no longer justified; indeed, it may impede progress in understanding vulnerability. It is likely more useful to ask “What are the vulnerability factors for syndrome X?” than to presuppose that different vulnerability factors account for its emergence in childhood and others for its emergence in adulthood. Overall, there may be more similarities than differences.

Future Directions for Research As for the future, we need a more sophisticated lifespan developmental perspective on the anxiety disorders, one not limited to differentiating “child” versus “adult” risk factors. In addition to identifying risk factors for anxiety, research from such a perspective would include (1) consideration of when risk factors emerge, and within what biopsychosocial and developmental contexts, as well as (2) developmental variations and similarities in symptom expression. Research to date has suggested a variety of potentially important risk factors for anxiety disorders, applicable throughout the lifespan. These fall into the categories of genetic, cognitive/affective, and social/environmental. Research into genetic vulnerability has to date focused on uncovering evidence of heritability. Scientists studying genetic transmission need to identify risk alleles associated with vulnerability to anxiety disorders and to track carriers from childhood onward. This prospective longitudinal approach, although expensive and time-consuming, is essential if we are to understand how genetic risk is expressed throughout development. This approach is also essential to understanding how interactions of genetic risk with environmental exposure result in the development and expression of anxiety disorders. However, there are good reasons to temper our enthusiasm for molecular genetic research in psychopathology. Genome-wide association studies designed to identify risk alleles require hundreds, often thousands, of subjects, and the results often do not replicate (Crow, 2008; Ioannidis, 2005). Researchers have assumed that a set of common alleles across the same genetic loci, each having a small effect size, drives vulnerability for common diseases (e.g., schizophrenia, anxiety disorders). These assumptions may be incorrect (Gorlov, Gorlova, Sunyaev, Spitz, & Amos, 2008). For example, rare allelic mutants at different loci may heighten vulnerability, making it difficult for association studies to uncover them. Additionally, epigenetic factors, only



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recently investigated, may play a larger role in neural development and function than most scientists ever imagined (Mehler, 2008). We need a similar prospective longitudinal approach for elucidating the role of cognitive/affective and social/environmental variables in the development and maintenance of anxiety. Studies examining cognitive and affective contributors to anxiety have suggested important roles of perceptions of control, a variety of cognitive errors and pathogenic beliefs, attentional control and threat bias, and emotional regulation. However, whether these cognitive and affective features increase vulnerability to anxiety disorders or instead constitute emerging symptoms of those disorders remains unclear due to the paucity of prospective longitudinal studies. Research on social/environmental risk factors for anxiety has focused on parenting behavior and parent–child relationships as risk factors for child anxiety and life events as risk factors for adult anxiety. Although this research has been successful in establishing the presence of disturbed parenting and adverse life events in the histories of a significant proportion of individuals with certain anxiety disorders, much of this research is retrospective. It is also problematic that in their studies on parental rearing practices psychosocial researchers have rarely distinguished between shared environmental and genetic influences on childhood psychopathology. In addition, findings to date, although limited, suggest that only a small proportion of individuals exposed to adverse life events or disturbed parenting actually develops anxiety disorders. Future research needs to expand beyond its current focus on risk factors to include identification and examination of protective factors as well. Finally, vulnerability researchers need to study how risk factors may vary across generational cohorts. Indeed, Twenge (2000) found that scores on standardized measures of anxiety and neuroticism have been climbing over the past several decades. She found that the average college student in the 1990s scored higher than 71% of college students in the 1970s and scored higher than 85% of college students in the 1950s. A similar pattern occurred for children. Schoolchildren in the 1980s scored higher on anxiety scales than did the average child psychiatric patient in the 1950s. Moreover, Twenge, Zhang, and Im (2004) found that children and college students have become increasingly more external in their locus of control during the past several decades. For example, the average college student in 2002 was more external than 80% of college students in the early 1960s. People characterized by high external locus of control are likely to experience difficulty in coping with stress relative to those characterized by a high internal locus of control. In conclusion, it is clear that, despite the inherent difficulties in reconciling specialized research tracks, progress in understanding vulnerability to anxiety will be facilitated by a reintegration of child- and adult-oriented perspectives into a truly lifespan perspective on anxiety. Such a reintegration necessitates prospective long-term longitudinal research, following from childhood through adulthood persons determined to be “at risk” due to their exposure to identified risk factors. Only in this way can we characterize short-

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and long-term general and specific anxiety-related outcomes and identify important interactions contributing to the emergence of anxiety disorders.

References Crow, T. J. (2008). The emperors of the schizophrenia polygene have no clothes. Psychological Medicine, 38, 1681–1685. Gorlov, I. P., Gorlova, O. Y., Sunyaev, S. R., Spitz, M. R., & Amos, C. I. (2008). Shifting paradigm of association studies: Value of rare single-nucleotide polymorphisms. American Journal of Human Genetics, 82, 100–112. Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2, 696–701. Mehler, M. F. (2008). Epigenetic principles and mechanisms underlying nervous system functions in health and disease. Progress in Neurobiology, 86, 305–341. Twenge, J. M. (2000). The age of anxiety?: Birth cohort change in anxiety and neuroticism. Journal of Personality and Social Psychology, 79, 1007–1021. Twenge, J. M., Zhang, L., & Im, C. (2004). It’s beyond my control: A cross-temporal metaanalysis of increasing externality in locus of control, 1960–2002. Personality and Social Psychology Review, 8, 308–319.

Schizophrenia

Chapter 14

Vulnerability to Schizophrenia in Childhood and Adolescence Patricia A. Brennan and Elaine F. Walker

Schizophrenia is a debilitating mental disorder that has posed formidable challenges to researchers. Despite decades of investigation, we have not yet identified any specific causal agent or pathophysiological process. Nonetheless, as empirical findings have accumulated, our conceptual framework about the etiology of schizophrenia has been modified to accommodate the data. As a result, contemporary theoretical models have become more complex and sophisticated and, it is hoped, more accurate. In recent years, what has come to be known as the “neurodevelopmental” perspective has played a central role in theorizing about the etiology of schizophrenia (Waddington & Buckley, 1996). The historical roots of contemporary neurodevelopmental models can be found in Meehl’s (1962) diathesis–stress model, which suggested an interaction between genetically based brain aberrations and noxious environmental events as the basis for the eventual outcome of schizophrenia. The accumulation of empirical data linking obstetrical complications with schizophrenia narrowed the focus on early brain development as a critical period. The central premise of current neurodevelopmental theories is that vulnerability for schizophrenia is acquired early in life and involves an aberration in the development of the central nervous system (Rapoport, Addington, & Frangou, 2005; Weinberger, 1995). The neurodevelopmental abnormalities are theorized to arise from obstetrical complications and/ or genetic predispositions. It is also theorized that the brain abnormalities observed in patients with schizophrenia reflect, at least in part, these early developmental deviations. The neurodevelopmental perspective is often contrasted with Kraepelin’s (1919) notion of schizophrenia as a degenerative brain pathology similar to

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dementia. The degenerative model implies that the neuropathology underlying schizophrenia arises in the prodromal period, usually late adolescence or early adulthood. In fact, however, the two perspectives, neurodevelopmental and degenerative, are not incompatible. It is possible that schizophrenia involves an abnormality in the embryogenesis of the central nervous system and that there is a subsequent neurodegenerative process prior to and/or following the onset of the clinical symptoms. Both of these processes may have a basis in genetic risk, via epigenetics. The concept that genes are not static over the course of life but rather are turned on and off by naturally occurring developmental changes as well as environmental stressors makes the differentiation between neurodevelopmental and neurodegenerative theories of schizophrenia far less discernible in many respects. Nevertheless, the current state of the field reflects an emphasis and a growing body of evidence supportive of a neurodevelopmental approach to schizophrenia. In this chapter, we examine some of the research evidence that lends support to a neurodevelopmental model of schizophrenia. Specifically, we posit a model that assumes that (1) schizophrenia involves a congenital neural abnormality, (2) the expression of this abnormality is moderated by ongoing brain maturation and experience, and (3) a neurodegenerative process can ensue as a consequence of this developmental process. We begin by discussing some key areas of evidence supporting a congenital brain abnormality in schizophrenia, including data on genetic and prenatal factors. We then explore the potential role of hormonal factors, including adrenal hormones, in triggering the expression of vulnerability for schizophrenia. In this connection, the effects of hormones on gene expression may prove to be important in the etiology of schizophrenia. Finally, we conclude with a discussion of the implications of neurodevelopmental theories for early identification and intervention with schizophrenia. (For a broader overview of vulnerability for schizophrenia outside the context of neurodevelopmental theory, see Compton & Harvey, Chapter 15, this volume).

Evidence of Congenital Vulnerability to Schizophrenia The clinical onset of schizophrenia typically occurs in early adulthood, after the individual has passed through the first two decades of life. It is theoretically plausible that the onset of the underlying neuropathology associated with schizophrenia coincides with the onset of the clinical syndrome. For example, a gene or polygene that leads to defective brain function may only be biologically expressed when the individual passes through a specific developmental stage. But several strands of empirical data have converged, instead, on the notion that the neurological vulnerability to schizophrenia is present at birth. Thus, the behavioral expression of the vulnerability may change in response to maturational processes, but it involves a brain abnormality that is congenital.



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Here we offer an overview of some of the findings that support this assumption.

Physical Signs of Vulnerability Assuming a biological basis for schizophrenia, investigators have searched for physical correlates of the illness for nearly a century. Postmortem studies of brain structure and electroencephalographic studies of brain function were initiated in the 1920s, and the introduction of modern neuroimaging techniques marked the beginning of the most rapid progress in reliably identifying the presence of brain abnormalities in schizophrenia and other mental disorders. Despite the large array of studies on brain abnormalities in patients with schizophrenia, very few prospective studies have examined associations between structural brain deficits and the later onset of psychosis. In the following section, we review those few studies as well as research linking perinatal risk factors to brain abnormalities in persons with schizophrenia. We also examine other physical indicators, most notably dysmorphic features of the body, that have provided convincing evidence about the congenital nature of the biological vulnerability for schizophrenia.

Structural Brain Abnormalities The most replicated structural brain deficit in patients with schizophrenia is lateral ventricular enlargement. This finding has been noted in both computed tomography (CT) studies (e.g., Andreasen et al., 1990) and magnetic resonance imaging (MRI) studies (e.g., Zipursky, Lim, Sullivan, Brown, & Pfefferbaum, 1992). A reduction in gray-matter volume in the hippocampus, amygdala, thalamus, and temporal cortex has also been noted (Cannon, 1998). These gray-matter deficits are consistent with those noted in prospective studies of individuals who eventually develop psychotic symptoms or disorders. For example, Pantelis and colleagues (2003) completed MRI scans on 75 individuals at high risk for schizophrenia prior to the onset of their first psychotic episode. One year later they compared these prospectively obtained MRI scans for those who qualified for a diagnosis of psychosis (n = 23) against those who did not (n = 52). Individuals who developed psychosis were found to have less gray matter in the cingulate cortex as well as the right temporal and frontal cortices. Borgwardt and colleagues (2007) employed a similar method, obtaining MRI scans on 35 individuals at high risk for psychosis and later comparing the brain volumes of those who became psychotic (n = 12) to those who did not (n = 23). The individuals who later developed psychoses again had decreased gray matter, this time in the right insula and inferior frontal and superior temporal gyrus. In the third prospective study in this area, Ho (2007) found an association between smaller gray-matter volumes in the frontal and temporal areas of the brain and prodromal symptoms assessed 1 year later in 35 relatives of probands with schizophrenia.

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Corresponding evidence of the congenital nature of neuroanatomical abnormality in schizophrenia comes from positive associations between early events or behavioral phenomena and adult brain morphology. In a longitudinal study of the Danish high-risk sample, Cannon and his colleagues (1993) linked exposure to delivery complications with ventricular enlargement in adult patients with schizophrenia. Two recent studies have replicated this finding, one noting a positive relationship between obstetrical complications and ventricle-to-brain ratio (VBR; Falkai et al., 2003) in adult schizophrenic patients and the other finding a positive relationship between minor physical anomalies and VBR in childhood-onset schizophrenia (Hata, Iida, Iwasaka, Negoro, & Kishimoto, 2003). In a related study, Walker, Lewine, and Neumann (1996) examined the association between childhood behavioral phenomena and adult brain morphology on MRI examination among patients with schizophrenia. Using childhood home movies as a source of data on early behavior, they found that neuromotor deficits and negative affect during infancy were linked with greater ventricular enlargement in adulthood. Also, parental ratings of the severity of “externalized” childhood behavior problems showed an inverse relation with adult cortical volume. These associations are consistent with neurodevelopmental theories of schizophrenia; they suggest that obstetrical factors contribute to brain abnormalities in schizophrenia and that these abnormalities can influence behavior. Of course, the neuroimaging results were obtained after the onset of schizophrenia, so a causal chain from prenatal risk to early brain abnormalities to later schizophrenia can only be inferred with these findings. But the evidence is persuasive and lends support to the assumption that the origins of schizophrenia lay in the early development of the central nervous system. At the same time, however, there is some evidence that a degenerative process characterizes at least some cases of schizophrenia. Several investigations involving repeated measures of brain structure have revealed increasing abnormalities over time (DeLisi, 1999; DeLisi et al., 1997; Rapoport et al., 1997; Thompson et al., 2001), although others have not provided evidence for degeneration over the course of the illness (Cannon, 1991; James, Javaloyes, James, & Smith, 2002; Keshavan, Schooler, Sweeney, Haas, & Pettegrew, 1998). Rapoport et al. (1997) found an increase in ventricular volume in the brains of children with onset of schizophrenia before age 12; during the course of adolescence, these young patients showed a measurable ventricular enlargement. Rapoport et al. (1999) also found that children with schizophrenia showed a decrease in the volume of temporal gray matter greater than that of healthy controls over a 4–year follow-up in adolescence. Along these same lines, a study of patients with chronic schizophrenia revealed that the volume of the hippocampus was correlated with age and illness duration (Velakoulis et al., 1999). A recent prospective study suggests that neurodevelopmental and neurodegenerative processes are likely both at work in schizophrenia (Pantelis et al., 2003). In this study, results from repeated MRI scans were compared between 10 individuals who were scanned prior to and after the onset of psy-



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chosis and 11 high-risk individuals who never developed psychosis. Although some gray-matter volume differences were evident prior to the onset of psychosis, additional structural changes (including reduced gray matter in the parahippocampal and orbitofrontal cortices) were noted only after the onset of the psychosis. Although the evidence for a degenerative brain process is suggestive, we must await the results of future research aimed at replicating these findings. The increased accessibility and safety of MRI structural and functional imaging procedures should pave the way for more prospective longitudinal studies of children at risk for schizophrenia, early brain pathology, and eventual schizophrenic outcomes.

Dysmorphic Features: Minor Physical Anomalies and Dermatoglyphic Abnormalities Minor physical anomalies (MPAs) are irregularities in the structure of the face, head, hands, and feet. The most widely used measure of MPAs, the Waldrop scale (Waldrop & Halverson, 1971), indexes anomalies such as steepled palate, asymmetric ears, and hyperteliorism. Research has provided evidence that MPAs are a consequence of fetal exposure to prenatal insult as well as genetic factors (Smith, 1982). The ectoderm, from which these external features of the head and extremities originate, undergoes rapid development during the first and second trimesters—the same periods when the central nervous system (CNS) undergoes significant development. Therefore, abnormalities in the morphological characteristics derived from the ectoderm are considered indirect markers of nonoptimal fetal neurodevelopment. MPAs have been found to occur at an elevated rate in individuals with a variety of disorders, including autism (Gualtieri, Adams, Chen, & Loiselle, 1982), attention-deficit/disorder (Deutsch, Matthysse, Swanson, & Farkas, 1990), childhood adjustment disorder (Fogel, Mednick, & Michelsen, 1985; Halverson & Victor, 1976; Pomeroy, Sprafkin, & Gadow, 1988), aggressive behavior (Kandel, Brennan, Mednick, & Michelson, 1989), schizophrenia (Griffiths et al., 1998), and schizotypal personality disorder (Davis-Weinstein, Diforio, Schiffman, Walker, & Bonsall, 1999). A recent study of the diagnostic specificity of MPAs concluded that MPAs are not specific to schizophrenia but also convey risk for affective psychoses (Lloyd et al., 2008). Taken together, the research findings suggest that MPAs are nonspecific indicators of abnormalities in fetal CNS development that compromise postnatal CNS function, thereby conferring an increased risk for a variety of behavioral abnormalities. It has been suggested that the nonspecificity of the relationship between MPAs and schizophrenia may be a result of methodological weaknesses of research in this area (Buckley, 1998). The most current research in this area is attempting to focus on craniofacial features that are easier to quantify than many other MPAs and that may also be more relevant to the development of schizophrenia. For example, a narrowing and heightening of the palate has been noted to be one of the most prominent

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MPAs related to schizophrenia (Lane, Larkin, Waddington, & O’Callaghan, 1996). Craniofacial abnormalities have recently been noted in both patients with schizophrenia and their parents (Gourion et al., 2004). Moreover, craniofacial abnormalities have been found to be related to ventricular surface in schizophrenia (Dequardo, Bookstein, Green, & Tandon, 1996), suggesting an important link between these features and neurological vulnerability for this disorder. The continued use of these refined measures may provide useful information about critical periods for prenatal damage that might be a source of vulnerability for schizophrenia. As described later, this issue of critical periods has arisen from work linking prenatal viral infection in the first and second trimesters to schizophrenic outcomes. Irregularities in palm prints and fingerprints are another dysmorphic sign associated with behavioral dysfunction (Schaumann & Alter, 1976). Among the most commonly measured aspects are differences in finger ridge counts between corresponding digits on the right and left hands (“fluctuating asymmetries,”or FAs), total finger ridge counts, and palmar a-b ridge count. Like MPAs, these irregularities have their origin in prenatal development and appear to be a consequence of both genetic factors and prenatal insult (Cummins & Midlow, 1961; Mellor, 1968). In addition, a causal effect of prenatal stress is indicated by findings that exposure of pregnant monkeys to stress results in an increase in dermatoglyphic abnormalities (DAs) in offspring (Newell-Morris, Fahrenbruch, & Sackett, 1989). The timing of dermatoglyphic formation in the upper limbs is primarily the 14th through the 22nd week of gestation, the first part of the second trimester. As with MPAs, it is assumed that DAs predict behavioral dysfunction because they are a nonspecific marker of neurodevelopmental abnormalities that compromise CNS structure (Schaumann & Alter, 1976). DAs occur at an elevated rate in several mental disorders, including affective disorders (Balgir, 1982), autism and developmental disorders (Hartin & Barry, 1979), and schizophrenia (Bracha, Torrey, Bigelow, Lohr, & Limington, 1991; Lohr & Flynn, 1993; Mellor, 1968; Reilly et al., 2001). The prenatal environmental origin of DAs is suggested by findings that, in comparison with their nonaffected twin controls, the affected twins in monozygotic pairs discordant for schizophrenia show reduced dermal ridges (Davis & Bracha, 1996). A recent family study also suggests that patients with schizophrenia and their first-degree relatives evidence higher numbers of DAs and that the specific DAs found in the patients could be traced to the second trimester of development (Avila, Sherr, Valentine, Blaxton, & Thaker, 2003). Again, this finding is consistent with the notion of critical periods in neurodevelopmental theory. Although it is assumed that the presence of dysmorphic features is an indirect indicator of abnormalities in CNS development, little research has been conducted on the relation between brain morphology and either MPAs or dermal abnormalities. The three reported studies of which we are aware indicated mixed results for an association between MPAs and



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ventricular volume in patients with schizophrenia (Dean et al., 2006; Hata et al., 2003; O’Callaghan, Buckley, Madigan, & Redmond, 1995). Clearly, this is an important issue for further investigation. To understand the significance of dysmorphic features, it is important to determine their relation to brain morphology in both disturbed and nondisturbed populations.

Behavioral Markers of Vulnerability The research findings reviewed previously offer persuasive evidence that some patients with schizophrenia have a congenital brain abnormality. But does this have any behavioral implications prior to the clinical onset of symptoms? The literature on premorbid behavior in schizophrenia suggests that the answer to this question is “yes.” In addition, the findings lend further support to the neurodevelopmental model.

Neuromotor Abnormalities Childhood neuromotor abnormalities are a consequence of both obstetrical complications (El-DeFrawi, Hirsch, Jurkowicz, & Craig, 1996; HaddersAlgra, Huisjes, & Touwen, 1988; Walker, 1994) and hereditary factors (Fouad, Servidei, Durcan, Bertini, & Ptacek, 1996). An extensive body of literature has also documented deficits in motor function among childhood psychiatric and learning disorders (Neumann & Walker, 1996). Gross motor and visual-motor deficits have been noted in infants and children with parents with schizophrenia (Fish, Marcus, Hans, Auerbach, & Perdue, 1992; Marcus, Hans, Auerbach, & Auerbach, 1993; McNeil, Harty, Blennow, & CantorGraae, 1993; Mednick, Mura, Schulsinger, & Mednick, 1971). Similarly, numerous studies have shown that motor abnormalities are associated with psychoses and affective disorder in adulthood (for reviews, see Neumann & Walker, 1996; Swerdlow & Koob, 1987; Walker, 1994). Consistent with neurodevelopmental theory, recent investigations have documented that childhood motor abnormality precedes the onset of major psychiatric disorder. For example, delays in reaching motor milestones were associated with schizophrenia in a British cohort follow-back study, although in the absence of a psychiatric control group the authors could not conclude that such motor delays are specific to schizophrenic outcomes (Davies, Russell, Jones, & Murray, 1998). Investigations that have compared children at risk for schizophrenia with those at risk for other psychiatric disorders have shown that motor deficits are more pronounced in those who subsequently develop schizophrenia (Fish & Kendler, 2005; Fish et al., 1992; McNeil et al., 1993; Walker, Savoie, & Davis, 1994). Thus, there appears to be some specificity of neuromotor dysfunction to schizophrenia. There is evidence suggesting that one subtype of motor abnormality, excessive involuntary movements (clinical and subclinical hyperkinesias, or

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“dyskinesias”), may be uniquely linked with schizophrenia and spectrum disorders (e.g., schizotypal personality disorder). Elevated rates of involuntary movements are observed in treatment-naive and medicated patients with schizophrenia (Cortese et al., 2005; Khot & Wyatt, 1991). Further, it has been shown that ratings of dyskinetic movements in adult patients with schizophrenia are positively correlated with the severity of childhood premorbid deficits (Chakos et al., 1996). Like adult patients with schizophrenia, children who subsequently manifest the disorder show heightened involuntary movements (e.g., hand posturing and irregular writhing movements of the hands), as observed in home movies of children from birth to 2 years of age who are preschizophrenic (Walker et al., 1994). Further, the severity of premorbid dyskinesia is predictive of the severity of psychiatric symptoms in adulthood (Neumann & Walker, 1996). Studies have also documented an excess of involuntary movements in children (Walker, Lewis, Loewy, & Palyo, 1999) and adults (Cassady, Adami, Moran, Kunkel, & Thaker, 1998) with schizotypal personality disorder. And two recent reports have linked movement abnormalities to prodromal symptoms and to risk for conversion to psychosis in adolescence (Mittal, Neumann, Saczawa, & Walker, 2008; Mittal & Walker, 2007). Observations of significant associations between childhood motor abnormalities and schizophrenia spectrum outcomes lend support to neurodevelopmental models of schizophrenia. The CNS abnormalities associated with hyperkinesias (e g., associated choreoathetoid and ballistic movements) have been localized to particular brain regions. Hyperkinesias are due to abnormalities in the striatum that, in interaction with dopamine (DA) activity, disrupt motor circuitry (Walker, 1994). Specifically, theories of the neural circuitry of movement disorders assume that hyperkinetic syndromes are due to overactivation of compromised DA pathways in the striatum, particularly the pathway mediated by the DA D2 receptor subtype (Alexander, Crutcher, & DeLong, 1990; Gerfen, 1992; Smith, Bevan, Shink, & Bolam, 1998). It has been proposed that DA overactivity in proximal striatal regions contributes to psychotic symptoms, and some authors have postulated neural mechanisms through which DA receptor abnormalities disrupt the striatalcortical neural circuitry to produce both movement disorder and psychotic symptoms (Swerdlow & Koob, 1990; Walker, 1994). Thus, based on contemporary neural circuitry models, the presence of hyperkinesia in children at risk for schizophrenia is consistent with neurodevelopmental etiological theories of schizophrenia.

Sustained Attention Attentional deficits have also been documented in patients with schizophrenia and in children at high risk for schizophrenia (Cornblatt, Obuchowski, Schnur, & O’Brien, 1998; Nuechterlein, 1983). Adults with schizophrenia, children of parents with schizophrenia, and premorbid individuals with schizophrenia



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have been found to evidence deficits in sustained attention on a variety of measures, most notably the continuous performance task (CPT). In this task, subjects are asked to attend to a series of letters or numbers and to detect an intermittently presented target stimulus. Individuals at risk for schizophrenia and those that have schizophrenia show poor detection of this target stimulus. This deficit is thought to reflect fragmented and inefficient attentional mechanisms. A deficit in working memory has also been hypothesized as the cause of this attentional difficulty (Nuechterlein et al., 1998). Longitudinal analyses from the New York High-Risk Project suggest that sustained attention deficits that appear early in development are relatively stable over time and may be specific to risk for schizophrenia in individuals at genetic risk for this disorder (Cornblatt, Obuchowski, Roberts, Pollack, & Erlenmeyer-Kimling, 1999). A subgroup of the offspring of parents with schizophrenia has been found to be attentionally deviant, and this subgroup is more likely to manifest adjustment problems in adolescence and schizophrenia in adulthood. This subgroup has been hypothesized to represent the 35–45% of adult patients with schizophrenia who also have significant attentional deficits. The presence of attentional deficits in children at risk for schizophrenia suggests that brain dysfunction precedes the onset of clinical symptoms. Again, this points to the likelihood of a congenital brain impairment.

Smooth-Pursuit Eye Movements Abnormalities in smooth-pursuit eye movement (SPEM) have also been found consistently in patients with schizophrenia and individuals at risk for the illness (Iacono & Clementz, 1993). SPEMs are elicited in normal individuals by a continuously moving stimulus such as a target on a screen or a swinging pendulum. In eye tracking, the eye velocity matches the target velocity within a specified range of movement. If eye tracking fails, then saccadic eye movements are observed rather than smooth tracking of the stimulus. The neural mechanisms that underlie SPEM have not been fully determined; however, there is evidence for hippocampal and frontal lobe involvement in this process (Katsanis & Iacono, 1991; Tregellas et al., 2004). A recent study also suggests that medication-induced hypodopaminergia in the cortex might directly disrupt SPEM in normal individuals (Malaspina et al., 1994). In this study, haloperidol disrupted eye tracking in healthy subjects and created saccadic movements similar to those noted in schizophrenics. It is assumed that haloperidol administration to healthy individuals results in reduced dopamine release in cortical but not subcortical brain regions (Lambert et al., 1995). Thus, haloperidol disruption of eye tracking may suggest a link between cortical hypodopaminergia and disruptions in SPEM. SPEM deficits have been found in patients with schizophrenia (e.g., Mialet & Pichot, 1981), their unaffected relatives (e.g., Holzman & Levy, 1977), and children at high genetic risk for schizophrenia (Mather, 1985). These deficits are evident early in the life course. For example, a study of high-risk children

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of patients with schizophrenia has noted deficits in anticipatory saccades in offspring as young as 6 years of age (Ross, Hommer, Radant, Roath, & Freedman, 1996). And these associations are strong: a recent study found that 94% of children with schizophrenia demonstrated SPEM deficits, compared to a rate of only 19% in controls (Ross, 2003). To date, however, no study has been able to test for the link between premorbid SPEM deficits and eventual schizophrenic outcomes. Overall, the research on eye tracking has provided compelling evidence that SPEM deficits qualify as a risk marker for schizophrenia (Iacono & Ficken, 1989; Iacono, Moreau, Beiser, Fleming, & Lin, 1992). These deficits have been found to be stable over time, to be present in patients under remission, to be present in first-degree relatives of persons with schizophrenias, to have higher concordance in monozygotic versus dizygotic twins, and to be relatively rare in normal individuals.

Prenatal and Perinatal Factors as Sources of Vulnerability There is now compelling evidence that obstetrical complications are linked with schizophrenia (Byrne, Agerbo, Bennedsen, Eaton, & Mortensen, 2007; Cannon, Jones, & Murray, 2002; Dalman, Allebeck, Cullberg, Grunewald, & Koester, 1999; Jones, Rantakallio, Hartikainen, Isohanni, & Sipila, 1998). Included among the factors that have been identified in multiple studies are preeclampsia, maternal bleeding, asphyxia, toxemia, and prolonged labor. The consequences of these complications for neural development are not known, but it is assumed that they compromise regions of the brain that are implicated in schizophrenia. During the winter and spring, there is also an increase in births of babies who later develop schizophrenia (Hare, 1988). One plausible explanation for this epidemiological finding is that schizophrenia is caused by exposure to viral infections during gestation (Mednick, Machon, Huttunen, & Bonet, 1988). Influenza exposure has also been linked to the outcome of major affective disorders, suggesting that the effect may not be specific to schizophrenia (Machon, Mednick, & Huttunen, 1992). Mednick et al. (1998) have proposed that the timing of the prenatal insult is critically important in that exposure during one window of fetal development may lead to schizophrenia whereas exposure during another window of fetal development may lead to affective disorder. To date, the particular gestational window of vulnerability remains unclear. A recent study that confirmed the maternal prenatal influenza–offspring schizophrenia association with direct serological evidence tied this effect to the first trimester of pregnancy (Brown et al., 2004). In contrast, previous research suggested that exposure during the second trimester was most highly associated with schizophrenic outcomes (Mednick et al., 1988; Sham et al., 1992). In a sample of patients with schizophrenia, a correlation has been reported between increased sylvan fissure volume and risk of influenza exposure dur-



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ing the second trimester (Takei, Lewis, Jones, Harvey, & Murray, 1994). This finding provides preliminary evidence for the hypothesized pathway from flu exposure in utero, to neurodevelopmental damage, to schizophrenia. Several hypotheses exist for the mechanisms by which flu exposure during a critical period of fetal development might lead to brain damage. These include increased risk for associated obstetrical complications, exposure to maternal antibodies or cytokines, heat shock, and stress. As described later, the literature on the relationship between stress and schizophrenia suggests that this factor, in particular, is a viable candidate as a neurodevelopmental factor in schizophrenia.

Genetics as a Source of Vulnerability Although there has long been a recognition that genetic factors play a substantial role in risk for schizophrenia (Gottesman, 1991), advances in genetic methods over the past decade have resulted in a more complex and refined understanding of the specific mechanisms through which genes might influence the risk for this and other psychiatric disorders. Current research in this area is focused on endophenotypes, candidate genes, gene–environment interactions, and epigenetics. A review of the genetic research on schizophrenia is beyond the scope of this chapter, but a few promising findings will be highlighted here. First, several candidate genes (COMT, DISC1, NRG1) have now been identified, and (more importantly) their associations with risk for schizophrenia have now been replicated (Lewandowski, 2007; Mackie, Millar, & Porteous, 2007; Tosato, Dazzan, & Collier, 2005). Importantly, each of these genes has been found to be associated with brain structure and function in a manner consistent with neurodevelopmental theories of schizophrenia. The COMT gene and its functional variant (Val158Met) have been linked to dopamine regulation in prefrontal areas of the brain (Gogos et al., 1998), DISC1 has been found to be associated with reduced gray-matter volume in the dorsolateral prefrontal cortex (Cannon et al., 2005), and NRG1 is involved in neuronal migration and connectivity as well as synaptic plasticity (Corfas, Roy, & Buxbaum, 2004). Despite these replicated findings on single-candidate genes, a recent study published in Science (Walsh et al., 2008) makes in eminently clear that the genetic basis for schizophrenia is multifaceted. In this study, microarray methods were used to examine the presence of rare microdeletions and microduplications across the genome in 150 individuals with schizophrenia and 268 controls. Novel individual deletions and duplications occurred in the DNA of schizophrenics at three times the rate noted in controls. These mutations were found predominantly in genes described as influencing neurodevelopment and were particularly prominent in cases of younger age of onset. Advances in genetic research continue to highlight the complex role of environmental factors in triggering the expression of genetic liabilities that confer vulnerability. This is particularly true if the vulnerability involves a

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polygenotype, as opposed to a single gene. Studies of monozygotic twins that are discordant for schizophrenia have illustrated the extent to which relatively subtle environmental factors can produce pronounced biological and behavioral differences (Stassen et al., 1999). Some of these environmental effects may be independent of the genotype, whereas others may reflect the impact of environmental factors on gene expression. For example, some prenatal insults may have a direct “mechanical” impact on the fetal brain that results in compromised function. Other prenatal events may affect the biochemical milieu, which, in turn, can alter gene expression (Schulkin, Gold, & McEwan, 1998). In either case, the end result is environmentally induced biological and behavioral changes that add complexity to the measurement of the phenotype. In the remainder of this chapter, we focus on the conceptualization of the neurodevelopmental processes involved in schizophrenia, with a special emphasis on developmental aspects of the expression of genotypes. Neuroscience has recently illuminated the mechanisms involved in gene expression as well as the potential role these processes can play in biological adaptation and maladaptation (Schulkin et al., 1998). In the following discussion, we explore the potential relevance of maturational processes and environmental factors for the behavioral expression of genetic liabilities.

Interactional Processes in the Neurodevelopment of Schizophrenia We have reviewed findings from several key areas that converge on two general conclusions: (1) that a substantial proportion of those at risk for schizophrenia have a congenital central nervous system vulnerability and (2) that subclinical manifestations of the vulnerability are measurable prior to the onset of clinical symptoms. The abnormalities in brain structure and the dysmorphic features observed in patients with schizophrenia point to fetal origins, in at least some cases. The cognitive and behavioral abnormalities manifested by children who are preschizophrenic indicate that the congenital liability is behaviorally expressed before the clinical syndrome arises. Although it is clear that congenital vulnerability to schizophrenia can be conferred through heredity, it also appears that its behavioral expression is often contingent upon environmental events. For example, a recent gene– environment study noted that genes regulated by hypoxia were predictive of schizophrenia only in cases where serious obstetric complications had also occurred (Nicodemus et al., 2008). Such interactional processes have been the core assumption of the diathesis–stress model, a central framework in theorizing about the etiology of schizophrenia for decades. Its basic assumption is that schizophrenia is the consequence of interactions among multiple factors—in particular, biological vulnerability and environmental stress. As our understanding of the neural mechanism mediating the effects of stress



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has increased in recent years, so has the heuristic value of the diathesis–stress model (Walker & Diforio, 1997).

The Role of Stress in the Etiology of Schizophrenia The notion that psychosocial stress can trigger or exacerbate psychopathology has received support from a substantial body of literature. Because a chief goal of much of this research has been to determine whether stress contributes to symptoms, the primary focus has been on stressful events that are not attributable to the individual’s behavior. Previous articles have reviewed the behavioral evidence for psychosocial stress effects on schizophrenia and spectrum disorders (Fowles, 1992; Norman & Malla, 1993). They conclude that the occurrence of stressors predicts subsequent worsening of symptoms. As noted previously, deleterious effects of stress in the premorbid period are suggested by findings that children at genetic high risk for mental illness (i.e., offspring of parents with major psychiatric disorders) show greater behavioral dysfunction if they are exposed to nonoptimal caregiving such as a disturbed adoptive parent or institutional child care (Tienari, 1991; Valone, Norton, Goldstein, & Doane, 1983; Walker, Cudek, Mednick, & Schulsinger, 1981; Walker, Downey, & Bergman, 1989). Extending this insight to the biological level, there is growing evidence of heightened secretion of the stress hormone cortisol in schizophrenia and other psychotic disorders (Walker, Mittal, & Tessner, 2008). Further, findings from our longitudinal study of adolescents who manifest behavioral signs of risk for psychosis (i.e., schizotypal personality disorder or prodromal signs) show that those who go on to develop a psychotic disorder within 4 years have a more dramatic developmental increase in cortisol secretion as compared to those who do not convert to psychosis (Walker, Brennan, Esterberg, & Brasfield, in press). Thus, heightened cortisol secretion precedes the onset of psychotic disorder in youth. It now appears likely that the role of stress in the etiology of psychopathology also extends to the prenatal period. Several studies have demonstrated that the rate of psychiatric disorder, including schizophrenia, is increased in the offspring of pregnant women exposed to stress. These studies have focused on the children of women exposed to a variety of stressors during pregnancy, including the death of a spouse (Huttunen, 1989), exposure to a major natural disaster (Watson & Mednick, 1998), and exposure to famine (St. Clair et al., 2005). A recent study of 1.38 million Danish births suggests that prenatal stress occurring in the first trimester was particularly likely to be associated with schizophrenia (Khashan et al., 2008). Laboratory studies of animals indicate that the effect of prenatal stress (restraint of the mother) on postnatal functioning is mediated by the hippocampal and hypothalamic–pituitary–adrenal (HPA) systems. When exposed to prenatal stress of sufficient magnitude, not only do subject animals manifest short-term behavioral changes and increases in corticosterone, but they

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also show an augmentation of subsequent behavioral and biological responses to stress (Levine, 1993; Plotsky & Meaney, 1993). Further, prenatal stress can produce hippocampal structural and cellular abnormalities in offspring (Maccari et al., 1995). Such hippocampal abnormalities have been observed in adult patients with schizophrenia (Jeste & Lohr, 1989; Waldo et al., 1994), and they are associated with younger age at onset of illness (Nasrallah & Olson, 1996) and higher levels of comorbid depression and anxiety, suggesting a particular sensitivity to stress (Smith et al., 2003).

Developmental Moderation of Vulnerability The pubertal period has been of intense interest to researchers in the field of psychopathology because it is during this period that the prodromal signs of schizophrenia and affective disorder typically emerge (Walker, Baum, & Diforio, 1998). Contemporary models of the neurodevelopmental processes involved in schizophrenia have attempted to account for this process. For example, Walker (1994) proposed that normal maturational changes in the circuitry linking cortical and subcortical regions may influence the behavioral expression of the brain abnormality underlying schizophrenia. In this model it is assumed that the congenital diathesis involves an abnormality in striatal dopamine activity and that functionally specialized striatal-cortical circuits come “on line” during different developmental periods. Striatal neuropathology can produce disruptions in the “late-maturing” circuits, such as the frontal and limbic circuits, that play a key role in higher-level cognitive functions. Thus, Walker theorizes that striatal dopaminergic abnormality manifests itself in distinct patterns of behavioral dysfunction during the course of development—pronounced neuromotor abnormalities early and late in life and psychotic symptoms in late adolescence/early adulthood. Weinberger (1987) also posits a developmental moderation model, suggesting that a congenital lesion in the dorsolateral prefrontal cortex may be the initial etiological factor in schizophrenia. The lesion is hypothesized to result in schizophrenic symptoms at the time of functional maturation of the dorsolateral prefrontal cortex, namely, during late adolescence/early adulthood. Prior to full maturation, however, the lesion is hypothesized to cause more subtle behavioral and emotional abnormalities—the types of deficits noted in premorbid histories of individuals with schizophrenia. Weinberger theorizes that the dorsolateral prefrontal lesion compromises the mesocortical dopamine system projecting from the prefrontal cortex to the midbrain. Hypodopaminergia in the cortex results in defect symptoms of schizophrenia (e.g., cognitive defects). Concomitant hyperdopaminergia in subcortical (mesolimbic) regions is assumed to result in positive symptoms of schizophrenia. Further, it is assumed the symptoms of schizophrenia arise in early adulthood because this is the time of maximum dopaminergic activity in the brain. To date, hormonal factors have been given relatively little attention in neurodevelopmental models of schizophrenia. Of course, adolescence is char-



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acterized by a dramatic change in the level of gonadol hormones (Susman, Worrall, Murowchick, Frobrose, & Schwab, 1996). In addition, adolescence may be associated with a normative increase in bio-behavioral sensitivity to stress. Our research and some other studies suggest that adolescence is associated with an increase in cortisol secretion (for a review, see Walker et al., 2008). It is therefore possible that maturational increases in HPA activity are one of the neurodevelopmental processes that potentiate symptom expression in vulnerable youth. The incorporation of the HPA system into neurodevelopmental models of developmental psychopathology yields a framework for explaining several key findings (Walker & Diforio, 1997). First, it suggests a biological mechanism for explaining the relation between psychosocial stress and psychopathology. Second, the demonstrated effect of persistent HPA overactivation on hippocampal morphology provides an explanation for the apparent worsening of the prognosis for schizophrenia when episodes recur or go untreated (Wyatt, 1995) and for the degenerative brain changes observed in some longitudinal studies of young patients with schizophrenia (DeLisi et al., 1997; Rapoport et al., 1997). Third, the apparent sensitivity of the HPA axis to prenatal events helps to explain the association between prenatal complications and risk for mental illness (Cantor-Graae, McNeil, Sjostrom, Nordstrom, & Rosenlund, 1995). Finally, neuromaturational changes in HPA function may be implicated in the gradually escalating behavioral problems observed in adolescents who subsequently show serious psychopathology (Neumann, Grimes, Walker, & Baum, 1995). Maturational changes could be a critical factor in triggering the expression of premorbid behavioral deficits, making adolescence/early adulthood the peak risk period for illness onset. This may be especially true of individuals with preexisting hippocampal abnormality and thus may explain the association between reduced hippocampal volume and earlier age at onset of psychotic symptoms (Nasrallah, Skinner, Schmalbrock, & Robitaille, 1994). Our understanding of the role of hormones in brain function has increased dramatically in recent years (Meyer et al., 1999; Plant & Shahab, 2002; Schulkin et al., 1998). It has been demonstrated that gonadal and adrenal hormones influence brain function through a variety of mechanisms. Some of the effects are nongenomic, whereas others are mediated by genomic mechanisms (Datson, Morsink, Meijer, & de Kloet, 2008; Picard, 1998). For example, in the realm of nongenomic effects, estrogen and progesterone can affect neurotransmitter activity by altering receptor sensitivity, neurotransmitter synthesis, and neurotransmitter release. Glucocorticoids can have similar effects. When the effects are genomic, they operate through intracellular mRNA transcription; thus the message from the genotype, in the form of protein synthesis, is moderated. Future research will undoubtedly unlock more of the mysteries of how the organism’s hormonal milieu influences the expression of genes. What these and related findings clearly indicate is that the hormonal changes produced by both normal maturation and environmental factors can

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play a significant role in determining how an inherited genetic vulnerability for a major mental illness is biologically and, therefore, behaviorally expressed. Figure 14.1 illustrates a hypothetical model of these causal pathways. The association between pubertal maturation and the onset of psychiatric symptoms may be attributable to hormonal influences on the expression of genes. These effects could be a consequence of genetically programmed gonadal and/or adrenal hormone changes. In addition, the individual’s environment has the potential for modulating adrenal hormone release across the lifespan. Thus, fluctuating levels of glucocorticoids might act in concert with gonadal hormones to determine the expression of genetic vulnerabilities. The genomic effects of hormones are, of course, not restricted to the peripubertal period. They are operative during fetal development and undoubtedly play a role in the effects of hormones on fetal brain development. One component or “subtype” of the inherited vulnerability for schizophrenia may be a heightened sensitivity to the deleterious effects of glucocorticoids on neurodevelopment. On the other hand, the diathesis for schizophrenia and other major mental disorders need not be inherited in order to be influenced by hormonal factors. A congenital brain abnormality produced by prenatal events could also be moderated in its expression by hormonal factors. Our findings, mentioned earlier, of an interactive effect of dysmorphic signs and cortisol secretion are consistent with this assumption.

Implications for Intervention At the present time, there are several ongoing studies of early intervention strategies under way in the United States and elsewhere (McGlashan & Johanessen, 1996). These studies have typically employed psychoeducational approaches with families in combination with medication trials immediately following the onset of psychotic symptoms. Preliminary results of these early intervention programs indicate that beneficial effects on psychotic relapse may not last over longer periods of follow-up (Linszen, Lenior, De Haan, Dingemans, & Gersons, 1998). Our model suggests that primary prevention might be a more useful strategy than early intervention with schizophrenia. To date, there are only a few systematic efforts under way to implement primary prevention programs for serious mental disorders, and outcome data are still tentative (Yung et al., 2007). But it is likely that the results of these trials will be available in the near future, and they will inspire the next generation of prevention research. It is likely that these future studies will draw on neurodevelopmental models of etiology as a basis for generating hypotheses about the critical periods and strategies for intervention (Beauchaine, Neuhaus, Brenner, & Gatzke-Kopp, 2008). For example, the model presented in this chapter suggests several poten-



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FIGURE 14.1.  Hypothesized neurodevelopmental influences on the course of schizophrenia.

tial strategies for prevention. First, the assumption that prenatal insults are involved in the etiological process implies the option of intervening to reduce fetal exposure to such complications. If it is the case that the genetic liability for schizophrenia confers a heightened sensitivity to factors that perturb fetal neurodevelopment, then the presence of a family history of schizophrenia might serve as one indicator for preventative intervention. Further, if heightened maternal steroids potentiate neurodevelopmental abnormalities, then pharmacological interventions aimed at buffering the fetus from the effects of steroid elevations might be plausible. Adolescence may be another key period for preventative intervention. Again, if hormonal changes are playing a role in triggering the expression of vulnerabilities during this period, the options for preventative intervention may entail modulating pubertal changes in adrenal and gonadal hormones. Psychosocial interventions that are effective in modulating stress reactivity may also be beneficial to adolescents at risk.

Directions for Future Research Although we have presented evidence that is consistent with a neurodevelopmental perspective on schizophrenia, there are many specific questions that remain unanswered in this area of research. Studies employing MRI technologies in high-risk groups, before and after the onset of schizophrenia, are necessary to determine the complex role of preexisting neuropathology and

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neurodegenerative processes in this disorder. The use of more refined measures of MPAs and the assessment of prenatal stressors linked to specific prenatal stages of development will help to better determine whether critical risk periods exist for the development of schizophrenia. We would also argue that more research is necessary on the potential role of the HPA axis in the diathesis–stress model of schizophrenia. Attention to the developmental phase of adolescence in terms of hormonal changes and stress responsivity would be a particularly fertile area of research and potentially could be linked with early-intervention or prevention programs designed to reduce the occurrence and severity of schizophrenia. Finally, the expanding area of gene expression research will have a significant impact on our conceptualization of the development of schizophrenia and all disorders with significant heritable components. We now recognize that genetic and environmental factors are in complex interaction from the very earliest stages of development. A promising strategy of research will be to examine the interactions of genetic and environmental effects (at molecular, cellular, neurological, hormonal, behavioral, familial, community, and societal levels) as they unfold over the process of development and culminate in the onset and course of schizophrenia.

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Neurobiology of smooth pursuit eye movement deficits in schizophrenia: An fMRI study. American Journal of Psychiatry, 161, 315–321. Valone, K., Norton, J. P., Goldstein, M. J., & Doane, J. A. (1983). Parental expressed emotion and affective style in an adolescent sample at risk for schizophrenia spectrum disorders. Journal of Abnormal Psychology, 92, 399–407. Velakoulis, D., Pantelis, C., McGorry, P. D., Dudgeon, P., Brewer, W., Cook, M., et al. (1999). Hippocampal volume in first-episode psychoses and chronic schizophrenia: A high resolution magnetic resonance imaging study. Archives of General Psychiatry, 56, 133–141. Waddington, J., & Buckley, P. (1996). The neurodevelopmental basis of schizophrenia. Austin, TX: Landes. Waldo, M. C., Cawthra, E., Adler, L. E., Dubester, S., Staunton, M., Nagamoto, H., et al. (1994). Auditory sensory gaiting, hippocampal volume, and catecholamine metabolism in schizophrenics and their siblings. Schizophrenia Research, 12, 93–106. Waldrop, M. F., & Halverson, C. F. (1971). Minor physical anomalies and hyperactive behavior in young children. In J. Helmuth (Ed.), Exceptional infant: Studies in abnormalities. New York: Brunner/Mazel. Walker, E. (1994). The developmentally moderated expression of the neuropathology underlying schizophrenia. Schizophrenia Bulletin, 20, 453–480. Walker, E., Baum, K., & Diforio, D. (1998). Developmental changes in the behavioral expression of vulnerability for schizophrenia. In M. Lenzenweger & B. Dworkin (Eds.), Origins and development of schizophrenia (pp. 469–492). Washington, DC: American Psychological Association. Walker, E. F., Brennan, P. A., Esterberg, M., Brasfield, J., Pearce, B., & Compton, M. (in press). Longitudinal changes in cortisol secretion and conversion to psychosis in at-risk youth. American Journal of Psychiatry. Walker, E., Cudek, R., Mednick, S. A., & Schulsinger, F. (1981). The effects of parental absence and institutionalization on the development of clinical symptoms in high-risk children. Acta Psychiatrica Scandinavica, 63, 95–109. Walker, E. F., & Diforio, D. (1997). Schizophrenia: A neural diathesis–stress model. Psychological Review, 104, 1–19. Walker, E. F., Downey, G., & Bergman, A. (1989). The effects of parental psychopathology and maltreatment on child behavior: A test of the diathesis–stress model. Child Development, 60, 15–24. Walker, E. F., Lewine, R. R. J., & Neumann, C. (1996). Childhood behavioral characteristics and adult brain morphology in schizophrenia. Schizophrenia Research, 22, 93–101. Walker, E., Lewis, N., Loewy, R., & Palyo, S. (1999). Motor dysfuntion and risk for schizophrenia. Development and Psychopathology, 11, 509–523. Walker, E., Mittal, V., & Tessner, K. (2008). Stress and the hypothalamic pituitary adrenal axis in the developmental course of schizophrenia. Annual Review of Clinical Psychology, 4, 189–216 . Walker, E. F., Savoie, T., & Davis, D. (1994). Neuromotor precursors of schizophrenia. Schizophrenia Bulletin, 20, 453–480. 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, 539–543. Watson, J., & Mednick, S. A. (1998, November). Depressive symptoms in offspring following severe prenatal stress. Paper presented at the annual meeting of the Society for Research in Psychopathology, Boston. Weinberger, D. R. (1987). Implications of normal brain development for the pathogenisis of schizophrenia. Archives of General Psychiatry, 44, 660–669. Weinberger, D. R. (1995). Schizophrenia: From neuropathology to neurodevelopment. Lancet, 346, 552–557. Wyatt, R. J. (1995). Antipsychotic medication and the long-term course of schizophrenia. In C.

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L. Shriqui & H. A. Nasrallah (Eds.), Contemporary issues in the treatment of schizophrenia (pp. 385–410). Washington, DC: American Psychiatric Association. Yung A. R., Killackey, E., Hetrick, S. E., Parker, A. G., Schultze-Lutter, F., Klosterkoetter, J., et al. (2007). The prevention of schizophrenia. International Review of Psychiatry, 19, 633–646. Zipursky, R. B., Lim, K. O., Sullivan, E. V., Brown, B. W., & Pfefferbaum, A. (1992). Widespread cerebral gray matter volume deficits in schizophrenia. Archives of General Psychiatry, 49, 195–205.

Chapter 15

Vulnerability to Schizophrenia in Adulthood Michael T. Compton and Philip D. Harvey

Schizophrenia is a devastating mental illness that has multiple direct and indirect costs to the individuals afflicted and to society in general. This illness has been a puzzle to researchers and clinicians because of the difficulty in its treatment and the long-standing problems in identifying even the basic components of the causes of the disorder. While the study of some aspects of the disorder, such as the prevalence, symptoms, course, and outcomes, has led to a comprehensive knowledge base, other aspects of the illness have remained elusive. Most elusive is the cause of the illness, including the combinations of genetic and environmental factors that lead to the expression of schizophrenia as a complex phenotype. This chapter presents information about factors that influence vulnerability for schizophrenia, with a focus on onset of the illness during late adolescence and early adulthood (as opposed to less common early- and late-onset variants of the disorder). After a brief overview of basic epidemiology of the illness and a description of its phenotype and phenomenology, the strengths and weaknesses of the broadly accepted diathesis–stress model are presented. Then, domains of vulnerability, in terms of both genetic factors and experiential/environmental factors, are reviewed, along with a summary of risk factors and trait vulnerability markers, or endophenotypes. Finally, the characteristic sequence of onset of the illness, including the premorbid phase, the prodrome, and the period of untreated psychosis, are described, especially as they pertain to potential future prevention efforts.

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Epidemiology: Prevalence, Incidence, and Gender and Ethnic Distributions Although it is difficult to make absolute statements about the prevalence of many relatively rare disorders, the disabling nature of schizophrenia as it is currently defined means that most cases can be identified. Recent decades have witnessed advances in case identification and case finding for epidemiological studies, largely attributable to well-defined and reliable diagnostic criteria (such as those available in the International Classification of Diseases and the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association, 2000), as well as semistructured examination tools used to reliably confirm diagnoses (such as the Present State Examination, the Structured Clinical Interview for DSM Axis I Disorders, and the Composite International Diagnostic Interview). The point prevalence of schizophrenia is roughly 3–8 per 1,000 (Eaton & Chen, 2006). Worldwide estimates of the prevalence of schizophrenia generally cite an overall lifetime prevalence of approximately 1%. Prevalence estimates and symptomatic presentation do not appear to vary markedly across different countries (World Health Organization, 1972). The prevalence has been reported to be slightly higher in isolated areas where the genetic pool is compacted because of geographic isolation (Kendler et al., 1993). The incidence of schizophrenia is about 0.1–0.7 per 1,000 per year (Eaton & Chen, 2006; Goldner, Hsu, Waraich, & Somers, 2002), and the point prevalence is usually more than 10 times the annual incidence, indicating the chronic nature of schizophrenia (Eaton & Chen, 2006). Populationbased incidence studies suggest that the peak age at onset is shifted across the genders, with males typically having an earlier age at onset. Some evidence suggests that not only do incidence rates vary over the lifetime risk period (i.e., higher incidence in late adolescence and young adulthood) and over the lifetime risk period by gender (i.e., later age at onset for women), but incidence rates may be higher for males more generally (Kirkbride et al., 2006; Thorup, Waltoft, Pedersen, Mortensen, & Nordentoft, 2007). Other research indicates that although incidence does not appear to vary markedly across countries, ethnic minority groups may have a higher incidence (Fearon et al., 2006; Kirkbride et al., 2006), consistent with the notion that immigration, and consequent discrimination and social adversity, may be risk factors, as discussed below.

Phenotype and Phenomenology: Symptoms, Cognitive Dysfunction, Age at Onset, and Course Schizophrenia as it is currently conceptualized is a disorder with a polythetic structure, meaning that the signs of illness are variable across individuals and



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some combination of these signs is required to identify the presence of the illness, with no single pathognomonic indicator or set of signs. In order to meet current American or worldwide criteria, an individual must show at least two different symptoms, including delusions (fixed false beliefs), hallucinations (aberrant perceptual experiences in any sensory modality, but usually in the auditory modality), impairments in communication or affect, bizarre behavior, or negative symptoms. If the delusions or hallucinations are of a particular type, such as those reminiscent of the first-rank symptoms defined by Kurt Schneider (1959), they can be the only active sign of the illness. Patients also must have signs of a 6-month or greater decline in their overall level of functioning, and the symptoms cannot be due to alcohol or drug abuse, the presence of a neurologic or general medical condition, or a primary affective disorder. This conception of schizophrenia has its basis in the group of illnesses termed “dementia praecox,” defined by Emil Kraepelin (1896). There are several aspects of schizophrenia that remain outside of the diagnostic criteria that merit attention. Extreme functional deficit is common in schizophrenia, and only 30% of patients with schizophrenia are ever able to live independently (with many being markedly socially isolated and impoverished). This level of functional deficit does not appear to have changed meaningfully over the past 100 years (Hegarty, Baldessarini, & Tohen, 1994). The vast majority of patients with schizophrenia, if not all (Wilk et al., 2004), also have significant cognitive impairments that can interfere substantially with academic, vocational, and interpersonal functioning. It is interesting that the diagnostic criteria for this illness, which do not contain any mention of cognitive impairment, still lead to the identification of a group in which cognitive impairments are present in nearly every identified case. As described below, the potential for cognitive impairments to be transmitted by susceptibility genes and to worsen during certain developmental stages of the illness is increasingly recognized. When Kraepelin defined dementia praecox over 100 years ago, incorporated into the term was his idea about the prototypical onset age. “Praecox” denotes late adolescence/early adulthood, and his belief was that this illness— characterized by a deteriorating course, cognitive and functional impairment, and a wide array of other symptoms—had its typical onset during these years. Although later clinicians, such as Eugen Bleuler (1911), disagreed with Kraepelin about the absoluteness of the age at onset of the illness, considerable research has indicated that the majority of individuals with schizophrenia have an onset of psychotic symptoms during the early adult years. Schizophrenia can have an onset age, according to current criteria, that ranges from early childhood to the end of life. However, the typical age at onset of schizophrenia, as marked by the greatest new incidence of cases with the illness, is late adolescence and early adulthood. Individuals who develop schizophrenia during this time period have a number of characteristics that separate them from those with other illnesses and from normal populations. Earlier age at onset is associated with a more adverse lifetime course, a

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poorer functional outcome, and a reduced likelihood of positive response to treatment. Patients with early onset (i.e., during adolescence) are more likely to have reduced academic and social achievement as well as a greater likelihood of having relatives with schizophrenia-spectrum conditions (Keefe et al., 1987; Zigler, Glick, & Marsh, 1979). Interestingly, in patients with a family history of schizophrenia, female patients are reported to have the same onset age as males (Albus & Maier, 1995), suggesting that family history may exert a stronger influence on onset age than gender. The course of schizophrenia is very heterogeneous. Many patients have a relapsing and remitting course of acute positive symptoms, though negative symptoms and cognitive dysfunction tend to be more persistent. A smaller proportion of patients have a persistent, unremitting (and in some cases, treatment-resistant) course with poor outcomes. An even smaller proportion have a course characterized by complete recovery. The fourth edition of the DSM (DSM-IV; American Psychiatric Association, 2000) provides five course specifiers that can be applied after at least 1 year has elapsed since the initial onset of active-phase symptoms: •• Episodic with interepisode residual symptoms, with or without prominent negative symptoms. •• Episodic with no interepisode residual symptoms. •• Continuous, with or without prominent negative symptoms. •• Single episode in partial remission, with or without prominent negative symptoms. •• Single episode in full remission. The long-term course of schizophrenia is typically marked by substantial psychosocial disability; educational progress is often disrupted (in part due to the usual age at onset of the disorder), more than 70% of people with the disorder remain unemployed, approximately 70% never marry, and most people with schizophrenia have limited social contacts and supports. In line with the variability observed in terms of course, many researchers assume the complex and heterogeneous phenotypes currently lumped as “schizophrenia” to be several different diseases that share behavioral features. There is enormous heterogeneity in this illness in terms of symptom presentation, clinical course, response to available treatments, family history of the illness, age at onset, mode of onset, premorbid adjustment, and other factors. In addition to the heterogeneity observed in clinical cases, accumulating evidence suggests that the psychosis phenotype is dimensionally distributed in the population with decreasing prevalence by increasing severity. Such a continuum of psychosis (Krabbendam, Myin-Germeys, Bak, & van Os, 2005; van Os, Hanssen, Bijl, & Ravelli, 2000) includes clinically insignificant self-reported psychotic symptoms in the general population (Johns et al., 2004; Wiles et al., 2006); limited psychotic experiences induced by substances or severe stressors; psychosis proneness, schizotypy, or schizotypal personality features (Raine, 2006); schizotypal personality disorder;



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and primary psychotic disorders, such as schizophrenia and related clinical disorders.

The Diathesis–Stress Model Because it has proven possible to identify several potential risk factors for the development of schizophrenia retrospectively and because no single factor appears to be a necessary and sufficient cause of the disorder, research has been aimed at explaining and predicting the factors associated with vulnerability to the development of schizophrenia. One of the most commonly applied models is the diathesis–stress model (Zubin & Spring, 1977), which suggests that there is a necessary but not sufficient predisposing factor for the illness, combined with a similarly necessary but not sufficient stressor that interacts with the diathesis, to cause the development of the illness. Such a predisposition could be genetically transmitted or acquired in early life, while the stressor could be psychological or physiological (Harvey, Walker, & Wielgus, 1986). Predispositions could have measurable psychological or physiological correlates, with the former being in the domains of cognitive deficits, personality traits, or behavioral tendencies. Biological correlates of the predisposition could be found in the domains of abnormal brain structure or activity, abnormal patterns of physiological reactivity to environmental stimuli, or neurocognitive markers, in addition to potential genetic markers.

Strengths of the Model The strengths of the diathesis–stress model are clear in that schizophrenia appears to have multiple domains of potential causes and to consist of several unique but similar phenotypic entities. This model helps to direct research attention to the fact that the symptomatic diversity in schizophrenia may be associated with diversity in etiological factors. The evidence regarding the etiology of schizophrenia has indicated that it is unlikely that a single factor is the root cause of all cases of the illness. For example, individuals who share similar potential predispositions (e.g., monozygotic twins) vary in the extent to which they express the full syndrome (Gottesman & Shields, 1984). Thus, research using this perspective might study individuals who share a common early predisposing factor and relate variation in their outcomes to differences in their life experiences or stressors. A similar approach could be applied to individuals who were exposed to similar stressors (e.g., maternal exposure to influenza or famine) in order to relate variations in their outcomes to variations in potential predisposing factors.

Weaknesses of the Model The principal weakness of the diathesis–stress model is that little is known precisely about either potential predispositions to schizophrenia or stressors

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that could activate these predispositions, although the sections that follow will review our current understanding of these domains. This approach often has been applied post hoc when either a risk factor or experience can be identified, in the absence of systematic understanding of the other domains. As a result, this framework is often used for explanatory purposes more than for predictive ones. It is possible that there is a biological factor, as yet undiscovered, that fully accounts for many cases of schizophrenia regardless of environment or experience. Similarly, certain experiential factors might cause schizophrenia in anyone exposed. A rigid application of the diathesis–stress model may inadvertently suppress research on factors that might prove to be necessary and sufficient factors that cause some cases of the illness.

Domains of Vulnerability Factors Factors that increase risk for schizophrenia arise from several different domains. These include factors that appear to be genetic, prenatal but not genetic, and postnatal experiential factors. The postnatal experiential factors include both general social experiences (e.g., social adversity) and more specific environmental events (e.g., adverse early life experiences, detrimental family interaction styles). Each of these domains has received considerable research attention, and there is reason to believe that in each instance they may be important factors in the development of some cases of schizophrenia.

Genetic Factors Genetic studies of schizophrenia generally have taken two forms. The first include large-scale population genetic studies that were conducted during the 1950s through the early 1980s. These studies identified the level of risk in the population and in family members of index cases (i.e., probands) with schizophrenia, attempting to rule out alternative population-wide explanations for the origin of the illness. These studies used family, twin, and adoption study methods. The second wave of genetic studies examined the association between the presence of the illness and the expression of various potential susceptibility genes. Facilitated by the mapping of the human genome, these studies have examined the occurrence of various preidentified gene variants in people with schizophrenia, as compared to healthy populations, and also have employed genome-wide association methods to identify associations between the occurrence of certain gene variants and the presence of schizophrenia. A similar strategy, referred to as the quantitative trait locus method, examines the correlation between the severity of impairment in domains such as symptoms or cognitive performance and the occurrence of various genotypes. One of the features of these new genetic studies is that they are often aimed at intermediate phenotypes, such as specific cognitive impairments. As



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discussed later, the heritability of schizophrenia itself does not fit neatly into Mendelian models, so identification of heritable subcomponents of the illness may be a strategy to identify the cascade of vulnerability factors, possibly arising from combinations of susceptibility genes, that result in schizophrenia.

Population Genetics of Schizophrenia Schizophrenia has been known to be familial since the earliest descriptions of it. Although “familial” does not necessarily mean genetic, adoption studies, focusing on adopted-away children of patients with schizophrenia, have suggested that their risk for illness is the same as that of children of parents with schizophrenia who were reared at home (Kety, Rosenthal, Wender, & Schulsinger, 1968). Large-scale studies involving relatives of affected individuals suggest a pattern of inheritance that is incompatible with a single-gene model with full penetrance (i.e., the actual genetic transmission of the trait) or expressivity (i.e., the extent to which the coded trait occurs in the phenotype of genetic carriers), or a simple polygenic model. As shown in Table 15.1, even monozygotic twins are concordant for the illness at levels much less than would be expected from any typical genetic inheritance model. Twin studies that examined differences in the concordance rates of monozygotic and dizygotic twins have suggested estimates of heritability in the range of 80% (though it should be noted that recent evidence suggest that gene–environment interactions may make up the bulk of this proportion; European Network of Schizophrenia Networks for the Study of Gene–Environment Interactions, 2008). Although relatives of individuals with schizophrenia are over 10 times as likely to develop the illness as compared to individuals without an affected relative, only about 30% of patients with schizophrenia have a relative who has some agreed-upon variant of the illness. Furthermore, an average concordance rate of 50% for monozygotic twins could be produced by some variants of the illness being determined completely by genetic factors and other vari-

TABLE 15.1. Risks for Schizophrenia as a Function of Relatedness to a Person with Schizophrenia Relationship Monozygotic co-twin Dizygotic co-twin Nontwin sibling Child Grandchild Spouse General population

Risk (%) 44.30 12.08   7.30   9.35   2.85   1.00   0.87

Note. Adapted from Gottesman and Shields (1984). Copyright 1984 by Cambridge University Press. Adapted by permission. Risk is expressed as a percentage.

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ants having a small or negligible genetic component. Given the heterogeneity of the symptoms and course of the illness, as reflected in the polythetic diagnostic criteria, this possibility does merit consideration. Alternative variants of schizophrenia, referred to as “schizophreniaspectrum” conditions (Kety, 1985), could be hypothesized to reflect the incomplete expression of the genetic predisposition for schizophrenia. For example, some individuals with affective flattening and social anhedonia may possess some of the genetically transmitted vulnerabilities to the illness without ever developing the full condition because they did not inherit other required traits. For instance, the Roscommon Family Study (Kendler et al., 1993) examined the concordance of various “spectrum-related” traits, including schizotypal symptoms, attentional deficits, and functional disability (indexed by unemployment). Many of these traits were much more highly concordant in first-degree relatives of probands with schizophrenia than in healthy samples.

An Example of the Genetics of Cognitive Endophenotypes A recent large-scale study aimed at endophenotypes—the Consortium on the Genetics of Schizophrenia (COGS)—examined the heritability of various prototypical cognitive impairments observed in schizophrenia within families with an individual with schizophrenia and in unaffected comparison families. The cognitive ability domains examined included domains that were known to be stable across clinical state in people with schizophrenia, present in nonpsychotic relatives of people with schizophrenia, not affected by treatments for the illness, possibly heritable based on previous studies, and suitable for use in large-scale genetics studies (Gur et al., 2007). The background review of the literature on potential cognitive ability domains revealed several important findings. Several different ability domains were identified as the most promising candidates, including attention (in particular vigilance), verbal learning and memory, and working memory. In addition, several subtests from a computerized cognitive assessment battery were examined, including face memory and affect recognition, spatial memory, and spatial reasoning and problem solving. Across these different cognitive ability domains, the literature review found that heritability estimates for performance on most tests were in the range of h = .50, with higher estimates in populations with more variance in scores, such as older adults. These data indicate that, in general, cognitive abilities share considerable variance across family members and the correlation within family members in terms of cognitive performance is much closer than many other traits. All of these potential cognitive endophenotypes were tested in a preliminary study. The study was based on 183 nuclear families determined by the presence of an individual with schizophrenia. Each family was required to have both parents available for assessment—as well as the index case and at least one unaffected full sibling. All of the cases in the



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study were tested with an assessment battery based on the cognitive domains described above. As might be expected from a systematic large-scale study, the estimates of heritability were slightly lower than those from the smaller studies that had preceded it. The range of heritability estimates was h = .24–.55 for performance-based cognitive measures and lower for putative psychophysiological measures (h = .10 for P50 suppression and h = .32 for prepulse inhibition; Greenwood et al., 2007). These data still suggest substantial levels of genetic influence on various aspects of cognitive functioning. The conclusion from the first stage of COGS is that classical cognitive impairments of schizophrenia are substantially heritable. These findings are even more interesting because of the nature of the assessments performed. The tests with higher heritability estimates were standard neuropsychological measures, not specialized neuroscience tests. It is not clear whether the higher heritability of the standard measures is attributable to their standardization or because they measure content that is intrinsically more heritable. Future research clearly will be focused on identification of genetic variation in experimental procedures as well as clinical ones.

Molecular Genetics of Schizophrenia With the mapping of the human genome and the development of sophisticated DNA- and RNA-oriented techniques to identify the presence of genetic variants, genetic combinations, and levels of gene expression, it has become possible to perform sophisticated hypothesis-driven studies of the relationships between genes and the presence or absence of schizophrenia and related disorders. Several potential candidate genes have been identified and found, in relatively small samples, to be associated with the presence of the schizophrenia phenotype. However, one issue that has not changed since the early days of genetic studies in schizophrenia is that most of these candidate genes have not shown widely replicated associations to schizophrenia across studies. Further, several of these genes have multiple single nucleotide polymorphisms (SNPs) and can co-aggregate with one another in organizations called “haplotypes.” This leads to increasing complexity and the possibility that different studies aimed at susceptibility genes in specific chromosomal locations may be studying slightly different samples of genetic material. Despite the strong suggestion that schizophrenia is genetic in nature and that several of its features are also heritable (such as cognitive impairments and symptom types), a recent large-scale study—involving 1,870 cases and 2,002 comparison subjects of unrelated individuals of European ancestry focused on 14 a priori selected genes—failed to find a single gene, SNP, or haplotype with significant association to schizophrenia (Sanders et al., 2008). While several of these genes had small positive odds ratios that could be associated with modest contributory effects to schizophrenia, none had an association strength that would likely confer vulnerability to the disorder on its own.

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These findings may have several important implications. Previous findings of association in smaller studies still may have identified valid subsets of the illness with heritability. Second, the individual features of the illness may be more heritable than the illness itself, as the illness is marked by considerable heterogeneity. Finally, the co-occurrence of multiple different gene variants may be the mechanism of inheritance of the illness, and identification of such combinations would require a very large sample for these hypotheses to be tested. Of note, recent research suggests that rare spontaneous (rather than inherited) microdeletions and microduplications in genes related to the development of the nervous system may be more common among people with schizophrenia, likely accounting for a considerable portion of phenotypic variations (Walsh et al., 2008).

Experiential/Environmental Factors Both experience and environment include exposure to both physiological factors (toxins, deprivation states) and psychological events. The latter can be discrete traumata or constant and cumulative stressors such as those associated with daily exposure to a stressful environment. These events and exposures (for a more detailed review, see Dean & Murray, 2005) can occur between conception and birth or between birth and the development of schizophrenia.

Prenatal Experiential/Environmental Factors Prenatal factors have been studied as risk factors for the development of schizophrenia. Maternal exposure to influenza (Takei et al., 1996) and famine (St. Clair et al., 2005; Susser et al., 1996) have been shown to increase the risk for schizophrenia. Specifically, having a mother who contracts influenza during the second trimester of gestation appears to be a factor that increases the likelihood of developing schizophrenia. In a study by Takei et al. (1996), for every 100,000 cases of influenza during the second trimester, there was a 12% increase in the rates of schizophrenia. Furthermore, the incidence of schizophrenia in the general population has also increased during disasters that led to maternal physiological stress, such as the Dutch Hunger Winter of 1944–1945 (Susser et al., 1996). While an increase in population incidence of schizophrenia associated with a famine or a pandemic may appear to suggest that the stressors alone increase risk for the development of the illness, it cannot be determined if there are genetic diatheses that are also involved. This stressor alone obviously could not be a necessary and sufficient cause of schizophrenia. In fact, Takei et al. (1996) reported that only 1.4% of the total cases of schizophrenia could be attributed to possible influenza-related causes. Furthermore, it has been reported that affective disorders also increase in prevalence among individuals exposed to influenza in utero during the second trimester (Machon, Mednick, & Huttinen, 1997). Finally, stress alone,



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including exposure to general environmental stress (e.g., the Nazi occupation of the Netherlands), is associated with increased risk for schizophrenia as well (van Os & Selten, 1998). Thus, both biological and psychological experiences of the mother and developing fetus appear to have the potential to lead to changes in fetal neurodevelopment associated with increased risk for schizophrenia. A number of indicators have suggested that the second trimester is the critical stage for the occurrence of prenatal incidents that influence the development of schizophrenia. For example, brain regions that develop rapidly during this trimester and require appropriate cell migration (e.g., the corpus callosum) are found to be abnormal in schizophrenia (Bunney, Potkin, & Bunney, 1995). In addition, abnormalities in body regions other than the brain that develop during the second trimester (e.g., dermatoglyphic symmetry) are found to be correlated with the presence of other minor physical anomalies and are elevated in patients with schizophrenia (Fananas et al., 1996). Because there have been some studies that failed to replicate the findings of second trimester influenza and schizophrenia (Morgan et al., 1997) and the number of patients in which the occurrence of influenza can be demonstrated is quite small, caution needs to be applied before second trimester maternal stress or illness is used as an intervention point for the primary prevention of schizophrenia.

Postnatal Experiential/Environmental Factors Postnatal environmental factors influencing the development of schizophrenia have proven difficult to identify. Toxic exposure, head trauma, and drug use in general appear remarkably unassociated with increased risk for enduring schizophrenia. Exposure to some drugs in adults, especially drugs that have effects on the glutamatergic system, appears to have the potential to cause states that resemble schizophrenia (Abi-Saab, D’Souza, Moghaddam, & Krystal, 1998). These drugs, like phencyclidine (PCP, or “angel dust”) and ketamine (“special K”), have been drugs of abuse for years and have been shown in experimental studies to exacerbate symptoms of schizophrenia and to cause transitory psychotic experiences in normal individuals (Krystal et al., 1994). The rate of exposure to these drugs is relatively low in the population as a whole and in individuals who develop schizophrenia, and it therefore cannot be considered a general risk factor for the illness. Perhaps even more important than compounds acting on the glutamatergic system, more widely used recreational drugs may be implicated in modifying risk for the development of schizophrenia. Most prominently, smoking cannabis has been linked to the development of schizophrenia in those predisposed (Degenhardt & Hall, 2006; Weiser & Noy, 2005). Population-based studies have indicated an increased rate of premorbid cannabis use in individuals who developed schizophrenia (Weiser et al., 2003). While it has been argued that an acute cannabis-related psychosis may simulate schizophrenia,

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the bulk of the evidence suggests that the effects of cannabis use, especially in adolescence, may be to exacerbate genetically related predispositions for the later development of schizophrenia. Despite the early primacy of psychological theories of the etiology of schizophrenia, including theories focusing on interpersonal interaction and communication, these potential causes were largely set aside while genetic factors were explored. However, recent evidence suggests that there may be experiential factors, such as urban birth/upbringing and being a recent immigrant, that affect population-wide risks of developing schizophrenia. Living in urban areas is associated with a slightly increased risk of schizophrenia. The effects of urban residence are exaggerated in individuals who have cognitive and social deficits, leading to a 9-fold increase in the effects of urban residence on schizophrenia in impaired cases as compared to unimpaired ones (Weiser et al., 2007). The majority of the data indicate that living in urban areas is associated with a higher risk for the development of schizophrenia and does not reflect a residential drift. Immigration as a risk factor for schizophrenia has been noted in several different countries. For example, being a Caribbean immigrant of African origin has been reported to be correlated with increased risk for the development of schizophrenia in the United Kingdom. Hypotheses about this relationship generally focus on the stressful effects of being different in appearance and culture and being in a minority situation characterized by discrimination and social adversity. Interestingly, very recent confirmatory evidence for this hypothesis originated from a study conducted in Israel (Weiser et al., 2008). Although the majority of Israelis are immigrants, most arrived in Israel from relatively similar cultures and with relatively consistent cultural beliefs. In a study of over 650,000 adolescents screened by the national draft board, the risk for schizophrenia in a first- or second-generation immigrant was significantly increased. The ethnic group with the highest risk was Ethiopian immigrants, who are the most culturally and physically distinct of the various immigrants who moved to Israel. Thus, the influence of immigration on schizophrenia risk may be mediated through the stress associated with being immediately identifiable as different and potentially being discriminated against as well. The results of these studies are consistent with the idea that identifiable environmental stressors can interact with potential predispositions to result in schizophrenia. These findings provide support for the utility of the diathesis– stress conception of vulnerability.

Risk Factors and Trait Vulnerability Markers While the foregoing has focused on several well-established risk factors, other research has identified a number of trait markers that probably do not cause schizophrenia per se but rather indicate vulnerability. Thus, risk factors refer to antecedents of the disorder, whereas vulnerability markers, or endophe-



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notypes, are biological or neuropsychological markers of the disease or the genetic liability for the disease.

Risk Factors As described above, a number of factors are currently considered to be risk factors for schizophrenia, including family history of a psychotic disorder in a first-degree relative, maternal exposure to influenza and other infections (Babulas, Factor-Litvak, Goetz, Schaefer, & Brown, 2006; Brown et al., 2005), poor prenatal nutrition or maternal exposure to famine, urban birth/upbringing, adolescent cannabis use, being a recent immigrant, and social adversity (Cooper et al., 2008; Wicks, Hjern, Gunnell, Lewis, & Dalman, 2005). Other risk factors may include advanced paternal age at conception; unwanted pregnancy; prenatal maternal exposure to severe adverse life events (Khashan et al., 2008); Rh incompatibility, hypoxia, fetal growth restriction, and other pregnancy/delivery complications (Cannon, Jones, & Murray, 2002; Gilmore & Murray, 2006); birth during winter or spring months; abnormal fetal growth and low birth weight; childhood central nervous system infections (Dalman et al., 2008; Rantakallio, Jones, Moring, & Von Wendt, 1997); separation from or death of a parent during childhood (Morgan et al., 2007); and detrimental neighborhood-level factors (Kirkbride et al., 2007). Obviously, some currently recognized risk factors (e.g., urban birth or upbringing, birth during winter or spring months) are proxies for exposures more directly linked to causality. Other risk factors are likely directly tied to specific genetic risk, such as microdeletions of chromosome 22q11, which causes velo-cardio-facial syndrome (Murphy, Jones, & Owen, 1999), or nondeletion variants of individual genes within the 22q11 region (Liu et al., 2002). Other risk factors that are ostensibly environmental may interact with risk genes to make some individuals vulnerable to the illness. This phenomenon is exemplified by recent findings on gene–environment interactions, such as the moderating effect of the catechol-O-methyltransferase (COMT) Val158Met functional polymorphism on adolescent-onset cannabis use (Caspi et al., 2005) and an interaction between this same polymorphism and stress exposure (Stefanis et al., 2007). Ongoing research to identify risk factors is critical, given its impact on elucidating pathophysiology and informing conceptions of prevention.

Endophenotypes A construct similar to risk factor is risk marker or vulnerability marker. As noted earlier, these biological correlates of the predisposition or diathesis toward developing a psychotic disorder may be found in the domains of abnormal brain structure or activity, abnormal patterns of physiological reactivity to environmental stimuli, or neurocognitive markers. Gottesman and Gould (2003) put forth criteria for a related concept, the endophenotype

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(also referred to as vulnerability marker, elementary phenotype, or intermediate phenotype; Adler, Freedman, Ross, Olincy, & Waldo, 1999; Kremen, Tsuang, Faraone, & Lyons, 1992). Such phenotypes may be particularly useful in psychiatric genetics, given that they are thought to be more closely linked to genetic underpinnings than are psychiatric syndromes. That is, endophenotypes are more elementary phenomena, and the number of genes required to produce variations in these traits may be fewer than those involved in producing a psychiatric syndrome (Flint & Munafò, 2007). Endophenotypes are (1) associated with the illness in the population, (2) heritable, (3) primarily stateindependent (manifesting in an individual whether or not the illness is active), (4) found to co-segregate with the illness within families, and (5) found in unaffected family members at a higher rate than in the general population (Gottesman & Gould, 2003). In addition to the vulnerability markers mentioned previously (e.g., attention, verbal learning, and working memory impairments being studied in the COGS group; Braff, Freedman, Schork, & Gottesman, 2007; Greenwood et al., 2007), others include minor physical anomalies and dermatoglyphic abnormalities, neurological signs and neuromotor deviations, eye-tracking dysfunction involving smooth-pursuit eye movements and the antisaccade task, and a number of electrophysiological findings. Other putative vulnerability markers, such as olfactory identification deficits, the inability to taste phenylthiocarbamide, blunted skin flush response to niacin, impaired facial affect recognition, and deficits in the cognitive process known as theory of mind, to name a few, require additional investigation. Research on vulnerability markers not only helps to elucidate the genetic underpinnings and neurodevelopmental trajectory of psychotic disorders but also may inform efforts to refine the targeting of future preventive interventions. For example, risk-prediction strategies aimed at individuals at “ultrahigh risk” or exhibiting “at-risk mental states” assumed to represent the prodrome may be enhanced by incorporating multiple risk markers into multivariable models. Several studies suggest that composite phenotypes, such as those incorporating minor physical anomalies and neurological soft signs (John, Arunachalam, Ratnam, & Isaac, 2008), or a combination of electrophysiological markers (Price et al., 2006), improve accuracy in predicting group membership (patient vs. unaffected controls). Future efforts require the testing of such multivariable risk-prediction models in those at risk for schizophrenia, with hopes of establishing a basis for risk stratification that informs preventive efforts. Two types of vulnerability markers, cognitive impairments and psychophysiological abnormalities, are reviewed briefly below.

Cognitive Impairments A number of cognitive impairments have been identified as likely endophenotypes. Patterns of cognitive deficits have been shown to be present in indi-



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viduals who later develop schizophrenia. In addition, patterns of cognitive impairments can be detected in individuals who are empirically at high risk for schizophrenia. These deficits are mainly in attention, vigilance, and accurate perception of rapidly presented information, especially under distracting conditions. These same deficits have been reported in children of patients with schizophrenia and in the adult relatives of individuals with schizophrenia (Harvey et al., 1986). One key area of cognitive dysfunction is that of vigilance or sustained attention. Deficits in the ability to process a rapidly presented series of visual stimuli and correctly identify a predetermined target stimulus have been reported in potentially vulnerable individuals for years. Children of patients with schizophrenia (Cornblatt & Erlenmeyer-Kimling, 1985), as well as first-degree relatives of patients with schizophrenia (Keefe et al., 1997), exhibit such deficits. These deficits typically have been detected with various versions of the continuous performance test (CPT). Findings suggest that vigilance deficits are one of the most consistently detected cognitive impairments in individuals who are potentially vulnerable to schizophrenia. Deficits in vigilance may be correlated with the presence of other vulnerability markers. For example, Keefe et al. (1997) found that adult first-degree relatives of patients with schizophrenia who manifested performance deficits on the CPT were also likely to manifest schizotypal personality features. CPT deficits detected in early adolescence may be powerful predictors of vulnerability to the development of adult-onset schizophrenia (Cornblatt & Malhotra, 2001). Deficits in the ability to identify rapidly presented visual information have been reported in schizophrenia for 40 years (Neale, McIntyre, Fox, & Cromwell, 1969). While there have been extensive debates about the underlying mechanism of these deficits, their relationship to vulnerability to schizophrenia appears clear. Likewise, poor performance on tests of vulnerability to the effects of backward masking appears linked to vulnerability to schizophrenia (Green, Nuechterlein, & Mintz, 1994). Deficits are seen both in patients with schizophrenia (Rund, 1993) and people with schizophrenia-spectrum disorders (Braff, 1981). Some studies have not found a strong relationship between poor performance and schizophrenia (Green et al., 1994), so this potential marker may be more limited in its predictive value than other aspects of attention and rapid visual processing. Excessive vulnerability to the effects of irrelevant distracting information during information processing appears to be related to risk for schizophrenia. Distractibility appears to be stable over time in patients with schizophrenia (Harvey, Docherty, Serper, & Rasmussen, 1990) and across variations in clinical state, and patients who respond better to treatment with conventional antipsychotic medications appear to respond in their level of distractibility as well (Serper, Davidson, & Harvey, 1994). As noted above, these and a number of other cognitive impairments are receiving increasing research attention as informative vulnerability markers (Gur et al., 2007).

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Psychophysiological Abnormalities Individuals with schizophrenia manifest a number of psychophysiological abnormalities, including reduced habituation of startle responses, reduced sensory gating, changes in event-related potentials (Friedman & Squires-Wheeler, 1994), altered psychophysiological reactivity to environmental events, and deficits in smooth-pursuit eye tracking. While many of these impairments in psychophysiological functioning have been confirmed in patients with schizophrenia, the aspect of psychophysiological functioning most consistently studied in individuals without clinical schizophrenia but with subclinical vulnerability is eye tracking (Levy, Holzman, Mathysse, & Mendell, 1994). For 35 years, it has been known that patients with schizophrenia (Holzman, Proctor, & Hughes, 1973) and about 60% of their first-degree relatives (Holzman et al., 1974) manifest abnormalities in smooth-pursuit eye movements. These deficits are measured in laboratory settings in which subjects are asked to follow the movement of an object with their eyes, with the object moving at either a consistent or accelerating rate. Several different eye movement abnormalities have been studied, including slow pursuit, irregular catch-up saccades, and generally irregular movements. Some of these measures have been shown to have high heritability (Hong et al., 2006). Although multiple theoretical models have been proposed to explain the reasons for eye-tracking deficits in relatives of patients with schizophrenia, an important finding to keep in mind is that eye-tracking deficits are not specific to patients with schizophrenia. In fact, eye-tracking deficits have been found to be uncorrelated with the severity of schizotypal symptoms in the first-degree relatives of patients with schizophrenia (Keefe et al., 1997). Thus, eye-tracking abnormalities are most likely related to some genetic features that are necessary, but not sufficient, for the development of schizophrenia. The finding that eye-tracking problems were unrelated to schizotypal symptom severity likely reflects the existence of multiple paths to the development of schizophrenia. For example, eye-tracking impairments are reliably found in individuals with the illness and some number of their relatives, but not necessarily those relatives who manifest the putative behavioral symptoms associated with the schizophrenia spectrum.

Sequential Onset of Illness: Premorbid Phase, Prodrome, Onset, and Period of Untreated Psychosis Although some features of the course of schizophrenia were described earlier, a more detailed review of the sequential onset of the illness not only supports the diathesis–stress and neurodevelopmental models but also sets the stage for a greater understanding of future potential prevention efforts. For this reason, the early course of psychotic illnesses, even prior to the first contact with mental health professionals, is receiving intense research attention.



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The premorbid phase of schizophrenia comprises the period of time, typically during the elementary, middle, and perhaps high school years, prior to the onset of any psychiatric symptoms. Numerous studies have shown deficits in premorbid functioning among those who later develop schizophrenia. Greater premorbid deficits are related to a number of poor prognostic features, including early age at onset of illness, cognitive and neuropsychological deficits, and more severe positive and negative symptoms (Addington & Addington, 2005; Rabinowitz, De Smedt, Harvey, & Davidson, 2002). Conversely, good premorbid functioning is predictive of better response to treatment and better course (Rabinowitz, Harvey, Eerdekens, & Davidson, 2006). The onset of prodromal symptoms, marking the end of the premorbid phase, is often gradual and cumulative. The prodrome of schizophrenia has been viewed traditionally as a prepsychotic state (an attenuated form of psychosis) identifiable only retrospectively after the onset of psychosis. However, recent efforts attempt to prospectively identify individuals meeting criteria for prodromal syndromes that confer an increased, though not absolute, vulnerability to developing psychosis (Yung et al., 1996). Such efforts reconceptualize the inherently retrospective prodrome concept as a current/prospective “atrisk mental state,” indicating that an affected person has clinical symptoms suggestive of elevated risk for developing psychosis in the near future relative to someone without such symptoms (though if symptoms resolve, the degree of increased risk diminishes as well; Yung, 2007; Yung & McGorry, 1996). Prodromal features include nonspecific psychiatric symptoms (e.g., anxiety, dysphoria, irritability, and sleep disturbance), early negative symptoms (e.g., anhedonia, apathy, asociality, avolition, blunted affect, impaired concentration, low energy, and social withdrawal), and subthreshold or attenuated positive symptoms and disorganization (e.g., ideas of reference, brief intermittent hallucinations or delusions, suspiciousness, perceptual abnormalities, unusual thought content, and trouble with thinking). Thus, like the premorbid phase during which time social and academic deterioration often gradually occurs, the prodrome is not psychosocially inconsequential. Numerous symptoms and a substantial level of disability and decline in functioning often develop during the prodromal phase of psychotic disorders (Cornblatt, Lencz, & Obuchowski, 2002; Niendam et al., 2007). As such, the social disability associated with schizophrenia often develops long before formal diagnosis or initiation of treatment. Wood et al. (2008) recently reviewed the limited but promising literature on neuroimaging and neuropsychological studies in symptomatic high-risk groups (samples consisting of putatively prodromal participants) and reported strong evidence for impairments of prefrontal cortex function. However, questions remain about when such brain changes occur with respect to the development of psychopathology. Additionally, a review of the literature on brain changes during the development of schizophrenia among samples at increased genetic risk (Lawrie, McIntosh, Hall, Owens, & Johnstone, 2008) also revealed that prefrontal cortex (and temporal lobe) function may deteriorate in at-risk subjects who develop psychosis. The emergence of psychotic symptoms, marking the end of the prodrome,

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is characterized by a heterogeneous mode of onset. The mode of onset of psychosis can be thought of as the rapidity with which psychotic symptoms emerge. Thus, as operationalized for the World Health Organization’s International Pilot Study of Schizophrenia (Jablensky, Sartorius, & Ernberg, 1992), the mode of onset of psychosis may be acute (psychotic symptoms developing over the course of up to 1 week), subacute (symptoms developing into a clear-cut psychotic state over a period of up to 1 month), gradual (the slow, incremental development of psychotic symptoms over a period of greater than 1 month, or a gradual transition from prodromal to psychotic symptoms), or insidious (indicating no clear demarcation between premorbid personality and the psychotic disorder). A gradual or insidious mode of onset of psychosis is thought to predict poorer outcomes than an acute mode (Bromet, Naz, Fochtmann, Carlson, & Tanenberg-Karant, 2005; Vaillant, 1978), and the DSM-IV refers to acute mode of onset as a good prognostic feature for schizophreniform disorder (American Psychiatric Association, 2000). Once psychotic symptoms develop, initiation of evaluation and treatment is usually delayed, as is true of treatment seeking for other psychiatric and physical health conditions (Compton, Goulding, Broussard, & Trotman, 2008). The duration of this delay, operationalized by early-course researchers as the duration of untreated psychosis (DUP), is likely driven by numerous factors (in addition to illness and course variables such as the mode of onset of psychosis; Compton, Chien, Leiner, Goulding, & Weiss, 2008) at the patient, family, and health system levels. Research on DUP reveals that it is typically quite lengthy, often averaging 6 months to 2 years, and that it is highly variable both within and across studies (Norman & Malla, 2001). Of importance, a substantial body of research, summarized by two meta-analyses (Marshall et al., 2005; Perkins, Gu, Boteva, & Lieberman, 2005), indicates that longer DUP is associated with poorer outcomes in several domains. The study of treatment delay and DUP has been informed by the pathways-to-care construct, or the various help-seeking contacts made between the onset of illness and engagement in treatment (Singh & Grange, 2006), and several studies indicate that routes to procuring professional help are markedly varied in first-episode samples. It is increasingly recognized that for some first-episode patients help seeking begins during the prodromal or even premorbid phase due to the significant symptoms and psychosocial impairments that often appear during these prepsychotic periods. Broome et al. (2005) synthesized conceptualizations of the causes of psychosis that account for this sequential onset, which can be summarized, though quite simplified, as follows: •• Genes involved in neurodevelopment and the dopaminergic system, and/or environmental insults in early life, lead to aberrant brain development, predisposing to later onset of psychosis. These brain developmental abnormalities may manifest as subtle developmental delays and cognitive impairments in childhood.



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•• There exists an interaction between this biological predisposition and psychological and social factors (e.g., urban upbringing, social isolation, migration) in a cascade of increasingly aberrant development. Such developmental abnormalities may be manifest as psychotic-like symptoms that never cross a diagnostic threshold or the accumulation of negative and affective symptoms that constitute an “at-risk mental state” or prodrome. •• Although most developmentally impaired or socially isolated adolescents with odd ideas and experiences (or individuals in the general population with psychotic-like symptoms) do not develop a psychotic disorder, affective symptoms (depression and anxiety) may provoke the onset of psychotic symptoms in some. •• A weakening of hippocampal control over the mesolimbic dopamine system, along with prefrontal dysfunction, leads to abnormal dopamine transmission, facilitating the formation of “meaningful connections” between coincident events and establishing a state of “aberrant salience” or the attribution of excessive significance to external perceptual or internal mental sources (Kapur, 2003). •• Such processes are facilitated by the “basic cognitive dysfunction” (Garety, Kuipers, Fowler, Freeman, & Bebbington, 2001) known to exist in prepsychotic adolescents, including impairments in attention, information processing, and theory of mind.

Toward a Prevention Perspective on Schizophrenia Like any other chronic disease, schizophrenia can be considered from a prevention perspective. Ongoing research on vulnerability will undoubtedly advance this approach. The foregoing discussion of the sequential onset of psychosis is important in any consideration of prevention efforts. While the symptoms of schizophrenia are treatable using both psychopharmacologic and psychosocial modalities, the disorder is not curable or preventable (in terms of primary prevention). Nonetheless, a number of efforts are under way to address the prevention of schizophrenia, and researchers view such efforts as very promising, albeit challenging (Lieberman & Corcoran, 2007). Prevention is classified traditionally into primary, secondary, and tertiary prevention (Compton, 2004; Koplan et al., 2007). Primary prevention is the application of health promotion or specific protective interventions that modify risk factors to reduce the incidence of disease. For example, primary prevention of cardiovascular disease includes efforts to promote cessation of cigarette smoking. In turn, primary prevention of cigarette smoking includes means to restrict access to cigarettes, taxation of tobacco products to prevent smoking initiation, and regulations against advertisements directed toward youth. The primary prevention of schizophrenia (incidence reduction at the

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population level), which would likely require preventive interventions to be applied in the premorbid phase, is not yet attainable. However, ongoing elucidation of risk factors, especially those that are modifiable (e.g., insufficient prenatal care, obstetric complications, cannabis use in adolescence, social adversity) and that confer a sizable population attributable risk, could move the field toward the primary prevention of schizophrenia. The term secondary prevention indicates screening, early identification, and treatment of incipient illnesses that may be in a latent stage before symptomatic presentation. An example is the use of mammography to detect breast cancer in very early stages, an intervention that is associated with decreased morbidity and mortality. Secondary prevention of schizophrenia would mean intervening very early in the course of the evolving psychotic disorder. Increased interest is being focused on secondary prevention of schizophrenia via reduction in treatment delays through early detection and intervention efforts (Compton, McGlashan, & McGorry, 2007). Secondary prevention in fact seems feasible, and research from Norway suggests that efforts aimed at reducing the community’s median DUP (Joa et al., 2008) lessen the severity of illness (Larsen et al., 2006; Melle et al., 2008). However, other efforts have not demonstrated an ability to reduce the median DUP (Malla, Norman, Scholten, Manchanda, & McLean, 2005), and the complex determinants of DUP are just beginning to be clarified (Compton & Broussard, 2009). A number of early intervention programs have been developed around the world, a prototype of which is the Early Psychosis Prevention and Intervention Centre (EPPIC) in Melbourne, Australia (McGorry, Edwards, Mihalopoulos, Harrigan, & Jackson, 1996). The early intervention paradigm is receiving considerable research attention (Addington, 2007). Efforts aimed at minimizing the morbidity and mortality of an established illness—through preventing relapse, comorbidity, psychosocial disability, and functional impairment—are referred to as tertiary prevention. Much of the treatment that clinicians provide, both in general medicine and psychiatry/psychology, can be considered tertiary prevention. Substance abuse prevention; prevention of relapse and hospitalization; suicide prevention; reduction of adverse health behaviors; and enhancement of academic, housing, interpersonal, and vocational functioning are all aspects of the tertiary prevention of schizophrenia that require ongoing research, programmatic, and policy attention. In addition to the traditional primary, secondary, and tertiary prevention categories, preventive interventions also can be classified according to the population to which an intervention is targeted (Mrazek & Haggerty, 1994). As such, primary prevention efforts are further defined as universal preventive interventions (those applied to the population in general, regardless of level of risk, such as water fluoridation, childhood vaccinations, media campaigns, and standards for prenatal care), selective preventive interventions (those applied to a specific subgroup experiencing a specific risk factor, such as interventions that target youth at elevated risk of delinquency, conduct disorder, or substance abuse), and indicated preventive interventions (applied to



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an even smaller group of individuals who are at particularly high risk, such as cognitive-behavioral programs for children and adolescents with subclinical disorders). There is considerable overlap between the constructs of secondary prevention and indicated preventive interventions. An emerging area of research involves recent attempts to prospectively identify adolescents and young adults who appear to be in a prodromal state (Addington et al., 2008) and then to provide and study psychopharmacologic intervention in the form of low-dose atypical antipsychotics (McGlashan et al., 2006; McGorry et al., 2002) or psychosocial interventions such as cognitivebehavioral therapy (McGorry et al., 2002). These approaches can be considered indicated preventive interventions. Meaningful levels of symptoms, functional disability, and cognitive impairment, occurring during (or even prior to) the prodrome, indicate important potential points of therapeutic intervention prior to the development of psychotic symptomatology. Prodromal syndromes have been defined for prospective case identification (Cornblatt et al., 2002; McGlashan, Miller, & Woods, 2001; McGorry, Yung, & Phillips, 2003), rating scales of prodromal symptoms have been studied (Yung et al., 2005), and a number of prodrome research and clinical programs have been developed around the world, a prototype of which is the Personal Assessment and Crisis Evaluation (PACE) program in Melbourne, Australia (Yung, 2007). In the United States, a consortium of prodrome researchers (Addington et al., 2007) has joined efforts to combine data sets to increase power for predictive studies (Cannon et al., 2008). Just as elucidation of risk factors may advance the primary prevention of schizophrenia, research on trait vulnerability markers may become especially informative as researchers work toward sharpening predictive ability (and thus better targeting future preventive interventions) in samples of adolescents and young adults with presumptively prodromal syndromes.

Summary Schizophrenia is an illness that is identified most commonly in the late adolescent and early adult years, although signs of the illness are detectable in many cases prior to formal diagnosis. Genetic and experiential factors associated with vulnerability generally conform to a diathesis–stress model of the illness. Research on vulnerability to schizophrenia has focused in the recent past on the identification of subsyndromal phenotypes of the illness, which may be more identifiable, treatable, and amenable to research than the full syndrome. Prevention efforts for the illness are more plausible now than at any time in the past, and the possibility of secondary prevention of the illness is now quite viable. Continuing study on the early identification of individuals at particularly high risk for the illness will be the key to advancing prevention to the primary prevention stage and also in reducing the illness-related morbidity that is associated with undetected or untreated early-stage illness.

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McGlashan, T. H., Zipursky, R. B., Perkins, D., Addington, J., Miller, T., Woods, S. W., et al. (2006). Randomized, double-blind trial of olanzapine versus placebo in patients prodromally symptomatic for psychosis. American Journal of Psychiatry, 163, 790–799. 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. McGorry, P. D., Yung, A. R., & Phillips, L. J. (2003). The “close-in” or ultra high-risk model: A safe and effective strategy for research and clinical intervention in prepsychotic mental disorder. Schizophrenia Bulletin, 29, 771–790. McGorry, P. D., Yung, A. R., Phillips, L. J., Yuen, H. P., Francey, S., Cosgrave, E. M., et al. (2002). Randomized controlled trial of interventions designed to reduce the risk of progression to first-episode psychosis in a clinical sample with subthreshold symptoms. Archives of General Psychiatry, 59, 921–928. Melle, I., Larsen, T. K., Haahr, U., Friis, S., Johannesen, J. O., Opjordsmoen, S., et al. (2008). Prevention of negative symptom psychopathologies in first-episode schizophrenia: Twoyear effects of reducing the duration of untreated psychosis. Archives of General Psychiatry, 65, 634–640. Morgan, C., Kirkbride, J., Leff, J., Craig, T., Hutchinson, G., McKenzie, K., et al. (2007). Parental separation, loss and psychosis in different ethnic groups: A case-control study. Psychological Medicine, 37, 495–503. Morgan, V., Castle, D., Page, A., Fazio, S., Gurrin, L., Burton, P., et al. (1997). Influenza epidemics and incidence of schizophrenia, affective disorders and mental retardation in Western Australia: No evidence of a major effect. Schizophrenia Research, 26, 25–39. Mrazek, P. J., & Haggerty, R. J. (1994). Reducing risks for mental disorders: Frontiers for preventive intervention research. Washington, DC: National Academy Press. Murphy, K .C., Jones, L. A., & Owen, M. J. (1999). High rates of schizophrenia in adults with velo-cardio-facial syndrome. Archives of General Psychiatry, 56, 940–945. Neale, J. M., McIntyre, C. W., Fox, R., & Cromwell, R. L. (1969). Span of apprehension in acute schizophrenics. Journal of Abnormal Psychology, 74, 593–596. Niendam, T. A., Bearden, C. E., Zinberg, J., Johnson, J. K., O’Brien, M., & Cannon, T. D. (2007). The course of neurocognition and social functioning in individuals at ultra high risk for psychosis. Schizophrenia Bulletin, 33, 772–781. Norman, R. M. G., & Malla, A. K. (2001). Duration of untreated psychosis: A critical examination of the concept and its importance. Psychological Medicine, 31, 381–400. Perkins, D. O., Gu, H., Boteva, K., & Lieberman, J. A. (2005). Relationship between duration of untreated psychosis and outcome in first-episode schizophrenia: A critical review and meta-analysis. American Journal of Psychiatry, 162, 1785–1804. Price, G. W., Michie, P. T., Johnston, J., Innes-Brown, H., Kent, A., Clissa, P., et al. (2006). A multivariate electrophysiological endophenotype, from a unitary cohort, shows greater research utility than any single feature in the Western Australian family study of schizophrenia. Biological Psychiatry, 60, 1–10. Rabinowitz, J., De Smedt, G., Harvey, P. D., & Davidson, M. (2002). Relationship between premorbid functioning and symptom severity as assessed at first episode of psychosis. American Journal of Psychiatry, 159, 2021–2026. Rabinowitz, J., Harvey, P. D., Eerdekens, M., & Davidson, M. (2006). Premorbid functioning and treatment response in recent-onset schizophrenia. British Journal of Psychiatry, 189, 31–35. Raine, A. (2006). Schizotypal personality: Neurodevelopmental and psychosocial trajectories. Annual Review of Clinical Psychology, 2, 291–326. Rantakallio, P., Jones, P., Moring, J., & Von Wendt, L. (1997). Association between central nervous system infections during childhood and adult onset schizophrenia and other psychoses: A 28-year follow-up. International Journal of Epidemiology, 26, 837–843. Rund, B. R. (1993). Backward masking performance in chronic and nonchronic schizophrenics,



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Chapter 16

Vulnerability to Schizophrenia across the Lifespan Patricia A. Brennan and Philip D. Harvey

We have each contributed to this volume a separate chapter focused on vulnerability to schizophrenia. Our separate chapters did not distinctly focus on child-onset versus adult-onset types of a particular psychiatric disorder. Rather, we focused on developmental versus other types of approaches that have been applied to research and theory concerning schizophrenia. Nevertheless, integration of the material across our chapters highlights the questions that remain regarding vulnerability to schizophrenia and also suggests important and necessary directions for future research. In our view, future research on schizophrenia needs to examine combinations of risk factors, to attend to potential developmental effects, to consider separate etiological pathways for subtypes of schizophrenia, and to use prediction models that test the utility of risk factors in identifying individuals who will eventually develop this disorder. The vast majority of individuals who are diagnosed with schizophrenia receive this diagnosis in late adolescence or later. Nevertheless, premorbid characteristics suggest that the process that ultimately results in this diagnostic outcome may already be under way in early infancy (e.g., Walker, Savoie, & Davis, 1994). Brennan and Walker (Chapter 14, this volume) argue that by examining the developmental course of schizophrenia carefully we might be able to discover the causal factors in this process and how they interact with one another to produce this illness. One difficulty with this tactic to date is that the factors associated with the premorbid phase of schizophrenia do not appear to be specific to schizophrenia. Longitudinal and follow-back studies have been able to compare those who develop schizophrenia with those who do not. They typically assess mean differences between these groups and have

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noted that those who later develop schizophrenia have comparatively worse attentional problems (e.g., Reichenberg et al., 2002), higher levels of motor abnormalities (e.g., Schiffman et al., 1994), and worse behavioral disturbances (e.g., Amminger et al., 1999). Evidence that any one of these premorbid factors necessarily results in schizophrenia rather than some other psychiatric illness or a relatively normal course of functioning is lacking. One method of potential discovery in this area is to look for particular combinations of vulnerability factors that occur at a base rate that is commensurate with the base rate of schizophrenia. Testing these particular combinations and their relationship to schizophrenic outcomes might help to determine both the necessary and sufficient causes of this disorder. This approach of focusing on combinations of vulnerability factors might also be helpful in determining the ultimate causes of schizophrenia. Many vulnerability factors are not themselves considered to be causal factors but, rather, markers of causal factors for schizophrenia. Deficits in smooth-pursuit eye movement (SPEM), for example, are thought not to cause schizophrenia but to be markers of a genetic cause for this disorder. Particular combinations of vulnerability factors might suggest a common underlying cause (e.g., neurotransmitter dysfunction) that can then be tested as a necessary and sufficient condition for schizophrenia. Neurodevelopmental models of schizophrenia suggest that the vulnerability factors associated with schizophrenia might vary in response to the interaction of pathological causal factors with normal maturation processes. As we continue to increase our knowledge base concerning normal neurodevelopmental processes, we should be able to combine it with developmentally specific findings of vulnerability to schizophrenia to better determine the underlying causes of this disorder. A focus on when as well as what vulnerabilities exist will be important in future research on schizophrenia. As Brennan and Walker (Chapter 14, this volume) suggest, neurodevelopmental and neurodegenerative models of schizophrenia need not be contradictory. It is likely that some deficits in neurological functioning may be apparent before the onset of schizophrenia, whereas others may result from the course of the illness itself. Comparisons of results from studies of adults with schizophrenia with those of children who later develop schizophrenia have been and will continue to be useful in distinguishing neurological precursors from neurological effects of this disorder. Compton and Harvey (Chapter 15, this volume) outline some of the weaknesses of the diathesis–stress model as it has been applied to the area of schizophrenia research. Current research on gene expression indicates that traditional diathesis–stress models do indeed need to be expanded. The earlier notion that a single gene, in combination with an environmental stressor that exceeds a certain threshold, results in schizophrenia does not capture the complexity of gene–environment interactions as we now understand them to exist. Not only are genes present or absent, but they are also turned on or off in response to developmental, hormonal, environmental, and (other) genetic



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effects. Further, even combinations of susceptibility genes or hapolotypes have not been consistently related to schizophrenia. Of course, the diathesis for schizophrenia need not be only genetic in nature but might be the result of early prenatal or perinatal insults to the central nervous system. Findings from animal research even suggest that an environmental diathesis in one generation might translate into a genetic diathesis in the next. Viral agents have been shown to change the genetic makeup of embryos, with these genetic alterations then being transmitted to the next generation of offspring (e.g., Lin et al., 1994). As gene-expression studies expand, our attention to their results will help us to revise and expand our notions of diathesis–stress as well. As Compton and Harvey point out, one potential downfall of the diathesis– stress model is that if it is adhered to too stringently the main effects of causal factors on schizophrenia may not be detected even if they do exist. They suggest that the failure to find strong results for individual predictors of schizophrenia to date might be the result of the heterogeneity of schizophrenia rather than the need for interactive models. They argue that, if we continue to treat all cases of schizophrenia as the same illness when they are different, we will obtain results that do not replicate and are not valid. The question we then face is how to create meaningful, etiologically distinct, subgroups of individuals with schizophrenia. The suggestion of considering subsyndromal risk variants, often referred to as endophenotypes, is a strategy that heads in that direction. Several researchers have distinguished between positive symptom and negative symptom types of schizophrenia, with distinct etiologies noted for each of these types (Baron, Gruen, & Romo-Gruen, 1992; Cannon, Mednick, & Parnas, 1990). Other researchers have compared the predictors of childhood-onset to adult-onset schizophrenia and have noted that there are more similarities than differences across these two groups (Nicolson & Rapoport, 1999). However, age of onset has been found to be related to family loading for schizophrenia, suggesting a potentially differential genetic basis for childhood-onset versus adult-onset schizophrenia. Because family history is related to age of onset (Suvisaari, Haukka, Tanskanen, & Loennqvist, 1998), it might be more parsimonious to compare family-history-present versus family-history-absent cases of schizophrenia to assess for potentially distinct etiological pathways to these conditions. This type of study is more rare than one would think. In fact, high-risk research usually focuses exclusively on individuals with a family history for this disorder. Thus, the question is left open concerning the generalizability of high-risk study results to the larger population of individuals with schizophrenia. Attention to family history might help to explain failures of replication in studies of the predictors of schizophrenia. Such a study would also be important in the context of recent findings of genetic mutations in the form of microdeletions in certain chromosomal regions. This type of research design would also address the issue of heterogeneity. If individuals with a positive family history of schizophrenia had, for exam-

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ple, a more homogenous presentation than individuals without such a history, then some ideas about the path from risk factors to clinical presentation could be developed. The study of “phenocopies” in other illnesses has helped to refine ideas about the breadth of genetic predispositions to the illness. Brennan and Walker (Chapter 14) present a model suggesting the interactive events and developmental processes that may predict the outcome of schizophrenia. This and other neurodevelopmental models may apply only to a subset of individuals with schizophrenia rather than all the individuals who evidence this diagnostic condition. It might be potentially useful to examine a subtype of individuals with schizophrenia who evidence particular neurological deficits (such as hippocampal damage) to see whether neurodevelopmental models can explain and predict their pathological outcomes. Such an approach is, of course, constrained by the prevalence of such neurological risk factors. Brennan and Walker’s model suggests that particular biological abnormalities, including hypothalamic–pituitary–adrenal (HPA) overactivation and striatal dopaminergic anomalies, might play a causal role in schizophrenia. Genetic and congenital risk factors are hypothesized to cause neurotransmitter anomalies that, in turn, might be related to the behavioral abnormalities observed in both individuals with schizophrenia and those at high genetic risk for schizophrenia. For example, dopaminergic anomalies might be related to both SPEM deficits and motor abnormalities. Brennan and Walker’s model also suggests that perinatal or environmental stressors may increase HPA activation, which, especially when combined with normal increases in gonadal hormone secretion during adolescence, may be related to hippocampal damage. Damage to the hippocampus may underlie some of the cognitive abnormalities noted in individuals with schizophrenia, including poor performance on sustained attention tasks. This neurodevelopmental model clearly requires further empirical support, especially in terms of its predictive utility. As noted previously, most studies examining vulnerability to schizophrenia use post hoc approaches rather than assessing for predictive validity. One exception to this rule is the recent work of Davidson et al. (1999). By combining behavioral and cognitive predictors, they were able to predict well who obtained a diagnosis schizophrenia in their cohort. Replications and extensions of their findings would be valuable and necessary tools for the translation of research on vulnerability into the practice of early intervention. Compton and Harvey (Chapter 15) also review the literature on recent developments in environmental risk factors. These factors, which include living in urban areas, being an immigrant, and cannabis use, have gained more credibility recently with their replication in the prospective studies by Davison and his colleagues (1999). Compton and Harvey also note that careful delineation of the phases of development of the illness, clearly separating premorbid characteristics associated with increased vulnerability from more precipitous changes associated with the earliest signs of illness in the prodrome, has the potential to refine the study of vulnerability processes. Early prevention



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efforts at various stages of the illness can provide some information about the extent to which vulnerability factors are modifiable, which could itself inform interested researchers of the differential contributions of these factors to the “final product” of schizophrenia. In summary, success in the identification of vulnerability processes in schizophrenia will be contingent upon several factors. Prospective research designs, despite the difficulty in conducting such studies, are a prerequisite. Comparative studies of as-yet-unaffected individuals who vary in risk factors (e.g., family history and occurrence of neurological events) are required. Finally, researchers must more closely attend to heterogeneity of the illness and its implications. Approaching schizophrenia as a single disease with a single cause, single course, and unitary outcome appears to have been an impediment to success in the past. The adoption of a lifespan perspective is essential to the future study of schizophrenia. Neurodevelopmental models of schizophrenia are primarily focused on development from prenatal stages through the onset of the symptoms of schizophrenia. Neurodegenerative models focus more on the postonset and later-life course of schizophrenia. A lifespan perspective suggests that we need to further explore both of these models in the study of schizophrenia. In doing so, we will discover both the complementary and distinctive roles of these models in determining the causes of and best available treatments for schizophrenia.

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Childhood videotaped social and neuromotor precursors of schizophrenia: A prospective investigation. American Journal of Psychiatry, 161, 2021–2027. Suvisaari, J. M., Haukka, J., Tanskanen, A., & Loennqvist, J. K. (1998). Age at onset and outcome in schizophrenia are related to the degree of familial loading. British Journal of Psychiatry, 173, 494–500. Walker, E. E., Savoie, T., & Davis, D. (1994). Neuromotor precursors of schizophrenia. Schizophrenia Bulletin, 20, 441–451.

Eating Disorders

Chapter 17

Vulnerability to Eating Disorders in Childhood and Adolescence K amryn T. Eddy, Pamela K. Keel, and Gloria R. Leon

In this chapter, we present a developmental perspective on eating disorders during childhood and adolescence within a biopsychosocial model. Eating disorders include the formal categories of anorexia nervosa (AN) and bulimia nervosa (BN) as well as several forms of eating pathology grouped within the classification of eating disorders not otherwise specified. Although AN may be the most easily recognized eating disorder, it is also the least common, with a lifetime prevalence of 0.5–1.0% (American Psychiatric Association, 2000). Under criteria defined by the fourth edition text revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000), individuals with AN deliberately starve themselves to weights below that expected (e.g., less than 85% of that expected for height). They also fear becoming fat and may think of themselves as being fat. Finally, AN is marked by loss of menstrual function for at least 3 consecutive months. Individuals with AN maintain their state with fasting and excessive exercise (restricting subtype) or recurrent binge eating and purging episodes (binge– purge subtype). In children and adolescents, these diagnostic criteria may be difficult to apply, particularly in youth who are still growing (and may exhibit failure to grow without pronounced weight loss) or are premenarcheal (Bravender et al., 2007). Further, youth may have difficulty articulating their motivations to restrict or lose weight and, instead, may be more likely to exhibit denial of the seriousness of their low weight (Bravender et al., 2007). BN is more common than AN in the United States, with lifetime prevalence estimates of 1–4% (American Psychiatric Association, 2000). The DSMIV-TR characterizes BN as involving recurrent binge-eating episodes coupled with behaviors that compensate for the caloric consumption. Weight and body

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shape unduly influence self-evaluation. Compensatory behaviors can include either purging (e.g., self-induced vomiting, laxative abuse, or diuretic abuse) or nonpurging (e.g., fasting or excessive exercise) methods. Weight is often normal or slightly above-average among individuals with BN. In adolescents, bingeing and compensatory behaviors may be more intermittent than those observed in older patients (Le Grange et al., 2006). A much higher percentage of the population suffers from eating disorders not otherwise specified (EDNOS), a heterogeneous diagnosis that includes individuals who narrowly miss criteria for AN or BN as well as those with clinically significant yet distinct eating disorder presentations. Binge-eating disorder (BED) represents one type within this heterogeneous classification and is characterized by recurrent binge eating in the absence of compensatory behaviors (American Psychiatric Association, 2000). Surveys of young adults indicate that BED affects 5.3% of women (Spitzer et al., 1992). While prevalence among youth is not known, age of onset is often noted in childhood or adolescence (Mussell et al., 1995). Individuals with BED are often overweight and obese (Spitzer et al., 1992), and nearly one-third of overweight youth report binge eating associated with clinical levels of distress or impairment (Eddy, Tanofsky-Kraff, et al., 2007; Glasofer et al., 2007; Goldschmidt, Aspen, Sinton, Tanofsky-Kraff, & Wilfley, 2008), and with excessive weight gain over time (Tanofsky-Kraff et al., 2006) even when full criteria for BED are not met. Other common forms of EDNOS include purging in the absence of recurrent binge-eating episodes, such as after the consumption of small amounts of food; rumination; and chewing and spitting out food without swallowing. In children, eating or feeding difficulties including selective or picky eating and food avoidance related to emotional issues (i.e., not secondary to shape/ weight concerns) have also been described (Bryant-Waugh, 2002) but are not currently included in the DSM-IV-TR eating disorder scheme (Bravender et al., 2007; Nicholls, Chater, & Lask, 2000). Taken together, EDNOS predominates in clinical samples, affecting approximately half of adolescents (Eddy, Celio Doyle, Hoste, Herzog, & Le Grange, 2008) and adults (e.g., Fairburn et al., 2007) seeking treatment for an eating disorder. Because many individuals affected by these disorders may not seek treatment, prevalence in the general population is unclear. Eating disorders are clearly more prevalent among women; however, 5–15% of cases of AN and BN, and approximately one third of BED cases, can occur in males (American Psychiatric Association, 2000).

Risk Factor Research Methodology A risk factor is defined as a variable that prospectively predicts a subsequent pathological outcome (Kazdin, Kraemer, Kessler, Kupfer, & Offord, 1997;



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Kraemer et al., 1997). The identification of risk factors for any disorder can be approached using cross-sectional and longitudinal designs. Cross-sectional designs are useful as a first step in risk factor research, as they seek to determine whether a given factor is concurrently associated with the presence of disordered-eating behaviors or attitudes. If a factor does not distinguish between individuals with disordered eating and individuals without disordered eating, it is unlikely to represent a risk factor for eating disorders. However, a concurrent association between eating pathology and a given factor does not demonstrate that the factor increases the risk for developing eating pathology. Unless the associated factor is “fixed” (e.g., gender, race/ethnicity, birth characteristics), it could be a result of the eating pathology. For example, neuroimaging studies indicate gray matter and white-matter volume decreases are associated with the presence of AN. However, these appear to be the result of severe malnutrition, as they improve with weight restoration (Frank, Bailer, Henry, Wagner, & Kaye, 2004). Alternatively, disordered eating and the correlated factor could both result from a common underlying determinant. For example, BN is associated with increased levels of depression. However, both the depression and the bulimic symptoms may be elevated by deficits in interpersonal relationships. In contrast to cross-sectional methods, longitudinal designs provide a more rigorous means by which to identify factors that are present prior to the onset of disordered eating. Employing the logic that cause precedes effect, factors that distinguish between who will and will not develop disordered eating at a later point in time represent risk factors. In eating disorders research, putative risk factors are considered for the development of both DSM-IV-TR eating disorders and eating disorder symptoms. Many studies rely on surveys or self-report questionnaires to assess the presence of disordered-eating attitudes and behaviors. However, frequencies of disordered-eating behaviors are often higher in self-report questionnaires than in interviews (French et al., 1998). The increased frequencies may reflect false positives because adolescents misinterpret the intent of particular questions. Alternatively, adolescents may feel reluctant to report certain eatingdisordered behaviors during a personal interview (French et al., 1998). The most appropriate methods aim to maximize the sensitivity (reduction of false negatives) and specificity (reduction of false positives) of assessment by employing both self-report surveys and semistructured interviews (e.g., Killen et al., 1996; Leon, Fulkerson, Perry, Keel, & Klump, 1999). Initial surveys screen for the possible presence of disordered-eating behaviors, and interviews confirm their presence.

Developmental Course of Eating Disorders Our biopsychosocial model of vulnerability in developing eating disorders is conceived within the context of a theory of normal development. The transi-

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tion periods from childhood to adolescence and adolescence to young adulthood are associated with increased risk for developing eating disorders. Our theory of normal development focuses on the particular intra- and interpersonal demands the individual is required to negotiate at different stages of development. We ascribe to the views of Erikson (1968) and others (Vaillant, 1977) who conceptualized adolescence as the period in which the influence of “society” replaces the childhood milieu. The core issues of interpersonal relationships, intimacy, and autonomy remain salient throughout the transition from childhood to adulthood. The transition from childhood to adolescence is marked by the initiation of pubertal changes that signal sexual maturation, identity formation, transition of intimate relationships from within the family to extra-family peers, and initiation of dating. The transition from adolescence to young adulthood is marked by choices regarding higher education or employment, living away from home, and the assumption of greater financial responsibility. Issues related to sexual preference and establishing enduring monogamous relationships take on added importance during this transition. These changing expectations and increasing demands within the individual’s life are marked by increased risk for eating disorders. Investigations of age of onset for AN indicate a typical onset in mid- to late adolescence (American Psychiatric Association, 2000) with specific increased risk at ages 14 and 18 (Halmi, Casper, Eckert, Goldberg, & Davies, 1979; Steinhausen, 1994). Age of onset for BN appears to be concentrated in the transition from adolescence to early adulthood and typically ranges from 18 to 22 years (American Psychiatric Association, 2000). Thus the transition from childhood to adolescence is associated with the onset of AN whereas the transition from adolescence to adulthood is associated with the onset of both AN and BN. Timing of onset for EDNOS has not been well studied. Although many of the challenges associated with these developmental transition periods are psychosocial in nature, they occur within a context of biological changes. In addition, biological factors likely influence responses to these challenges. Viewing risk factors in terms of interactions among biological, psychological, and social processes seems most useful because divisions among them can be fairly artificial. Data collected within a predominantly psychosocial paradigm may be reinterpreted according to biological influences, and vice versa. To facilitate discussion of interactions among biological, psychological, and social processes, we review research relevant to each.

Biological Contributions to Eating Pathology Genetic Factors Eating disorders are more common among first-degree female relatives of individuals with eating disorders than among females from the general population (Lilenfeld et al., 1998; Stein et al., 1999; Strober et al., 2000; Strober,



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Freeman, Lampert, Diamond, & Kaye, 2001; Woodside, Field, Garfinkel, & Heinmaa, 1998). Research on twins indicates that genetic factors have an influence (Fichter & Noegel, 1990; Hsu, Chesler, & Santhouse, 1990; Kendler et al., 1991; Klump, Miller, Keel, McGue, & Iacono, 2001). Review of the literature suggests that genetic effects account for 58–88% of the risk for AN and 28–83% of the risk for BN (Jacobi, Hayward, de Zwaan, Kraemer, & Agra, 2004). More recently, twin and family studies have begun to look at shared transmission between eating disorders and other forms of psychopathology. Several investigations (Keel, Klump, Miller, McGue, & Iacono, 2005; Kendler et al., 1995; Lilenfeld et al., 1998; Silberg & Bulik, 2005) support the possibility that eating disorders and anxiety disorders may share a common genetic liability. These data support the role of genetic factors in creating a nonspecific diathesis for the development of eating disorders and anxiety disorders. Both association studies, involving the consideration of specific candidate genes in individuals with and without eating disorders, and linkage studies, requiring large samples of probands and an affected relative, are of interest in eating disorders (see Bulik & Tozzi, 2004). To date, association studies have yielded inconsistent findings. An international family-based linkage study of eating disorders is currently under way (Kaye et al., 2000, 2004, 2008). This research has indicated preliminary evidence for a susceptibility locus to restricting AN on chromosome 1p (Grice et al., 2002) and one to BN with vomiting on chromosome 10p (Bulik et al., 2003). Age of onset and gender differences in eating disorder prevalence also are being explored from a biological perspective. One line of research has suggested that prenatal sex hormone exposure may be associated with eating disorder pathology in adolescence (Culbert, Breedlove, Burt, & Klump, 2008). This recent twin research demonstrated that the risk of eating disorder pathology broadly (Culbert et al., 2008) was highest in female–female twins but also increased in males with female co-twins as compared to male–male twins, which may implicate relatively lower prenatal testosterone and higher prenatal estrogen with the later onset of eating disorder symptoms. Further, some investigators question whether puberty and its associated hormonal changes may trigger the expression of genes that confer increased risk for eating pathology during adolescence for females (Klump & Gobrogge, 2005). For example, investigators utilized longitudinal data collected through the Minnesota Twin Family Study to examine changes in genetic influence on eating disorder pathology from childhood through adolescence (Klump, Burt, McGue, & Iacono, 2007; Klump, McGue, & Iacono, 2000; Klump, McGue, & Iacono, 2003). While genetic factors accounted for a small percentage of the variance in eating disorder symptoms in prepubertal children, these factors accounted for nearly half of the variance in symptoms expressed in adolescence. The investigators posit that hormonal changes occurring during puberty may moderate genetic influences on eating disorder symptoms.

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Notably, both age of onset and gender difference issues have also been conceptualized from a psychosocial perspective, described later.

Neurophysiological Function Neurotransmitter function has long been a focus of research attempting to discern the biological underpinnings of psychopathology. Given the association between serotonin (5-HT) and disturbances in appetite, impulse control, and mood, research has focused attention on 5-HT function as a mechanism for conferring a risk for eating pathology (for review, see Kaye, 2008). This type of research examines serotonin function in individuals with eating disorders during acute illness as well as postrecovery, to avoid the confounding effects of malnutrition on biology. Serotonin function is dysregulated in individuals with AN and BN. During acute illness, cerebrospinal fluid 5-HT metabolites (5-HIAA) are decreased in patients with AN as compared to normal controls (e.g., Kaye, Ebert, Gwirtsman, & Weiss, 1984; Kaye, Gwirtsman, George, Jimerson, & Ebert, 1988); decreased 5-HIAA has also been linked to severity of binge– purge symptoms in BN (Jimerson, Lesem, Kaye, & Brewerton, 1992) but less consistently (Kaye et al., 1990). Patients with acute AN and BN show altered 5-HT receptor function (Kaye, 2008). Imaging research demonstrates specific alterations in the binding potential of the 5-HT1A and 5-HT2A receptors in both disorders (see Kaye, 2008). Further, patients with eating disorders have demonstrated diminished prolactin release in response to ingestion of a serotonin agonist (Brewerton, Mueller, Lesem, & Brandt, 1992; Golden & Shenker, 1994; McBride, Anderson, Khait, Sunday, & Halmi, 1991). Investigators have begun to explore the presence of serotonin dysfunction among recovered patients as a possible indication of premorbid serotonin function. Postrecovery, individuals with a history of AN and BN demonstrate significantly increased 5-HIAA as compared to healthy controls at concentrations that are about 50% greater than those CSF 5-HIAA concentrations observed during the ill state (Kaye et al., 1998). Some alterations in the binding potential of 5-HT1A and 5-HT2A continue to be observed in many brain regions, but often in opposite directions from those observed during the ill state (Kaye, 2008). Some authors (e.g., Kaye, 2008) have suggested that these findings may reflect the presence of excessive serotonin function prior to disordered eating. Reduced dietary intake decreases tryptophan (an amino acid precursor to 5-HT), and tryptophan depletion has been found to be associated with reductions in anxiety and dysphoria specifically in individuals who have recovered from AN (e.g., Kaye et al., 2003). Thus Kaye and colleagues have hypothesized that dieting may function to regulate the overactivity of serotonin and be reinforcing by initially reducing anxiety and dysphoria in these individuals (Barbarich, Kaye, & Jimerson, 2003; Kaye, 2008; Kaye, Barbarich, et al., 2003). It is possible that increased serotonin function may rep-



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resent a biologically based temperamental predisposition to perfectionism and obsessionality among individuals who develop AN (Barbarich et al., 2003; Kaye, 2008; Kaye, Frank, Bailer, & Henry, 2005; Kaye, Frank, Bailer, Henry, Meltzer, et al., 2005). This hypothesis could explain the high comorbidity between eating disorders and anxiety disorders. However, this work is currently limited by the lack of premorbid neurobiological data; thus, it is also possible that the serotonin dysregulation that exists postrecovery represents a consequence of the illness. Continued research on individuals who are in long-term recovery from all types of eating disorders may further our understanding of the mechanisms by which 5-HT function confers risk for eating disorders. Identifying endophenotypes for eating disorders, such as those related to 5-HT dysfunction, could potentially be explored in some of the ongoing genetic studies of eating disorders.

Temperament Temperament has been examined as a risk factor for eating disorders. Negative affectivity is one such temperament that appears to represent a nonspecific diathesis for the development of general psychopathology (Clark, Watson, & Mineka, 1994; Watson, Clark, & Harkness, 1994), particularly disorders involving mood and anxiety disturbance. One prospective longitudinal study of the development of disordered eating among adolescents ages 13–18 found that high levels of negative affectivity on the Multidimensional Personality Questionnaire (Tellegen, 1982) predicted the development of disordered-eating behaviors and attitudes in both girls and boys over time (Leon et al., 1999). The impact of negative affectivity was demonstrated among students who had no eating pathology at baseline assessment and those with moderate to high levels of disordered eating at initial testing. As a diathesis, negative affectivity is likely to be associated with negative attitudes toward the self, leading to low self-esteem and dissatisfaction with many aspects of the self, including physical appearance. Supporting this diathesis, in the more recent longitudinal McKnight Risk Factor Study (McKnight Investigators, 2003) of 1,103 adolescent girls in grades 6–9 assessed annually for up to 3 years, negative emotionality was associated with preoccupation with thinness and social pressure to be thin. When these variables were entered into prediction models of eating disorder pathology, negative emotionality did not emerge as an independent predictor, suggesting that its influence on eating disorder pathology may be explained by its association with a preoccupation with thinness and perceived pressure to be thin. These attitudes are discussed in more detail in a later section of this chapter. Much research has demonstrated significant comorbidity among eating, mood, anxiety, and substance use disorders in adolescents (e.g., Leon et al., 1999), a finding that supports the role of temperament as a nonspecific diathesis.

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A temperamental style characterized by perfectionism also has been described in patients with AN and BN (for a review, see Lilenfeld et al., 2006). Cross-sectional findings are bolstered by research indicating that increased perfectionism persists in patients with eating disorders postrecovery (Bastiani, Rao, Weltzin, & Kaye, 1995; Kaye et al., 1998; Kaye, Gwirtsman, George, & Ebert, 1991). More recently, Wade and colleagues (2008) demonstrated that perfectionism, specifically high personal standards, was associated with AN in a large female twin sample and was increased in nonaffected co-twins of anorexic probands as compared to controls. The authors concluded that high personal standards may represent a familial trait that confers increased risk for AN (Wade et al., 2008). Notably, however, the longitudinal research examining perfectionism as a risk factor for eating disorder pathology has been equivocal, particularly in younger patients (e.g., Leon et al., 1999; Shaw, Stice, & Springer, 2004). As with negative affect, perfectionism may represent a general risk factor for psychopathology that, when combined with body dissatisfaction or perceived pressure to be thin, is channeled into pursuit of thinness and increases risk specifically for eating disorder pathology.

Psychological Contributions to Eating Pathology Several psychological variables have been explored as possible contributors to the development of disordered eating. These factors include personality, learning, and maladaptive responses to stress. Bruch (1978) proposed that the underlying cause of eating disorders is the inability to correctly identify and differentiate the signals of hunger and other bodily and emotional sensations, a condition Sifneos (1972) termed “alexithymia.” Bruch (1978) believed that this confusion resulted from early childhood experiences of a mother responding to all of her infant’s emotional needs with the giving of food, or failing to respond to her infant’s hunger with feeding. Research supports this thesis of disrupted feeding interactions between mothers and infants who exhibit food refusal (Chatoor, Egan, Getson, Menvielle, & O’Donnell, 1988). Indeed, these types of early feeding and digestive difficulties have been associated with the development of eating disorders (Kotler, Cohen, Davies, Pine, & Walsh, 2001; Marchi & Cohen, 1990). According to Bruch (1978), the mother’s inability to appropriately mirror the child’s desires results in the child’s inability to differentiate between physical and emotional needs and undermines the child’s sense of identity, autonomy, and control. Because the child is unable to secure an appropriate response from (typically) her caretaker, she modifies her expectations of her role within the world and attempts to alter her needs to fit the care that is given. This pattern of overcompliance with the expectations of others is radically altered with the onset of disordered eating in which the adolescent attempts to achieve a feeling of autonomy by controlling her food intake and weight (Bruch, 1978). Longitudinal research supported the importance of



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poor interoceptive awareness, which is defined as an ability to recognize and label one’s internal emotional state, as a predictor of the development of eating disorder symptoms in adolescents but did not support ineffectiveness, or one’s sense of self-esteem/self-efficacy, as a predictor of disordered eating (e.g., Leon et al., 1999). Other investigators have also found higher alexithymia scores in eating-disordered as compared to normal control groups (Bourke, Taylor, Parker, & Bagby, 1992; Schmidt, Jiwany, & Treasure, 1993). Thus, empirical research supports part but not all of Bruch’s (1978) theory. Some researchers have argued that difficulties labeling hunger and satiation result from chronic dieting (Polivy & Herman, 1985), thus shifting the focus from early parent–child relationships to results of denying or ignoring one’s own physical needs in attempts to lose weight. A multitude of longitudinal studies have supported the relationship between dieting and subsequent development of an eating disorder (for a review, see Jacobi et al., 2004; Stice, 2002). For example, Patton, Selzer, Coffey, Carlin, and Wolfe (1999) demonstrated that adolescent girls who reported significant dieting at ages 14–15 were 18 times more likely to develop an eating disorder 3 years later as compared to girls with no history of dieting. The association between dieting and AN is relatively direct—attempts to lose weight through food restriction represent the core behavior of AN. The association between dieting and bulimia nervosa can be explained by the restraint hypothesis (Polivy & Herman, 1985), which posits that dieting causes binge eating. Polivy and Herman (1985) suggest that attempts to control food intake leave an individual vulnerable to disinhibitors that can be cognitive, emotional, or pharmacological in form. A 14-year-old girl may initiate a diet to lose weight. However, her attempts to control her food intake are undermined when she becomes upset after arguing with her older brother (emotional disinhibitor). This event then leads to counterregulation (binge eating). Several laboratory experiments have supported an association between dietary restraint and increased food intake in nonclinical populations (Ruderman, 1985). Longitudinal research has also supported a prospective association between dieting and the later development of binge eating, with one study demonstrating that dieting predicted increased binge eating in a large ethnically diverse community sample (N = 2,516) of female and male adolescents during a 5-year follow-up period (Neumark-Sztainer, Wall, Haines, Story, & Eisenberg, 2007). Thus, dieting may lead indirectly to the core feature of both BN and BED (Polivy & Herman, 1985). Heatherton and Baumeister (1991) provided a slightly different explanation of the relationship between dieting and binge eating. These authors suggested that individuals with low self-esteem were more likely to diet in an attempt to improve self-worth. However, difficulty losing weight decreased self-esteem and increased feelings of ineffectiveness. The binge eating episode then served to shift attention from aversive self-perceptions to the simple physical act of eating. Thus binge eating was motivated by the desire to escape self-awareness. Anecdotal evidence from women with bulimic episodes suggests that many use binge eating to “zone out.” However, the escape from self-awareness hypothesis

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would be exceptionally difficult to test experimentally because the very act of asking women to report their levels of self-awareness preceding, during, and following a binge episode would alter their level of self-awareness. Although dieting often precedes binge eating in retrospective reports of individuals with eating disorders, nearly 17% of women with BN and 48% of individuals with BED report the onset of binge eating prior to the first weight-loss diet (Mussell et al., 1997; Spitzer et al., 1992, respectively). In overweight children with BED, one study indicated that two-thirds reported loss of control eating prior to dieting (Tanofsky-Kraff, Faden, Yanovski, Wilfley, & Yanovski, 2005). In addition, concerns have been raised regarding the extent to which measures of dietary restraint measure actual restriction of food intake rather than a propensity to overeat (Stice, Cooper, Schoeller, Tappe, & Lowe, 2007). Some authors (Arnow, Kenardy, & Agras, 1992; Ruderman, 1986) have argued that binge eating can be directly triggered by negative emotions in the absence of dieting behaviors. Research (Arnow, Kenardy, & Agras, 1995; Telch, Pratt, & Niego, 1998) supports the theory that binge eating is used to cope with negative emotional states. Indeed, using the novel technique of ecological momentary assessment, Smyth et al. (2007) recently demonstrated that women with BN are likely to engage in binge–purge episodes directly following experiencing aversive emotions (e.g., negative affect, anger, stress). Immediately following the binge/purge episodes, these women reported increased positive affect and an alleviation of the aversive emotions (Smyth et al., 2007), supporting this escape-avoidant coping theory. Some research suggests that binge eating may provide an exchange of less tolerable negative states, such as anger, for more acceptable negative emotions such as guilt (Kenardy, Arnow, & Agras, 1996). Thus, negative emotional states precipitate both dieting and binge eating behaviors. Notably, a temperament marked by negative affectivity would increase an individual’s predisposition to experience such negative emotional states. Negative affectivity likely increases negative attitudes toward the self, such as low self-esteem and body dissatisfaction. Several prospective studies of the development of eating pathology in girls linked poor self-esteem to the onset of disordered-eating behaviors, particularly bulimic symptoms (Button, Sonuga-Barke, Davies, & Thompson, 1996; Cervera et al., 2003; Ghaderi & Scott, 2001). However, other studies (Keel, Fulkerson, & Leon, 1997; Leon et al., 1999) have not found a significant association between low self-esteem and the development of disordered eating in multivariate analyses. It is likely that self-esteem is an important factor in determining the onset of eating pathology, but its influence is probably not independent of other factors that would be strongly related to disordered eating, such as body dissatisfaction. Indeed body dissatisfaction has proven to be a robust predictor of eating disorder pathology in longitudinal research. For example, Johnson and Wardle (2005) found that body dissatisfaction was the strongest independent predictor of the development of disordered-eating attitudes and behaviors in 1177 adolescent girls (ages 13–15) followed for 10 months. Killen et al. (1996)



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found that weight concerns predicted the onset of partial syndrome eating disorders over a 4-year prospective follow-up study of 877 high school girls. Similar results for boys have been found. Keel, Fulkerson, et al. (1997) demonstrated that poor body image predicted the onset of disordered eating in a 1-year prospective follow-up study of 102 elementary school boys. This finding has been replicated cross-culturally: Beato-Fernandez, Rodriguez-Cano, Belmonte-Llario, and Martinez-Delgado (2004) similarly identified baseline body dissatisfaction as a strong predictor of eating disorders 2 years later in a Spanish mixed gender community sample of adolescents (N = 1,076). Dieting, body dissatisfaction, and unrealistic weight ideals have a high base rate among girls (Neumark-Sztainer & Hannan, 2000). According to the National Centers for Disease Control and Prevention, the point prevalence of dieting among high school girls was 44%. Dieting, body dissatisfaction, and disordered eating are evident even among preadolescent girls (Keel, Fulkerson, et al., 1997; Keel, Heatherton, Harnden, & Hornig, 1997). Among pre- and early adolescents, girls report worse body image, lower self-esteem, and greater disordered eating as compared to boys (Keel, Fulkerson, et al., 1997). However, some researchers (e.g., Adams, Katz, Beauchamp, Cohen, & Zavis, 1993) have found significant gender differences only among older adolescents. The significant gender differences in disordered eating, the presence of these problems at such early ages, and the pervasiveness of related behaviors and attitudes in the general population all point to societal contributions to eating pathology.

Social Contributions to Eating Pathology Important societal influences in the development of eating disorders are suggested by three general findings: (1) the relatively recent increase in the prevalence of AN and BN (for a review, see Keel & Klump, 2003), (2) the increased rate of eating disorders in industrialized as compared to nonindustrialized nations (Becker, Burwell, Gilman, Herzog, & Hamburg, 2002; Hoek et al., 2005; Lee & Lee, 2001), and (3) the significant gender difference in who is at risk for eating disorders. Social influences can be viewed as existing at multiple levels (Bronfenbrenner, 1979). At the level of culture, studies (e.g., ByrdBedbrenner, Murray, Schlussel, 2005) indicated increasingly thinner beauty ideals during the last third of the 20th century. Indeed, fashion models represent unrealistic weight ideals for the average female. Ironically, as girls enter puberty, body fat composition increases, as does girls’ internalization of these unrealistic societal aesthetic ideals (e.g., Hermes & Keel, 2003). The association between societal aesthetic ideals and body dissatisfaction among women has been well demonstrated. Several cross-sectional studies have found an association between body dissatisfaction or thin-internalization (both of which predict eating disorder pathology) and media exposure (e.g., Field et al., 1999; Tiggemann & Pickering, 1996). Further, several experimental studies have supported a causal relationship between media images

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and body dissatisfaction (e.g., Hargreaves & Tiggemann, 2004; Tiggemann & Slater, 2004). For example, Heinberg and Thompson (1995) randomly assigned female subjects to view television commercials containing either appearance-related images or non-appearance-related images. The authors found that, after exposure, women who viewed the appearance-related commercials reported significantly greater body dissatisfaction as compared to those in the non-appearance-related condition. Associations between media exposure and eating disorder symptoms have also been demonstrated crossculturally (e.g., Eddy, Hennessey, & Thompson-Brenner, 2007). In a unique naturalistic longitudinal “experiment,” Becker and colleagues (2002) found that the introduction of Western media was associated with the onset of body dissatisfaction and the development of eating disorder symptoms in young Fijian adolescents. Thus, cultural ideals of beauty can influence levels of body dissatisfaction experienced by girls. Several explanations exist for the current emphasis on thinness. Historian Joan Brumberg (1988) followed women’s social roles in U.S. society and weight ideals and notes an association between thinness as an aesthetic ideal and periods in which women are encouraged to adopt responsibilities outside the home and outside their roles as wives and mothers. This theory explains changing rates of eating disorders demonstrated in one meta-analytic review (Keel & Klump, 2003). Hsu (1989) argued that financial prosperity following the Industrial Revolution led to an abundance of food that disrupted the traditional positive correlation between wealth and weight. In societies in which wealth is associated with thinness, beauty is associated with thinness (Hsu, 1989). This theory may explain the increased prevalence of eating disorders in industrialized as compared to nonindustrialized nations and why rates of eating pathology increase as cultures become more Westernized. Bordo (1990) has argued that industrial societies promote two conflicting ideals: immediate gratification through consumerism and delay of gratification (in order to reinvest profits to produce greater profits). This conflict leads to ideals of self-control competing with attainment of happiness through consumption (Bordo, 1990). A review of these perspectives on societal values suggests that the development of eating disorders may be overdetermined within our current cultural climate. Below the level of cultural influence, there exists the influence of local social networks such as schools, peer groups, and extracurricular activities. Research has demonstrated that individuals who participate in athletic activities that place emphasis on thinness are at increased risk for eating disorders (for a review, see Smolak, Murnen, & Ruble, 2000). For example, girls enrolled in ballet schools report higher rates of eating disorder pathology as compared to control girls (e.g., Thomas, Keel, & Heatherton, 2006), as do adolescent males who participate in sports with weight limits such as wrestling (e.g., Garner & Rosen, 1991). For males, sexual preference has been posited as a risk factor for eating pathology (Carlat & Camargo, 1991), and several studies have found increased rates of eating disorders among gay and bisexual men



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as compared to heterosexual men (e.g., Carlat, Camargo, & Herzog, 1997; Feldman & Meyer, 2007; Russell & Keel, 2002). Homosexual and bisexual males may experience greater pressure to maintain lean and muscular physiques than do heterosexual males (Epel, Spanakos, Kasl-Godley, & Brownell, 1996). In these cases, societal values are reinforced by emphasis placed on weight either for performance or appearance within local social networks. Peer influence has been posited as a causal factor in the development of BN during adolescence. As teenagers shift from spending time with their families to spending time with their peers, peers become an important reference group. Mirroring findings in studies of smoking, alcohol use, and drug use, research indicates that bulimic symptom levels are more similar within friendship groups than between friendship groups in high school girls. The process of socialization may cause this similarity. Evidence for the socialization of bulimic symptoms comes from longitudinal research on friendship groups in college sororities (Crandall, 1988). This work demonstrated that friends’ binge eating grew increasingly similar over the course of the academic year. In addition, popularity was related to the extent to which an individual’s binge eating was similar to the norm for her sorority. However, binge eating patterns differed between sororities, suggesting that the “right” level of disordered eating depended upon local social norms—rather than reflecting college- or culture-wide norms. In an extension of this work, Zalta and Keel (2006) found socialization of bulimic symptoms in a general college sample, but this effect was specific to peers who had been selected on the basis of having similar levels of perfectionism and self-esteem. In addition, this effect was temporary. After a period of separation (i.e., after summer break), friends no longer demonstrated greater similarity in bulimic symptom levels as compared to the nonpeers. A third level of social influences involves the family. Although family factors have already been implicated with biological and psychological aspects of the biopsychosocial model, a family may further reinforce societal ideals of thinness. This reinforcement may occur via modeling or directly encouraging a child to adopt disordered-eating behaviors and attitudes (Cooley, Toray, Wang, & Valdez, 2008; Pike & Rodin, 1991). There is evidence of increased eating pathology among mothers of daughters with disordered eating (Pike & Rodin, 1991) as well as increased eating disorder pathology in the children of mothers with eating disorders (Stein et al., 2006). Critical comments made by parents about children’s weight as well as tendencies to restrict food intake are associated with increased child body dissatisfaction and eating disorder symptoms (e.g., Field et al., 2005; Francis & Birch, 2005). For example, one longitudinal community study of mother–daughter dyads (studied when daughters were 5, 7, 9, and 11 years old) demonstrated that mothers who were preoccupied with their own weight/shape were more likely to restrict their daughters’ intake and encourage them to lose weight (Francis & Birch, 2005). In turn, these daughters were more restrictive eaters, and the authors suggest they may be at risk for other eating disorder pathology in adolescence (Francis & Birch,

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2005). Continued follow-up through periods of increased risk for the onset of eating disorders in cohorts such as that of Francis and Birch (2005) and Stein and colleagues (2006) will continue to elucidate these dynamic relationships between parental modeling and childhood eating disorder risk. Much literature on the development of eating pathology has focused on the role of trauma, particularly sexual abuse. Although sexual abuse is associated with increased risk for eating pathology (e.g., Rayworth, Wise, & Harlow, 2004), it does not appear to be a risk factor unique to eating disorders (Finn, Hartman, Leon, & Lawson, 1986). Several studies have demonstrated an increased rate of sexual abuse among women with eating disorders as compared to normal controls; however, no significant difference is found between women with eating disorders and women with other forms of psychopathology (Wonderlich, Brewerton, Jocic, Dansky, & Abbott, 1997). To date, only one prospective study has demonstrated that childhood maltreatment (abuse or neglect) is associated with the development of eating disorder pathology in adolescents (Johnson, Cohen, Kasen, & Brook, 2002). Consistent with the findings from cross-sectional studies, the authors also found that childhood maltreatment was associated with increases in other types of psychopathology (e.g., suicidality; Johnson, Cohen, Gould, et al., 2002), suggesting that, similar to the role of temperament as a nonspecific diathesis, sexual abuse appears to represent a nonspecific stressor in the development of disordered eating. Eating disorders are precipitated through an interaction at several levels within an individual’s culture, mind, and body. At the cultural level, our society values and rewards thinness. This cultural value may be further emphasized within groups, such as athletic teams, friendship groups, or families. Families may influence a child at several levels in the development of eating pathology. The family may directly convey the importance of thinness or becoming aesthetically pleasing to others. In addition, the family may influence the selection of extracurricular activities and thus peer groups. Members of a family also may model disordered eating or contribute to early childhood difficulties in differentiating between physical and emotional needs. Families may engender significant levels of conflict or inhibit an adolescent’s quest for autonomy, leading to disordered eating as a coping response. Finally, families contribute the genetic material that may form a child’s temperament in predisposing his or her reactions to stress with emotional and behavioral dysregulation. These same biological contributors may shape levels of constraint and perfectionism, which may compel the individual to seek a “perfect body” or to participate in activities that emphasize success through self-denial. These personality features may leave the person ill equipped to deal with minor setbacks, increasing the likelihood of counterregulation (binge eating) in response to cognitive disinhibitors (such as a minor violation of one’s diet). Thus biological, psychological, and social factors require integration for a comprehensive understanding of vulnerability to developing eating pathology during childhood and adolescence.



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Developmental Changes in Risk Factors In this chapter we reviewed factors that act as a diathesis and how these factors interact with one another within the context of stressors brought about by developmental changes. We now turn to a discussion of developmental transitions in risk factors. Specifically, we address how certain factors may increase vulnerability to developing an eating disorder only at younger ages. These factors include pubertal development, actual body weight, and shared family influences. Studies have demonstrated that younger girls are more likely to demonstrate body dissatisfaction (Gralen, Levine, Smolak, & Murnen, 1990) and disordered-eating behaviors (Keel, Fulkerson, et al., 1997) if they weigh more for their height than do their peers. Conversely, studies of older adolescents demonstrate no significant relationship between actual body weight and body dissatisfaction, dieting, or disordered eating (Leon, Fulkerson, Perry, & Cudeck, 1993; Leon, Fulkerson, Perry, & Early-Zald, 1995; Leon et al., 1999). In addition, pubertal development has been uniquely associated with disordered eating in younger girls (Attie & Brooks-Gunn, 1989; Gralen et al., 1990; Keel, Fulkerson, et al., 1997; Killen et al., 1992; Koff & Rierdan, 1993) but not older adolescents (Gralen et al., 1990; Leon et al., 1993, 1995, 1999). These findings are consistent with developmental shifts occurring during adolescence. As a child matures, emphasis may shift from concrete aspects of the self, such as actual body size, to abstract aspects of the self, such as body image. As a cohort of children mature, individual differences in pubertal level diminish and thus decrease in their impact on behaviors and attitudes. A study of genetic versus environmental factors associated with disordered eating in twins (Klump et al., 2000) demonstrated that shared family environmental factors (e.g., parental styles and socioeconomic status) were a significant predictor of disordered eating for 11-year-old twins but not for 17-year-old twins. As children mature, interpersonal influences on eating behaviors and attitudes expand beyond the family to the peer group, and decisions surrounding food and eating are made outside the home more frequently. This increased autonomy, in concert with hormonal changes associated with puberty, may increase the impact of genetically influenced temperamental styles or preferences on decisions surrounding eating and exercise.

The Biopsychosocial Model: Integration of Biological, Psychological, and Social Influences Thus far, this chapter has presented an overview of research findings supporting the role of biological, psychological, and social factors in the development of eating pathology among children and adolescents. However, we feel the true strength of this conceptual approach comes from the integration of these various factors in understanding the etiology of eating disorders within the

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course of normal development. To take advantage of this strength, we now present a case history derived from a composite of patients and explore the congruence of factors leading to this adolescent’s eating disorder. Riley was 17 years old when she began treatment at the eating disorders clinic. Her mother accompanied Riley to her initial assessment. According to her mother, Riley had always been healthy and performed well in sports, academics, and music. Indeed, she was an exceptional student and had been selected for a summer program for gifted and talented students over the past summer. Although Riley had attended summer camp since she was 10 years of age, the 8-week summer enrichment program represented the longest period of time that she had been separated from her home, family, and friends. During the first week of the program, Riley reported feeling awkward in her attempts to meet people and make friends. She felt particularly insecure in her interactions with boys and noticed that everyone around her, including her roommate, appeared to have paired off into couples as if they were preparing for “Noah’s Ark.” Rather than feeling like a “third arm,” Riley decided to begin a rigorous exercise program in her free time. She reasoned that she would take advantage of the program’s facilities to ensure that she was in especially good shape at the beginning of her school’s soccer season. Riley was initially satisfied with her training program of running, swimming, and weight lifting. However, one day on her way from the pool to the women’s locker room, she passed by some boys and heard them making derogatory comments about her body. As she entered the locker room, she stopped in front of the mirror and suddenly noticed her thighs. According to Riley, her thighs were “pale and bumpy like cottage cheese.” She reported an epiphany at that moment that she was “too fat.” She skipped dinner that night and did leg lifts before bed and after getting up the next morning. She decided to limit herself to eating only “healthy foods” such as fruits and vegetables and only in small amounts. When asked how she decided what foods were healthy or how many calories per day she could eat, Riley reported that she occasionally read her mother’s magazines and scanned through the “lose 10 pounds in a week!” diets. In fact, for fun, she and her mom had gone on a diet together when Riley was 12 years old. Riley joked that it was not a “real diet” because she and her mother would eat several high-calorie, highfat foods like peanut butter on celery sticks or ice cream in diet root beer floats. Riley reported other short-lived diets that involved eating tuna fish or grapefruit that she and her friends would go on together. However, the summer diet was the first time that Riley followed a rigid program of food and exercise. Riley reported that her program made her feel “great”—she felt “strong and in control” and was frequently complimented by her roommate for how “good” she was. Riley also noticed that, if she went long enough without eating, she would stop feeling hungry. When she would eat, she would feel full after very little food. She took this as evidence that her stomach was shrinking. When Riley returned home from the summer program,



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her mother was dismayed by how much weight her daughter had lost. Riley had gone from weighing 125 pounds at 5′5″ to weighing 105 pounds. Meal times became very stressful, as Riley refused to eat anything with her family. However, Riley’s mother started noticing certain food items would disappear overnight. After 4 months of rigid adherence to her summer program, Riley reported that she “lost control” one night and ate an entire package of cookies. Distraught by her actions, she resolved to eat nothing the next day and doubled her exercise routine. Within a week, Riley had another episode in which she consumed a gallon of ice cream at night when everyone else was asleep. Riley’s binge episodes came more frequently, and, despite her frantic efforts to compensate through exercising and fasting, she quickly regained all the weight she had lost. Riley reported feeling “trapped.” Every attempt she made to regain control was thwarted with binge eating episodes. By late fall, Riley became increasingly depressed and anxious over her binge eating. As she became more depressed, her binge episodes grew worse, and as her binge episodes grew worse, she became more depressed. Her cycle of binge eating followed by fasting and exercising increased during times of stress such as soccer finals and college interviews. Riley’s mother was particularly concerned about the impact the eating disorder was having on Riley’s mood and on the family. Riley began talking about “feeling suicidal,” and Riley’s 10-year-old sister was beginning to talk about “feeling fat” and “needing to lose weight.” This case study illustrates many of the points made earlier in this chapter. Riley’s disordered eating occurred during her first significant separation from her home, which may signal the separation associated with going to college. The summer program also presented Riley with a developmental shift from interpersonal affiliations within the family to monogamous dating relationships. These changes represented stressors in her life. With regard to her diathesis or vulnerability for eating pathology, she was exposed to societal idealization of thinness through her mother’s magazines. She was also encouraged to engage in dieting by her mother and peers, starting at 12 years of age as she was transitioning into puberty. Riley received positive reinforcement for being “good” from her roommate in the summer program. Indeed, the evaluation of Riley’s self-denial as being “good” by her roommate represented a culturally embedded moral declaration. At the level of psychological factors, Riley’s exercise program was initiated during a period of feeling insecure in her peer interactions. Her diet program was initiated after feeling self-conscious about her body in front of teenage boys. Riley’s epiphany of “being fat” engendered body dissatisfaction that motivated her dieting. Her severe food restriction interfered with her hunger and satiety signals. Later, her dieting seemed to lead to binge eating and the eventual use of binge eating episodes to cope with feelings of depression and anxiety. For biological risk factors, Riley’s case history suggests a temperament

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marked by high stress reactivity (a factor within the larger domain of negative affectivity) and perfectionism. This temperamental characteristic led Riley to be vulnerable not only to eating disorders but also to significant levels of depression and anxiety. Although her 10-year-old sister’s statements about weight and diet may be a result of modeling, they may also reflect a culturally shaped response to a shared genetic vulnerability for high-stress reactivity. For Riley, treatment involved individual psychotherapy and antidepressant medication.

Treatment and Prevention Eating disorders often require multimodal treatments involving psychotherapy, pharmacotherapy, medical management, and nutrition counseling. The level and intensity of treatment may vary from outpatient to residential, or inpatient, based on the clinical severity of the illness. Given the developmental differences between children and adolescents, on the one hand, and adults, it is critical to include youth in treatment research and to focus efforts on developing interventions aimed at addressing eating disorders in youth (for a review, see Keel & Haedt, 2008). One example of these efforts has been the considerable research on family-based treatment for adolescent AN (e.g., Lock, Agras, Bryson, & Kraemer, 2005) and more recently BN (Le Grange et al., 2007). Family-based treatment for eating disorders is an outpatient family therapy approach that takes an agnostic view of the cause of the eating disorder and aims at refeeding the undernourished child patient and interrupting the binge–purge cycle. Parents are actively involved in the therapy and empowered to initially take more control over their child’s eating to help restore her health. Parents then begin to step back when the child’s eating disorder symptoms are under control. This approach has received empirical support in a number of clinical trials with adolescents with AN (e.g., Lock, Agras, et al., 2005; Lock, Couturier, & Agras, 2006) more recently in a randomized controlled clinical trial of adolescents with BN and related EDNOS (Le Grange, Crosby, Rathouz, & Leventhal, 2007), and in a case series of children, ages 9–12, with eating disorders (Lock, Le Grange, Forsberg, & Hewell, 2006). Individual psychotherapy is often used for adolescents with eating disorders. Therapy that incorporates cognitive-behavioral techniques involving psychoeducation about the links between dietary restraint and binge eating, the identification of affective and interpersonal triggers of restricting, binge eating, and purging may be useful (Schmidt et al., 2007). This treatment may make explicit and challenge associations between cultural ideals of thinness, body dissatisfaction, dieting, and disordered eating. While cognitive-behavioral therapy and interpersonal therapy for eating disorders have not yet been studied in younger adolescents, they are likely to be useful with some develop-



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mental modifications. For example, younger patients may have more difficulty recognizing and articulating their cognitions, and thus the focus may be more on behavioral change. Pharmacological treatment often involves antidepressant medications, especially selective serotonin reuptake inhibitors due to their more tolerable side effects. Interestingly, the efficacy of antidepressant medication in reducing binge eating behavior appears to be independent of its impact on levels of depression (Mitchell et al., 1990). Notably, empirical study of the efficacy of pharmacological treatments for eating disorders in younger patients has been limited. Given the recent black box warnings about the possibility that antidepressant medications may increase suicidality in youth, these interventions should be used with careful monitoring (e.g., Lock, Walker, Rickert, Katzman, & Society for Adolescent Medicine, 2005). Overall, the efficacy of each of these treatment modalities further supports the biopsychosocial model in conceptualizing eating disorder vulnerability. A wide range of programs aimed at the prevention of eating disorders have been developed and tested in child and adolescent samples (for recent reviews, see Levine & Smolak, 2007; Stice, Shaw, & Marti, 2007; Taylor, 2005). These programs focus on decreasing variables that have been identified as risk factors for eating disorders (e.g., body dissatisfaction, thin-internalization) and increasing variables that may help to prevent eating disorders (e.g., self-esteem, media literacy). Components of these programs have included psychoeducation to increase adolescents’ awareness of media influences on “ideal” body types, determinants of body size, nutritional needs, consequences of dieting, and consequences of disordered eating. Recent reviews generally indicate that programs targeting specific at-risk populations (e.g., Elliot et al., 2004; Stice, Shaw, Burton, & Wade, 2006) are most effective, although universal programs that focus on changing peer “norms” can also be effective, particularly for younger populations (e.g., Austin, Field, Wiecha, Peterson, & Gortmaker, 2005; McVey et al., 2007). Notably, the existing literature suggests that prevention programs may be most effective when administered to adolescents who are 15 years or older and thus considered to be in the period of risk for the development of an eating disorder (Stice et al., 2007). However, given that there does not seem to be an iatrogenic effect of these programs, it is also possible that longer-term follow-up studies of children who participate in prevention programs may demonstrate decreased risk over time (e.g., a “sleeper effect”). Prevention efforts will likely improve with further development and refinement.

Future Directions Future research could benefit from identifying factors that protect against the development of eating pathology in children and adolescents who appear to be

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at high risk. Such factors may include social support, a greater range of qualities influencing self-worth, and greater flexibility in responding to change. One study found that male and female athletes reported greater body satisfaction (Fulkerson, Keel, Leon, & Dorr, 1999), suggesting that participation in “nonelite” athletics may serve as a protective factor. The identification of protective factors would significantly contribute to the efficacy of prevention programs. Given the confluence of onset of eating pathology with a developmental shift in primary relationships from the nuclear family to peers, research on the mechanisms by which peers influence the development of eating pathology also seems warranted. Such research may elucidate the transmission of specific behaviors such as fasting that appear to spread within peer groups. In addition, this focus may reveal how membership within certain peer groups may protect girls from the development of eating disorders during adolescence. Because longitudinal studies with frequent follow-up intervals extending throughout the period of risk are labor- and time-intensive, collaborative studies that evaluate risk and protective factors for several forms of psychopathology may be efficient in terms of costs and the variety of relevant findings. This approach increases the feasibility of studying a full range of factors in large samples from early childhood to adulthood. This research also provides a model for studying developmental psychopathology within a biopsychosocial model.

Conclusions In this chapter, we presented a developmental perspective on eating disorders during childhood and adolescence within a biopsychosocial model. The periods of risk for the onset of eating disorders are marked by developmental transitions from childhood to adolescence and from adolescence to adulthood. The changing demands of these developmental transitions provide the context in which various biological, psychological, and social risk factors increase vulnerability to eating pathology. Temperamental styles marked by negative affectivity, genetic liability to develop eating pathology and anxiety disorders, and serotonin dysregulation have all received empirical support as biological factors that may contribute to the etiology of eating disorders. Psychodynamic, behavioral, and cognitive emotional perspectives have shed light on the role of psychological factors such as alexythymia, dieting, body dissatisfaction, emotion regulation, and self-esteem in the development of disordered eating. We have reviewed the levels of social influence, ranging from cultural ideals of beauty and morality to the impact of family and peer groups, in the adoption of disordered-eating behaviors and attitudes. Finally, we presented an integration of these various factors into a unified biopsychosocial model, also tracing the development of an eating disorder through reference to a case study.



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Although many risk factors may remain stable in their impact on vulnerability throughout the lifespan, we presented research suggesting developmental changes in risk factors. As more research is conducted utilizing a developmental perspective, we anticipate that more developmental changes in risk factors will be revealed. Attention to this question may improve the formation of appropriate intervention and prevention programs. Continued research is required to develop and validate developmentally sensitive intervention and prevention programs that will hopefully turn back the tide of young girls and boys developing eating disorders.

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Chapter 18

Vulnerability to Eating Disorders in Adulthood Jennifer J. Thomas, Marlene B. Schwartz, and Kelly D. Brownell

The aim of this chapter is to present two distinct etiological models of vulnerability to eating disorders in adulthood and to evaluate the empirical support for each within a biopsychosocial model. Eating disorders encompass three distinct diagnoses in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000): anorexia nervosa (AN), bulimia nervosa (BN), and eating disorder not otherwise specified (EDNOS). Epidemiological studies indicate that the most prevalent eating disorder in community samples is a subtype of EDNOS called binge-eating disorder (BED; Hudson, Hiripi, Pope, & Kessler, 2007). As Eddy, Keel, and Leon (Chapter 17, this volume) highlight, AN and BN most often present during critical life transitions among young females. However, body dissatisfaction and weight-control behaviors are normative among adult women throughout the lifespan (Mangweth-Matzek et al., 2006; Tiggemann, 2004), and late-onset cases of AN, BN, and EDNOS have been reported in adults up to 70–80 years old (Beck, Casper, & Andersen, 1996; Parke, Yager, & Apfeldorf, 2008). Furthermore, available data suggest that approximately half of individuals with BED experience their first binge-eating episodes in adulthood (Abbott et al, 1998; Spurrell, Wilfley, Tanofsky, & Brownell, 1997) and that the average age of BED onset is approximately 25 (Hudson et al., 2007). Therefore, in this chapter on adult-onset eating disorders, we will focus exclusively on the etiology of BED. We will present two distinct etiological models—the dietary restraint model and the interpersonal vulnerability model—and then review the empirical support for each from both biological and psychosocial perspectives. Finally, we will discuss the implications of

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these models for both treatment and prevention as well as highlight promising directions for future research.

Definition of BED The diagnostic presentation of BED is similar to that of BN in that both disorders feature a recurrent pattern of overeating accompanied by a sense of loss of control. The primary difference between the two is that individuals with BED do not engage in the concomitant compensatory behaviors (i.e., vomiting, laxative use, diuretic use, fasting, or excessive exercise) that are the hallmark of BN. Table 18.1 presents the DSM-IV-TR criteria for BED.

Prevalence of BED in Adults Epidemiological studies indicate that the prevalence of BED is probably higher than the prevalence of both AN and BN combined. In the National Comorbidity Survey Replication, which featured face-to-face diagnostic interviews of 2,980 nationally representative U.S. adults, 3.5% of women and 2.0% of men met the lifetime criteria for BED (Hudson et al., 2007), whereas only 0.6% and 1.0% of participants met the lifetime criteria for AN and BN, respectively. Smaller-scale community studies have produced BED point prevalence estimates ranging from 2.0 to 4.6% (Spitzer et al., 1992, 1993). The prevalence of BED appears to be substantially higher among individuals seeking weight-loss treatment than in the general population. Specifically, 30% of individuals seeking behavioral weight-loss assistance at a university clinic (Spitzer et al., 1992, 1993) and 15% of those attending Jenny Craig, a commercial weight-loss program (Schwartz & Brownell, 1998), met the criteria for BED. The highest rates of BED have been identified in the self-help group Overeaters Anonymous, with estimates ranging from 50% (Schwartz & Brownell, 1998) to 70% (Spitzer et al., 1993). In addition to individuals experiencing full syndrome BED, a significant minority of obese persons experience some binge eating and loss of control. Robertson and Palmer (1997) found that 24% of women with a history of obesity reported eating unusually large amounts of food, and half of those (i.e., 12%) endorsed loss of control while overeating.

Scientific Approaches to the Study of Risk Factors In this chapter we will review genotypes, demographic characteristics, psychological processes, and life events that are more commonly observed in individuals with BED than in healthy controls. However, a true risk factor for a

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TABLE 18.1.  DSM-IV-TR Research Criteria for Binge-Eating Disorder A. Recurrent episodes of binge eating. An episode of binge eating is characterized by both of the following: (1) eating, in a discrete period of time (e.g., within any 2-hour period), an amount of food that is definitely larger than most people would eat in a similar period of time under similar circumstances (2) a sense of lack of control over eating during the episode (e.g., a feeling that one cannot stop eating or control what or how much one is eating) B. The binge-eating episodes are associated with three (or more) of the following: (1) eating much more rapidly than normal (2) eating until feeling uncomfortably full (3) eating large amounts of food when not feeling physically hungry (4) eating alone because of being embarrassed by how much one is eating (5) feeling disgusted with oneself, depressed, or very guilty after overeating C. Marked distress regarding binge eating is present. D. The binge eating occurs, on average, at least 2 days a week for 6 months. E. The binge eating is not associated with the regular use of inappropriate compensatory behaviors (e.g., purging, fasting, excessive exercise) and does not occur exclusively during the course of Anorexia Nervosa or Bulimia Nervosa. Note. From American Psychiatric Association (2000). Copyright 2000 by the American Psychiatric Association. Reprinted by permission.

psychiatric disorder both precedes the onset of the disorder and can be used to reliably divide a population into high- and low-risk groups (Jacobi, Hayward, de Zwaan, Kraemer, & Agras, 2004; Kraemer et al., 1997). Moreover, a causal risk factor can be purposefully manipulated in order to prospectively alter an individual’s risk for the disorder (Kraemer et al., 1997). Thus, risk factors can only be accurately identified through longitudinal and experimental designs. Because BED was added to the psychiatric nomenclature less than 20 years ago with the 1994 publication of DSM-IV, no variables have yet earned the distinction of being designated a causal risk factor. However, carefully constructed cross-sectional and retrospective studies have identified several theoretically interesting disease correlates that may ultimately achieve status as an empirical risk factor through future prospective work.

Two Research Generations of BED Etiology The study of the etiology of BED can be divided into two research generations comprising distinct classes of study designs. The first generation featured retrospective and case-control studies and typically evaluated individuals with BED presenting for weight loss or eating disorder treatment. Such designs are quite useful in identifying disease correlates, especially when a disorder is rare and little is known about its etiology. In retrospective self-report studies, individuals are asked to recall relevant life events that preceded their binge eating (e.g., the age at which they began dieting) (see Abbott et al., 1998; Spurrell et al., 1997). Similarly, in case-control studies, individuals who have



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the disorder are identified, and for each subject a control subject with the same demographic profile is identified. This method is used by Fairburn et al. (1998) to compare individuals with BED to healthy controls matched on age and parental social class. These studies are valuable in identifying individual characteristics and life events that are associated with BED. However, true risk factors cannot be established in retrospective and case-control studies, because it is possible that the variables under study are merely symptoms or consequences of BED rather than causal antecedents. Similarly, the comparison of BED patients versus healthy controls raises the possibility that the observed between-group differences are due in part to treatment-seeking status rather than binge-eating status. Thus, the second generation of etiological research has attempted to use experimental designs to evaluate whether the correlates of BED identified in the first research generation can be classified as true risk factors for the disorder rather than mere correlates. Experimental studies randomly assign participants to engage in a behavior hypothesized to either cause or protect against binge eating. They then evaluate whether participants assigned to this condition are more or less likely than control participants to develop binge eating during the experiment. Such studies typically recruit healthy participants from the general community rather than relying on BED patient samples. For example, Presnell and Stice (2003) randomly assigned nonobese adult women to a 6-week low-calorie diet program or a wait-list control condition to determine whether dieting would precipitate binge-eating behaviors. Another method that helps to rule out rival hypotheses is the prospective longitudinal study. Longitudinal studies measure disease correlates at baseline before individuals develop a disorder and then evaluate whether these correlates prospectively predict the onset of the disorder over time. To our knowledge, there have not yet been any long-term prospective studies of full-syndrome BED onset, although a handful of studies have examined longitudinal trends in the prevalence of binge eating as individuals transition into early and middle adulthood. Prospective studies of BED onset would be very informative, but they are quite costly and require very large sample sizes because most participants will not go on to ultimately develop BED. Thus, these designs will likely figure prominently in the third generation of etiological research.

Methods of Assessment The study of eating disorders uses two primary methods of assessment: questionnaires and interviews. Because the variables of interest are behaviors that individuals often hide due to shame (i.e., binge eating and purging), it is difficult to validate measures by observation or corroborative interviews with family members. The features associated with BED are also difficult to describe; for example, evidence indicates that people do not agree on what constitutes a binge (Beglin & Fairburn, 1992). Although weight and other physiological measures may suggest binge eating or purging, these are typically not used

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in research as indicators of psychopathology. Sometimes self-monitoring of food intake is used to assess eating behavior. This may be more accurate than retrospective self-report, but it is time-consuming and the process of recording intake may promote change. A few studies have measured binge eating in the laboratory, but these studies are most useful in examining responses to specific stimuli rather than in observing normative consumption patterns (Wilson, 1993). The most common method of eating disorder assessment is the self-report questionnaire. Commonly used measures include the Binge Eating Scale (BES; Gormally, Black, Daston, & Rardin, 1982), the Eating Disorder Inventory (EDI-3; Garner, 2004), the Eating Disorders Examination Questionnaire (EDE-Q-6.0; Fairburn & Beglin, 2008), and the Questionnaire on Eating and Weight Patterns (QEWP-R; Spitzer et al., 1993). Each of these measures has adequate psychometric properties, although due to the secretive nature of eating disorder symptoms, validity remains a concern. The second method of assessment is the interview. The Eating Disorder Examination (EDE 16.0; Fairburn, Cooper, & O’Connor, 2008) is an investigator-based semistructured interview that assesses the core psychopathology of eating disorders. This technique has historically been preferred over self-report questionnaires because the interviewer can clarify definitions for participants and use a standard set of criteria when assessing participants’ scores on different features. Although it was initially assumed that interviews would generate more accurate eating disorder diagnoses than questionnaires, two recent studies have demonstrated that a substantial minority of individuals exhibit greater candor about their eating disorder symptoms in questionnaires, perhaps due to the greater anonymity afforded by the self-report versus the face-to-face format (Keel, Crow, Davis, & Mitchell, 2002; Mond, Hay, Rodgers, & Owen, 2007). Several studies have evaluated the concordance between the EDE interview and the corresponding self-report version, the EDE-Q. In general, findings suggest that the interview and questionnaire correspond most closely for salient behavioral items (e.g., purging) and less so for more complex cognitive features (e.g., overconcern about shape and weight) (Black & Wilson, 1996; Wilfley, Schwartz, Spurrell, & Fairburn, 1997). Concordance between interviews and questionnaires can be improved by having respondents read hypothetical descriptions of complex concepts, such as the amount of food consumed during a typical binge episode, before completing the questionnaire (Goldfein, Devlin, & Kamenetz, 2005).

Models of the Etiology of BED To date, two distinct etiological models of BED have received the most empirical support: the dietary restraint model and the interpersonal vulnerability



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model (see Wilfley, Pike, & Striegel-Moore, 1997). Schematics of each model are presented in Figure 18.1. It is possible that individuals develop BED through either the dietary restraint or interpersonal vulnerability pathway, or that both pathways operate simultaneously and interactively to precipitate the onset of the disorder within a single individual.

The Dietary Restraint Model The dietary restraint model emphasizes the role of extreme dieting as an immediate precursor to the initiation of binge eating (Polivy & Herman, 1993). This model posits that individuals experience an emphasis on weight and shape in their social network, which they then internalize as priorities for themselves. These unrealistic pressures for thinness create body dissatisfaction, which individuals attempt to ameliorate through overrestrictive dieting. Overrestrictive diets include behaviors such as fasting, skipping meals, completely avoiding certain foods, and labeling certain foods as categorically “bad.” Diets that involve the complete avoidance of certain foods may increase the likelihood of binge eating through the abstinence violation effect (Wilson, 1995a). The abstinence violation effect occurs when people decide to avoid a particular type of food (e.g., cake) and then find themselves in a situation in which eating that food seems unavoidable (e.g., a birthday party). After eating a normal portion of the food (or even just a single bite), they feel they have “blown it” and they may as well continue eating. The binge-eating behavior can be attributed to all-or-nothing thinking: “If I can’t eat perfectly, I may as well not try to restrain at all.” Another cognitive factor that may trigger binge eating in this overrestrictive context is the plan to resume the diet tomorrow. One experimental study found that merely notifying chronic dieters that they had been randomly assigned to embark on a new diet the next day caused them to consume more cookies in a laboratory-based taste test as compared to chronic dieters assigned to the no-diet condition, a phenomenon theorists refer to as the “last-supper effect” (Urbszat, Herman, & Polivy, 2002). Following a binge-eating episode, the diet typically becomes even more rigid, which perpetuates the diet–binge cycle. Wilfley, Pike, et al. (1997) present evidence in support of the dietary restraint model for each stage and note that the primary strength of the model is that it describes a set of very specific putative risk factors. They add that the weakness of the model, however, is that each of the variables may be neither necessary nor sufficient to predict the development of an eating disorder. For example, many people diet, yet only a small minority ultimately develop eating disorders (see Wilson, 1995a). In addition, evidence presented later in this chapter demonstrates that dieting does not always precede binge eating among individuals with BED and that assigning healthy individuals to a dieting condition does not typically precipitate binge eating in experimental studies.

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CLINICAL SYNDROMES RESTRAINT MODEL Emphasis on weight/shape in social network

INTERPERSONAL VULNERABILITY MODEL Disturbance in early child–caretaker relationship

Internalized social expectations about thinness and beauty

Insecure attachment

Body image concerns

Disturbance in self (social self-disturbance, low self-esteem)

Extreme dietary restraint

Affective dysregulation

Binge eating

Binge eating

FIGURE 18.1.  Models of etiology of binge eating: Dietary restraint and interpersonal vulnerability. From Wilfley, Pike, and Striegel-Moore (1997). Copyright 1997 by Plenum Publishing Corp. Reprinted by permission of Springer Science and Business Media.

The Interpersonal Vulnerability Model The interpersonal vulnerability model differs most clearly from the dietary restraint model in that dieting is not necessarily a precursor to binge eating. Rather, this model states that binge eating develops as a way of coping with negative affect. Wilfley, Pike et al. (1997) present a detailed description of this model as well as the research findings that support it. To summarize, vulnerability begins in childhood with a disturbance in the individual’s relationship with early caregivers. If caregivers are unable to meet the child’s physical and emotional needs, the individual develops an insecure attachment style. This leads to low self-esteem and social self-disturbance, which is defined as a heightened concern about how one is viewed by others, an excessive need for a positive self-presentation and social approval, and a feeling of inadequacy when compared to others (Wilfley, Pike, et al., 1997). This impairment in social functioning then leads to affective dysregulation and depression, which the person tries to cope with by binge eating. The binge eating is presumed to help the person “numb out” these negative feelings and escape from selfawareness (Heatherton & Baumeister, 1991). Indeed, ecological momentary assessment paradigms in which individuals with BED record feelings and behaviors in real time on palm top computers indicate that binges are typically preceded by high levels of negative affect (Hilbert & Tuschen-Caffier, 2007; Stein et al., 2007). Historically, it is interesting to note that both the dietary restraint and interpersonal vulnerability models originated in the BN literature and emerged



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as a pair after the finding that BN patients responded equally well to interpersonal therapy and cognitive-behavioral therapy (Fairburn, Jones, Peveler, Hope, & O’Connor, 1993). These treatments were then adapted and tested with patients with BED, and results suggest that both treatment approaches are effective in treating binge eating (Wilfley et al., 1993; Wilfley et al., 2002).

The Biological Perspective Although many individuals go on diets and experience interpersonal difficulties throughout the lifespan, only a minority eventually develop BED in adulthood. Thus, it is likely that some individuals exhibit greater biological vulnerability to the development of the disorder. Family and twin studies indicate that eating disorders, including BED, are clearly heritable and tend to run in families. However, investigations of individual candidate genes have not yet conclusively identified which alleles are most likely to increase biological risk for these disorders (Becker et al., 2004). Two familial factors—childhood obesity and parental mood disorders—are more common among individuals with BED than in controls, and therefore these highlight possible mechanisms of familial transmission.

Family and Twin Studies Several recent studies have demonstrated that BED runs in families (Hudson et al., 2006; Javaras et al., 2008; Lilenfeld, Ringham, Kalarchian, & Marcus, 2008). For example, Hudson and colleagues (2006) interviewed 150 individuals with BED, 150 individuals without BED, and 888 of their first-degree relatives. They found that family members of individuals with BED were twice as likely to have BED themselves than family members of individuals without BED. This pattern of aggregation among relatives is suggestive of genetic effects, but family studies cannot entirely rule out environmental influences. For example, parents can affect their children’s caloric intake, food preferences, and weight status by role modeling the consumption of specific foods, applying pressure to eat (e.g., “finish your soup”), or restricting the availability of specific foods in the home (Ventura & Birch, 2008). Thus, psychosocial processes could account for the observed pattern of familial aggregation even in the absence of genetic effects. Twin studies provide an avenue through which genetic explanations can be evaluated alongside environmental ones. Twin studies of binge eating indicate that monozygotic twins, who share 100% of their genes, are more likely than dizygotic twins, who share approximately 50% of their genes, to be concordant for binge eating in the absence of compensatory behaviors (Reichborn-Kjennerud, Bulik, Tambs, & Harris, 2004) and also to be concordant for full-syndrome BED (Javaras et al., 2008). Heritability estimates range from 41% for binge eating behaviors (Reichborn-Kjennerud et al., 2004) to

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39% for full-syndrome BED (Javaras et al., 2008) and are slightly lower than comparable estimates for AN and BN (Jacobi et al., 2004).

Candidate Gene Studies The familial clustering of BED clearly raises the question of which genes are most likely to confer risk for the disorder. However, the pathophysiological mechanisms of BED remain poorly understood. Only a handful of alleles have been linked to BED in the nascent study of candidate genes, and replications are needed before firm conclusions can be drawn. Nevertheless, newfound genetic associations have inspired interesting hypotheses about abnormalities in neurotransmitter and hormone systems—including serotonin, ghrelin, and melanocortin—that may set the stage for binge eating.

Serotonin Function Serotonin is a neurotransmitter thought to influence both appetite and mood. The 5HT transporter protein regulates the amount of serotonin present in the synaptic cleft. In one study, individuals with BED were more than twice as likely as individuals without BED to be carriers of the L allele in the 5-HTTLPR polymorphism (Monteleone, Tortorella, Castaldo, & Maj, 2006). Because the L allele is associated with increased synaptic 5-HT uptake, the investigators hypothesized that decreased synaptic concentration of serotonin may leave individuals vulnerable to binge eating. The potential association between serotenergic dysfunction and binge eating is consistent with meta-analytic findings that selective serotonin reuptake inhibitor (SSRI) antidepressant medications, which work in part through altering serotonin function, are at least modestly efficacious in the pharmacologic management of BED (Reas & Grilo, 2008).

Melanocortin Function Melanocortin is a hormone that regulates appetite, and genetic mutations to the melanocortin 4 receptor (MC4R) gene have been linked to both overeating and obesity in humans. In a recent genetic study, 100% of individuals with an MC4R mutation met diagnostic criteria for BED, compared to just 14% of obese and 0% of nonobese individuals without this mutation (Branson et al., 2003). These findings suggest that melanocortin dysfunction may increase risk for the development of BED, possibly through stimulating appetite or enhancing metabolic efficiency.

Ghrelin Function Ghrelin is another hormone that stimulates appetite. Laboratory studies have demonstrated that, compared to healthy controls, individuals with BED exhibit lower levels of fasting ghrelin and also experience smaller postpran-



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dial decreases in ghrelin concentration (Geliebter, Gluck, & Hashim, 2005). The C214A gene, which regulates ghrelin function, features the Leu72Leu, Leu72Met, and Met72Met genotypes. In a recent study, individuals with BED were nearly three times as likely as individuals without BED to have the Leu72Met genotype of the C214A gene (Monteleone, Tortorella, Castaldo, Di Filippo, & Maj, 2007). Thus, the investigators hypothesized that this genotype may confer biological vulnerability to binge eating.

Possible Mechanisms of Familial Transmission In the absence of more robust data on specific candidate genes, theorists have hypothesized alternative pathways through which BED may be transmitted in families. To date, childhood obesity and parental mood disorders have received the most research attention. Either of these factors could plausibly increase BED risk via genetic or environmental processes.

Childhood Obesity The majority of individuals with BED are obese, and individuals with BED have significantly higher body mass indices than unaffected individuals (Hudson et al., 2007). Body weight is influenced by both genetics and environment (Brownell & Wadden, 1992). Specifically, obese parents may be more likely to produce obese offspring because they passively transmit obesogenic genes or because they actively role model greater caloric consumption and a sedentary lifestyle. Two separate community-based case-control studies (Fairburn et al., 1998; Striegel-Moore et al., 2005) found that individuals with BED are more likely than individuals with other psychiatric disorders to report a history of childhood obesity, suggesting that pediatric obesity may be a specific risk factor for BED. Similarly, in a large sample of BED treatment seekers, nearly two-thirds (63%) reported that they had been at least 10–15 pounds overweight prior to the onset of their eating disorder (Reas & Grilo, 2007). Among participants whose weight problems preceded binge eating, the mean age of overweight onset was 12.2 years, and the mean age of BED onset was 27.3 years (Reas & Grilo, 2007). Childhood obesity may lead to vulnerability as outlined by the dietary restraint model if being overweight increases the likelihood of dieting. On the other hand, in a recent family study of BED, the familial clustering of BED was independent of the familial clustering of obesity (Hudson et al., 2006). Therefore, although obesity and BED often cooccur, neither is necessary nor sufficient to cause the other. In addition to childhood obesity, adult obesity may increase individuals’ risk for adult-onset BED. Many studies have tested the hypothesis that individuals who are obese exhibit greater levels of psychopathology than do individuals of normal weight. This hypothesis has received mixed support (Hrabosky & Thomas, 2008). Friedman and Brownell (1995) review this literature and present a model for research suggesting that obesity alone is

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not related to psychological distress; rather, additional variables combine to place specific individuals who are obese at higher risk of psychopathology. One possible mediator between obesity and psychopathology is binge-eating behavior. For example, Telch and Agras (1994) divided a sample of obese women with BED into those with moderate or severe binge eating and those with moderate or severe obesity. They then compared the groups on measures of depression, self-esteem, interpersonal problems, and general distress. They found that severity of binge eating, not level of obesity, accounted for the differences between groups on these psychological variables. This supports the view that binge eating may partially mediate the relationship between obesity and psychopathology. It is possible that individuals born with a genetic predisposition for becoming overweight engage in dieting behavior as they become heavier, which, in turn, precipitates the onset of binge eating. As the binge eating worsens, their weight increases, both of which fuel increases in psychological distress.

Parental Mood Disorder Individuals with BED report higher rates of parental lifetime mood disorders and more conflictual parent–child relationships than healthy controls (Fairburn et al., 1998; Striegel-Moore et al., 2005). Both of these retrospective correlates are consistent with the interpersonal vulnerability model of BED etiology. Having a parent with a mood disorder can increase one’s own risk of developing a mood disorder through either genetic or environmental pathways (Harrington, 1996; Marton & Maharaj, 1993). However, a recent family study demonstrating that BED clusters in families independently of familial mood disorders (Lilenfeld et al., 2008) provides greater support for environmental versus genetic explanations. For example, high levels of negative affect and interpersonal difficulties may confer generalized mental health risk for a variety of maladaptive coping behaviors. The development of binge eating in particular may stem from preexisting biological vulnerabilities (ghrelin dysfunction) or social learning (seeing others use food to numb out negative affect).

the Psychosocial Perspective In contrast to the limited number of empirical studies on potential biological risk factors for binge eating, there is a substantial literature on psychological and social factors that may contribute to BED risk. Within a biopsychosocial model, individuals who possess an underlying genetic predisposition for binge eating may be especially vulnerable to the effects of psychosocial stressors and thus more likely to ultimately express BED symptoms. Put more succinctly, “Genetic background loads the gun, but the environment pulls the trigger” (Bray, 2004, p. 115). The proposed psychosocial correlates of BED can be broadly categorized into demographic characteristics, psychological charac-



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teristics, and life events that may precipitate the development of the disorder in genetically vulnerable individuals.

Demographic Characteristics of Individuals with BED Demographic variables, such as sex, ethnicity, and sexual orientation, provide interesting insights into risk for psychiatric disorders because they are determined at birth and do not change spontaneously throughout the lifespan. Such static variables are called fixed markers (Kraemer et al., 1997). Their empirical association with BED in correlational studies is especially informative because, by definition, they precede the onset of the disorder and therefore cannot merely be consequences of it. Of course, in the absence of prospective longitudinal studies, the possibility that a third variable explains their cooccurrence cannot be ruled out.

Gender Approximately 90% of individuals with AN and BN are female. In contrast, observational studies indicate that 40% (Wilson, Nonas, & Rosenblum, 1993) to 50% (Hudson et al., 2007) of individuals who binge eat are male. Therefore, while biological sex is undoubtedly a fixed marker for AN and BN, the relationship between sex and BED risk is less clear. Interestingly, males are less likely than females to report feeling distressed after overeating episodes (Lewinsohn, Seeley, Moerk, & Striegel-Moore, 2002). Differential levels of distress may be due in part to pervasive gender-based consumption stereotypes. Observers negatively label females who eat large portions as appearing less feminine, but positively label males who eat large portions as appearing more masculine (Vartanian, Herman, & Polivy, 2007). Some preliminary work has examined potential sex differences between male and female BED patients. Two studies did not reveal any sex differences in eating disorder features, level of depression, or self-esteem (Barry, Grilo, & Masheb, 2002; Tanofsky, Wilfley, Spurrell, Welch, & Brownell, 1997). However, one of these studies found that males with BED were more likely than their female counterparts to be obese (Barry et al., 2002), and both studies reported a significantly greater lifetime prevalence of substance abuse in males than females (Barry et al., 2002; Tanofsky et al., 1997). Because environmental pressures to engage in disordered eating behaviors are arguably greater among women, it is possible that the greater substance use seen in male BED patients is reflective of the greater genetic loading necessary for males to develop an eating disorder. However, this hypothesis has yet to be empirically tested.

Ethnicity Eating disorders have historically been considered a problem that affects affluent Caucasian women. With the emergence of BED as a diagnostic category,

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however, that stereotype is changing. Indeed, while one large populationbased study found that Caucasians were twice as likely as African Americans to meet criteria for BED (2.7 vs. 1.4%, respectively), the difference was only marginally statistically significant (OR = 2.0, 95% CI [1.0, 3.8]; StriegelMoore et al., 2003), and other studies have not identified higher rates of BED in Caucasians than in other ethnic minority groups (Fitzgibbon et al., 1998; Sanchez-Johnsen, Dymek, Alverdy, & Le Grange, 2003). Caldwell, Brownell, and Wilfley (1997) hypothesize that studies identifying higher levels of eating pathology among Caucasian than ethnic minority women may reflect class rather than race effects. For example, they found similar levels of body dissatisfaction and self-esteem among African American and Caucasian dieters when both groups were of middle or high socioeconomic status (Caldwell et al., 1997).

Sexual Orientation Homosexual orientation appears to be associated with greater levels of binge eating among men but not women. Early studies of males with eating disorders reported that a disproportionately high number of them were gay or struggling with their sexual orientation (e.g., Herzog, Norman, Gordon, & Pepose, 1984; Schneider & Agras, 1987), and several subsequent studies have identified higher rates of eating pathology among gay versus heterosexual men in nonclinical samples. In a self-report questionnaire study of undergraduates, gay men reported greater concern about physical attractiveness, greater body dissatisfaction, and higher levels of eating disorder psychopathology than heterosexual men (Siever, 1994). Similarly, a large community-based study utilizing face-to-face interviews identified higher rates of full- and partialsyndrome eating disorders, including BED, among gay versus heterosexual men (Feldman & Meyer, 2007). In contrast, lesbian orientation has not been reliably associated with eating disorder risk. Several studies have found comparable levels of eating disorder symptoms, including binge eating, among lesbian and heterosexual women (Beren, Hayden, Wilfley, & Grilo, 1996; Feldman & Meyer, 2007; Siever, 1994). Although one study reported elevated rates of BED among lesbians (Heffernan, 1996), this finding has not been replicated. Theorists have interpreted this pattern of findings as reflecting the degree to which individuals experience sexual objectification by their sexual partners. Because heterosexual women and gay men ostensibly experience this objectification to a greater degree than either lesbians or heterosexual men, they may be at increased risk for disordered eating (Siever, 1994).

Psychological Characteristics of Individuals with BED Many studies have attempted to identify the psychological characteristics of individuals with BED. Investigations have typically compared general



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cognitive styles, specific personality traits, and comorbid psychiatric diagnoses among individuals with versus without the disorder. A major limitation of these cross-sectional designs is that, in contrast to fixed markers like sex and ethnicity, psychological characteristics are not static throughout the lifespan. Thus, while it is possible that these characteristics represent causal risk factors that predispose individuals to the development of BED, it is equally plausible that they simply represent correlates or consequences of the disorder itself. Indeed, longitudinal studies have only just begun examining the temporal precedence of personality traits versus eating behaviors.

Personality and Cognitive Factors Case-control studies suggest that individuals with BED struggle with perfectionism, impulsivity, and low self-esteem. For example, de Zwaan et al. (1994) conducted interviews with 100 obese women presenting for weight-loss treatment and found that greater problems with binge eating were associated with higher levels of ineffectiveness, perfectionism, and impulsivity. Binge eating was also associated with lower levels of self-esteem and interoceptive awareness (i.e., difficulty interpreting internal bodily cues). Similar patterns have been observed in non-treatment-seeking samples. In a large population-based study, obese binge eaters endorsed higher levels of neuroticism, dependency, and depressive symptoms than obese non-binge eaters (Bulik, Sullivan, & Kendler, 2002). Individuals with BED also tend to endorse more depressive cognitive styles than individuals without BED. Kuehnel and Wadden (1994) assessed 70 women who presented for weight-loss treatment at a university clinic. They compared patients with BED to those without BED and subclinical binge eaters and found that individuals with BED reported higher levels of depression and a greater frequency of negative automatic thoughts than did the other two groups. The participants with BED also had more dysfunctional attitudes (i.e., vulnerability, need for approval, need to please others, and imperatives) than did participants without BED. Kuehnel and Wadden (1994) concluded that people with BED tend to “(1) lack confidence in their ability to deal effectively with a world they view as threatening and (2) use an external frame of reference in determining self-worth” (p. 326). These findings are consistent with the cognitive style described in the dietary restraint model (i.e., “I have to diet perfectly, but I can’t diet perfectly, so I may as well binge”). The tendency to see the world as a threatening place, low self-esteem, and difficulty interpreting internal bodily cues are plausible precursors to turning to food as a means of coping. In addition, using an external frame of reference in determining self-worth may make some individuals more vulnerable to society’s pressure for thinness as a sign of personal success, leading to body image disturbance and subsequent dieting.

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Comorbid Axis I and Axis II Disorders Individuals with BED also report significantly higher levels of comorbid psychopathology than do individuals without BED (Antony, Johnson, CarrNangle, & Abel, 1994; Telch & Stice, 1998; Yanovski, Nelson, Dubbert, & Spitzer, 1993). Specifically, individuals with BED endorse elevated rates of Axis I mood disorders and Axis II Cluster B personality disorders. For example, Antony et al. (1994) divided participants into three groups: BED, subclinical binge eaters, and non-eating-disordered controls. They found that the BED group reported significantly higher rates of self-reported depression, anxiety, and body dissatisfaction than did the control group; the scores for subclinical binge eaters fell in between. Subsequent studies in nonclinical community samples have replicated the finding of higher rates of depression among individuals with BED (Telch & Stice, 1998) and individuals who endorse binge eating (Bulik et al., 2002) as compared to healthy controls. In an interview study, Yanovski et al. (1993) interviewed obese men and women recruited through either general advertisements for subjects or a weight-loss program. They used an interview based on DSM-IV criteria to assess BED, the Structured Clinical Interview for DSM-III-R to assess Axis I diagnoses (SCID; Spitzer, Williams, Gibbon, & First, 1990a), and the Structured Clinical Interview for DSM-III-R Personality Disorders to assess Axis II diagnoses (SCID-II; Spitzer, Williams, Gibbon, & First, 1990b). They found that 34% of the participants met criteria for BED, and the participants with BED had a greater prevalence of any lifetime Axis I or Axis II disorder. The specific disorders that were more prevalent in the participants with BED were major depression, panic disorder, BN, borderline personality disorder, and avoidant personality disorder. Specker, de Zwaan, Raymond, and Mitchell (1994) identified a similar pattern in a comparison of obese women with and without BED presenting for weight-loss treatment. BED participants had higher lifetime prevalence rates for any Axis I diagnosis, and specifically for major depression and BN. Participants with BED also had higher rates of Cluster B and Cluster C personality disorders. The three personality disorders with the highest prevalence rates in the BED group were histrionic personality disorder (47%), borderline personality disorder (30%), and avoidant personality disorder (26%). The findings of a recent longitudinal investigation are consistent with the interpretation that personality disorders themselves may confer risk for binge eating. Specifically, the presence of at least one personality disorder by age 22 prospectively predicted the onset of recurrent binge eating at age 33 among men and women reporting no prior history of eating and weight problems in a community prevalence study (Johnson, Cohen, Kasen, & Brook, 2006). Furthermore, comorbid personality disorders may be associated with greater BED severity. In a recent treatment efficacy study, BED patients with comorbid Cluster B diagnoses endorsed greater baseline binge frequency and exhibited poorer treatment responses at 1-year follow-up as compared to patients without Cluster B diagnoses (Wilfley, Friedman, et al., 2000).



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To summarize, approximately half of obese patients with BED presenting for treatment have a comorbid mood disorder. Whether the depression is a trigger for binge eating, a consequence of binge eating, or both, these findings suggest the importance of addressing depression when treating patients with BED. In terms of etiology, the interpersonal vulnerability model posits that for some people depression is a precursor to binge eating and individuals use binge eating to numb out negative affect. This suggests that current or lifetime depression may place one at greater risk for binge eating. Second, individuals with BED are more likely than their obese counterparts without BED to have histrionic, borderline, or avoidant personality disorder, and the presence of personality disorders prospectively predicts the onset of binge eating over time. All three of these personality disorders have interpersonal features that link to the “disturbance of social self” described in the interpersonal vulnerability model. One of the features of borderline personality disorder is unstable and intense interpersonal relationships; a feature of histrionic personality disorder is that one considers relationships to be more intimate than they are; and a feature of avoidant personality disorder is an unwillingness to get involved with people due to a fear of rejection (American Psychiatric Association, 2000). The interpersonal vulnerability model posits that binge eating follows negative affect and low self-esteem due to interpersonal difficulty. This suggests that people with borderline, histrionic, or avoidant personality disorder may be vulnerable to the development of binge eating due to their experience of interpersonal distress.

The Controversial Role of Dieting Restraint theory posits that food restriction directly precipitates binge eating in vulnerable individuals, and many BED patients report that their first binge-eating episodes were triggered by failed attempts at dietary restraint. In contrast, approximately one-third (Abbott et al., 1998; Grilo & Masheb, 2000) to one-half (Spurrell et al., 1997) of individuals with BED report that their first binge-eating episodes predated any attempts to diet. Indeed, in one study, only 8.7% of participants with BED reported having been on a strict diet when they began to binge eat (Wilson, Nonas, & Rosenblum, 1993). Similarly, while early retrospective studies pinpointed dieting as an important precursor to binge eating in vulnerable individuals, more recent experimental studies have not supported the hypothesis that dieting induces binge eating in otherwise healthy people. These conflicting findings call into question the validity of the dietary restraint model in the development of BED and pose interesting questions for future research.

Retrospective Studies of Dieting Several retrospective studies have divided individuals with BED into dietfirst versus binge-first groups in order to identify similarities and differences

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that might provide clues to the disorder’s etiology. For example, Spurrell et al. (1997) interviewed 87 male and female patients with BED presenting for treatment at a university clinic. The average age at which participants were first overweight was 17 years old, and the age of their first diet was 17.6 years. Following that, the average age of their first binge was 18 years old. This suggests a general pattern of becoming overweight, dieting, and then binge eating within a 1-year span of time. When asked directly which came first, 55% reported binge eating first, while 45% reported dieting first. Binge-first individuals said they began this behavior on average at age 12.6, whereas the diet-first group said they began binge eating at age 24.9. The younger age of BED onset in the binge-first group has been replicated in several subsequent investigations (Abbott et al., 1998; Grilo & Masheb, 2000; Manwaring et al., 2006). Taken together, these data suggest that there are two critical periods for the development of BED; the first is adolescence (which is clearly consistent with the window of vulnerability for the other eating disorders), and the second is young adulthood (i.e., mid-20s). If dieting does play a role in precipitating binge eating in vulnerable individuals, its potency may be greater among adults. In contrast, children and adolescents may be more likely to binge eat in response to stressors other than dietary restraint, such as negative affect. Comparisons of diet-first versus binge-first BED have also investigated the degree to which differential risk factors may give rise to the development of BED in childhood versus adulthood. Some studies have identified similarities in eating disorder severity and comorbid psychopathology between the two groups (Grilo & Masheb, 2000), whereas others have highlighted important differences (Spurrell et al., 1997; Manwaring et al., 2006). For example, Spurrell et al. (1997) looked at the age of onset of obesity as well as the individuals’ perception of themselves as overweight as children. There were no significant differences between the diet-first and binge-first groups in terms of age of onset of perceptions of overweightedness (both groups reported becoming overweight in their mid- to late teens), but binge-first participants were more likely to perceive themselves as overweight (even though they were not) between the ages of 6 and 12. Binge-first participants reported more sibling and family problems as well as more life events related to the onset of binge eating. Similarly, Grilo and Masheb (2000) found that binge-first BED patients were more likely to report having been teased about their weight as children than diet-first patients. Taken together, these results suggest that adolescents who begin to binge eat before dieting may do so in response to environmental stressors, especially those of an interpersonal nature. Future research is needed to identify whether risk factors actually differ prospectively between diet-first and binge-first BED.

Experimental Studies of Dieting While retrospective studies have highlighted dieting as a putative risk factor for adult-onset BED, experimental studies paradoxically have not found that



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randomly assigning healthy individuals to reduced-calorie diet programs actually promotes binge eating (Presnell & Stice, 2003; Presnell, Stice, & Tristan, 2008; Wadden et al., 2004; Williamson et al., 2008). In the first study of its kind, Presnell and Stice (2003) randomly assigned healthy normal-weight participants to either a 6-week reduced-calorie diet or a wait-list control condition. They found that individuals assigned to the dieting condition actually experienced greater reductions in binge eating and purging behaviors at the end of the trial than individuals on the wait-list. Similarly, in another study, obese individuals assigned to either a reduced-calorie eating plan or a meal replacement plan (in which they consumed mainly fortified shakes) did not exhibit increases in binge eating at the end of the treatment trial as compared to a no-diet control group (Wadden et al., 2004). The investigators of both trials concluded that dieting is safe and is unlikely to promote binge eating directly. Given the incongruence between retrospective and experimental studies of dieting, additional studies are needed to identify the role of restrictive eating patterns, if any, in the etiology of BED. It is possible that the dieting methods employed by individuals with eating disorders (e.g., fasting, cutting out entire classes of food, labeling certain foods as “forbidden”) are more likely than the relatively sensible—albeit reduced-calorie—eating plans evaluated in dieting experiments to induce the hunger and cravings that ultimately promote binge eating. Alternatively, it could be that a third variable (such as melanocortin dysfunction, or depressive symptoms) either fully or partially mediates the relationship between dieting and binge eating so often observed in naturalistic settings. Indeed, Presnell et al. (2008) found that individuals with higher levels of baseline depression exhibited smaller reductions in bulimic symptoms after dieting than did individuals with lower levels of baseline depression.

Weight Cycling Taken together, the findings of both retrospective and experimental studies suggest that dieting plays a role in the development of BED for some individuals but not others. Accordingly, other studies have examined aspects of dieting that may promote binge eating apart from the caloric restriction itself. For example, some have investigated the potential etiological role of weight cycling (repeated weight losses followed by regain; Brownell, 1995). To examine this question, a number of studies have measured the history of weight cycling in individuals with BED and compared those histories to obese individuals without BED. Some have found that individuals with BED report higher rates of weight cycling (e.g., de Zwaan et al., 1994; Giusti, Heraief, Gaillard, Burckhardt, 2004), whereas others have not (e.g., Kuehnel & Wadden, 1994). One issue in the weight cycling literature is the lack of consistency in how cycling is measured. Studies have measured it as number of diets, number of pounds lost and regained, amount of weight regained after a specific weight-loss attempt, and whether participants self-identify as weight cyclers.

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The subjective experience of oneself as a weight cycler appears to account for more variance in psychological variables (i.e., body satisfaction, life satisfaction, and self-esteem) than does the actual number of pounds lost and regained (Friedman, Schwartz, & Brownell, 1998). Therefore it is possible that the role of weight cycling in the etiology of eating disorders is cognitive; self-definition as a weight cycler may create a self-fulfilling prophecy of restriction, lapses, the abstinence violation effect, and binge eating.

Life Events That Affect Vulnerability In addition to demographic and psychological characteristics, investigators have also identified several life events that may contribute to BED risk. Some of these (i.e., abuse and bullying) are obviously pernicious, whereas others (i.e., the initiation of ostensibly helpful psychotropic medications) may operate more insidiously. Life events associated with assuming adult roles and responsibilities may temporarily increase self-focus and body dissatisfaction (i.e. weddings, pregnancy), but ultimately provide protection against disorderedeating behaviors as they come to fruition (i.e., life partnership, parenthood) across the lifespan.

Abuse and Bullying Women with BED have reported significantly higher rates of sexual abuse, physical abuse, and physical bullying by peers in comparison to healthy control women in community-based case-control studies (Fairburn et al., 1998; Striegel-Moore, Dohm, Pike, Wilfley, & Fairburn, 2002). One of these studies reported alarmingly high rates of abuse among women with BED; 43% of BED participants reported having been sexually abused, and 55% reported having been physically abused prior to the onset of their eating disorder (StriegelMoore et al., 2002). Because early abuse experiences have also been associated with increased risk for other Axis I and II disorders, they may confer risk for psychiatric distress in general rather than for BED specifically. Childhood abuse may leave individuals vulnerable to the development of binge eating through the interpersonal vulnerability pathway. Specifically, sexual or physical violation by a caregiver or even a stranger may shatter children’s view of the world as a safe place and hinder their ability to form trusting relationships with family and peers. In turn, the combination of heightened negative affect and diminished interpersonal support may lead to increased risk for binge eating as a way of escaping from overwhelming emotions.

Marriage and Life Partnership Although the initial stress of wedding planning intensifies pressure for brides to conform to the thin ideal, the successful attainment of a life partnership may ultimately protect married women from disordered-eating attitudes and



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behaviors. Recent research has indicated that the majority of women engaged to be married wish to lose weight for their wedding day, and that those who do wish to be approximately 20 pounds lighter (Neighbors & Sobal, 2008; Prichard & Tiggemann, 2008). In one study, 26% of brides who wished to lose weight reported resorting to extreme behaviors, such as meal skipping, fasting, and purging to attain their wedding weight goals (Neighbors & Sobal, 2008). However, once women have settled into married life, the effects of marriage appear to be protective. In one longitudinal study, women who were married at baseline were less likely than unmarried women to report intense dieting at 6-year follow-up (Vogeltanz-Holm et al., 2000), although the two groups did not differ with regard to binge eating. Moreover, in a 20-year longitudinal study of men and women first assessed in their college years, marriage was associated with significant decreases in the Drive for Thinness and Bulimia subscales of the Eating Disorder Inventory among women but not men (Keel, Baxter, Heatherton, & Joiner, 2007). Given that the majority of items on the Bulimia subscale assess the frequency and severity of binge eating, these findings have potential relevance for the etiology and maintenance of BED. Specifically, the investigators posited that the selection of a life partner may promote decreases in disordered eating by alleviating perceived pressure to conform to the thin ideal in order to increase attractiveness to new partners (Keel et al., 2007). Alternatively, an overarching third variable, such as interpersonal or affect management difficulties, may simultaneously increase the probability of singlehood as well as disordered eating.

Pregnancy and Parenthood In one study, women with BED were significantly more likely than age-matched control women to report having been pregnant prior to the age of eating disorder onset (Fairburn et al., 1998). Pregnancy represents a time of significant physical and psychological changes for adult women, including salient alterations in eating, weight, and body shape. For some, the postpartum period may be a vulnerable time for the development of an eating disorder. The first aspect of pregnancy that may increase vulnerability is weight gain. It is now recommended that women gain between 15 and 40 pounds during their pregnancies, depending on their prepregnancy weight status (Moore & Greenwood, 1995). Although most women slowly lose the majority of this excess weight during the postpartum year, the average woman still weighs 3 pounds more than her prepregnancy weight at 1-year postpartum (Moore & Greenwood, 1995). Many women also experience a disturbance in body image during pregnancy. One group at particular risk may be women with a history of dieting; Fairburn and Welch (1990) assessed the feelings of a sample of female dieters during pregnancy and found that they felt worse about their bodies during pregnancy than when they were not pregnant. Prospective studies suggest that the postpartum period is often particularly challenging. Fairburn, Stein, and Jones (1992) assessed 100 pregnant women at 15 and 32 weeks of pregnancy

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and also administered an eating disorder interview the month before pregnancy. Women’s concern about eating, shape, and weight, as well as restraint, decreased from prepregnancy to 15 weeks but then went back up again by 32 weeks. This finding suggests that the early stages of pregnancy may provide an opportunity for dietary disinhibition and relaxed feelings about body shape and weight, but as the body becomes significantly different by the end of pregnancy, feelings of distress return. Stein and Fairburn (1996) followed normal women’s eating disorder symptoms at 3 months and 6 months postpartum, using the EDE interview. There was an increase in dietary restraint and concerns about eating, shape, and weight at 3 months postpartum, but all but the weight concern reached a plateau at 6 months. In the women for whom weight concern continued to rise, several cases turned into clinical eating disorders. Women who had retained the most weight were the ones experiencing the most eating disorder symptoms (Stein & Fairburn, 1996). Interestingly, women with preexisting eating disorders demonstrate similar patterns of gestational symptom remission and postnatal symptom relapse (Crow, Agras, Crosby, Halmi, & Mitchell, 2008). Taken together, these findings highlight the gestational period as a potentially promising timeframe for both eating disorder prevention efforts among nonclinical women and eating disorder intervention efforts among symptomatic women. While many studies have traced the relative prevalence of disordered eating among women during the gestational and immediate postpartum periods, the potential longer-term effects of parenthood on risk for disordered eating have received very little research attention. In a 20-year longitudinal study, motherhood was associated with significant decreases in EDI Drive for Thinness and Bulimia in women, and fatherhood was associated with significant decreases in Drive for Thinness in men (Keel et al., 2007). The investigators posited that parenthood may protect adults from disordered eating as they age because successful childrearing may become increasingly paramount to individuals’ schemes for self-evaluation as they assume the parental role, thereby decreasing the relative importance of shape and weight.

Psychiatric Medications That Cause Weight Gain Weight gain is a well-known side effect of many neuroleptics (Casey, 1996; Umbricht & Kane, 1996). For example, in a study of 42 patients taking clozapine, patients’ average body mass index rose from 23.2 to 29.1 in women and from 26.4 to 29.7 in men (Frankenburg, Zanarini, Kando, & Centorrino, 1998). In light of the World Health Organization guidelines that a body mass index of 25 suggests overweightedness and a BMI of 30 defines obesity, these patients are making a clinically significant shift toward obesity. To address this problem, the literature on the adverse effects of medications such as olanzapine (Gupta, Droney, Al-Samarrai, Keller, & Frank, 1998), clozapine (Young, Bowers, & Mazure, 1998), and risperidone (Kelly, Conley, Love, Horn, & Ushchak, 1998) recommends dietary education and exercise as part of the



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drug treatment program. In addition to antipsychotics, weight gain has also been observed with the initiation of other psychotropic medications, including lithium (Baptista et al., 1995) and antidepressants (Benazzi, 1998). In a study of adolescents with psychotic disorders who had recently been prescribed atypical antipsychotic medications, 50% endorsed binge eating and 26% met lifetime criteria for full- or partial-syndrome BED or BN (Theisen et al., 2003). Because the majority of patients stated that medication use had preceded the onset of their binge eating, the investigators proposed that “medication-induced eating disorders” be added as a new nosologic category to successive versions of DSM. The specific mechanism through which antipsychotic medications may lead to binge eating remains unclear. They may increase vulnerability simply by increasing appetite or food cravings. Alternatively, individuals may attempt to diet in order to counteract medication-induced weight gain and subsequently begin binge eating through the dietary restraint pathway.

Bulimia Nervosa Because BN and BED share the symptom of binge eating in common, investigations into the development of BN have been informative for generating analogous etiological theories of BED (e.g., the dietary restraint and interpersonal vulnerability models). The frequent diagnostic migration between BN and BED and the existence of atypical cases of BN with a similar age of onset to BED (i.e. mid-20s) provide further evidence for the possibility of shared etiological mechanisms.

Transition from BN to BED A subset of individuals with BED once had BN but have stopped purging. Thus, a potential risk factor for developing BED in adulthood may be a history of adolescent BN. A 12-year longitudinal study of 311 eating disorder patients revealed that diagnostic migration between the BN and BED categories was common throughout the observation period whereas a crossover between BED and AN never took place (Fichter & Quadflieg, 2007). Interestingly, BN and BED exhibited similar long-term outcomes, with two-thirds of patients in each category being classified as recovered at 12-year follow-up (Fichter & Quadflieg, 2007). Investigators have also attempted to evaluate whether a history of purging is associated with BED severity or outcome. In one study, 63 individuals with BED were divided into those having a history of purging (i.e., vomiting and laxative abuse) or no history of purging (Peterson et al., 1998). The groups were compared on measures of Axis I psychopathology, depression, body dissatisfaction, eating disorder symptoms, and self-esteem. Surprisingly, a history of purging was not related to any variable. The authors suggest that because they excluded people who had purged in the preceding 6 months, were currently in psychotherapy or on psychotropic

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medication, and had experienced substance abuse or dependence within the last 6 months, they may have inadvertently excluded the people for whom a history of purging would be a meaningful subgroup classification and indicator of psychopathology.

Late-Onset BN One study has compared individuals with typical versus late-onset BN (Mitchell, Hatsukami, Pyle, Eckert, & Soll, 1987). The authors defined late-onset as age 25 or older and typical onset as age 20 or earlier. The findings were that members of the late-onset group differed from those in the other group in several ways. First, they had higher rates of mood disorders (both current and lifetime) and were more likely to have received treatment for a mood disorder. Second, they were more likely to have made a suicide attempt. Third, they were more likely to report chemical dependency problems (both current and lifetime) and showed a trend toward higher rates of chemical dependency treatment. Taken together, these findings suggest that the late-onset group had higher rates of psychopathology than did typical-onset BN patients. It is possible that their vulnerability to developing BN in adulthood is linked to their struggles with mood disorders and substance abuse. As discussed earlier, mood disorders are common among individuals with eating disorders, and many questions remain about the possible causal link between the two (e.g., Mitchell & Mussell, 1995). This study suggests that a current or past mood disorder may be a risk factor for the development of BN in adulthood. Substance abuse is also a common comorbid diagnosis for patients with BN; patients with eating disorders show higher rates of past and present substance abuse than would be expected in the general population (see review by Wilson, 1995b). Although there is debate regarding whether eating disorders can be considered addictive disorders, this study does suggest that a history of substance abuse may increase vulnerability to the development of BN in adulthood.

Etiologically Informed Treatments Treatment outcome studies that attempt to reduce the influence of a putative risk factor for a disorder represent a fruitful avenue for evaluating the role and potency of that factor in the onset and maintenance of the disorder (Kraemer et al., 1997). Both the dietary restraint model and the interpersonal vulnerability model provide rich theoretical frameworks for two empirically supported psychosocial treatments for BED: cognitive-behavioral therapy and interpersonal therapy (for detailed descriptions, see Wilfley, Mackenzie, et al., 2000; Fairburn, 2008). Each of these treatment protocols can be delivered in individual or group formats; however, the research on BED has primarily used group treatments (e.g., Wilfley et al., 2002). Although the efficacy of each treatment provides preliminary support for its respective etiological theory, the mecha-



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nisms of action of each treatment remain unclear, meaning that future research is needed to determine whether one model is superior to the other or whether they can both operate simultaneously within the same individual.

Cognitive-Behavioral Therapy Cognitive-behavioral therapy (CBT; Fairburn, 2008) uses a short-term (typically 20 sessions) problem-directed approach focused on the present and future rather than the past. Clients are taught the cognitive-behavioral view of the etiology and maintenance of their eating disorder (i.e., the dietary restraint model). The goal of CBT is to change the maladaptive behaviors and distorted cognitions that are associated with binge eating. Developmental and psychodynamic issues are not addressed, and interpersonal problems are addressed only to the extent that they serve as triggers for binge episodes. The first stage of this treatment is the behavioral prescription to eat three meals a day plus one or two snacks. The purpose is to create a regular eating pattern and reduce the patterns of grazing or restricting all day that may lead to binge eating later that night. Clients are taught about proper nutrition and are encouraged to make healthy food choices. They learn how to self-monitor their food intake; make better choices about where, when, and with whom to eat; and modulate the speed of their eating. This information is used to identify binge triggers, such as going too long without eating or eating late at night. The second stage of treatment is to identify the thoughts and feelings that lead up to a binge. The primary goal here is to challenge the belief that binge episodes occur randomly; instead, clients learn that they can predict when they are at risk for a binge by noticing the chain of events, thoughts, and feelings that occur first. As they identify those thoughts (e.g., all-or-nothing thinking and the abstinence violation effect), cognitive restructuring is used to challenge the dysfunctional beliefs. This strategy is also used to challenge dysfunctional cognitions regarding interpersonal events, which helps prevent interpersonal distress from becoming a binge trigger. The final stage of CBT focuses on relapse prevention. Clients learn how to maintain the changes they have made after treatment ends and to use problem-solving and coping skills when they encounter high-risk situations. A major challenge for obese clients with BED is that they may have successfully been able to stop their binge eating but they are likely to still be significantly overweight. Indeed, a recent systematic review of BED treatments highlighted the efficacy of CBT in helping individuals with BED achieve abstinence from binge eating but underscored that CBT is unlikely to result in significant weight loss (Brownley, Berkman, Sedway, Lohr, & Bulik, 2007). It may be useful to follow up successful CBT treatment with a behavioral weight-loss intervention designed to help obese clients continue to make healthy food choices and increase their exercise level in the service of decreasing adiposity.

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Interpersonal Therapy Interpersonal therapy (IPT) was originally developed as a treatment for depression (Klerman, Weissman, Rounsaville, & Chevron, 1984) and has since been adapted for eating disorders (see Wilfley, Mackenzie, et al., 2000). It is designed as a short-term treatment that is problem-focused and emphasizes the quality of current interpersonal relationships. The central premise of IPT is that binge eating is a maladaptive coping strategy used to manage negative affect linked to interpersonal distress (i.e., the interpersonal vulnerability model). Past relationships are considered important information for the therapist to gather in the initial evaluation, but the treatment focuses on current relationships and changes that can be made in the here and now. During the evaluation and first stage of treatment, each individual identifies his or her problem areas and how they are linked to binge eating. Klerman et al. (1984) outlined four major interpersonal problem areas: (1) grief, (2) interpersonal disputes (e.g., with spouse, children), (3) role transitions (e.g., new job, relocation), and (4) interpersonal deficits (e.g., loneliness and social isolation). Among clients with BED, the most common problem areas are interpersonal deficits, followed by interpersonal disputes (Wilfley et al., 1993). In linking the problem area to eating, someone with interpersonal deficits might describe binge eating while feeling lonely and isolated on a weekend night, while someone with interpersonal disputes might describe binge eating at night after a heated spousal argument while her husband is in the next room drinking alcohol and watching television. The second stage of IPT treatment is to actively work to solve the problem that has been identified. For example, one patient’s goal may be to reduce social isolation; thus the treatment would focus on strategies for forming new relationships. Another patient’s goal may be to foster communication with her husband about their relationship and see if resolution is possible; if not, she may need to move on to mourn the loss of the relationship. The final stage of treatment addresses termination and preparation for the future. The end of the treatment is used as an opportunity to practice managing feelings of loss. Therapists emphasize the progress clients made during treatment and also anticipate future challenges and coping strategies. Clients are taught that they will probably always be vulnerable to eating problems when they are in distress. However, this can help them recognize when they are upset about something, so they can then use a more adaptive way of coping, such as turning to people for support rather than to food.

A Comprehensive View of Vulnerability After two generations of research on the etiology of BED, the field has identified several fixed markers and dynamic processes that are correlated with the onset of the disorder. Specifically, a genetic propensity for obesity, a family



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history of BED, and abnormalities in serotonin, ghrelin, and melanocortin function may set the stage for biological vulnerability. Demographic variables fixed at birth—such as female gender and male homosexuality—may further increase risk. Furthermore, comorbid depression and personality disorders, as well as character traits including low self-esteem, impulsivity, and perfectionism, may increase the probability of turning to food as a way of managing negative affect. Throughout the lifespan, catalytic adverse events—such as physical and sexual abuse, parental criticism about shape and weight, and peer bullying—or events that promote weight gain—such as pregnancy and the initiation of antipsychotic medication—may ultimately bring latent biological vulnerabilities to fruition. These fixed markers and correlates—all potential risk factors for BED—are summarized in Figure 18.2. The first two generations of BED risk factor research were stimulated in part by two distinct etiological theories of the disorder: the dietary restraint model and the interpersonal vulnerability model. As reviewed in this chapter, components of each model have received considerable empirical support. For example, hormonal dysregulation leading to increased hunger and life events contributing to weight gain (e.g., pregnancy, the initiation of antipsychotic medications) can be readily conceptualized within the framework of the dietary restraint pathway. Alternatively, the high rates of depression and adverse life events (e.g., abuse, bullying) among individuals with BED provide a close theoretical fit with interpersonal vulnerability theory. Thus, available data do not provide greater evidence in favor of one etiological model versus the other. It seems more likely that within a framework of equifinality each model represents a distinct pathway toward the development of binge eating. Alternatively, both models may operate simultaneously within a single individual to precipitate the onset and maintenance of the disorder.

Implications for Prevention The putative risk factors reviewed in this chapter that feature the strongest implications for BED prevention are the life events that precipitate weight gain. Although only a handful of life events have demonstrated possible empirical association with BED (e.g., pregnancy, the use of antipsychotic medications), there are many events in adulthood that may lead individuals to gain weight. We believe it is important for medical professionals to be aware of weight gain as a potential risk factor for the development of an eating disorder and to help patients anticipate their reactions to changes in body weight and eating behavior throughout the lifespan. First, health care professionals could regularly assess eating disorder symptoms (particularly overconcern with shape and weight) in pregnant women to help predict which subgroups are most likely to experience difficulties with changes in body shape and weight. Once identified, these women could receive a brief intervention to help them understand what to expect

480

CLINICAL SYNDROMES Overweight and Obesity

Familial BED Familial binge eating Female biological sex Parental depression Genes affecting mood and satiety • 5-HTTLPR L alelle • MC4R mutation • Leu72Met ghrelin genotype

Personality traits: • Low self-esteem, ineffectiveness • Perfectionism, self-criticism • Impulsivity Comorbid Psychopathology: • Axis I mood disorders • Axis II borderline, avoidant, histrionic personality disorders Peer bullying

Dieting, weight cycling

Sexual or physical abuse

Medication-induced weight gain

Parent–child conflicts Weight and shape criticism

Birth

Childhood

Adulthood

BED Onset

FIGURE 18.2.  A comprehensive view of fixed markers and correlates of BED from birth to eating disorder onset. Factors represented in darker gray have greater empirical support.

in terms of weight gain during pregnancy and how to set realistic goals for weight loss following delivery. Another finding with prevention implications is that patients with BED are more likely to have been obese as children (Fairburn et al., 1998; StriegelMoore et al., 2005) and to have been criticized by family members about shape, weight, and eating (Fairburn et al., 1998). This suggests that efforts to curb childhood obesity may subsequently prevent the development of new cases of BED. Two recent meta-analyses have examined the efficacy of programs designed to treat (Wilfley et al., 2007) and prevent (Stice, Shaw, & Marti, 2006) childhood obesity. The most important elements for childhood obesity treatment appear to be promoting parental involvement, increasing exercise, and reducing time spent in sedentary activities (Epstein et al., 1995); lifestyle intervention programs are superior to waitlist or education-only programs in reducing pediatric overweight (Wilfley et al., 2007). The most effective childhood obesity prevention programs are short in duration and targeted specifically toward obesity rather than featuring a multidimensional focus on general health behaviors (Stice et al., 2006). In addition to preventing childhood obesity, another important public health message is to prevent the criticism of overweight children by family members. Many parents may criticize their child out of worry or their own feelings of helplessness. While family-based treatments teach parents how to use positive reinforcement with their children, only a small percentage of parents with obese children in our country have the opportunity to participate in treatment groups. On a broader scale, public health education campaigns may



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be useful to help parents learn how to communicate with their children about eating, shape, and weight in a productive manner.

Directions for Future Research The cross-sectional and retrospective designs that comprised the first and second generations of etiological research have generated a rich array of hypotheses about the causal pathways to BED onset. In order to determine whether the fixed markers and correlates identified to date represent true risk factors for the disorder, the field must embark on a third research generation that (1) attempts to replicate promising preliminary findings and (2) employs longitudinal and experimental designs. A major direction for future research is further investigation of the biological underpinnings of BED. Preliminary candidate gene associations are interesting but clearly need replication. In addition, as our understanding of gene–environment interplay increases, our etiological theories should become more sophisticated. The original biopsychosocial model hypothesized that genetic predisposition confers individuals with a certain probability for the development of a disorder at birth and that psychosocial influences determine whether this latent vulnerability is ultimately expressed. In contrast, investigators are now theorizing that the relationship between biological and psychosocial factors may be even more dynamic, such that psychosocial and biological factors influence each other bidirectionally throughout the lifespan via epigenetic processes (Fish et al., 2004). A second area in need of investigation is the controversial role of dieting in the development of binge eating. The putative link identified in retrospective studies has not been supported in subsequent experimental work. More research is needed to determine whether dieting is a mere correlate or a symptom of BED itself, or whether certain types of overrestrictive eating patterns may place individuals at special risk for loss-of-control eating. It will also be important to determine whether individual differences in dieters’ personality traits or cognitive styles act as possible moderators of the diet–binge relationship. Another area for future research is the evaluation of binge-eating prevention programs. For example, multiple issues need to be covered with pregnant women and newly medicated psychotic patients, and addressing eating and weight issues may not be at the top of the priority list. Research testing the cost effectiveness of providing an eating-and-weight intervention at these potentially vulnerable times would provide important information for practitioners and patients. Similarly, although clinicians can teach parents one at a time how to help their overweight children, a public health campaign on how parents and teachers can facilitate weight loss, health, and self-esteem in children may be a more cost-effective approach. Thus, developing and evaluating community-based interventions is an important area for future work.

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Lastly, many of the putative risk factors for BED are conceptually related and may work together to increase risk. It would be ideal to design prospective longitudinal studies that could assess the developmental sequence of cognitive, personality, eating, weight, and psychological changes. Advanced statistical approaches, such as hierarchical linear modeling and structural equation modeling, could be utilized to evaluate the potentially additive or interactive contributions of each factor. It is possible, for example, that some adverse life events are more iatrogenic to individuals with certain underlying biological or demographic vulnerabilities. Such findings would assist clinicians and educators in tailoring treatment and prevention efforts to the individuals for whom they are most likely to provide relief.

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Chapter 19

Vulnerability to Eating Disorders across the Lifespan Pamela K. Keel, K amryn T. Eddy, Jennifer J. Thomas, and Marlene B. Schwartz

This summary provides an integrated perspective on risk factors and disease correlates for eating disorders across the lifespan. Review of Chapter 17 (Eddy, Keel, & Leon) and Chapter 18 (Thomas, Schwartz, & Brownell) in this volume reveals commonalities and differences in understanding eating disorder risk factors for both children/adolescents and adults. First, we review apparent commonalities in risk factors for childhood/adolescence and adulthood. We follow this discussion with a review of differences in risk factors. Finally, we discuss how future research endeavors could be designed to advance our understanding of eating disorders risk in individuals during different developmental periods. The first striking theme in the developmental literature is the differential window of vulnerability for each disorder. Anorexia nervosa (AN) is associated with the earliest age of onset, with an initial peak age at 14 years followed by a second peak at 18 years. Conversely, bulimia nervosa (BN) is associated with a peak age of onset around 19 years of age and often develops in girls with a history of AN. Finally, binge-eating disorder (BED) appears to have a slightly later age of onset at 25 years, although notably one subgroup of individuals with BED report beginning binge eating during adolescence (before their first diet).

Common Themes, Issues, and Risk Factors Despite the apparent age-related differences in eating pathology, it is possible for a single individual to develop AN as she transitions from childhood to ado

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lescence, to develop BN as she begins her transition from adolescence to adulthood, and finally to develop BED as she transitions fully to adulthood. Such a pattern suggests that certain risk factors may form a common core from which disordered eating develops. For example, biology, such as temperament, neurotransmitter function, and genes that influence temperament or predisposition to have a higher body weight, may represent stable underlying factors that contribute to a vulnerability to disordered eating across the lifespan. Psychological factors, such as low self-esteem, poor interoceptive awareness, dietary restraint, and body dissatisfaction, similarly represent risk factors common to children, adolescents, and adults. While social pressures may differ across the lifespan, a commonality is the backdrop of a contemporary industrialized society that emphasizes the thin-female ideal. These biological, psychological, and social risk factors may then interact with developmental and life transitions that lead to somewhat distinct behavioral patterns at varying points during the lifespan. Individuals who are vulnerable to developing eating disorders may have a temperamental style marked by negative affectivity—that is, the tendency to experience greater levels of dysphoria and anxiety and to find transitions particularly stressful. This temperamental style may contribute to or be exacerbated by disturbances in the individual’s early relationships with caregivers. If caregivers are unable to meet their child’s physical and emotional needs, the child is predisposed to experience greater levels of depression and low self-esteem due to both an insecure attachment style and his or her temperament. This pattern may contribute to a disturbance in the child’s social self, characterized by a heightened concern for how she is perceived by others, an excessive need for social approval, and a feeling of inadequacy. This core can lead to disordered eating patterns such as severely restrictive dieting, purging, and binge eating. Binge eating may represent a means of coping with negative affect, as suggested by the interpersonal vulnerability model. Alternatively, low self-esteem may increase an individual’s likelihood of engaging in severely restrictive dieting in an attempt to gain social approval from others. Severely restrictive dieting could then produce AN or contribute to the onset of binge eating episodes, according to the dietary restraint hypothesis. In Chapters 17 and 18, evidence supporting a relationship between selfimposed strict dieting and disordered eating in individuals at risk for eating disorders was presented, suggesting that strict dieting may contribute to the development of disordered eating across the lifespan. In addition to contributing to the severe weight loss characterizing AN, self-imposed strict dieting appears to increase the likelihood of developing binge-eating episodes by contributing to an “all-or-nothing” cognitive style. Specifically, severely restrictive diets characterize foods as being either “good” or “bad” and often categorize important nutritional components (such as fat) as “unacceptable.” If the rigid dietary rules are broken, the individual experiences the abstinence violation effect—a sense that she has failed completely. Moreover, three potato chips and a 12-ounce bag of potato chips represent the same level of failure;



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thus, the person feels she might as well consume the entire bag of chips. This response is particularly likely if the individual anticipates returning to her severely restrictive diet the next day. Across the lifespan, women are more likely to develop disordered eating than are men, however, this effect is markedly more pronounced for the risk of AN and BN, compared to BED. This difference is most salient in adolescence, where women make up 85–90% of individuals with AN and BN, while among adults women appear to be somewhat more likely than men to have BED. Sociocultural factors, including increased pressure on women to be thin and, accordingly, increased thin-internalization, body dissatisfaction, and likelihood of dieting among women have traditionally been cited as explanations for these gender differences in eating disorder risk. More recent research, however, posits that biological factors including prenatal testosterone exposure or hormonal changes associated with puberty may also be important in understanding sex differences. Such findings highlight the dynamic relationship between identifying developmental risk factors—that is, risk factors that occur during different stages of development—and understanding how an immutable risk factor, sex, is related to increased risk for developing eating disorders. Notably, across the lifespan, eating disorders are associated with increased comorbid depression, anxiety, and substance use problems. These patterns suggest that eating disorders share risk factors with other disorders, including family history of affective disorders, family environment that is high in expressed emotion, and poor peer relationships. These factors are likely to be particularly influential in times of role transition, such as puberty, leaving the home environment, leaving a college environment, and pregnancy. With each transition, individuals face challenges requiring the ability to form new relationships. When psychological (poor self-worth) and environmental (poor support in family relationships) factors impair interpersonal functioning, such transitions are likely to increase the potential for the emergence or relapse of eating pathology.

Differences in Risk Factors While commonalities in risk factors associated with eating disorders across the lifespan outnumber the differences, these differences warrant mention. First, phenomenological and epidemiological differences are noteworthy. In children and adolescents, eating disorders could be conceptualized as dieting disorders, as key features of both AN and BN involve attempts to reduce or control weight through restrictive eating or compensatory behaviors. In addition, these disorders are far more common in females compared to males. Conversely, adults are more likely to have BED than AN or BN, and the role of dieting in the etiology and maintenance of BED is less clear. Although dieting may have preceded the onset of BED for a subset of individuals, there is also a

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group of individuals who began binge eating first, and experimental random assignment to low-calorie diets has not promoted binge eating in otherwise healthy individuals. Unlike definitions for AN and BN, the use of strategies to control weight (i.e., fasting or inappropriate compensatory behaviors) is not a diagnostic criterion for BED, nor is body image disturbance—although individuals with BED often have very low body esteem. Moreover, compared to adolescents, adults are less likely to use inappropriate compensatory behaviors following binge-eating episodes. This disinclination may be attributable to decreased pressure to maintain an ultrathin physique in adulthood compared to adolescence. It also may be due to maturity and increased concern about the physical risks of self-induced vomiting or laxative abuse. Another difference between BED and the other eating disorders, as just noted, is that as many as 40% of individuals with BED appear to be male, representing a less extreme gender difference for this form of pathology in adults. The decreased gender difference in the development of BED compared to AN and BN may be understood in the context of the interpersonal vulnerability model. This model can be applied to understanding the development of AN, BN, and BED, as food intake may be used to cope with interpersonal difficulties in all three disorders. However, men may be less likely to starve themselves or compensate after binge-eating episodes by purging, fasting, or excessive exercise because of the decreased societal pressure to maintain a thin physique in men. The apparent underrepresentation of boys in adolescent eating disordered samples may reflect a failure to study behaviors characteristic of BED rather than AN or BN in these studies. The accuracy of the interpersonal vulnerability model in explaining the decreased gender difference in the prevalence of BED could be explored through cross-cultural research. The presence of BED in either gender in societies that do not endorse a thin ideal may serve as an analogy to the presence of BED in men within our society. Such research might demonstrate that BED is represented cross-culturally as long as large quantities of food are widely available. Moreover, seeking solace from emotional pain through food may represent a fairly universal coping mechanism, given the association between food and nurturing. The majority of eating disorders research has studied adolescent and young adult female populations to understand risk factors. The focus on these populations grew from the understanding that AN and BN typically developed in these demographic groups. However, the recent delineation of BED has increased research focus on adult populations, although there is a lack of parity in study designs employed with populations of different ages. As noted by Thomas, Schwartz, and Brownell (Chapter 18, this volume), very few longitudinal prospective studies have been conducted to detect risk factors for eating disorders in adult populations. Thus, many of the conclusions regarding risk factors that influence disordered eating among adults rest on data from cross-sectional, case-control, retrospective, and experimental studies. Although AN and BN have been closely associated with adolescence, long-



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term follow-up studies suggest that these disorders often persist into middle age. Thus, factors that contribute to the maintenance of disordered eating are not limited to adolescence. Further, the disparity in research on eating disorders in females versus males is far greater than the actual disparity in the prevalence of eating disorders in females versus males. Unfortunately, a tendency to focus on female populations seems to have been adopted within studies of adult populations despite evidence that men represent a much higher proportion of individuals with eating disorders in adulthood compared to childhood or adolescence. Given recent findings from both the child/adolescent and adult literatures, there appears to be potential for cross-fertilization for the benefit of future research on eating disorder risk factors.

Future Research Directions Although longitudinal prospective designs are costly, the use of collaborative studies in which several forms of psychopathology are investigated seems to be a viable approach. For further efficiency in the use of resources, communitybased samples that were assessed during adolescence for the onset of AN and BN could be included in further follow-up to assess for the development of BED during adulthood. Such study samples offer careful assessment of numerous factors that may be important for understanding the development of disordered eating across the lifespan. For example, dieting history, weight, and problems in self-esteem and affect have been carefully documented in these samples, as they are relevant for the onset of both AN and BN. These variables appear to be important for understanding BED as well. Rather than relying on retrospective reports, which may introduce recall bias, future studies could assess adults who participated in assessments during pre- and early adolescence to determine how factors such as dieting and interpersonal difficulties are important in the development of all eating disorders. In this way, research on childhood/adolescent risk factors may make significant contributions to understanding risk factors associated with eating disorders in adulthood. Further, taking cues from the child/adolescent literature, which highlights the developmental periods of transition that are associated with increased risk, more research is needed to include times of transition in adulthood such as pregnancy, marital status, and menopause. Conversely, research on childhood/adolescent risk factors can benefit from perspectives taken within the adult literature. For example, more research on disordered eating in males seems justified, considering that recurrent binge eating appears to be almost as common in males as in females and that these patterns may begin as early as 12 years of age. The adult literature has proposed the expansion of existing etiological models of eating disorders to account for the presence of BED in both men and women and Caucasians and minority groups. Although BED may simply differ from AN and BN on

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demographic variables, the diversity represented in clinical descriptions of BED highlights the need to revisit assumptions concerning who develops eating pathology throughout the lifespan. Lastly, although psychosocial risk factors have dominated research designs in both the child/adolescent and adult literatures, emerging biological data suggest that genetic factors play a role in the etiology of eating disorders. Continued genetics research in eating disorders that is informed by diagnostic classification findings that aim to clarify phenotypes and endophenotypes for these disorders is needed. Transdisciplinary work is needed to examine the extent to which gene–environment interactions may favor the development of one form of eating pathology over another. Similarly, longitudinal studies should investigate whether the peak ages of eating disorder onset, which have traditionally been conceptualized as corresponding to critical psychosocial life transitions, are in part due to epigenetic processes. In this summary, we sought to provide an integrated view of risk factors and disease correlates for eating disorders across the lifespan. For a more indepth treatment of the issues raised in this summary chapter and citations, readers are referred to Chapters 17 and 18. This summary chapter reveals a pattern of greater commonality rather than distinctions among risk factors and disease correlates for eating disorders across childhood/adolescence and adulthood. The recognition of common themes and issues will ideally contribute to ongoing research attempting to understand the etiology of eating disorders.

Part IV

Summary and Future Directions of the Vulnerability Approach

Chapter 20

Future Directions in the Study of Vulnerability to Psychopathology Joseph M. Price and Rick E. Ingram

Our goal in compiling the chapters for the second edition of this volume was to provide readers with an overview of the current theory and research on vulnerability processes associated with several of the major forms of psychopathology as manifested across the age span. As is evident from the chapters in this volume, research on vulnerability to psychopathology continues to flourish. In the four decades since Meehl (1962) first introduced the concept of vulnerability, a wide range of vulnerability processes has been identified and examined. Progress has been made in uncovering both genetic and environmentally based vulnerability processes. Single-factor models of vulnerability to psychopathology have been replaced by diathesis–stress and developmental models of psychopathology. These more comprehensive and ecologically valid models view psychopathology as resulting from a complex and dynamic series of interactions between the characteristics of the individual, including his or her genotype, acquired cognitive, affective, and behavioral orientations, and the characteristics of the person’s social contexts, culture, and stressors. Guided by these models, progress has been made in understanding the interactions between vulnerability processes and environmental stressors and in determining the influences of these interactions on both the emergence and maintenance of psychopathology. Yet, in spite of these advances, several unanswered questions and unresolved issues remain. In this final chapter, our goal is to propose several directions for future research on vulnerability to psychopathology and to do so by synthesizing the recommendations of the authors of chapters of this volume along with our own recommendations for the directions of future research.

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Understanding the Nature and Characteristics of the Disorders Understanding the nature of a particular disorder and having well-defined diagnostic criteria are essential for being able to then proceed with the identification of the vulnerability processes associated with that disorder. Whereas for some disorders there appears to be consensus about the nature and defining characteristics of the disorder (e.g., eating disorders), for other forms of psychopathology there is less agreement about the nature of the disorder and whether the disorder is best conceptualized as a single unified condition or heterogeneous disorder with various subgroups (e.g., schizophrenia). Whether a given disorder is conceptualized as a singular or heterogeneous condition has important implications for research on the vulnerability processes associated with that particular disorder. In Chapter 15, Compton and Harvey contend that one of the impediments to the identification of causal processes in schizophrenia has been the tendency to view schizophrenia as a homogeneous rather than heterogeneous disorder. Consequently, Brennan and Harvey (Chapter 16) call for researchers to attend to the heterogeneity of schizophrenia and its implications for identifying vulnerability processes. Similarly, Chassin et al. (Chapter 7) advocate for more research on the potential heterogeneity of substance abuse and dependence, especially among adolescent populations. The need for clearer and more precise conceptualizations of maladjustment and psychopathology is a theme that has been repeatedly echoed by many of the authors in this volume. In general, the nature and characteristics of disorders manifested during adulthood are better understood and more clearly defined than are disorders that appear in childhood and adolescence. For example, there continue to be uncertainties regarding distinctions among various anxiety disorders manifested during childhood (Bernstein & Victor, 2008). Similarly, in their chapter on vulnerability processes related to personality disorders, Geiger and Crick (Chapter 4) point out ambiguities concerning the nature of personality disorders during childhood and adolescence. There are several possible explanations for this more limited understanding of the nature of childhood and adolescent disorders relative to adult disorders. First, dramatic developmental changes occur across all domains of functioning during childhood and adolescence, making it more difficult to determine the degree of commonality in a particular disorder across age groups during these developmental periods. Second, as a consequence of these changes, the line between normal functioning within a particular domain and deviance in that domain is often more difficult to determine during childhood and adolescence than during adulthood. As Malcarne, Hansdottir, and Merz (Chapter 11) point out regarding patterns of anxiety during childhood, anxiety is a common experience for children. Consequently, it is essential to understand normative developmental patterns within domains of functioning during childhood in



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order to be able to determine the parameters of maladjustment. In addition, as a result, careful attention needs to be devoted to understanding and defining impairment as it occurs during this period of development. A third explanation is that development appears to proceed from undifferentiation among developmental processes (e.g., biological, cognitive, linguistic, and affective) toward differentiation and distinction between processes (Ciccehtti, 2006). Thus, during childhood it would not be surprising to find less organization and cohesion in the symptoms of disorders than during adulthood. Future research directed toward delineating the nature and characteristics of childhood disorders should help to decrease the disparity between the child and adult literatures and also facilitate lifespan research on vulnerability processes. An important avenue for future research in this area will be to determine the degree of commonality among the child, adolescent, and adult variants of particular disorders. In this volume, several possibilities were offered for the relation between childhood manifestations and adult manifestations of particular disorders. One proposed possibility is that there may be a high degree of similarity and commonality in a disorder across developmental periods, which McNally et al. (Chapter 13) suggest is the case for certain phobias (e.g., fear of blood or certain animals). Second, the childhood manifestation of a disorder might represent a developmental variant of an adult syndrome, as McNally et al. contend is the connection between overanxious disorder in childhood and generalized disorder in adulthood. Third, for some disorders, while the underlying nature of the disorder may be the same across developmental periods, the behavioral manifestation may vary across developmental periods (referred to as “heterotypic continuity”). Several decades ago, Kagan (1971) suggested that although homotypical continuity, or the same behavioral manifestations of an underlying process at different points in development, can occur, it is likely to be rare. Heterotypical continuity, involving persistence in the underlying organization and meaning of behavior despite changing behavioral manifestations, may more accurately represent the developmental nature of certain disorders. For example, Keel, Eddy, Thomas, and Schwartz (Chapter 19) suggest that certain biological, psychological, and social risk factors may interact with developmental and life transitions to lead to distinct manifestations of eating disorders at different ages. Thus, an individual might develop anorexia nervosa in adolescence, bulimia nervosa in early adulthood, and BED further into adulthood. Finally, it is possible that the childhood manifestation of a particular disorder constitutes a different form of the disorder than does the adult version, as might be the case with schizophrenia or even depression (see Hammen, Garber, & Ingram, Chapter 10). Vulnerability research may also benefit from taking a step back in the process of scientific inquiry and collecting additional descriptive and qualitative data on the nature and characteristics of various forms of psychopathology. This avenue of research would contribute to the development of more accurate

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constructs and operational definitions of disorders. Research on vulnerability processes would also benefit from descriptive and qualitative research directed toward better understanding the nature and characteristics of the vulnerability processes themselves. Such research is likely to play a pivotal role in helping us to understand the very nature of the disorders associated with these vulnerability processes.

Continuing the Search for Vulnerability Factors and Relations among Vulnerability Factors As has been revealed in this updated volume, over the past several decades there have been significant advancements in identifying biological, cognitive, and affective-based vulnerability processes. Advances in the biological and behavioral sciences have contributed to this trend. Progress on the Human Genome Project and advances in behavioral genetics have aided in providing clues to potential sources of vulnerability processes that are rooted in hereditary processes. In regard to most forms of psychopathology, our knowledge has moved beyond the mere partitioning of hereditary and environmental contributions to identifying specific genes that may play a causal role in the emergence of a specific disorder and the contribution of specific gene–environment interactions. Advances in brain imaging techniques and neurophysiological assessments and the increased availability of such techniques have made it easier to assess neurological processes that serve as vulnerability factors for a wide range of disorders. Further advances in identifying and assessing cognitive and affective processes have contributed to understanding the role of these processes in the development of psychopathology. In addition, recent research that has identified linkages between characteristics of the prenatal environment and psychopathology (e.g., Brennan & Walker, Chapter 14) has helped to broaden the definition and scope of environmentally based vulnerability factors. Finally, continued research on the impact of early social experiences on cognitive and affective processes related to psychopathology continues to increase our understanding of learning-based factors that may function as vulnerability processes. Attempts to identify endophenotypic markers of vulnerability factors represent another area in which there have been major advances. Endophenotypic markers are biological and behavioral markers of latent vulnerabilities for psychopathology that can only be observed by careful measurement; they lie along the causal sequence between genotype and phenotype and, therefore, closer to the genetic vulnerabilities of disorders than do psychological processes or behavior (Lenzenweger, 2004). For example, Hammen, Bistricky, and Ingram (Chapter 9), cite research indicating a connection between the short version of the serotonin transporter gene (5-HTTLPR) and stress reac-



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tivity, which is possibly mediated by the amygdala. Individuals who are carriers of these shorter versions are more likely to develop depression if they have experienced a significant stressor either in childhood or adulthood. In this case, candidate endophenotypic markers of vulnerability factors could include serotonin transport, reactivity of the amygdala, or even stress–environmental sensitivity. Compton and Harvey (Chapter 15) list a number of endophenotypes that have been examined in relation to the development of schizophrenia, including a variety of attentional, memory, cognitive, and physical anomalies. They also note that recent research suggests that composite endophenotypes improve the prediction of a diagnosis of schizophrenia. Thus, the identification of single vulnerability processes cannot be the end point of our efforts if we are to fully understand the role of vulnerability processes in the etiology and treatment of disorder. Many of this volume’s contributors have called for the need to examine the role of combinations of vulnerability factors in the etiology of psychopathology. As noted by Rutter (1996), even in medicine the search for multidimensional causality is the rule rather than the exception. As we move beyond models that assert that disorders arise from singular endogenous pathogens, the need to investigate multiple determinants of psychopathology becomes even more apparent. In addition, developmental psychopathology theorists argue that the emergence of psychopathology is governed by the unique interaction of both vulnerability and protective factors (Cicchetti, 2006; Masten & Powell, 2003). Therefore, expanding this line of inquiry will require examining how combinations of specific vulnerability and protective factors contribute to the onset, maintenance, and even remission of specific forms of psychopathology. We now have at our disposal the statistical techniques and software programs that enable us to examine the interactions of these various influences and to assess these interactions as they unfold over time. In addition to expanding our knowledge base on the complexity of the nature of the etiological of psychopathology, another benefit of examining multiple vulnerability factors simultaneously will be in making distinctions between true vulnerability factors—that is, factors that play some sort of causal role in the development of the disorder—and factors that serve as markers of causal factors. Although correlational studies of the associations between vulnerability processes and psychopathology have been valuable in helping to identify potential vulnerability processes, such designs do not differentiate between true causal factors and factors that are associated with the disorder because of their relation to the vulnerability factor or some other correlated factor. Future research efforts need to be directed toward identifying and understanding these important distinctions between true vulnerability processes and marker variables. An example of this kind of research are studies indicating that deficiencies in smooth-pursuit eye movement serves as a marker of a genetic cause for schizophrenia (Brennan & Walker, Chapter 14; Compton & Harvey, Chapter 15).

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Another important benefit of the inclusion of multiple vulnerability processes in future research will be helping to distinguish between factors that are involved in the onset of the disorder and factors that play an important role in the maintenance of the disorder. This is not to imply that a particular vulnerability process cannot be simultaneously involved in both the onset and maintenance of a disorder. As research on the cognitive vulnerabilities to depression suggests, it is certainly possible for a specific vulnerability process to contribute both to the emergence and clinical course of a disorder. Rather, for certain disorders, different vulnerability factors may serve different functions. Whereas one factor may play a crucial role in the emergence of the disorder, another may be more involved in the maintenance of the disorder. For example, hostile attributional biases have been implicated in the development and onset of certain forms of aggressive behavior in children, in particular, reactive aggression (see Orobio de Castro, Veerman, Koops, Bosch, & Monshouwer, 2002). A hostile attributional bias could be conceptualized as a learned causal vulnerability factor, perhaps as a result of physical abuse (Dodge, Bates, & Pettit, 1990; Price & Glad, 2003). In contrast, peer rejection and the accompanying feelings of social rejection and loneliness, which often result from displays of aggression toward peers, appear to play a role in maintaining and perpetuating the aggressive child’s antisocial tendencies (Dodge et al., 2003). Multiple vulnerability and protective factors can be examined in relation to multiple forms of psychopathology to determine the degree to which a particular vulnerability factor or set of factors is specific to a particular disorder, as opposed to increasing the likelihood of disorder in general. Whereas some vulnerability factors may be specific to the development of a particular disorder, such as dopaminergic hyperactivity in relation to schizophrenia, other types of vulnerability factors may individually be related to a variety of disorders. For example, perceptions of lack of control and negative affect appear to be associated with a variety of disorders, including anxiety, depression, and eating disorders. Likewise, an insecure attachment has been found to be linked to anxiety, depression, conduct disorder, substance abuse, and personality disorders (see Gieger & Crick, Chapter 4). Thus, perceptions of lack of control, negative affect, and an insecure attachment may turn out to be vulnerability factors that are associated with psychopathology in general rather than any specific form of psychopathology. The challenge that remains is to determine the degree of specificity and globality of association of the various types of vulnerability factors identified in this volume with various forms of psychopathology (Ingram, 1990; Ingram & Malcarne, 1995). This can only be accomplished by examining multiple vulnerability processes in relation to multiple forms of psychopathology Finally, future research on the cumulative impact of multiple vulnerability and protective factors will contribute to efforts to improve the targeting of preventative interventions. By identifying sets of vulnerability and protective



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factors, prevention efforts can be directed toward addressing specific vulnerability processes and enhancing specific protective factors and competencies that, in concert, may serve to improve the overall effectiveness and perhaps even duration of preventative interventions.

Understanding Continuity and Change in Vulnerability Processes across the Lifespan As is clear from the organization of this volume, our goal was to present a review of vulnerability processes associated with psychopathology across the lifespan. We chose to accomplish this goal by bringing together researchers from the fields of child and adult psychopathology and by having them share their perspectives on their own and one another’s fields of research. As we have seen in these chapters, there appears to be both continuity and discontinuity in the vulnerability processes across developmental periods, depending on the type and nature of the psychopathology being examined. Yet, as beneficial as the discussion afforded by this volume is in shedding light on the continuity and change in vulnerability processes across the life cycle, there is a paucity of research that directly examines the continuity and discontinuity of vulnerability processes across developmental periods. Certain disorders may share vulnerability processes across both the child and adult manifestations of the disorder. For example, Keel, Eddy, Thomas, and Schwartz (Chapter 19) contend that a core set of vulnerability processes may underlie eating disorders that are manifested across developmental periods. They suggest that in the right cultural context poor self-esteem and perfectionism may predispose an individual to anorexia nervosa in childhood and binge-eating disorders in adulthood. Thus, although the behavioral manifestation of the eating disorders may change across developmental periods, the underlying organization and influence of the vulnerability processes remain the same. In contrast, for some types of disorders, the earlier-onset version might be associated with different combinations of vulnerability processes than the later-onset version. For example, antisocial behavior is more predictive of the onset of alcohol abuse during adolescence than it is for the onset of alcohol abuse in adulthood (Chassin et al., Chapter 7). Research on the continuity and discontinuity of vulnerability factors could also help to reveal distinctions between proximal and distal vulnerability factors. As defined by Ingram, Miranda, and Segal (1998), proximal factors are those that immediately precede the disorder. As an example of a proximal vulnerability factor, these researchers note that dysfunctional cognitive interpretations of a recent event will result in depression. In contrast, distal vulnerability factors emerge much earlier than the onset of the disorder. An example of a distal vulnerability factor might be a negative self-schema that has its origins in childhood. Thus, distal vulnerability factors might rep-

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resent developmental antecedents for a particular disorder. Lifespan research on the continuity of vulnerability processes could help to identify important distinctions between proximal and distal causes of psychopathology, and at each developmental period. In addition to these research directions, research on the continuity and change of vulnerability processes will naturally lead to the examination of the interaction between vulnerability factors and normal maturational processes (e.g., puberty). Research by Brennan and Walker (Chapter 14) suggests that early neurological deficits associated with schizophrenia may interact with normative hormonal changes in adolescence to contribute to the onset of the disorder in late adolescence and early adulthood. This research illustrates how endogenous vulnerability processes may interact with normal maturational processes to determine the conditions for the emergence of psychopathology. Finally, research on the continuity and discontinuity in vulnerability processes across the lifespan can also provide insights into how vulnerability processes might interact with major life transitions to contribute to the development of disorder. For instance, with its associated stresses, the transition between adolescence and adulthood has been hypothesized to play a contributory role in the emergence of schizophrenia. It is possible that major life transitions such as the transition to elementary, middle, or high school, the transition to parenthood, the transition to retirement, or the transitions that result from disruptions in primary relationships may play similar roles in the onset of other forms of psychopathology. Naturally, issues of the continuity and discontinuity of vulnerability processes implies the use of longitudinal or follow-up research designs. Specifically, these issues call for the use of longitudinal research across major periods of development. For example, the use of longitudinal designs can help explain the linkage between early temperament (e.g., difficult temperament) and adult personality (e.g., negative affectivity) and whether these personality constructs are related to a particular disorder, or disorder in general, in the same manner across the lifespan. The specific developmental periods that should be included in such research depend on the type of disorder being examined. For some disorders, the most critical developmental periods might include the span of time between childhood and adolescence (e.g., anorexia nervosa), whereas for other disorders the most informative developmental time span would range from childhood through adulthood (e.g., schizophrenia, depression). As insightful as longitudinal research might be in addressing these issues, the drawbacks of longitudinal research are the time and expense involved in collecting the relevant data. As a way of facilitating the collection of longitudinal data and of decreasing the time and costs involved, child and adult researchers might consider collaborating in studies that use follow-ups in adulthood on samples of children and/or adolescents for whom extensive data on vulnerability processes already exist, as is suggested by Keel, Eddy, Thomas,



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and Schwartz (Chapter 19). Such collaboration would facilitate interactions among researchers of child, adolescent, and adult forms of a specific type of psychopathology.

Understanding the Interactions between Vulnerability Processes and the Environmental Context Both the diathesis–stress and the developmental psychopathology perspectives emphasize the importance of the environmental context in the emergence of maladaptation and psychopathology. According to both perspectives, the characteristics of the individual, including endogenous vulnerability processes, interact with the specific characteristics of the individual’s environmental context to influence the trajectory either toward or away from maladjustment and psychopathology. Thus far, some of the environmental factors that have been identified include the quality of the person’s interactions with significant relationship figures during various developmental periods, socioeconomic conditions, cultural values and norms, and a wide range of stressors (e.g., violence, divorce, school and work pressures). Where progress needs to continue is in determining which specific features of environmental contexts interact with which specific vulnerability processes to contribute to particular forms of psychopathology. Moreover, as Hammen, Garber, and Ingram (Chapter 10) suggest, the role of the transactional dynamics of the relation between the individual—with his or her own unique vulnerability processes— and the social environment in the development of psychopathology warrants further attention. Another direction for future research is to examine vulnerability to psychopathology across various environmental contexts. If, as is suggested by both the diathesis–stress and developmental psychopathology models, vulnerability processes interact with environmental stressors and demands, then differences in environmental contexts may change the susceptibility to disorder and the defining features of the disorder. Unfortunately, there is a paucity of research on contextual differences in the vulnerability to psychopathology, especially such important social contexts as culture. Not only will research on cultural differences in vulnerability to psychopathology help to extend the generalizability of current models of psychopathology to a wider range of cultural and ethnic groups, but it will also lead to interventions that are more sensitive to individual differences. In addition to understanding the interactions between vulnerability processes and the environmental context, it is equally important to understand the changing influence of social contexts across the lifespan. Chassin et al. (Chapter 7) point out that with substance abuse disorders the specific sources of influence may vary somewhat at different stages of development. During childhood, parents and family members may serve as models and socializers;

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during adolescence, peers are an increasingly important socialization influence; and during adulthood, relationship partners become a more important factor. Similar developmental changes in social influences could be associated with other types of psychopathology as well.

Understanding Developmental Pathways: The Importance of Individual Differences Since the origins of risk research, the typical approach to examining vulnerability factors has been to use variable-oriented strategies that strive to identify the primary causal agents involved in the etiology of the psychopathology. These variable-oriented strategies are important because they reveal vulnerability and protective processes that contribute to psychopathology at the group level. This particular research approach also helps us to understand the average or most expected outcomes associated with particular vulnerability processes. In addition, the variable-oriented approach helps to establish relations between particular vulnerability and protective factors and particular forms of psychopathology within the general population. The limitation of this approach, however, is that it reveals little about individual patterns of psychopathology and the diversity of pathways that lead to psychopathology. To gain a better understanding of the alternative pathways taken by individuals en route to psychopathology, Cicchetti and Rogosch (1996) advocate the use of a pathways, or person-oriented, approach. Such an approach to understanding psychopathology focuses on identifying the various routes or pathways taken by different individuals to particular maladaptive outcomes. For example, whereas for one individual the pathway to a borderline personality disorder might be rooted in an insecure attachment relationship during infancy, for someone else the same disordered personality structure might have its original trajectory determined by a chaotic home life during later childhood. A pathways approach also attends to common and uncommon outcomes associated with particular pathways. For instance, depending on the individual genotype and the availability of social support, the experience of early physical abuse might lead to depression in one person but to a conduct or antisocial personality disorder in another. Sroufe (1997) has argued that, whenever possible, developmental pathways should be traced from a point prior to the onset of disturbance. By tracing pathways from a point prior to the emergence of psychopathology, one can better discover the heterogeneity in disorder. Individuals who display similar “symptoms” may in fact be on different developmental pathways when examined longitudinally and may have predictably different outcomes. Following the suggestion of Cicchetti and Rogosch (1996), one way to facilitate the transition between variable-oriented and person-oriented research in a particular area is to use homogeneous subgroups of the disor-



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der to examine the diversity of vulnerability processes and psychopathology outcomes associated with the various subgroupings. Along these lines, Brennan and Harvey (Chapter 16) advocate identifying subgroups associated with schizophrenia based on common etiology. Chassin et al. (Chapter 7) also argue for the value of identifying subgroups associated with substance abuse among adolescents. However, as they point out, difficulties in subtyping may occur because some subcategories of a disorder may not develop until early adulthood. Thus, although it might be possible to identify subtypes of a particular disorder at one point in the lifespan (e.g., adulthood), the disorder might be manifest as a homogeneous and unified condition at another point (e.g., childhood). Another avenue of research within a pathways perspective would be to examine the role of individual choices and actions in the development of psychopathology. With development, the individual plays an increasingly active role in adaptation, interpreting and creating experience as well as responding to a variety of internal and external changes. For example, the literature on depression suggests that, by withdrawing from social interaction and failing to complete daily responsibilities, individuals who are depressed contribute to their own feelings of worthlessness, which, in turn, perpetuates their depressive state. However, to date, little research has been devoted to examining the role of individual choices and actions in the development of psychopathology or examining how the individual’s choices and actions may interact with vulnerability processes and environmental stressors. As the chapters in this volume reveal, for many forms of psychopathology a substantial empirical base has been built up by using variable-oriented strategies. Subgroup and pathways approaches can extend this knowledge base by examining the different types of pathways and vulnerability processes that could be associated with various forms of psychopathology. In turn, this information can be used to develop a wider range of intervention strategies that could be tailored to the specific needs of individuals.

Understanding the Malleability of Vulnerability Factors and Processes One of the core issues that remains to be adequately addressed in vulnerability research is the extent to which vulnerability processes are open to malleability and change (Ingram et al., 1998). It might be expected that biologically based vulnerability processes that are rooted in genotypes or environmental trauma would be less open to change than vulnerability processes acquired through socialization and learning. However, the question of the extent to which both hereditary and learning-based vulnerability processes are malleable remains largely unanswered in the vulnerability literature. It may be possible that even hereditary-based biological vulnerabilities can be altered to some extent. Conversely, although learning-based vulnerabilities such as learned helplessness

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SUMMARY AND FUTURE DIRECTIONS

might be expected to be receptive to alteration, they may, nonetheless, be quite resistant to change. Many developmental theorists and researchers (e.g., Cicchetti, 2006; Sroufe, 1997) contend that change in psychological processes may be constrained by prior adaptation. That is, the longer a maladaptive pathway has been followed, the less likely it is that the person will reclaim positive adaptation. Thus, even learning-based vulnerability processes (e.g., learned helplessness), if used consistently and over a long period, may be resistant to change. Recent theory and research on the developing brain and neural plasticity may prove particularly informative in improving our understanding of the degree to which malleability of specific vulnerability processes is possible across the lifespan (see Cicchetti & Curtis, 2006). Numerous studies have consistently verified the brain’s ability to recover various degrees of functioning following lesions and other injuries to its physical structure (see Kolb & Gibb, 2001). Thus, a vulnerability process, and its accompanying neural substrates, that may have resulted from early trauma or an adverse experience might be amenable to a certain degree of malleability. The degree of malleability is likely to be dependent upon the presence or absence of other vulnerability and protective factors as well as such environmental experiences as exposure to early intervention. The malleability of vulnerability processes could be examined using existing data from prevention and treatment intervention research literatures to determine the extent to which vulnerability processes have been able to be altered and whether the degree of change depends on developmental level. Data available from prevention projects could provide insights into the extent to which vulnerability processes can be altered prior to the onset of the disorder. Likewise, data available from treatment studies could be used to examine the degree to which vulnerability processes can be modified after the onset of disorder. The next step in the process of determining the extent to which vulnerability processes can be altered would be to design prevention and treatment studies with the explicit goal of targeting specific vulnerability processes for change.

Summary At the close of this volume, we stand in agreement with our esteemed collaborators in calling for increased dialogue between researchers of vulnerabilities to both child and adult psychopathology. As is revealed in the child and adult integration chapters, such communication increases our overall understanding of the vulnerability processes that are associated with various forms of maladjustment and psychopathology as they occur across the lifespan. These discussions provide a rich context for the generation of new ideas and directions for future research. We also agree with the authors that a developmental perspective will greatly enhance our future research efforts in identifying and understanding vulnerability processes within developmental periods and



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across the lifespan. Both general and specific developmental models of psychopathology exist to guide this line of inquiry. In addition, sophisticated statistical procedures for analyzing longitudinal data with multiple variables (e.g., HLM and LISREL-based techniques) exist to facilitate more lifespan research. The current state of the field of vulnerability research in combination with technological and methodological advances will contribute to initiating an informative era of the study of vulnerability to psychopathology. It is our hope that as investigators of childhood disorders and investigators of adult disorders increase their dialogue—as we have attempted to facilitate in this volume—the focus of the next era of research will be on vulnerability to psychopathology across the entire lifespan.

References Bernstein, G. A., & Victor, P. J. (2008). Childhood anxiety disorders. In S. Hossein Fatemi & P. J. Clayton (Eds.), The medical basis of psychiatry (pp. 375–390). New York: Humana Press. Cicchetti, D. (2006). Developmental psychopathology. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology (Vol. 1, pp. 1–23). New York: Wiley. Cicchetti, D., & Curtis, W. J. (2006). The developing brain and neural plasticity: Implications for normality, psychopathology, and resilience. In D. Cicchetti & D. J. Cohen (Eds.), Developmental psychopathology (Vol. 2, pp. 1–64). New York: Wiley. Cicchetti, D., & Rogosch, E. A. (1996). Equifinality and multifinality in developmental psychopathology. Development and psychopathology, 8, 597–600. Dodge, K. A., Bates, J. E., & Pettit, G. S. (1990). Mechanisms in the cycle of violence. Science, 250, 1678–1683. Dodge, K. A., Landford, J. E., Burks, V. S., Bates, J. E., Petitt, G. S., Fontaine, R., et al. (2003). Peer rejection and social information-processing factors in the development of aggressive behavior problems in children. Child Development, 74, 374–393. Ingram, R. E. (1990). Self-focused attention in clinical disorders: Review and a conceptual model. Psychological Bulletin, 107, 156–176. Ingram, R. E., & Malcarne, V. L. (1995). Cognition in depression and anxiety: Same, different, or little of both? In K. D. Craig & K. S. Dobson (Eds.), Anxiety and depression in adults and children (pp. 37–56). Newbury Park, CA: Sage. Ingram, R. E., Miranda, J., & Segal, Z. V. (1998). Cognitive vulnerability to depression. New York: Guilford Press. Kagan, J. (1971). Change and continuity in infancy. New York: Wiley. Kolb, G., & Gibb, R. (2001). Early brain injury, plasticity, and behavior. In C. A. Nelson & M. Luciana (Eds.), Handbook of developmental cognitive neuroscience (pp. 175–190). Cambridge. MA: MIT Press. Lenzenweger, M. F. (2004). Consideration of the challenges, complications, and pitfalls of taxometric analysis. Journal of Abnormal Psychology, 113(1), 10–23. Masten, A. S., & Powell, J. L. (2003). A resilience framework for research, policy, and practice. In S. S. Luthar (Ed.), Reslience and vulnerability: Adaptation in the context of childhood adversities (pp. 1–28). New York: Cambridge University Press. Meehl, P. E. (1962). Schizotaxia, schizotypy, and schizophrenia. American Psychologist, 17, 827–838. Orobio de Castro, B., Veerman, J. W., Koops, W., Bosch, J. D., & Monshouwer, H. J. (2002). Hostile attribution of intent and aggressive behavior: A meta-analysis. Child Development, 73, 916–934.

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Price, J. M., & Glad, K. (2003). Attributional tendencies in maltreated children. Journal of Abnormal Child Psychology, 31, 329–343. Rutter, M. (1996). Developmental psychopathology: Concepts and prospects. In M. Lenzenseger & J. Havguard (Eds.), Frontiers of developmental psychopathology (pp. 209–237). New York: Oxford University Press. Sroufe, L. A. (1997). Psychopathology as an outcome of development. Development and Psychopathology, 9, 251–268.

Index

“f” following a page number indicates a figure; “t” following a page number indicates a table. defining, 13–15 depression in, 42–44, 248–273 biological factors, 253–259 cognitive factors, 259–263 comorbidity and, 250–251 course and outcome of, 251–253 defining, 248–250 epidemiology and demographics of, 253 future directions regarding, 272–273 interpersonal factors and, 268–272 life stress approaches to, 263–267 theory and research and, 253–272 disorders of, 40–45, 498–500. see also specific disorders eating disorders in, 41–42, 454–482, 499 assessment and, 457–458 biological factors, 461–464 comprehensive view of vulnerability for, 478–479, 480f defining, 455, 456t demographic characteristics associated with, 465–466 dietary restraint model and, 458–461, 460f dieting and, 469–472 etiology of, 458–461, 460f future directions regarding, 481–482, 493–494 interpersonal vulnerability model of, 460–461, 460f life events and, 472–475 prevalence of, 455 prevention and, 479–481

Abstinence violation effect, 459 Abuse, child. see Child maltreatment Acceptance, parental, 312–313 Acetylcholine, 205 Addiction, 143. see also Substance use disorders Adolescence. see also Childhood/ adolescence anxiety disorders and, 295–296, 305–306 depression and, 198–199 hormonal factors and, 376–378 schizophrenia and, 376–378 substance use disorders and, 176–183 Adulthood anxiety disorders in, 44–45, 334–350, 349–350 anxiety sensitivity and, 336–338 cognitive factors and, 348–349 genetic factors and, 341–342, 347–348 history of theory and research and, 335 information-processing biases and, 338–340 neurobiological factors and, 348 obsessive–compulsive disorder and, 347–349 panic disorder and agoraphobia, 335–342 posttraumatic stress disorder and, 342–347 smoking and, 340 trauma and, 342–347



511

512 Adulthood, eating disorders in (continued) psychological factors and, 466–469 psychosocial perspectives, 464–472 risk factors and, 455–458 treatment and, 476–478 personality disorders childhood/adolescence precursors to, 66–93 stability of, 65–66 schizophrenia in, 45, 389–409 diathesis–stress model of, 393–394 epidemiology of, 390 experiential/environmental factors, 398–400 genetic factors and, 394–398, 395t phenotype and phenomenology of, 390–393 prevention perspective of, 407–409 sequential onset of, 404–407 substance use disorders in, 40–41, 141–166 clinical characteristics, 144–146 conceptualizations, 142–144 intervention and, 161–166 models of, 148–150 prevalence of, 146–148 research on, 150–160 vulnerability in, 39–52 Affect, flat, 67–68, 72–74 Affective disorders. see Mood or affective disorders Affective factors anxiety disorders and, 305–306 childhood/adolescence, 27t, 28 substance use disorders and, 123–125, 156–157 Age factors anxiety disorders and, 299 comorbidity and, 193 depression and, 193, 251–252 eating disorders and, 428, 429–430 personality disorders and, 94 schizophrenia and, 391–392, 419 substance use disorders and, 115–117, 179 Aggression impulsivity and, 75 personality disorders and, 96–97 relationships and, 79, 83 Agoraphobia, 293, 335–342. see also Anxiety disorders

Index Agreeableness, 68, 153–154 Alcohol use and disorders. see also Substance use disorders across the lifespan, 176–183 interpersonal factors and, 159–160 prevalence of, 147–148 All-or-nothing thinking, 459 Amygdalar functioning anxiety disorders and, 305 depression and, 205–207 overview, 500–501 Anger, 79, 434 Anorexia nervosa. see also Eating disorders age of onset, 428 lifespan and, 489–494 overview, 40–41 perfectionism and, 77 prevalence of, 425–426 psychological factors and, 433 Antisocial personality disorder, 75 Anxiety, 27t Anxiety disorders in adulthood, 44–45, 334–350 anxiety sensitivity and, 336–338 cognitive factors and, 348–349 future directions regarding, 349–350 genetic factors and, 341–342, 347–348 history of theory and research and, 335 information-processing biases and, 338–340 neurobiological factors and, 348 obsessive–compulsive disorder and, 347–349 panic disorder and agoraphobia, 335–342 posttraumatic stress disorder and, 342–347 smoking and, 340 trauma and, 342–347 in childhood/adolescence, 291–321, 498–500 biological factors, 301–305 cognitive factors, 305–306 comorbidity and, 298 course and stability of, 294–298 depression and, 193–194 emotion regulation and, 306–307 epidemiology of, 292–293 future directions regarding, 319–321



Index

prevention and treatment and, 316–319 processing bias and, 307–311 risk factors and, 299–301 social and environmental factors, 311–316 depression and, 297, 298 future directions regarding, 358–360 lifespan and, 357–360 substance use disorders and, 154–155 Anxiety sensitivity, 154–155, 336–338 Anxiety Sensitivity Index (ASI), 336–337 Assessment depression and, 195, 248 eating disorders and, 457–458 personality disorders and, 63–65 Attachment relationships anxiety disorders and, 312–313, 314–315 depression and, 217–219, 268–269 personality disorders and, 73–74, 80–81 Attachment styles, 88–89 Attachment theory, 217–218 Attentional processes anxiety disorders and, 307–311 impulsivity and, 75–76 overview, 212–213 schizophrenia and, 370–371, 403 Attention-deficit/hyperactivity disorder (ADHD) depression and, 193–194 impulsivity and, 75–76 substance use disorders and, 123 vulnerability factors related to, 27t Attributional models, 261, 502 Avoidant disorder of childhood (AVD), 291, 305–306. see also Anxiety disorders Avoidant personality disorder eating disorders and, 468 relationships and, 81–82 sense of self and, 84–90

B Behavioral factors childhood/adolescence, 27t, 28 schizophrenia and, 369–372 substance use disorders and, 157–159 Behavioral inhibition, 301–302, 315 Behavioral regulation, 212–213 Behavioral therapies, 162–163 Binge Eating Scale (BES), 458

513

Binge-eating disorder (BED). see also Eating disorders in adulthood, 454–482 assessment and, 457–458 biological factors, 461–464 bulimia nervosa and, 475–476 comprehensive view of vulnerability for, 478–479, 480f demographic characteristics associated with, 465–466 developmental factors, 499 dietary restraint model and, 458–461, 460f dieting and, 469–472 etiology of, 458–461, 460f future directions regarding, 481–482, 493–494 interpersonal vulnerability model of, 460–461, 460f life events and, 472–475 lifespan and, 489–494 prevalence of, 426 prevention and, 479–481 psychological factors and, 433–434 psychosocial perspectives, 464–472 risk factors and, 455–458 treatment and, 476–478 Biological factors. see also Genetic factors; Neurobiological factors anxiety disorders and, 301–305 depression and, 253–259 eating disorders and, 428–432, 481 emotion regulation and, 69–70 relationships and, 80 substance use disorders and, 151–153 Biopsychosocial model depression and, 222–224, 223f eating disorders and, 427–428, 439–442, 444, 481 substance use disorders and, 149–150, 182–183 Bipolar disorder, 43–44. see also Mood or affective disorders Body image, eating disorders and, 473–474 Borderline personality disorder. see also Personality disorders eating disorders and, 468 hostile world view and, 67–68 impulsivity and, 74–75 relationships and, 79 sense of self and, 86–89

514 Brain. see also Neurobiological factors anxiety disorders and, 304–305, 348 depression and, 203–208, 256–259 personality disorders and, 70 posttraumatic stress disorder and, 344–345 schizophrenia and, 365–367, 405 substance use disorders and, 116–117 Brain imaging studies anxiety disorders and, 305 depression and, 205–207, 258–259 schizophrenia and, 365–367 Brief Body Sensations Interpretation Questionnaire (BBSIQ), 339 Bulimia nervosa. see also Eating disorders in adulthood, 475–476 age of onset, 428 lifespan and, 489–494 overview, 42 prevalence of, 425–426 psychological factors and, 433–434 Bullying, 220–221, 472

C Cardiovascular functioning, 304–305 Causal risk factors. see also Risk factors depression and, 199 overview, 4–5 schizophrenia and, 406–407 substance use disorders and, 151 Central nervous system, 370 Child development movement model, 25 Child maltreatment borderline personality disorder and, 88 depression and, 261, 265–266 eating disorders and, 472 emotion regulation and, 71 posttraumatic stress disorder and, 344 Childhood/adolescence anxiety disorders in, 291–321, 498–500 biological factors, 301–305 cognitive factors, 305–306 comorbidity and, 298 course and stability of, 294–298 emotion regulation and, 306–307 epidemiology of, 292–293 future directions regarding, 319–321 prevention and treatment and, 316–319 processing bias and, 307–311 risk factors and, 299–301

Index social and environmental factors, 311–316 defining, 13–15 depression in, 189–224 comorbidity and, 192–194 continuity of, 194–195 course and outcome of, 195–197, 251–252 future directions regarding, 221–224, 223f gender differences, 198–199 genetic factors and, 201–203 interpersonal factors and, 217–221 life events and trauma and, 214–217 neurobiological factors and, 203–208 phenomenology of, 189–192 prevalence of, 197–198 research methodology and, 199–200 self-regulation and coping and, 212–214 temperament and, 208–209 theory and research and, 200–221 disorders of, 498–500 eating disorders in, 425–445, 499 biological factors, 428–432 biopsychosocial model and, 439–442 case example of, 440–442 development of, 427–428, 439 future directions regarding, 443–444, 493–494 psychological factors, 432–435 research methodology and, 426–427 social factors, 435–438 temperament and, 431–432 treatment and prevention and, 442–443 personality disorders, 58 assessment and, 65 emotions and, 68–74 impulsivity and, 74–76 precursors of in adults and, 66–93 relationships and, 78–83 rigidity and, 76–78 sense of self and, 84–90 stability of, 65–66 personality disorders in, 498 lack of concern for norms or the needs of others and, 92–93 thoughts and behaviors and, 90–92 psychopathology and, 19–20 schizophrenia in, 363–380



Index

behavioral markers of, 369–372 congenital factors, 364–374 future directions regarding, 379–380 genetic factors and, 373–374 intervention and, 378–379 neurodevelopmental perspective of, 374–378, 379f physical signs of, 365–369 prenatal and perinatal factors, 372–373 substance use disorders in, 113–129 age factors and, 115–117 epidemiology of, 114–117 future directions regarding, 128–129 negative affect pathway and, 123–125 prevention and, 126–127 reinforcing effects and, 125–126 research and methodology, 117–123 treatment and, 127–129 vulnerability in, 18–34, 24–33, 27t Chronicity, 252–253 Cigarette smoking, 340 Classification systems, 13–14 Cognitions, 209–212, 219, 309–311 Cognitive distortions, 459 Cognitive factors anxiety disorders and, 305–306, 348–349 childhood/adolescence, 27t depression and, 259–263, 284–285 eating disorders and, 467 personality disorders and, 68 schizophrenia and, 402–403 sense of self and, 85 substance use disorders and, 121–122 Cognitive models, depression and, 209– 212, 220, 259–263 Cognitive restructuring, 317–318 Cognitive therapy, 7 Cognitive-behavioral therapy, 317, 318–319, 477 Comorbidity anxiety disorders and, 296, 298 depression and, 192–194 eating disorders and, 468–469 Compensatory reaction, 145 Conduct disorder childhood/adolescence, 27t, 28 depression and, 193 “Fast Track” prevention program and, 22–23

515

Conduct problems, 118–119, 123 Conscientiousness, 153–154, 177 Consequences, 154 CONSORT criteria, 317 Consortium on the Genetics of Schizophrenia (COGS), 396–397 Continuity of care, 161–162 Control, perception of, 308–309 Coolidge Personality and Neuropsychological Inventory for Children (CPNI), 65 Coping Cat intervention, 317 Coping skills depression and, 212–214 emotion regulation and, 70–71 overview, 212–213 Cortisol levels, depression and, 203–205, 207, 256–257 Criticism, parental, 312–313 Cross-sectional studies, 427 Cultural factors, 177, 438

D Decision-making skills, 121–122 Degenerative model of schizophrenia, 363–364, 366–367, 418 Delusions, 91, 391–392. see also Schizophrenia Dependency beliefs, 271 Dependent behavior, 78–83, 96–97 Dependent personality disorder, 84–90 Depression. see also Mood or affective disorders in adulthood, 43, 248–273 biological factors, 253–259 cognitive factors, 259–263 comorbidity and, 250–251 course and outcome of, 251–253 defining, 248–250 epidemiology and demographics of, 253 future directions regarding, 272– 273 interpersonal factors and, 268–272 life stress approaches to, 263–267 theory and research and, 253–272 anxiety disorders and, 297, 298 causality and, 4–5 in childhood/adolescence, 189–224 comorbidity and, 192–194 continuity of, 194–195

516

Index

Depression, in childhood/adolescence (continued) course and outcome of, 195–197, 251–252 future directions regarding, 221–224, 223f gender differences, 198–199 genetic factors and, 201–203 interpersonal factors and, 217–221 life events and trauma and, 214–217 neurobiological factors and, 203–208 phenomenology of, 189–192 prevalence of, 197–198 research methodology and, 199–200 self-regulation and coping and, 212–214 temperament and, 208–209 theory and research and, 200–221 vulnerability factors related to, 27t eating disorders and, 468 lifespan and, 282–286 personality disorders and, 72 Detoxification, 145–146 Developmental factors. see also Lifespan anxiety disorders and, 294–298 childhood/adolescence, 28–29 comorbidity and, 193–194 depression and, 190–191 eating disorders and, 427–428, 439 individual differences and, 506–507 overview, 499 personality disorders and, 96–97 schizophrenia and, 374–378, 417–418 sense of self and, 84 substance use disorders and, 116–117, 178–182 Developmental models childhood/adolescence and, 29–30, 32 depression and, 190–191 eating disorders and, 444 overview, 58 personality disorders and, 96 Developmental moderation model, 376 Developmental psychopathology perspective impulsivity and, 75–76 overview, 26–28, 27t, 505–506 Deviance proneness models, 120–123 Diagnosis anxiety disorders and, 319–320 defining childhood and adulthood and, 14

depression and, 249–250, 282–283 disorders of adulthood and, 40–45 eating disorders and, 456t overview, 498 personality disorders and, 58, 94–95 posttraumatic stress disorder and, 342 schizophrenia and, 391 substance use disorders and, 113, 142–146, 178–179 Diathesis–stress models anxiety disorders and, 357 compared to developmental models, 29–30 depression and, 260–261, 262 overview, 10, 32, 505–506 schizophrenia and, 26, 374–375, 393–394, 418–419 strengths of, 393 weaknesses of, 393–394 Dietary restraint model, 458–461, 460f Dieting, eating disorders and, 469–472, 473–474, 481, 489–490, 491–492 Dimensional model, 95 Discipline, 217–219 Disease models, 29, 32, 149 Disengagement coping, 213 Disorders, 14, 498–500. see also specific disorders Disorganization, 71 Dissociation, 88–89 Distress tolerance, 158–159 Dopaminergic system, 255 Drinking restraint model, 180 Drug-induced euphoria, 144 DSM (DSM-III, DSM- IV, DSM-IV-TR) anxiety disorders and, 291–292, 319–320 defining childhood and adulthood with, 13–14 depression and, 197 disorders of adulthood and, 40 anxiety disorders, 44–45 depression, 249 eating disorders, 41–42 mood or affective disorders, 43–44 schizophrenia, 45 substance-related disorders, 40–41 disorders of childhood/adolescence and depression and, 189–190 psychopathology and, 19



Index

eating disorders and, 425, 454, 456t, 468–469 personality disorders and, 58–62, 60t–61t, 94–95 schizophrenia and, 392 substance use disorders and, 40–41, 113, 143 Dyskinesia, 369–370 Dysthymia, 189–190. see also Depression

E Eating Disorder Examination (EDE 16.0), 458 Eating Disorder Inventory (EDI-3), 458 Eating disorders in adulthood, 41–42, 454–482, 499 assessment and, 457–458 biological factors, 461–464 comprehensive view of vulnerability for, 478–479, 480f defining, 455, 456t demographic characteristics associated with, 465–466 dietary restraint model and, 459, 460f dieting and, 469–472 etiology of, 458–461, 460f future directions regarding, 481–482, 493–494 interpersonal vulnerability model of, 460–461, 460f life events and, 472–475 prevalence of, 455 prevention and, 479–481 psychological factors and, 466–469 psychosocial perspectives, 464–472 risk factors and, 455–458 treatment and, 476–478 in childhood/adolescence, 425–445, 499 biological factors, 428–432 biopsychosocial model and, 439–442 case example of, 440–442 development of, 427–428, 439 future directions regarding, 443–444, 493–494 psychological factors, 432–435 research methodology and, 426–427 social factors, 435–438 temperament and, 431–432 treatment and prevention and, 442–443 lifespan and, 489–494

517

overview, 41–42 perfectionism and, 77 personality disorders and, 77 Eating Disorders Examination Questionnaire (EDE-Q-6.0), 458 Eating disorders not otherwise specified (EDNOS), 426, 428. see also Eating disorders Ecological momentary assessment (EMA) techniques, 180–181 Emotion, 68–74, 156–157. see also Affective factors Emotion regulation anxiety disorders and, 306–307 overview, 212–213 personality disorders and, 68–74, 92–93 Empathy, personality disorders and, 92–93 Endogenous variables, 8–9 Endophenotypes, 401–404, 500–501 Engagement coping, 213 Enhanced reinforcement model, 125–126 Environmental factors anxiety disorders and, 311–316, 357, 359 emotion regulation and, 69–71 overview, 505–506 schizophrenia and, 380, 398–400, 401, 420–421 substance use disorders and, 120, 128–129, 177 Ethnicity anxiety disorders and, 300 eating disorders and, 465–466 substance use disorders and, 115 Event-related potential (ERP), 152 Evidence-based intervention programs, 161–162 Executive functioning skills, 74–75, 121 Experiential factors, 398–400 Exposure techniques, 317–318 Extraversion, 153–154

F “False-self behavior”, 85–86 Family environment. see also Home environment depression and, 217–219 eating disorders and, 437–438, 461, 463–464 prevention of eating disorders and, 480–481 relationships and, 79–80

518

Index

Family therapy anxiety disorders and, 318–319 prevention of eating disorders and, 480–481 substance use disorders and, 162 “Fast Track” prevention program, 22–23 Feared sensations, 336–337 Fearfulness, 93 Fearlessness, 93 Five-axis classification system, 190 Five-factor model of personality, 153–154 Flat affect, 67–68, 72–74 Focus on Families program, 126–127

G Gender anxiety disorders and, 297–298, 299–300 comorbidity and, 193 depression and, 193, 198–199, 208–209, 254–255, 264 eating disorders and, 429–430, 492 personality disorders and, 63, 94 posttraumatic stress disorder and, 345 schizophrenia and, 45 substance use disorders and, 115 temperament and, 208–209 Gene–environment interactions, 119, 129 Generalized anxiety disorder (GAD), 291. see also Anxiety disorders Genetic factors. see also Biological factors anxiety disorders and, 303–304, 341–342, 357 depression and, 199, 201–203, 254–255, 283–284 eating disorders and, 428–430, 438, 462–463, 465, 481 emotion regulation and, 69–71 history of theory and research and, 50 overview, 500–501 personality traits and, 7 posttraumatic stress disorder and, 345 schizophrenia and, 371–372, 373–374, 380, 394–398, 395t, 405 substance use disorders and, 119–120, 129, 152–153, 176–177 Group treatment, 318 Growth hormone, 204–205 “Guidance movement” model, 25 Guilt, 434

H Hallucinations, 90–91, 391–392. see also Schizophrenia Heart-rate variability, 304–305 Heredity-based vulnerability cognitions and, 211 depression and, 201–203, 211 eating disorders and, 461–462 overview, 26 schizophrenia and, 395–396, 395t substance use disorders and, 119–120 Heterogeneity, 179–180 Home environment, 71, 79–80 Hopelessness model, 260–261 Hormonal factors, 376–378, 379f, 462–463 Hostile attributional bias, 502 Hostile world view, 67–68 HPA axis anxiety disorders and, 304 depression and, 255, 256–257, 267 schizophrenia and, 375–376, 377, 380 Hyperkinesia, 369–370

I Identity, 86 Implicit Association Test (IAT), 339 Impulsivity, 68, 74–76, 121 Indicated preventive interventions, 408– 409. see also Prevention interventions Individual differences overview, 506–507 personality disorders and, 94 substance use disorders and, 125–126, 154–155 Infants. see also Childhood/adolescence anxiety disorders and, 294 depression in, 190, 197 life events and trauma and, 214– 215 schizophrenia and, 372–373, 376, 399–400 Information-processing skills anxiety sensitivity and, 338–340 depression and, 209–212 hostile world view and, 67–68 relationships and, 79 Inhibition, 301–302, 315 Inhibitory control, 212–213 Integrated models, 222, 272–273 Intelligence, 344, 346



Index

International Classification of Diseases (ICD-10), 292 Interpersonal factors. see also Relationships depression and, 216, 217–221, 268–272 substance use disorders and, 159–160 Interpersonal therapy, 478 Interpersonal vulnerability model, 460–461, 460f Interpretation bias, 307–311 Interventions. see also Prevention interventions; Treatment anxiety disorders and, 316, 317–319 eating disorders and, 442–443 personality disorders and, 94–96 schizophrenia and, 378–379, 408–409 substance use disorders and, 161–166 Involuntary movements, 369–370 IQ, 344, 346

K Kindling process, 48, 262, 266–267

L Learning problems, 122, 128, 179 Life events anxiety disorders and, 315–316, 359 depression and, 214–217, 263–267, 285 eating disorders and, 472–475 Life partnership, eating disorders and, 472–473 Lifespan. see also Developmental factors anxiety disorders and, 357–360 depression and, 196–197, 282–286 eating disorders and, 478–479, 480f, 489–494 schizophrenia and, 417–421 substance use disorders across, 176– 183 Lifespan models, 29–30 Limbic–hypothalamic–pituitary– adrenocortical (LHPA) system, 203–205, 214 Limit violation effect (LVE), 180 Longitudinal studies continuity and change in vulnerability and, 504–505 eating disorders and, 427, 432–433 substance use disorders and, 182– 183 Loss, 216, 315–316

519

M Maintenance factors, 151 Maltreatment, child borderline personality disorder and, 88 depression and, 261, 265–266 eating disorders and, 472 emotion regulation and, 71 posttraumatic stress disorder and, 344 Marijuana use and disorders, 148, 155– 156. see also Substance use disorders Marital functioning, 269–270, 315–316 Marriage, eating disorders and, 472–473 McKnight Risk Factor Study, 431 Media influences, 436 Medications, 6–7, 165–166. see also Pharmacotherapy Millon Adolescent Clinical Inventory (MACI), 65 Minnesota Multiphasic Personality Inventory—Adolescent (MMPI-A), 65 Minor physical anomalies (MPAs), schizophrenia and, 367–369, 380 Modeling of behaviors, anxiety disorders and, 313–314 Molecular genetics of schizophrenia, 397–398 Monitoring the Future (MTF) project, 114 Mood or affective disorders, 42–44, 48, 464. see also Depression Motivation, 145, 154 Motivational therapies, 163–164 Motor abnormality, schizophrenia and, 369–370 Multidimensional Personality Questionnaire, 431 Multisystemic therapy (MST), 122, 162

N Needs of others, 92–93 Negative affect. see also Neuroticism depression and, 208, 271 eating disorders and, 434 substance use disorders and, 145, 156–157, 177, 180–181 Negative affect pathway, 123–125 Negative cognitions, 209–212, 309–311. see also Cognitions Negative symptoms, 45, 419

520

Index

Neurobiological factors. see also Biological factors; Brain anxiety disorders and, 304–305, 348 depression and, 203–208, 256–259, 284 eating disorders and, 430–431 posttraumatic stress disorder and, 344–345 schizophrenia and, 405 Neurochemical dysregulation, 207–208 Neurodevelopmental perspective of schizophrenia future directions regarding, 380 overview, 363–364, 374–378, 379f, 418 Neuroticism. see also Negative affect depression and, 271 personality disorders and, 68 substance use disorders and, 153–154, 177 Neurotransmitters, 205, 257–258 Noradrenergic system, 255 Norepinephrine, 205 Norms, 92–93, 160

O Obesity dieting and, 469–472 eating disorders and, 463–464 prevention of eating disorders and, 479–481 Obsessive–compulsive disorder (OCD). see also Anxiety disorders course of, 295–296 epidemiology of, 293 genetic factors and, 347–348 overview, 292, 347–349 perfectionism and, 77 personality disorders and, 77 Openness, 153–154 Oppositional defiant disorder (ODD), 193 Outcome expectancies, 154 Overanxious disorder (OAD). see also Anxiety disorders course of, 295 epidemiology of, 293 overview, 291

P Panic attacks, 337 Panic disorder. see also Anxiety disorders cognitive factors, 305–306 eating disorders and, 468

epidemiology of, 293 overview, 335–342 Paranoid personality disorder, 58–59, 67–68. see also Personality disorders Paranoid world view, 67–68 Parental anxiety management (PAM), 318 Parental mood disorders, 464 Parent–child relationship anxiety disorders and, 311–315 depression and, 268–269 eating disorders and, 433, 437–438 emotion regulation and, 69 Parenting anxiety disorders and, 311–315 cognitions and, 211 depression and, 209, 211, 217–219, 261, 268–272 eating disorders and, 433, 437–438, 463–464, 473–474 emotion regulation and, 69 life events and trauma and, 214–215 personality disorders and, 68, 73–74, 93 prevention of eating disorders and, 480–481 substance use disorders and, 120–123, 128 temperament and, 209 Pathways approach, 506–507 Peer relationships depression and, 219–221 substance use disorders and, 122, 127, 128 Perceived control, 308–309 Perfectionism, 77, 432 Perinatal factors, 372–373. see also Infants Personal Assessment and Crisis Evaluation (PACE) program, 409 Personality depression and, 271 eating disorders and, 467 overview, 57 schizophrenia and, 400–404 substance use disorders and, 153–154, 177 Personality Diagnostic Questionnaire (PDQ), 64–65 Personality disorders assessment and, 63–65 in childhood/adolescence, 58, 498 emotions and, 68–74 flat affect, 68–74 hostile world view and, 67–68



Index

impulsivity and, 74–76 lack of concern for norms or the needs of others and, 92–93 relationships and, 78–83 rigidity and, 76–78 sense of self and, 84–90 thoughts and behaviors and, 90–92 DSM and, 58–62, 60t–61t eating disorders and, 468–469 future directions regarding, 96–98 individual differences and, 94 intervention and, 94–96 overview, 57–63, 60t–61t stability of, 63, 65–66 Personality Disorders Examination (PDE), 64–65 Personality traits, 6–8 Person-oriented approach, 506–507 Pharmacotherapy anxiety disorders and, 318 depression and, 204, 205 eating disorders and, 443, 474–475 personality traits and, 6–7 substance use disorders and, 165–166 weight gain and, 474–475 Physical abuse, 88, 265–266. see also Child maltreatment Physical features, 367–369, 380 Positive emotionality, 208 Positive symptoms, schizophrenia and, 45, 419 Posttraumatic stress disorder (PTSD). see also Anxiety disorders depression and, 215 epidemiology of, 293 overview, 316, 342–347 rationale for the study of vulnerability and, 46 substance use disorders and, 157 Pregnancy, eating disorders and, 473–474 Prenatal factors, schizophrenia and, 372–373, 376, 398–399 Prevention interventions anxiety disorders and, 316–317 eating disorders and, 442–443 “Fast Track” prevention program and, 22–23 schizophrenia and, 407–409, 420–421 substance use disorders and, 126–127 Primary prevention, 407–408. see also Prevention interventions

521

Problem-focused coping, 212–213 Processing bias, 307–311 Protective factors, 501 Proxy risk factors, 151. see also Risk factors Psychological factors, 153–156, 432–435, 466–469 Psychological vulnerability models, 272–273 Psychopathology, 15, 19–20. see also individual disorders Psychophysiological abnormalities, schizophrenia and, 404 Psychosis, 155–156, 405–406. see also Schizophrenia Psychosocial perspectives, 464–472 Psychotic processes, 90–91

Q Questionnaire on Eating and Weight Patterns (QEWP-R), 458

R Reassurance seeking, 271 Recurrence of disorders, 195–196, 252–253 Reinforcing effects, 125–126 Rejection, depression and, 220 Relapse, 197, 392 Relapse prevention, 477 Relationships, 78–83, 268–272, 472–473. see also Interpersonal factors Relaxation techniques, 317–318 Research methodology, 30–33 Resilience, 11–12, 13f, 179 Restraint model, 180–181 Restricted affect. see Flat affect Reverse causality, depression and, 199 Reverse tolerance, 144, 266–267 Rigidity, personality disorders and, 76–78 Risk factors anxiety disorders and, 299–301, 316 depression and, 262–263 eating disorders and, 455–458, 489–493 personality disorders and, 58, 93 posttraumatic stress disorder and, 343–346 relationship between vulnerability and, 11–12, 23 schizophrenia and, 400–404 substance use disorders and, 150–151, 179

522 Rituals, 146 Role performance, 177–178 Routine, 146

S Schizoid personality disorder, 72–74 Schizophrenia in adulthood, 45, 389–409 diathesis–stress model of, 393–394 epidemiology of, 390 experiential/environmental factors, 398–400 genetic factors and, 394–398, 395t phenotype and phenomenology of, 390–393 prevention perspective of, 407–409 risk factors and trait vulnerability markers and, 400–404 sequential onset of, 404–407 in childhood/adolescence, 363–380 behavioral markers of, 369–372 congenital factors, 364–374 flat affect and, 72–74 future directions regarding, 379– 380 genetic factors and, 373–374 intervention and, 378–379 neurodevelopmental perspective of, 374–378, 379f physical signs of, 365–369 prenatal and perinatal factors, 372–373 vulnerability factors related to, 27t diathesis–stress model of, 26 history of theory and research and, 49–50 lifespan and, 417–421 overview, 389, 500–501 personality traits and, 7 research methodology and, 30–31 vulnerability and, 21 Schizotypal personality disorder, 58–59, 67–68, 73. see also Personality disorders School functioning, 122, 128 School-based programs, 127 Secondary prevention, 408. see also Prevention interventions Selective preventive interventions, 408. see also Prevention interventions

Index Selective-serotonin reuptake inhibitors (SSRIs), 205. see also Pharmacotherapy Self, sense of exaggerated, 89–90 lack of, 86–89 negative sense of self, 85–86 personality disorders and, 84–90 Self-control strength theory, 181 Self-esteem, 433–434 Self-regulation depression and, 212–214 impulsivity and, 75 overview, 212 substance use disorders and, 177, 179, 181 Self-report measures, 195, 248, 458 Self-statements, 310 Self-talk, 317–318 Sensitization, 144, 266–267 Separation anxiety, 193 Separation anxiety disorder (SAD). see also Anxiety disorders course of, 294, 295 epidemiology of, 293 overview, 291 Serotonin system anxiety disorders and, 305 depression and, 202–203, 205, 207–208, 255, 257–258, 263 eating disorders and, 430, 462 overview, 500–501 Sexual abuse. see also Child maltreatment borderline personality disorder and, 88 depression and, 265–266 eating disorders and, 472 posttraumatic stress disorder and, 344 Sexual orientation, eating disorders and, 436–437, 466 Sibling relationships, depression and, 218–219 Sleep, depression and, 207–208 Smoking, 340 Smooth-pursuit eye movement (SPEM), 371–372, 418, 420 Social deviance model, 149 Social factors anxiety disorders and, 311–316, 359 childhood/adolescence, 27t, 28 depression and, 265, 284–285



Index

eating disorders and, 435–438, 444 substance use disorders and, 159–160, 177 Social information-processing skills, 67–68 Social phobia, 291, 292. see also Anxiety disorders Social skills, 219–221 Social support, 160, 216, 271–272 Social withdrawal, 81–82 Socialization effects, 177–178 Societal factors, 13–15 Socioeconomic status, 160, 300–301 Sociological model, 25 Specific phobia (SP), 292, 293, 295. see also Anxiety disorders Specific vulnerability hypothesis, 216 Stability, anxiety disorders and, 296–298 Strengthening Families program, 126–127 Stress depression and, 203–205, 263–267, 285 life events and trauma and, 215–216 neurobiological factors and, 203–205 overview, 500–501 role of, 9–10 schizophrenia and, 374–376, 392–393 substance use disorders and, 124 Stress exposure model, 216–217 Stress generation effect, 267, 271 Structured Clinical Interview for the DSM-IV Axis II Disorders (SCID-II), 64–65 Substance use disorders across the lifespan, 176–183 in adulthood, 40–41, 141–166 clinical characteristics, 144–146 conceptualizations, 142–144 intervention and, 161–166 models of, 148–150 prevalence of, 146–148 research on, 150–160 in childhood/adolescence, 113–129 age factors and, 115–117 depression and, 193 epidemiology of, 114–117 future directions regarding, 128–129 negative affect pathway and, 123–125 prevention and, 126–127 reinforcing effects and, 125–126 research and methodology, 117–123 treatment and, 127–129 overview, 40–41, 113, 142–146

523

Surgency. see Positive emotionality Symptoms, 249–250, 390–393, 405–406

T Temperament anxiety disorders and, 301–302, 315 depression and, 208–209, 213 eating disorders and, 431–432, 444, 489 emotion regulation and, 69–70 substance use disorders and, 121, 177 Tertiary prevention, 408. see also Prevention interventions Theoretical models adulthood and, 49–51 childhood/adolescence and, 24–30, 27t history of, 49–51 Thought disorder, 91 Threat attention, 307–311 Tobacco use. see also Substance use disorders distress tolerance and, 159 pharmacotherapy and, 165–166 posttraumatic stress disorder and, 157 prevalence of, 147 Tolerance, 144 Trait vulnerability markers, 400–404 Transactional hypothesis, 220 Trauma anxiety disorders and, 316 depression and, 214–217 posttraumatic stress disorder and, 342–347 Treatment. see also Interventions eating disorders and, 442–443, 476– 478 risk and, 11 substance use disorders and, 127–129 Tripartite model of anxiety and depression, 208 12-step programs, 164 Two-factor learning theory, 335

U Universal preventive interventions, 408. see also Prevention interventions

V Variable risk factors, 151. see also Risk factors Violence, emotion regulation and, 71

524 Vulnerability. see also Adulthood; Childhood/adolescence in adulthood, 39–52 in childhood/adolescence, 18–34 continuity and change in, 503–505 defining, 5–11, 23–24 environmental factors and, 505–506 features of, 5–11, 498–500 malleability of, 507–508 overview, 500–503, 508–509 psychopathology and, 15 rationale for the study of, 20–23, 46– 48

Index relationship between risk and resilience and, 11–12, 13f role of, 3–15 theory and research and, 24–33, 27t, 49–51 Vulnerability terminology perspectives, 150–151

W Weakest link hypothesis, 211 Weight cycling, 471–472 Weight gain, 474–475, 479–481 Withdrawal symptoms, 145–146, 165