International Review of Research in Mental Retardation, Volume 36

V O LU M E T H I RT Y S I X INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION Board of Associate Editors PH...

Author: Laraine Masters Glidden

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V O LU M E

T H I RT Y

S I X

INTERNATIONAL REVIEW OF

RESEARCH IN MENTAL RETARDATION

Board of Associate Editors

PHILIP DAVIDSON University of Rochester School of Medicine and Dentistry

ELISABETH DYKENS Vanderbilt University

MICHAEL GURALNICK University of Washington

RICHARD HASTINGS University of Wales, Bangor

LINDA HICKSON Columbia University

CONNIE KASARI University of California, Los Angeles

WILLIAM McILVANE E. K. Shriver Center

GLYNIS MURPHY University of Kent

TED NETTELBECK Adelaide University

MARSHA M. SELTZER University of Wisconsin-Madison

JAN WALLANDER Sociometrics Corporation

V O LU M E

T H I RT Y

S I X

INTERNATIONAL REVIEW OF

RESEARCH IN MENTAL RETARDATION Edited by

LARAINE MASTERS GLIDDEN Department of Psychology St. Mary’s College of Maryland St. Mary’s City, Maryland

AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier

Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 84 Theobald’s Road, London WC1X 8RR, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2008 Copyright ß 2008, Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-374476-0 ISSN: 0074-7750 For information on all Academic Press publications visit our website at books.elsevier.com Printed and bound in the United States of America 08 09 10 10 9 8 7 6 5 4 3 2 1

CONTENTS

Contributors Preface

ix xi

1. Newborn Screening for Intellectual Disability: Past, Present, and Future

1

Don Bailey 1. Introduction 2. Evolving Guidelines and Practices for Newborn Screening 3. Current Issues in Newborn Screening 4. The Nature of the Condition 5. Test Characteristics 6. Benefits From Screening 7. Summary and Future Directions References

2. Responsive Parenting: Closing the Learning Gap for Children with Early Developmental Problems

2 4 8 8 13 15 19 22

27

Susan H. Landry, Heather B. Taylor, Cathy Guttentag, and Karen E. Smith 1. 2. 3. 4. 5. 6.

Introduction School-Age Developmental Characteristics Shared Challenges for Effective Learning What is Responsive Parenting? What Supports Responsive Parenting? Evidence for the Specialized Support of Responsive Parenting for Core Deficits 7. Evidence from Longitudinal Studies for Closing the Learning Gap for At-risk Children 8. Evidence from Experimental Findings for Closing the Learning Gap 9. Summary and Conclusions, Implications and Future Directions References

28 30 31 36 38 39 44 45 50 54

v

vi

Contents

3. Trisomy 21: Causes and Consequences

61

Jeannie Visootsak and Stephanie L. Sherman 1. Introduction 2. Major Cause of DS: Meiotic Nondisjunction in Oocytes 3. Prevalence and Survival of Individuals with DS Throughout the Life Span 4. Etiology of DS-Associated Medical Disorders 5. Neurodevelopmental Outcomes of Comorbid Medical Conditions in DS 6. Psychiatric and Neurobehavioral Issues in DS 7. Summary References

4. Alzheimer’s Disease in Adults with Down Syndrome

61 64 72 77 82 87 89 90

103

Warren B. Zigman, Darlynne A. Devenny, Sharon J. Krinsky-McHale, Edmund C. Jenkins, Tiina K. Urv, Jerzy Wegiel, Nicole Schupf, and Wayne Silverman 1. Introduction 2. Down Syndrome/Alzheimer’s Disease Research Program References

104 108 135

5. Foolish Action in Adults with Intellectual Disabilities: The Forgotten Problem of Risk-Unawareness

147

Stephen Greenspan 1. Introduction 2. A Four-Factor Model of Foolish Action 3. Varieties of Foolish Acts Committed By Different Populations 4. Brain Damage and Foolish Action: FASD as an Exemplar 5. Research and Policy Implications 6. Conclusion References

6. Animal Models of Self-Injurious Behavior: Induction, Prevention, and Recovery

148 152 162 176 182 188 189

195

Stephen R. Schroeder, Pippa S. Loupe, and Richard E. Tessel 1. Introduction 2. Animal Models of Induction of SIB 3. Animal Models of Prevention of SIB 4. Animal Models of Recovery from SIB 5. Overall Summary and Future Directions References

196 199 209 210 220 224

Contents

7. Theoretical and Methodological Issues in Sibling Research

vii

233

J. Carolyn Graff, Susan Neely-Barnes, and Heather Smith 1. Introduction 2. Themes in Sibling Research 3. Theoretical Approach 4. Research Method 5. Frontiers and Directions for Sibling Research 6. Conclusion References

8. Understanding Individual Differences in Adaptation in Parents of Children with Intellectual Disabilities: A Risk and Resilience Perspective

234 235 240 245 265 269 271

281

Malin B. Olsson 1. Introduction 2. Risk and Protective Factors in the Field of Families with a Child with ID 3. Risk Factors 4. Protective Factors 5. Outcomes 6. Discussion 7. Conclusion References

9. ‘‘What do you Think if . . .’’: Using Vignettes to Study Attitudes Toward Adult Sibling Caregiving and Competence of Parents of Children with Disabilities

282 285 287 293 301 303 307 307

317

Brian M. Jobe and Laraine M. Glidden 1. Introduction 2. Topic 1: Young Adults’ Levels of Caregiving for Hypothetical Siblings 3. Topic 2: Stereotypic Views of Parental Competence and Family Expansion 4. Summary and General Discussion References Index Contents of Previous Volumes

318 320 326 331 337 343 351

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CONTRIBUTORS

Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Don Bailey (1) RTI International, Research Triangle Park, North Carolina 27709-2194 Darlynne A. Devenny (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Laraine M. Glidden (317) Center on Health and Education, Georgetown University, and Department of Psychology, St. Mary’s College of Maryland J. Carolyn Graff (233) University of Memphis, College of Nursing, Boiling Center for Developmental Disabilities, Memphis, Tennessee 38105 Stephen Greenspan (147) University of Colorado Health Sciences Center, Colorado 80045; Email: stephen. [email protected] Cathy Guttentag (27) University of Texas Health Science Center, Houston, Texas 77030 Edmund C. Jenkins (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Brian M. Jobe (317) University of Maryland, Baltimore, Maryland 21228; Email: [email protected] Sharon J. Krinsky-McHale (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Susan H. Landry (27) The University of Texas Health Science Center, Houston, Texas 77030 Pippa S. Loupe (195) Bureau of Child Research, University of Kansas, Dole Human Development Center, Lawrence, Kansas 66045-7555 Susan Neely-Barnes (233) University of Tennessee, College of Social Work, Memphis, Tennessee 38103 ix

x

Contributors

Malin B. Olsson (281) Department of Psychology, Go¨teborg University, Go¨teborg, Sweden Stephen R. Schroeder (195) Bureau of Child Research, University of Kansas, Dole Human Development Center, Lawrence, Kansas 66045-7555 Nicole Schupf (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Stephanie L. Sherman (61) Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia 30033 Wayne Silverman (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Heather Smith (233) University of North Carolina, North Carolina 27599 Karen E. Smith (27) University of Texas Medical Branch at Galveston, Houston, Texas 77030 Heather B. Taylor (27) University of Texas Health Science Center, Houston, Texas 77030 Richard E. Tessel (195) Bureau of Child Research, University of Kansas, Dole Human Development Center, Lawrence, Kansas 66045-7555 Tiina K. Urv (103) Mental Retardation & Developmental Disabilities Branch, National Institute of Child Health and Human Development, Bethesda, Maryland 20892 Jeannie Visootsak (61) Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia 30033 Jerzy Wegiel (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Warren B. Zigman (103) New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314

PREFACE

As you have come to expect in eclectic volumes of the International Review of Research in Mental Retardation, the range of focus in Volume 36 is broad. The empirical work described includes animal models and research as well as investigations with human participants. The core domains intersect with medical decision-making, intervention approaches, social psychology, and family issues. Two chapters focus on Trisomy 21/Down syndrome, although from quite different perspectives, and important theoretical issues are addressed in a number of chapters with intent sometimes to address the entire field of intellectual disabilities and other times a selected portion of it. As usual, both as editor and as reader, I owe a great deal to the individuals who provided expert review for these highly diverse original manuscripts. Collectively, they were able to span the breadth of the field of intellectual disability from its basic biological underpinnings to its applications for ameliorating learning problems. Three of these reviewers were members of the Board of Associate Editors and I am especially grateful to Mike Guralnick, Richard Hastings, and Linda Hickson for their continuing support in multiple ways, as well as to Elisabeth Dykens who coauthored a chapter in this volume. Listed in alphabetical order, the following additional reviewers provided timely and constructive comments: Rhonda Black, Monica Cuskelly, Bob Edgerton, Charlotte Hobbs, Rodney Howell, Jim Leffert, Mark Lewis, Gael Orsmond, Sonja Rasmussen, Curt Sandman, Davida Sears, Travis Thompson, Steve Warren, and Michael Watson. The first two chapters focus early in the lifespan. In Chapter 1, Don Bailey gives us a peek into the future as he anticipates the brave new world of newborn screening for intellectual disability. He cautions us that economic and cultural factors cannot be divorced from medical decisionmaking and that challenges lay ahead regardless of the course that is charted. Susan H. Landry, Heather Taylor, Cathy Guttentag, and Karen E. Smith address a different set of challenges in Chapter 2 on responsive parenting. They review the importance of the parental role in early development of children with spina bifida, Down syndrome, and very low birthweight. Their longitudinal research with children from this last group provides

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Preface

convincing evidence that risk can be ameliorated with effective environmental manipulations such as contingent responsiveness and rich verbal input. Jeannie Visootsak and Stephanie L. Sherman also focus on Trisomy 21 leading to Down syndrome. Their emphasis is on the causes of meiotic nondisjunction in oocytes, the most frequently occurring etiology of Trisomy 21, as well as how associated defects affect neurodevelopmental outcomes. Their emphasis is on children, but they do briefly address symptoms of dementia arising later in the lifespan, an excellent segue into Chapter 4 on Alzheimer’s disease in adults with Down syndrome by a research team that has been studying this condition for many years. Warren B. Zigman and his seven coauthors document that despite the elevated risk for Alzheimer’s disease faced by adults with Down syndrome, substantial variability in outcomes is part of the profile, and is interesting and important both for science and human services. Stephen Greenspan takes us on quite a different journey in Chapter 5 in which he develops and explains a new (but rooted in historical writings) theory of the core deficit in mental retardation/intellectual disability. Even the title—Foolish Action in Adults with Intellectual Disabilities: The Forgotten Problem of Risk-Unawareness—in intriguing, and its promise of provoking an examination of the meaning of mental retardation is fulfilled by the end of the chapter. You may not agree with everything that Steve Greenspan has written here, but you will, nonetheless, be glad that he has written it. In Chapter 6, Stephen R. Schroeder, Pippa S. Loupe, and Richard E. Tessel (deceased) review five decades of research on animal models of selfinjurious behavior (SIB), concluding that four models have been especially productive in inducing it. Some readers will be especially interested in the authors’ own 10-year program of research involving research for training from recovery from SIB, as it has important implications for treatment. In the next three chapters, the focus is on family. J. Carolyn Graff and her coauthors, Susan Neely-Barnes and Heather Smith (Chapter 7) and Malin Broberg Olsson (Chapter 8), review extensive research databases with an aim to understanding the themes and issues that have dominated their field. Siblings are in the forefront in Chapter 7, whereas parents are the primary interest in Chapter 8. Nonetheless, some of the core constructs, such as adaptation, risk, and resilience, and the factors that influence them are themes in both the chapters. My coauthored chapter with Brian M. Jobe is squarely in the tradition of the experimental psychology of intellectual disability. In taking this approach, we tackle two different domains of family—sibling caregiving and judged parent competence. We propose and (I hope) persuade that the use of vignettes to study the attitudes of people about disability issues has value both for the data it contributes to the field and also the didactic and training opportunities it affords.

Preface

xiii

Finally, writing this preface is a bittersweet task for me. This volume is the penultimate one for my editorship, and the last one that is eclectic and singly edited. After Volume 37, which I will coedit with Marsha Seltzer with Families as its theme, the Series Editorship will be assumed by Bob Hodapp of Vanderbilt University. Indeed, as I write this preface, Bob is developing Volume 38. Please contact him for information about the Series as it moves forward. He has some exciting plans and I am grateful to have him as my successor. To all the readers, regular or occasional, I thank you for your interest and urge you to continue your loyalty to the International Review of Research in Mental Retardation. LARAINE MASTERS GLIDDEN

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C H A P T E R

O N E

Newborn Screening for Intellectual Disability: Past, Present, and Future Don Bailey* Contents 2 4 8 8 13 15 19 21 22

1. Introduction 2. Evolving Guidelines and Practices for Newborn Screening 3. Current Issues in Newborn Screening 4. The Nature of the Condition 5. Test Characteristics 6. Benefits From Screening 7. Summary and Future Directions Acknowledgments References

Abstract Newborn screening began in the 1960s with a condition causing severe intellectual disability, phenylketonuria, a disease that could be remediated through a dietary change that prevented intellectual disability. Since then newborn screening has become a significant public health initiative offered in every birthing hospital in the United States, sometimes for more than 50 conditions. The landscape of newborn screening is changing rapidly, however, as a result of new gene discoveries, technological developments, advocacy efforts, and private market forces. Soon it will be possible to screen for many conditions causing intellectual disability, but for which there will be no immediate medical treatment, evoking issues related to the ethics of disclosing genetic information about ‘‘untreatable conditions’’ and the support systems that would be necessary to help families and children cope with this information. Fundamental questions have been asked about the likelihood of various costs and benefits of early identification, prompting a whole new set of demands for data on the efficacy of earlier psychosocial interventions and the timing of treatments. This

* RTI International, Research Triangle Park, North Carolina 27709–2194

International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00001-3

#

2008 Elsevier Inc. All rights reserved.

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Don Bailey

chapter reviews the history and current status of newborn screening for intellectual disability, envisions a likely future of possible genetic disclosure, and identifies research questions that will need to be answered to help inform public policy.

1. Introduction The history of newborn screening is well-known and has been described extensively in a number of publications (e.g., American Academy of Pediatrics Newborn Screening Task Force, 2000). Of special relevance to the International Review of Research in Mental Retardation is that the disease that prompted the development of newborn screening was phenylketonuria, a well-known cause of intellectual disability. Individuals with untreated PKU typically have moderate to severe intellectual disability. A dietary change can almost completely prevent intellectual disability from occurring, but to be effective, the altered diet must begin shortly after birth, since damage caused by untreated PKU is difficult to reverse. Unlike Down syndrome, the phenotype for PKU is not obvious at birth through symptoms or physical features, and can only reliably be detected for purposes of prevention through a diagnostic test. Robert Guthrie’s work in developing a technique using blood spots to cheaply and easily detect PKU made newborn screening for this condition technically possible, and subsequent research showed dramatic differences in IQ scores of individuals treated following early identification (e.g., Berry, O’Grady, Perlmutter, & Bofinger, 1979; Koch & de la Cruz, 1999). These powerful data set the stage for advocacy efforts that led to newborn screening for PKU. However, it took nearly a decade for screening to be established in every state, as the United States had not established a public health infrastructure for newborn screening, policies had not been set establishing criteria for selecting conditions to be screened, and concerns were expressed about both the specificity of the treatment and uncertainties about whether every identified child actually needed treatment (Watson, 2006). In the ensuing years, newborn screening has grown into a mature public health program in the United States and continues to expand. But this expansion has been variable across states due to variations in such factors as laboratory capabilities, financial resources, governmental leadership, and advocacy efforts. Until recently most states in the United States screened for fewer than 10 conditions. Intense lobbying by various advocacy groups, advances in screening technology, and a recent task force report issued under the auspice of the American College of Medical Genetics (Watson, Mann, Lloyd-Puryear, Rinaldo, & Howell, 2006) have led to a significant expansion of the number of conditions screened just in the last

Newborn Screening for Intellectual Disability

3

few years. Most states now screen for more than 40 conditions, and this number is likely to continue to increase over the next few years. Internationally, newborn screening programs vary widely by region. Most countries screen for many fewer conditions than does the United States (Bodamer, Hoffman, & Lindner, 2007; Borrajo, 2007; Padilla & Therrell, 2007; Saadallah & Rashed, 2007; Therrell & Adams, 2007). Cross-country differences are accounted for by a wide range of variables, including limited financial resources, differences in the incidence rate of selected conditions across countries, variable advocacy initiatives, and differences in cultural perspectives and values (Pollit, 2007). In some regions, there are countries that have no newborn screening program at all, or if they do, it focuses on only a few conditions and is not universal. For many developing countries, newborn screening may pale in comparison to much larger risk factors (e.g., stunting, inadequate cognitive stimulation, iodine deficiency, and iron deficiency anemia) that must be addressed to reduce adverse outcomes and avoid the loss of developmental potential in millions of young children worldwide (Engle et al., 2007; Walker et al., 2007). A recent commentary stated ‘‘Few things we do in preventive medicine have been as remarkably successful as has newborn screening’’ (Howell, 2006a, p. 229). Despite this glowing assessment, however, the continued expansion of newborn screening is a topic of much current debate. Historically this debate has pitted ‘‘advocates’’ (often parents of affected children whose condition could have been prevented or lessened had newborn screening been available) against a more conservative public health system that insists on strong evidence for proven benefit (reduced morbidity and mortality) in a cost-effective fashion. However, rapid advances in technology will likely lead to testing platforms in the next 5–10 years in which literally hundreds of conditions or gene variants could be screened cheaply and simultaneously, making the cost of adding a new condition irrelevant from a laboratory perspective. This likely scenario has led to renewed and intensified discussions about problematic ethical, legal, and social issues surrounding the disclosure of complex genetic information at birth (Bailey, Armstrong, Kemper, Skinner, & Warren, 2008; Botkin et al., 2006), and expanding conceptions of what constitutes ‘‘benefit’’ when determining whether to screen for a particular condition (Bailey, Skinner, & Warren, 2005; Bailey, Beskow, Davis, & Skinner, 2006; Grosse, Boyle, Kenneson, Khoury, & Wilfond, 2006). A 2004 review revealed 282 molecularly identified genes related to intellectual disability (Inlow & Restifo, 2004). More have subsequently been discovered, and the authors estimate that hundreds more mental retardation genes remain to be identified. Obviously, only a few of these conditions are currently included in newborn screening. As gene discovery and technological innovation proceed at a rapid pace, how do genetic conditions causing intellectual and developmental disabilities fit into

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newborn screening, both now and in the future? To answer this question, we begin by reviewing the evolving criteria for newborn screening over the past 50 years. Issues evoked in a possible ‘‘second-generation’’ of newborn screening are described and an aggressive research agenda is proposed to assure that expanded screening maximizes benefit and minimizes harm.

2. Evolving Guidelines and Practices for Newborn Screening Since the possibility of widespread genetic testing through programs such as newborn screening was first realized, several major organizations have formed committees and issued reports to guide decision-making about newborn screening. These include the World Health Organization, often referred to as the seminal work on this topic led by Wilson and Junger (1968), the National Academy of Sciences (Committee for the Study of Inborn Errors of Metabolism, 1975), the Institute of Medicine (Andrews, Fullarton, Holtzman, & Motulsky, 1994), the American Society of Human Genetics and the American College of Medical Genetics (ASHG/ACMG, 1995), the National Institutes of Health in partnership with the Department of Energy (Holtzman & Watson, 1997), and the American Academy of Pediatrics Newborn Screening Task Force (AAP, 2000). For the most part, these reports have been remarkably consistent in their recommendations. Newborn screening should be conducted for conditions that meet four core standards: (1) The condition must be a significant public health problem, one that has serious consequences for the infant’s physical health, development, or life itself, and occurs frequently enough in the population to warrant universal screening. (2) A screening test must be available that is economical, acceptable to parents, rapid, and very accurate, with virtually no false negatives (missing no children who actually have the condition) and only a small number of false positives (unnecessarily incurring the expense of follow-up testing and heightening anxiety for parents). (3) There must be a demonstrable benefit to the infant, almost always defined as a medical treatment or nutritional intervention that reduces morbidity and mortality associated with the condition. (4) A comprehensive system of services must be in place so that primary care providers and families get screening information in a timely fashion, families receive adequate information and support, and appropriate treatments and follow-up services are available. Despite these standards, however, states vary widely in the conditions actually screened, for several reasons. From the beginning, newborn screening was determined to be a state, not federal, responsibility. Each state operates an independent newborn screening program through its

Newborn Screening for Intellectual Disability

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department of health, often guided by an advisory committee. Decisions about which conditions to include are entirely the responsibility of states, and therefore much variability has been due to state-by-state variations in laboratory capacity, advocacy efforts, or professional initiatives. As new conditions were discovered, new treatments developed, and new technologies created, cross-state discrepancies became more obvious. To address this problem, in 2000, the March of Dimes launched a national campaign, mobilizing local chapters and volunteers to advocate that each U.S. state and territory screen all infants for a core set of 10 conditions: PKU, congenital hypothyroidism, congenital adrenal hyperplasia, biotinidase deficiency, maple syrup urine disease, galactosemia, homocystinuria, sickle cell disease, medium-chain acyl-CoA dehydrogenase (MCAD) deficiency, and hearing impairment (Howse, Weiss, & Green, 2006). This campaign was buttressed by a simultaneous call from the American Academy of Pediatrics Newborn Screening Task Force (2000) for a national agenda on state newborn screening programs and a subsequent report from the U.S. General Accounting Office (2003) highlighting cross-state discrepancies in screening and urging action to insure equity in access to comparable screening tests across the country. In 2003, the Health Resources and Services Administration in the U.S. Department of Health and Human Services established a Secretary’s Advisory Committee on Heritable Disorders and Genetic Diseases in Newborns and Children to advise the Secretary of Health regarding newborn screening policy and practice. But almost as soon as these efforts had begun, other forces began pushing for even greater expansion, a movement catalyzed by the introduction of tandem mass spectrometry (MS/MS) as the technology of choice for newborn screening (Materin & Rinaldo, 2003). MS/MS dramatically expanded the number of disorders that could rapidly be detected in a single blood spot, with great precision and cheaply. In fact, the cost of detecting one condition was essentially the same as detecting multiple conditions. As states began to acquire tandem mass equipment or have access to regional labs with MS/MS capacity, they quickly faced important decisions about how to report MS/MS results, as some detected conditions did not meet the traditional criteria for newborn screening (i.e., no treatment available). Since the equipment is expensive and not every state could afford it, for several years MS/MS actually increased cross-state discrepancies in the number of conditions screened. But it also provided advocacy groups further ammunition to push for standardized expanded screening across all states. Since the authority to determine screened conditions rests with states, federal agencies faced a fundamental dilemma: How to support expansion and standardization of screening in the absence of any mechanism for requiring it. To address this issue, the Maternal and Child Health Bureau of the Health Resources and Services Administration funded the American College of Medical Genetics to convene experts and reach consensus

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on: (1) an expanded set of standards for deciding which conditions should be included in newborn screening and (2) a uniform screening panel based on current best knowledge about a set of candidate conditions. A scoring system for evaluating conditions was developed, and nearly 300 experts and other stakeholders were invited to use the system to evaluate one or more of 78 potential conditions for screening, resulting in nearly 4,000 ratings (Watson et al., 2006). As a result of these efforts, the committee recommended that all states screen for a core panel of 29 conditions for which there is an accurate screening test and strong agreement on the overall benefits of screening. The committee also recommended 25 additional ‘‘secondary targets,’’ conditions for which there was less agreement about the desirability of screening (e.g., very rare conditions or those for which there is no current treatment), but which would necessarily be identified when using techniques such as MS/MS to identify the 29 core conditions. The scoring system developed by the expert group to evaluate conditions for newborn screening is displayed in Fig. 1.1. Fourteen categories are proposed with scoring criteria for each. Some items are given more weight than others, based on the committee’s evaluation of their relative importance. The maximum score a condition could be rated is 2,100 points. Interestingly, no disease or condition received a perfect score. The highest mean score was assigned to MCAD deficiency, with a score of 1,799. MCAD is an autosomal recessive disease that affects the body’s ability to metabolize fat. Undetected, MCAD can result in death (30–50% death rate) if a child goes for even a relatively short period of time without eating (over 10–12 h), as might occur when the child has some other illness. The main treatment is to avoid fasting and aggressively treat any illnesses. Other conditions receiving high scores include congenital hypothyroidism (loss of thyroid function that leads to intellectual impairment, treatable by thyroxine supplements; score of 1,718), PKU (1,663), biotinidase deficiency (a condition in which the body is unable to reuse or recycle the vitamin biotin, resulting in delays and physical impairments, treatable by a form of biotin that does not bind to protein or other molecules; score of 1,542), and sickle cell anemia (1,533). Neonatal hyperbilirubinemia also received a high score (1,584) but was not recommended for screening due to lack of a test. The scoring system, expert ratings, and full recommendations were published in a special supplement to Genetics in Medicine (Watson et al., 2006). In the remainder of this chapter, these components are collectively referred to as the ACMG report. The scoring system, which was developed by a subcommittee known as the Newborn Screening Conditions and Criteria Work Group, is referred to as the Newborn Screening Condition Evaluation Tool. The 29 conditions recommended for newborn screening are referred to as the Core Panel. The conditions recommended as ‘‘reportout’’ conditions (those that do not fully meet the standards for newborn

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Newborn Screening for Intellectual Disability

CRITERIA

CATEGORIES

SCORE >1:5,000 >1:25,000

Incidence of condition

>1:50,000 >1:75,000 <1:100,000 Never

Sign & Symptoms clinically identifiable in the first 48 hours

<25% of cases <50% of cases <75% of cases Always Profound

Burden of disease (Natural Hx if untreated)

Severe Moderate Mild Minimal

Does a sensitive AND specific screening test currently exist?

YES NO Doable in neonatal blood spots OR by a simple, in-nursery physical method High throughput (>200/day/FTE)

Test characteristics (Yes = apply score; No = zero)

Overall analytical cost <1$ per test per condition Multiple analytes relevant to one condition are detected in same run Other conditions identified by same analytes Multiple conditions detected by same test (multiplex platform) Treatment exists and is widely available in most communities

Availability of treatment

Treatment exists but availability is limited No treatment available or necessary

Cost of treatment

Inexpensive Expensive (>$50,000/patient/year) To prevent ALL negative consequences

Potential efficacy of existing treatment

To prevent MOST negative consequences To prevent SOME negative consequences Treatment efficacy not proven

Benefits of early intervention (INDIVIDUAL OUTCOME) Benefits of early identification (FAMILY & SOCIETY)

Clear scientific evidence that early intervention resulting from screening optimizes outcome Some scientific evidence that early intervention resulting from screening optimizes outcome No scientific evidence that early intervention resulting from screening optimizes outcome

Early identification provides clear benefits to family and society (education, understanding prevalence and natural history, cost effectiveness) Early identification provides some benefits to family and society No evidence of benefits

Early diagnosis and treatment prevent mortality Availability of diagnostic confirmation

YES NO Providers of diagnostic confirmation are widely available Limited availability of providers of diagnostic confirmation Diagnostic confirmation is available only in a few centers Providers of acute management are widely available

Acute management

Limited availability of providers of acute management Acute management is available only in a few centers Management at the primary care or family level

Simplicity of therapy

Requires periodic involvement of a specialist Requires regular involvement of a specialist Max score

100 75 50 25 0 100 75 50 25 0 100 75 50 25 0 200 0 100 50 50 50 50 200 50 25 0 50 0 200 100 50 0 200 100 0 100 50 0 100 0 100 50 0 100 50 0 200 100 0 2100

Figure 1.1 The Newborn Screening Condition Evaluation Tool. Reprinted with permission, American College of Medical Genetics.

screening but should be reported since they are detected when testing for the Core Panel) are referred to as the Secondary Panel. Collectively these efforts have resulted in dramatic changes in the number of conditions screened by states, as evidenced in Fig. 1.2. In 2001, most states screened for fewer than 10 conditions. By 2007, most states were screening for more than 40 conditions, and the numbers change monthly. The National Newborn Screening and Genetics Resource Center

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40

Number of states

35

2001 2005 2007

30 25 20 15 10 5 0

<10

<20

<40 <50 <30 Number of disorders screened

≥50

Figure 1.2 Number of disorders included in state-mandated newborn screening programs by year. (Figure created from data published online by the National Newborn Screening and Genetics Resource Center: http://genes-r-us.uthscsa.edu/nbsdisorders.pdf).

maintains an updated website funded by the Maternal and Child Health Bureau listing the status of newborn screening for each state and for each condition screened: http://genes-r-us.uthscsa.edu/nbsdisorders.pdf.

3. Current Issues in Newborn Screening As described earlier, the criteria for making decisions about newborn screening have remained relatively consistent for the past 30 years. However, in each of the major domains, significant changes are underway that challenge these criteria. This section addresses three sets of issues that are now under intense discussion: the nature of the condition, characteristics of the screening test, and benefits from screening. Historical perspectives on each are reviewed and examples of current or potential controversies are described.

4. The Nature of the Condition As depicted in the Newborn Screening Condition Evaluation Tool (Fig. 1.1), three features of a disease or condition traditionally have been considered when evaluating screening and these features remain at the core of the recent ACMG report: incidence rate, clinically obvious phenotype, and disease burden. Incidence rate. It is commonly accepted that screening should only be done for conditions that cross a threshold of frequency of occurrence in the

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general population, on the assumption that it would not be a wise investment of limited public resources to screen for extremely rare conditions. Before the ACMG report, there were no published guidelines as to what this threshold might be. The Newborn Screening Condition Evaluation Tool gives maximum credit (100 points) if the incidence rate is greater than 1 per 5,000 births. No points are given if the incidence rate is less than 1 per 100,000 births. However, an examination of the Core Panel conditions highlights challenges in using the incidence rate criterion. First, the report notes that for many of the conditions, the incidence rate is either unknown or there was significant disagreement among raters regarding incidence. This will be an inevitable problem with newly discovered conditions but often is the case with any disease, especially those that are relatively rare. Since it is virtually impossible to do systematic, population-based studies of the incidence of each and every condition, incidence rates often reflect the accumulated reports of identified cases over time, but this can underestimate incidence since many cases may be missed, and one or two cases could have a significant effect on estimates of rare conditions. For example, in a state with 100,000 births per year, the difference between 1 versus 2 identified children dramatically changes the estimated rate of occurrence from 1:100,000 to 1:50,000. Second, within the Core Panel there is wide variability in incidence rates of the recommended conditions, and many are rare. Twelve of the recommended conditions occur in less than 1 per 100,000 births and thus received the lowest rating possible for incidence rate. Only 20 cases of trifunctional protein deficiency and fewer than 50 cases of beta-ketothiolase deficiency have been reported in the literature, yet the report recommends that all states screen for these conditions. Why? Because the conditions can be identified by MS/MS (thus incurring no additional cost) and because treatments are available to prevent some of the negative consequences of these conditions. Introduction of MS/MS technology has significantly reduced the importance of incidence rate as a screening criterion. Evolving technologies such as automated fluorometric tests, microarray analyses, DNA testing, or the ‘‘ $1,000 genome’’ (the National Human Genome Research Institute is currently soliciting grant applications to develop novel technologies that will enable extremely low-cost DNA sequencing of a mammalian-sized genome for $1,000) will soon make incidence rate an irrelevant criterion. The situation is further complicated when incidence rates vary by ethnicity or country of origin, as in the case of selectively higher rates of diseases such as sickle cell anemia (African Americans), 3-hydroxy 3-methyl glutaric aciduria (Saudi Arabia), and glutaric acidemia type I (higher carrier frequency in Old Order Amish). Variable incidence rates force complicated decisions, such as whether to offer sickle cell screening in a state with a very small African American population or whether to selectively offer screening

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to families based on ethnicity or country of origin. Unfortunately, most diseases are not exclusive to one group, and limiting screening would almost certainly mean that some children would be missed. A final consideration regarding incidence rate is the opposite question of what is typically asked: What if screening identified very large numbers of individuals? A clear example of this would happen if newborn screening were conducted for fragile X syndrome (FXS) (the most common inherited cause of intellectual disability) using a screening test that would also detect carrier status. If current estimates of female carrier status are correct—about 1:257 women—a state such as North Carolina with 60,000 female births per year would identify more than 230 carrier females per year. Their parents and likely their extended family members will need extensive counseling, and state capacity to provide this service is likely to be limited. Incidence rate will continue to be a consideration in newborn screening. In some respects, its importance will diminish with the emergence of new technologies that make the cost of screening for rare conditions irrelevant. New issues will arise as screening identifies rare conditions requiring very expensive treatment in specialized clinics, and will be especially contentious, if the treatments are only partially effective. A very different set of issues will arise if screening identifies large numbers of individuals with gene variants, and will necessitate wide-spread and fundamental changes in the nature of medical practice, information systems, and family supports. Clinically obvious phenotype. A second criterion of the condition addressed in the ACMG (Fig. 1.1) report is whether signs and symptoms of the disease are clinically identifiable in the first 48 h. Experts rated most conditions in both the Core Panel (68%) and the Secondary Panel (75%) as almost never identifiable in the first 48 h through clinical features, and in almost all other cases experts rated the condition as clinically identifiable in less than 25% of the cases. The only exception was congenital adrenal hyperplasia, rated as identifiable in less than 50% of the cases, primarily because males are typically not detected (females can be detected through ambiguous genitalia). The clinically obvious phenotype criterion is inextricably linked to treatment benefit since some conditions must be treated quickly to prevent damage or death. An example of a condition causing intellectual disability that does not meet these criteria is Down syndrome. Almost all cases of Down syndrome are clinically identifiable within the first 48 h. This fact, coupled with the fact that there is no time-sensitive treatment that could reverse or prevent the effects of Down syndrome (as is the case with PKU) means that newborn screening for Down syndrome is not under consideration. Consequences of the condition. A fundamental tenet of newborn screening is that screening must only be conducted for conditions that represent significant health consequences for the infant and for which early treatment is necessary. But what constitutes a significant health problem? The ACMG

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report defined consequences in terms of ‘‘burden’’ of the disease if untreated; 100 points were allocated to disease burden, with a range from profound (100) to minimal (0). No definitions were given for ratings, and experts were allowed to make their own interpretations of the meanings of profound, severe, moderate, mild, and minimal. Of the 29 conditions in the Core Panel, 21 (72%) were rated as having profound impact on the individual. With one exception (3-methylcrotonylglycinuria), the remaining conditions in the Core Panel were rated as having severe impact. 3-Methylcrotonylglycinuria was rated moderate because not all individuals with the analytes associated with the condition display any clinical symptoms. Since this condition is identified through MS/MS, it is included as a primary target but the report indicates that a primary reason for this decision is that by so doing it would allow for long-term follow-up that could lead to a better understanding of the range of clinical manifestations of the condition. There is a wider range of severity levels assigned to the secondary targets, with 6 rated as having profound impact, 9 severe, 7 moderate, and 2 mild. Historically, conditions included in newborn screening have been those that result in a level of disease or a consequence that almost anyone would agree to be significant. Most of the conditions in the Core Panel result in severe intellectual or motor impairment, and several can result in death if not treated. The inclusion of conditions with mild impact in newborn screening currently occurs because these conditions are necessarily identified when screening for those with more severe impact. But similar to the situation in which considerations regarding incidence rate are changing, future technologies inevitably will allow screening for a wider array of conditions and characteristics that have milder consequences or for which the consequences will be uncertain (McGuire, Cho, McGuire, & Caulfield, 2007). This will force a reconsideration of the ‘‘line’’ across which screening currently does not cross, as evidenced by several examples. One scenario involves conditions for which the phenotype or clinical presentation is highly variable, including mild or asymptomatic cases. In the case of FXS, almost all males with the full mutation will ultimately have moderate to severe intellectual disability. Subsets of this population (probably 25–40%) will also have autism, seizures, or self-injurious behavior, although these do not necessarily co-occur. Some cases of ‘‘high functioning’’ individuals have been reported (e.g., Han, Powell, Phalin, & Chehab, 2006). For females, the variability is even greater, as some could be severely delayed, whereas others may have normal intellectual ability. The core problem is that none of this variability can be predicted based on genetic data. Botkin (2005) argues that technology could lead to a scenario in which a gene mutation or other variant is discovered through screening, but only some of the individuals identified will need or benefit from treatment, and some could actually be harmed by receiving unnecessary treatment. We address treatment issues later in this chapter, but it is worth noting here that although

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there is an explicit assumption that only the most severe cases should be identified through screening, it has been argued for years that mild cases of intellectual impairment may be the most important to identify early because those may be the most amenable to significant changes in long-term developmental outcomes or perhaps the prevention of intellectual disability (e.g., Ramey & Ramey, 1999). A recent study found that mothers of children with borderline intelligence exhibited less-positive and less-sensitive parenting than did mothers of typically developing children or mothers of children with more significant developmental disabilities (Fenning, Baker, Baker, & Crnic, 2007). The data were collected when the children were 5 years of age and none identified as a result of newborn screening. Nonetheless, these findings suggest that newborn screening could identify a group of borderline children at high risk for negative parenting styles that might be preventable through early detection and family support. Conditions for which a genetic variant or set of variants increases risk for a deleterious outcome, further exemplify these issues. For example, the BRCA-1 gene conveys a higher risk for breast cancer, but even the majority of individuals with this gene variant do not get breast cancer. Research has either identified genes associated with various developmental disabilities or has shown that conditions such as specific reading disabilities, autism, schizophrenia, and attention disorders have a high degree of heritability (Cook, 1998; DeFries & Alarcon, 1996; Plomin & McGuffin, 2003). If newborn screening could tell parents about increased risk for such conditions, what would be the implications for treatment, possible stigmatization, or the effects on parenting style (e.g., hyperanxiety or hypervigilance)? Would disclosing such information be helpful or harmful? Would individuals or parents want to know this information? These issues will require comprehensive models for thinking about genetic risk and how families can be supported in their efforts to understand and make appropriate use of information received (Rolland & Williams, 2005). A related issue regards the potential detection of carriers of a disease or condition, as will certainly be the case in the future, especially if newborn screening moves to DNA-based technologies or incorporates multi-tier testing to improve accuracy. This point was demonstrated in a study of newborn screening for cystic fibrosis (Comeau et al., 2004). The authors used a two-tiered screening system (two different tests, administered sequentially) to test for the multiple mutations that can cause cystic fibrosis. The process resulted in much greater predictive accuracy for CF detection but also increased the likelihood of detecting infants who are carriers of CF. Likewise, depending on the test used, newborn screening for FXS could detect children who are carriers of fragile X. The disclosure of infant carrier status could provide important information about the carrier status of parents, and knowledge of reproductive risk would help parents make informed decisions about whether to have additional children. And for

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some conditions, carriers may have late-onset characteristics that could possibly be prevented or for which adaptations could be developed, if known. For example, 20% of female carriers of FXS will develop primary ovarian insufficiency, possibly as early as their late teens or early 20s. Knowing this would be useful information when a woman is making decisions about when to have children. Male carriers of fragile X have an increased risk of developing FXTAS, a debilitating tremor/ataxia syndrome that can begin in middle age. Knowledge of this risk could heighten vigilance in symptom development so that new treatments could be tested for their efficacy. But none of this information is necessary during the early childhood period. The Institute of Medicine report on genetic testing (Andrews et al., 1994) clearly articulates the dilemmas posed by the detection of carrier status, using sickle cell anemia as an example. Carrier status alone does not meet the ‘‘burden if untreated’’ standard, as it typically does not confer a health problem on the infant, and it is possible that stigmatization could result by labeling children early. As a result, testing for carrier status is currently not recommended (American Academy of Pediatrics Committee on Bioethics, 2001). But surveys typically show that parents want information about their child’s genetic makeup, especially if that information also has implications for them and their reproductive decisions (Anido, Carlson, Taft, & Sherman, 2005; Skinner, Sparkman, & Bailey, 2003), although clearly some women do not fully understand the implications of carrier status and some are ambivalent about the value of this information (Anido et al., 2005; Anido, Carlson, & Sherman, 2007). In the near future, carrier detection will not be a primary goal of newborn screening, but rather will occur as a by-product of testing for affected children. If detected through screening, carrier status would be disclosed to parents under the general principal that it would be unethical to withhold such information.

5. Test Characteristics A diagnostic test is one that determines whether an individual has a particular disease or condition. Diagnostic confirmation may require specialized testing and be expensive, but should be definitive. A screening test differs from a diagnostic test in that its primary purpose is to identify from a large pool of individuals those who have a high probability of having a disease or condition, and who would be referred for diagnostic follow-up and confirmation. Thus newborn screening does not diagnose disease, but rather identifies individuals for further testing. The availability of an accurate and cost-effective screening test is an obvious central prerequisite to newborn screening. More than 4,000,000

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babies are born in the United States annually, so cost of screening is an important consideration. The ACMG evaluation criteria used $1.00 per test per condition as the metric against which a screening test should be evaluated, but obviously the cost of screening must be weighed against the benefits. A more expensive test may be justified if it results in significant reduction of cost to individuals or to society. In the early days of screening, separate tests were used for each condition. The advent of MS/MS technology made it possible to screen for multiple conditions using the same test. Newer technologies such as high throughput oligonucleotide microarrays and DNA-based testing will further enhance the capacity to test hundreds or even thousands of genes and gene mutations in parallel, yielding both promise for more efficient disease identification (Hacia & Collins, 1999) and concerns about a wide array of issues such as consent, privacy, clinical utility, and stigmatization (e.g., Grody, 2003). Ideally, a test should have no false negatives (never missing children who actually have the disease) and very few false positives (rarely identifying children as possibly having the disease who in reality do not). Although newborn screening, historically, has been concerned about both types of errors, concern about false negatives has been the primary consideration, due to the potentially dire consequences of missing a person with a serious condition that needs immediate treatment. An ongoing analysis of proficiency testing errors in U.S. newborn screening laboratories suggests very low rates of false negatives for all screened conditions, the highest occurring for cystic fibrosis (2.6%), congenital hypothyroidism (2.4%), and congenital adrenal hyperplasia (2.2%) (Therrell & Hannon, 2006). Ideally a screening test should differentiate those individuals who need immediate treatment from those who do not, but this is not always possible. Kemper et al. (in press) reviewed the scientific evidence in support of newborn screening for Pompe disease, a lysosomal storage disorder that leads to muscle weakness, organ damage, and death. A treatment has recently become available that leads to improved outcomes, but newborn screening cannot distinguish between infantile Pompe disease (for which it is known that early enzyme therapy is necessary) and a late-onset form of the disease (which can be just as severe but for which timing of treatments is currently unknown, including any risks associated with early treatment of a late-onset condition). Concern has been expressed that with the increased number of conditions being tested through MS/MS, there will be more false-positive results (Howell, 2006; Tarini, Christakis, & Welch, 2006). The immediate and most obvious effects of false positives relate to cost, as each false-positive screen means that a more expensive diagnostic follow-up will be conducted unnecessarily. But some research has indicated that false positives can result in significant stress for some families (Gurian, Kinnamon, Henry, & Waisbren, 2006; Hewlett & Waisbren, 2006), stress that could be avoided

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with a more accurate test. And Howell (2006b) suggests that too many false positives could reduce the urgency felt by practitioners as a result of a positive screen, resulting in possibly deleterious results for the infant screened.

6. Benefits From Screening ‘‘Of all the criteria that a screening test should fulfill, the ability to treat the condition adequately, when discovered, is perhaps the most important’’ (Wilson & Junger, 1968, p. 27). This 40-year-old exhortation from the first major report on genetic testing issued by the World Health Organization remains a guiding principle for newborn screening today. The essential argument, one that has been reinforced in every subsequent task force report (AAP, 2000; Andrews et al., 1994; ASHG/ACMG, 1995; Committee for the Study of Inborn Errors of Metabolism, 1975; Holtzman & Watson, 1997; Watson et al., 2006), is that screening must result in benefit to the infant by reducing morbidity or mortality associated with the condition. The ACMG report (Watson et al., 2006) gives considerable weight to treatment and the possibility of benefit, as exemplified in Fig. 1.1. Of the 2,100 total points, 1,000 are directly related to treatment efficacy and availability. Factors rated include availability and cost of treatment, potential efficacy to prevent negative consequences, including mortality, whether scientific evidence exists showing that early intervention resulting from screening optimizes outcome, the level of specialization required to provide the treatment, and the availability of providers of acute management. Although benefit is considered fundamental to newborn screening, a close examination reveals a more complex set of issues that are rapidly changing. My immersion into these issues began when my colleagues and I published a series of studies on how families discovered that their child had FXS (Bailey, Skinner, Hatton, & Roberts, 2000; Bailey, Skinner, & Sparkman, 2003). These studies showed that parents often experienced an extended ‘‘diagnostic odyssey,’’ frequently lasting two or more years until finally FXS was diagnosed. Numerous costs were associated with this journey: Parents were frustrated with the health care system, many experienced doubts about their parenting ability (seeing their child not develop normally but being told by professionals not to worry), their children did not have access to timely early intervention services, and many families had additional children with FXS without knowing their own status as carriers. We viewed these factors as ‘‘costs’’ associated with late identification, and explored a variety of strategies for earlier identification. We found that males with FXS often demonstrated developmental delays and abnormalities during the first year of life that could be detected

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through parent observations (Roberts, Hatton, & Bailey, 2001), developmental screening (Mirrett, Bailey, Roberts, & Hatton, 2004), and microanalysis of behaviors seen in videotapes of everyday activities (Baranek et al., 2005). But although delays are evident, the lack of an obvious FX phenotype during the early years, the milder phenotype exhibited by girls, and the challenges associated with instituting regular developmental screening in pediatric practice (Sices, Feudtner, McLaughlin, Drotar, & Williams, 2003) led us to recommend that the best way to facilitate early identification of FXS would be through newborn screening (Bailey, 2004; Bailey, Roberts, Mirrett, & Hatton, 2001). We argued that newborn screening would eliminate the aforementioned costs—families would avoid the prolonged frustrations and self-doubts associated with the search for a diagnosis, children would have access to early intervention programs, and families would know their carrier status and thus be able to assess reproductive risk and make informed decisions about future children. It should also be more equitable in that ethnicity or economic status should not affect timing of identification and the gap in age of identification of affected girls in comparison to affected boys (Bailey et al., 2003) would be eliminated. Not having worked in the world of newborn screening, these arguments seemed logical to us and constituted a clear set of benefits deriving from early identification. We thus were surprised when challenged by some members of the public health community who argued that since there was no medical treatment for fragile X, screening could not be justified. These views stood in sharp contrast to our interviews with parents, who strongly endorsed newborn screening for FXS (Skinner et al., 2003) and our own views about the value of early intervention, both for children and for families. It soon became clear to us that psycho-social interventions such as those provided through early intervention programs did not meet the standards held by some individuals for ‘‘benefit,’’ and there was skepticism about whether early intervention in general had been shown to be effective for children with intellectual disabilities. Furthermore, since there has never been a study (much less a randomized trial) of the efficacy of early intervention for children with FXS or data showing that earlier intervention produces better longitudinal outcomes for children than does later services, a decision to screen newborns for FX would not be evidence-based. These arguments led us to write two papers in which we directly addressed the meaning and complexity of benefit in the context of newborn screening. In the first paper (Bailey et al., 2005), we suggested that it is time to reframe presumptive benefit of newborn screening for intellectual and developmental disabilities, moving beyond the standard set by PKU (a medical treatment that essentially prevented all negative consequences of the condition) to a more expansive set of benefits that are both possible and justifiable, even in the absence of a medical treatment. We argued that newborn screening would have direct benefits for children and families,

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in that it would: (a) allow for optimization of the infant’s home environment and provide access to early intervention programs that have been shown to be generally effective in enhancing developmental outcomes (Guralnick, 2005) and are viewed as positive and effective by families (Bailey, Hebbeler, Scarborough, Spiker, & Mallik, 2004; Bailey, Nelson, Hebbeler, & Spiker, 2007); (b) provide access to support services and information that parents consider helpful and could help promote positive outcomes for families (Bailey, Hebbeler, et al., 2005; Bailey, Bruder, et al., 2006); (c) be consistent with extensive research on consumer preferences for information about their child’s genetic risk; and (d) provide a range of other societal benefits. For example, newborn screening could provide a better estimate of the true incidence of a condition (because screening is population-based, not selective), allow for studies of early development not possible when children are identified later, and would make possible studies of the efficacy of early intervention, therapy, or even medical treatments as they become available. We included a caveat in this paper, assuming that any screening test used would be accurate, accessible to all, and voluntary, with an adequate system for follow-up and support for families. In the second paper (Bailey et al., 2006), we conducted a historical analysis of changing perspectives on the benefits of newborn screening by reviewing the various task force reports issued in the last 40 years, examined how the conditions rated by the ACMG task force fared with respect to benefit, and analyzed how benefit was reflected in public comments submitted in response to the ACMG report. From this paper emerged several reflections on the changing concepts of benefit:

The potential for benefit is necessary to justify screening, but almost all (95%) of the 78 conditions reviewed by experts were rated as having a treatment that could prevent at least some negative consequences for the child and all (100%) could result in at least some family and societal benefits. Thus, it appears that once a screening test becomes available and at least some form of safe and partially effective medical treatment exists, a condition can be considered for screening. Clearly there is no agreed-upon threshold for ‘‘meaningful’’ benefit. Most discussions of benefit focus on improved physical health of the infant via medical treatment, although ‘‘treatment’’ and ‘‘benefit’’ have often been used interchangeably in the literature. These two concepts are related but distinct. Interestingly, however, newborn screening rarely prevents all negative consequences of a condition. Figure 1.3 summarizes the ratings assigned to the 78 conditions, and the most frequent rating across all groups was that newborn screening could prevent ‘‘some’’ of the negative consequences of the condition. Only four of the Core Panel conditions were rated as having treatments that prevented almost all negative consequences:

Percentage of conditions

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100 90 80 70 60 50 40 30 20 10 0 Core panel Prevent ALL

Secondary targets

No test

Prevent MOST

Not All conditions recommended

Prevent SOME

Treatment Unproven

Percentage of conditions

Figure 1.3 Summary of ratings of 78 conditions with respect to the potential efficacy of existing treatments. (Figure created from tables presented in Watson et al., 2006.) 100 90 80 70 60 50 40 30 20 10 0 Core panel

Secondary targets

CLEAR benefits

No test

Not recommended

SOME benefits

All conditions

NO benefits

Figure 1.4 Summary of ratings of 78 conditions with respect to benefits of early identification for family and society. (Figure created from tables presented in Watson et al., 2006.)

congenital hypothyroidism, biotinidase deficiency, PKU, and MCAD. Thus, the PKU model is not a realistic one nor is it the typical standard for newborn screening. Screening for all conditions has perceived benefits for family and society, as depicted in Fig. 1.4. Although all of the earlier task force reports acknowledge the possibility of these benefits, most considered such benefits as additive to infant benefits rather than a stand-alone justification for screening. The ACMG report was the first to include such benefits in a rating system, although the maximum number of points possible for such benefits was 100.

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Stakeholders differ in their expectations for and definitions of benefit. Historically, professionals have tended to insist on improved health outcomes while parents and advocacy groups consider other factors; for some, information about a condition would constitute sufficient benefit, regardless of treatment potential. Clearly benefit is a multifaceted construct that has both objective and subjective components.

These reviews suggest the critical importance of benefit but also show that benefit can only be one part of the decision-making process.

7. Summary and Future Directions In the 40 years since Guthrie developed a blood spot test for PKU, the United States and most affluent countries have developed large-scale public health programs to screen for a range of disorders that have serious health consequences for infants. Although the concept of critical periods has rarely been invoked as the basis for newborn screening (Bailey & Gariepy, 2008), this argument could easily be made, as screening has typically been limited to conditions that require treatment during the first few days or weeks of life to be effective and to prevent or reduce irreparable damage. Grosse et al. (2006) characterize these programs as resting on a ‘‘public health emergency’’ model. As a result, changes to newborn screening systems have generally been incremental, with new conditions being added slowly and with deliberation, contingent on the availability of treatments that are needed during the first weeks and months of life. Conditions causing intellectual and developmental disabilities are included in newborn screening, but only if they have medical treatments. Historically, the availability of educational, psychological, or therapeutic (i.e., speech therapy, physical therapy) interventions have not been considered sufficient benefit to warrant screening, despite 30 years of federal legislation acknowledging the importance of early intervention for children with or at risk for developmental disabilities, or those with established conditions likely to lead to disability (Bailey, 2000; Bailey, Aytch, Odom, Symons, & Wolery, 1999). I predict that we are nearing the end of this first generation of newborn screening and will soon enter a second generation, one that will differ dramatically from what is currently offered. New technologies will make it possible to screen for hundreds of gene variants, many of which are related to intellectual and developmental disabilities. Most will be rare and will not have medical treatments likely to substantially enhance developmental outcomes. For many gene variants, there may be a range of phenotypic outcomes, from severe to nonexistent. Genomics will increasingly be

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integrated into a new era of personalized medicine. As Khoury, Gwinn, Burke, Bowen, and Zimmern (2007) suggest, this could exacerbate current schisms between medicine (which focuses on individual cases) and public health (which takes a population-based approach to prevention), but could also force a movement toward what the authors refer to as a shared ‘‘population health’’ perspective. Recent surveys suggest that professionals such as pediatricians and genetic counselors are generally supportive of expanding screening to conditions such as FXS, with some reservations (Acharya, Ackerman, & Ross, 2005; Hiraki, Ormond, Kim, & Ross, 2006). But private market forces and advocacy groups will push this agenda faster and further, a goal for which most professionals are currently unprepared, and the public health system will need to make fundamental decisions about the relative roles of public health screening and private screening. A parallel system of private fee-based screening will inevitably lead to inequities in who has access to screening and for what purposes. But the public health system has limited resources both for screening and for follow up, and difficult choices will need to be made. Grosse et al. (2006) characterize this second generation of newborn screening as a shift from screening as public health emergency to public health service. But controversies exist about the nature of information that should be disclosed and the possibility of harms that could occur (Dhondt, 2007). Grob’s (2006) characterization of newborn screening in the genomic age as a ‘‘cursed blessing’’ captures the range of feelings many consumers have about both the hopes and fears associated with expanded newborn screening. Research is urgently needed to lay the groundwork for these inevitable changes and address the concerns that have been raised as well as create an infrastructure to evaluate unanticipated future challenges that will arise (Alexander & Hanson, 2006; Bailey, Skinner, Davis, Whitmarsh, & Powell, 2008; Botkin, 2005). Among the many questions that will need to be answered include the following:

What would be the public acceptability and effects of a two-tiered screening program, one that is required for all children (current status) and a second that is voluntary, with informed consent? To what extent do families from diverse cultural and ethnic groups consent to expanded newborn screening, what are their reasons for declining or accepting screening, and what family or sociocultural factors are related to screening decisions? What strategies should be used for informed consent and informed decision-making to assure that families of identified children are adequately informed about the possible results from screening and are satisfied with their decision to participate?

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Do families experience adverse mental health outcomes following a diagnosis, and how does adaptation vary as a function of child, family, and support variables? Is the quality or nature of parent–child relations affected by information gained through expanded newborn screening? How do parents and extended family members respond to, share, and use information gained from expanded newborn screening, and what factors are related to successful patterns of communication? To what extent is the full range of potential benefits of newborn screening (Bailey et al., 2005) achieved for both infants and families? What systems need to be in place to assure that the hoped-for benefits of screening accrue to children and families (Bailey, Armstrong et al., 2008)? How often do potential concerns raised about expanded newborn screening (e.g., Bailey, Skinner et al., 2008) occur, to what extent do they result in harm for children or families, and what factors are associated with poor outcomes? How can we quantify the wide range of benefits and costs of expanded genetic testing, differentiating appropriately between cost-effective and cost-saving interventions (Grosse, 2005; Khoury, Jones, & Grosse, 2006)?

Answering questions such as these will be complicated and require systematic, prospective longitudinal research, incorporating a wide range of variables. A research network is needed so that as new conditions are discovered or new treatments are developed, their effects can be tested. But ultimately it will be virtually impossible to conduct randomized clinical trials on the desirability of newborn screening for each individual condition, as has been the case to date. What is needed is a thorough examination of the desirability of disclosing classes of genetic information (e.g., carrier status, uncertain phenotype, probabilistic likelihoods of phenotypic outcomes) to determine whether and how such information should be shared, using a few prototypic conditions. Tunis, Stryer, and Clancy (2003) characterize such studies as ‘‘practical clinical trials,’’ studies that select clinically relevant issues with clear policy ramifications and study a range of outcomes in the context of typical practice settings. Then expensive clinical trials can be reserved for evaluating the efficacy of specific treatments for specific conditions, rather than trying to answer the more general question of whether screening and the subsequent disclosure of various forms of information about genetic variants in and of itself is desirable.

ACKNOWLEDGMENTS Preparation of this chapter was supported in part by grants from the Ethical, Legal, and Social Implications Research Program, the National Human Genome Research Institute (Grant number 1P50-HG004488), and the National Institute for Child Health and Human Development (Grant number R21-HD043616).

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REFERENCES Acharya, K., Ackerman, P. D., & Ross, L. F. (2005). Pediatricians’ attitudes toward expanding newborn screening. Pediatrics, 116, e476–e484. Alexander, D., & Hanson, J. W. (2006). NICHD research initiative in newborn screening. Mental Retardation and Developmental Disabilities Research Reviews, 12, 301–304. American Academy of Pediatrics Committee on Bioethics (2001). Ethical issues with genetic testing in pediatrics. Pediatrics, 107, 1451–1455. American Academy of Pediatrics Newborn Screening Task Force (2000). Serving the family from birth to the medical home. Newborn screening: A blueprint for the future. Pediatrics, 106(Supplement), 389–427. American Society of Human Genetics/American College of Medical Genetics (ASHG/ ACMG) (1995). Points to consider: Ethical, legal, and psychosocial implications of genetic testing in children and adolescents. American Journal of Human Genetics, 57, 1233–1241. Andrews, L. B., Fullarton, J. E., Holtzman, M. A., & Motulsky, A. G. (Eds.) (1994). Assessing genetic risks: Implications for health and social policy. Washington, DC: National Institute of Sciences. Anido, A., Carlson, L. M., Taft, L., & Sherman, S. L. (2005). Women’s attitudes toward testing for fragile X carrier status: A qualitative analysis. Journal of Genetic Counseling, 14, 295–301. Anido, A., Carlson, M., & Sherman, S. L. (2007). Attitudes toward fragile X mutation carrier testing from women identified in a general population survey. Journal of Genetic Counseling, 16, 97–104. Bailey, D. B. (2000). The federal role in early intervention: Prospects for the future. Topics in Early Childhood Special Education, 20(2), 71–78. Bailey, D. B. (2004). Newborn screening for fragile X syndrome. Mental Retardation and Developmental Disabilities Research Reviews, 10, 3–10. Bailey, D. B., Armstrong, F. D., Kemper, A. R., Skinner, D., & Warren, S. F. (2008). Supporting family adaptation to pre-symptomatic and ‘‘untreatable’’ conditions in an era of expanded newborn screening. Journal of Pediatric Psychology, 33, 1–14. Bailey, D. B., Aytch, L. S., Odom, S. L., Symons, F., & Wolery, M. (1999). Early intervention as we know it. Mental Retardation and Developmental Disabilities Research Reviews, 5, 11–20. Bailey, D. B., Beskow, L. M., Davis, A. M., & Skinner, D. (2006). Changing perspectives on the benefits of newborn screening. Mental Retardation and Developmental Disabilities Research Reviews, 12, 27–279. Bailey, D. B., Bruder, M. B., Hebbeler, K., Carta, J., DeFosset, M., Greenwood, C., et al. (2006). Recommended outcomes for families of young children with disabilities. Journal of Early Intervention, 28, 227–251. Bailey, D. B., & Gariepy, J. (2008). Critical periods. In M. M. Haith, & J. B. Benson (Eds.), Encyclopedia of infant and early childhood development (pp. 322–332). San Diego, CA: Elsevier. Bailey, D. B., Hebbeler, K., Scarborough, A., Spiker, D., & Mallik, S. (2004). First experiences with early intervention: A national perspective. Pediatrics, 113, 887–896. Bailey, D. B., Hebbeler, K., Spiker, D., Scarborough, A., Mallik, S., & Nelson, L. (2005). 36-month outcomes for families of children with disabilities participating in early intervention. Pediatrics, 116, 1346–1352. Bailey, D. B., Nelson, L., Hebbeler, K., & Spiker, D. (2007). Modeling the impact of formal and informal supports for young children with disabilities and their families. Pediatrics, 120, e992–e1001. Bailey, D. B., Roberts, J. E., Mirrett, P., & Hatton, D. (2001). Identifying infants and toddlers with fragile X syndrome: Issues and recommendations. Infants and Young Children, 14, 24–33.

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Bailey, D. B., Skinner, D., Davis, A., Whitmarsh, I., & Powell, C. (2008). Ethical, legal, and social concerns about expanded newborn screening: Fragile X syndrome as a prototype for emerging issues. Pediatrics, 121, e693–e704. Bailey, D. B., Skinner, D., Hatton, D., & Roberts, J. (2000). Family experiences and factors associated with the diagnosis of fragile X syndrome. Developmental and Behavioral Pediatrics, 21, 315–321. Bailey, D. B., Skinner, D., & Sparkman, K. (2003). Discovering fragile X syndrome: Family experiences and perceptions. Pediatrics, 111, 407–416. Bailey, D. B., Skinner, D., & Warren, S. F. (2005). Newborn screening for developmental disability: Reframing presumptive benefit. American Journal of Public Health, 95, 1889–1893. Baranek, G. T., Danko, C. D., Skinner, M. L., Bailey, D. B., Hatton, D. D., Roberts, J. E., et al. (2005). Video analysis of sensory-motor features in infants with fragile X syndrome at 9–12 months of age. Journal of Autism and Developmental Disorders, 35, 645–656. Berry, H. K., O’Grady, D. J., Perlmutter, L. J., & Bofinger, M. K. (1979). Intellectual development and academic achievement of children treated early for phenylketonuria. Developmental Medicine and Child Neurology, 21, 311–320. Bodamer, O. A., Hoffman, G. F., & Lindner, M. (2007). Expanded newborn screening in Europe 2007. Journal of Inherited Metabolic Disorders, 30, 439–444. Borrajo, G. J. C. (2007). Newborn screening in Latin America at the beginning of the 21st century. Journal of Inherited Metabolic Disorders, 30, 466–481. Botkin, J. R. (2005). Research for newborn screening: Developing a national framework. Pediatrics, 116, 862–871. Botkin, J. R., Clayton, E. W., Fost, N. C., Burke, W., Murray, T. H., Baily, M. A., et al. (2006). Newborn screening technology: Proceed with caution. Pediatrics, 117, 1793–1799. Comeau, A. M., Parad, R. B., Dorkin, H. L., Dovey, M., Gerstle, R., Haver, K., et al. (2004). Population-based newborn screening for genetic disorders when multiple mutation DNA testing is incorporated: A cystic fibrosis newborn screening model demonstrating increased sensitivity but more carrier detections. Pediatrics, 113, 1573–1581. Committee for the Study of Inborn Errors of Metabolism (1975). Genetic screening programs, principles, and research. Washington, DC: National Academy of Sciences. Cook, E. H. (1998). Genetics of autism. Mental Retardation and Developmental Disabilities Research Reviews, 4, 113–120. DeFries, J. C., & Alarcon, M. (1996). Genetics of specific reading disability. Mental Retardation and Developmental Disabilities Research Reviews, 2, 39–47. Dhondt, J.-L. (2007). Neonatal screening: From the ‘Guthrie age’ to the ‘genetic age. Journal of Inherited Metabolic Disorders, 30, 418–422. Engle, P. L., Black, M. M., Behrman, J. R., de Mello, M. C., Gertler, P. J., Kapiriri, L., et al. (2007). Strategies to avoid the loss of developmental potential in more than 200 million children in the developing world. Lancet, 369, 229–242. Fenning, R. M., Baker, J. K., Baker, B. L., & Crnic, K. A. (2007). Parenting children with borderline intellectual functioning: A unique risk population. American Journal on Mental Retardation, 112, 107–121. Grob, R. (2006). Parenting in the genomic age: The ‘cursed blessing’ of newborn screening. New Genetics and Society, 25, 159–170. Grody, W. W. (2003). Ethical issues raised by genetic testing with oligonucleotide mocroarrays. Molecular Biotechnology, 23, 127–138. Grosse, S. D. (2005). Does newborn screening save money? The difference between costeffective and cost-saving interventions. Journal of Pediatrics, 146, 168–170. Grosse, S. D., Boyle, C. A., Kenneson, A., Khoury, M. J., & Wilfond, B. S. (2006). From public health emergency to public health services: The implications of evolving criteria for newborn screening panels. Pediatrics, 117, 923–929.

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Guralnick, M. (2005). Early intervention for children with intellectual disabilities: Current knowledge and future prospects. Journal of Applied Research in Intellectual Disabilities, 18, 313–324. Gurian, E. A., Kinnamon, D. D., Henry, J. J., & Waisbren, S. E. (2006). Expanded newborn screening for biochemical disorders: The effect of a false-positive result. Pediatrics, 117, 1915–1921. Hacia, J. G., & Collins, F. S. (1999). Mutational analysis using oligonucleotide microarrays. Journal of Medical Genetics, 36, 730–736. Han, X., Powell, B. R., Phalin, J. L., & Chehab, F. F. (2006). Mosaicism for a full mutation, premutation, and deletion of the CGG repeats results in 22% FMRP and elevated FMR1 mRNA levels in a high-functioning fragile X male. American Journal of Medical Genetics, 140A, 1463–1471. Hewlett, J., & Waisbren, S. E. (2006). A review of the psychosocial effects of false-positive results on parents and current communication practices in newborn screening. Journal of Inherited Metabolic Disease, 20, 677–682. Hiraki, S., Ormond, K. E., Kim, K., & Ross, L. F. (2006). Attitudes of genetic counselors toward expanding newborn screening and offering predictive genetic testing to children. American Journal of Medical Genetics Part A, 140A, 2312–2319. Holtzman, N. A., & Watson, M. S. (1997). Promoting safe and effective genetic testing in the United States: Final report of the Task Force on Genetic Testing. Bethesda, MD: National Institutes of Health. Howell, R. R. (2006a). Introduction: Newborn screening. Mental Retardation and Developmental Disabilities Research Reviews, 12, 229. Howell, R. R. (2006b). The high price of false positives. Molecular Genetics and Metabolism, 87, 180–183. Howse, J. L., Weiss, M., & Green, N. S. (2006). Critical role of the March of Dimes in the expansion of newborn screening. Mental Retardation and Developmental Disabilities Research Reviews, 12, 280–287. Inlow, J. K., & Restifo, L. L. (2004). Molecular and comparative genetics of mental retardation. Genetics, 166, 835–881. Kemper, A.R., Hwu, W.-L., Lloyd-Puryear, M., Kishnani, P.S. (2007). Newborn screening for Pompe disease: A synthesis of the evidence. Pediatrics, 120, e1327–1334. Khoury, M. J., Gwinn, M., Burke, W., Bowen, S., & Zimmern, R. (2007). Will genomics widen or help heal the schism between medicine and public health. American Journal of Preventive Medicine, 33, 310–317. Khoury, M. J., Jones, K., & Grosse, S. D. (2006). Quantifying the health benefits of genetic tests: The importance of a population perspective. Genetics in Medicine, 8, 191–195. Koch, R., & de la Cruz, F. (1999). Historical aspects and overview of research on phenylketonuria. Mental Retardation and Developmental Disabilities Research Reviews, 5, 101–104. Materin, D., & Rinaldo, P. (2003, August). Newborn screening: Opportunities and challenges of tandem mass spectrometry. Clinical Laboratory News, 12–15. McGuire, A. L., Cho, M. K., McGuire, S. E., & Caulfield, T. (2007). The future of personal genomics. Science, 317, 1687. Mirrett, P. L., Bailey, D. B., Roberts, J. E., & Hatton, D. D. (2004). Developmental screening and detection of developmental delays in infants and toddlers with fragile X syndrome. Developmental and Behavioral Pediatrics, 25, 21–27. Padilla, C. D., & Therrell, B. L. (2007). Newborn screening in the Asia Pacific region. Journal of Inherited Metabolic Disorders, 30, 490–506. Plomin, R., & McGuffin, P. (2003). Psychopathology in the postgenomic era. Annual Review of Psychology, 54, 205–228. Pollit, R. J. (2007). Introducing new screens: Why are we all doing different things. Journal of Inherited Metabolic Disorders, 30, 423–429.

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Ramey, S. L., & Ramey, C. T. (1999). Early experience and early intervention for children ‘‘at risk’’ for developmental delay and mental retardation. Mental Retardation and Developmental Disabilities Research Reviews, 5, 1–10. Roberts, J. E., Hatton, D. D., & Bailey, D. B. (2001). Development and behavior of male toddlers with fragile X syndrome. Journal of Early Intervention, 24, 207–223. Rolland, J. S., & Williams, J. K. (2005). Toward a biopsychosocial model for 21st-century genetics. Family Process, 44, 3–24. Saadallah, A. A., & Rashed, M. S. (2007). Newborn screening: Experiences in the Middle East and North Africa. Journal of Inherited Metabolic Disorders, 30, 482–489. Sices, L., Feudtner, C., McLaughlin, J., Drotar, D., & Williams, M. (2003). How do primary care physicians identify young children with developmental delays? A national survey. Developmental and Behavioral Pediatrics, 24, 409–417. Skinner, D., Sparkman, K., & Bailey, D. B. (2003). Screening for fragile X syndrome: Parent attitudes and perspectives. Genetics in Medicine, 5, 378–384. Tarini, B. A., Christakis, D. A., & Welch, H. G. (2006). State newborn screening in the tandem mass spectrometry era: More tests, more false-positive results. Pediatrics, 118, 448–456. Therrell, B. L., & Adams, J. (2007). Newborn screening in North America. Journal of Inherited Metabolic Disorders, 30, 447–465. Therrell, B. L., & Hannon, W. H. (2006). National evaluation of U.S. newborn screening system components. Mental Retardation and Developmental Disabilities Research Reviews, 12, 236–245. Tunis, S. R., Stryer, D. B., & Clancy, C. M. (2003). Practical clinical trials: Increasing the value of clinical research for decision making in clinical and health policy. Journal of the American Medical Association, 290, 1624–1632. United States General Accounting Office (2003). Newborn screening: Characteristics of state programs (Report GAO-03–449). Washington, DC: U.S. General Accounting Office. Walker, S. P., Wachs, T. D., Gardner, J. M., Lozoff, B., Wasserman, G. A., Pollitt, E., et al. (2007). Child development: Risk factors for adverse outcomes in developing countries. Lancet, 369, 145–157. Watson, M. S. (2006). Current status of newborn screening: Decision-making about the conditions to include in screening programs. Mental Retardation and Developmental Disabilities Research Reviews, 12, 230–235. Watson, M. S., Mann, M. M., Lloyd-Puryear, M. A., Rinaldo, P., & Howell, R. R. (Eds.) (2006). Newborn screening: Toward a uniform screening panel and system. Genetics in Medicine, 8(Supplement 1), 1S–252S. Wilson, J. M. G., & Junger, F. (1968). Principles and practice of screening for disease. Public Health Papers No. 34. Geneva: World Health Organization.

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C H A P T E R

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Responsive Parenting: Closing the Learning Gap for Children with Early Developmental Problems Susan H. Landry,* Heather B. Taylor,* Cathy Guttentag,* and Karen E. Smith† Contents 1. Introduction 2. School-Age Developmental Characteristics 2.1. Children born VLBW 2.2. Children with SB 2.3. Children with DS 3. Shared Challenges for Effective Learning 3.1. Motor control/motor learning 3.2. Attention regulation/information processing 3.3. Goal-directed behavior 3.4. Interrelated early core skills 4. What is Responsive Parenting? 4.1. Affective-emotional style 4.2. Cognitively supportive behaviors 4.3. Adapting to needs of the child 5. What Supports Responsive Parenting? 6. Evidence for the Specialized Support of Responsive Parenting for Core Deficits 6.1. Linking specialized responsive scaffolding to early learning problems 6.2. Maintaining focus of attention 6.3. Use of directives 6.4. Warm sensitivity, contingent responsiveness, and avoidance of restrictiveness 6.5. Rich language input 6.6. Bidirectionality of influence

* {

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Department of Pediatrics, Children’s Learning Institute, The University of Texas Health Science Center, Houston, Texas 77030 University of Texas Medical Branch at Galveston, Houston, Texas 77030

International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00002-5

#

2008 Elsevier Inc. All rights reserved.

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7. Evidence from Longitudinal Studies for Closing the Learning Gap for At-risk Children 8. Evidence from Experimental Findings for Closing the Learning Gap 8.1. Effects of PALS on maternal behaviors 8.2. Effects of PALS on infant skills 8.3. The influence of aspects of responsiveness on domains of infant development 8.4. Evidence for individual profiles of parenting 8.5. The optimal timing for responsive parenting intervention 9. Summary and Conclusions, Implications and Future Directions 9.1. Summary and conclusions 9.2. Implications and future directions Acknowledgments References

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Abstract Responsive parenting strategies have the potential to provide specific scaffolding for common deficits found in developmentally at-risk children. This chapter describes findings from our research conducted across the past two decades with three groups of children known to have increased risk for compromised outcomes in a range of developmental domains (e.g., motor, social). These groups include children born at very low birth weight (VLBW) with varying degrees of neonatal complications associated with preterm birth, those born with spina bifida, and those born with Down syndrome. Although these three groups have striking differences in their developmental profiles, they share a common set of developmental difficulties that can be ameliorated through responsive parenting. In this chapter, we describe our research in responsive parenting, including cross-sectional studies that demonstrate how specific parenting strategies can provide supportive scaffolding to address the common deficits found in these groups of children. Evidence is then provided from a longitudinal study that documents how responsive parenting can close the learning gap for one group of children, those born at VLBW. Finally, results from a random assignment, responsive parenting intervention study that included children born at VLBW are discussed. These findings provide support for a causal role of responsive parenting in promoting more optimal development for children at risk for developmental problems.

1. Introduction There is strong support for early childhood being a critically important time for environmental influences on brain development (Dawson, Klinger, Panagiotides, Hill, & Spieker, 1992; DiPietro, 2000; Elman et al., 1996; Neville et al., 1998). Recent evidence from basic science research and

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longitudinal behavioral and intervention studies reaffirms that brain development in the early years (birth to five) is influenced by experiences that affect learning, behavior, and physical and mental health throughout life (Dawson et al., 1992; DiPietro, 2000; Elman et al., 1996; Neville et al., 1998). These findings may be especially true for at-risk children who have to manage various problems that impact their development. There are many biological and environmental conditions that may place children at risk for suboptimal developmental outcomes in the cognitive/academic or social/ emotional domains. The term ‘‘at risk’’ can be used to describe children who do not currently show developmental problems (or who are too young to assess for such problems) but with risk factors in their background which may lead to later emerging problems. Alternatively, the term ‘‘at risk’’ can be used to describe children who have current delays or disorders and are likely to continue to struggle in their development. In this chapter, we review research on several different populations of children who represent both of these categories. Therefore, for the purposes of this chapter, the term ‘‘at risk’’ will be used to refer to children who have an above-average likelihood of experiencing later learning problems, whether due to currently existing disabilities and/or delays, or due to background factors which predispose them, statistically, to such difficulties. A substantial number of children are born each year with medical conditions that put them at risk for developmental difficulties, including children born at very low birth weight (VLBW), with spina bifida (SB), or Down syndrome (DS). Many of these children show difficulties in infancy that impact their development, and the influence of the parenting environment may be even greater for them than for typically developing children (Bornstein, 1985; Landry, Smith, Miller-Loncar, & Swank, 1997). One feature of the caregiving environment consistently reported to be important for children’s outcomes is a responsive parenting style (Bornstein & Tamis-Lemonda, 1989; Londerville & Main, 1981; Olson, Bates, & Bayles, 1984). Because a highlight of responsive parenting is the reciprocal connection between the child’s needs and the parent’s response, this style may have the potential to provide a buffering effect on the developmental problems often seen in children with special needs. This chapter describes findings from our research conducted across the past two decades that has explored the potential of responsive parenting to support the developmental needs of at-risk children. This research was conducted with three groups of children known to have increased risk for impairment in a range of developmental domains (e.g., motor, social). These groups include children born at VLBW with varying degrees of medical risk associated with preterm birth, those born with SB, and children with DS. Although the three groups have striking differences in their developmental profiles, as infants and young children they have some developmental difficulties in common and these are described first. These findings of similar early learning issues across groups provide support for

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broader generalizations in regard to how these groups may benefit similarly from responsive parenting. Second, we define responsive parenting as it is described in two theoretical frameworks including four key behavioral aspects that comprise this style. This is followed by results from crosssectional studies that demonstrate how parenting strategies can provide specific scaffolding to ameliorate the common deficits found in these groups of children. Evidence is then provided from a longitudinal study that documents how responsive parenting can close the learning gap for one group of children, those born at VLBW. Finally, the causal role of a responsive parenting style in facilitating at-risk children’s development is supported with results from an experimental study with parents of young children, including those born at VLBW.

2. School-Age Developmental Characteristics In order to better understand the potential importance of early responsive parenting for the three targeted groups, it is useful to examine the longer term outcomes described in the literature for these children. As will be described, outcomes across the three groups are disparate in terms of intellectual status, motor skills, and language outcomes. However, all three groups have some degree of difficulty in cognitive, academic, and socialbehavioral areas.

2.1. Children born VLBW For school-age VLBW children, longitudinal studies have documented a high incidence of social, behavioral, and learning problems (Taylor, Hack, Klein, & Schatschneider, 1995). More adverse developmental outcomes may be associated with specific types of medical complications including acute and chronic respiratory complications (Goldson, 1983; Landry et al., 1984; Ruiz, LeFever, Hakanson, Clark, & Williams, 1981; Vohr, Bell, & Williamson, 1982) and intraventricular hemorrhage (IVH) (Landry, Fletcher, Denson, & Chapieski, 1993; Landry, Schmidt, & Richardson, 1989). Long-term learning problems may be due, in part, to early difficulties these children show in developing joint attention skills that allow them to learn from interactions with others.

2.2. Children with SB In addition to moderate to severe difficulties in gross motor development (Bushnell & Boudreau, 1993; Dennis et al., 2004; Landry, Jordan, & Fletcher, 1994b; Lomax-Bream, Barnes, Copeland, Taylor, & Landry,

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2007a), a broad range of neurobehavioral problems also are found for older children and adults with SB, including cognitive problems such as difficulty with focusing and shifting attention (Brewer, Fletcher, Hiscock, & Davidson, 2001; Dennis, Landry, Barnes, & Fletcher, 2006), visualperceptual problem solving (Dennis, Fletcher, Rogers, Hetherington, & Francis, 2002), and sequencing reasoning skills to carry out math procedures (Barnes et al., 2006; Dennis & Barnes, 2002). A majority also have academic problems such as reading comprehension (Barnes & Dennis, 2004). While there has been less research on the early precursors of these later developmental problems, information now is becoming available (Lomax-Bream et al., 2007b).

2.3. Children with DS Unlike the previous two groups of children, the majority of those with DS have long-term deficiencies in intellectual development and almost always function in an IQ range consistent with a mental retardation diagnosis (Ramirez & Morgan, 1998). In studies examining later language and communication development, there are particular problems in language production, syntax, and poor speech intelligibility (Roberts, Price, & Malkin, 2007). The most widely cited behavioral problems identified at later ages include impulsivity (Goldberg & Marcovitch, 1989) and problems with focused attention (Kasari, Freeman, Mundy, & Sigman, 1995). Unlike children with SB, considerable research has focused on the early development of those with DS (e.g., Ramirez & Morgan, 1998; Roberts et al., 2007) as well as the early influence of the caretaking environment for understanding variability in their outcome (Mahoney, Perales, Wiggers, & Herman, 2006; Tannock, 1988).

3. Shared Challenges for Effective Learning Although there are unique developmental issues specific to individuals and medical conditions, children with SB, DS, and those born VLBW share similar learning challenges in infancy. These common problems reflect difficulties in motor control/learning, regulating and shifting attention, and goal-directed behavior. In typically developing children, this core set of interrelated early skills becomes part of a foundation that helps learning. This in turn impacts the development of future skills necessary for success in a range of content domains including academic and social learning. Unfortunately, children with the above conditions have been found to demonstrate difficulty with these core skills.

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3.1. Motor control/motor learning Developmentally at-risk infants often have difficulty with motor responses, especially motor timing and motor control/learning. Motor timing is related to a general lack of coordination and poor synchronization of movement. Motor control/learning causes problems on tasks requiring infants to learn and execute motor contingencies. Thelen and Smith (1995) posit that early success in effective motoric organization and exploration of the environment is essential in development of skills necessary for appropriate cognitive development. Motor impairment restricts the infant’s ability to explore the environment, thereby restricting sensory experiences. It may also distort sensory input experienced by the infant when handling objects. Piaget (1952) suggests that the extent that an infant learns about the world is formulated through the transactions between the infant’s own actions and objects. In this way, it is the coordination of sensorimotor activity that produces higher levels of cognitive functioning. Infants with DS typically have central hypotonia. Consequently, gross motor movements are often delayed. On the average, most children with DS do not sit up until 11 months of age or walk until 19 months (Winders, 1997), with boys being slightly more delayed than girls (Melyn & White, 1973). Nonetheless, children with DS may learn to run, ride bicycles, and participate in sports (Adirim & Fine, 2002). For infants with DS, motor difficulty may impact their ability to explore and learn from the environment. In one study conducted by Landry and Chapieski (1989), infants with DS demonstrated significantly more difficulties with motor organization than preterm infants when responding to mothers directing toy play. These infants were far more likely than preterm infants to respond to mother with a look, but they were less likely to reach for and manipulate toys during play. Infants with SB often have a complex array of physical symptoms which can include flaccid or spastic paralysis (Mazur, Stillwell, & Menelaus, 1986), sensory loss below the lesion level, and hydrocephalus. The extent of motor paralysis and sensory loss depends on the location of the lesion in the spinal cord (Liptak, 2002). In a longitudinal study on children with SB followed from 6 to 36 months, having SB was associated with lower levels of performance on the Bayley Motor Scale. Furthermore, on this motor measure, having a shunt or a higher lesion level also predicted significantly lower scores than having SB without a shunt or having lower lesion levels, respectively (Lomax-Bream et al., 2007a). Extremely low-birth-weight infants are often more likely than full-term infants to have motor difficulties (McCormick, McCarton, Tonascia, & Brooks-Gunn, 1993). Factors that increase the likelihood of motor difficulties include severity of neonatal complications including infections with chronic lung disease (Skidmore, Rivers, & Hack, 1990), and CNS insults (Paneth, 1993; Papile, Munsick-Bruno, & Schaefer, 1983; Pinto-Martin,

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Whitaker, Feldman, Van Rossem, & Paneth, 2000; Sinha, D’Souza, Rivlin, & Chiswick, 1990; Vohr et al., 1991). Anderson, Swank, Wildin, Landry, and Smith (1999) conducted a longitudinal study that followed children born prematurely from 6 months (corrected) to 54 months of age. Using a composite score including motor tone, motor coordination, and reflex subscales on a neurological examination, both low-risk and high-risk infants demonstrated higher neurological scores across all time points compared to full-term infants (higher scores ¼ more abnormality). Furthermore, the term infants demonstrated minimal change in neurological patterns over time, while the preterm groups (both high and low risk) demonstrated complex, nonlinear patterns of change in their neurologic scores. Whereas low-risk preterms demonstrated a trend toward normalization at 54 months, this was not the case for high-risk preterm infants.

3.2. Attention regulation/information processing At a very young age, typically developing infants are able to modulate arousal states and activate early attention behaviors. Infants’ ability to attend to their environment fosters learning from their surroundings. These attention modulation and activation skills improve with the support of mediators such as neurophysiological maturation and parent interactions (Block & Block, 1979; Kopp, 1982; Mischel & Patterson, 1979; Wertsch, 1979). Although there are many aspects of attention, this section will focus on two types of early visual attention processes in infants: attention getting (i.e., turning toward a stimulus) and attention holding (i.e., sustained fixation on the stimulus after turning). Adequate development in these attentional processes allows infants to move on to, and learn about, other environmental stimuli (Ruff & Lawson, 1991). It is important to document and understand attention difficulties found even in infancy if interventions are to be implemented. Children with motor problems often also have problems with attention (Kaplan, Wilson, Dewey, & Crawford, 1998). Even though they manifest differently in different groups (i.e., SB, DS), motor difficulties of various kinds may strain infants’ limited attentional capacities and reduce their ability to learn from their environment. Kaplan et al. (1998) postulated that attention deficit/hyperactivity disorder and other childhood developmental disorders show a high comorbidity due to brain dysmorphology during early brain development. It is well documented that the increased risk for attention-related school problems can have a negative impact on academic achievement for children with DS (Ramirez & Morgan, 1998), SB (Dennis et al., 2006), and those born at VLBW (Schothorst & van Engeland, 1996; Weindrich, Jennen-Steinmetz, Laucht, & Schmidt, 2003). Investigation of early attentional processes among infants with DS have found that these infants may have difficulty with both attention holding (Vietze, McCarthy, McQuiston, MacTurk, & Yarrow, 1983) and shifts in

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looking at aspects of their environment (attention getting) (Krakow & Kopp, 1983). In addition, one study compared 6-month-old infants with DS (n ¼ 14) to mental and motor age-matched high-risk VLBW infants (n ¼ 15) (Landry & Chapieski, 1990). Results of this study on joint attention suggested that although infants with DS were able to shift their attention from interest in mother to interest in toys, they did so at a slower rate than the VLBW infants. In addition, infants were evaluated in their ability to hold attention on toys (i.e., mean length of time looking at toys). In regard to this sustained attention (i.e., attention holding), the average length of looking and the average length of examination of toys were not different for the two groups. However, infants with DS spent significantly less total time looking at toys and significantly more time looking at their mothers. Similarly, studies conducted on children born with SB or at VLBW demonstrated significant difficulty with attention getting but less difficulty with attention holding. For example, in one study (SB ¼ 47; Control ¼ 40), 18-month-old infants with SB took significantly longer to shift their attention from a blinking light to a face stimulus projected on a screen (i.e., attention getting) than typically developing infants (Taylor, Landry, Cohen, Barnes, & Swank, 2006). A similar result was found in a study conducted with infants born VLBW (n ¼ 14 with respiratory distress syndrome, RDS, and IVH; n ¼ 9 with RDS without IVH). Attention getting difficulties in this group were detected at 7 months corrected for prematurity, with the VLBW infants with IVH and RDS taking significantly longer to shift their attention than both the lower risk VLBW and typically developing infants (Landry, Leslie, Fletcher, & Francis, 1985). These same studies reported no difference in their samples of infants born VLBW (Landry et al., 1985) and with SB (Taylor et al., 2006) in their ability to habituate, or show a decremental response, to a familiar stimulus when compared to typically developing infants. When evaluating response to a novel stimulus, infants born VLBW did not differ in their ability to show an incremental response. In contrast, Taylor et al. (2006) found in their study that infants with SB had shorter fixation times to a novel stimulus compared to typically developing infants, and this finding was significantly related to infants’ motor scores, suggesting that infants with higher motor performance were more likely to have an incremental response to a novel stimulus than those with lower motor scores. This was true for both infants with SB and typical developing children.

3.3. Goal-directed behavior Goal-directed behavior is an important component of motivation, playing an essential role in successful learning (White, 1959). This can also be described as executive functioning or in other cases, rule-based problem solving. It is a complex, multifaceted construct that involves more than one psychological

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process. Some important components necessary for goal-directed behavior to occur include (1) identifying a particular interest, (2) planning the actions necessary to carry out the activity, and (3) initiating and persisting in these actions in order to achieve an identified goal. A fourth critical component of these goal-directed behaviors is that the child self-initiate purposeful action rather than being dependent on the structure provided by others. Research suggests that older children with developmental difficulties (including children born with SB, DS, or at VLBW) tend to have difficulty in regulating their behavior toward the achievement of particular goals. For example, findings regarding the performance of school-aged children with SB working on independent problem-solving tasks showed that these children had more difficulty maintaining goal-directed activities during play than did age- and IQ-matched typically developing children (Landry, Robinson, Copeland, & Garner, 1993). More specifically, the children with SB had difficulty sequencing their own behavior in order to reach a goal. Children with DS appear to experience particular difficulties with maintaining goal-directed behavior and inhibiting themselves from distraction. Kopp (1990) found that waiting and delay of gratification were particularly difficult for this group. Children with DS have also been found to demonstrate fewer social initiations than do mental age-matched control children. In one study by Landry, Garner, Pirie, and Swank (1994a), children with DS initiated fewer exchanges with their mothers but were comparable to typically developing children on self-directed behavior. Gilmore, Cuskelly, and Hayes (2003) evaluated planfulness and maintenance of goal-directed behavior in a sample of 26 children with DS compared to 43 typically developing children, matched for mental age (24–36 months). Both groups showed similar levels of competence, planfulness, and distractibility. But, children with DS demonstrated more difficulty with task-avoidant behavior. Children born very preterm or at extremely low birth weight have been found to exhibit considerable difficulty with executive functioning (maintaining goal-directed behavior) compared to normal birth peers at 8 years of age (Anderson, Doyle, & Victorian Infant Collaborative Study Group, 2004). In Anderson et al.’s (2004), they found preterm infants to have a global pattern of executive deficits rather than a specific pattern. This is consistent with other studies suggesting difficulties with impulse control, planning ability, motor sequencing, spatial working memory, spatial organization, and mental flexibility (Harvey, O’Callaghan, & Mohay, 1999; Luciana, Lindeke, Mills, & Nelson, 1999; Taylor, Hack, & Klein, 1998; Waber & McCormick, 1995).

3.4. Interrelated early core skills Core skills in attention, motor performance, and goal-directed behavior play a large role in learning. These skills are clearly interrelated as they impact infants’ ability to learn from their environment. For example, problems in

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attentional capacity are critical to infants’ response to their environment (e.g. toy play) (Landry, 1995), and this process is also further complicated by motor difficulties. Impairment in these interrelated early core skills may in turn interfere with later, more complex goal-directed behavior.

4. What is Responsive Parenting? Responsiveness is an aspect of supportive parenting referred to in several theories and research frameworks, including attachment (Ainsworth, Blehar, Waters, & Wall, 1978; Sroufe, 1983), socio-cultural (Rogoff, 1990; Vygotsky, 1978), and socialization of young children (Grusec & Kuczynski, 1980; Maccoby & Martin, 1983). The literature supports at least four types of responsive behaviors: contingent responding, emotional/affective support, language input that supports developmental needs, and support for infant foci of attention. Responsiveness can be considered an overarching construct that includes a number of distinct but conceptually related behaviors, and their distinctiveness may be based in part on the type of support each provide (Martin, 1989; Van Egeren, Barratt, & Roach, 2001). Two components within a responsive parenting style include behaviors related to an affective-emotional style and those that are cognitively supportive.

4.1. Affective-emotional style An affective-emotional style of parenting is emphasized in the attachment framework and involves positive affect with high levels of warmth and nurturance (Darling & Steinberg, 1993), responses that are contingently linked to the child’s signals, and acceptance of the child as a unique individual (Ainsworth et al., 1978; Bornstein, 1985). Warm acceptance of infants’ needs and interests with responses that are contingent on infants’ signals are thought to support infants’ ability to self regulate by facilitating the development of mechanisms for coping with stress and novelty. In turn, a trust and bond with the caregiver is developed through the process of internalization (Ainsworth et al., 1978; Bornstein & Tamis-Lemonda, 1989). This encourages an interest and willingness in infants to explore their environment, to continue to signal, and to cooperate with caregiver requests (Baumrind, 1989; Darling & Steinberg, 1993). This process occurs through a three-term chain of events in which the infant signals, the caregiver responds in a prompt and sensitive manner, and the infant experiences that her needs are met in a predictable way (e.g., Bornstein & TamisLemonda, 1989). Maternal responsive behaviors such as warmth and contingent responsiveness are considered to provide affective-emotional

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support. Evidence indicates that they facilitate social development such as increased cooperation in young children (Lytton, 1977; Parpal & Maccoby, 1985) and may be even more important for the social functioning of developmentally at-risk children.

4.2. Cognitively supportive behaviors Cognitively supportive behaviors emphasized in a socio-cultural framework include support for the child’s focus of attention and rich language input. These in combination with affective-emotional support are thought to facilitate development of both social and cognitive skills (Landry, Smith, & Swank, 2006). Supporting a child’s focus of attention through maintaining appears to facilitate a young child’s learning by providing a structure that supports the young child’s immature attention and cognitive abilities (Akhtar, Dunham, & Dunham, 1991; Tomasello & Farrar, 1986). In contrast, redirecting attentional focus is thought to hinder a child’s ability to focus and process new information as it places increased demands on a young child’s capabilities. Along with this support for attentional skills, rich language input promotes the child’s ability to develop richer knowledge of how and why things work and are organized. While this is critical for both language development and background knowledge, it also plays an important role in facilitating a child’s social–emotional development, as it provides labels and explanations for feelings and social understanding. Maternal responsive behaviors that are cognitively responsive by maintaining rather than redirecting children’s interests have been found to facilitate the exploratory behaviors of toddlers (Landry, Garner, Denson, Swank, & Baldwin, 1993), while rich language input is predictive of greater cognitive and language skills as well as later reading (Dieterich, Assel, Swank, Smith, & Landry, 2006; Landry et al., 1990).

4.3. Adapting to needs of the child Another aspect of responsive parenting is the ability to adapt to the young child’s changing needs. Although some behaviors are supportive of learning at high levels across childhood (e.g., contingent responsiveness, rich language input), others such as the provision of structure, or directiveness, may need to change across time. Research has shown that in the infant and early toddler period, higher levels of structure may support children’s ability to understand what is expected of them and thus increase regulatory capacity and cooperation (Marfo, 1992). However, if this aspect of parenting remains at high levels into the early preschool years when children are becoming more capable of directing their own learning, it can actually compromise children’s ability to take initiative in their learning (Landry, Smith, Swank, & Miller-Loncar, 2000).

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5. What Supports Responsive Parenting? As the child’s learning occurs through direct interactions with the parent, it is important to recognize that the parent’s ability to be responsive may be hindered and/or buffered by factors such as characteristics of the child, family economic status, and social and personal attributes of the caregiver. For example, characteristics of a child at risk for developmental delays can disrupt positive mother–child interactions (Goldberg, 1978; Kogan, 1980), particularly when the mother is already burdened with the problems associated with low socio-economic status (SES) (Drillien, 1964). Disorganized responses to stimulation (Als, Lester, & Brazelton, 1979) and difficult temperaments (Desmond, Wilson, Alt, & Fisher, 1980), characteristics frequently associated with developmentally at-risk infants, can cause parents to question their ability to adequately care for these infants. Since mothers with low SES, regardless of the medical status of their infants, have often been described as believing that their actions have little effect on their children, and as having lower expectations for their development (Hess & Shipman, 1965), these infants are likely to be in double jeopardy for poor mother–child interactions. A mother’s own child-rearing history may also influence her self-esteem and how she cares for her children (Belsky, Hertzog, & Rovine, 1986). Mothers who perceive that they were nurtured and had parents who were responsive to their needs have been found to provide high levels of responsiveness to normal and high-risk infants, while those with highly negative perceptions found it particularly difficult to parent responsively when they had a high-risk child (Hammond, Landry, Swank, & Smith, 2000). In addition, maternal psychological distress has been related to lower levels of maternal responsiveness and poorer developmental outcomes in their children (Bee et al., 1982; Field, 1987; Wilfong, Saylor, & Elksnin, 1991). This appears to occur even when psychological distress is at subclinical levels (Assel, Landry, Swank, Steelman, & Smith, 2002). Variability in child-rearing practices may be explained in part by social factors in the family’s environment that can serve to buffer the negative effects of factors such as low SES. A mother’s interactions with family and friends, for example, can act to buffer the stress of raising an at-risk child (Crockenberg, 1981; Gallagher, Cross, & Scharfman, 1981; Weinraub & Wolf, 1983). Social factors appear to influence caretaking behaviors even after taking into account the infant’s birth status and behavior (Feiring, Fox, Jaskir, & Lewis, 1987). The source and type of social support received by mothers can be important modifiers of caretaking behavior (Colletta & Gregg, 1981; Crnic, Greenberg, Ragozin, Robinson, & Basham, 1983). For example, mothers who report that family and friends provide assistance in caregiving and support them as a parent demonstrated a high level of responsive behaviors in interactions with children (Landry, Smith, Swank, Assel, &

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Vellet, 2001). However, a higher density of family members in a support network for a parent of a medically high-risk child may make it more difficult for the mother to feel supported, as the stress of this child is shared by everyone in the social network (Zarling, Hirsch, & Landry, 1988). In a recent intervention study, social support was found to be a unique predictor of mothers’ ability to move from an unresponsive style to a responsive style of parenting (Guttentag, Pedrosa-Josic, Landry, Smith, & Swank, 2006). This is an encouraging finding as interventions can provide greater degrees of social support for mothers with high-risk characteristics or from high-risk backgrounds (Dieterich, Landry, Smith, Swank, & Hebert, 2006).

6. Evidence for the Specialized Support of Responsive Parenting for Core Deficits 6.1. Linking specialized responsive scaffolding to early learning problems Previously in this chapter, we have described a range of early developmental difficulties that are similar across children with SB, DS, or VLBW. These include problems with regulating attention, processing new information, organizing motor movements to solve problems, and initiating goaldirected behavior in both social and cognitive problem-solving situations. In order to participate successfully in problem-solving tasks and social interactions, children need to be able to integrate these varied skills. The goal of the next section is to describe how specific responsiveness behaviors provide specialized support to buffer these common developmental difficulties that could compromise children’s learning. The theoretical framework that guided this work was the socio-cultural framework, where children’s learning is described as developing from a social context (Vygotsky, 1978). In this context, the parent provides a specialized form of support that allows the child to attend, process, and engage in a learning interaction in spite of having immature attentional and cognitive capacities. Thus, the caregiver’s support is a form of ‘‘other regulation’’ for the child, allowing him or her to begin to develop self-regulation abilities and take over a more active role in learning. The parent’s specialized support, or scaffolding, is the origin of the child’s later independent functioning, a critical milestone in a child’s development. The following studies examined maternal scaffolding and its effect on high-risk children’s learning.

6.2. Maintaining focus of attention Across all three of the developmentally at-risk groups, there are reports of difficulties in controlling attentional focus as well as shifting attention. Assisting a child in maintaining attentional focus is thought to be an

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important supportive behavior because it does not require the child to inhibit a response to something of interest and redirect their attention to another object or topic. Thus, young children do not have to use their limited attentional and cognitive capacity to reorient and organize a response, and in contrast, can use this capacity to process information about the original object of interest. Examples of maintaining strategies include naming and talking about the object to which the child is actively attending, showing the child how to use the object, or moving the object closer to the child to facilitate reaching and grasping. In our research, these behaviors were coded by frequency counts of instances when mothers’ verbal or nonverbal behaviors maintained or supported their children’s current focus of attention. With consistent use of maintaining strategies, a parent should be able to support a higher level of learning, particularly for a child with early learning difficulties. The findings of Landry, Garner, Swank, and Baldwin (1996) provide an example of the facilitative support of maintaining attention for children who were born at high medical risk (HR),VLBW. The children’s ability to process information was assessed in this study by examining the probability of an infant showing a higher level exploratory play response following a maternal attention-directing request. Infants were observed during toy centered interactions with their mothers and coded for their level of play prior to a maternal request that either maintained or redirected their infants’ current focus of attention. Of interest was the level of play response that followed the maternal request. For HR, VLBW infants, level of play following a request was comparable to that of term-born and low medical risk (LR), VLBW infants if their mothers maintained their foci of interest. In contrast, they showed significantly lower levels of play behavior than did the other two infant groups following a request to redirect their attention. Similar support for maintaining was found in a study examining children with Down syndrome’s ability to control and regulate attention in problemsolving situations (Landry et al., 1989). Using a similar paradigm to that noted above, mothers’ attempts to maintain attention were more likely to be followed by children manipulating a toy than by a more passive response of looking at, and/or holding, the toy. Of importance, this responsiveness strategy was more effective in eliciting higher level responses from the children than any verbal technique such as asking questions or providing imperatives. In the presence of maintaining, when mothers gave or showed a toy to their child with DS, their children were more likely to display a higher level toy manipulation response than when mothers demonstrated the toy function. In another study, if the interest of a child with DS was followed up on by the mother, the child was more apt to cooperate with maternal requests at levels similar to normal controls in a social tea party situation (Landry et al., 1994a).

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Most recently, children with SB were found to show higher levels and faster growth trajectories in cognitive skills through 3 years of age when their mothers used higher levels of maintaining behaviors, even after controlling for family SES and child’s motor development (Lomax-Bream et al., 2007b). Similar results were found for language development, and the influence of maternal maintaining on these outcomes was comparable for those with SB and typically developing children.

6.3. Use of directives Preschool-age children with DS were more likely than mental age-matched controls to follow through with a request when their mothers’ request was a direction rather than a suggestion or question (Landry et al., 1994a). In a similar paradigm, use of directiveness at these ages interfered with VLBW children’s ability to follow a request (Landry & Chapieski, 1990). Thus, continued provision of high levels of structure across the preschool period may provide more effective scaffolding technique for children with DS but not those born at VLBW. The type of support that continued use of this technique provides for children with DS may be effective due to their greater need for help in understanding what is expected of them in light of their compromised cognitive skills. Other research has indicated that young children with DS whose mothers interacted with them in a highly responsive manner (i.e., sensitive, reciprocal, and playful) had higher cognitive development scores than those whose mothers engaged with them in a highly directive, teaching-oriented manner (Mahoney et al., 2006). Since that study used a cross-sectional design, however, it was not possible to determine the directionality of this correlation; it may be that mothers of higher functioning children found it less necessary to be so directive in their approach. In our studies of children born at VLBW, higher levels of directiveness at 2 years of age predicted higher levels of cognitive skill and cooperation with social requests. However, by 3 years of age, if mothers did not decrease in their use of this strategy and adopt a more choice-providing approach, their children’s cognitive goal-directed and social initiative skills were at lower levels by 4 years of age.

6.4. Warm sensitivity, contingent responsiveness, and avoidance of restrictiveness Through much of our research with children born VLBW, high correlations have been found between observations of warmth and contingent responsiveness. Therefore, many of our studies have combined these two responsiveness behaviors into a single score, warm flexibility, and examined the predictive influence on children’s skill development. For example, children who experienced higher levels of warm flexibility during infancy

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were more likely to have higher levels of social responsiveness when interacting with their mothers at 4 years of age (Steelman, Assel, Swank, Smith, & Landry, 2002). In addition to this impressive direct effect, this maternal strategy had several indirect effects, one of which was through a positive influence on children’s language across 12–54 months. Maternal disciplinary preferences also mediated the relation between warm responsiveness and later social skills such that a mother who was warmly responsive was less likely to use physically punitive techniques. This, in turn, facilitated children’s cooperation during social interactions. Through factor analysis, we found that contingent responsiveness loads on the same factor as avoidance of restrictiveness (Landry et al., 2006). This makes sense given that restricting young children’s behaviors shows a disregard of their interests. It is important to note that the majority of maternal restrictions were not attempts to keep children safe but rather were imperative statements that limited the child’s actions (e.g., ‘‘Don’t put it in there’’ or ‘‘Stop pouring’’ while child engaged with toys). In a longitudinal study of children born at VLBW, high levels of restrictiveness predicted lower levels of initiating and cognitive skill for term and VLBW born children from 6 to 36 months of age (Landry et al., 1997). What was most striking about these results was the significantly greater influence that restrictiveness had for the children born at HR as compared to those at lower medical risk or term born. Mothers who frequently restrict medically high-risk children’s attempts to interact socially or explore their environment may interfere with the children’s learning to act on their own interests. This may occur, in part, because attempts to take an active role do not result in a predictable response from their caregivers. Thus, children whose early experiences are frequently interrupted with requests to stop doing something are not able to assume the development of independence in their learning at a normal rate.

6.5. Rich language input The quality of language input is well known to positively influence language development (Risley & Hart, 2006). However, it also can have a positive effect on children’s early executive processing skills that are thought to lay the foundation for later, more complex goal-oriented behaviors. In our longitudinal study of parenting and development of infants born at VLBW, greater maternal use of rich language input during the early preschool period was found to support children’s ability to sequence their behaviors at higher levels during an independent goal-directed play task and a search retrieval task (Landry, Miller-Loncar, Smith, & Swank, 2002). Verbal support (e.g., explanations, analogies) guides children to understand how to sequence their behavior to solve problems. This includes helping them understand associations between objects and their actions as well as verbal guidance that references specific planning strategies (Freund,

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1990). With this form of verbal support, children increase their capacity for self-regulation and ultimately become competent in solving problems on their own. Rich language input also was found to predict both verbal and nonverbal reasoning abilities at 6 years of age, with the relation between maternal language and nonverbal reasoning being stronger for those born at VLBW compared to term children (Smith, Landry, & Swank, 2000). Given that VLBW children have specific deficits in visual-motor problem solving, it is likely that this type of support that occurs during everyday interactions can help children with concept formation related to objects.

6.6. Bidirectionality of influence In correlational studies, the evaluation of the influence of parenting behaviors on child development can only be inferred, as there is always the possibility of bidirectional influences. This would mean that relations could be due to the child’s effect on the parent’s behavior, rather than vice versa or both. One means of further examining this question in a correlational, longitudinal study is through the use of cross-lag analyses. We previously examined cross-lag panel analyses from mother–child interactions in two studies with VLBW born children (Landry et al., 2000) and those with SB (Lomax-Bream et al., 2007b). Although the time periods varied slightly (1, 2, and 3 years of age in the VLBW cohort; 1, 1½, and 2 years of age for SB), the statistical approach was the same. In multiple models, the crosslag coefficients from mother to child with those from child to mother were compared to determine direction of influence. With the VLBW cohort, mothers’ maintaining the child’s focus of interest related to cognitive language skills from 1 to 2 years and 2 to 3 years of age, and to warm responsiveness across these same ages. However, there were no significant relations from the child’s social constructs to mothers’ maintaining, providing support that the direction of influence was from mothers’ maintaining to the child’s social behavior. The two child social constructs included responsiveness, which measures the child’s ability to respond to maternal requests, and initiating, which examines the child’s ability to guide maternal attention to an activity of interest. With the SB cohort, the maternal responsiveness construct included maintaining, warm sensitivity, and contingent responsiveness and the child construct was language skill. The results of the cross-lag analysis revealed that both the 1-year child language and responsiveness parenting constructs were significantly related to the 1½-year child language construct. In addition, both the maternal and child 1-year constructs were related to the 1½-year parenting. However, at the later ages, only the 1½-year parenting predicted the 2-year parenting construct. Thus, consistent with the ‘‘back and forth’’ influence noted by others (Bell, 1988; Braungart-Rieker, Garwood, & Stifter, 1997), at the

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earlier age bidirectional influences were seen, while at later ages, the relation became one of mother effects on the child.

7. Evidence from Longitudinal Studies for Closing the Learning Gap for At-risk Children Two findings needed to support the critical role of responsive parenting in promoting children’s development are: (1) relations of high responsive levels with more positive trajectories of cognitive and social development as compared to slower developmental progress when responsiveness is absent and (2) evidence that the influence of responsive parenting is even greater for children with special needs. Landry et al. (2001) evaluated early responsiveness among families from lower SES backgrounds and for groups of term and VLBW born children, with a particular interest in whether early responsiveness played a special role in development or whether consistency in this parenting style over time was necessary for optimal outcomes. Four maternal clusters based on warm and contingent responsiveness behaviors observed early in infancy and toddlerhood (i.e., 6, 12, 24 months) and the preschool period (i.e., 3, 4 years) were identified: mothers who demonstrated high responsiveness across both developmental periods, mothers who demonstrated minimal responsiveness across both periods, mothers who showed high responsiveness during infancy but declined in the toddler period, and mothers who showed low levels during infancy with some increase in the toddler period. Children born preterm, including those born with the highest medical risk, who experienced consistently high maternal responsiveness were more likely to perform at levels similar to full-term children on social and cognitive development through entry into kindergarten. In contrast, all children parented with minimal responsiveness showed the poorest development. This was particularly detrimental for the HR VLBW children, who showed only 7.6 months of skill growth for every 12 months. This suggests that the impact of unresponsive parenting on children’s deficits may be twofold if the caregiving environment lacks responsiveness and the child is at greater risk for developmental problems. The importance of an early responsive caregiving environment was further demonstrated when the children were followed through 8 years of age, even after controlling for parenting during the school-age years (Landry et al., 2006). With this same cohort of children, mothers’ responsiveness predicted children’s reading comprehension skills at 8 years of age (Taylor et al., 2006). However, a significant interaction revealed that maternal responsiveness had a greater impact on later comprehension skills with children who had lower, rather than higher, cognitive abilities. This was most evident when mothers demonstrated high responsiveness in infancy.

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Longitudinal studies also may provide information about specific aspects of responsive parenting for promoting different areas of social and cognitive development. In this same cohort of children, those who received high levels of rich language input that provided information about labels and connections between objects and actions had significantly higher levels of reading achievement at 10 years (Dieterich et al., 2006). If children experienced this type of language input during the toddler period, they were more likely to have higher levels of executive processing skills during 1st grade (Landry et al., 2002). In our longitudinal study, inconsistency in responsive parenting appeared to be less optimal than consistency for children’s development, but was better than the absence of responsiveness. Although this was particularly true for growth in cognitive skills, children’s ability to respond in social interactions with their mothers showed a more complex picture. Those born term showed similar trajectories of growth in social skills if their mothers had high responsiveness at least across infancy. In contrast, the medically high-risk VLBW children required consistency in responsiveness across infancy and early childhood for the same level of skill. This may be due to the difficulty that the high risk, VLBW children had in internalizing the regulatory capacity and motivation to continue to respond socially when maternal responsiveness decreased. In this way, inconsistent responsiveness may disrupt the internalization of social regulatory behaviors for a group of children at higher risk for problems in social development. Our research is consistent with others’ longitudinal research on maternal responsiveness. For example, Bradley, Caldwell, and Rock (1988) measured responsiveness using the parental involvement and family participation subscales from the HOME inventory and found that early responsiveness predicted 10-year social behaviors, while cognitive outcomes were predicted by stability in parental involvement through age 10 years. Wakschlag and Hans (1999) also found maternal responsiveness in infancy to predict fewer behavior problems in middle childhood after controlling for concurrent parenting behaviors.

8. Evidence from Experimental Findings for Closing the Learning Gap Based upon results from our longitudinal studies of infants born at VLBW (described above), we set out to investigate whether parents of children born at risk could be assisted to enhance their specific responsive parenting practices to promote their children’s optimal developmental outcomes. Toward that end, we developed a responsive parenting intervention for mothers of infants and assessed its effectiveness through a systematic, randomized control design.

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Our intervention curriculum, known as ‘‘Playing and Learning Strategies’’ (PALS) consisted of 10 home-based sessions, each lasting about 1.5 h. Sessions were conducted one-on-one by a trained facilitator. Facilitators used a detailed curriculum that included scripts to guide interactions with mothers, probing questions, and points for discussion, an approach necessary to ensure systematic implementation across families. However, facilitators were trained to use the curriculum in a flexible manner to meet the learning needs of individual families. The format for each PALS home visit included: (1) asking mothers to review their experiences across the last week related to their efforts to try the targeted behaviors; (2) describing the current visit’s target behavior; (3) watching and discussing with mother the educational videotape; (4) videotaping mothers interacting with their infants, with coaching from facilitator, in situations that mother selected (e.g., toy play, feeding, bathing); (5) supporting mothers to critique their behaviors and their infants’ responses during the videotaped practice; and (6) planning with mothers for when they could practice the targeted behaviors over the next week. Target behaviors were chosen for their support of premature infants’ immature abilities in signaling interest, shifting attention, organizing behaviors, and developing early communication skills. In the control condition, known as Developmental Assessment Sessions (DAS), families received the same number of home visits and their children received attention and informal assessment from the facilitator, but no parenting intervention was provided. Mothers and infants were assessed at four time points (i.e., Pre, Interim, Post, 3-month Follow-up), and the timing of intervention, as well as assessment administration and scoring, was conducted using corrections for infants’ gestational age. Growth curve modeling was used to examine change in maternal responsive behaviors and infant skills. The experimental study cohort included 264 mother–infant pairs from lower–middle to low SES backgrounds, whose study participation occurred when the infant was about 6–10 months of age. The VLBW infants were divided into two groups: LR, based on the presence of acute respiratory disorders and/or mild IVH, and HR, based on the presence of chronic respiratory disorders and/or more severe grades of IVH without hydrocephalus (e.g., Landry et al., 2001). A group of healthy full-term infants were recruited to match the demographics of those born VLBW. Families who spoke either English or Spanish were recruited as the study could be implemented in either language. Further information regarding the sample and procedures can be found in Landry, Smith, and Swank (2006).

8.1. Effects of PALS on maternal behaviors Positive improvement in mothers’ skills was found across a range of targeted behaviors in favor of mothers in the PALS as compared to DAS condition. Many effects were found for parents irrespective of the type of infant they

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were parenting. For example, following intervention, mothers in the PALS condition responded to children’s signals and learning needs in ways that were prompt, contingent, and appropriate more often than those in the DAS condition. PALS mothers also maintained their infants’ attention more, redirected less, and stimulated their children’s language development more through verbal scaffolding, labeling of objects and actions, and verbal encouragement. PALS mothers across all risk groups also showed more positive changes in warm sensitivity and voice tone compared with DAS mothers. Several findings were specific to the mothers of children born VLBW. For example, PALS mothers of LR VLBW infants showed higher levels and greater increases in positive affect than did DAS mothers of similar infants. PALS mothers of infants born HR VLBW used significantly lower levels of restrictive behaviors, and showed slower increases in these behaviors over time than did DAS mothers of VLBW infants.

8.2. Effects of PALS on infant skills Infants whose mothers received PALS demonstrated significantly greater increases in their use of words and showed lower levels of negative affect while playing with toys, particularly for those born HR VLBW. A trend for higher levels and greater increases in infant cooperation with maternal requests also was found if their mothers were in PALS versus DAS. Evidence of the ability to internalize the skills developed when interacting with their mothers was found in the target infants’ greater ability to use toys in goal-directed, functional, and more complex ways when playing alone. There was some evidence that the changes the target infants displayed with their mothers generalized to interactions with a novel adult. For example, infants whose mothers had received PALS, as compared to DAS, showed a greater increase in the use of words during interactions with the examiner, and those born LR VLBW were more cooperative with the examiner.

8.3. The influence of aspects of responsiveness on domains of infant development To address the question of whether different aspects of responsiveness were important in understanding the intervention effect on different skill domains, we first examined whether there was empirical support for considering different aspects within a broader construct of responsiveness. Such support was found through the identification of underlying factors that related to four types of responsiveness behaviors. These were stable over time and, in general, across contexts. The four factors were: (1) contingent responsiveness/lack of negative emotionality, (2) positive emotional

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support, (3) responses to infant foci of attention, and (4) quality of language input. This empirical support is complementary to theoretical descriptions of these behaviors. Results from mediation models demonstrated that the different aspects of responsive behaviors, supported by the factor analyses, showed significant relations with cognitive and emotional skills, and that change in these maternal behaviors mediated the intervention effect on two infant outcomes: cooperation and use of words. This suggested that in order to optimize infant cooperation, mothers needed to show responsive behaviors that cut across theoretical frameworks and provided different types of support. This finding was applicable to children in all risk groups.

8.4. Evidence for individual profiles of parenting Further examination of the data from the PALS study (Guttentag et al., 2006) revealed that mothers could be grouped into four classes, or profile groups, that demonstrated distinct patterns of parenting skills prior to intervention. The four groups included mothers who demonstrated: (1) relatively low levels of warmth, responsiveness to signals, rich language input, and maintaining infant’s attentional focus; (2) moderate levels of each of these behaviors; (3) relatively high levels of each of these behaviors; and (4) a mixed style consisting of relatively high rich language input and maintaining, but low levels of warmth and responsiveness to infant signals. The emergence of this mixed profile group provided additional support for proposals that a responsive parenting style is comprised of distinct components that parents may possess to a greater or lesser degree, rather than only as a whole on a continuum. While no infant characteristics, including biological risk status, predicted the preintervention profile group membership, parenting beliefs did. Mothers with more child-centered parenting beliefs were significantly more likely to be in the relatively higher profile group than in the lower or mixed group. Following intervention, mothers who had been randomly assigned to the PALS intervention, regardless of initial profile group status and infant risk status, were more likely than comparison mothers to transition from weaker to stronger profile groups. Social support was the only significant predictor of positive change among intervention mothers. That is, mothers who perceived the availability of more social support were significantly more likely to retain their initial responsive parenting skills, and to increase, rather than decrease, their responsive behaviors over the course of the intervention. Thus, parenting beliefs and social support, both potentially modifiable maternal characteristics, appear to be important components to address when attempting to enhance and sustain mothers’ responsive parenting practices.

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8.5. The optimal timing for responsive parenting intervention Families who participated in PALS during infancy were re-randomized into either the Playing and Learning Strategies II or a Developmental Assessment condition (DAS II) when their children were, on average, 26 months of age (term, n ¼ 80; VLBW, n ¼ 86). This resulted in four study groups that allowed for the examination of whether a second toddler phase of intervention was needed to support mothers’ use of responsive behavior into the next developmental period; PALS I/DAS II, n ¼ 33; PALS I/PALS II, n ¼ 34; DAS I/PALS II, n ¼ 50; DAS I/DAS II, n ¼ 49. Intervention influences were found for all aspects of maternal responsiveness and child outcomes. However, the most optimal timing of the intervention was dependent on the type of support the maternal behavior provided to a child and the child’s biological risk status. Responsiveness behaviors best facilitated by PALS I included those that provided warmth and nurturance, whether or not mothers also received intervention during the toddler period. Warmth is described in the attachment framework as critically important across the first year of life for establishing a secure and trusting relationship between a mother and her infant (e.g., Ainsworth et al., 1978). Our results suggest that there is a unique salience about the early developmental period for intervention to support mothers’ expressions of warmth that will extend beyond the first year of life. In contrast, responsiveness behaviors that provided rich verbal input were best supported by PALS II even if mothers did not receive PALS I. Maternal responsiveness behaviors that were more complex because they required the mother to adopt and respond to the child’s changing developmental needs (e.g., contingent responsiveness, maintaining) required both phases of PALS for optimal results. Although the timing of intervention effects was found irrespective of children’s biological risk, several effects were especially salient for mothers of infants born at VLBW. For example, while PALS I resulted in lasting effects on mothers’ warmth across risk groups through the toddler period, those parenting children born HR, VLBW showed an added benefit if they also received PALS II. Higher levels of warmth have a stronger relation with more positive growth in cognitive and social skills for these children than for those born at term (e.g., Landry et al., 2001). An advantage for a later ‘‘dose’’ of PALS for mothers of HR, VLBW infants may be due to the mothers’ need for further facilitation of their efforts to respond in warm sensitive ways at a time when their toddlers are known to show considerable variability in organizing behavior and engaging in interactions with their caregivers (e.g., Landry, 1995). A second example of differential effects for children born at VLBW was the intervention’s effect on maternal expression of positive affect, another responsiveness behavior described in the attachment framework as critically important during the first year of life. For

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mothers parenting children born at VLBW, positive affect was best facilitated by PALS if it occurred at least during the early period, and this influence was not seen for mothers of term children. One focus of PALS I was to help mothers appreciate and receive pleasure in their infants’ efforts. This focus seems to be particularly helpful for those parenting VLBW children, given their children’s greater vulnerability in learning new behaviors, and, perhaps, greater maternal concern regarding development. Facilitating mothers in this early period to notice and take pleasure in their infants’ attempts to interact, appears to promote a greater bond and acceptance of their children’s behavior in spite of their children’s risk status.

9. Summary and Conclusions, Implications and Future Directions 9.1. Summary and conclusions This chapter has described a body of research that demonstrates a common set of deficits across three groups of children at risk for later learning problems, and the importance of responsive parenting for supporting their development. We have reviewed evidence that children with different diagnoses (i.e., children with DS, SB, and those born preterm at VLBW) show early developmental vulnerability in several interrelated areas which impact their ability to learn and grow. These areas include motor control, attention regulation, and goal-directed behavior. Together, these foundational skills help children to take in information from the environment, organize and execute behavioral responses, and thus learn and build more complex skills through active engagement with objects and people. When disabilities or developmental delays hamper children’s abilities in these areas, they are at increased risk for continuing learning problems. They are also more vulnerable and may be more reliant than typically developing children on the support and scaffolding they receive through sensitive, responsive parenting. Responsiveness has been defined in our research as a group of distinct but related caregiving behaviors that cross theoretical frameworks and have potential to provide specialized support for at-risk children to be able to learn from interactions. This support can be viewed as comprising two major areas: affective/emotional support and cognitive support. In order to optimally enhance at-risk children’s development, both types of support should be provided during the early developmental years. Research has shown that providing one or the other (e.g., warmth without cognitive support, or rich language input without emotional sensitivity) is not sufficient. A variety of behaviors under the rubric of responsive parenting, encompassing both the major areas of support (e.g., maintaining children’s

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focus of attention, contingent responsiveness, rich language stimulation), may be able to buffer the effects of specific early core deficits so that they are less likely to interfere with the at-risk child’s learning. We have illustrated through a program of research with cross-sectional studies how different aspects of responsiveness support the development of all three groups of children in similar ways. An exception may be maternal directiveness, where there is evidence that some children show greater compliance with requests (though not necessarily stronger cognitive skills) when provided with higher levels of this form of support for longer periods of time. The essence of a responsive parenting style is paying close attention to the child’s communicative signals and responding promptly with supportive behaviors that are linked to the child’s signals. Thus, regardless of the child’s diagnosis, responsive parenting practices may support the individual child’s development by providing support where the child shows a need (e.g., encouragement to continue attending to an object of interest, assistance with visually guided reaching, hand-over hand assistance with goal-directed play actions, etc.). This high level of attunement and matching responses to the child’s needs has been shown to be particularly important for children born preterm, who may be more easily overwhelmed by too much stimulation, less adept at providing clear signals to the parent, and/or slower to organize a coordinated behavioral response than full-term, nondisabled children. Rich language input also has been shown to be a strong predictor of children’s later verbal and nonverbal reasoning abilities, and the relationship between maternal language stimulation and children’s later reading skills development was found to be even stronger for children at risk with low cognitive ability. Typically developing children appeared to benefit from responsive parenting practices as well, but they show greater resiliency in the face of suboptimal parenting and more stable developmental trajectories over time than at-risk children. Evidence has been presented that supports the above conceptualization by demonstrating, for example, that when parents of VLBW infants provide support for their focus of attention, their infants show higher levels of play behavior than when parents make requests that require their infants to shift their attention. By matching specific supportive behaviors to their infants’ needs, parents can positively impact VLBW children’s ability to focus and learn. Thus, parents can alter their children’s developmental trajectory in the positive direction, even amidst the challenges of poverty and their child’s medical vulnerabilities. These findings provide further support for recent evidence from basic science research highlighting the importance of the environment during the early years for brain development. Most promising are recent findings that a responsive parenting style can be taught to parents who may not previously have possessed these skills, that these skills and the positive impact on the child can be achieved in a relatively brief time frame, and that there may be optimal developmental

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time windows for focusing on specific aspects of the responsive parenting style for maximum benefit. For example, during the first year of life it appears to be most critical for parents to become emotionally attuned to their VLBW infants, establishing a foundation of warmth, positive affect, and lack of unnecessary restrictiveness. During toddlerhood, the focus of responsive parenting must include provision of rich language stimulation (e.g., labeling objects and actions, describing and connecting objects to their functions) in order to best support VLBW children’s cognitive and language development. Contingent responsiveness needs to be provided consistently across infancy and toddlerhood to support optimal outcomes. This chapter also highlights the benefits of using longitudinal data to evaluate the influence of parenting behaviors on child development. There are numerous advantages of longitudinal studies over cross-sectional studies. Cross-sectional snapshots may provide a misleading picture of the impact of parenting on child development. For example, differences in outcomes may reflect factors already existing pre-onset and they do not allow researchers to learn how the parent–child relationship develops over time. In contrast, longitudinal studies can evaluate the development of parent– child relationships over time, as these are fundamentally longitudinal in nature. Researchers can model both the cross-sectional and time series trends as well as conduct cross-lag and/or growth curve analyses. Crosslag analyses are particularly helpful to respond to questions of directionality in this research (e.g., is impact from parent to child, or child to parent?). In this way, researchers can evaluate change and consider time precedents. It is important to note, however, that correlational studies do not demonstrate causality; experimental designs are required for this purpose.

9.2. Implications and future directions One important implication of the reviewed literature is that it is profitable to look at commonalities in children’s developmental issues and areas of vulnerability across different diagnostic categories. We have shown how children with diagnoses as diverse as SB, DS, and prematurity/VLBW show weaknesses in some similar areas, and that responsive parenting behaviors have been correlated with positive developmental outcomes within each of these populations. Often, bodies of research literature focus on the development of children with specific disorders, with little attention to commonalities and underlying developmental processes across these diagnostic groups. The fact that we do see similarities in early learning problems and the potential for responsiveness to parent-focused intervention across several types of at-risk populations of children suggests a level of robustness and generalizability of the conceptual framework of responsive parenting. However, to truly make this generalization, it is necessary to

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evaluate responsive parenting interventions using samples from additional diverse risk groups and random assignment to treatment conditions. There are several implications for future directions for this line of research. Continuing to investigate similarities and differences in the impact of specific parenting behaviors on children from different developmental risk groups (i.e., different medical or genetic disorders) will contribute to the literature on those disorders as well as to the responsive parenting literature. In addition, examining the impact of timing of intervention within different groups of at-risk children would allow comparison to the findings for children born at VLBW, leading to further understanding of these results. Establishing collaborations with clinicians who provide Early Childhood Intervention services to young children with disabilities may be beneficial in several ways. For example, these professionals have expertise in supportive environmental modifications that may enhance children’s ability to respond to parents’ efforts, such as adjustments in physical positioning to support upper body control, or specific techniques for working with children with visual or hearing impairments. Another example of the benefits of collaboration with ECI professionals is the potential for blending training in responsive parenting practices with the kinds of targeted skills development work that these clinicians typically provide. Such an approach may lead to greater willingness in parents to take a more active role in their child’s ECI activities. Carefully developed, randomized control designs are needed to investigate these issues. The role of social support for parents of at-risk children also needs further attention. Raising a child with special needs adds a level of complexity and stress to the typical challenges of parenting, which may be exacerbated or ameliorated by the quality of the parents’ social support system. Understanding the conditions under which support networks function most effectively, and exploring ways to build or enhance such networks for more isolated or discordant families may add a valuable component to the intervention research. We have begun to investigate these ideas by showing that providing community mentors to supplement a responsive parenting intervention with social support had a positive impact, over and above the parenting curriculum, on low-income mothers and their young children. We also showed in a separate study that among mothers receiving a responsive parenting intervention, social support predicted positive change in parenting behaviors. This area is important to continue to pursue, since families’ social networks can serve as an ongoing source of support and resources beyond the time-limited period of a parenting intervention. As we move forward toward establishing empirically supported approaches to optimizing the development of children at risk for later learning problems, it is important to recognize the critical role of responsive caregiving practices. By using a general set of responsive interaction skills, parents can address core areas of weakness in children with diverse

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developmental profiles and diagnoses. In this way, a consistently responsive environment can begin to close the learning gap and help these children reach their potential as they grow.

ACKNOWLEDGMENTS This study was supported, in part, by NIH grants HD36099, HD25128, and HD046609.

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C H A P T E R

T H R E E

Trisomy 21: Causes and Consequences Jeannie Visootsak and Stephanie L. Sherman Contents 61 64

1. Introduction 2. Major Cause of DS: Meiotic Nondisjunction in Oocytes 3. Prevalence and Survival of Individuals with DS Throughout the Life Span 4. Etiology of DS-Associated Medical Disorders 5. Neurodevelopmental Outcomes of Comorbid Medical Conditions in DS 6. Psychiatric and Neurobehavioral Issues in DS 7. Summary Acknowledgments References

72 77 82 87 89 90 90

Abstract Trisomy 21, leading to Down syndrome (DS), is the most common genetic cause of mental retardation, specific birth defects, and medical conditions. Clinical and epidemiological studies over the last 100 years have been primarily focused on infants with DS to determine the prevalence, cause, and clinical significance of the syndrome. Studies to understand the consequence of trisomy 21 with respect to the variability of specific DS-associated medical conditions and to determine how these conditions influence cognitive and behavioral outcomes are only just beginning. Here, we provide an overview of current clinical and epidemiological research that characterizes the causes of trisomy 21 and its medical consequences.

1. Introduction In this review, we will describe epidemiological approaches to understand the causes and consequences of trisomy 21, the genetic condition leading to Down syndrome (DS). To be clear, epidemiology and genetic

Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia 30033 International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00003-7

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2008 Elsevier Inc. All rights reserved.

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epidemiology provide approaches to study the patterns and causes of healthrelated traits in defined populations, with the latter paying specific attention to potential susceptibility genes and their interaction with environmental factors. Results from such studies form a foundation for interventional medicine. These types of clinical research studies are done best in parallel with basic science approaches that use experimental model systems to uncover underlying mechanisms that cause susceptibility. Although we will not review such studies here, they show tremendous promise to delineate the biological alterations that result from the extra dosage of chromosome 21 genes (for an example of a recent review, see Reeves & Garner, 2007). For DS, observational studies began in the mid-1800s when several astute physicians described groups of patients who had mental retardation and short stature along with specific facial characteristics including upslanting palpebral fissures, epicanthal folds, flat nasal bridge, and protruding tongue (Down, 1866; Esquirol, 1838; Se´guin, 1846, 1856). J. Langdon Down, after whom DS was named, contributed significantly to the progress of the study of DS by emphasizing that this set of clinical findings constituted a distinct entity, and affected individuals could be distinguished from the heterogeneous group of all those with intellectual disabilities. In an excellent review of the history of DS, Rynders and Pueschel (1982) continued the story of the recognition of DS through the late 1800s and early 1900s. Once DS was recognized as a separate medical condition, it became possible to identify determinants that play a role in its occurrence. The first to be linked to DS was increased parental age at the birth of the infant with DS (e.g., Thurston & Jenkins, 1931; Van der Scheer, 1927). Shortly thereafter, Penrose demonstrated clearly that advanced maternal age, not paternal age or birth order, was the key determining factor for DS (Penrose, 1933, 1934). In 1954, Penrose further suggested that there could be different causes of DS: he observed that approximately one-third of cases in his series were not associated with maternal age (Penrose, 1954). Further, in families with two affected siblings, the mean maternal age was lower compared to the general sample of infants with DS. With remarkable insight, he posited several plausible causes of DS: genetic susceptibility, unbalanced chromosomes caused by translocation, and factors associated with fluctuating endocrine disturbance. The next major advance in DS, and in fact human medical genetics as a whole, came with the advent of chromosome staining and karyotyping, leading to the ability to characterize the human chromosome complement. With this technological advance, the etiology of DS was identified in 1959 as the presence of an extra chromosome 21 (Book et al., 1959; Ford et al., 1959; Jacobs et al., 1959; Lejeune, 1959). More recent studies have shown that 95% of individuals with DS have an extra chromosome 21 as a result of meiotic nondisjunction, or the abnormal segregation of chromosomes

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Meiosis I error

Meiosis II error

Homologs don’t separate

“Meiosis II” error

Homologs don’t separate

Sisters chromatids don’t separate

Sisters chromatids don’t separate

Figure 3.1 Illustration of the types of meiotic chromosomal nondisjunction errors in females. Only 1 of the 23 pairs of homologous chromosomes is shown for simplification. ‘‘MII’’ refers to meiosis [MII] errors that might be initiated in MI.

during gamete formation (Fig. 3.1). Of the remaining 5%, less than 1% is due to somatic mosaicism and the rest to chromosome 21 translocations. Interestingly, in 1964, Penrose proposed that the maternal age–dependent cases of DS could be due to meiotic nondisjunction, but succinctly stated that ‘‘The traditional explanation that the ovum becomes abnormal with age is unhelpful unless some attempt is made to link the supposed deterioration with the observed distribution curve.’’ (i.e., observed maternal age pattern) (Penrose, 1964). In summary, by the early 1960s, the syndrome hallmarks were described, the cytogenetic causes identified, and the most significant risk factor determined, namely, maternal age. DS, or trisomy 21, is now one of the most widely studied human aneuploid conditions. It is estimated that about 80% of conceptuses with an extra chromosome 21 are spontaneously lost during gestation, while some 20% are carried to term. In contrast, trisomies of other chromosomes seldom survive through gestation (for review, see Hassold & Hunt, 2001). More importantly, once medical complications at birth are appropriately treated, individuals with DS can live, on average, into their 50s or 60s, with full and productive lives if important educational, medical, and societal resources are provided. This review will survey the current field to focus attention on gaps in research. Thus, we will omit a large body of significant literature that truly pushed the field ahead to allow advances in technology and resources to make their mark. First, we will review the progress that has been made to

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understand the leading cause of trisomy 21, namely, meiotic nondisjunction. Next, we will review the aspects of mortality and morbidity among individuals with DS. We will show that the previous focus on the prevalence and survival of individuals with DS around birth has shifted to that in adults due to the significantly increased survival of individuals with DS over the years. We will outline some of the medical conditions that are prevalent among individuals with DS and finally discuss their influence on cognition, behavior, and mental health.

2. Major Cause of DS: Meiotic Nondisjunction in Oocytes As emphasized by Penrose in the early 1900s, the ability to identify the biological mechanisms and associated risk factors for trisomy 21 has benefited from studies that focus on a specific type of error. Soon after the chromosomal basis of DS became known in 1959, cytogenetic techniques allowed investigators to distinguish the underlying types of chromosome errors: (1) standard trisomy 21, (2) chromosome translocations, and (3) mosaicism (one normal cell line and one trisomic cell line). The use of chromosome heteromorphisms and DNA polymorphisms led to the ability to categorize chromosome 21 nondisjunction errors by parental origin (e.g., whether the error occurred in egg [‘‘maternal’’] or sperm [‘‘paternal’’]) and type of error (e.g., whether the error was initiated in meiosis I [MI] or meiosis II [MII] [Fig. 3.1] or postzygotic mitotic). To date, the largest study to categorize these nondisjunctional errors is the National Down Syndrome Project (NDSP), a population-based study conducted from 2000 to 2005 at six national sites representing 11% of annual births in the United States (Freeman et al., 2007). Through this population-based study, 907 infants born with DS were characterized based on the type of chromosome error. For a comparison group to examine risk factors for nondisjunction, 977 infants born without DS drawn from the same geographical areas were enrolled. Based on results from the NDSP (Table 3.1) and other population-based series (e.g., Gomez et al., 2000; Mikkelsen et al., 1995), over 90% of nondisjunction errors leading to trisomy 21 occur in the oocyte and the majority of those occur during MI. This pattern is similar to other trisomies due to chromosome nondisjunction (e.g., Hassold & Hunt, 2001). To date, most studies have focused on searching for risk factors related to maternal nondisjunction of chromosome 21 due to its frequent occurrence. We will do the same here in our review. A recent review provides an overview of our limited knowledge of paternal nondisjunction and its associated risk factors (Sherman et al., 2005).

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Table 3.1 Origin of trisomy 21 Origin

Maternal Meiosis I (MI) Meiosis II (MII) Stage unknowna Subtotal Paternal Meiosis I (PI) Meiosis II (PII) Stage unknowna Subtotal Postzygotic mitotic Total informative cases (all)

N

Proportion

Percent

529 179 21 729

MI/(MI þ MII) ¼ 529/708 MII/(MI þ MII) ¼ 179/708

74.7 25.3

M/All ¼ 729/782

93.2

13 18 1 32 21 782

PI/(PI þ PII) ¼ 13/31 PII/(PI þ PII) ¼ 18/31

41.9 58.1

P/all ¼ 32/782 Mitotics/All ¼ 21/782

4.1 2.7

Stage unknown ¼ DNA markers in the centromeric region were not informative. Data taken from Freeman et al. (2007).

a

2.1. Advanced maternal age Advanced maternal age is possibly, by far, the most significant factor related to chromosome 21 nondisjunction. We and others have shown that the increased age of the mother at conception exerts its influence on chromosome segregation in the egg (Sherman et al., 2005; e.g., Antonarakis et al., 1992; Ballesta et al., 1999; Muller et al., 2000). That is, advanced maternal age is not observed among mothers whose offspring received the extra chromosome 21 from a nonmaternal source. Mothers of offspring with a nondisjunction error in spermatogenesis (paternal error) do not have an increased age (Petersen et al., 1993; Sherman et al., 2005; Yoon et al., 1996). Similarly, advanced maternal age is not present among women with an offspring with DS due to a postzygotic mitotic error (e.g., Antonarakis et al., 1993; Sherman et al., 2005) or a chromosome translocation (inherited or de novo) (Hook, 1983). Interestingly, advanced maternal age is a risk factor for both MI and MII maternal nondisjunction errors (e.g., Antonarakis et al., 1992; Muller et al., 2000; Sherman et al., 2005; Yoon et al., 1996). The timeline for oogenesis compared with spermatogenesis points to possible error-prone stages of egg formation. Meiosis is initiated in oocytes during fetal life around 12 weeks of gestation. After homologous chromosomes synapse and initiate recombination, meiosis arrests and remains in this state until the oocyte is recruited for ovulation. Thus, MI spans some 10–50 years depending on when that specific oocyte is ovulated. MII only extends over the 3- to 4-day ovulation period and is completed after fertilization. This timeline differs significantly

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from that in spermatogenesis which begins at puberty; cells entering meiosis move from one stage to the other without delay. Plausible explanations for maternal age–related nondisjunction in both MI and MII include, but are not limited to (1) an accumulation of toxic effects of the environment during the arrested state of the oocyte, (2) a degradation of meiotic machinery over time while in the arrested state, leading to a suboptimal resumption of MI and MII, and/or (3) a change in ovarian functioning due to suboptimal hormonal signaling. Most likely, several processes are affected by advanced maternal age; thus, more than one or all of these hypotheses may prove to be true. Several excellent reviews of hypotheses to explain the maternal age effect are available (e.g., Eichenlaub-Ritter, 1996; Gaulden, 1992) along with a recent review of hypotheses related to biological aging of the ovary (Warburton, 2005). One potential way to understand the maternal age effect is to examine maternal health factors and environmental exposures among mothers who have had a recognized pregnancy with chromosome 21 nondisjunction. Once a risk factor for nondisjunction is identified, it can be further evaluated in the context of biological aging to provide insight into the mechanism causing the maternal age effect. For example, biological aging of the ovary is characterized by a decline in the total oocyte pool, a decline in the number of antral follicles maturing per cycle and in reproductive hormonal changes. A decrease in the number of maturing follicles has been hypothesized to decrease the probability that one of them will be at the precise stage necessary for optimal response to follicle stimulating hormone (FSH), the trigger for ovulation. Warburton (1989) put forth the ‘‘limited oocyte pool’’ hypothesis suggesting that under these circumstances, the follicle ‘‘selected’’ for ovulation may be one whose oocyte is under- or overripe and thus more susceptible to chromosome malsegregation. In an excellent review, Warburton (2005) found inconsistent results among the studies that have examined the relationship between nondisjunction and biological aging of the ovary. For example, Freeman et al. (2000) found that mothers with a maternally derived chromosome 21 nondisjunction error were more likely to have a reduced ovarian complement (congenital or surgical) compared with mothers of infants without DS (odds ratio [OR] ¼ 9.61; 95% confidence interval [CI] ¼ 1.18–46.3). Women with reduced ovarian complement have a smaller oocyte reserve and thus would ‘‘mimic’’ an older woman. However, this observation has not been confirmed. Other indirect evidence to support ovarian aging specifically for chromosome 21 nondisjunction was reported by van Montfrans et al. (1999). They examined serum FSH levels taken on menstrual days 2, 3, or 4 in three consecutive cycles from 118 women who had a child with DS to 102 women who had at least 2 children and no history of a child with DS. Women were matched for age (all under age 40 years and no difference in group means) and for menstrual cycle history. They found higher levels of FSH, an indicator of decreased ovarian reserve, among

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women with an infant with DS compared with controls. Results from their follow-up study that measured estradiol and inhibin B on this same study group suggested that the elevated FSH levels reflected early depletion of the primordial follicle pool (van Montfrans et al., 2002). A more recent case– control study compared maternal serum anti-mullerian hormone (AMH) levels, another marker for ovarian reserve. They measured AMH on banked serum collected for first trimester prenatal screening among 25 women who had a pregnancy with DS and among control samples that included women with an unaffected pregnancy and were individually matched for maternal age (within 2 years), gestational age (same completed week), and duration of storage (within a month). Although the sample size was limited, they did not find any differences in AMH levels during pregnancy between the women with a DS fetus and their controls (Seifer et al., 2007). In a recent review, Warburton (2005) concluded that much of the evidence to date suggests that, if processes of ovarian aging are related to chromosome nondisjunction, they probably involve factors other than those measured by oocyte or antral follicle pool size and reproductive hormone levels.

2.2. Recombination patterns along chromosome 21 alter the risk for maternal nondisjunction Aside from maternal age, only one additional factor has been shown to be unequivocally associated with maternal nondisjunction, that is, altered recombination patterns. Warren et al. (1987) provided the first evidence that a proportion of maternal nondisjunction errors was associated with reduced recombination along chromosome 21. In addition to the absence of an exchange, the location of an exchange along the nondisjoined chromosome is an important susceptibility factor for chromosome 21 malsegregation (Lamb et al., 2005a; Sherman et al., 2005). Briefly, examination of recombination along the maternal nondisjoined chromosome 21 has suggested three susceptibility exchange patterns: (1) no exchange leads to an increased risk of MI errors, (2) a single telomeric (i.e., end of chromosome) exchange leads to an increased risk of MI errors, and (3) a pericentromeric exchange leads to an increased risk of MII errors (Lamb et al., 1996, 1997) (Fig. 3.2). The association of maternal MII errors with a specific recombination pattern suggests that at least some proportion of MII errors are initiated in MI (e.g., Fig. 3.1). We will simply use the designation ‘‘MII’’ to indicate this suggestion. More recently, we have examined altered recombination patterns of maternal nondisjoined chromosomes 21 stratified by maternal age to gain insight into possible mechanisms of nondisjunction. The data on 400 maternal MI errors grouped by maternal ages <29 years, 29–34 years, and >34 years indicate that there are multiple causes of nondisjunction, some age dependent and others age independent (Lamb et al., 2005b). In a young

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no exchange MI error

single telomeric exchange

MI error

single peri-centromeric exchange MII error

Figure 3.2 Summary of the susceptible exchange configurations observed among maternal nondisjoined chromosomes 21 and their associated risks for MI or ‘‘MII’’ errors.

woman, meiotic machinery (spindle function, sister chromatid adhesive proteins, microtubule motor proteins, and so on) functions optimally and, as a result, can correctly segregate all but the most error-prone exchange configurations. For young women then, the most frequent risk factor for MI nondisjunction is the presence of a telomeric exchange. As a woman ages, her meiotic machinery may be exposed to an accumulation of environmental and age-related insults, becoming less efficient/more error-prone. For example, recent studies have indicated changes in gene expression in younger compared with older oocytes in both mouse (Hamatani et al., 2004; Pan et al., 2008) and human studies (Steuerwald et al., 2007). Gene profiles that were altered included those involved in cell cycle regulation, cytoskeletal structure, energy pathways, transcription control, and stress responses. Such changes could play a role in the abnormalities of meiotic spindle that have been frequently observed in oocytes of aged mothers (Battaglia et al., 1996; Eichenlaub-Ritter et al., 2004). Among these older oocytes, suboptimal exchange patterns still increase susceptibility to nondisjunction, but now even homologous chromosomes with optimally located exchanges are at risk. Over time, the proportion of nondisjunction due to normal exchange configurations increases as age-dependent risk factors exert their influence. As a result, the most prevalent exchange profile of nondisjoined oocytes shifts from susceptible to nonsusceptible patterns with increasing age of the oocyte. If ‘‘MII’’ errors are initiated in MI, exchange patterns among maternal age groups with ‘‘MII’’ errors are predicted to be similar to those observed for MI errors. Our current data contradict this hypothesis (Oliver et al., 2008). Among 58, 69, and 126 maternal MII errors grouped by maternal ages of

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<29 years, 29–34 years, and >34 years, respectively, the proportion of susceptible pericentromeric exchanges increased with age, the opposite pattern to that observed in MI. This pattern indicates that there is an interaction with the effect of the pericentromeric exchange and advanced maternal age. We suggest two alternative explanations to fit these data. First, the pericentromeric exchange may establish a suboptimal condition that exacerbates the effect of maternal age–related risk factors. Alternatively, the pericentromeric exchange protects the bivalent from maternal age–related risk factors allowing the proper segregation of homologs, but not sister chromatids. This would represent a ‘‘true’’ MII error in the classical sense (Fig. 3.1). Clearly, additional work needs to be done to distinguish these alternatives.

2.3. Environmental influences on chromosome 21 nondisjunction Over the years, a large number of potential environmental influences have been identified in epidemiological studies of DS, but almost none have been replicated. Smoking at the time of pregnancy is an excellent example of the difficulties and limitations of such studies. Previously, a number of studies reported that women who smoke around the time of conception are at decreased risk for having an infant with DS (e.g., Chen et al., 1999; Hook & Cross, 1985, 1988; Kline et al., 1983, 1993; Shiono et al., 1986). One explanation for the negative association was that trisomic conceptuses were selectively lost prenatally among women who smoke (Hook & Cross, 1985; Kline et al., 1993). However, other studies have concluded that there is no association between DS and periconceptional smoking (e.g., Cuckle et al., 1990; Kallen, 1997; Torfs & Christianson, 2000). In contrast, Yang et al. (1999) analyzed periconceptional smoking among women less than 35 years with maternal MI and ‘‘MII’’ errors separately and found an increased frequency of smoking among women with ‘‘MII’’ errors only (OR ¼ 2.98; 95% CI ¼ 1.01–8.87). The odds ratio for this group of women increased significantly if the interaction term of periconceptional smoking and oral contraceptive use (2 month around conception) was modeled (OR ¼ 7.62; 95% CI ¼ 1.63–35.6). The authors speculated that this combined risk factor may compromise the blood flow surrounding the developing follicle, depleting the follicular fluid of oxygen. The resulting hypoxic environment may cause the meiotic machinery to malfunction. The hypothesis was based on the findings of Van Blerkom et al. (1997). They examined the oxygen content of follicular fluids from 1,000 follicles of equivalent size and ultrasonographic appearance taken from 116 in vitro fertilization (IVF) patients. Oocytes from severely hypoxic follicles were associated with high frequencies of chromosome disorganization on the metaphase spindle. Such disorganization could lead to nondisjunction and resulting aneuploidy. This speculation is similar to that proposed by

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Gaulden (1992) to explain maternal age–related nondisjunction. She suggested that the follicular microcirculation may be compromised in an aging ovary because of abnormal hormone signaling. Although the study of Yang et al. must be confirmed with a larger sample size, this example illustrates the potential of using identified risk factors to help dissect the maternal age effect. Other factors such as alcohol (e.g., Kaufman, 1983), maternal irradiation (e.g., Padmanabhan et al., 2004; Strigini et al., 1990; Uchida, 1979), fertility drugs (e.g., Boue & Boue, 1973), oral contraceptives (e.g., Harlap et al., 1979; Yang et al., 1999), spermicides (e.g., Rothman, 1983; Strobino et al., 1986), parity (reviewed by Chan, 2003), and low socio economic status (Christianson et al., 2004; Torfs & Christianson, 2003) have been implicated, but not confirmed. It seems almost certain that environmental risk factors for chromosome nondisjunction exist. Studies from model organisms make it clear that a wide variety of genetic and environmental disturbances can affect aneuploidy levels. Most recently, Dr. Hunt and her team have convincingly shown that exposure of oocytes in mice to bisphenol A (BPA) has a detrimental effect on mammalian oogenesis. BPA is an estrogenic chemical that is a component of polycarbonate plastics, resins lining food containers, and additives in a variety of consumer products; thus, it is present in almost all environments. In their first series of experiments, Hunt et al. (2003) found that, in the female mouse, short-term, low-dose exposure during the final stages of oocyte growth was sufficient to cause meiotic effects and that those effects increased the risk of aneuploidy. More recently, they have shown that exposure of developing oocytes during MI prophase in vivo, at doses comparable to human exposure, leads to synaptic defects and increased levels of recombination (Susiarjo et al., 2007). In the mature female, these aberrations lead to increased rates of aneuploidy in eggs and embryos. Further work indicated that BPA acts as an estrogen antagonist and suggests that the oocyte is sensitive to estrogen during early oogenesis. Understanding the influence of BPA, as well as other endocrine disruptors, on humans is an intense area of research. Certainly, understanding important risk factors, such as BPA, helps to address a major public health concern. Identification of such factors in humans is particularly difficult as oocyte development is initiated during fetal life and continues until the oocyte is ovulated. Full evaluation requires knowledge of the grandmother’s as well as the mother’s exposures. Large population-based studies that separate individuals with DS by type of nondisjunction error will increase the power to identify risk factors that have remained elusive. New epidemiological study designs and/or large prospective cohort designs of two or more generations will be needed to capture information from women and their mothers to reliably examine environmental exposures throughout the lifecycle of the oocyte. Clearly such studies will be difficult and labor intensive.

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In this case, model systems may be more efficient to address maternal grandmother exposures.

2.4. Candidate genes for chromosome 21 nondisjunction Model organisms have been used to identify genes that are important in the proper segregation of chromosomes. Genes involved in the meiotic process (e.g., homolog pairing, assembly of the synaptonemal complex, chiasmata formation, sister chromosome cohesion, meiotic spindle formation) may predispose an organism to chromosome nondisjunction. To date, a large study to investigate the association of variants in these genes with nondisjunction of human chromosome 21 has not been conducted. Candidate gene studies of the folate pathway provide the best example of genetic epidemiological approaches being used to evaluate the association of genetic variants with nondisjunction. James et al. (1999) provided preliminary evidence that the C677T polymorphism in the methylenetetrahydrofolate reductase (MTHFR) gene increased the chance of having a child with DS (OR ¼ 2.6; 95% CI ¼ 1.2–5.8). This polymorphism is associated with an elevation in plasma homocysteine and/or low folate status. The authors hypothesized that low folate status, whether due to dietary or genetic factors, could induce centromeric DNA hypomethylation and alterations in chromatin structure. Such alterations could adversely affect DNA–protein interactions required for centromeric cohesion and meiotic segregation. Later studies of the MTHFR C677T polymorphism, as well as several other allelic variants in genes in the folate pathway (e.g., MTHFR A1298C, MTRR A66G, MTR C2756G, RFC1 A80G), generated inconsistent results, most likely due to limited sample sizes, varying population characteristics, and sampling strategies. Moreover, some studies examined single gene effects, while others included gene–gene and gene–nutrition interactions. Still others examined biomarkers such as total plasma homocysteine levels. Although a thorough review is beyond the scope of this chapter, some important findings can be highlighted. Most studies that have examined blood homocysteine levels, a broad-spectrum indicator of nutritional and/or genetic impairment in folate/B12 metabolism, have documented a significantly higher level among the mothers of children with DS compared with control mothers, irrespective of population origin (Bosco et al., 2003; da Silva et al., 2005; James et al., 1999; Martinez-Frias et al., 2006; Takamura et al., 2004; Wang et al., 2007). As studies that examined one or two variants of MTHFR provided inconsistent results, Zintzaras (2007) conducted a comprehensive meta-analysis using strict criteria to evaluate the results from 11 case–control studies that examined MTHFR C677T, MTHFR A1298C, and/or MTRR A66G variants to the maternal risk for DS. The analysis was complicated by the statistically significant heterogeneity between studies. Nevertheless, the meta-analyses using several

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approaches indicated that the pooled odds ratios were not significant for any of the variants. The cumulative meta-analysis of MTHFR C677T showed a trend toward an association as the amount of data increased. Overall, the author suggested that there was insufficient evidence for claiming or denying an association for the gene variants. More recent studies have focused on the interaction among genes in the folate pathway adjusting for covariants and continue to find intriguing correlations (e.g., Biselli et al., 2008; Bosco et al., 2003; Coppede et al., 2006; da Silva et al., 2005; Hobbs et al., 2000; Martinez-Frias et al., 2006; Rai et al., 2006; Scala et al., 2006, 2007; Wang et al., 2008). In all studies that examined multiple variants, they found that the effect was additive (e.g., Biselli et al., 2008; Hobbs et al., 2000; Martinez-Frias, 2008; Rai et al., 2006; Scala et al., 2006; Wang et al., 2008) Clearly, this story needs to be pursued. Future studies should focus on gene–gene and gene–nutrition interactions in the folate pathway using large sample sizes, appropriate controls, and genetic epidemiological methods that adjust for possible confounding due to population substructure.

3. Prevalence and Survival of Individuals with DS Throughout the Life Span The survival prospect of individuals with DS in developed countries has improved considerably over time with the shift from institutional care to community-based care, improved clinical interventions, and overall health of the population. For example, survival to 1 and to 10 years was estimated to be 76% and 65% in a birth cohort in the United States from the years 1950–1967 (Fabia & Drolette, 1970a). Although not directly comparable, a more recent study showed that the 1- and 10-year survival rates in another US birth cohort from the years 1979–1998 was 93% and 89%, respectively (Rasmussen et al., 2006). Significant increases in survival have been noted in other developed countries as well (reviewed in Glasson et al., 2002). Even more importantly, the overall life expectancy of an individual with DS has increased significantly and is estimated to be about 60 years in developed countries (e.g., Glasson et al., 2002). This impressive change over time should shift our research emphasis to assessing causes of morbidity and mortality throughout the life stages of an individual with DS, in addition to obtaining accurate estimates of prevalence. We will provide recent examples of both types of studies to indicate the direction of the field. An important point to reiterate is that the majority of pregnancies of fetuses with trisomy 21 are spontaneously lost prior to term. For example, the rate of fetal loss has been estimated to be about 40% between the time of chorionic villus sampling (CVS) and birth and about 25% between amniocentesis and birth, although these estimates are not straightforward to derive

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(for review, see Cuckle, 1999; Snijders, 1999). More recently, Savva et al. (2006) conducted a survival analysis on follow-up of 5,177 prenatally diagnosed cases of DS to determine if spontaneous loss depended on maternal age. They found that the rate of loss increases with increasing maternal age. The average fetal loss rate between the time of CVS and term was 32% (95% CI ¼ 26–38) and increased from 23% (95% CI ¼ 16–31) to 25–44% (33–56) for women aged 45. The average fetal loss rate between the time of amniocentesis and term was 25% (21–31) and increased from 19% (14–27) to 33% (26–45) across the same age range. Importantly, this does not include the loss prior to recognizing a pregnancy or prior to prenatal diagnosis. Thus, the estimates of the prevalence among live births not only exclude those pregnancies that were medically terminated but also those that were spontaneously lost.

3.1. Mortality and morbidity among individuals with DS Before examining trends in prevalence, it is helpful to provide an overview of the causes of mortality and morbidity over the life span of individuals with DS. A recent study has provided an excellent framework to consider these issues by dividing the lifespan into four time periods: (1) prenatal, (2) childhood, and adolescence (0–18 years), (3) adulthood (19–40 years), and (4) senescence (>40 years) (Bittles et al., 2007). We will use this study as an example of one that begins to identify increased length of survival of individuals with DS and provides a focus for future efforts. The study of Bittles et al. was based on the successful registration of individuals with DS by the Disability Services Commission of Western Australia. This commission is a primary support agency for those with intellectual disability in Western Australia since 1952. Thus, one limitation of the study is that some proportion of individuals may not get registered with the commission. Nevertheless, the study data are based on the electronic linkage of 1,332 individuals with DS in the Disability Services Commission from 1953 to 2000 with the (1) Western Australia Cancer Registry (1981 to present), (2) the Western Australia Death Registry and the state Coroner’s office, and (3) the National Death Index (1980 to present). In addition, information on overall DS survival trends for the Western Australia population from 1980 to 2004 was obtained from the Western Australia Birth Defects Registry. We will only highlight some of the findings of each period to show the value of the data collected. In the prenatal stage/birth stage, this study indicated that the overall prevalence of DS (live births, fetal deaths, and medical terminations) per 1,000 births increased from 1.1 to 2.9 per 1,000 births in 1980–2004, respectively. This increase paralleled the increase in maternal age in the population. In 1980, 4.8% of women giving birth in Western Australia were

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35 years or older compared with 18.6% in 2004. This trend has been observed in other populations as well (see below). The next stage of life, infancy to early adulthood proves to be a medically vulnerable one. About half of the 298 deaths identified among the 1,332 individuals with DS occurred before age 18 and about 36% before age 5. As in other studies, the leading causes of death between ages 0–18 years were pneumonia and other respiratory infections (33%) and congenital heart defects (CHDs) (13%). Because children with DS have a >20-fold increased risk of developing leukemia in childhood (see below), this condition was further examined during this life stage. Data from the Western Australia Cancer Registry indicated that about 54% (14/26) of cancers recorded in individuals with DS were childhood leukemia. Twelve of 14 cases were diagnosed before 5 years of age and in 4 cases it was fatal. In adulthood (19–40 years), the investigators noted that many agerelated health problems and/or medical disorders in DS begin earlier than in the general population. About 13% of the 298 deaths between 1953 and 2002 occurred in the 19–40 year age group. The main causes of death recorded were pneumonia and other respiratory infections (23%), cardiac, renal, and respiratory failure (10%), and cancers (8%). Cerebrovascular accident and coronary artery disease were recorded as causes of death in about 5% and 3% of the cases, respectively. Lastly, about 30% of individuals with DS registered in the Disability Services Commission cohort were aged >50 years at the time of death and 25% died between 57 and 62 years. Information on cause of death was available for 97 of the 111 deceased persons >40 years of age. Pneumonia and other respiratory infections were the most common causes of death (40%), followed by coronary artery disease (9.9%), cardiac, renal, and respiratory failure (9.0%) cerebrovascular accident (6.3%), and cancers (5.4%). Alzheimer’s dementia was listed as a contributory cause of death in only three cases. The above account of causes of mortality only shows a limited picture of the medical problems encountered by those with DS. The use of information from death certificates is fraught with problems as pointed out by others (e.g., Rasmussen et al., 2006; Shin et al., 2007; Yang et al., 2002), but still provides a basic overview. The age-associated morbidity patterns of DS are an area of considerable clinical research. The study of van Allen et al. (1999) indicated that significant health problems among adults with DS include untreated congenital heart anomalies (16%), acquired cardiac disease (16%), pulmonary hypertension (8%), recurrent respiratory infections/aspiration (30%), complications from presenile dementia/Alzheimer-type disease (42%), adultonset epilepsy (37%), osteoarthritic degeneration of the spine (32%), osteoporosis with resultant fractures of the long bones (55%) or vertebral bodies (30%), and untreated atlantooccipital instability (8%). In addition, they showed that acquired sensory deficits including loss of vision due to

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early onset of adult cataracts (50%), recurrent keratitis (21%), or keratoconus (16%), and measurable hearing loss (25%) were significant problems. Importantly, population-based surveillance of common medical conditions in adults with DS is infrequent. Henderson et al. (2007) found that 48% of adults with DS had not seen a doctor in the previous 12 months and 33% had not had a medical assessment in the previous 3 years. Untreated hypothyroidism, a common problem for adults with DS may lead to symptoms that mimic cognitive decline; it may also be associated with decreased energy, and weight gain (Finesilver, 2002). The causes and consequences of obesity in individuals with DS have only recently been studied (e.g., Fonseca et al., 2005; Melville et al., 2005). As Barnhart and Connolly (2007) emphasize, a shift must be made from disability prevention to the prevention of conditions that limit activity and participation of adults with DS. Consideration of exercise and healthy diet regimen will positively affect the overall health of adults with DS and, thus, will increase their quality of life.

3.2. Implication of factors that influence the prevalence of DS The recent report by Canfield et al. (2006) provides an excellent example of a large study to obtain an estimate of the birth prevalence of DS in the United States and to identify factors that may influence prevalence estimates. Eleven birth surveillance systems used active-case finding methods to identify all pregnancy outcomes with DS, including live births, fetal deaths, spontaneous and induced abortions. The national estimate for DS based on the surveillance of 22% of births in the United States and maternal age– adjusted prevalence was 13.65 (95% CI ¼ 13.22–14.09) per 10,000 live births, or 1/733. This suggests that 5,400 of the approximate 4 million infants born each year in the United States have DS. Canfield et al. further investigated the maternal age–adjusted prevalence rates among three major maternal racial/ethnic groups in the United States: non-Hispanic white, non-Hispanic black, and Hispanic. Compared with non-Hispanic white mothers, the prevalence ratio was 0.77 (95% CI ¼ 0.69–0.87) for non-Hispanic black mothers and 1.12 (95% CI ¼ 1.03–1.21) for Hispanic mothers. The causes of the increased prevalence among Hispanic and decreased prevalence among non-Hispanic black mothers are important to discern. Differences could be related to variation among surveillance systems: The authors state that each surveillance system differed in its access to prenatal records and diagnoses, spontaneous abortions, fetal deaths, and live births. If ability to ascertain information at various gestational time points varied by racial/ethnic groups, prevalence estimates would differ. Alternatively, prevalence rates could be influenced by factors that affect access to health care, such as socioeconomic status or education (e.g., Coory et al., 2007; Khoshnood et al., 2004, 2006). Differences could be due to racial/ethnic variation in use of prenatal care, prenatal diagnosis,

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and/or pregnancy termination (e.g., Forrester & Merz, 1999; Siffel et al., 2004). Lastly, important environmental exposures (e.g., smoking, nutrition, socioeconomic status) or genetic risk factors (e.g., variants involved in meiosis, oocyte development, or fetus survival) could vary by racial/ethnic group. Each one of these explanations is plausible and carries significant implications for future public health interventions. A significant number of important studies have been conducted that examine the birth prevalence of DS among populations using various methods of case ascertainment. Hook and his colleagues have contributed significantly to this field, not only in terms of study design and statistical methods but also in presenting results from populations with different demographics (e.g., Carothers et al., 1999, 2001; Hecht & Hook, 1996; Hook, 1981, 1983; Hook et al., 1995, 1999). In a review of 49 population groups using an index to allow comparison between studies, Carothers et al. (1999) suggested that ‘‘real’’ variation between population groups probably amounts to about 25%. Interestingly, the pattern of prevalence estimates among the racial/ethnic groups identified in this meta-analysis is the same as that observed in Canfield et al. (2006): There was an increase in the prevalence among individuals of Hispanic origin compared with those of African-American or African origin. This prevalence variation observed among groups defined by their ‘‘self-reported’’ race/ethnicity needs to be dissected. The categorization of race/ethnicity is imprecise and displays considerable in-group heterogeneity. This measure becomes more imprecise with ever-increasing numbers of individuals classified as multiethnic and multiracial. Nevertheless, there is considerable motivation to identify the underlying cause of the differences in prevalence observed among groups. The prevalence of DS among births in a specific population, of course, depends on the maternal age structure of the population, the availability of prenatal diagnosis, the option for elective terminations, and the culture’s attitude toward pregnancy terminations as well as the prospect of caring for a disabled child. Recent studies have not shown large changes in the prevalence of DS among live births over time (e.g., Bittles et al., 2007; Dolk et al., 2005; Iliyasu et al., 2002; Khoshnood et al., 2004; Rosch et al., 2000). For example, in the ethnic/racial diverse population of the fivecountry metropolitan area of Atlanta, GA, the proportion of pregnancies among women in their late 30s has increased in recent years. Interestingly, the prevalence of DS among infants of women in this age group has also shown an increase (Besser et al., 2007; Siffel et al., 2004). The reasons for this stabilization or slight increase of prevalence among births needs to be further tracked to better understand (1) the consequence of screening for trisomic conceptuses and the use of prenatal diagnosis as an intervention, (2) the decisions that families are making with respect to timing of pregnancies and use of prenatal diagnoses, and (3) the public health allocation of resources to accommodate these trends.

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As emphasized by many, it is essential to obtain accurate estimates of survival rates among individuals with DS. Survival rates differ among racial/ ethnic groups and suggest that additional studies are needed to understand such differences (e.g., Besser et al., 2007; Day et al., 2005; Rasmussen et al., 2006; Yang et al., 2002). Studies to assess prevalence of individuals with DS in adolescence and adulthood are just beginning. For example, Besser et al. (2007) recently conducted a study of children with DS born in metropolitan Atlanta, GA, from 1979 to 2003 ascertained from a population-based birth defects registry. These ascertained cases were followed using linkage to vital records and the National Death Index. The prevalence was estimated by dividing the children surviving with DS by the population obtained from the US Census estimates. They found that there were 13.0 per 10,000 live births with DS in 2003 and 8.3 per 10,000 ages 0–19 years. The prevalence of DS among 0–14 year olds increased over time, which parallels the studies outlined above that show improved medical care. Importantly, within each 5-year cohort, the prevalence decreased with age and this decrease was greater among blacks than among whites. This discrepancy between racial/ ethnic groups has also been observed using other approaches (Rasmussen et al., 2006; Yang et al., 2002). The next step is to understand the cause of the differential mortality rates to provide for those who are most at risk for childhood morbidity and mortality.

4. Etiology of DS-Associated Medical Disorders Almost universally, individuals with DS have characteristic facial features, mental retardation, and hypotonia; however, even these features vary in severity. Importantly, other features including specific birth defects and medical disorders vary considerably. They are present at a higher frequency among individuals with DS compared with the general population; however, these DS-associated conditions are not present in all individuals with an extra chromosome 21. For example, CHDs occur in about 50% of individuals with DS, gastrointestinal tract abnormalities (e.g., duodenal stenosis or atresia) occur in about 5–10%, and childhood leukemia in about 1%; these all occur at significantly higher frequencies than in the general population (for review, see Epstein, 2001). Thus, the extra chromosome 21 either (1) ‘‘sensitizes’’ the genetic background and unmasks variability in the rest of the genome and/or (2) leads to increased chromosome 21 variability, directly influencing susceptibility. Patterson (2007) reviewed possible molecular mechanisms resulting from trisomy 21 that lead to manifestations of DS. Two important epidemiological questions are (1) Among individuals with DS, what is the prevalence of a specific trait and is it increased or

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decreased compared with those without DS? and (2) What are the associated factors that explain the reduced penetrance and variable expression of DS-associated traits? There are few studies to date that have addressed these significant questions using population-based strategies (e.g., Fabia & Drolette, 1970b; Freeman et al., 1998; Kallen et al., 1996; Stoll et al., 1990; Torfs & Christianson, 1998). One example of a recent population-based study that examined both questions is that conducted by Torfs and Christianson (1998, 1999). They studied 2,894 confirmed cases of DS collected through the California Birth Defects Monitoring Program (CBDMP) between 1983 and 1993. They compared the frequencies of specific birth defects among infants with DS to those in 2.5 million newborn infants from the same population. They recorded 61 major birth defects known to be uniformly ascertained through the CBDMP, that is, those that could be diagnosed in an infant through age one or those that require early action. Forty-five defects were significantly more common in DS. For example, the chance for atrioventricular septal defects (AVSD, or sometimes called atrioventricular canal) was increased 1,000-fold over that for infants without DS. Other cardiac defects were also increased including atrial septal defects (ASD), ventricular septal defects (VSD), and defects of cardiac valves. Gastrointestinal defects were about 20 times more common in infants with DS. Duodenal atresia and annular pancreas had the highest risk ratios (265 and 430, respectively). Most defects of the primary developmental field and midline defects were either not significantly associated or not observed in infants with DS (e.g., anencephaly, spina bifida, encephalocele, and diaphragmatic hernia). In the next section, we will review two DS-associated disorders to probe further into studies that ask the second question: What factors are associated with the reduced penetrance and variable expression of DS-associated traits? CHDs will provide an example of a condition that is just beginning to be dissected with respect to etiology. Next, we will describe recent studies on DS-associated childhood leukemia. For this disorder, researchers have made some progress with respect to understanding the genes that may be involved in susceptibility. We discuss both disorders further as examples of conditions that may influence later cognitive and behavioral outcomes. We will not review another important DS-associated condition, that of Alzheimer disease. This is due to space limitations, but we point to a recent review of this significant area of focus (Zigman & Lott, 2007; also see Chapter 4).

4.1. DS-associated CHDs Most studies have shown that about 45–50% of infants with DS have CHDs with one defect, namely AVSD, being particularly common. Several recent reports have suggested that the distribution of CHDs in DS varies by race/ ethnicity (de Rubens et al., 2003; Ferencz et al., 1997; Jacobs et al., 2000;

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Khoury & Erickson, 1992b; Lo et al., 1989; Marino, 1996; Torfs & Christianson, 1999), but most population-based studies have not had broad ethnic representation. We have recently analyzed data collected from the NDSP to examine variation in rates of CHD in a racially/ethnically diverse US population (Freeman et al., 2008). The noted limitations of the study can be stated first: (1) only families in which the mother spoke English or Spanish were eligible and (2) pregnancy losses, medical terminations, fetal deaths, or infants who died after birth but before the family could be enrolled were not included. First, we found that 44% of infants with DS have CHDs, a rate consistent with other studies (Freeman et al., 1998; Kallen et al., 1996; Stoll et al., 1998; Torfs & Christianson, 1998). We then estimated the proportion of cases with specific types of heart defects, knowing that infants with DS were particularly susceptible to AVSD. We found in the NDSP study population that a partial or complete AVSD was present in 17% of eligible infants (39% of those with a reported CHD), a rate similar to that found in most other studies (Calzolari et al., 2003; Fixler & Threlkeld, 1998; Freeman et al., 1998; Frid et al., 1999; Kallen et al., 1996; Rowe & Uchida, 1961; Stoll et al., 1998; Torfs & Christianson, 1998; Wells et al., 1994). In contrast to the similar estimates of AVSD among infants with DS, ASD and VSD rates vary widely among studies: 4–42% and 11–44%, respectively (Calzolari et al., 2003; Fixler & Threlkeld, 1998; Freeman et al., 1998, 2008; Frid et al., 1999; Kallen et al., 1996; Rowe & Uchida, 1961; Spahis & Wilson, 1999; Stoll et al., 1998; Torfs & Christianson, 1998; Wells et al., 1994). We then examined demographic characteristics of infants with specific types of CHD to determine if such factors provide insight into susceptibility. The NDSP was particularly useful for the analyses of race/ethnicity, as it includes three ethnic groups represented at greater than a 10% frequency: non-Hispanic white, non-Hispanic black, and Hispanic. This permitted a direct examination of possible differences in CHD rates among ethnic groups. AVSDs demonstrated the most striking ethnic differences. Specifically, black infants with DS had about twice the risk of AVSD as white infants (OR ¼ 1.98; 95% CI ¼ 1.31–2.99) whereas Hispanics had one-half the risk of whites (OR ¼ 0.60; 95% CI ¼ 0.40–0.99). Similar ethnic differences in AVSD rates at multiple sites strengthen the overall NDSP findings. In contrast, we found no significant ethnic differences in VSD rates in the NDSP as a whole or among the sites. For ASD, we noted a marginally significant increased OR for blacks compared with white infants with DS. This observed increase among black infants could be a true increase or may be due to the diagnostic misclassification of AVSD as ASD. This needs to be further examined. We also found a predominance of females among infants with AVSD (OR ¼ 2.06; 95% CI ¼ 1.55–2.75), which has been reported previously in infants with and without DS (Ferencz et al., 1997; Harris et al., 2003; Kallen et al., 1996; Park et al., 1977; Pinto et al., 1990). Interestingly, some studies

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have reported that males with DS have a significantly greater life expectancy compared with females with DS (Fabia & Drolette, 1970a; Glasson et al., 2003; Leonard et al., 2000), although not all report this difference (Day et al., 2005; Dupont et al., 1986; Malone, 1988; Mastroiacovo et al., 1992; Mulcahy, 1979; Rasmussen et al., 2006; Yang et al., 2002). If true, this observation is contrary to the male:female ratio in the general population and in most individuals with intellectual disabilities. One explanation provided for this difference may be an increased preponderance of CHD, in particular AVSDs, among females with DS (Glasson et al., 2003). Clearly more research needs to be done to understand these ethnic/racial and gender differences. Both of these parameters are surrogates for many characteristics that may prove to be susceptibility factors. One example of a study that began to further examine factors that underlie susceptibility to DS-associated birth defects is that of Torfs and Christianson (1999). They compared demographic information, pregnancy, and medical histories, and use of tobacco, alcohol, and coffee among mothers of infants with DS with and without specific birth defects in a case/control study based on 687 infants with DS. Taking CHD and tobacco use as an example, smoking was found to be associated with CHD overall (OR ¼ 2.0; 95% CI ¼ 1.2–3.2) and specifically, with AVSD, ASD, and tetralogy of Fallot. Maternal race, age, parity, income, and education did not confound the association. Others have examined smoking and DS-associated CHD and have not found a significant association; however, comparison of studies is difficult as sample sizes were smaller, the timeframe of tobacco use differed (prior to conception vs during the first trimester), and the diagnostic methods used to identify and classify CHD were older (e.g., Fixler & Threlkeld, 1998; Khoury & Erickson, 1992a). Nevertheless, the combined results suggest smoking may be a risk factor. However, as suggested by Torfs and Christianson (1999), at least in their dataset, smoking only played a small role in susceptibility for abnormal heart development among those with DS, as the frequency of periconceptional smoking was low and the association modest.

4.2. DS-associated leukemia Several studies have now documented that although the overall incidence of cancer in individuals with DS is similar to that of the general population, it shows a strikingly different profile of cancer types (e.g., Hasle et al., 2000; Patja, 2006; Sullivan et al., 2007; Yang et al., 2002). For example, in a population-based study of 2,814 individuals with DS, the incidence of solid tumors was reduced by about one-half in all age groups; however, leukemia occurred 10- to 20-fold more frequently among those with DS (Hasle et al., 2000). Importantly, the largest relative risk for leukemia was observed in children with DS under age five. In this group, acute myeloid leukemia (AML) was 153-fold more frequent than in the general population.

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Moreover, the incidence of acute megakaryoblastic leukemia (AMKL) is estimated to be 500-fold increased in children with DS compared with the general population (Zipursky et al., 1992). AMKL explains about 62–86% of AML in children with DS, a significant increase compared with the general pediatric population (Creutzig et al., 2005; Lange et al., 1998). Comparison of AML associated with and not associated with DS indicates that distinct phenotypes exist. The median age of onset is much younger—about 2 years compared with 8 years in the general population (Creutzig et al., 2005; Lange et al., 1998). Also, many times a myelodysplastic syndrome with thrombocytopenia and/or anemia and abnormal bone marrow morphology precedes AML in DS, but is usually de novo in nonsyndromic AML children (Zipursky et al., 1987, 1994). A remarkable feature of DS-associated AML is the sensitivity to therapy (e.g., Kudo et al., 2007; Lange, 2000; Ravindranath et al., 1992); disease resistance and recurrence are uncommon. In fact, children with DS have been found to be more sensitive or responsive to chemotherapy. Until treatments were altered, high rates of toxicity occurred, which sometimes led to mortality (Craze et al., 1999; Lange et al., 1998). In addition to AML, about 10% of infants with DS develop transient myeloproliferative disorder (TMD) (Hitzler & Zipursky, 2005). TMD in newborns with DS is characterized by circulating blasts with morphologic features of leukemic cells. Studies have shown that these immature megakaryoblasts are clonal and are present in the liver, bone marrow, and peripheral blood (e.g., Kurahashi et al., 1991; Miyashita et al., 1991). In a recent study of 48 newborns with DS and TMD, 25% were asymptomatic, but the others had a significant elevation of blast counts with consequences such as bruising, respiratory distress, and liver dysfunction (Massey et al., 2006). Although TMD usually resolves spontaneously within 3 months, a small percentage of neonates develops severe and sometimes fatal complications. These include hepatic fibrosis or hydrops (e.g., Dormann et al., 2004; Schwab et al., 1998). Although considered transient, recent studies have shown that 20–30% of neonates who recover from TMD develop AMKL within 3–4 years (Hitzler & Zipursky, 2005; Massey et al., 2006). There is evidence that TMD and AMKL arise from a common precursor; however, the underlying mechanism of the susceptibility of children with DS to leukemia is only beginning to be understood (reviewed in Hitzler, 2007). One of the major breakthroughs has been the discovery that nearly all of children with DS who develop either TMD or AMKL have mutations in the transcription factor GATA1 (Ahmed et al., 2004; Groet et al., 2003; Hitzler et al., 2003; Rainis et al., 2003). GATA1 is an X-linked gene that encodes a zinc-finger transcription factor. This factor is essential for normal erythroid and megakaryocytic differentiation. Although the mechanism of action is still not understood, another question comes to the forefront: How

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does the mutation in the X-linked GATA1 gene cause a leukemic condition in individuals with an extra chromosome 21? The current thinking is that such mutations interact with chromosome 21 specific genes and/or with nonchromosome 21 genes that are not regulated appropriately as a consequence of the extra chromosome 21. This interaction(s) need to explain both the variability of the presence of TMD in neonates and the conversion of TMD to AMLK in a subset of individuals. One candidate gene that is located on chromosome 21 is RUNX1. This hematopoietic transcription factor has been shown to interact physically and functionally with GATA1 (Elagib et al., 2003; Xu et al., 2006), although the mechanisms of the interaction are not well understood. Intense research is ongoing to better define the interaction between GATA1 and RUNX1, and to identify factors involved in this leukemic process.

4.3. Summary The above description provides examples of both epidemiological and molecular approaches that are being taken to begin to address the etiology of specific disorders for which individuals with DS are significantly predisposed. Additional basic epidemiological studies need to be conducted to understand these associations throughout the life span of those with DS. New bioinformatic approaches that take advantage of large, epidemiological databases and of anonymized electronic medical records, may allow new questions to be answered (e.g., Hodapp et al., 2006). In addition, these studies in concert with molecular approaches will begin to provide insight into the etiology of, for example, abnormal heart development or Alzheimer disease, in the context of trisomy 21, but may also contribute to the understanding of these conditions in general.

5. Neurodevelopmental Outcomes of Comorbid Medical Conditions in DS Despite our wealth of knowledge regarding the cognitive and behavioral phenotypes of DS, the influence of DS-associated medical problems is often not considered in neurodevelopmental outcome studies. Here, we will review the current knowledge on the relationship of several DSassociated medical conditions and neurodevelopmental outcome after providing an overview of the cognitive phenotype in DS.

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5.1. Overview of cognitive phenotype in DS DS is the most prevalent genetic cause of mental retardation with its own unique cognitive, adaptive, and behavioral profiles. Unlike other genetic conditions, individuals with DS are typically diagnosed in the newborn period based on their distinctive physical characteristics. Thus, DS should be an ideal model to study the link between infancy to aging with respect to cognitive and behavioral phenotypes. As emphasized previously, the vast majority of our current knowledge on DS focuses on the early childhood and the adult years. Research is needed to connect these two endpoints to identify how symptoms evolve and change over time, especially from the adolescent through young adult years (Dykens, 2007). To this end, in 2006, the US Congress mandated that the National Institutes of Health (NIH) establish a trans-NIH taskforce charged with creating a research plan to identify, create, and implement programs to maximize and maintain cognitive function throughout the lifespan of individuals with DS. The resulting NIH DS Working Group’s 2007 Research Plan on DS highlights the need for more research focused on identifying the cognitive phenotype of DS throughout the lifespan, especially studies on comorbid psychiatric and medical conditions. The degree of cognitive deficits in individuals with DS varies from mild to moderate mental retardation with a typical range of 40–72 (Nicham et al., 2003). Children with DS between 6.5 and 8.0 years have IQ levels between 45 and 71 (mean 55.6) compared to adolescents with DS between 12.2 and 25.9 years with IQ levels between 28 and 47 (mean 37.6) (Melyn & White, 1973). Performance strengths are recognized on visual–spatial tasks compared with short-term memory auditory and verbal tasks ( Jarrold et al., 2002; Wang & Bellugi, 1994). Indeed, the cognitive deficits in DS may further delay language learning, as cognitive abilities serve as prerequisites for acquiring certain linguistic achievement (Abbeduto et al., 2001). Age-related decline in IQ is seen in individuals with DS, typically in the third or fourth decades, which may or may not be influenced by dementia (Devenny et al., 2000). In adulthood, 70% of individuals with DS function in the moderate–severe range, 20% in the mild–moderate range, and 8% in the mild range (Devenny et al., 2000; Temple et al., 2001). The mean IQ level is 45 by adulthood with significant variability in the range of IQ levels (Carr, 1994). It is usually a challenge to distinguish between the presence of early dementia and the declines related to normal aging process and lifelong cognitive deficits (Devenny et al., 2000; Chapter 4). In a longitudinal study conducted by Devenny et al. (1996), adults with DS with suspected or possible dementia of Alzheimer type show significant decline in cognitive abilities compared to nondemented adults.

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5.2. Impact of DS-associated CHDs on neurodevelopmental outcome As reviewed previously, about half of infants with DS have CHDs, with many having to undergo surgery for repair. Several neurodevelopmental studies in typically developing children with CHDs have shown neurocognitive and psychomotor deficits (Mahle et al., 2006), yet the impact of CHD in children with DS has not been described. In a cross-sectional study design, we compared 6 children with DS and AVSD (mean age 17 months) with 11 children with DS without a CHD (mean age 16 months) and found significant developmental delay in the group with AVSD (unpublished data). Those with AVSD had a greater developmental age delay difference compared with age-matched children with DS without CHDs, as indicated by a 2.91 month delay in the cognitive domain, 3.72 months delay in expressive language, 1.91 months delay in receptive language, and 1.00 month delay in gross motor. These preliminary data emphasize the need for further study to understand why these differences occur and to identify treatment strategies that may ameliorate these delays. There are many factors that must be considered in neurodevelopmental outcome studies in children with CHD. For instance, Gaynor et al. (2007) have suggested that patient-specific factors are more important than intraoperative factors (e.g., race, birth weight) in determining neurodevelopmental outcome in children with CHDs. This finding is important because there are significant ethnic and gender differences in the prevalence of CHDs, specifically for AVSD as described above. Furthermore, abnormal brain microstructure and metabolism noted shortly after birth in newborns with CHD suggests that these newborns have impaired brain development in utero, possibly related to impaired cerebral oxygen and substrate delivery prenatally (Donofrio et al., 2003). A recent study by Miller et al. (2007) describes a high incidence of injury to white matter that resembled periventricular leukomalacia in term newborns with CHD. This morphology is similar to that seen in premature infants and is related to impaired brain development that is detected preoperatively, shortly after birth. Hence, newborns with CHD are at risk for impaired brain development in utero. Longitudinal studies are needed to understand the neurodevelopment outcome of individuals with DS and CHD, possibly beginning with fetal brain development.

5.3. Impact of DS-associated leukemia on neurodevelopmental outcome As described above, the incidence of AMKL is estimated to be 500-fold increased in children with DS compared with the general population. Although there have not been any studies that examine the neurodevelopmental

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outcome of children with DS and leukemia, some studies have investigated the neurodevelopment of typically developing children with acute lymphoblastic leukemia (ALL). In the past, cranial radiation therapy resulted in declines in intelligence among survivors of childhood ALL (Fletcher & Copeland, 1988). As a result, pediatric oncologists began to substitute intrathecal chemotherapy for CNS prophylaxis in an attempt to improve cognitive outcomes. Intrathecal chemotherapy improved survival rates and appeared to be less detrimental to a child’s neurocognitive development when compared to cranial radiation therapy. Yet, ALL survivors receiving intrathecal chemotherapy continue to demonstrate slight decline on cognitive and academic abilities (Copeland et al., 1996). Research is needed to understand the influence of leukemia treatment on the neurodevelopmental outcome in children with DS, given the increased risk of leukemia in this cohort.

5.4. Impact of DS-associated obstructive sleep apnea on neurodevelopmental outcome Children with DS are at greater risk for development of obstructive sleep apnea syndrome (OSAS), with an estimated incidence of 30–60% compared to 0.7–2.0% in the general pediatric population (Gislason & Benediktsdottir, 1995; Marcus et al., 1991; Stebbens et al., 1991). OSAS includes episodes of apnea and hypopnea, and hypoventilation with hypercarbia and episodes of sleep fragmentation with increased arousals during sleep (Shott, 2006). Predisposing factors in DS include abnormal small upper airway, mid-face, and mandibular hypoplasia, large adenoids, protruding tongue, generalized hypotonia, and obesity (Shott, 2006). Sleep fragmentation and increased sleep arousals may impair daytime functioning, resulting in learning and behavior problems (Marcus et al., 1991). Despite the high frequency of OSAS and multiple predisposing risk factors, neurodevelopmental outcome studies do not currently exist in children with DS and OSAS. In studies involving typically developing children, OSAS is correlated with lower IQ performance testing and behavioral problems, including inattention and hyperactivity (Bass et al., 2004; Chervin et al., 2002).

5.5. Impact of DS-associated seizure disorder on neurodevelopmental outcome Seizure disorder is the most common neurologic disorder associated with mental retardation, with the prevalence of 4–8 per 1,000 in individuals with mental retardation compared to 3–4 per 1,000 in the general population (Steffenburg et al., 1995). The prevalence appears to increase with decreasing cognitive abilities with 28–38% in the profound mental retardation range and 14% with mild mental retardation (Steffenburg et al., 1995). In

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individuals with DS, the prevalence of seizures is higher than the general population, but lower than among individuals with mental retardation of other etiologies (Goldberg-Stern et al., 2001). Studies have indicated the rates of epilepsy to be 8% of children and adolescents with DS and 16% in adults with DS (Goldberg-Stern et al., 2001; Prasher, 1995). The type of seizure disorders vary in children with DS with 47% partial seizures, 32% infantile spasm, and 21–69% tonic-clonic seizures (Goldberg-Stern et al., 2001; Stafstrom et al., 1991). Stafstrom et al. (1991) conducted a large, retrospective study of 737 individuals with DS and seizure disorders and hypothesized that the increased susceptibility to seizures is likely to be associated with the hypoxia caused by cardiovascular complications, including congenital heart disease, severe intracardiac shunts, infection, and neonatal hypoxia or ischemia. In addition, reduced inhibitory interneurons, altered neuronal structure, and increased excitability of membranes may play a role in epileptogenesis in DS (Stafstrom et al., 1991). There is also a bimodal distribution of seizure onset with early-onset seizures in childhood and late-onset seizures in middle-aged individuals. The late-onset seizures in older individuals may be related to the presence of underlying changes of Alzheimer’s disease (Mann, 1988). Children with both epilepsy and mental retardation are at heightened risk for behavioral problems and psychopathology. In children with mental retardation and epilepsy, 57% had at least one psychiatric diagnosis, including autistic spectrum disorder, autism-like condition, Asperger syndrome, attention/deficit hyperactivity disorder, and conduct and tic disorder (Steffenburg et al., 1996). There have been no studies to date on the impact of seizures on the intellectual outcome and behavior of children with DS. Case studies have revealed that the neurodevelopmental outcome has been poor despite relatively good seizure control in children with DS and infantile spasms (Goldberg-Stern et al., 2001). Three of five children with DS and infantile spasm displayed autistic-like features (Goldberg-Stern et al., 2001). Additional studies are needed to understand the intellectual and behavioral profile of individuals with DS and seizures in order to plan effective intervention to improve their neurodevelopmental outcome.

5.6. Impact of DS-associated hearing loss on neurodevelopmental outcome Children with DS have a three times higher likelihood of developing chronic ear disease and secondary hearing loss than children with other developmental delays (Dahle & McCollister, 1986). The higher incidence is attributed to their anatomic anomalies, including mid-face hypoplasia, easily collapsible eustachian tube, stenotic ear canals, and small external canals (Shott, 2006). Furthermore, children with DS have frequent upper respiratory infections, possibly caused by the immaturity of the immune

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system (Shott, 2006). Shott et al. (2001) has shown that with aggressive medical and surgical management of chronic middle ear effusions and chronic otitis media starting soon after birth, only 2% had hearing loss after the first year in the study. Studies have shown that even a mild hearing loss can affect a child’s articulation (Bess, 1985). Children with DS have language deficits, particularly in expressive language, vocabulary production, and speech intelligibility, which may be further complicated by their chronic ear disease and hearing loss (Shott, 2006). The small oral cavity, open mouth posture, protruding tongue, and irregular dentition may further affect their speech production. Overall, there is significant weakness in communication compared to daily living and socialization skills (Dykens et al., 2006), which may hinder independent living and inclusion in the community (Chapman & Hesketh, 2000). Thus, aggressive monitoring and management of chronic otitis media is recommended to prevent hearing loss and consequently, deficits in communication skills.

6. Psychiatric and Neurobehavioral Issues in DS In the past, neurobehavioral disorders in individuals with mental retardation were often ignored and assumed to be linked to their cognitive deficits. Clinicians may attribute these behavioral and psychiatric problems to the intellectual disability. This bias is often referred to as ‘‘diagnostic overshadowing’’ as clinicians may not consider the presence of a dual diagnosis, co-occurrence of mental retardation and a psychiatric disorder, in their evaluation (Lovell & Reiss, 1993; Reiss et al., 1982). Because this is a significant area of clinical research in DS and one that will lead to improved treatment of symptoms associated with DS, we will provide an overview of the topic. Individuals with DS are at much higher risk for having a wide array of psychiatric and behavioral disorders, yet the rate is lower compared with individuals with mental retardation of other etiology. Approximately 20–40% of individuals with DS have clinically elevated maladaptive behavior (Chapman et al., 1998; Coe et al., 1999; Dykens & Kasari, 1997; Dykens et al., 2002), which is low compared with children with other intellectual disabilities. However, comparison of these rates to typical peers and siblings of children with DS indicates that their behavioral problems are significant. In a study of children with DS between age 5 and 15 years compared with their siblings without developmental delay, children with DS exhibit more overall maladaptive behavior, including inattention and impulsivity (Cuskelly & Dadds, 1992).

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The patterns of behavioral disorders appear to change with increasing age (Chapman et al., 1998; Dykens et al., 2002; Nicham et al., 2003). For example, externalizing disorders (dominant, opposition, hyperactivity, impulsivity, inattention) are more frequent during childhood, whereas internalizing behavior problems (shyness, decreased confidence) are more common in adolescence and adulthood (Nicham et al., 2003). Dykens et al. (2006) also revealed similar patterns in a cohort of 211 individuals with DS. Increased externalizing symptoms (aggression and delinquency) is present between 4 and 19 years in contrast to older adolescents who are vulnerable to internalizing symptoms (withdrawal, somatic, anxiety). This shift in behavior from childhood to adolescence appears unique in DS because individuals in other groups with intellectual disability do not have similar age-related withdrawal (Dykens, 2003). Dykens et al. (2002) have postulated that subtle increases in internalizing symptoms over the adolescent period may increase the risk for later-onset depressive disorders, mood or behavioral changes. The risk for psychopathologies continues through adulthood, and it becomes a challenge to determine if it is influenced by age-related cognitive decline or to clinical dementia of the Alzheimer type (Holland et al., 2000). In addition to Alzheimer’s disease, adults with DS are prone to depression, with an estimated rate of 11%, compared to only 4% in adults with other mental retardation (Collacott et al., 1992). Depressed mood, crying, decreased interest, psychomotor slowing, fatigue, appetite/weight change, and sleep disturbance are symptoms observed in individuals with DS and major depression (Capone et al., 2006). Lack of interest in activities with withdrawal, mutism, psychomotor retardation, low mood, decreased appetite, weight loss, and insomnia may be present. Verbal expression of preoccupations of suicide, death, and guilt are not common in adults with DS and major depression (Myers & Pueschel, 1995). Risks for depression that are unassociated with dementia include several factors associated with the challenges in transitioning from childhood to adulthood. As children with DS become older, they become aware that they are different, with loss or changes in relationships with peers (Capone et al., 2006). Furthermore, they may not have the appropriate mechanism to cope with stress, transitions, and changes in their life. They are also prone to obesity and other medical issues, such as hypothyroidism, which may lead to a sedentary life style. As a result, withdrawal and depression may begin to emerge. In adults with DS, the early, preclinical stages of dementia include behavioral and personality changes as opposed to memory changes (Ball et al., 2006). Thus, symptoms of depression and dementia of the Alzheimer type in adults with DS may appear very similar. In adults with DS and dementia, low mood, restlessness, disturbed sleep, excessive uncooperativeness, and auditory hallucination may be present (Cooper & Prasher, 1998).

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Since the symptoms of dementia and depression are closely related, it is important to consider both conditions in the differential diagnosis in order to provide appropriate treatment. Co-occurrence of autism spectrum disorder (ASD) or pervasive developmental disorders in DS may exist. The prevalence of ASD among children with DS ranges from 1 to 13% (Capone et al., 2005; Kent et al., 1999; Myers & Pueschel, 1991). Kent et al. (1999) estimated the prevalence of ASD in children with DS to be 7% using the Childhood Autism Rating Scale, Asperger Syndrome Screening Questionnaire, and International classification of Diseases (ICD-9) criteria. Capone et al. (2005) estimated a prevalence rate of 13% from clinic population, although the ascertainment may be biased since subjects are based on referrals. In this cohort, the DS and ASD group has lower IQ levels and higher levels of lethargy, stereotypy, and hyperactivity compared to DS without ASD. Additionally, Myers et al. (1995) sampled 497 individuals with DS and reported 13% of children under age 10 with externalizing behavioral problems, 20% of those between 10 and 20 years of age, and 25% of those over 20 years of age. The most significant problems include attention, conduct/ oppositional, and aggressive behaviors in those younger than 20 years. Other findings include 1% with infantile autism, 9% with childhood psychosis, 15% conduct problems, and 3% emotional disturbances. Similar to children with DS, psychiatric disorders are not common in adults with DS compared to adults with intellectual disabilities of other etiology. In 164 adults with DS, the prevalence of a psychiatric disorder is 26% compared to other studies which revealed a 32–59% rate in adults with mental retardation (Lund, 1985; Myers & Pueschel, 1995). Symptoms of delusions and hallucinations may exist together with social isolation, bland affect, apathy, and sleep disturbance in adults with DS and psychiatric disorders, and are often mistaken for major depression (Capone et al., 2006; Myers & Pueschel, 1994). Although psychiatric disorders seem uncommon in adults with DS, there continues to be gaps in our knowledge regarding the development and course of these problems across the lifespan (Dykens, 2007). It is essential to have standardized criteria and diagnostic procedures for adults with DS in order to improve intervention and treatment for these individuals and their families.

7. Summary Importantly, the prevalence of DS at birth has the potential to increase with the trend for women to extend their reproductive life span into their late 30s and 40s. Moreover, individuals with DS now have an increased life expectancy due to community-based care and medical and health

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improvements; thus, they have the potential to live long and productive lives. In this review, we have indicated the need to conduct additional epidemiological studies to determine the prevalence, cause, and clinical significance of the syndrome throughout the lifespan. From this knowledge, we can begin to determine the influence of specific DS-associated medical conditions on cognitive and behavioral outcomes. This will lead to appropriate intervention and treatment to enhance the quality of life for individuals with DS.

ACKNOWLEDGMENTS NIH/NCRR 1KL2RR025009, National Down Syndrome Society, Emory Egleston Children’s Research Center ( JV); NIH R01 HD38979, and NIH R01 HL083300 (SLS).

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C H A P T E R

F O U R

Alzheimer’s Disease in Adults with Down Syndrome Warren B. Zigman,* Darlynne A. Devenny,* Sharon J. Krinsky-McHale,* Edmund C. Jenkins,† Tiina K. Urv,‡ Jerzy Wegiel,§ Nicole Schupf,*,},** and Wayne Silverman††,‡‡ Contents 104 108 111 115 122

1. Introduction 2. Down syndrome/Alzheimer’s Disease Research Program 2.1. Classification and diagnosis 2.2. Adaptive behavior and cognitive processes 2.3. Maladaptive behavior 2.4. Alzheimer’s disease and life span neuropathology in individuals with Down syndrome 2.5. Risk factors 2.6. Strategies for future research Acknowledgments References

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Department of Psychology, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 Department of Human Genetics, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 { Mental Retardation & Developmental Disabilities Branch, National Institute of Child Health and Human Development, Bethesda, Maryland 20892 } Department of Developmental Neurobiology, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York 10314 } The Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University College of Physicians and Surgeons, New York, NewYork 10032 ** Departments of Epidemiology and Psychiatry, Columbia University Medical Center, New York, New York 10032 {{ Department of Behavioral Psychology, Kennedy Krieger Institute, Baltimore, Maryland 21205 {{ Department of Psychiatry and Behavioral Medicine, Johns Hopkins University Medical School, Baltimore, Maryland 21205 * {

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Abstract Down syndrome is associated with increased mortality rates due to congenital cardiac defects and leukemia early in life, and with Alzheimer’s disease and a tendency toward premature aging later in life. Alzheimer’s disease was once considered an inexorable result of growing old with Down syndrome, but recent data indicate that risk does not reach 100%. Although some individuals exhibit signs and symptoms of Alzheimer’s disease in their 40s, other individuals have reached the age of 70 without developing dementia. This chapter presents a wealth of data from a longstanding longitudinal study with the overall objective of understanding and recounting the mechanisms responsible for these substantial individual differences.

1. Introduction Down syndrome is the most common chromosomal abnormality leading to intellectual disabilities, and results from any one of three different genotypes. The first, and most common, is free trisomy 21, where three full copies of the 21st chromosome are present (~95% of cases). The second is mosaic Down syndrome (~1% of cases), where some but not all cells are trisomic for chromosome 21. The degree of mosaicism can range from <1% to 99þ%. The third is translocation Down syndrome, where extra critical regions of chromosome 21 are attached to chromosome 14, 21, or 22 (~4% of cases). Most chromosome 21 translocations are now thought to be isochromosomes where the extra chromosome 21 material originated as a duplication of chromosome 21q material, originating de novo in postzygotic mitosis via misdivision (Gardner & Sutherland, 2004). The region at the end of the long arm of chromosome 21, including portions of bands 21q22.2 and 21q22.3, represents the ‘‘Down syndrome critical region,’’ the region generally believed to be responsible for much, but not all, of the Down syndrome phenotype. The presence, in triplicate, of the genes within this region is associated with many of the neuropathological and clinical features of Down syndrome (Korenberg et al., 1994; Robakis et al., 1987), although recent results from studies of mouse models suggest a more complex genotype–phenotype relationship (Olson et al., 2007). In the early twentieth century, mean survival for children with Down syndrome was 9 years (Penrose, 1949), and during the second half of that century placement of affected individuals in large institutional settings became an accepted practice (Lakin & Stancliffe, 2007). Since then, disability advocacy groups and other proponents of rights for individuals with disabilities have been effective in expanding supports that have led to important improvements in quality of life. However, issues related to aging into late adulthood were largely ignored until quite recently, probably

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due to the abbreviated life span that characterized previous generations (Carter & Jancar, 1983). In fact, it was not until 1985 that research which was explicitly focused on aging-related changes in health status and cognition of adults with intellectual disabilities, and in particular those with Down syndrome, began in earnest. The first book focusing on aging of adults with intellectual/developmental disabilities appeared in 1985 ( Janicki & Wisniewski, 1985), and since then, a wealth of information regarding the aging process in people with intellectual disabilities has been generated. One topic, the association between Down syndrome and Alzheimer’s disease, has perhaps received more attention than any other aspect of aging among adults with intellectual/developmental disabilities [including a previous chapter in this series (Zigman, Schupf, Zigman, & Silverman, 1993)]. Presenile dementia in adults with Down syndrome was first recognized more than 130 years ago (Fraser & Mitchell, 1876), and the development of some aspects of neuropathology characteristic of Alzheimer’s disease was noted in several classic studies ( Jervis, 1948; Malamud, 1972; Struwe, 1929). Late-onset or sporadic Alzheimer’s disease is the major cause of dementia among older people and currently affects over 26 million people worldwide (Brookmeyer, Johnson, Ziegler-Graham, & Arrighi, 2007). Clinically, Alzheimer’s disease is characterized by a mid- to late-life onset of progressive deterioration in cognitive and functional abilities, with considerable variability in behavioral manifestation. Alzheimer’s disease affects parts of the brain that control thought, memory, and language abilities during its earlier stages and progresses to other areas over time, causing serious declines in an affected individual’s ability to carry out all aspects of daily activities (Victor & Ropper, 2001). Three lesions are particularly characteristic of Alzheimer’s disease: (a) neuritic plaques, extracellular deposits of fibrillar b-amyloid surrounded by degenerating neuronal processes and terminals, (b) intraneuronal neurofibrillary tangles, primarily composed of abnormally hyperphospholated t-protein, and (c) vascular b-amyloidosis associated with fibrillar amyloid deposition within the vascular wall (Victor & Ropper, 2001). Over time, these pathological processes contribute to synaptic and neuronal loss, deterioration of neuronal networks, brain atrophy, and dementia (Victor & Ropper, 2001). Alzheimer’s disease has now become a major public health concern due to ever-increasing longevity and the resulting increase in the proportion of the world’s population over the age of 60 [10% in 2005 vs. an estimated 22% in 2050 (World Health Organization, 2005b)]. Annual costs in the United States, both direct (i.e., Medicare and Medicaid) and indirect [i.e., lost productivity of caretakers], have been estimated to exceed $148 billion in 2005, and are projected to increase to over $189 billion by 2015 (Alzheimer’s Association, 2007). A substantial increase in life expectancy for people with Down syndrome during recent decades can be linked to both societal and medical factors.

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Societal attitudes regarding the institutionalization of people with intellectual/developmental disabilities underwent a radical transition beginning in the 1960s, resulting in the depopulation and closing of many of the nation’s institutions that continues to this day (Landesman-Dwyer, 1981). Medical factors included the availability of corrective surgery for congenital cardiac problems (Glasson et al., 2002), common in children with Down syndrome (Yang, Rasmussen, & Friedman, 2002), and all the other general advances in medical care, nutrition and public health practices that have resulted in extensions of life expectancy for all Americans (Silverman, Zigman, Kim, Krinsky-McHale, & Wisniewski, 1998). Despite improved survival rates, people with Down syndrome continue to experience atypical life span development, with anatomic, immunologic, neurological, endocrine, and metabolic disorders characteristic of the phenotype (van Schrojenstein Lantman-de Valk, Haveman, & Crebolder, 1996). Down syndrome is still associated with increased mortality rates, both during early and later life span development, and age-specific mortality risk remains higher in adults with Down syndrome (Minin˜o, Heron, & Smith, 2006), even compared with other people with intellectual disabilities (Bittles et al., 2002). Whether, and when, life expectancy for people with Down syndrome will equal that of the typically developing population remains an open question, but the outlook continues to improve. Causes of increased mortality rates early in life are still due primarily to the increased incidence of congenital defects and leukemia. Causes of higher mortality rates later in life may be due to a number of factors, two of which are an increased risk for dementia due to Alzheimer’s disease and an apparent tendency toward premature aging (Yang et al., 2002). Dementia is defined in the current edition of the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994) as the development of multiple cognitive deficits, involving memory, and aphasia (language impairment), apraxia (motor impairment), agnosia (perceptual impairment), or disturbance in executive functioning. Additionally, dementia is characterized by substantial declines in adaptive abilities and significant functional impairment. Progressive deterioration also occurs in the ability to perform coordinated movements, and affected individuals eventually can no longer walk, show severe signs of disorientation and lose all self-care skills (Reisberg et al., 1986). Investigators at the New York State Institute for Basic Research in Mental Retardation [now Developmental Disabilities (IBR)] have conducted research on Down syndrome and Alzheimer’s disease during the last four decades. IBR opened its doors in 1966, with Dr. George Jervis as Director. Before his appointment at IBR, Dr. Jervis, a physician, had been a distinguished researcher and the Director of Research at Letchworth Village State School, at that time one of the largest institutions in the world caring for people with intellectual/developmental disabilities. His groundbreaking

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studies of the genetic defect responsible for phenylketonuria (PKU) were followed by seminal research regarding the development of Alzheimer’s disease in adults with Down syndrome. He published the first article directly linking Alzheimer’s disease-type neuropathology to clinical dementia in adults with Down syndrome ( Jervis, 1948). His interests in the neural underpinnings of behavior led him to develop a brain bank that included over 2,000 cases with their medical and behavioral records. This valuable archive stimulated a wide-range of subsequent research, much of which focused on psychological, neuropathological, and neurobiological aspects of aging and intellectual disabilities (Barcikowska et al., 1989; Popovitch et al., 1990; Silverman et al., 1993; Wegiel, Wisniewski, Dziewiatkowski, Popovitch, & Tarnawski, 1996), as well as on the linkage between Down syndrome and Alzheimer’s disease (Wisniewski, Dalton, McLachlan, Wen, & Wisniewski, 1985; Wisniewski, Wisniewski, & Wen, 1985). Dr. Jervis retired as IBR’s Director in 1973 and was succeeded by Dr. Henry Wisniewski, an internationally recognized authority on Alzheimer’s disease, and the association between Down syndrome, atypical aging and Alzheimer’s disease became a major part of IBR’s research agenda. The discrepancy between the ubiquity of Alzheimer’s disease neuropathology in adults with Down syndrome by age 35–40 without apparent signs and symptoms of dementia was one issue of immediate interest (Devenny et al., 1996), as were studies of the prevalence of dementia and Alzheimer’s disease neuropathology in adults with intellectual disabilities without Down syndrome (Barcikowska et al., 1989; Popovitch et al., 1990). The remainder of this chapter will acquaint the reader with an in-depth description of the IBR’s research programs on Down syndrome, aging, and Alzheimer’s disease and the implications of this research for improving the health and well-being of persons with Down syndrome. In 1993, when a previous chapter regarding Alzheimer’s disease in adults with Down syndrome appeared in this series (Zigman et al., 1993), the discrepancy between the prevalence of Alzheimer’s disease pathology in adults with Down syndrome (i.e., presumed to be 100% by age 40) and the prevalence of dementia (i.e., 2–5% by age 40 and 70% by age 70) was a major focus. One factor originally proposed to explain the discrepancy between the widespread presence of Alzheimer’s disease neuropathology and the less than universal occurrence of clinical dementia among adults with Down syndrome was diagnostic imprecision caused by preexisting cognitive impairments of varying severity (Silverman et al., 1998). Diagnostic overshadowing, a phenomenon in which signs and symptoms of psychopathology and dementia are attributed to intellectual disabilities rather than a separate disease process (Reiss, Levitan, & Szyszko, 1982) was also considered a very real possibility. However, results of our earlier program findings, as well as those of others, provided convincing evidence that the vast majority of adults with Down syndrome in their 30s and 40s did

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not have dementia (Devenny, Hill, Patxot, Silverman, & Wisniewski, 1992; Zigman, Schupf, Urv, Zigman, & Silverman, 2002) and relevant research programs have gone on to address other issues. Only minor consideration was given in that earlier chapter to explaining the variation in differential risk for dementia evident among adults with Down syndrome, and even less time to theorizing about factors that could reduce risk. Over the last 15 years, the field has advanced, and considerable attention will now be given to factors modifying risk of Alzheimer’s disease/dementia within the population with Down syndrome. Whereas Alzheimer’s disease was once considered an inexorable result of growing old with Down syndrome, recent data indicate that risk does not reach 100%. Although some individuals exhibit signs and symptoms of Alzheimer’s disease in their 40s, other individuals have reached the age of 70 without dementia (Head, Lott, Patterson, Doran, & Haier, 2007; Schupf, 2002; Zigman & Lott, 2007), and it is important to understand the mechanisms responsible for these substantial individual differences if promotion of successful aging is to be maximized. The remainder of this chapter is divided into eight parts. The first summarizes efforts to develop a test battery that would be sensitive to changes in functional and cognitive ability in adults with Down syndrome. The second describes efforts to develop procedures for classifying signs and symptoms of dementia objectively and reliably, a task complicated by the presence of preexisting cognitive impairments that can vary considerably in their severity within this population. The third reviews findings regarding changes in functional and cognitive capabilities as a consequence of aging and the development of Alzheimer’s disease. The fourth examines the occurrence of maladaptive behaviors and psychiatric symptoms associated with the progression of dementia. The fifth focuses on studies of the influence of neurogenetics and neuropathology on life span development and the Down syndrome phenotype. The sixth examines factors, both genetic and somatic, mediating overall and age-specific risk for dementia. Investigations of biomarkers, physical signs or laboratory measurements that occur in association with the development of a specific disease or disease process (Lesko & Atkinson, 2001) are discussed in the seventh section of this chapter. Finally, the eighth part of this chapter discusses implications of future research to improve the health and well-being of people with Down syndrome.

2. Down syndrome/Alzheimer’s Disease Research Program Much of the data described below were generated by IBR’s multidisciplinary program focused on aging, and the development of Alzheimer’s disease in adults with Down syndrome funded by the National Institutes of

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Health since the mid-1980s. Initially, this program was codirected by Drs. Henry Wisniewski and Wayne Silverman, with Dr. Silverman assuming the role of Principal Investigator in 1997. Early studies included individuals with intellectual disability without Down syndrome, but studies that are more recent have focused solely on adults with Down syndrome, primarily due to their features of atypical aging and dramatically increased risk of Alzheimer’s disease (Zigman et al., 1993; Zigman, Silverman, & Wisniewski, 1996). The common dataset for most of these studies includes descriptions of performance and health status collected during the long-term follow-up, for as much as 15–20 years, of more than 400 adults with Down syndrome over the age of 40 and more than 125 adults with intellectual disabilities without Down syndrome over the age of 60. The primary requirement for a clinical diagnosis of dementia is evidence of a decline in memory and at least one other aspect of cognition sufficient to impair personal activities of daily living (World Health Organization, 2005a). In the case of Alzheimer’s disease, impairments of memory typically affect the registration, storage, and retrieval of new information during relatively early stages of dementia, but previously learned and familiar material may be lost, particularly as the disease progresses. Evidence of these impairments in the presence of clear consciousness is required to ensure that delirium is not the principal cause. These impairments must have been evident for at least 6 months for a clinical diagnosis of dementia to be made. Further, for a diagnosis of Alzheimer’s disease, alternative causes of dementia must be ruled out (i.e., untreated hypothyroidism, traumatic dementia, Parkinson’s disease, dysfunction associated with late onset depression or other psychopathology, development of sensorimotor impairment, and stroke). In the general population without Down syndrome, the second most frequent cause of dementia is cerebrovascular disease. However, because the presence of Alzheimer’s disease neuropathology is virtually universal in adults with Down syndrome, ‘‘pure’’ vascular dementia would not be an appropriate diagnosis in this population, although there may be some mixed cases (Collacott, Cooper, & Ismail, 1994). Cognitive impairments of older adults with intellectual disability are, by definition, of longstanding duration, given that onset must have occurred before the age 18 (Luckasson et al., 2002). Therefore, the impact of Alzheimer’s disease, as well as of any other old age-associated dementing disorder, has to be assessed against a background of substantial preexisting impairment (Burt et al., 1998). Currently, there are no broadly adopted protocols for diagnosing Alzheimer’s disease in adults with intellectual disability, largely because tests routinely used to diagnose dementia were never intended to differentiate between dementia and cognitive impairments associated with intellectual disability. In addition, because adults with intellectual disability vary tremendously in cognitive capabilities from person to person, assessment methods need to be developed that can take this

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variation in baseline abilities into account. These considerations dictated the structure of the assessment battery. Measures were focused on those that were likely to be sensitive to changes associated with developmental aging and dementia, and/or could be useful in describing profiles of changes that differentiated between these two very different situations. In making selections of procedures, maximizing compatibility with recommendations published by a Working Group focused on assessment of dementia within the population with intellectual disability was desired (Aylward, Burt, Thorpe, Lai, & Dalton, 1997; Burt & Aylward, 2000). Direct participant testing had to be sufficiently brief and had to incorporate frequent breaks to avoid fatigue and to avoid approaching the limits of attention span, both of which could exert strong effects on performance. Given these considerations, the final battery of assessments included measures of adaptive and cognitive functioning together with a comprehensive review of clinical records. This battery included a mix of procedures involving direct assessments of performance and informant reports. Informant-based assessments included: (a) the Dementia Questionnaire for Mentally Retarded Persons (DMR; Evenhuis, 1992, 1996), a questionnaire measuring changes in social and cognitive functioning suggestive of dementia, (b) Part I of the American Association on Mental Deficiency Adaptive Behavior Scale (ABS) (Nihira, Foster, Shellhaas, & Leland, 1974), an instrument measuring functional abilities, (c) the Reiss Screen for Maladaptive Behavior (Reiss & Valenti-Hein, 1994) to screen for possible depression, psychosis and behavior management problems, the symptoms of which might mimic dementia or be associated with its progression, and (d) a Life Events Questionnaire (LEQ; G. Seltzer, personal communication, January 31, 1997), a measure of stressful life events that might increase risk for dementia or result in a temporary pseudodementia syndrome. Cognitive abilities of all Program participants have also been described based upon the following individually administered tests: (a) a slightly enhanced version of the Down Syndrome Mental Status Examination (DSMSE) developed by Haxby (1989) and Silverman et al. (2004), (b) the IBR Evaluation of Mental Status (IBREMS; Wisniewski & Hill, 1985), (c) the Test for Severe Impairment (TSI; Albert & Cohen, 1992), (d) an adaptation of the McCarthy (McCarthy, 1972) verbal fluency test (MCVF), (e) the Beery Visual Motor Integration (VMI) test to ascertain construction ability (Beery & Buktenica, 1989), and (f) a modified version of the Selective Reminding Test (SRT; Buschke, 1973; Krinsky-McHale, Devenny, & Silverman, 2002) appropriate for use with the target population. Blood samples have been collected to examine genetic markers that might be associated with risk for Alzheimer’s disease or be sensitive to disease progression, as well as to confirm the clinical diagnosis of Down syndrome for participants without prior cytogenetic diagnoses of Down syndrome. Neurological examinations have also been conducted to determine

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differential diagnoses for participants who develop dementia. [Full descriptions of the instrument battery and its measurement characteristics have been previously published (Silverman et al., 2004; Zigman et al., 2004).] Subsequent to each participant’s full evaluation, conducted at 14–18month intervals, dementia status was classified in a clinical consensus conference consistent with ICD-10 criteria (World Health Organization, 2005a). Dementia status classifications included: (a) nondemented, indicating that criteria for dementia were definitely not met, (b) questionable, indicating substantial uncertainty regarding dementia status, although some indications of mild functional and cognitive declines were present, (c) possible dementia, indicating that ICD-10 criteria were met but that evidence of progressive decline over an extended period of time was judged to be insufficient for clinical judgment to be ‘‘definite,’’ (d) definite dementia, indicating that ICD-10 criteria were met and there was convincing evidence of progressive decline over time, (e) uncertain with complications, indicating that criteria for dementia were met, but that symptoms might have been caused by some other substantial concern, usually a medical condition unrelated to a dementing disorder (e.g., loss of vision, poorly resolved hip fracture, loss of social support network due to relocation), and (f) undeterminable, indicating that preexisting impairments were so severe that detection of declines indicative of dementia was not possible. Using these case classifications, a number of studies relating diagnostic criteria, patterns of adaptive and cognitive change, risk factors and the development of maladaptive behaviors, and psychiatric symptomology to dementia status, both cross-sectionally and longitudinally, were conducted.

2.1. Classification and diagnosis As noted above, making a diagnosis of Alzheimer’s disease and/or dementia in adults with preexisting intellectual disability can be a daunting task; in fact, it is significantly more difficult than making the similar diagnosis in typically developing adults. In the general population, there is a baseline level of ability that can be reasonably assumed. While, clearly, there is interindividual variability in intellectual functioning, the vast majority of adults are self-sufficient in daily activities of living as well as in the ability to perform typical cognitive tasks necessary for independent coping within the complex demands of modern society. When these abilities are lost, it is clear that dementia is present, and the true task is to determine its etiology. Adults with Down syndrome, in contrast, have substantial lifelong cognitive impairments of varying degrees that complicate diagnosis of dementia. Clinical presentation can be atypical, both for Alzheimer’s disease and for other conditions causing dementia, and even illnesses completely unrelated to central nervous system function can present as a pseudodementia (either due to secondary symptoms of the condition itself or due to atypical side

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effects of medications used to treat the primary concern). Given this situation, the optimal method of diagnosing dementia in adults with Down syndrome is to document substantial decline from previous status. Unfortunately, appropriate baseline premorbid data are unlikely to be available and, even if they are, they may be of uncertain quality/validity. These issues could be addressed by development of practical dementia assessment methods targeting the population with intellectual disabilities analogous to those currently used in evaluations of elderly adults without intellectual disabilities, but with specific classification criteria anchored to premorbid levels of intellectual ability [e.g., measured against available full scale intelligence quotient test scores (FSIQ)]. When diagnosing dementia in the typically developing population, both informant interviews (e.g., Berg, 1988; Blessed, Tomlinson, & Roth, 1968; Teri et al., 1992) and direct assessments of mental status (e.g., Folstein, Folstein, & McHugh, 1975) can provide valid indications of dementia status from a single administration in most cases, and it would be of enormous value if comparable methods and classification criteria were available for use with adults who have intellectual disabilities. Silverman and colleagues (Silverman, Devenny, Krinsky-McHale, Ryan, & Zigman, 2006; Silverman et al., 2004) have tackled this issue using the DMR, an informant-based measure of dementia status developed by Evenhuis (Evenhuis, 1992, 1996), and the IBREMS, a direct assessment of cognitive status based upon the MiniMental State Exam (Folstein, Folstein, & McHugh, 1975), which was modified (Wisniewski & Hill, 1985) to be used with adults who have intellectual disabilities. Silverman (Silverman et al., 2004) evaluated the sensitivity and specificity of these two instruments for classifying dementia status, as determined in the clinical consensus conferences mentioned above. Specificity is defined as the proportion of individuals ‘‘without dementia’’ correctly classified as not having dementia; sensitivity is defined by the proportion of individuals ‘‘with dementia’’ correctly classified. The DMR generates two scores: the Sum of Cognitive Scores (SCS, reflecting cognitive abilities) and the Sum of Social Scores (SSS, reflecting social skills). By plotting the SCS against FSIQs, Silverman et al. (2004) was able to generate a function that distinguished adults with dementia from those without dementia. As illustrated in Fig. 4.1, classification of SCS falling on or above this curve as positive for dementia produced results that converged well with the Consensus Dementia Status ratings, indicating a strong overall association between SCS and dementia status. To determine the diagnostic utility of the IBREMS, Silverman plotted total scores (minus colors and concentration scores which for most participants proved to be too easy or too difficult, respectively) against FSIQ and again generated a function that distinguished adults with dementia from those without dementia. Figure 4.2, illustrates this function, and with scores falling below this curve indicating dementia, results were again quite

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Figure 4.1 Scatterplot relating the Sum of Cognitive Scores (Evenhuis, 1995) for individuals within each consensus dementia status group. (The plotted line indicates IQ-referenced criteria for distinguishing individuals with dementia from those without dementia.) Reprinted with the kind permission of the American Association on Intellectual and Developmental Disabilities (Silverman et al., 2004).

consistent with the Consensus Dementia Status rating. However, the correspondence between consensus classifications and IBREMS results were imperfect, and, for example, 21% of nondemented individuals were misclassified as having dementia. This rate of false positives would make use in clinical settings impractical, and therefore strategies to improve accuracy were explored. Silverman evaluated the sensitivity of two combinations of the FSIQreferenced criteria, one requiring a positive indicator on both the DMR-SCS and the IBREMS to be consistent with dementia and the other requiring a positive indicator on either of the two standards (Silverman et al., 2004).

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Figure 4.2 Scatterplot relating IQs to performance on the modified IBR Mental Status Examination (IBREMS) for individuals within each consensus dementia status group. (The plotted line indicates IQ-referenced criteria for distinguishing individuals with from those without dementia.) Reprinted with the kind permission of the American Association on Intellectual and Developmental Disabilities (Silverman et al., 2004).

When both FSIQ-referenced criteria had to be met for a dementia classification to be made, specificity increased to .85, indicating that only 15 of every 100 individuals without dementia (consensus categories of either ‘‘nondemented’’ or ‘‘questionable’’) would be misclassified. In contrast, sensitivity was only .78; indicating that slightly more than 1 in 5 individuals with dementia would be incorrectly classified as not having dementia. An alternative was to classify individuals as having dementia if either one or the other of the two FSIQ-referenced criteria were met. Of course, this is a more liberal criterion and, as expected, specificity dropped to.70, an unacceptable rate of error. In contrast, every case having dementia was now classified correctly, and a way to maintain this high sensitivity while improving specificity needed to be found. Fortunately, this was accomplished by simply adding consideration of caregiver concern into the classification procedure.

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Operationally, if concerns about Alzheimer’s disease or nonspecific memory loss were either present in clinical records or expressed during informant interviews, and either of the two FSIQ-referenced criteria were met, then the case would be classified as having dementia. If neither FSIQ-referenced criterion was met or if no concern about dementia or Alzheimer’s disease were expressed in the clinical record or by an informant, then the case would be classified as not having dementia. This expanded classification rule produced a specificity of .90 and a sensitivity of .89. The results of these analyses indicated that, in principle, relatively straightforward procedures involving a combination of direct assessments, informant interviews, and an examination of medical records at a single point in time could provide a valid basis for classification of dementia when performance is referenced to an individual’s FSIQ. Because dementia, by its very nature, involves declines in cognition and function, users of these types of assessment tools should prefer to base final diagnoses on actual observations of substantial decline over time, but these findings demonstrated that declines can be inferred even when high-quality baseline descriptions of cognitive capabilities are unavailable. Future efforts should seek additional measures of performance together with criteria that might be more sensitive to early stages of Alzheimer’s disease. It will also be important to confirm the validity of the specific criteria described by Silverman in independent samples of adults with Down syndrome, given that they were generated post hoc (Silverman et al., 2004). Finally, these results can only be generalized to populations with composite FSIQs over 25 and parallel procedures appropriate for use with people having more severe lifelong impairments need to be developed. Once classification criteria conceptually comparable to those described here are in place, more informed decisions regarding diagnosis, prognosis, and evolving treatment options can be made. The DMR-SCS and the IBREMS are just two of potentially many tools that show promise for classifying the dementia status of adults with intellectual disabilities. When interpreted thoughtfully, these assessment methods should be of clear value to clinicians as they evaluate adults with intellectual disabilities who find themselves in the same position as any other individual with real or suspected dementia.

2.2. Adaptive behavior and cognitive processes 2.2.1. Adaptive behavior Dementia is defined in the current edition of the Diagnostic and Statistical Manual of Mental Disorders as the development of multiple cognitive deficits, involving memory, and aphasia (language impairment), apraxia (motor impairment), agnosia (perceptual impairment), or disturbance in executive functioning. Additionally, it is characterized by a substantial decline in adaptive abilities and significant functional impairment. Zigman and

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colleagues (Strauss & Zigman, 1996; Zigman, Schupf, Lubin, & Silverman, 1987; Zigman, Schupf, Sersen, & Silverman, 1996; Zigman et al., 2002) have conducted a series of studies examining functional impairment in adults with intellectual disabilities, both with and without Down syndrome, as a function of age, disability etiology, and dementia diagnosis. The age-associated incidence of significant decline in adaptive behavior, presumed to reflect dementia, and the temporal pattern of decline in specific functional skill domains were examined in a longitudinal study of 646 adults with intellectual disabilities through 88 years of age (Zigman et al., 2002). Cumulative incidence of significant decline in adaptive behavior for adults with Down syndrome increased from less than 4% at age 50 to 67% by age 72, whereas cumulative incidence of significant decline in adaptive behavior for adults with intellectual disabilities without Down syndrome increased from less than 2% at age 50 to 52% at age 88. Rates of dementia in adults with intellectual disabilities without Down syndrome were equivalent to the general population rate of Alzheimer’s disease [i.e., ﬃ47% affected over age 85 (Evans et al., 1989)]. Given that individual differences in vulnerability to Alzheimer’s disease have been hypothesized to be due to variation in lifelong cognitive capabilities (the cognitive ‘‘reserve’’ hypothesis), adults with intellectual disabilities should be at increased risk. This suggests that factors determining intelligence may have little or no direct relationship to risk for dementia and that other predisposing factors for Alzheimer’s disease may be responsible for the association between risk and lifelong cognitive capabilities within the general population. However, this conclusion needs to be qualified somewhat. Because individuals were recruited varying widely in their age at entry into this study, the possibility that older participants, who should have been at highest risk for dementia, were, as a group, physically more robust than their original birth cohort must be considered. In other words, differential healthy survivor effects may have masked population differences. Among adults experiencing overall decline on the ABS, Part 1, four separate clusters of adaptive functioning differing in the timing and magnitude of change over time were found (Zigman et al., 2002). Relatively large and early declines in performance were observed for care of clothing/dressing/undressing, domestic activities, and vocational activities. Relatively early, but somewhat smaller declines in performance were seen in responsibility, socialization, economic activities, physical development, travel and general independent functioning activities. Proficiency in these skills may be considered necessary to function competently in everyday activities of daily life outside the home. Clusters reflecting more basic activities of daily living skills declined slightly later. Larger declines were observed for self-direction, toileting, numbers, time and cleanliness. Smaller declines were seen for comprehension, social language, appearance, eating and expression. In general, these results indicated that functional declines

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are first noted in skills that are more complex and then progress to more basic and fundamental abilities. Not surprisingly, skills related to eating, understanding spoken language, and ambulating were among the last to be affected. These types of patterns are consistent with the clinical progression of Alzheimer’s disease for adults in the typically developing population (Perneczky et al., 2006). Three additional studies using two alternative adaptive behavior scales with thousands of participants from both New York and California revealed generally comparable results (Strauss & Zigman, 1996; Zigman et al., 1987; Zigman, Schupf et al., 1996), as has a similar study based in England (Prasher, Chung, & Haque, 1998). As has been stated previously, standard diagnostic methods used to evaluate individuals with suspected dementia in the general population are not appropriate for use with adults with Down syndrome (see Silverman et al., 1998), many of whom have never developed the specific cognitive and adaptive skills that are measured by these assessment instruments. Therefore, the use of the ABS as a surrogate measure of dementia could meet a very real need for informing clinical diagnosis. However, the emphasis of the ABS on functional behavior may result in dementia being diagnosed relatively late in the disease process, as small changes in various higher level cognitive abilities may not yet affect performance measures (Krinsky-McHale et al., 2002). Optimally, a highly sensitive and specific assessment battery will eventually be developed that uses the most reliable and valid aspects of each instrument to classify dementia in Down syndrome at the earliest possible stage. 2.2.2. Cognitive processes, aging, and dementia in Down syndrome 2.2.2.1. Program description Devenny and her colleagues (Devenny et al., 1992; Devenny, Krinsky-McHale, Sersen, & Silverman, 2000; Devenny et al., 1996; Devenny et al., 2005; Devenny, Zimmerli, Kittler, & Krinsky-McHale, 2002; Kittler, Krinsky-McHale, & Devenny, 2004, 2006; Krinsky-McHale, Devenny, Kittler, & Silverman, 2003; Krinsky-McHale et al., 2002) have examined the effects of aging on memory and cognition of adults with intellectual disabilities. The major goals of these studies have been to characterize changes in memory and cognition associated with normal aging in adults with intellectual disabilities and to distinguish them from the declines associated with dementia and to develop methods useful for recognizing Alzheimer’s disease in its earliest stages. The general research strategy involved recruitment of a large sample of convenience (N ¼ 192) and the prospective tracking of status over time, with some individuals followed for almost 20 years. Participants were initially selected on the basis of the following inclusion criteria: no suspicion of dementia by caregivers at the time of their entry into the study, IQ >35, age >30 years, no uncontrolled seizures or severe motor restrictions, no severe sensory impairments and participation in a community workshop.

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Adults were chosen who had overall functioning levels in the mild-moderate range of intellectual disability so that their scores on a cognitive battery assessment could provide reliable and objective measurement of any decline over time that might emerge. (A large number of participants in this study were also enrolled in the multidisciplinary study described above). The test battery included the IBREMS (Wisniewski & Hill, 1985) to evaluate mental status, the modified SRT (Buschke, 1973) to measure episodic memory, the Visual Delayed Match-to-Sample Test (VDMST; Devenny et al., 1992) to measure short-term visual memory, the Digit Span to measure verbal working memory (Wechsler, 1974), the Cued Recall Test (CRT) to measure performance on multiple memory processes, the forward and backward Corsi Span task to measure visuospatial working memory, and the raw scores of the Wechsler Intelligence Scale for Children-Revised (WISC-R) (Wechsler, 1974) to provide a profile of overall cognitive functioning. Early findings indicated that adults with Down syndrome maintained their overall cognitive abilities at least through their 40s and many maintained them through older ages (Devenny et al., 1996), confirming the findings already described of a disparity between the age of onset of dementia and the presumed onset of the neuropathology of Alzheimer’s disease (e.g., Zigman et al., 1987; Zigman, Schupf et al., 1996). However, decline in cognition associated with both ‘‘normal aging’’ and dementia became evident as participants continued to age. 2.2.2.2. Memory processes Declines in memory are a predominant behavioral indication of early-stage dementia. Memory, however, is not a single entity, but a complex system with multiple components. While it is important to recognize that components of memory can influence one another, and that these interactions may differ in populations with and without intellectual/developmental disability (as well as with and without dementia), selective influences of aging and dementia within the memory system can still be examined. One component, episodic memory, is involved in the encoding and retrieval of events located in time and place and can be assessed using listlearning tasks. The SRT, a test of episodic memory [modified from a task employed in the general population (Buschke, 1973)], was found to be sensitive to declines associated with normal aging in healthy adults with Down syndrome (Devenny et al., 1996; Krinsky-McHale et al., 2002). In addition, it was also determined that individuals with dementia showed consistent declines on the SRT, and an in-depth evaluation of performance on this task showed that both storage and retrieval of test items were affected (Krinsky-McHale et al., 2002). While decline in the SRT performance was consistent for adults developing dementia, it has already been noted that, in practice, performance would rarely be assessed before the emergence of concerns about possible dementia.

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A test that could distinguish between individuals with and without dementia based upon a single administration would be a more useful clinical tool, and this need seems to be met by a modified version of the CRT (Buschke, 1984). The original version of this test was developed for the general population as another method to assess memory performance, and the method entails presenting a list of items to be recalled together with category cues specific to each item (e.g., ball: toy; mouse: animal). By selecting items of low vocabulary levels, reducing the number of items for presentation and recall, and providing opportunities for initial list-learning, nondemented adults with Down syndrome were able to perform well. More importantly, even individuals with low scores on free recall retrieved many additional items when category cues were provided. In contrast, individuals with early-stage dementia performed poorly, for not only the free recall portion of the test, but also when cues were provided. In a recent analysis including 115 adults with Down syndrome, 32 of whom had a medical diagnosis of Alzheimer’s disease, a total score on the CRT (i.e., free plus cued recall) of 23 on three trials (maximum possible score ¼ 36) yielded a sensitivity of 91% and specificity of 75% for detecting dementia (Devenny, Krinsky-McHale, & Kittler, 2006 August), suggesting that this method may be useful clinically even with a single administration. Interestingly, this criterion seemed to work well regardless of premorbid IQ, at least within the range tested, suggesting that use of this method in broad practice could be quite straightforward. To gain a better understanding of aging, dementia, and memory processes, the test battery was expanded to include measures of auditory and visuospatial working memory. Baddeley (2000) has conceptualized working memory as the processes that extract information from the environment (or from longstanding personal knowledge) and temporarily maintain it in consciousness. Baddeley’s framework includes four components, one responsible for controlling processing within the system (Central Executive) and three subsystems responsible for temporary storage of information: (a) the phonological loop for sound and speech, (b) the visuospatial sketchpad for visual information, and (c) an episodic buffer dedicated to forming integrated representations and chronological ordering. The auditory/phonological loop component was examined in one study (Kittler et al., 2004), with a forward and backward Digit span task and by the immediate repetition of word lists consisting of three types of words: monosyllabic, phonologically different words; monosyllabic, phonologically similar words; and multisyllabic words. The visuospatial sketchpad was also studied with a forward and backward Corsi Span task. Findings replicated the well-established tendency for children and young adults with Down syndrome to exhibit relatively better performance on visuospatial tasks compared to verbal tasks, an advantage that persisted in older adulthood. This contrasted with findings for adults with intellectual/ developmental disability from unknown etiologies that showed a more

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typical pattern of a relative advantage for auditory working memory. In fact, adults with Down syndrome were poorer than their peers with intellectual/developmental disability from other etiologies on all word lists (Kittler et al., 2004). Phonological loop processes seem to be preserved in the very earliest stages of dementia, but declines in performance on the tasks became apparent as dementia progressed (Devenny et al., 2000). The presence of verbal intrusions (irrelevant responses made in the course of recalling word lists) suggests difficulty in executive control and might be early indications of cognitive decline. Individuals with Down syndrome who made even a single intrusion on any one of the tasks were more likely to show subsequent declines in other measures of cognition 3 years later (Kittler et al., 2006). Implicit memory involves a very different type of processing, and reflects the acquisition of knowledge and its retrieval without awareness or intentionality. It is thought to be less sensitive to variations in factors such as cognitive ability, aging, and severity of early to mid-stage Alzheimer’s disease. For example, implicit memory can be measured by a fragmented pictures task (Corwin & Snodgrass, 1987). The procedure requires pictures of familiar objects to be identified from a sequence of segments that starts with a very sparse representation and builds up, through ordered steps, to a completely intact and easily identifiable drawing. The initial task does not require the picture or its fragmented representations to be remembered, but information is ‘‘automatically’’ stored in memory nevertheless, and representation of the images results in picture identification at a more fragmented state in the sequence. This type of implicit memory has been found to be less affected by aging and FSIQ than other aspects of memory (KrinskyMcHale et al., 2003), and in fact it was better preserved in adults with Down syndrome who developed dementia (Krinsky-McHale et al., 2005). 2.2.2.3. Other cognitive processes Early in the longitudinal studies, it was observed that individuals who were showing signs of early-stage dementia also had difficulty on tasks measuring visuospatial organization, such as the Block Design subtest from the WISC-R (Wechsler, 1974). This task consists of reproducing patterns from models using Kohs blocks in which each block has surfaces that are solid red, solid white, and red and white separated diagonally. However, on this task not all participants were able to achieve a sufficiently high score, even when healthy, to allow for the measurement of change. Therefore, an adaptation described by Haxby (1989) was added that extends the test by eight simpler trials. Participants who were showing signs of memory impairment also experienced significant decline on the combined Block Design task (Devenny et al., 2000). Declines on a paper-and-pencil cancellation task assessing selective attention also occurred as much as 2 years before a diagnosis of dementia in adults

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with Down syndrome (Krinsky-McHale et al., 2005). The task simply requires prechosen target figures embedded in a page of other pictures to be marked, placing minimal demands on memory. Scoring involved consideration of both accuracy and speed. Adults with Down syndrome with what now is suspected to be ‘‘mild cognitive impairment’’ (MCI) were slower and made more errors (crossing out additional test items) than their healthy peers, but they were still able to adequately identify targets. By the time these same individuals reached early-stage dementia, they also had difficulty in selectively attending to targets correctly. 2.2.2.4. Case studies In addition to the wealth of data provided from the large-scale prospective studies described above, single case studies can also help to illustrate diversity in the outcome of the aging process in adults with Down syndrome. A 70-year-old man with a free trisomy 21 karyotype has been one of the research program’s participants for over 16 years, and his performance profile represents a model of successful aging (KrinskyMcHale et al., 2008). He has mild to moderate intellectual disability and a history of cataracts and hearing loss, normal thyroid functioning, and no congenital heart defect. Across multiple administrations of the assessment battery described above, no signs of substantial declines on measures of memory or adaptive behavior have occurred and visuospatial abilities have shown small declines consistent with normal aging. This case study confirmed that dementia associated with Alzheimer’s disease could be avoided, even through the seventh decade of life, for individuals with Down syndrome despite the presence of a complete third copy of chromosome 21. Additional studies are now needed to identify the specific factors supporting successful aging within this population. A second case study involved a woman, also with a free trisomy 21 karyotype, who died at the age of 57 after showing cognitive and behavioral declines associated with dementia (Devenny et al., 2005). Descriptions by caregivers indicated lapses in her judgment, social withdrawal, and the presence of an eating disorder 5 years before her diagnosis. At the time of her diagnosis, substantial declines were evident in episodic memory and visuospatial organization. Orientation to time was also quite impaired as measured by the IBREMS. Although caregivers observed that her ability to travel within her immediate neighborhood had clearly declined, she continued to answer questions on the IBREMS related to orientation to place correctly for the next 3 years. This illustrates a pattern of sequential decline in various abilities throughout the progression of dementia and the need for both direct cognitive testing and systematic informant reports. Further examination of declines in memory and other cognitive functions should provide clinicians and researchers with valid and reliable metrics of change as well as objective assessments of cognitive and functional status that

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can be diagnostic of both MCI and dementia in adults with Down syndrome throughout the full range of intellectual functioning.

2.3. Maladaptive behavior In the typically developing population, the development of Alzheimer’s disease is often accompanied by the occurrence of psychopathology and behavior problems (Scarmeas et al., 2007; Teng, Lu, & Cummings, 2007). In fact, disruptive behavior is very common in Alzheimer’s disease and predicts cognitive and functional decline as well as future out-of-home placement (Teng et al., 2007). Research on Alzheimer’s disease in Down syndrome has primarily emphasized adaptive, cognitive, and physiological changes, with psychopathology and maladaptive behavior receiving far less attention. Subtle changes in various maladaptive behaviors, especially among individuals with more severe impairments, may be among the earliest indicators caregivers are likely to notice for individuals who may be in the beginning stages of dementia. Precision in diagnosis is especially important for individuals with Down syndrome where preexisting maladaptive behaviors may be exacerbated by declines in cognitive and adaptive behavior; where any new declines may overtax already limited coping skills; and where individuals with different levels of functioning may present underlying changes in status quite differently. Midway though the large multidisciplinary study described above, a project was added to investigate behavioral changes (i.e., maladaptive behavior and psychopathology) related to age-associated adaptive declines in adults with intellectual disabilities (both with and without Down syndrome; Urv, Zigman, & Silverman, 2003). Although individuals with no significant adaptive decline displayed stable patterns of maladaptive behavior over a 3-year period, those with declines in functional status showed patterns that were more variable. Certain maladaptive behaviors were related to the onset of adaptive declines, with increasing concerns in some areas emerging even before adaptive declines were noted (e.g., lack of boundaries). Other behaviors increased as adaptive declines developed (e.g., withdrawal). In general, findings again suggested similarities in the course of dementia of adults with and without intellectual disabilities and indicated that increases in selected areas of maladaptive behavior may be early indicators of concern for individuals at risk (Urv et al., 2003). A second study investigated changes in maladaptive behaviors related to specific stages of dementia in adults with Down syndrome (Urv, Zigman, & Silverman, 2008). Generally, individuals who were neither demented nor affected by MCI exhibited a lesser severity of maladaptive behavior than did other participants. Differences in the patterns of maladaptive behavior in individuals as a function of dementia status were evident in both the breadth of concerns and their severity. Individuals transitioning from ‘‘healthy’’

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aging into what might reflect early indications of Alzheimer’s disease displayed increased aggression, fearfulness, sadness, sleep problems, social inadequacy, stealing, and general regressive behavior. Continued analyses of these data are aimed at determining specific symptoms that can be successfully used as metrics of the onset of MCI and frank dementia.

2.4. Alzheimer’s disease and life span neuropathology in individuals with Down syndrome Neuropathology characteristic of some key features of Alzheimer’s disease is a virtually universal occurrence in people with Down syndrome over the age of 40 (Mann & Esiri, 1989; Wisniewski, Dalton et al., 1985). In adults with Down syndrome, this pathology is superimposed on a neural substrate already affected by preexisting developmental abnormalities. Therefore, as dementia must be assessed against a baseline of lifelong intellectual disabilities (Aylward et al., 1997), neuropathology must be assessed against neurodevelopmental abnormalities that include defects of neurogenesis, synaptogenesis and lamination producing reductions in the sizes of specific brain structures (Crome, 1972; Raz et al., 1995), and a reduced number of neurons and synapses (Ross, Galaburda, & Kemper, 1984; Wisniewski, 1990). Neuropathological studies have indicated that although trisomy 21 is associated with prenatal defects of neuro- and synaptogenesis, significant gross brain pathology is not present in utero but emerges during early postnatal development (e.g., Wisniewski, 1990). Brain weight at birth is roughly comparable to (or only slightly lower than) that of normal neonates, but subsequent reduction in maturation results in clear retardation of brain growth by age 5. During the first 5 years of life, significant inhibition of growth of dendritic trees and dendritic atrophy is also observed in children with Down syndrome (Schmidt-Sidor, Wisniewski, Shepard, & Sersen, 1990; Wisniewski, 1990). In part, the developmental abnormalities and intellectual disability characteristic of Down syndrome might be associated with an extra copy of the MNB/DYRK1A (minibrain-kinase) gene. The gene encoding minibrainkinase maps to the Down syndrome critical region (HSA21q22.2), and its overexpression has been suggested as a strong candidate for causing cognitive impairments associated with Down syndrome. For example, transgenic mice carrying an extra human minibrain-kinase gene show defects in learning and memory (Smith et al., 1997; Smith & Rubin, 1997). Experimental studies of hippocampal cells overexpressing minibrain-kinase have shown large increases in apoptotic cell death and reduction in neuronal differentiation (Park, Yang, Yoon, & Chung, 2007; Wisniewski, 1990), and this mechanism may underlie the altered neuronal plasticity and intellectual disability observed in Down syndrome (Murakami et al., 2006).

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b-amyloid deposition in neuritic plaques and in the wall of brain vessels, neurofibrillary degeneration, and neuronal loss are major neuropathological hallmarks of Alzheimer’s disease. The gene coding for amyloid precursor protein (APP), a protein from which b-amyloid peptide is derived, is located on the proximal/mid part of the long arm of chromosome 21 (21q21.3), and its overexpression is considered a factor critical for the early onset of brain amyloidosis seen in people with Down syndrome. In the early childhood of individuals with and without Down syndrome, the majority of neurons in the cortex and subcortical structures are b-amyloid positive, and the distribution of b-amyloid within the brain established during late childhood is maintained during adulthood. The stable distribution of intracellular b-amyloid without neuronal pathology during essentially the entire life span suggests that b-amyloid within neurons represents a product of normal metabolism. Thus, the extracellular b-amyloid deposited in neuritic plaques contributing to the progression of Alzheimer’s disease would seem to reflect another process (Wegiel et al., 2007). A unique feature of brain amyloidosis in Down syndrome is the deposition of b-amyloid in diffuse, nonfibrillar, and amorphous plaques. This seems to begin as early as 8 years of age (Leverenz & Raskind, 1998), with many individuals with Down syndrome under age 35 showing these deposits (Kida, Wisniewski, & Wisniewski, 1995). These early plaques appear to have negligible effects on neurons, and their deposition has no observable clinical consequences (Wisniewski & Wegiel, 1995). Thus, there seems to be a period of about 30 years during which numerous but almost exclusively diffuse, nonfibrillized amyloid deposits are formed and this occurs in the absence of any other indication of Alzheimer’s disease neuropathology (Wisniewski & Wegiel, 1995). The onset of dementia observed in older people with Down syndrome, typically in their 50s, appears to be related to neurofibrillary degeneration and the development of neuritic, fibrillized plaques associated with neuropil degeneration (Sadowski et al., 1999; Wegiel et al., 1996). [The neuropil is a complex network of axonal, dendritic, and glial arborizations that constitute the bulk of the grey matter in which nerve cell bodies are embedded (Stegman, 2006).] While early brain amyloidosis appears to be directly associated with overexpression of the APP gene for people with Down syndrome, the precise mechanisms leading to neurofibrillary degeneration, another key feature of Alzheimer’s neuropathology, is unknown. Phosphorylation is a process by which a phosphate [PO4] group is added to a protein molecule. This is a fundamental mechanism controlling the activity of enzymes and receptors, which are switched ‘‘on’’ or ‘‘off’’ by phosphorylation and dephosphorylation, respectively, providing crucial regulation of appropriate cell function. In neurons, phosphorylation is involved in normal neuritic outgrowth and axonal transport processes, and aberrant phosphorylation plays a pivotal role in the accumulation

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of neurofibrillary tangles, abnormal twisted protein filaments that form within affected neurons and are composed mainly of hyperphosphorylated t-protein (Hardy & Allsop, 1991). Recent studies revealed that neurofibrillary tangles are immunoreactive with antibodies detecting minibrain-kinase. A higher prevalence of minibrain kinase-positive neurofibrillary tangles in the brains of people with Down syndrome and Alzheimer’s disease and familial early onset Alzheimer’s disease than in other individuals with sporadic Alzheimer’s disease suggests that overexpressed minibrain-kinase may be the factor modifying the onset and progression of neurofibrillary degeneration in Down syndrome (Wegiel et al., 2008, submitted (in press)). Hyperphosphorylation of t-protein in the brains of transgenic mice with an extra human minibrain-kinase gene also suggests that overexpression of minibrain-kinase could contribute to the early onset of Alzheimer’s disease associated with Down syndrome (Ryoo et al., 2007), and it is important to discover the mechanism by which minibrainkinase influences t-protein processing and how this mechanism is affected by life span development. The implications of this body of research extend beyond the origins of Alzheimer’s type neuropathology in adults with Down syndrome. Given that the neurobiological deficits noted in the neural substrate of infants with Down syndrome may develop postnatally, and that the development of neuritic plaques and neurofibrillary pathology tends not to appear until adults with Down syndrome are in their 50s, it is at least theoretically possible that therapeutic inhibition of excessive minibrain-kinase activity may prevent or reduce both developmental abnormalities as well as Alzheimer’s disease-type neuropathology. Clearly, these results should be extended before their implications for intervention are considered, but they do portend hope for preventing or minimizing cognitive impairments associated with the Trisomy 21 genotype.

2.5. Risk factors A major effort has been placed on the discovery of risk factors associated with Alzheimer’s disease within the population of adults with Down syndrome, defined simply as factors that either increase or decrease that risk. The heterogeneity in the clinical expression of Alzheimer’s disease observed within the population of adults with Down syndrome may be due to the additive and/or interactive effects of a number of these risk factors, including, but not limited to genotypic variation, sex, age, health activity, and diet (e.g., Chace et al., 2007; Patel et al., 2004; Patel, Seltzer, Wu, & Schupf, 2001; Prasher et al., 2008 in press; Schupf, Kapell, Lee, Ottman, & Mayeux, 1994; Schupf et al., 1996, 1998, 2003, 2006, 2007; Schupf, Kapell et al., 2001; Schupf, Patel et al., 2001; Zigman, Jenkins, Tycko, Schupf, & Silverman, 2005; Zigman et al., 2007; Zigman, Schupf, & Silverman, 2005). The search

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for factors predictive of dementia in people with Down syndrome closely parallels analogous investigations in the typically developing population. It is important to emphasize that while risk factors are associated with the likelihood that a disease will occur, all individuals at elevated risk will not necessarily develop the disease, nor will individuals at reduced risk be immune (Mausner & Kramer, 1985). 2.5.1. Age One factor that has been conclusively linked to an increase in risk for dementia in Down syndrome is advancing age (e.g., Schupf, 2002; Schupf et al., 1996, 2003; Zigman, Schupf, Haveman, & Silverman, 1997). These studies have consistently found that overall dementia risk increases substantially beginning in the late 40s or early 50s, some 20 years earlier than it does within the general population. However, it is clear that individuals vary considerably in their age at onset. A small minority of adults with Down syndrome begin to experience substantial declines in cognition before age 50, yet another minority is able to mature well into their late 60s or early 70s without experiencing signs or symptoms of Alzheimer’s disease. Thus, there must be risk factors in addition to the presence of Down syndrome that contribute to this heterogeneity (Schupf, 2002). 2.5.2. Shared genetic susceptibility Nondisjunction, or the failure of chromosome pairs to separate properly during meiosis or mitosis, is the principal cause of Down syndrome, and is of maternal origin over 90% of the time (Freeman et al., 2007). Schupf and her associates (Schupf et al., 1994; Schupf, Kapell et al., 2001) therefore postulated that if there was a shared genetic susceptibility for Down syndrome and Alzheimer’s disease, it should only be most evident among mothers and maternal relatives of individuals with Down syndrome. They further hypothesized that evidence of shared susceptibility would be strongest in the population of relatively young mothers for whom having child with Down syndrome at a relatively young age might reflect an accelerated aging process in which they were biologically older than their chronological age. Findings clearly supported these hypotheses. There was a fourfold increase in risk of dementia among mothers who gave birth to their children with Down syndrome under 35 years of age compared with mothers who were older than 35 years of age when their child with Down syndrome was born or compared with mothers of children with other intellectual disabilities. There was no increase in risk of dementia among mothers who were over 35 when their child with Down syndrome was born, and no differential patterns of dementia risk in older versus younger fathers of children with Down syndrome or children with other intellectual disabilities. In a follow-up study of the familial aggregation of Down syndrome and Alzheimer’s disease, Schupf replicated her previous findings

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and clearly determined that the increased risk for Alzheimer’s disease was not reflected in increased risk for other age-related neurological diseases (Schupf, Kapell et al., 2001). This suggests that risk for both Alzheimer’s disease and having a child with Down syndrome at a relatively young age is determined, at least in part, by some common underlying mechanism, perhaps controlling some aspect rate of aging. 2.5.3. Sex differences and estrogen Evidence of increased risk for Alzheimer’s disease in women compared with men in the typically developing population is reasonably robust (Yip, Brayne, & Matthews, 2006); although see Edland, Rocca, Petersen, Cha, and Kokmen (2002). The most widely accepted explanation of this difference postulates that postmenopausal estrogen deficiency in women contributes to decreased cholinergic function as well as increased b-amyloid deposition that over time leads to Alzheimer’s disease (Schupf, 2002). The existing literature regarding sex differences in risk for dementia in adults with Down syndrome is limited. As has been reviewed by Schupf (Lai et al., 1999; Schupf, 2002; Schupf et al., 1998), no firm conclusions regarding the influence of sex can be made at this time. Nevertheless, several lines of evidence support the hypothesis that postmenopausal estrogen deficiency may contribute to individual differences in the cognitive declines associated with Alzheimer’s disease among women with Down syndrome (Schupf, 2002). In a series of studies, Schupf and her colleagues (Patel et al., 2004, 2001; Schupf et al., 2003, 2006, 1997; Seltzer, Schupf, & Wu, 2001) examined a large sample of women with Down syndrome, in collaboration with the mulidisciplinary study described above. Using the identical assessment battery, data were collected every 14–18 months from cognitive assessments, caregiver interviews, medical record reviews, blood assays, and neurological examinations to establish the dementia status of each study participant and to relate performance to measures sensitive to, in this case, estrogen biochemistry. In one study, women with early onset of menopause (46 years or younger) had earlier onset and increased risk of Alzheimer’s disease compared with women with onset of menopause after 46 years, presumably related to long-term lower estrogen bioavailability for the former group (Schupf et al., 2003). In a follow-up prospective study, postmenopausal women with Down syndrome and lower bioavailable estradiol were more likely to develop Alzheimer’s disease (Schupf et al., 2006). Similar findings were apparent in a series of studies relating estrogen levels to cognitive ability. Premenopausal women performed better than age-matched male peers did while postmenopausal women performed more poorly than agematched male peers did. Premenopausal women and young men showed no significant declines in cognition over time, while postmenopausal women, but not their matched male peers, showed significant declines in cognitive

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function (Patel et al., 2004, 2001). These results support the hypothesis that cognitive declines are associated with estrogen deficiency in older women, and provide convincing support for the hypothesis that reduction in bioavailable estrogen following menopause contributes to the cascade of pathological processes leading to Alzheimer’s disease. In the typically developing population, reductions in bioavailable estrogen levels also has been related to increase in risk for Alzheimer’s disease (Hoskin, Tang, Manly, & Mayeux, 2004), but estrogen or hormone replacement therapy has variously been related either to slower declines in cognitive function and decreased risk of Alzheimer’s disease (Tang et al., 1996) or to increases in risk for Alzheimer’s disease (Shumaker et al., 2004). Clinical trials focused explicitly on women with Down syndrome will be necessary to determine whether estrogen replacement in women with Down syndrome can help to reduce their risk for Alzheimer’s disease and its associated dementia. If initial studies suggest benefits, then additional research when used in the premenopausal period will be needed to determine the most effective treatment regimens. 2.5.4. Cognitive reserve Down syndrome affects brain development in many ways. These include, but are not limited to, decreased brain weight and size, reduced frontal lobe volume, decreased dendritic branching, and increased apoptosis early in fetal development (Capone, 2001). Typically developing brains can tolerate losses of ‘‘small’’ numbers of neurons, regardless of the causes, and consequences for cognitive and functional capabilities will be negligible until an individual’s capacity to compensate for these losses, referred to as ‘‘cognitive reserve,’’ is exceeded. For the typically developing population, there is support for a cognitive reserve theory of individual differences in risk for dementia (Manly, Schupf, Tang, & Stern, 2005; Riley, Snowdon, Desrosiers, & Markesbery, 2005; Roe, Xiong, Miller, & Morris, 2007; Snowdon et al., 1996; Whalley et al., 2000), with lower literacy or educational attainment related to earlier incidences of Alzheimer’s disease. Because the degree of loss sufficient to exceed an individual’s cognitive reserve should vary as a function of education and premorbid intelligence ( Jorm, 1996), it is not unreasonable to assume that people with Down syndrome who function at higher levels [e.g., higher premorbid FSIQs, education, occupation, verbal ability (all of which are highly interrelated)] should be at decreased risk for Alzheimer’s disease compared with their peers with lower levels of functioning. Differences in the design and outcome of the few existing studies regarding cognitive reserve and Alzheimer’s disease risk in adults with Down syndrome make it difficult to draw conclusive inferences. However, in a series of studies where FSIQ was included as a covariate in analyses, FSIQ was not related to risk or age at onset of Alzheimer’s disease for adults with Down syndrome (Schupf et al.,

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2006; Zigman et al., 2007; Zigman, Schupf et al., 2005). Although rate of cognitive decline was related to lower initial levels of functioning in a few studies (e.g., Prasher & Chung, 1996), contradictory findings have also been found (Prasher, Chung et al., 1998; Zigman, Schupf et al., 2005). These results, in concert with the previously reported finding that rates of Alzheimer’s disease in populations with intellectual disability without Down syndrome were equivalent to the typically developing population, suggest that factors determining intelligence may have little or no direct relationship to risk for Alzheimer’s disease. These conclusions are clearly intriguing, but it is possible that the older adults with more severe intellectual disability represent the very healthiest segment of their birth cohorts, introducing a ‘‘healthy survivor’’ confound. With the weight of the body of literature supporting the concept of cognitive reserve for the typically developing population, it seems premature to reject the hypothesis at this point, but additional studies critically evaluating the concept should be conducted. 2.5.5. Apolipoprotein E The Apolipoprotein E (APOE) gene, located on chromosome 19, is the most important genetic risk factor found thus far for late onset Alzheimer’s disease in the typically developing population (Corder et al., 1993; Saunders et al., 1993). The APOE gene, which occurs predominately in three variants or alleles (i.e., e2, e3, or e4), is involved in cholesterol transport and lipid metabolism in plasma (Dupuy et al., 2001) as well as accumulation of b-amyloid protein in the brains of typically developing elderly people, both with and without Alzheimer’s disease (Lambert et al., 2001; Polvikowski et al., 1995]. In numerous studies, participants with Alzheimer’s disease have been found to have higher frequencies of the APOE e4 allele compared with those with other APOE genotypes, and those with the e4 allele have an earlier age of onset of Alzheimer’s disease (Corder et al., 1993; de-Andrade, Larrandaburu, Callegari-Jacques, Gastaldo, & Hutz, 2000; Isbir et al., 2001; Mayeux et al., 1993). APOE e4 is also associated with greater deposition of b-amyloid protein in the brains of adults with and without Down syndrome (Hyman, West, Rebeck, Lai, & Mann, 1995), and as for the typically developing population, increased risk for Alzheimer’s disease has been associated with the presence of an e4 allele (Deb et al., 2000; Prasher, Chowdhury, Rowe, & Bain, 1997; Schupf et al., 1996). The presence of an APOE e4 allele has also been related to increased overall risk of mortality for adults with Down syndrome without Alzheimer’s disease (Zigman, Jenkins et al., 2005), and it may be associated with intellectual decline during early adulthood (Del Bo et al., 1997). More positively, the presence of the least common allele, APOE e2, has been associated with a decreased risk of Alzheimer’s disease for adults with Down syndrome (Lai et al., 1999; Royston et al., 1994; Rubinsztein et al., 1999; Schupf et al., 1996), again showing an effect that parallels observations within

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the general population. Thus, the influence of APOE genotype on risk for morbidity, mortality, and Alzheimer’s disease in Down syndrome suggests that future studies of Alzheimer’s disease risk in Down syndrome should be mindful of its potential effects (Schupf et al., 2007; Zigman et al., 2007; Zigman, Jenkins et al., 2005). 2.5.6. SORL1 Variants in the sortilin-related receptor gene (SORL1), located on chromosome 11, have been found to increase the risk for late onset Alzheimer’s disease in various populations (Rogaeva et al., 2007). It is thought that SORL1 acts to aid in the disposal of excess b-amyloid protein (Rogaeva et al., 2007). Therefore, the under-expression of SORL1 may contribute to an increase in amyloid b-peptides, leading to the amyloid cascade that characterizes Alzheimer’s disease. Given the high background level of b-amyloid protein in the brains of adults with Down syndrome, it seemed natural that any genetic variation that leads to an increase in amyloid b-protein would significantly affect the risk of Alzheimer’s disease. Lee and colleagues investigated the associations between each of seven variants in the gene for SORL1 to age at onset and risk for Alzheimer’s disease and found that homozygosity for two alleles was associated with a later age at onset and reduced overall risk of Alzheimer’s disease (Lee et al., 2007). These findings indicate a modest association of variants in SORL1 with Alzheimer’s disease within the adult population with Down syndrome. However, any conclusion about the relationship between SORL1 and Alzheimer’s disease in adults with Down syndrome must be considered tentative until further studies clarify the mechanism by which this genotypic variability influences phenotype for this vulnerable population (Lee et al., 2007). 2.5.7. Atypical karyotypes The Down syndrome genotype encompasses three different patterns of chromosomal abnormalities: free trisomy 21, translocation Down syndrome, and mosaic Down syndrome (previously described). A handful of case studies [reviewed by Schupf (2002)] have been conducted to discern whether atypical karyotypes are associated with better long-term outcomes compared to free trisomy 21. For example, elderly individuals with partial trisomy 21(i.e., disomy of selected genes) or mosaic Down syndrome may not develop the clinical and/or pathological signs of Alzheimer’s disease at relatively young ages. In fact, variants in genotype have been found in quite elderly people with Down syndrome who remained nondemented, including selective disomy of the APP gene on Chromosome 21 (Prasher, Farrer et al., 1998; Schupf, 2002). Zigman and his colleagues examined the comparative rate of mosaicism in adults with Down syndrome as a function of age and found a significantly increased

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rate of mosaicism in adults with Down syndrome aged 65 and older, but the majority of these ‘‘old’’ individuals still had free trisomy 21 (Zigman et al., 2000). With the advent of microarray analyses capable of determining DNA sequence copy number, it seems likely that additional genetic variations will be found to influence risk for Alzheimer’s disease in adults with Down syndrome. 2.5.8. Cholesterol and statins An interaction among APOE genotype, serum cholesterol level, and Alzheimer’s disease within the general population has been proposed in a number of reports (Evans et al., 2000; Hoshino, Kamino, & Matsumoto, 2002; Isbir et al., 2001; Wehr et al., 2000). Cholesterol is transported by high-density lipoproteins such as APOE, and it has been hypothesized that the relationship between APOE and risk of Alzheimer’s disease may be linked to cholesterol metabolism (Launer, White, Petrovitch, Ross, & Curb, 2001). To date, though, evidence has been inconsistent, with total cholesterol not always significantly related to risk for or severity of Alzheimer’s disease (Evans et al., 2000; Kivipelto et al., 2001; Romas, Tang, Berglund, & Mayeux, 1999). Statins or HMG-CoA [3 hydroxy-3 methylglutaryl-coenzyme A] reductase inhibitors are currently the most widely prescribed class of cholesterol-lowering medication. Statin use has also been found to be related to a lower risk for Alzheimer’s disease in a number of studies (Green, Jayakumar, Benke, & Farrer, 2002; Jick, Zornberg, Jick, Seshadri, & Drachman, 2000), although results of a recent large study were negative (Arvanitakis et al., 2008). Until recently, no study had examined the relationship between total cholesterol levels, statin use, and Alzheimer’s disease in adults with Down syndrome, but Zigman and his colleagues have found that a total cholesterol level of 200 mg/dl or more was associated with increased risk of developing Alzheimer’s disease in this population (Zigman et al., 2007). Further, for participants with a total cholesterol level of 200 mg/dl or more, statin use significantly lowered dementia risk to a level comparable to that of their peers with lower total cholesterol. If the protective effects of statins can be further validated in a clinical trial, these findings suggest that their use may delay or prevent Alzheimer’s disease onset in vulnerable populations. It must be noted that current clinical trials of statin use for Alzheimer’s disease prevention in typically developing populations have not produced encouraging results (Sparks et al., 2005; Zandi et al., 2005), but the life span neurobiology of adults with Down syndrome and their elevated amyloid levels make this population unique. Therefore, the potential benefit of statin use specifically for individuals with Down syndrome with elevated total cholesterol levels still seems worth investigating.

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2.5.9. Biomarkers Biomarkers are physical signs or laboratory measurements that occur in association with the development of a specific disease or disease process (Lesko & Atkinson, 2001). They can help confirm diagnoses, especially in conditions like Alzheimer’s disease where, with currently available technology, the ‘‘gold standard’’ diagnosis can only be determined by direct examination of brain tissue (rarely from a biopsy, but more usually based upon postmortem findings). Biomarkers can also monitor disease progression, which can be especially useful in quantifying the effects of any available treatment regimen. Because biomarkers are strongly associated with disease risk, detection of early changes in biomarker levels provides an opportunity for early intervention (if effective interventions are available) to delay or prevent disease onset. In Alzheimer’s disease, which is especially difficult to diagnose in adults with Down syndrome, a reliable and valid biomarker would be extremely useful for informing diagnostic decisions, as well as for planning care and treatment. To date, validated biomarkers for Alzheimer’s disease in adults with Down syndrome have yet to be discovered. However, a few have been investigated. These include measures of the quantity and type of b-amyloid protein found in blood plasma (Schupf et al., 2007; Schupf, Patel et al., 2001), and telomere size in metaphase and interphase preparations as well as on individual chromosomes ( Jenkins, Velinov, Ye, Gu, Pang et al., 2006; Jenkins, Velinov, Ye, Gu, Li et al., 2006). 2.5.10. Amyloid b-peptides As discussed already, Alzheimer’s disease is associated with the deposition of extracellular b-amyloid protein within the brain. Two b-amyloid peptides (i.e., b-amyloid 1–40 and b-amyloid 1–42) found in brain, cerebral spinal fluid, and blood plasma of typically developing adults have been found to be related to cognitive status and incident Alzheimer’s disease (Blennow & Hampel, 2003; Naslund et al., 2000), although conflicting findings can be found (van Oijen, Hofman, Soares, Koudstaal, & Breteler, 2006). b-amyloid 1–40 and b-amyloid 1–42 are generated by sequential proteolytic cleavage by b and d secretases of the APP gene. In a series of studies using both crosssectional and prospective analyses, Schupf reported that plasma b-amyloid 1–42 levels but not b-amyloid 1–40 levels in demented adults with Down syndrome were increased compared with nondemented adults with Down syndrome (Schupf, Patel et al., 2001). In addition, participants who were nondemented at baseline with the highest levels of plasma b-amyloid 1–42 levels were more than two times as likely to develop Alzheimer’s disease as those with lower levels (Schupf et al., 2007), and participants with the highest levels of b-amyloid peptide 1–42 were twice as likely to die during the course of the study (Schupf et al., 2007). Although

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these findings indicate that progression of Alzheimer’s disease may reflect b-amyloid 1–42 levels in plasma, the precise relationship between brain pathology and systematic b-amyloid metabolism is still unclear. More discouraging with respect to the issue of biomarkers, the overlap in the distributions of plasma b-amyloid 1–42 levels in groups with and without Alzheimer’s disease may reflect that these measures cannot be used to inform diagnostic decisions in clinical settings.

2.5.11. Telomere shortening Telomeres are sequences of DNA on chromosome ends consisting of a series of repeats of the TTAGGG nucleotide sequence. These DNA sequences undergo shortening with each cell division, serving as markers of a cell’s replicative history and an indicator of cellular aging. Telomere shortening has been linked to Alzheimer’s disease in the typically developing population (Panossian et al., 2003), and Jenkins et al. (2006) hypothesized that a similar association might exist in adults with Down syndrome. Using quantitative telomere protein nucleic acid fluorescent in situ hybridization analyses of metaphase and interphase preparations from age-matched pairs of participants with Down syndrome with and without dementia, Jenkins observed: (a) shorter telomeres in individuals with dementia, (b) that individual chromosomes 1 and 21 could be used alone and/or in combination to detect telomere shortening (Jenkins et al., 2006), (c) that cells from individuals with dementia or MCI had reduced numbers of telomere signals when analyzed using a PNA telomere probe ( Jenkins et al., 2007), and (e) shorter telomeres in individuals with MCI ( Jenkins et al., 2008 accepted). These preliminary results are encouraging, but the procedure used required samples from each affected case together with his or her matched comparison to be processed simultaneously, and in clinical practice, this circumstance would rarely occur. Additional research is underway to standardize procedures that should eliminate the need for simultaneous processing of paired samples.

2.6. Strategies for future research Individuals with Down syndrome are at a significantly increased risk for developing Alzheimer’s disease compared to typically developing individuals; this fact has been known for more than 100 years. However, contrary to the generally accepted belief, as recent as 25 years ago, that cognitive decline was inevitable by middle age in this population, there is a more positive outlook for adults with Down syndrome as they age into their senior years.

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The studies presented above, as well as others, have demonstrated that successful aging for adults with Down syndrome is possible, even as they age into their late 60s and early 70s (e.g., Krinsky-McHale et al., 2008). It appears that risk of Alzheimer’s disease may be modified by many factors, static and not amenable to change as well as fluid and potentially modifiable through intervention. The cholesterol findings, for example, seem to indicate that lowering total cholesterol levels and/or using cholesterol-lowering medications such as statins, may lead to a decreased risk of developing Alzheimer’s disease for people with relatively high cholesterol. However, because these findings were based upon an observational study where there was no control over prescription practices or other medical treatments, they are not sufficiently convincing to make any recommendations regarding the broad use of cholesterol reduction practices to reduce lower Alzheimer’s disease risk, and more rigorously controlled clinical trials are needed. While investments in clinical trials targeting Alzheimer’s disease in the typically developing population have increased substantially in recent years, few studies have included samples of adults with Down syndrome. (Two such trials are currently in progress, but no findings have been published to date.) Whether the lack of clinical trials in adults with Down syndrome is a function of lack of interest or a hesitancy to conduct ‘‘greater than minimal risk’’ studies of individuals without the capacity to provide full informed consent, the scientific community and government agencies must move quickly to encourage research in this area. Given the increasing population of elderly adults with Down syndrome at an elevated risk for Alzheimer’s disease (Silverman et al., 1998), these issues need to be promptly addressed. Knowledge of biomarkers of Alzheimer’s disease is still at a rudimentary stage. There are some exciting advances in the use of advanced imaging techniques, but such techniques might not be as useful in adults with Down syndrome where the background level of b-amyloid deposition is substantial and neuropathological changes are superimposed on a background of variable abnormal neurodevelopment. Currently, there are no generally available biomarkers with sufficient sensitivity and specificity to predict accurately the onset of dementia or to monitor the rate of Alzheimer’s disease progression. Advances in molecular biology and neurogenetics may provide the most positive outlook for people with Down syndrome. If further research clarifies the role of specific genes in regulating neurobiological development and brain function throughout the life span, interventions based on this knowledge could prevent or minimize developmental impairments as well as prevent the neurodegeneration associated with Alzheimer’s disease. Of course, these are long-term goals that, today, are more dreams than

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expectations. However, it was only a short time ago that survival into adulthood was just a dream for most people with Down syndrome, and there is every reason to believe that current research will provide the foundation for further, perhaps even more impressive, future advances in prevention and treatment.

ACKNOWLEDGMENTS Supported by NIH grants AG014763, HD35897, HD37425, and HD43960; by funds provided by the National Down Syndrome Society in collaboration with the NIH; by Alzheimer’s Association grants IIRG-07-60558, IIRG-99-1598, and IIRG-96-077; and by New York State through its Office of Mental Retardation and Developmental Disabilities.

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Wisniewski, H. M., & Wegiel, J. (1995). The neuropathology of Alzheimer’s disease. Neuroimaging Clinics of North America, 5, 45–57. Wisniewski, K., Dalton, A. J., McLachlan, C., Wen, G. Y., & Wisniewski, H. M. (1985). Alzheimer’s disease in Down’s syndrome: Clinicopathologic studies. Neurology, 35, 957–961. Wisniewski, K., & Hill, A., (Eds.) (1985). Clinical aspects of dementia in mental retardation and developmental disabilities Baltimore, MD: Brookes. Wisniewski, K., Wisniewski, H. M., & Wen, G. Y. (1985). Occurrence of neuropathological changes and dementia of Alzheimer’s disease in Down’s syndrome. Annals of Neurology, 17, 278–282. Wisniewski, K. E. (1990). Down syndrome children often have brain with maturation delay, retardation of growth, and cortical dysgenesis. American Journal of Medical Genetics Supplement, 7, 274–281. World Health Organization (2005a). International Statistical Classification of Diseases and Health Related Problems (The) ICD-10 Second Edition: Author. World Health Organization (2005b). World Population Prospects: The 2004 Revision: Author. Yang, Q., Rasmussen, S. A., & Friedman, J. M. (2002). Mortality associated with Down’s syndrome in the USA from 1983 to 1997: A population-based study. Lancet, 359, 1019–1025. Yip, A. G., Brayne, C., & Matthews, F. E. (2006). Risk factors for incident dementia in England and Wales: The Medical Research Council Cognitive Function and Ageing Study. A population-based nested case-control study. Age and Ageing, 35, 154–160. Zandi, P. P., Sparks, D. L., Khachaturian, A. S., Tschanz, J., Norton, M., Steinberg, M., et al. (2005). Do statins reduce risk of incident Dementia and Alzheimer disease?: The cache county study. Archives of General Psychiatry, 62, 217–224. Zigman, W. B., Jenkins, E., Mehta, P., Schupf, N., Urv, T., Silverman, W., et al. (2000). Alzheimer’s disease, survival, and genetics in the ‘‘oldest old’’ with Down syndrome. Paper presented at the Down Syndrome Research Foundation (Canada)/National Down Syndrome Society (US) New Directions in Down Syndrome Research Conference. Zigman, W. B., Jenkins, E. C., Tycko, B., Schupf, N., & Silverman, W. (2005). Mortality is associated with apolipoprotein E epsilon4 in nondemented adults with Down syndrome. Neuroscience Letters, 390, 93–97. Zigman, W. B., & Lott, I. T. (2007). Alzheimer’s disease in Down syndrome: Neurobiology and risk. Mental Retardation and Developmental Disabilities Research Reviews, 13, 237–246. Zigman, W. B., Schupf, N., Devenny, D. A., Miezejeski, C., Ryan, R., Urv, T. K., et al. (2004). Incidence and prevalence of dementia in elderly adults with mental retardation without Down syndrome. American Journal on Mental Retardation, 109, 126–141. Zigman, W. B., Schupf, N., Haveman, M., & Silverman, W. (1997). The epidemiology of Alzheimer disease in intellectual disability: Results and recommendations from an international conference. Journal of Intellectual Disability Research, 41, 76–80. Zigman, W. B., Schupf, N., Jenkins, E. C., Urv, T. K., Tycko, B., & Silverman, W. (2007). Cholesterol level, statin use and Alzheimer’s disease in adults with Down syndrome. Neuroscience Letters, 416, 279–284. Zigman, W. B., Schupf, N., Lubin, R. A., & Silverman, W. P. (1987). Premature regression of adults with Down syndrome. American Journal of Mental Deficiency, 92, 161–168. Zigman, W. B., Schupf, N., Sersen, E., & Silverman, W. (1996). Prevalence of dementia in adults with and without Down syndrome. American Journal on Mental Retardation, 100, 403–412. Zigman, W. B., Schupf, N., & Silverman, W. (2005). Cognitive reserve and dementia risk in adults with Down syndrome. Paper presented at the 38th Annual Gatlinburg Conference on Research & Theory in Intellectual & Developmental Disabilities.

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Zigman, W. B., Schupf, N., Urv, T., Zigman, A., & Silverman, W. (2002). Incidence and temporal patterns of adaptive behavior change in adults with mental retardation. American Journal on Mental Retardation, 107, 161–174. Zigman, W., Schupf, N., Zigman, A., & Silverman, W. (1993). Aging and Alzheimer disease in people with mental retardation. In N.W Bray (Ed.), International Review of Research in Mental Retardation (Vol. 19, pp. 41–70). New York: Academic Press. Zigman, W. B., Silverman, W., & Wisniewski, H. M. (1996). Aging and Alzheimer’s disease in Down syndrome: Clinical and pathological changes. Mental Retardation and Developmental Disabilities Research Reviews, 2, 73–79.

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C H A P T E R

F I V E

Foolish Action in Adults with Intellectual Disabilities: The Forgotten Problem of Risk-Unawareness Stephen Greenspan Contents 1. Introduction 2. A Four-Factor Model of Foolish Action 2.1. Situational demand as a contributing factor 2.2. Cognition as a contributing factor 2.3. Affect and state as contributing factors 2.4. Personality as a contributing factor 2.5. Summary 3. Varieties of Foolish Acts Committed By Different Populations 3.1. Foolish acts in adults With ID 3.2. Foolish acts in normally developing youths 3.3. Foolish acts in adults of average or above-average IQ 3.4. Comparing nature and causes of foolish acts across groups 4. Brain Damage and Foolish Action: FASD as an Exemplar 4.1. Examples of foolish action in adults with FASD 5. Research and Policy Implications 5.1. Research implications 5.2. Policy implications 6. Conclusion References

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Abstract This chapter explores the importance of the construct of ‘‘foolish action.’’ Foolish action is behavior that has a high likelihood of backfiring, because of a failure to attend to risks that are obvious to most people. A comparison of

University of Colorado Health Sciences Center, Colorado, 80045; Email: [email protected] International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00005-0

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actual foolish episodes in three groups (adults with intellectual disabilities [ID], adults, and youths without ID) illuminates the role of foolish action, especially induced socially foolish action, as a threat to the successful community adaptation of adults with ID. Research and policy implications of the once appreciated, but recently forgotten, construct of foolish action for the field of ID are discussed. One consequence of this discussion is to move the construct of ‘‘gullibility’’ (induced social foolishness) from being just one among many maladaptive behaviors associated with ID to something much more central to the ID construct.

‘‘Who is not a fool?’’ [‘‘Qui non stultus?’’] Horace (65–8 BCE), Satires, 2.3.158

1. Introduction The term ‘‘foolish action,’’ in the title of a chapter aimed at researchers specializing in intellectual disabilities (ID), is likely to stir up concern among those old enough to remember when highly dehumanizing nouns such as ‘‘defective,’’ ‘‘imbecile,’’ ‘‘fool,’’ and ‘‘moron’’ (a term that means ‘‘foolishness’’ in Greek) were in wide currency. I have strongly supported the move towards more respectful language (Greenspan & Love, 1995a,b) but feel that it is appropriate to use the term foolish action to describe an overlooked aspect of human behavior that (a) is found in all people, not just those with ID and (b) goes to the heart of why people with ID need services, supports, and protections. In his book The Cloak of Competence, Robert Edgerton (1967/1993) wrote that ‘‘. . . the social sciences have failed to make a concerted effort to develop a sociology, or social psychology, of stupidity’’ (pp. 5–6). By stupidity (which is a harsh pejorative term for which I have substituted the softer and more descriptive term foolish action), Edgerton meant the real-world incompetent behaviors that people with impaired intelligence engage in during the course of everyday life. The need to study real-world incompetence stems from the fact that the ID field has tended to use artificial constructs, such as ‘‘adaptive behavior,’’ that were intended to tap aspects of incompetence, but that were solidified in measures without first examining the precise nature of that incompetence as it manifests itself in real-world settings. As a result, the items on adaptive behavior measures tend to reflect conventional behaviors (such as maintaining good hygiene) that, however important for leading a healthy or happy life, do not tap those ‘‘cognitive’’ and ‘‘foolishness-avoiding’’ behaviors that experienced clinicians and family members see as much more central to the ID construct (Borthwick-Duffy, Greenspan, & Ho, 2006).

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The basic position that is developed in this chapter is that the critical struggle of people with ID to adapt in the community—as studied by Edgerton in The Cloak of Competence—is to avoid behaving, or appearing to behave, foolishly. A consequence of this position is that if adaptive behavior is to ever become more central to the definition and diagnosis of ID it must be viewed and assessed not in terms of the ability to button one’s shirt or play a game but rather as the ability to avoid behaving foolishly. By foolish action, I am referring to ‘‘behavior that has a high likelihood of backfiring, sometimes with disastrous consequences, because of a failure to attend to risks that are obvious to most people.’’ If foolish action involves the failure to recognize obvious risk, then its obverse, ‘‘wise action,’’ can be defined as ‘‘behavior that reflects an awareness of relatively subtle and hidden risks.’’ This can be seen in the ‘‘wise counsel’’ to avoid some course of action (such as padding one’s expense account) that is superficially attractive and seemingly safe but which contains risk of consequences that could be catastrophic if realized. Thus, foolish action lacks a ‘‘brake’’ mechanism in the face of any superficially attractive behavioral option, while the majority of people possess such a brake when the risks are obvious, but not necessarily when the risks are subtle and appreciated mainly by the very wise. These risks fall into two broad categories: ‘‘practical’’ and ‘‘social.’’ Practical risks involve potential physical harm (to person or property). Two examples of foolish action in the practical domain would be eating foods that are dangerous for someone with particular health concerns (Smyth & Bell, 2006), and failing to take proper precautionsfor severeweather, as was thecase with Millard Fillmore Hathaway, the much-loved ‘‘town fool’’ profiled by Nora Groce (1992), who froze to death one winter when he failed to take adequate precautions. Social risks involve potential interpersonal harm (to oneself or others); two examples of foolish action in the social domain would be allowing a suspicious-looking stranger into your home, and being coerced into performing demeaning sexual acts, as in the ‘‘Glen Ridge Rape’’ case profiled by Bernard Lefkowitz (1997). This typology of foolish actions is depicted in Fig. 5.1. In line with the previous discussion, two forms of foolish action are depicted in Fig. 5.1: practically foolish action (characterized by insufficient awareness of physical danger) and socially foolish action (characterized by insufficient awareness of interpersonal danger). Socially foolish action is further subdivided into ‘‘induced’’ and ‘‘noninduced’’ subtypes. Induced socially foolish action mainly manifests itself as ‘‘gullibility,’’ which is the aspect of foolish action that first drew my attention (Greenspan, 1998; Greenspan, Loughlin, & Black, 2001). Induced socially foolish action occurs in the context of manipulation by one or more other persons, in which one agrees to a course of action that is not in one’s interest, on the basis of false information or encouragement. An example, from the recent

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Foolish action

Practically foolish action

Socially foolish action

Noninduced

Figure 5.1

Induced (Gullible)

Types of foolish action.

movie documentary ‘‘The Collector of Bedford Street’’ (Elliot, 2002) occurred when the protagonist, a 60-year-old man with mild ID named Larry Selman, continued to lend his apartment key to homeless people he barely knew, even after his possessions along with those of others in his building had been repeatedly stolen or damaged. In theory, one could divide practically foolish action into induced and noninduced subtypes as well, which would have created more symmetry in Fig. 5.1. An example of induced practically foolish action would be ingesting a dangerous chemical substance on the advice of a highly unqualified acquaintance. I prefer to keep the typology as it is, however, as induction is a common, and possibly the most common, variety of socially foolish action, while I believe it to be a relatively uncommon variety of practically foolish action. Furthermore, one might consider every act of induced practically foolish action to be also a socially foolish act. Thus, in the case of a person ingesting a dangerous substance on the advice of an acquaintance, while the danger is physical (death or serious physical harm), the act is social in that it occurs in an interpersonal context. I recognize that this distinction may be unconvincing, however, and it is possible that a future version of this theory will adopt a more symmetrical typology. Noninduced socially foolish action also is not in one’s own interest, but is not triggered by encouragement, whether deceptive or nondeceptive, from someone else. Several examples of noninduced socially foolish action can be found in a decades-old study exploring why people with ID are fired from competitive employment (Greenspan & Shoultz, 1981). These examples include a hotel chambermaid who told guests to ‘‘get your ass out of bed,’’ an office worker who interrupted formal meetings to talk about what he had seen on TV the night before, and a factory worker who masturbated regularly in a stall in the men’s room.

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All human beings behave foolishly on occasion, but people with ID behave foolishly more frequently and in situations where danger signs are evident to most individuals, and their foolish actions are more likely to have serious life-altering consequences. While foolish action in people with or without ID are influenced by numerous noncognitive factors such as emotion, sexual drive, personality, exhaustion, and context, cognitive factors (such as ability to read people or recognize risk) are more likely to come into play whenever a person with ID behaves foolishly. In fact, I shall argue that it is possible to redefine ID as ‘‘a condition which, because of significant intellectual limitations, makes it difficult for an individual to anticipate negative consequences of everyday decisions and, thus, causes the individual to need supports and protections to minimize the risks from his or her ‘foolish’ actions.’’ In the subtitle of this chapter, I describe risk-unawareness, which I see as the core problem underlying foolish action in people with ID, as a ‘‘forgotten problem.’’ I describe it that way because at one time it was widely discussed, but today one can barely find any mention of the problem. As example, nineteenth century textbooks in psychiatry (Morrison, 1824) and mental retardation (Ireland, 1877) emphasized deficits in ‘‘credulity’’ (a construct closely related to gullibility) as a core characteristic, but today awareness of this problem is just beginning to filter back into the consciousness of the field. Part of the reason why deficits in general, and vulnerabilities in particular, are so little emphasized in the recent ID literature is, undoubtedly a result of the so-called paradigm shift (Bradley & Knoll, 1995) away from ‘‘paternalism’’ (over-control motivated by the need to protect) to supports (under-control motivated by ethics and a need to spur growth). In spite of this shift away from emphasizing risk and vulnerability, concern over the practical and social dangers stemming from foolish action continues to justify two forms of support—legal guardianship and supervised living arrangements—commonly given to many adults with ID but not to people who are considered nondisabled, except, of course, to juveniles (for the same vulnerability-based reasons). In the balance of this chapter, I shall explore implications of the construct of foolish action for understanding and defining ID. The scholarly literature on foolishness will be reviewed and a multidimensional linear model of foolish action will be presented. This model helps to explain why all human beings, including most readers of this chapter, behave foolishly on occasion. One might ask, then, ‘‘what is so unique about ID if any human being can behave foolishly for the same reasons?’’ The answer, which is similar to that given by Zigler and colleagues (Zigler & Balla, 1982) in describing his ‘‘Developmental’’ (vs. ‘‘Difference’’) theory, is that people with ID are similar in their susceptibility to being influenced by the same motivational, cognitive, and situational factors that influence all people, but differ in terms of outcomes (in this case, potentially dangerous ones) because

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of where they fall on those factors. Hopefully, this explanation will become more understandable as the reader works his or her way through this chapter.

2. A Four-Factor Model of Foolish Action Although the synonymous words ‘‘foolishness,’’ ‘‘stupid,’’ and ‘‘dumb’’ are very common folk terms, used derisively even by young children, there has been remarkably little scholarly work on the constructs. Reflecting the hold that IQ has on the general imagination, and also reflecting the lack of interest that most psychologists have in social or other nonacademic aspects of intelligence, many assume that foolishness equals low IQ and let it go at that. This is seen in the emphasis on low IQ in the first option in most dictionary definitions of foolishness/stupidity (a second option sometimes emphasizes poor real-world judgment). It is also seen in the very meager results of a PsychInfo search using these three keywords. While the keyword ‘‘intelligence’’ turned up over 60,000 hits, a similar search using keywords ‘‘stupidity,’’ ‘‘dumbness,’’ and ‘‘foolishness’’ turned up barely over 100 (overlapping) hits each, with many of these dealing not with the study of individual differences but with literature and history (Ronell, 2002; Van Boxsel, 2003), theology (Manning, 2006), intervention fads (Kozloff, 2005), or social institutions (Welles, 1995). This is in addition to various works of fiction, such as The Idiot (Dostoevsky, 1869/1998), a novel dealing with a saintly man whose naı¨vely trusting nature, aided by a lack of real-world experience, made him too foolish to survive outside of a monastery. What little scholarly literature there is on the psychology of foolishness has focused for the most part on foolish behavior in people of average or above-average intelligence, where such behavior seems unexplainable other than as a form of psychopathology. For example, psychoanalyst Edmund Bergler (1998), in his book A Talent for Stupidity, labeled foolish patients of his with the acronym ‘‘B.I.I.’’ (‘‘the bungler, the incompetent and the ineffectual’’). He suggested that virtually all foolishness, even when rising to the level of ‘‘pseudo-mental deficiency,’’ could be attributed entirely to neurotic processes, such as repressed hostility. A less extreme treatment of the problem of foolish behavior in people of average or above-average intelligence is found in an edited book by Robert J. Sternberg (2002a), titled Why Smart People Are So Stupid. In spite of the word stupid in the title, Sternberg quickly indicated a preference for the word ‘‘foolishness’’ and used that word in his own chapter in the book and in a subsequent paper (Sternberg, 2002b, 2004). The primary construct used by Sternberg and his long-time collaborator Richard Wagner to explain foolish action is a cognitive one, which they term ‘‘tacit knowledge.’’ This construct, which forms the heart of their

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thinking about ‘‘practical intelligence,’’ can be defined as one’s level of understanding of what is likely to work or not work in solving real-world problems or attaining desired goals. When describing highly intelligent individuals who behave foolishly, however, Sternberg and Wagner understood the limitations of a tacit knowledge explanation, and adopted a second factor not dissimilar to the personality/psychopathology explanation of Bregler’s. Thus, Wagner (2002) writing about self-destructive executives (such as a college president done in by a habit of insulting his Board members) attributed their foolishness to deviant personality processes that short-circuited their otherwise adequate cognitive processes. Similarly, Sternberg (2002b), recognizing that former president Bill Clinton possessed more than adequate tacit knowledge about the legal and political prohibitions against sexual contact with an intern in the workplace, attributed his very foolish behavior in the Lewinsky matter to likely arrogance, specifically a sense of immunity and entitlement. A third explanatory factor has attracted the interest of Keith Stanovich (1999) among others, and that is the role of affect and impulsivity. Under the rubric of ‘‘irrationality’’ (i.e., nonintelligent decisions in people seemingly capable of making intelligent decisions), Stanovich (2002) has concentrated his attention on impulsivity-induced failure to use logic in addressing problems of the kind favored by economists and decision theorists such as Tversky and Shafir (1992). This research, like most of the examples in Sternberg (2002a), has avoided addressing problems that pose grave threats to an individual’s existence or well-being. A fourth factor that might contribute to explaining foolish action attracted little systematic attention by any of the contributors to Sternberg’s book, and that is the role of context or situation. Obviously, one is more likely to behave foolishly when dangers are less obvious, when there are aspects of a situation (such as an influencer using persuasion ploys) that induce fear or longing, or when there are no others in the immediate context who are able and willing to intervene on one’s behalf. These four factors—situation, cognition, affect, and personality—are depicted in Fig. 5.2, which is labeled a ‘‘Linear Explanatory Model of Foolish Action.’’ The affect box is expanded to ‘‘affect/state,’’ in order to incorporate another sub-domain virtually unmentioned in Sternberg’s book, and that is the role of ‘‘biological disequilibrium’’ factors such as inebriation, sexual drive, and exhaustion (the last two of which likely were implicated, along with context [an encouraging thong-snap], in the Clinton–Lewinsky example so much favored by Sternberg and other contributors to a book that grew out of a conference that occurred around the time of Clinton’s impeachment trial). In calling this an ‘‘action model,’’ I mean to indicate that any particular behavior can be explained after the fact as resulting from the confluence of some combination of these four factors, with the weight varying according

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=

Situation

Figure 5.2

+

Cognition

+

Affect and state

+

Personality

Explanatory model of foolish behavior.

to the situation and the person. In spite of recent efforts to devise a multidimensional systems approach to understanding human conduct (e.g., Carver & Scheier, 1998; Ford & Lerner, 1992), a dynamic action model has never really caught the attention of the psychology field. This state of affairs likely explains the continued reliance on single isolated factors, such as tacit knowledge or arrogance, to explain foolish behavior. The particular model in Fig. 5.2 was inspired by the motivational theory of Martin Ford (1992), and was proposed initially by me as a framework for explaining gullibility (Greenspan, 1998; Greenspan, Loughlin, & Black, 2001), in manipulative micro-contexts. As I have come to view gullibility as a subtype of socially foolish action, it is not much of a stretch to expand a narrow explanatory model of gullibility to a broader explanatory model of foolish action. My interest in expanding my model of gullibility to a model of foolish action grew out of concern over the absence from the Sternberg (2002a) book of any chapter that discussed all four of the major explanatory dimensions of foolish action. Specifically, I was concerned about the absence (except, to some extent, in the contribution by Perkins) of any discussion of how various situational and personological factors work in concert to influence any specific act of foolishness. Although the focus of the Sternberg book was mainly on foolishness in people with average or above-average intelligence, a comprehensive flow model of foolish action can be used to explain foolish action in all people, including adults with intelligence low enough to qualify them for a diagnosis of ID. In the remainder of this section, I shall elaborate on the four factors in the linear model and explore briefly whether they might be even more likely to pertain to adults with ID. Following this, I shall illustrate how the model can be used to analyze specific foolish acts in people with or without ID.

2.1. Situational demand as a contributing factor Every foolish act occurs as a failure to solve some situational problem. In a sense, therefore, situations always contribute to foolish behavior. However, some situations pose much bigger challenges than others, and can thus be said to be major contributors to a foolish act, while others do not. Three aspects of situations will be discussed briefly: time pressures, social pressures, and novelty/ambiguity.

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2.1.1. Time pressure Many foolish actions occur in situations where a decision must be made very quickly and almost automatically, with little time for reflection. Under such circumstances, one is much more likely to behave foolishly. An example, given by Perkins (2002), involved a truck driver who at the end of a long day came to a railroad crossing just as the gate was coming down. He made the very foolish decision to drive around the gate and across the tracks, with the result that the train (a fast passenger train, not the slow freight train he perhaps expected) plowed into the body of the truck, killing several people in the process. Perkins (2002) explained this act as a failure of what he termed ‘‘self-organizing criticality,’’ of which an important aspect is ‘‘emergent activity switching.’’ Perkins points out that when having to make a decision on the spur of the moment, foolish action sometimes emerges because of a failure to regulate an impulse which could (as in this case) have disastrous consequences. Situations requiring quick decision-making obviously place a great strain on the cognitive resources of people with ID (Merrill, 1990). There is considerable research showing that individuals with ID process information at a slower rate, and that under time pressure their accuracy diminishes at a rate higher than is true of the general population (Kail, 1992; Nettelbeck & Brewer, 1981; Nettelbeck & Wilson, 1997). The decreased cognitive efficiency of people with ID suggests, therefore, that when evaluating a behavioral choice in a situation where there is considerable time pressure, adults with ID are more likely to make an inaccurate, that is, foolish, choice. 2.1.2. Social pressure There is considerable research on ‘‘persuasion’’ by social psychologists attesting to the role of social pressure in inducing people to do things that they do not want to do or that are not in their own best interest (Cialdini, 1984). This research is focused typically on the deceptive and other tactics used by the persuader rather than on individual differences in the outcome, which can be considered foolish in that it is not typically something desired or beneficial. Social pressure can take numerous forms, ranging from sheer numbers (police interrogators, con artists, and other persuaders often work as a group), to various ploys, such as reciprocity tricks (do someone a small favor and they will be much more likely to do a big one back). Social pressure can have a more passive face, as in inhibiting autonomous behavior (often a requirement to act nonfoolishly) as in the famous conformity studies of Solomon Asch (1956). While social pressure seems most relevant to explaining socially foolish action, it undoubtedly is a big contributor to practically foolish action as well. According to developmental psychologist Lewis Lipsitt (2003) (Lewin, 2006), ‘‘more young people die of behavioral misadventure than of all

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diseases combined,’’ and many if not most of these behavioral misadventures take place with the active or passive encouragement of peers. The most prevalent of these fatal misadventures is, undoubtedly, car accidents. It is for a very good reason that many states prohibit newly licensed drivers from having other youths riding in their car, as reckless driving is much more likely to occur when a young person has an audience of peers egging him or her on to take risks. Individuals with mild ID are especially susceptible to social influence, because of their social neediness (Switzky, 1997; Zigler & Balla, 1982) and because of the tendency of low-IQ individuals to use others as models and benefactors (Edgerton, 1993). Adults with ID tend to have an ‘‘external’’ orientation, in which they look to others for clues as to how to avoid looking foolish. Although this tactic is generally functional, it can be a formula for foolish action when one is in the presence of others who have a malign agenda. 2.1.3. Novelty/Ambiguity Halpern (2002) addressed the contribution to foolish action of situations that appear on the surface to be familiar but that are changed in important ways. This causes the individual to rely automatically on a response that no longer is really suited to the subtly changed circumstances. Others who have also addressed the mindlessly foolish misapplication of formerly successful schemas are Hyman (2002), who explained why eminent scientists often fail miserably when they move outside their area of specific expertise, and Moldoveanu and Langer (2002), who discussed how learned self-defining negative ‘‘scripts’’ precipitate failure in novel situations where success is within reach. Some scholars have defined ID in terms of cognitive ‘‘rigidity,’’ that is, in a tendency to rely on learned schemas even when they no longer fit changed circumstances. Herman Spitz (1988) has argued that ID is a disorder of ‘‘thinking’’ rather than learning. By that he meant that while people with, especially mild, ID are very capable of mastering simple learned routines, they have great difficulty in adapting those routines to novel, ambiguous, or threatening circumstances. Furthermore, the cognitive limitations of people with ID make it difficult for them to recognize when some alteration of routine, or call for assistance, is needed. This suggests that situations that are complex, ambiguous, or novel are likely to pose particular challenges for people with ID.

2.2. Cognition as a contributing factor Any volitional act is affected to some extent by one’s ability to cognitively process a problem situation and evaluate the likely consequences of different courses of action. Thus, cognition enters into most practical or social

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behaviors and is implicated, to some extent (less so when the act is relatively automatic and reflexive) in most cases of foolish action. I have already discussed how one’s information processing style, as reflecting both one’s personality and the role of affect, can contribute to foolish action. Stanovich (1999) has argued that real-world problems can be approached by individuals on one or the other of two levels of cognitive analysis: the algorithmic level (what he terms computational efficiency) and the intentional level (what he terms cognitive disposition or intellectual style). An IQ score only taps thinking at the algorithmic level and fails to address intellectual dispositions, or how people actually think in the real world. Thus, the paradox of smart people behaving foolishly disappears when one realizes that IQ does not directly measure pragmatic thinking. Whereas ‘‘fluid intelligence’’ (ability to integrate and attend to various aspects of a situation) affects judgment in practical and social situations, most of the emphasis in the literature has been on ‘‘crystallized intelligence,’’ reflecting knowledge and understanding of social and practical phenomena. For example, if it were generally known that cell phones are easily traceable, including placing one at a particular spot at a particular time, then this knowledge should reduce the use of cell phones in criminal acts. Sternberg and colleagues have discussed content knowledge aspects of crystallized intelligence, with particular use of ‘‘tacit knowledge’’ (Sternberg, Wagner, & Okagaki, 1993) to describe the everyday domain of cognition most relevant to understanding foolish action. Tacit knowledge, involving understanding how to succeed at various tasks (whether cooking a meal or succeeding in a job interview), is typically acquired through experience, including failure experience, and is usually not taught explicitly. Sternberg and colleagues have argued that tacit knowledge deficit plays a big role in explaining foolishness, even in people with relatively adequate IQ. In Sternberg’s writings about practical intelligence, he uses the term to encompass all of nonacademic (i.e., non-IQ-based) intelligence, while most other intelligence scholars refer to practical intelligence more narrowly, as one half of nonacademic intelligence, with the other half being ‘‘social intelligence.’’ Most models of multiple intelligences, except for Gardner’s (1983) highly idiosyncratic model, are based on E. L. Thorndike’s (1920) tripartite model, in which the three types of intelligences are ‘‘academic’’ (or ‘‘conceptual’’ intelligence, termed ‘‘abstract’’ by Thorndike, and measured by IQ), ‘‘practical’’ intelligence (knowledge of the physical world), and ‘‘social’’ intelligence (knowledge of the interpersonal world). My preference is to keep practical and social intelligence separate, rather than lumping them together as Sternberg has done. Although significant impairment in IQ is the one universal requirement for diagnosis of ID under existing official definitions, there is considerable evidence that people with ID are also significantly impaired in social and

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practical intelligence (Borthwick-Duffy, 2007; McGrew, Bruininks, & Johnson, 1996; Thompson, McGrew, & Bruininks, 2002; Widaman & McGrew, 1996). That in fact is why I have argued over the years (Greenspan, 1981, 1999, 2006) for the use of the tripartite model of intelligence, with a relaxed IQ criterion, as the basis for a definition of ID as well as the second definitional ‘‘prong’’ of deficits in adaptive behavior. Continuing relevance of this formulation is found in the considerable attention paid recently to risk outcomes, such as sexual exploitation and financial exploitation faced by adults with ID as a result of deficits in practical and, especially, social intelligence (Hickson & Khemka, 1999; Khemka & Hickson, 2000, 2006; Suto, Clare, Holland, & Watson, 2005).

2.3. Affect and state as contributing factors Foolish behavior often occurs when a person is in a condition of emotional or state imbalance. Such dysregulation can act as a ‘‘motor’’ impelling a person to act in a manner that he or she would not when in a calmer or more rested condition. Certainly, most cases of extreme violence, even in individuals with a propensity for violence, can be characterized in this manner (Davidson, Putnam, & Larson, 2000). Affect refers to the type and degree of emotion one is experiencing, while state refers to how alert, vigilant, or energetic one feels. As a rule, affective disequilibrium pushes one to engage in a foolish act, while state disequilibrium removes inhibitions against acting foolishly. Thus, affective and state disequilibrium both increase the likelihood of acting foolishly, albeit for different reasons. Affect contributes to the kinds of inefficient information processing style mentioned earlier as a major contributor to foolish thinking and behavior. Stanovich (2002), relying on the ideas of Pollock (1991), emphasized the role of emotion in causing individuals to be stuck in the mode of system 1, or ‘‘quick and inflexible’’ (Q&I), modules rather than more rational, but slower, system 2, or ‘‘intellective’’ modules. In other words, people who think rationally are more able to set strong emotions aside. Most people, when thinking about everyday matters, are stuck in the Q&I mode, and this is especially the case when affect enters the picture. However, Stanovich also points out that there is an opposite case, where an individual is unable to become sufficiently affectively aroused as to know that a different mode of thinking is required. An example of this (www.iasa.com) involved the pilot of doomed Swissair Flight 111, who in 1998 wasted 20 valuable minutes going deliberately through a lengthy checklist to locate the source of smoke in the cabin, rather than scrambling to get the plane down on the ground immediately. As mentioned, a major omission in Sternberg’s (2002) edited book on foolishness was an almost total absence of attention to the contribution that biological state makes to foolish behavior. Among such state factors are

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sexual arousal, exhaustion, and intoxication. Roy Baumeister (2001) is the psychologist who has done the most to explore the link between tiredness and foolish action. In a number of studies, both with children and with adults, Baumeister and colleagues (Baumeister, 2001; Munraven & Baumeister, 2000; Munravaven, Tice, & Baumeister, 1998) have found a distinct lessening of perseverance and performance occurring on a variety of cognitive and behavioral tasks as one’s energy becomes depleted. Even relatively small demands can result in what Baumeister terms ‘‘selfregulatory depletion.’’ As stated by Baumeister (2001), ‘‘the exhaustion theory holds that once the self has become depleted, it lacks the resources necessary for further exertion of volition’’ (p. 310). Baumeister (2001) argues that ‘‘ . . . the self has a single resource that resembles energy or strength . . . [and it] is used for a broad variety of seemingly quite different operations, including making choices, taking responsibility, exerting selfcontrol, showing initiative, and avoiding passivity.’’ Clearly, according to this view, depleted energy, as through sleep-deprivation, can contribute to the making of a foolish choice, as in the well-documented phenomenon of sleep-deprived individuals being more likely to cave in to coercive police or military interrogations (Blagrove, 1996; Gudjonsson, 1995). A related aspect of state impairment that also likely makes a significant contribution to foolish behavior is the reduced judgment and inhibition that comes from alcohol or drug intoxication. A very large percentage of the foolish behaviors that result in arrest occur under the influence of alcohol or drugs (Newcomb, 1989). There is some evidence in the scientific literature for the connection between intoxication and judgment impairment. For example, Solowij (2002) has found that marijuana use impairs executive function, and other researchers (e.g., Johnson, Malow, Corrigan, & West, 1993; Webster & Jackson, 1997) have found a significant connection between alcohol use and highly impulsive behaviors, such as problem gambling. There is no research specifically implicating affective or state factors in the foolish behavior of adults with ID. However, there is research suggesting that adults with ID are, as a group, more emotionally reactive, a characteristic which would make them more likely to behave foolishly in situations where emotion is activated. In a review of over 200 peerreviewed papers on the prevalence of mental health disorders in people with ID, Kerker, Owens, Zigler, and Horwitz (2004), citing a study by Reiss (1990), asserted that the prevalence rate for anxiety disorders among people with mild ID is over 30%, which is three or four times that for the general population. Individuals with ID also show other evidence of much higher rates of emotional instability, as seen in a much higher rate of panic attacks (Ollendick, Oswald, & Ollendick, 1993), a higher sensitivity to anxiety-producing situations (Reiss, 1998, 2001), and also in a dramatically higher rate of psychotic disorders (Eaton & Menolascino, 1982).

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The connection between state disequilibrium and ID is less obvious, but many individuals with ID have depleted energy as a result of metabolic and other physical diseases, and such energy depletion likely contributes, along with cognitive and personality factors, to a tendency to ‘‘give up’’ in situations where nonfoolish action requires a considerable expenditure of energy.

2.4. Personality as a contributing factor The term ‘‘personality’’ refers to habitual dispositions, needs, traits, and intrapsychic tendencies that are peculiar to an individual, and that give his or her behavior a relative degree of self-definition and consistency over time. Two subsidiary constructs are ‘‘character’’ (degree of one’s moral strength) and ‘‘temperament’’ (manner of one’s reacting to stimuli). Personality can be a major contributor to foolish action and thought processes. For example, there is research indicating that people high on the trait of ‘‘openmindedness’’ are more likely to make rational decisions than are people with similar IQs who are low on that personality trait (Stanovich, 1999). The reason for this is fairly evident: closed-minded people are less able to view the world as it really is as opposed to how they would like to think that it is. The notion of ‘‘character strength,’’ that is, the extent to which one can maintain moral autonomy in the face of temptation, has obvious implications for socially foolish action, given that manipulators appeal to motives, such as greed or fear, that test moral will power. Although not much emphasized by personality theorists in recent decades (Berrios & Gili, 1995), the notion of conscious will has been making a comeback, particularly in the writings of Walter Mischel and colleagues. Ayduk and Mischel (2002) cite studies that demonstrate the importance of will power as an aspect of ‘‘emotional intelligence’’ with important implications for life success and avoidance of making foolish choices. Specifically, they argue that there are two forms of self-regulation, an emotional hot system and a cognitive cool system. People with weak willpower, in their view, are more likely to rely on the emotional hot system and, thus, are more susceptible to foolish action. Another aspect of character strength is ‘‘self-efficacy,’’ also known as ‘‘agency beliefs.’’ This term refers to the extent to which one feels confident in one’s ability to perform various tasks. As conceptualized by Alfred Bandura (1977), self-efficacy is not a general personality trait but is applied very narrowly to specific domains of competence, such as ‘‘interpersonal self-efficacy’’ (the belief that one can prevail in a stressful social interaction). This is a type of agency belief that would appear to be very predictive of foolishness, especially gullibility, as one is more likely to give in to a

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manipulator if one does not feel there is any chance of prevailing in such a contest. In fact, as described by Dweck (2002), children and adults with a history of poor academic performance tend to adopt a resigned attitude which makes them likely to be even less competent than one would predict from their IQs. Although adults with ID have a wide range of personality styles, there are biological (e.g., prenatal alcohol exposure) and experiential (e.g., lifetime of failure) aspects of having ID that increase the likelihood of having a personality style that contributes to foolish action. In a previous subsection dealing with Contextual factors, I mentioned research (Switzky, 1997; Zigler and Balla, 1982) showing that people with ID are easily influenced by social pressure, because of a highly ‘‘external’’ personality style. People with ID also tend to be more impulsive in their approach to academic and everyday problems, as reflected in a comorbid prevalence of Attention Deficit-Hyperactivity Disorder (ADHD) that is three or four times that for the general population (Handen & Feldman, 1992). Moreover, a contributor to foolish action is aboulia, or paralyzed will, and a core aspect of ID, recognized even in medieval times, is a diminished ability to assert will (Goodey & Stainton, 2001). It is for this reason that contracts, confessions, and other legal actions by adults with ID, as well as normally developing children, are typically voided, because of the established principle that their will can be ‘‘overborne’’ (Feld, 2006; Grano, 1979).

2.5. Summary In all three of the ‘‘personal’’ factors discussed above, adults with ID are more likely than the general population to be affected in a negative manner, with these limitations contributing to increased levels of foolish action, and increased levels of practical and social risk. Because of the fact that cognitive impairment is the one universal characteristic of people with ID, deficits in social and practical intelligence, tacit knowledge, and rational thought processes pose obstacles to making wise decisions. But people with ID are also more likely to have an ‘‘external’’ personality style, to be impulsive, to have anxiety disorders and to lack stamina, and all of these factors, in combination with cognitive factors, increase the likelihood of acting without adequate thought given to practical and social risks. As with any vulnerable person, context can serve a protective function, but with the move to community integration such protections are often not in place. This was termed by integration advocate Robert Perske ‘‘the dark side of community integration’’ as seen in such unfortunate outcomes as the numerous cases of false confession to murder by people with ID profiled so movingly by him and his colleagues (Keyes, Edwards, & Perske, 1997; Perske, 1991).

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3. Varieties of Foolish Acts Committed By Different Populations To move this discussion in a more concrete direction, I have collected 42 examples of real-world foolish action by adults with ID and two comparison groups: non-ID adults and non-ID teens or preteens. These stories all actually occurred as described, although minor identifying details (e.g., gender, setting) have been altered or omitted in some cases. Table 5.1 lists 14 foolish acts by adults with ID, Table 5.3 lists 14 foolish acts by normally developing young people, and Table 5.5 lists 14 foolish acts by adults with average or above-average IQ. An analysis of these acts helps to illustrate how the four-factor model depicted in Fig. 5.2 can aid in a historical attempt to explain why these people behaved foolishly. Crosstabulating the nature of the acts and of the factors that appear to contribute to them can also help to generate some hypotheses about the nature and causes of foolish action in people with ID, as compared to foolish action in other populations. These analyses are portrayed in Tables 5.2, 5.4, and 5.6, and a comparison of the frequencies portrayed in those three tables concludes this section. Two obvious limitations of this exercise are (a) the source of examples differed somewhat for the three groups and (b) this author, with his own conscious and unconscious agenda, was the arbiter of which stories made it into the tables, and there was no effort to test the reliability of the analyses, as by use of one or more other raters. The stories collected should not, therefore, be considered a representative sample of foolish actions in these groups, and the comparisons of actions among the three groups are illustrative and interesting but by no means ‘‘scientific.’’ Basically, these illustrations are intended only to aid understanding of the theoretical framework and also to generate hypotheses for future research, and are not intended to answer research questions. While two of the stories about ID adults in Table 5.1 came from the media (1D a widely reported crime, 1H a notable documentary film), most came from conversations with colleagues with experience in the field, and from my own experiences as a researcher, clinical consultant, and family member (sibling of a brother with ID) over the years. Stories were generated until I filled my quota of 14. A couple of the stories in Table 5.3 (young people) came from news articles (story 3A appeared in my local newspaper recently and 3N describes a widely reported incident of a few years ago), but most came from conversations with friends who are parents of teenagers, and from my own knowledge. As with Table 5.1, stories were assembled sequentially until the quota of 14 was reached, and no dropping of entries was necessitated.

Foolish Action in Adults with Intellectual Disabilities

Table 5.1

163

Foolish acts committed by adults with intellectual impairments

1A—A young woman asked the head of a vocational agency for help in collecting a debt. When he inquired as to the nature of the debt, the woman said of a young man on her van: ‘‘_ promised to give me ten dollars for a blow job and now he won’t pay up.’’ 1B—A man visiting his sister started to cook some fried chicken in a pan on the stove. He sat down on the couch to watch TV and forgot about the chicken. His sister came home to find that the oil in the pan had caught fire and flames were licking up the walls. The house was spared but significant damage occurred. 1C—An office worker frequently passed gas when riding alone in an elevator, not anticipating that others will get on at the next stop and immediately know that he was the offending party. 1D—A young woman was tricked into getting in a car with some young men. When she got to a house they went into the basement, where she was talked into performing sexual acts after a threat was made to tell her mother that she had gone to the house. 1E—A young father noticed that his daughter was unconscious, and had bruises around her face. He called his more competent wife at work and she told him to call 911 but to deny that she had been home when the injury happened. Instead, he was to say that the girl had fallen off the refrigerator. The police did not buy this story and he was arrested and charged with the crime actually committed by his wife. 1F—Two parents were being monitored on a regular basis by child protective workers. A mirror fell off a wall and shattered, and the parents allowed the broken glass to stay on the floor for over a week, even though it was in an area where their young child often crawled. 1G—A young woman opened her door at night and allowed in a strange man who said he was selling magazine subscriptions. He terrorized her and stole her belongings. 1H—A man was living in his own apartment. Friendly to all, he agreed to lend his keys to homeless people, in order that they could use his bathroom. He found his meager belongings ripped off, there was damage to the building from these intruders, and his neighbors became so alarmed that they tried to get him evicted. 1I—A young man was in jail in a cell adjoining that of a well-known gang leader. He insulted the leader with ethnic slurs and kept him up at night with loud singing. The gang leader asked the man to come close to the bars as he wanted to show him something. The young man complied and the gang leader slit his throat. 1J—A man was fired from his job after he was discovered masturbating in a men’s room stall. 1K—A man innocent of any crime was persuaded to waive his Miranda rights, and began to sign incriminating statements late at night, after 10 h of an interrogation that included various false threats and promises. (continued)

164 Table 5.1

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(continued)

1L—A man worried about money walks around with all of his cash wadded up in his socks or holding it in his hand. Often, he would lose a lot of money this way, but he could not be talked into depositing anything in his account. 1M—An elderly woman in the early stages of dementia was tricked into lending her jewels to a crook who offered to get them appraised so she could receive lowered insurance costs. 1N—A young man makes some money by doing odd jobs in the neighborhood. One neighbor never pays him, or pays only a portion of what is promised. The young man continues to do jobs for this neighbor, and never thinks to ask for payment up front.

The stories in Table 5.5 (average or above-average adults) came mostly from news articles, ranging from very recent (5A and 5N) to decades old (5I), supplemented by a couple of stories from the research literature (5E) or personal knowledge (5F). Again, stories were assembled sequentially until the quota was reached. An obvious source of bias is that different methods were used to generate stories, especially in the heavy use of news sources for Table 5.5 and much lighter reliance on those sources for Tables 5.1 and 5.3. This limitation alone could explain any differences in the nature of depicted foolish acts across groups. An obvious point, which shall be repeated frequently, is that some of the foolish acts (such as caving in to a coercive police interrogation) listed in any table could be performed by members of the other groups. In spite of these limitations, it may still be possible to generate some useful insights and hypotheses from examining these true stories carefully.

3.1. Foolish acts in adults With ID The 14 foolish acts by adults with ID are described in Table 5.1 and analyzed in Table 5.2. To illustrate how the analysis was carried out, one of the stories is singled out for discussion. In story 1A (a young women who asked an agency director to help her collect money promised in exchange for a sexual act), the foolish behavior stemmed not from performing the sexual act (although that could be a separate story, marked by gullibility) as much as in thinking the agency director would respond sympathetically to this request. This behavior can be categorized as ‘‘Noninduced Socially Foolish Action’’, as the hidden risk was interpersonal (major consternation), but there was no inducement, other than a question, from the agency director. In terms of the contributing factors, a primary cause was cognition, in that the woman failed to take the perspective of the agency director and understand how he would respond. Affect/state was involved as well, in that the woman was very upset about the unpaid debt. The consequence was relatively trivial (nothing bad happend to the girl; the same couldn’t be said

Table 5.2

Analysis of foolish acts by adults with ID

Foolish action stories (from Table 5.1)

Type of foolish act Social Social Practical noninduced induced

1A—Asked staff to help collect for van sex 1B—Fire on stove 1C—Elevator gas 1D— Basement rape 1E—Father call 911 1F—Glass on floor 1G—Open door to stranger

Factors contributing to foolish act Affect Situation Cognition & state

X

X

X

X

X

Obviousness of risk

Personality Serious Trivial Obvious Hidden

X

X

X X

Consequences

X X

X

X X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X

X

X

X

X

X

X

(continued)

Table 5.2

(continued)

Foolish action stories (from Table 5.1)

Type of foolish act Social Social Practical noninduced induced

1H—Lend keys to homeless 1I—Got throat slit 1J—Wanking in men’s room 1K—False confession 1L—Money in X socks 1M—Lend jewels 1N—Stiffed by neighbor

Factors contributing to foolish act Affect Situation Cognition & state

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X X

X

X X

Obviousness of risk

Personality Serious Trivial Obvious Hidden

X

X

Consequences

X X

X

X X

X

X

Foolish Action in Adults with Intellectual Disabilities

Table 5.3

167

Foolish acts committed by normally developing youths

3A—Two teenage boys carried out a stunt where they cut the top off a junk car and ran it off a ramp into a pond. They failed to take any lifesaving precautions and one of the boys who was a poor swimmer drowned when the pond turned out to be deeper than anticipated. 3B—Three high school students got into some beer when alone in a house with no adult supervision. They decided to go to a school basketball game when they were obviously impaired. Their behavior was noticed and they were suspended from school. 3C—A young man came home from a church meeting to find his mother near death from an assault. Interrogated for many hours, he admitted he might have killed her after being falsely told that a polygraph proved he did it but had blacked out and thus had no memory of doing such a deed. 3D—A high school couple were necking and got carried away. Even though the boy had a condom on him, they had unprotected sex and the girl became pregnant. 3E—A group of teenagers played a prank by setting up a bogus web page for their high school principal, complete with picture and a statement suggesting he approved of sexually molesting children. They were suspended. 3F—A 13-year-old girl with no history of misbehavior became friendly with a 15-year-old girl with a more troubled history. The older girl convinced the younger one to sneak out late at night and take her for a joy ride in the family car, even though she lacked a license or any driving experience. 3G—An adolescent with no experience with animals decided to adopt a stray male cat. He was surprised to discover the next day that the stray cat had attacked and severely injured one of the cats already living inside. 3H—Some preteen boys set off a rocket in a park where dry conditions had made for dangerous fire conditions. A spark caused a grass fire that endangered a neighborhood and brought legal consequences. 3I—At a summer residential sports camp for lacrosse players of differing ages, the younger campers would always come home significantly poorer by being tricked by older campers into buying used lacrosse equipment at greatly inflated prices. 3J—A 14-year-old boy in a Middle Eastern country was persuaded by supposed religious leaders into making an attempt on the life of a politician they did not like. 3K—A girl wanted to surprise her dad by shoveling heavy snow off his car. She did not have a broom, so she used a metal shovel. The shovel caused significant damage to the car’s finish. 3L—A girl was taking a short-cut home from school. She was accosted by an unfamiliar man who took her by the hand and ordered her to come with him. Instead of resisting or screaming, the girl passively got into the man’s car with him. (continued)

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Stephen Greenspan

(continued)

3M—A boy who had his driver’s license for only a month was driving someplace when a text message rang on his cell phone. He glanced down to read the message, sailed through a red light and caused an accident that could have been fatal. 3N—A preteen boy with few friends was approached by a more popular peer who made a bet that he did not have the courage to shout a certain word in public. He did not know the word (an obscenity) but took the bet and there was great hilarity that he had been thus tricked.

for the young man or the bus driver). The risk was relatively obvious, in that it is difficult to imagine any average adult thinking such a request of the agency director would be appropriate. Most of the stories are placed in one ‘‘type of foolish act’’ category but one of them, story 1F, is placed in both the ‘‘Practical’’ and the ‘‘Social-Noninduced’’ categories. That is because leaving broken glass in an area where a toddler can crawl is physically dangerous, but when one’s parenting competence is being monitored on a daily basis by child protective workers looking for evidence of incompetence, that is also very socially foolish. An examination of Table 5.2 shows that the majority of the examples of foolish acts in these adults with ID involved socially foolish acts, and twothirds of those were induced (i.e., involved gullibility). While affect/state, personality, and situation were often involved as explanatory factors, cognitive factors were almost always involved. In most cases, the consequences were fairly serious, and in all but one case, the risks involved were fairly obvious.

3.2. Foolish acts in normally developing youths The 14 foolish acts by normally developing young people are described in Table 5.3 and analyzed in Table 5.4. To illustrate how the analysis was carried out, one of the stories is singled out for discussion. Story 3A, in which two boys ran a car off a ramp into a pond with one of the boys drowning, was obviously a form of practically foolish action. However, it was also classified as socially induced foolish action, because one of the boys allowed himself to get talked into it by the initiator, and there was also general encouragement from an audience of peers, most of whom had the sense to decline to participate themselves. Cases 3H (setting off a rocket in dry grass) and 3M (checking text messages while driving) are also classified as both practical and social-induced for the same reasons, although in 3M the social inducement (a peer hoping for an immediate reply) is less direct.

Table 5.4

Analysis of foolish acts by typical youths

Foolish action stories (from Table 5.3)

Type of foolish act

Factors contributing to foolish act

Social Social Affect Practical noninduced induced Situation Cognition & state

3A—Ran car off ramp 3B—Drunk at school 3C—Gave false confession 3D— Unprotected sex 3E—Prank on principal 3F—Took parents’ car for joyride 3G—Kumbaya for cats 3H—Rocket in dry grass

X

X

X

X

X

X

X

X

X X

X X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X

Personality Serious Trivial Obvious Hidden

X

X

Obviousness of risk

Consequences

X

X

X X

(continued)

Table 5.4 (continued) Foolish action stories (from Table 5.3)

Type of foolish act

Factors contributing to foolish act

Social Social Affect Practical noninduced induced Situation Cognition & state

3I—One-sided lacrosse equipment swap 3J—Young terrorist recruit 3K—Clean snow X off car with metal shovel 3L—Going with strange man 3M—Check text X messages while driving 3N—Tricked into uttering an obscenity

X

X

X

X

X

X

Personality Serious Trivial Obvious Hidden

X

X

X

X

X

X

X

X X

X X

X

X

X

X

X

Obviousness of risk

Consequences

X

X

X

X

X

X

X

X

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Table 5.5 Foolish acts committed by adults with average IQ

5A—A prominent judge was obsessed with a woman in whom he had a romantic interest. He started to stalk her and send harassing letters and he eventually lost his career and freedom. 5B—A university president made frequent obscene phone calls from his office. A call was traced and he was forced to resign in disgrace. 5C—A woman fell for the Nigeria internet inheritance scam, and lost a great deal of money as a result. 5D—A truck driver came to a railroad crossing just as the gates came down. Trying to beat the train, he drove around the gate and across the tracks. The train plowed into the body of the truck, injuring and killing many. 5E—A man decided to save money by trimming some overhanging tree branches with his chain saw, rather than calling a tree company. A large branch swung back at him, knocking him off his ladder and killing him. 5F—Several people entered a radio station–sponsored contest to see how much water they could drink without going to the bathroom. A woman was urged to continue drinking, and agreed to do so, even after she started to experience serious physical symptoms which led eventually to her death. 5G—A famous young man took up flying as a way to avoid being approached at airports. Although he was not yet instrument-proficient, he went on a trip late in the day under challenging visibility conditions, became disoriented and crashed. 5H—Two young women were tied up by a burglar whom they encountered when they returned to their apartment. He was about to leave with his loot when one of the young women said that she was certain she could pick him out of a photo lineup, but would not do so if he left the items. He panicked and killed them both. [note: the incompetence under consideration here is the victim’s, not the killer’s]. 5I—A high county official had an affair and exchanged intimate e-mails at work with a female employee who received large pay raises from him. Another employee, incensed over the pay raises, blew the whistle. 5J—The CEO of a biotech firm got advance notice that a promising new drug was not going to be approved for use. He sold his company stock and later went to jail for insider trading. 5K—The superintendent of a school district felt the need to be funny whenever he gave a speech. During an orientation at the start of a school year, he used a doctored video that depicted teachers seeming to sponsor terrorism. This was leaked to the news media and as a result of the ensuing uproar he was fired. 5L—A political leader entered into a disastrous sexual relationship with a college student intern. This began one evening when he was very tired and she snapped her thong flirtatiously at him. 5M—Although on notice that any future episode of illegal behavior would result in disciplinary action, a professional athlete was arrested for domestic (continued)

172

Table 5.5

Stephen Greenspan

(continued)

abuse one night when he had been drinking. As a result, he was suspended and lost significant income. 5N—The female assistant to an administrator has a strong dislike for a poorly performing male employee in their unit. Her boss does not feel the time is ripe to discipline this man, so his assistant decides to go over his head to try to get the man fired.

In case 3A, the causative factors were cognitive (a lack of basic understanding of how fast a car sinks and a disinclination to find out) and situational (the role of so many peers encouraging the two boys to perform the stunt). The consequences were obviously very serious, but I would consider the risk to be relatively nonobvious (as compared, say, to driving a car into a wall, driving into water could seem rather benign). An examination of Table 5.4 shows that 12 of the 14 stories involved a social cause, with all of those being induced by one of more other persons. Ten of the stories could be explained causally at least in part by cognitive factors, 11 of the stories could be explained at least partially by situational factors, and 8 of the stories involved both cognitive and situational factors acting in concert. The outcomes were evenly divided between serious and trivial, and 10 of the 14 stories involved risks that could be considered somewhat hidden.

3.3. Foolish acts in adults of average or above-average IQ The 14 foolish acts by mature adults with average or above-average IQ are described in Table 5.5 and analyzed in Table 5.6. To illustrate how the analysis was carried out, one of the stories is singled out for discussion. Example 5G involved a famous young man who took up flying a small plane in part to avoid being approached by autograph-seekers at airports. Like a lot of busy professionals who take up flying, he was not able to put in enough time to become proficient in any and all conditions, but he possessed sufficient intelligence and self-confidence to perhaps think he could handle whatever challenge came up. In this sense, personality (self-confidence and a reluctance to give up) was one of the contributing factors to the foolish decision to fly under difficult conditions and to the tragic outcome. Situation also entered into the equation, in that his departure was delayed until late in the day, but the shift in conditions (an extremely hazy evening) was ambiguous, at least at the point where he set out from. Affect/state was also part of this equation, as he and his passengers were very anxious to get to their destination (a much-anticipated

Table 5.6

Analyses of foolish acts by average adults

Foolish action stories (from Table 5.5)

Type of foolish act

Factors contributing to foolish act

Consequences

Obviousness of risk

Social Social Affect Practical noninduced induced Situation Cognition & state Personality Serious Trivial Obvious

5A—Judge stalks woman 5B—College president makes obscene calls 5C—Woman fall for inheritance scam 5D—Truck driver tries to beat train 5E—Man killed while trimming tree 5F—Woman killed in water drinking contest 5G— Unqualified Pilot exceeding his limits

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Hidden

X X

X

X

X

X

X

X

(continued)

Table 5.6

(continued)

Foolish action stories (from Table 5.5)

Type of foolish act

Factors contributing to foolish act

Consequences

Obviousness of risk

Social Social Affect Practical noninduced induced Situation Cognition & state Personality Serious Trivial Obvious

5H—Woman bargaining with a burglar 5I—Official giving raises to and e-mailing lover 5J—Exec sells stock when drug disapproved 5K—School superintendent doctors videos 5L—Politician fools around with intern at work 5M—Athlete fired for domestic abuse 5N—Assistant goes over her boss’s head

Hidden

X

X

X

X

X

X

X

X

X

X

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X

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wedding party) that evening. The consequences were, obviously, of the most serious kind. The risk was, to me, somewhat hidden, as the conditions at the onset of the flight seemed ordinary enough. An examination of Table 5.6 shows that the great majority of the stories involved socially foolish action, but three-quarters of them were noninduced. Cognition and situation played a relatively small part in these stories, while personality was a very frequent contributing factor and affect/state was involved in all but one of the stories. Another interesting finding is that 12 of the 14 stories involved risks that could be considered relatively hidden.

3.4. Comparing nature and causes of foolish acts across groups Before examining differences in foolish acts across the three groups, it is necessary to repeat the caution that this exercise was a heuristic one intended to illuminate the model and to generate research hypotheses about the forms and differences in foolish action across groups. Another obvious limitation is that even if these were representative, we have no idea of the base rate in, say a day or month, of foolish action among the three groups. We can assume (as anyone who has ever been around teenagers can attest) that the normally developing youths act foolishly far more frequently than the average-IQ adults. We can also assume that the normally developing youths act foolishly less frequently than adults with ID (who are probably operating at a much younger ‘‘foolishness-age’’). But these are assumptions for which we do not have confirming or disconfirming data at the present time. In examining Tables 5.2, 5.4, and 5.6, we note that all four of the explanatory factors can be found to be operating on all three of the groups. Thus, echoing the point made over the years by motivation researchers (Switzky, 1997; Zigler & Balla, 1982), one must see people with ID as ‘‘whole persons’’ affected by situational, affective, personality, and other forces that affect all human beings, and not just by their low score on an IQ test. For all three of the groups, socially foolish action was the most frequent type, although there seemed to be a higher frequency of practically foolish acts among the normally developing youths. This overrepresentation of social foolishness likely reflected the bias of the selector (yours truly), but it is the case that there is far more to be found in the ID literature on socially foolish actions than on practically foolish actions (one will look in vain, for example, for anything on cooking, driving, or other physical accidents in people with ID but the literature on, say, financial or sexual exploitation, is extensive). One interesting difference is that while the socially foolish acts of adults with ID and (even more so) normally developing youths are mainly of the induced variety, the socially foolish acts in adults with average IQ were

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mostly noninduced. Cognition and situation played a very small role in explaining the foolish acts of adults with average intelligence, whereas personality and (especially) affect/state played a very big role for that group. In contrast, cognition was a major explanatory factor for normally developing youths and was an almost universal factor for adults with ID. In terms of seriousness of consequences, an interesting finding is that most of the foolish acts of the normally developing youths were of the fairly trivial variety, whereas the foolish acts committed by adults with and (especially without) ID tended to have very serious consequences. An obvious explanation for this, however, is that more of these stories came from media reports, and these tend of course to focus more on tragic and serious events. In terms of obviousness of risks, the risks ignored by normally developing youths and (especially) adults of average intelligence tended to be relatively hidden, while the risks ignored by adults with ID tended to be relatively obvious. While not sources of ‘‘data,’’ these comparisons do provide some interesting hypotheses for future investigation. Among the research questions that came out of this exercise are the following: (a) Are adults with ID more likely to exhibit social than practical foolishness?; (b) Is it true that adults with ID are affected by all four explanatory factors, but their foolish action almost always reflects the influence of cognitive limitations?; (c) Are adults with ID more likely to act foolishly in situations where the risks would be relatively obvious to most people?; and (d) Is it true that the foolish acts committed by adults with ID often have very serious consequences for their well-being?

4. Brain Damage and Foolish Action: FASD as an Exemplar A number of early Renaissance artists, most notably pre-Surrealist painter Hieronymus Bosch, produced paintings or etchings depicting a form of brain surgery (Gross, 1999; image at www.Princeton.educggross/Trends Neurosci 10 429.pdf ). One of Bosch’s most famous works is titled ‘‘The Cure of Folly.’’ The inscription can be translated as ‘‘Master, dig out the stones of folly, my name is Lubbert Das’’ (which according to Stainton, 2004, can be understood to mean ‘‘stupid everyman’’). For that reason, this category of art works is known as the ‘‘Stone Operation’’ pictures. According to psychologist C. G. Gross (1999), Bosch likely depicted an actual operation, an early version of ‘‘trepanning,’’ in which a piece of skull bone is removed through a surgical incision. However, there are hints in the painting (e.g., a water tulip being pulled out by a surgeon in clerical garb who is wearing a funnel on his head), that suggest that Bosch was making

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fun of what he considered the foolishness of those who would engage or believe in such nonsense. The word ‘‘folly,’’ used by Bosch, included a broad range of behaviors, including ‘‘madness,’’ although in that period (up to less than a century ago, for that matter), a clear distinction was not always made between mental illness and ID. At any rate, this form of psychosurgery, an offshoot of which is the twentieth century practice of lobotomy, reflects a long-standing view that foolish conduct is often an external manifestation of underlying brain abnormality. A propensity for foolish action, especially in the social domain, is a commonly noted symptom of a wide variety of neurologically based syndromes, even when IQ is noted to be in the normal or low-average range. Probably the best-known example of this is the socially foolish behavior that is associated with Ventromedial Fronal Lobe lesion (also know as Phineas Gage syndrome; Damasio, 1994) and to people with damage to the prefrontal cortex in general, even when IQ remains relatively intact (Wood, 2003). But a high rate of foolish behavior is a common outcome of all sorts of neuro-behavioral syndromes associated mainly with borderline, rather than ID-qualifying, levels of intellectual functioning. As example, a survey of adults with Myotonic Muscular Dystrophy, a chromosomally transmitted neuromuscular disorder associated with learning difficulties, found a homogeneous personality profile, in which ‘‘the most frequently encountered type of behavior . . . is saying something foolish’’ (Delaporte, 1998, p. 338). Drawing on findings with induced frontal brain damage in animals (Kolb, 1995), there is a strong possibility that ‘‘species specific’’ behaviors (such as abnormal peer or sexual interaction) is a more likely consequence of certain forms of brain damage than is incompetent formal academic problem-solving (e.g., maze memorizing in rats, full-scale IQ score in humans). A strong propensity for foolish action, quite often in the absence of severe global intellectual impairment, especially in the social domain, has been noted among a number of brain-based syndromes, including other forms of Traumatic Brain Injury (McCabe & Bliss, 1996); Williams syndrome (Greer, Brown, Pai, Choudry, & Klein, 1998), Dandy–Walker syndrome, and other forms of hydrocephalus (Dennis & Barnes, 1993); Turner syndrome (McCauley, Kay, Ito, & Treder, 1987); and Attention Deficit-Hyperactivity Disorder (Wender, Wolf, & Wasserstein, 2001). Although all of the above-cited disorders are associated with much higher than average rates of foolish behavior, the likely explanatory mechanisms are different, depending on the nature of the disorder and the location and globality of the underlying lesion or other biological causes. Thus, in the case of Ventromedial Frontal Lobe lesions, individuals behave in a manner indicating an inability to anticipate social consequences, in spite of doing well on formal measures tapping understanding of consequences of portrayed acts. Writing about a formerly very competent adult subject named Elliot, Damasio (1994) wrote: ‘‘we should not attribute Elliot’s

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decision-making defect to lack of social knowledge, or to an elementary impairment of reasoning, or, even less, to an elementary defect in attention or working memory . . .. The defect appeared to set in at the late stages of reasoning, close to or at the point at which choice making or response selection must occur.’’ (p. 50). The problem is that when confronted with a choice among several paths, Elliot lost the ability to select the correct path; this was accompanied by an inability to understand and empathize with the emotional reactions of others. The likely explanation, according to Damasio (1994) is that the prefrontal cortices are very involved in categorization of situations (a prerequisite for making wise choices), and—especially when involving the ventromedial area—have particular importance in the ‘‘bioregulatory and social domain’’ (p. 183). Whereas the likely explanation for the foolish behavior of individuals with Ventromedial Frontal Lobe lesions may lie in cognitive pathways used to make choices in emotionally charged social situations, other forms of cognitive impairment—such as a basic inability to process social or communicative cues—may be the culprit in autistic-like disorders such as Dandy–Walker or Fragile X syndromes. In other cases, such as ADHD, extreme impulsivity may be the culprit, while in virtually all forms of Developmental Disability, a secondary personality adaptation of compliance and reliance on external social cues is a likely contributor. Because of space limitations, and because it is a fruitful disorder for exploring foolish action and related policy issues, the remainder of this discussion shall focus on a single disorder: Fetal Alcohol Spectrum Disorders (FASD). This is a birth defect caused by prenatal alcohol consumption that often results in ID but, even when it does not, almost always causes judgment problems that manifest in a high frequency of foolish behaviors. FASD, while not yet in use as a clinical diagnosis, is an umbrella that includes fetal alcohol syndrome (FAS, which always presents with dysmorphic facial features in combination with rather dramatic cognitive limitations), fetal alcohol effects (FAE; with less severe cognitive impairment than in FAS, and without dysmorphic facial features), alcohol-related neurodevelopmental disorder (ARND), and alcohol-related birth defects (ARBD). It is estimated that FASD affects as much as 1% of the population (Fetal Alcohol Spectrum Disorders Center for Excellence; www. fascenter. samsha.gov), although in some at-risk subgroups, such as North American aboriginal populations (Burd & Moffatt, 1994), the prevalence rate is much higher. Perhaps reflecting the general tendency of psychologists to overemphasize cognitive (i.e., academic) ability, there is very little research or even anecdotal data pertaining to social and practical limitations, particularly in adults where such limitations are especially problematic for long-term life success. In a report by a Committee of the National Research Council (Stratton, Howe, & Battaglia, 1996), it was noted that ‘‘. . . there are no systematic studies of adults with FAS. Thus, there is no information about

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longevity, sexuality, parenting, vulnerability to disease or mental illness, or other data that would be valuable in planning for these individuals’’ (p. 166). However, there is some indication that the effects of (particularly moderate doses of ) prenatal alcohol exposure may become more apparent later in an individual’s development ‘‘perhaps due to the nature of a disorder that may affect behaviors associated with more mature social functioning’’ (p. 168). Research on the attributes of individuals with FASD has indicated a number of problems that could help to explain their often-noted propensity for foolish action. Animal studies, and studies with humans using scanning and postmortem analytic methods have shown abnormalities in a number of brain regions in organisms exposed in utero to alcohol (Stratton et al., 1996, p. 169). Studies using psychological methods have shown a pattern of deficits very similar to those found in individuals with frontal lobe injury. ‘‘Specifically, those persons with FAS show impaired judgment, lability, poor impulse control, and deficits in social and adaptive functioning similar to the kinds of problems seen in patients who have frontal lobe injuries . . .’’ (Stratton et al., 1996, p. 169). All of these impairments can be linked to the three within-person theoretical constructs of cognition, personality, and affect/state and have obvious utility in explaining foolish action. As is the case with many brain damage-related conditions, the mean IQ of people with FASD fluctuates around the upper boundary of the mild ID subcategory. This means that many affected individuals are not eligible for services available to people with a diagnosis of ID, when agencies (as is, unfortunately, typically the case) rely rigidly on a 70–75 upper cutting score. It has been noted, however, that deficits in nonacademic aspects of life functioning are typically even more dramatic than one might predict from IQ, as reflected for example in low Vineland ratings, particularly on social skill areas (Streissguth et al., 2004). One is reluctant, however, to argue for a strict reliance on formal adaptive behavior ratings as a preferred method for diagnosing ID in people with FASD for two reasons: (a) studies typically use a mixed sample of individuals with FAS and FAE, meaning that the FAS subgroup is mainly responsible for the lowered adaptive behavior scores and many in the FAE group may not qualify on that basis, and especially as (b) adaptive behavior instruments have few if any foolish action items (e.g., the Vineland-2 has one gullibility item, the Adaptive Behavior Assessment System-2 none), and the concern expressed by clinicians and advocates over the incompetence of individuals with FAE is over their vulnerability stemming from a lack of risk-awareness. This is reflected in accounts such as that by the late anthropologist and novelist Michael Dorris (1989) who, in The Broken Cord, told many poignant stories about his adopted son Adam, someone with FASD whose IQ was at the upper boundary of mild ID but whose penchant for acting foolishly as a young adult made it very risky for him to live outside of the protected environment of a supervised living arrangement.

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4.1. Examples of foolish action in adults with FASD Following are some examples of foolish action, in both social and practical spheres, of young adults with FASD. These have been taken from interviews which I conducted with clinicians experienced in dealing with individuals who have FASD and borderline intelligence. The sources of the stories are not cited, and names are fictitious, in order to protect the anonymity of the subjects. The most important point of these stories is that the foolish actions depicted here as performed by people with FASD but borderline intelligence are also characteristic of people (with or without FASD) who qualify as having ID. Thus, I am using these examples not to create some contrast between people with or without ID, but rather to (a) illustrate the kinds of foolish actions that get people with ID in trouble and (b) buttress a case (made later) for expanding the ID category to include people with borderline intelligence but who make similar kinds of cognitively mediated mistakes. 4.1.1. Criminal victimization It may seem like victim-bashing to describe criminal victimization as a form of foolish action, but it is often possible to prevent being robbed or otherwise victimized by avoiding risky settings or attending to various warning signs. Nettelbeck and Wilson (2002) have found that people with ID are often at risk of being victimized criminally, for reasons having to do both with their cognitive limitations and associated personality adaptations (especially an acquiescent interpersonal style). A case of criminal victimization of a person with FASD follows. It involves ‘‘Sharon,’’ a woman in her 30s. Sharon lived alone and bemoaned the fact that she did not have a boyfriend. A van driver told her he liked her and would be her boyfriend if she gave him $1,000. Sharon emptied her bank account to give the man the money. 4.1.2. Naı¨ve criminal conduct While adults with ID are capable of committing crimes with full criminal intent, it is often the case that they lack mens reas, a legal term meaning ‘‘guilty mind.’’ Norval Morris (1982) coined the term ‘‘naı¨ve offender’’ to describe criminal behavior exhibited by people with ID, where the individual is talked or tricked into participating in a crime without fully understanding what is going on. A case of naı¨ve criminal conduct in a person with FASD follows. It involved ‘‘Tom’’ a young man of 19. Tom was asked by his uncle to come along for a ride. It turns out that the uncle planned to break into a home where a woman lived who supposedly kept money in the house. When they got there, Tom was ordered to be the lookout. The woman turned out to be home and she was killed. Tom was convicted of murder, even though he had no history of violence and most likely was duped into participating.

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4.1.3. Incompetent parenting When adults with ID become parents, they run a relatively high risk of having their children removed by a child protective agency for reasons that typically fall more in the category of neglect (i.e., that involve poor judgment) than abuse (Budd & Greenspan, 1984). While such harsh agency action sometimes reflects prejudice, combined with an absence of clear standards for evaluating childrearing adequacy, there are many cases where parents with ID foolishly endanger the welfare of their children. An example involved ‘‘Theresa,’’ a woman in her 20s with FASD who had previously had a child removed by child protective services. Theresa had recently moved into her own apartment, where she was living with her 18-month-old son ‘‘Robert.’’ Several relatives came to visit. Although sexual abuse was rampant in Theresa’s family, she allowed a female cousin to take Robert to his room unsupervised. A visiting social worker happened to come by and found signs that Robert had been molested. 4.1.4. False confession behavior Although physical coercion (i.e., torture) is now prohibited as a legitimate police interrogation technique, psychologically coercive methods (known to police agencies as the ‘‘Reid technique’’) have come to be widely used. These methods are quite effective in eliciting confessions from persons who have committed a crime. A major problem, generally not acknowledged by those who advocate for this technique, is that they sometimes elicit confessions from people who are innocent. Minors and people with ID are especially vulnerable to such techniques, and there have been several well-known cases where people with and without ID have later been exonerated of crimes to which they had earlier confessed (Drizin & Leo, 2004; Perske, 1991). A case of false confession by a person with FASD involved ‘‘Stan,’’ a man around 30. Stan was suspected of participating in a murder and he was brought in for questioning. He waived his ‘‘Miranda’’ (right to an attorney and to remain silent) rights because he was innocent and wanted to persuade the police. After being told he had flunked a lie detector test and faced a death sentence unless he confessed, Stan signed a statement that was essentially dictated to him. 4.1.5. Household accidents People with ID are at increased risk of injury from household accidents caused often by poor judgment about practical activities (Slayter et al., 2006). Here is case of such an accident in a person, named ‘‘Mary,’’ with FASD. Mary was cooking a meal, for herself and her roommate, using a cook book. Mary misunderstood the recipe and put a poisonous substance in the dish. She and her roommate both wound up in the emergency room.

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4.1.6. Health mistakes People with ID often make poor health decisions, owing to mistaken ideas about illness, lack of knowledge about healthy practices, difficulty knowing when to seek help, and lack of ability to follow through on medical regimens (McGuire, Daly, & Smyth, 2007). A health mistake of a woman, ‘‘Bridget,’’ with FASD, is illustrative. Bridget was a sexually active young woman who had contracted genital herpes. During an outbreak of the disease, she became very upset and tried to cut the herpes sores off with a scissor. 4.1.7. Poor driving decisions People with mild ID are often capable of driving a car, but obtaining a driver’s license, understanding road rules, and driving safely can be a challenge (Gottfredson, 2007). Because having a car is an almost universally desired goal in adults living in first-world countries, people with ID will often drive illegally, without a license. Here is a case involving a poor driving decision by an adult with FASD. ‘‘John,’’ a young man in his 20s with FASD made a poor driving decision. He had obtained a driver’s license after several attempts, but failed to get it reinstated after it was suspended. One evening, John was driving and noticed in his rear-view mirror a police car signaling him to pull over. John panicked and jumped out of his car while it was still moving. His rationale for this dangerous act was a belief that the police would continue to chase the car rather than him.

5. Research and Policy Implications In the space remaining, I shall address research and policy implications arising from this discussion of the problem of foolish action in adults with ID. The focus of the research subsection will be on the need to develop both descriptive and quantitative methods and measures for studying individual differences in foolish action. The focus of the policy subsection will be on ways of bringing the notion of foolish action, and the risks stemming from it, into ongoing discussions of how to define and diagnose ID.

5.1. Research implications Although I have cited a great deal of research that pertains indirectly to the problem of foolish action, very little of it specifically addresses foolish action in the general population, and virtually none of it specifically addresses foolish action in people with ID. Given that a high propensity for foolish action is one of the most salient characteristics of people with ID, talked

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about for centuries, the absence of modern research on foolish action in that population is rather striking. My main reason for writing this chapter is, in fact, to stimulate interest among researchers in this important but forgotten area of functioning. There are several reasons that might explain why social scientists have addressed so little attention to the problem of foolish action. The current zeitgeist is one in which any focus on deficits in people with ID, let alone one described by the adjective ‘‘foolish,’’ is likely to be strongly deplored. Related to that is the fact that the field of ‘‘disability studies,’’ which is conducted for the most part with scholars operating out of a labeling theory sociological tradition, have concentrated on the disabling role of social institutions and settings in creating deviance and incompetence, and has little or no place in it for any attempt to locate deviance or incompetence in the individual. Within psychology, four obstacles to studying foolish action have been (1) the continued preoccupation with IQ as the only aspect of intelligence worthy of concern, (2) the tendency to restrict conversations about the meaning of adaptive behavior (as with intelligence) to the factor structure of existing measures, (3) the absence of action models or methods sophisticated enough to explain complex volitional actions in specific contexts, and (4) the failure to generate adequate measures of foolish action. Because of the centrality of the measurement problem, I shall present some ideas below about how the development of measures pertaining to foolish action might be approached. 5.1.1. Social and practical risk ratings One very simple approach to measuring social or practical foolishness in adults with ID is in the form of a rating measure, analogous to an adaptive behavior instrument. Such measures would be completed by third-party raters (teachers, direct-care staff, counselors, family members, etc.) much as is the case with existing adaptive behavior measures such as the Vineland. An initial effort to develop such an instrument, focused on induced social foolishness (i.e., gullibility), is the ‘‘Social Vulnerability Scale’’ (SVS; Pinsker, Stone, Pachana, & Greenspan, 2006). Developed at Australia’s University of Queensland, the SVS has 22 items, 2 of which are ‘‘talked into giving up money or other objects of value to someone else’’ and ‘‘believes what another person tells him/her even when (s)he knows that person has lied in the past.’’ There is a 5-point rating instrument, ranging from ‘‘never’’ to ‘‘always.’’ The instrument thus far has been validated with older adults (a particular interest of the lead author, Donna Pinsker) and has been found to strongly discriminate between age-matched older adults with or without Alzheimer’s. However, there is no reason why this scale, or one similar to it, perhaps with practical foolishnesss content added, could not be used with much younger adults with ID and related disorders.

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A somewhat different approach is reflected in the ‘‘Adult and Adolescent Vulnerability Index’’ (AAVI; Greenspan & Stainton, in preparation), a rating instrument being developed for the adult ID service system in British Columbia. The AAVI uses somewhat more molar items, such as ‘‘Vulnerability to Appliance Use Mistakes’’ and ‘‘Vulnerability to Criminal Victimization,’’ with rating items indicting the level of vulnerability on a 4-point scale. Such molarity in items is generally avoided by instrument developers, who tend to believe that narrowly worded items make for greater inter-rater reliability. My view, however, in line with the ideas of Guilford (1956), is that some loss of reliability is occasionally necessary in order to devise valid instruments (because the way that researchers often get high reliability is by throwing out complex but interesting constructs in favor of constructs which owe their ease of measurement to the fact that they are uninteresting and overly narrow). 5.1.2. Measures of foolish behavior frequency A somewhat different approach involves collecting information about the frequency with which a subject exhibits, or is likely to exhibit, socially or practically foolish actions. Such measures do not yet exist and are not in development, but would be worthwhile. A measure of actual foolish behavior (again to be filled out by a third-party rater) would involve listing many different types of practically and socially foolish behaviors and the frequency with which a subject has performed a similar behavior in the last week, month, or year. An alternative approach would be to describe a challenging situation and then ask a rater to choose from a list of possible (relatively foolish or nonfoolish) behaviors as likely outcomes. A measure, termed the ‘‘Predicted Behavior Scale,’’ was developed and validated for children with ID some years ago (Monson, Greenspan, & Simeonsson, 1979) but could be easily adapted for use with adults, and with a focus more on risk-related behavioral outcomes. 5.1.3. Measures of risk awareness Although cognitive measures of risk awareness cannot assess foolish action directly, they can be a pretty good predictor. That is because while there are many noncognitive factors (e.g., intoxication, emotion) that contribute to foolish action in people with generally good risk-awareness, an inability to recognize obvious risk would almost certainly suggest a propensity for foolish action, even in someone in a relatively nonimpaired state. The problem is that except for a few specialized applications (e.g., recognition of driving dangers in programs aimed at reducing adolescent car accidents), one will search in vain for cognitive measures of risk-awareness. Cognitive measures, whether of intelligence, or of other (e.g., social) kinds of problem-solving, always ask a subject to generate or identify one or more good solutions. A measure of risk-awareness, on the other hand, would ask a

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subject to show that he or she recognizes a bad solution, specifically one that would put the self or others at risk. An example of such a measure, involving recognition of sexual-abuse risk, can be found in the research of Khemka and Hickson (2000). A recognition-of-risk measure is a type of intelligence test, but one that could be especially useful in predicting who would be likely to mess up in the realm of everyday functioning. The closest analogue to such a method can be found in the area of writing and grammar assessment, when a subject is asked to find and fix errors. Given the current advanced state of digital technology, the best—and probably most ecologically valid—method for devising a cognitive test of risk recognition would involve video or animated stimulus items. Such a measure does not, to my knowledge, currently exist, except for at least one preliminary effort to develop a video measure of practical wisdom. That measure, developed by an Israeli occupational therapist with my consultation (Yalon-Chamovitz & Greenspan, 2005), presented video scenarios of various everyday tasks (e.g., washing the floor, making a grilled cheese sandwich, doing the laundry). At various points in a scenario, a bell would sound and a subject would be asked to identify any mistake (e.g., omitting oil in the pan or soap in the washing machine) that had occurred just prior to the bell. This preliminary measure was predictive of community adaptation in adults with mild and moderate ID. Such a method could be adapted to make it more risk-relevant, by using items that pose some danger, for example, replacing a burnt-out fuse with a coin. Similar video-based measures could also be developed in the realm of social risk-awareness. Video technology has been used to assess socialcognitive competence in individuals with ID, most notably in research by Leffert and Siperstein (2002). Such measures have not yet, however, been converted into clinical assessment instruments, and they tend to focus on recognition of internal states rather than on recognition of risky behaviors. A recognition-of-risk measure using photos or drawings accompanied by verbally presented narratives could also prove promising in identifying individuals likely to engage in socially or practically foolish behaviors. One such measure, currently under development, is the ‘‘Test of Practical and Social Intelligence’’ (TOPSI; Greenspan & Patton, in preparation). The TOPSI consists of 100 items, half of them involving practical risks and half involving social risks. Each item involves a brief story read by the examiner, in which some problem situation (such as the heat going off) is presented. Then the examiner shows and describes three pictures to the subject, with each picture depicting a solution. Typically none of the solutions are ideal, but only one of them (as determined by a panel during the item development phase) is very bad and potentially dangerous. The subject is asked to pick the worst of the three solutions (in the example given above, lighting a charcoal brazier in a closed bedroom). Three summary scores (practical risk

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awareness, social risk awareness, overall risk awareness) are generated, based on number of correct (i.e., wrong) answers identified. Once the development of the TOPSI is complete, these raw scores will be converted to standardized scores on an IQ-like metric, indicating where an individual falls in relation to the general population in his or her ability to recognize risk.

5.2. Policy implications A heretofore unsolvable problem in defining ID, especially at its upper boundary, is identifying the category’s essential behavioral features (Greenspan, 2006).The criteria that have been developed for differentiating someone with ID from someone without ID—an IQ score approximately two standard deviations below the mean and adaptive deficits in one out of three domains—are artificial, indirect, and arbitrary. Although IQ score is an indirect predictor of behavior (especially in the academic realm), it is a mistake to consider it a direct behavior of interest. Furthermore, no justification, other than statistical elegance, has ever been provided for setting ID’s upper IQ boundary at minus two standard deviations. This problem of arbitrariness of cutting scores is equally apparent in the realm of adaptive behavior, as rating instruments measure behaviors, such as ‘‘has pleasant breath’’ (an item on the ABAS-2), that in no way are connected to the core behavioral features of ID (sometimes termed its ‘‘taxon’’). The criteria used (1 out of 3 adaptive skill domains in the tenth American Association on Mental Retardation (AAMR) diagnostic manual, 2 out of 10 or 11 adaptive skills in the ninth AAMR manual and Diagnostic and Statistical Manual, 4th edition Text Revision (DSM 4-TR), respectively) are quite arbitrary, as is the recent suggestion to extend the two standard deviation cutting score standard to adaptive behavior (Greenspan, 2006). Various recent efforts to devise a better definition of ID (see Switzky & Greenspan, 2006 for an overview) are mainly efforts to devise a better artificial formula. Such efforts are, in my opinion, doomed to failure, until they become more grounded in a quest to understand ID’s natural taxon. That natural taxon, in my opinion, is to be found in a high rate of foolish action flowing partly, but not exclusively, out of cognitive impairments which limit one’s ability to recognize practical and social risk. Decision-making research (see Hickson & Khemka, 1999) also suggests a role for ‘‘other possible sources of foolish action, including a failure to generate appropriate alternative actions, a failure to choose the most effective alternative action, or a failure to prioritize safety as a goal’’ (L. Hickson, February 15, 2008). A characteristic of most recent efforts to define ID is that there is no single quality in the realm of adaptive functioning that is a universal requirement for a diagnosis. This leaves low IQ score as the sole universal requirement. That makes sense if one assumes that low IQ is the only meaningful index of ‘‘impairments in intellectual functioning.’’ If one

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recognizes, however, that intellectual impairment manifests in foolish action and related vulnerabilities in the everyday world, then it would be possible to not only reduce the role of IQ score but also rectify the current tendency to see adaptive functioning as of secondary and peripheral importance. Although the assertion would still prevail that a person with ID can be competent (even above-average) in many areas of life functioning, it would now be recognized that a person who has a normal ability to recognize social and practical risks could not have ID, regardless of what other problems he or she might have. ID in adults would, thus, be grounded mainly in social and practical foolishness, defined behaviorally as failure to recognize and avoid risk. For children with ID, there would still be a place for emphasizing academic risks, although social risk is also a frequent problem for intellectually impaired children (Siperstein, Norins, & Mohler, 2007). In fact, the ID category is being used with decreasing frequency with children and might even be rethought of as solely an adult disability category. This is in line with suggestions (MacMillan, Siperstein, & Gresham, 1996) for a new category of General Learning Disability as a home for children with learning difficulties that straddle the 70 IQ boundary. In addition to serving borderline IQ students currently often excluded from receiving appropriate services, such a move would ‘‘protect the integrity of the [specific] LD concept [by reserving it for students with average IQ] . . .’’ (Vaughn & Fuchs (2003, p. 137) and promote the notion of ‘‘identification of students based on [academic] risk rather than deficit . . .’’ (p. 137). A more naturally grounded definition of ID in adulthood would, thus, read something like this: ‘‘the term ID refers to a disabling condition that makes one vulnerable to physical and social risk as a result mainly of inability to recognize and understand such risks. Adult services, protections, and supports of an ongoing nature are needed in order to minimize the realization and consequences of these social and physical risks.’’ One advantage of such a definition of ID is that it would force the field to develop cognitive and behavioral measures—as well as interventions— that are directly relevant to the social and physical risks that form the core of the disability. There could still be a place for IQ assessment, as part of the effort to better understand an individual and his or her cognitive abilities. But the idea that a particular IQ score could define a disability category whose essence is to be found in foolish behavior and failure to avoid social and practical risk would be seen for the absurdity that it is. Two other advantages of such a definition are that it would broaden the ID class somewhat, and it would create a more central home for gullibility, a construct which is attracting increased interest—as in mention for the first time in the AAMR diagnostic manual (Luckasson et al., 2002) and revised Vineland (Sparrow, Balla, & Cicchetti, 2006)—but whose core importance to the phenomenology of ID is not yet fully appreciated.

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6. Conclusion My purpose in writing this chapter was to stimulate interest in foolish action, a construct that seems to have many implications for the field of ID. As with any initial foray into a relatively unexplored area, there are many questions that I am not yet able to answer fully. Some of these questions cannot be answered because relevant data (e.g., about the prevalence of various forms of foolish behavior) is yet to be gathered, some because the theory is not yet fully developed, and some because the model embraces a degree of indeterminacy that may seem overly fuzzy to some. Five somewhat overlapping examples of this last set of concerns have been raised by one or more reviewers ( J. Leffert, personal communication, January 18, 2008): (a) lack of clear distinction between ‘‘obvious’’ and ‘‘nonobvious’’ risk, (b) inability to separate out the causal contributions of ‘‘cognitive’’ and ‘‘noncognitive’’ factors, (c) artificiality of the distinction between social and practical risk, (d) difficulty of trying to combine socialcognitive (e.g., Bandura) with psychodynamic (e.g., Shapiro) explanations for foolish behavior, and (e) lack of clear delineation between foolish behavior in people with ID and people with mental illness, such as schizophrenia or character disorder. In time, these questions may be answered more clearly as a result of ongoing empirical and theoretical efforts. Some of the fuzziness which is attributed to the model is intentional, however, and reflects a ‘‘historicalcontextualist’’ worldview (see Greenspan, 1998) that is very different from the mechanistic and static ‘‘boxology’’ that still characterizes much of the scholarly and clinical work in the ID field and, for that matter, in psychology generally. The combining of cognitive and personological explanations reflects my belief that neither approach, in itself, is sufficient to explain foolish behavior. The blurring of the distinction between ID, mental illness, and other categories is, furthermore, a good thing, and reflects my oft-stated preference for a more dimensional and functional approach to categorizing human beings. The construct of foolish action can contribute, I believe, not only to a clarification of the muddy construct of ID but also to the development of a more unified and comprehensive understanding of human disability. Being nondisabled, in my view, involves an ability to function in society with minimal protections and supports against those situations which pull for foolish (i.e., very likely-to-backfire) behaviors. The fact that many people without disability act foolishly is seen by some, such as L. M. Glidden (personal communication, February 25, 2008), as a problem for a proposed definition of ID grounded in foolish action. To the contrary, I see it as very much in line with a ‘‘Developmental’’ view of ID, in which the same explanations can be used to explain behavior in all people, even those

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whose vulnerabilities rise to the level where a disability label becomes attached to them. Exploring the varieties and causes of foolish behavior, thus, seems a worthwhile step towards better understanding how one becomes, and remains, ‘‘normal’’ or disabled.

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Animal Models of Self-Injurious Behavior: Induction, Prevention, and Recovery Stephen R. Schroeder,* Pippa S. Loupe,* and Richard E. Tessel*,† Contents 196 199 199 203 205 206 209 210 220 223 224

1. Introduction 2. Animal Models of Induction of SIB 2.1. Environmental restriction or deprivation and SIB 2.2. Animal lesion models of SIB 2.3. Genetic mouse models of SIB 2.4. Chemical induction of SIB in normal animals 3. Animal Models of Prevention of SIB 4. Animal Models of Recovery from SIB 5. Overall Summary and Future Directions Acknowledgments References

Abstract The purpose of this review is to organize the literature over the past 50 years on animal models for self-injurious behavior (SIB). Of the many animal models for SIB, there are four models for inducing it which have been very productive: (1) the isolate-rearing model in rhesus monkeys; (2) the neonate 6-hydroxydopamine (6-OHDA) lesion model in rats; (3) the administration of stimulants, e.g. amphetamine and pemoline to normal rats; and (4) the administration of the l-type calcium channel blocker BayK8644 to mice. A model of prevention of repetitive behavior in deer mice, some of which is self-injurious, is based upon environmental enrichment and environmental complexity. The final section of the paper reviews a 10-year research program by the authors on training-induced recovery from SIB. In general, the animal literature supports the neurobiological bases for induction, prevention, and recovery from SIB. * {

Schiefelbusch Institute for Life span studies and the Department of Pharmacology and Toxicology and the Department of Applied Behaviour Sciences, University of Kansas, Lawrence, Kansas 66045 Richard Tessel passed away in August 2004

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1. Introduction Self-injurious behavior (SIB) refers to acts directed toward one’s self that result in tissue damage (see Rojahn, Schroeder, & Hoch, 2008; Schroeder, Oster-Granite, & Thompson, 2002, for comprehensive reviews). It occurs most frequently among persons who have severe or profound intellectual developmental disabilities (IDD) and/or autism. It is a cardinal symptom of several genetically linked syndromes, e.g. Lesch–Nyhan Syndrome, which involves a disorder of purine metabolism (Lesch & Nyhan, 1964). The purpose of this review is to organize current knowledge that we know from the research on several animal models of SIB and to relate it to the variety of potential causes of SIB in humans, its possible prevention and training-induced recovery. Prevalence estimates of SIB among people with IDD range from 2% to 90%, depending upon the age, IQ, medical condition, place of residence, and a variety of other variables. Many of these studies are flawed because of the difficulties in accessing the populations under study. Cross-cultural studies in the Federal Republic of Germany agree with a figure of 13.2% (Rojahn & Esbensen, 2002), and, on average, this is the most frequently cited prevalence rate. At a prevalence estimate of c. 13% of people with severe or profound IDD who live in residential facilities and who have SIB, it is estimated that there are at least 35,000 such persons in the United States exhibiting serious SIB annually, often resulting in serious tissue damage, permanent impairments, and death. The total prevalence including milder forms of SIB among higher functioning people is unknown, but it is likely much higher (c. 600,000þ). It is a significant problem. Self-injurious behavior is a devastating chronic condition for which there is no known cure. A Consensus Development Conference by the National Institute of Child Health and Human Development (NICHD, 1991) estimated that the annual cost of services to people with IDD (formerly called mental retardation) who injure themselves or harm others or damage property in the U.S. exceeds $3.5 billion dollars per year. Thus far, few preventative efforts have been made, although there is good agreement on the risk factors related to its occurrence: lower level of retardation; several medical problems, such as otitis media, seizures, etc.; restrictive residential settings; chronological age; several psychiatric disorders; and sensory and communication deficits (Schroeder, Reese, Hellings, Loupe, & Tessel, 1999). There have been at least 10 different hypotheses as to the etiology of SIB over the past 30 years (for an extensive review, see Rojahn et al., 2008). About half of them are based upon the premise that much of SIB is learned, since behavioral intervention procedures can change it in many cases. Only

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about 10% of studies in this area, however, have experimented with generalization and maintenance of their interventions (Kahng, Iwata, & Lewin, 2002). Unfortunately, most of these behavioral changes do not generalize well and are not maintained in the long term without surveillance and continued intervention. Psychopharmacological interventions for SIB, especially those guided by research on modulators of dopamine, serotonin, and opioid peptide hormones, have shown some success in subsets of the SIB population who have disorders in these neurotransmitter systems, but there remains a large number of individuals for whom results are mixed or negative. These treatment failures have led researchers to take a closer and more experimental look at both the behavioral and biological antecedents of SIB, which affect the probability of development and occurrence of SIB in all of its forms and functions. Thompson and Caruso (2002) provided a thoughtful overview reflecting the multiple causes and effects of this likely polygenic disorder we call SIB. They offered a rational approach for investigating SIB. SIB is likely not a single disorder with one primary deficit. It is multiply caused and multiply affected. It is manifested in at least 38 different topographies (Rojahn, 1994) at selected locations on the surface of the body, although the most frequent ones are head-banging with body part, head-banging with objects, selfbiting, self-scratching, self-pinching, and hair-pulling (Rojahn et al., 2008). The functional dynamics of each of these behaviors differs and their interrelationship needs to be mapped (Newell & Bodfish, 2002). In addition, the relationship of SIB in IDD needs to be related to the psychiatric and anthropological literature on self-mutilation. The Rojahn et al. (2008) book attempts to reconcile these two literatures. The psychiatric and anthropological views are more molar, covering people with and without IDD, while the biobehavioral views are more molecular in their approach, covering mostly people with IDD. Biobehavioral etiological hypotheses for SIB in IDD are based upon a variety of behavioral and biological theories and/or genetic syndromes. The discovery of Lesch–Nyhan syndrome (Lesch & Nyhan, 1964) was a major milestone in the study of the etiology of SIB. Here was the first genetic disorder with a very high incidence of a distinctive behavioral phenotype in its population, (i.e. severe self-biting) and for years has served as a neurobiological window for studying neurotransmitter functions and pharmacotherapy for SIB. Early hypotheses related to serotonin dysfunction led to clinical trials with 5-hydroxytryptophan, but it showed only a temporary improvement (Nyhan et al., 1980). In 1981 an important postmortem study of three Lesch–Nyhan cases by Lloyd et al. (1981) revealed a 60%–90% depletion of dopamine in corpus striatum neurons in the basal ganglia and elevation of serotonin in the substantia nigra.

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Another complementary hypothesis for explaining SIB was the opioid peptide hypothesis by Sandman in 1983. It was based upon the observation that some individuals exhibiting SIB seem to be insensitive to pain. Perhaps their endorphin system was malfunctioning and could be modulated by endorphin blockers such as naloxone. The first clinical trials of naloxone by Sandman et al. presented in 1981 at the Gatlinburg Conference for Research in MRDD and published in 1983 (Sandman et al., 1983) showed a dose–response effect. Early work from animal models had supported Sandman’s hypotheses (Cronin, Wiepkema, & van Ree, 1985; Dodman et al., 1987; Redbo, 1990). The Sandman et al. (1983) results have since been replicated with the orally administered counterpart to naloxone, naltrexone, in over 50 studies (Symons, Thompson, & Rodriguez, 2004). Thus a new line of research has been initiated on drug treatment for SIB in IDD which is based on a specific neurochemical hypothesis (see Symons et al., 2004 for a review). For a comprehensive review on the role of altered pain sensitivity in SIB of humans see Symons and Thompson (1997). Since 1964 several animal models have been developed which explore the brain circuitry involved in SIB and study possible behavioral and pharmaceutical interventions to prevent SIB occurrence.

1.1. The advent of animal models of SIB The present review attempts to analyze the main animal models relevant to the experimental induction of, prevention of, and recovery from SIB. Identified are four models of induction of SIB, one of prevention of SIB and one of training-induced recovery of SIB. These genetic and neurochemical hypotheses for SIB have started a new generation of models and theories in IDD with a level of specificity far beyond what was heretofore imagined possible. Such work, which requires interdisciplinary collaboration to do well, is likely to change our view of SIB substantially in the future. What Should We Model? The use of animal models permits the investigation of many aspects of SIB which would be unethical to explore among humans, for instance, brain lesion work, the use of genetic models, the testing of experimental drugs, the use of environmentally restrictive procedures, etc. The shorter life span of certain species allows life-span developmental studies which have never been performed with humans. Animal models also have many limitations which must be considered: (1) first of all, we should model homologies that occur in various organ systems affected in SIB rather than in the disease itself. A rat’s SIB is not necessarily homologous to a human’s SIB. Similarly, there is no homologue

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of human IQ for rats’ IQ. Rather subsystems involving appropriately adapted instruments must be used to test rats’ intelligence and memory; (2) secondly, it is usually better to model the human condition in the animal model rather than vice-versa. Often animal modelers find an interesting discovery in animals and look for an analogue in humans. This practice often is putting the cart before the horse. The reverse should be done, and homologies should be validated at all levels of species possible, to gain confidence that the finding is real; (3) finally, caution in generalizing across species is always required. Even within species, the same genotype may have different behavioral phenotypes across strains. For instance, the isolaterearing effect on SIB of stub-tailed Macaque monkeys is not the same for other species of primates (Sackett, Holm, & Ruppenthal, 1976). If we observe the above cautions, we can learn much from animal models about SIB, as we will see below.

2. Animal Models of Induction of SIB Four types of animal models of induction of SIB have been studied: (1) environmental deprivation or restriction; (2) lesion models of SIB; (3) genetic models; and (4) neurochemical induction models of SIB. These models have been very instrumental in mapping the brain circuitry involved in SIB.

2.1. Environmental restriction or deprivation and SIB 2.1.1. Environmental restriction The study of stereotyped behaviors of animals kept in captivity has a large literature (see Mason, 1990 for a review). The relevance of this research to people with IDD was explored over 50 years ago (Berkson, 1967; Berkson & Mason, 1964; Davenport & Berkson, 1963). More recent summary books on stereotyped behavior are Sprague and Newell (1996) and Mason and Rushen (2007). Continuous caging and tethering of mammals has pervasive effects on the behavior and physiology of nearly every species investigated (Lewis, Tanimura, Lee, & Bodfish, 2007). Hyperactivity, aggression, and stereotyped behavior, some of which is self-injurious, are frequently observed in domesticated animals, such as pigs, horses, and cattle, and in wild animals, such as zoo animals and wild rodents, and in laboratory animals, such as rodents and primates (Cronin et al., 1985; Dodman et al., 1987; Kennes, Odberg, & Bouquet, 1988; Redbo, 1990). These behaviors are

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often accompanied by elevated blood cortisol and endogenous opioid peptide levels, and they are selectively reduced by opioid antagonists such as naloxone. For instance, Cronin et al. (1985) found that partially restrained sows often rubbed against their restraints until severe lesions developed. Intramuscular injections of naloxone reduced their self-injurious rubbing. The rationale for this treatment, based upon altered pain sensitivity, was similar to the Sandman, Barron, and Colman (1990) opioid peptide hypothesis for SIB in people with IDD. 2.1.2. Isolate rearing and SIB The isolate rearing model for SIB had its roots in the literature with a publication by Harlow (1958) entitled, ‘‘The Nature of Love.’’ In it he described the effects of separation of infant rhesus monkeys from their mothers and rearing them with various types of surrogate cloth mothers. In 1992, Kraemer wrote a summary of the isolate-rearing research in the Harlow laboratories at the Wisconsin Regional Primate Center (Kraemer, 1992). The standard experimental treatment involved removing infants from their mothers shortly after birth and placing them in standard stainless steel individual cages for the next 9 months (Sackett, 1968). They could hear and smell, but not see the other animals. Light was provided in a typical 12-hr. cycle. Limited handling was done for the first 20 days to facilitate feeding. Social control monkeys were reared with maternal and peer contact for the first 9 months of life and then transferred to standard laboratory group housing. This level of environmental deprivation led to pervasive changes in the social and central nervous system development of the isolate-reared monkeys as adults. The list includes: aberrant motor patterns, especially repetitive behaviors, low blink rate, cataleptic movements; hyperphagia; polydipsia; poorer performance on cognitive tests; lack of social control of impulses and sexual/parental behavior; disrupted habits, hyperresponsiveness to minor changes in their routines; self-directed behaviors, such as self-mouthing, digit-sucking, hand-to-mouth stereotypies, vicious selfbiting of feet, hands, or legs, head-banging, and eye-gouging; failure to avoid barriers. These same animals have also been used as animal models of psychotic depression (Kraemer, Ebert, Schmidt, & McKinney, 1989). Kraemer and colleagues found disturbances in the biogenic amine systems of isolate-reared monkeys. In normal monkeys, the levels of norepinephrine, dopamine, and serotonin metabolites in their cerebrospinal fluid are stable across time and correlated with each other, suggesting a functional relationship among these major neurotransmitter systems. Isolate rearing appears to decouple these systems in the brain impairing the ‘‘tuning’’ process effected by the norephinephrine (NE) system, of the ‘‘switching’’ processes by the dopamine (DA) system and by the ‘‘gatekeeping’’ or

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‘‘enabling’’ functions effected by the serotonin (5HT) system (Kraemer, Schmidt, & Ebert, 1997; Kraemer et al., 1989). Social isolation is thought to produce cytoarchitectural changes in these brain biogenic amine systems that result in their dysregulation, such that the animal is not prepared to respond appropriately to normal social stimuli, but performs inappropriate behaviors instead. This idea of CNS changes is supported only modestly by direct evidence. Most of it is indirect evidence inferred from assays of neurotransmitters, their precursors, and their metabolites in cerebrospinal fluid of live monkeys (Mason, 1992; Tiefenbacher, Novak, Jorgenson, & Meyer, 2000). Nevertheless, Kraemer’s approach began to reflect the complexity of the effects of environmental and biological interactions on the development of stereotypy, self-injury, and aggression, and pointed to future directions for research in terms of its neuroplasticity and the possibility of modifying it through behavioral and/or pharmacological intervention. More recently, Novak, Crockett, and Sackett (2002), Lutz, Well and Novak (2003), and Novak (2003) corroborated and extended Kraemer’s results to the primate populations at both the Northwestern (University of Washington) and the New England Regional Primate Centers (NERPC). At NERPC they also found similar results with macaque monkeys who had been reared socially, but were housed separately as adults. Therapies, such as environmental enrichment and increasing cage size, did not improve their behavior. When measuring SIB monkeys’ heart rate and blood cortisol levels in response to mild stress, i.e. placing them in a harness and sedating them, they were surprised to find a lowering of heart rate and cortisol levels instead of the expected elevated levels compared to non-SIB controls. They concluded that SIB monkeys have a disturbed hypothalamic-pituitary-adrenal axis (HPA), a result similar to Sandman and Touchette’s (2002) work on uncoupling of POMC and ACTH peptides in human SIB cases, where Sandman also invoked an uncoupling of the HPA axis. This phenomenon of uncoupling of the pituitary-adrenal hormonal system has now been used in several different models of SIB. At this point it appears to be more a description than an explanation, but it points us in a fruitful direction to look for future answers. Tiefenbacher et al. (2003) examined serum prolactin and cortisol response to D,L fenfluramine (FEN), a serotonin releasing agent, in their isolate-reared rhesus monkeys with and without SIB and aggression. They found dissociation between SIB and aggression in that there was a negative relationship between aggression and prolactin levels, but not between SIB and prolactin levels, as a result of fenfluramine challenge. No significant results were found for cortisol levels. This inverse relationship was found between serotonin levels and aggression in nonhuman and human primates in a variety of past studies. Tiefenbacher, Fahey, Rowlet, & Meyer (2005) examined the effects of diazepam, an anxiolytic drug, on self-wounding and other behaviors of their

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isolate-reared rhesus monkeys and found two distinct subsets of responders and non-responders. Responders had a documented history of self-biting. Tiefenbacher, Novak, Lutz, and Meyer (2005) have summarized a model of SIB based upon disruption of functions related to the hypothalamicpituitary-adrenal (HPA) axis. They have postulated that their SIB monkeys can be classified into two subpopulations, i.e. those who reflect lifetime stressful experiences due to isolation and stress in which SIB emerges and is responsive to anxiolytic drugs, and another subpopulation in which SIB is more strongly related to other factors, e.g. genetics, and is not responsive to anxiolytic treatment. The former group shows a number of similarities to self-mutilators found among people with borderline personality. This is a very interesting new hypothesis which may help to reconcile the disparate literatures on SIB and self-mutilation in humans (Rojahn et al., 2008) which has been an anomaly in the literature for the past 70 years. People with IDD and SIB do not respond well to anxiolytic drugs, while self-mutilators with borderline personality do. Their hypothesis is also consistent with the opioid peptide hypothesis in that anxiety may lead to self-biting and subsequent release of endogenous opioids, as occurs in SIB of persons with borderline personality and also among people with IDD. Work by Lewis, Gluck, Beauchamp, Kerestury, and Mailman (1990) and Martin, Spicer, Lewis, Gluck, and Cork (1991) at the Southwest Regional Primate Center showed that isolate-reared rhesus monkeys as older adults had abnormal anatomical brain features that were related to dopamine deficits in the striatum and striatal cortex. Using the standard isolate-rearing paradigm, they compared isolate-reared and control rhesus monkeys at 18–21 years of age before and after a pharmacological challenge with a dopamine agonist, apomorphine. There were no differences in baseline CSF metabolite levels of dopamine, serotonin, or norepinephrine, or in eye blinking, a behavioral marker for dopamine, or stereotyped behavior or SIB. There was an increase in blink rate, stereotyped behavior and SIB at the higher dose of apomorphine challenge compared to the lower doses, suggesting a long-term increase in dopamine receptor sensitivity as a result of early isolate rearing. 2.1.3. Summary These findings in studies of primate models of stereotypy and SIB from four Regional Primate Centers support the idea that there may be important abnormalities in neurochemistry and neuroanatomy of humans and primates with stereotyped behavior and SIB which are related to isolaterearing. These primates are an important population in which to study SIB because of their detailed documented behavioral, genetic, and, veterinary histories. With respect to the isolate rearing model of SIB related to stereotyped behavior, the following homologies have been found in humans and non-human primates: (1) disturbances in the hypothalamic

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pituitary axis (HPA); (2) lower blink rates; (3) lower plasma homovanillic acid (HVA) levels, the major dopamine metabolite; (4) dopamine hypersensitivity to dopamine agonists; and (5) selected responsiveness to dopamine antagonists. The isolate-rearing model is of interest because it does not rely on pharmacological and/or surgical experimental treatments to induce SIB. Rather it develops spontaneously out of a complex mixture of extrinsic (e.g. cage housing) and intrinsic (e.g. stress and anxiety) factors, thus perhaps making it more like the development of SIB in humans.

2.2. Animal lesion models of SIB 2.2.1. Destruction of the nigrostriatal pathways Breese and Traylor (1970) showed that intracisternal injections of 6-OHDA into neonate 5-day-old rat pups resulted in severe dopamine depletion and a marked increase in serotonin in the striatum as adults. Hyperactivity, aggression, and SIB (self-biting) occurred in response to challenges with dopamine agonists such as apomorphine and L-DOPA. It was not until the publication of an important post-mortem study of three cases of Lesch–Nyhan syndrome by Lloyd et al. (1981) showing a drastic reduction in brain dopamine and elevation of serotonin in the nigrostriatal pathways of the basal ganglia that age of onset was seen as a potentially important variable. Lesch–Nyhan syndrome (Lesch & Nyhan, 1964) is an early-onset cross-linked metabolic disorder of purine metabolism with a long list of biochemical, enzymatic, pathogenic, genetic, and motor symptoms (see Nyhan, 2002 for a review). Among these symptoms is a distinct behavioral phenotype of vicious selfbiting to the point of removal of digits and orofacial tissue in nearly 100% of cases with the full syndrome. Patients with a milder dose of the disease tend not to self-bite (Harris, Wong, Jinnah, Schretlin, & Parker, 2002). Fortuitously, in 1982, one of Breese’s post-doctoral fellows was Alan Baumeister, a psychologist with extensive clinical experience with human SIB cases. The connection was made that early age of onset of the 6-OHDA-lesioned rat and dopamine supersensitivity as adults may be a model for Lesch–Nyhan selfbiting. The stage was then set for the exploration of the factors that affected selfbiting in the neonatal 6-OHDA model and the drugs that would stimulate it or block it. They began the identification of the various neurotransmitter systems affecting susceptibility for SIB in the 6-OHDA model. Over the next 25 years of research with the 6-OHDA model, Breese, Knapp, Criswell, Moy, Papadeas, and Blake (2005) made several important discoveries of interest to our understanding of SIB in humans: 1. When a variety of selective agonists and antagonists are given to 6-OHDA-lesioned rats, they block SIB in a manner that is consistent with the view that dopamine is depleted and serotonin is increased in the

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striatum, while GABA receptor agonists, such as muscimol, increased sensitivity in striatal neurons. GABA agonists tend to have an inhibitory role in the circuitry related to dopaminergic and serotonergic function. The exact mechanism of action remains to be worked out, but, in humans who have deficits in GABA receptor function, e.g. Prader– Willi syndrome, GABA agonists have been effective in decreasing their self-scratching and self-gauging (Shapira, Lessig, Lewis, Goodman, & Driscoll, 2004). Atypical antipsychotics, most of which have modulatory functions on both dopamine and serotonin receptors, have been shown to be effective with over half of the cases with SIB studied (Rojahn et al., 2008). 2. The receptor subtypes of the above neurotransmitters likely increase the selectivity of their modulating effects. For instance, SIB induced by L-DOPA in 6-OHDA-neonate-lesioned rats is primarily linked to activation of D1-dopamine receptors, with the facilitation by D2-dopamine receptors. Breese et al. also reported that neonate 6-OHDA-lesioned rats exhibited increased sprouting of serotonergic neurons. These findings have not yet been replicated in humans. As yet, there is no pure D1 dopamine blocker approved for use in humans. 3. Priming (repeated administration of dopamine agonists) is an important way to sensitize a neonate-lesioned 6-OHDA rat to perform SIB. A single administration of L-DOPA, for instance, was insufficient to elicit SIB. The phenomenon of sensitization is important to the study of SIB in humans. For instance, the administration of dopamine agonists, such as dextro-amphetamine, to SIB cases with hyperactivity and aggression has sometimes made them worse (Campbell et al., 1972). The relationship between dopamine supersensitivity and behavioral sensitivity in humans has not been studied extensively in SIB cases, but it is an important area to explore, as has been shown by Stodgell, Loupe, Schroeder, and Tessel (1998) discussed below in the section on training-induced recovery from SIB. Overall, the Breese/Baumeister neonate-6-OHDA-lesioned rat has been a major animal model of SIB guiding our research into its causes and its prevention and treatment. In one of our earlier studies (Stodgell et al., 1998) we looked at whether priming with an environmental stressor such as footshock altered the responsiveness of the 6-OHDA animals to apomorphine administrations in the elicitation of SIB. Priming is an important clinical phenomenon for setting the stage for SIB. Stressful environmental events can sensitize an individual, lowering the threshold for aberrant behavior which then may interact with endogenous variables, e.g. dopamine and/or endorphin release, which provide a discriminative stimulus for further SIB. Thompson, Symons, Delaney, and England (1995) give a compelling analysis of how such interactions might occur. Since

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pharmacological priming was necessary in the Breese et al. (1984) neonate 6-OHDA lesion model for SIB, we wanted to test the interaction between behavioral priming and pharmacological priming in the neonate 6-OHDA animal model (Stodgell et al., 1998). We found that SB or SIB were manifested only during the acute apomorphine dose–effects curve by 6-OHDA-treated animals primed with either apomorphine and/or footshock-session. However, significantly more manifested SIB after acute apomorphine when the animals had been primed with both apomorphine and footshock combination. In addition, the potency and efficacy with which apomorphine injections increased locomotor activity, self-biting frequencies, and ‘‘taffy pulling’’ frequencies was greatest in the latter animals suggesting that apomorphine-induced increases in these behaviors may be related to the incidence with which this drug elicits SIB. However, footshock experience alone did not elicit SIB or SB. Neonatal 6-OHDA treatment markedly depleted norepinephrine, dopamine and metabolite levels. Nevertheless, this depletion was modestly but significantly reversed in 6-OHDA-treated rats primed with the apomorphine-foot shock combination. These results suggest that stressinduced elevations in susceptibility to acute apomorphine-induced SIB are mediated by elevations in endogenous dopamine synthesis and release which, when combined with an exogenous dopamine agonist, such as inescapable foot shock, are sufficient to induce SIB. This recognition of the impact of environmental conditions on pharmacological interventions leading to biochemical changes in lesioned animals was the basis of our own work on prevention and recovery from SIB which we will discuss in detail in a subsequent section. The early dopamine depletion model has also been shown in green monkeys with surgical unilateral lesions in the ventromedial tegmentum (Goldstein, Kuga, Kusano, Meller, Dancis, & Schwarcz, 1986). The surgery was performed at 2–3 years and animals were tested 10–14 years later. Dopamine agonists elicited self-biting similar to Lesch–Nyhan syndrome just as in the Breese rat model, so the neonatal dopamine depletion model is not just confined to rats.

2.3. Genetic mouse models of SIB Although there are several genetic mouse models of repetitive behavior (Lewis et al., 2007) there are only a few related to SIB. Genetic models for Lesch–Nyhan syndrome have been produced by inactivating the HPRT gene in different strains of mice (Hooper et al., 1987; Kasim & Jinnah, 2002; Kuehn, Bradley, Robertson, & Evans 1987; Visser et al., 2002). These mice show many of the metabolic abnormalities of Lesch– Nyhan syndrome, but not SIB.

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Metamphetamine-induced neurotoxicity in striatal dopamine neurons in BALB/c and C57BL/6 mice, an HPRT mutant model, (Halliday et al., 2003; Kita, Matsunari, Shimada, et al., 2000; Kita, Saraya, Konishi, et al., 2003; Mori, Ito, & Sawaguchi, 2004) is also of relevance. This methamphetamine model produces dose-dependent SIB, stereotyped behavior, hyperactivity, hyperthermia, and other neurotoxic effects which can be blocked by pretreatment with SCH23390, haloperidol, acetamenophen, or MPTP (1-methyl4-phenyl-1,2,3,6-tetrahydropyridine). These substances help to differentiate the effects of various dopamine antagonists and serotonin agonists on hyperactivity, stereotyped behavior and SIB in amphetamine-treated genetic mouse models. This information may be useful as we learn more about them.

2.4. Chemical induction of SIB in normal animals With lesion work, there is always the concern that other CNS sites in addition to the target site may have been modified by the invasive lesioning procedure. Replication of findings in normal animals is, therefore, important (see Kasim, Kahn & Jinnah, 2002 for a review). 2.4.1. Psychostimulants In rodents, the acute administration of 1–5 mg/kg of amphetamine or methamphetamine typically produces motor hyperactivity with stereotypical behaviors such as repetitive sniffing, grooming, licking, or gnawing. Doses of 5–50 mg/kg cause exaggerated stereotypical behavior and often SIB, typically expressed by biting of the paws or abdomen (Hohn & Lasagna, 1960; Shishido et al., 2000). Kelley, Gauthier, & Lang (1989) and Kelley, Lang, and Gauthier (1988) have shown that direct microinjection of amphetamine into discrete areas of the striatum can dissociate its effects on ingestive behavior, hyperactivity, stereotypy, and SIB. Although the expression of SIB typically requires relatively high doses of psychostimulants, it may also occur with chronic delivery of smaller doses of these drugs (King, Au, & Poland,1995; Mueller, Hollingsworth, & Petit, 1986; Mueller & Nyhan, 1983) or the dopamine presynaptic uptake inhibitor, GBR-12909 (Sivam, 1995). In susceptible children, amphetamine has also been reported to precipitate trichotillomania (hair pulling) and extreme fingernail biting with bleeding and tissue damage (Sokol, Campbell, Goldstein, & Kriechman,1991). Pemoline provokes a similar neurobehavioral syndrome, with hyperactive motor behavior at 5–20 mg/kg and intense stereotypy with SIB at 50–200 mg/kg (Cromwell, Levine, & King, 1999; Genovese, Napoli, & BolegoZonta, 1969; Kies & Devine, 2004; King et al., 1995, 1998; Mueller & Hsiao, 1980; Mueller & Nyhan, 1982). King, Au, and Poland (1993) showed that low-doses of naltrexone inhibited pemoline-induced self-biting in rats.

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Recently, Devine and colleagues have been actively pursuing the pemoline model of SIB. Kies and Devine (2004) compared caffeine and pemoline administration on the SIB of rats. Caffeine only produced mild SIB at very high toxic doses, whereas pemoline reliably produced SIB across doses with no toxicity. Speed of onset, incidence, and severity were dosedependent, suggesting that the pemoline model would be a useful analogue for exploring the neurobiological factors underpinning some forms of SIB in humans. Muehlman and Devine (in press) followed up an earlier finding by King et al. (1995) that showed that MK-801 inhibited pemoline-induced selfbiting behavior in rats while still stimulating their hyperactivity. MK801 (dizocilpine) is a non-competitive N-methyl-D-aspartate (NMDA) receptor antagonist thought to modulate the glutamate system, a cortically mediated part of the brain circuitry affecting the release of dopamine and serotonin, and GABA. Lewis et al. (2007) gave an extensive review and offered a model of this brain circuitry which may be related to performance of repetitive behaviors such as stereotyped behavior and SIB. MK801 is a high-affinity antagonist which blocks glutamate-mediated neuroplasticity and behavioral sensitization to other pschostimulants. Muehlman and Devine (in press) replicated the King et al. (1995) findings, but they also compared MK801 with a low-affinity antagonist, memantine, which does not block glutamate-mediated neuroplasticity and which had no effect on pemoline-induced SIB. The pemoline model may thus offer a method for teasing out some of these specific neurochemical factors contributing to SIB. 2.4.2. Methylxanthines Administration of the methylxanthines, caffeine, or theophylline, in doses ranging from 5–50 mg/kg produces hyperactivity, tremor, and stereotypy in rodents. Daily administration of high doses of these drugs in the range of 50–200 mg/kg also result in the emergence of SIB in a significant proportion of animals (Ferrer, Costell, & Grisolia, 1982; Lloyd & Stone, 1981; Minana & Grisolia, 1986). SIB typically manifests by biting of the paws or abdomen. Unfortunately, the regimens required to induce SIB are often lethal, and the chronic use of very high doses makes interpretations of underlying neurochemical mechanisms quite difficult. 2.4.3. Clonidine Clonidine at doses of 1–5 mg/kg provokes hyperactivity and aggressiveness in mice (Morpurgo, 1968; Nikulina & Klimek, 1993; Razzak, Fujiwara, Ueki, 1975). Much higher doses of 50–100 mg/kg produce prostration, severe tremor, and SIB (Razzak, Fujiwara, Oishi, & Ueki,1977; Razzak et al., 1975). Animals typically bite their forepaws, and mortality is significant at the higher doses. Although clonidine is often used as an adrenergic

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agonist, it also binds to adenosine and imidazoline receptors (Stone & Taylor, 1978a,b), and the high doses required to produce SIB make interpretations of the underlying mechanisms uncertain. 2.4.4. Bay K 8644 Calcium channels are expressed throughout the nervous system and in other organs, where they play an important role in stimulus response coupling. Several calcium channel subtypes are currently recognized by their different pharmacological and electrophysiological properties (Catterall, 1995). The L-type calcium channel is voltage-gated and allows a transient influx of calcium in response to cell membrane depolarization. These channels are expressed widely in the brain with particularly high levels in the striatum, cortex, and hippocampus (Hirota & Lambert, 1997). The dihydropyridine Bay K 8644 functions as an L-type calcium channel activator that increases calcium fluxes in response to depolarizing stimuli (Triggle & Janis, 1987). Bay K 8644 was recently shown to provoke SIB in normal mice ( Jinnah et al., 1999). In normal adult mice, doses in the range of 4–12 mg/kg reliably provoked self-biting that could lead to severe tissue injury in a dose-dependent manner. The behavior typically emerged 10–15 min after drug administration and lasted for 30–90 min. Biting was most commonly directed towards the forepaws, with less common targets being the rear paws, abdomen, or shoulders. Though the majority of biting was directed toward the animal’s own body, some mice occasionally bit the bedding material or cage walls during testing. Other mice engaged in vacuous chewing movements with nothing in the mouth. Of note, weanling mice were notably more susceptible to the ability of Bay K 8644 to provoke SIB than were adult mice. The animals would sometimes vocalize and dart after biting, suggesting that they felt pain. The behavior did not appear to be due to drug-induced peripheral paresthesias, since it could also be induced by direct injection of small amounts of the drug into the lateral ventricles. Kasim and Jinnah (2002, 2003) designed a test of whether drugs influencing dopamine systems affected the ability of Bay K 8644 to provoke SIB. Pretreatment by amphetamine or GBR 12909, both dopamine agonists, increased the ability of Bay K 8644 to increase SIB, while two drugs that deplete dopamine stores, reserpine, and tetrabenzine, decreased the effects of Bay K 8644. Thus, dopamine systems played a role in the ability of the calcium channel activator, Bay K 8644, to provoke SIB in this mouse model. Blake, Muehlmann, Egami, Breese, Devine, and Jinnah (2007) showed that pretreatment with nifedipine, a calcium channel blocker, suppressed SIB in four previously unrelated animal models of SIB, i.e. Bay K 8644 or methamphetamine models of SIB in mice, the 6-OHDA model of SIB in rats, and the pemoline model of SIB in rats. The effect was not due to sedation or to other nonspecific mechanisms. Nifedipine apparently

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targeted a common biological mechanism related to SIB whose sensitivity and specificity as yet remains unknown. But this is a very interesting finding that merits further exploration. Nifedipine is a commonly used clinically approved drug to treat hypertension. It, therefore, does not have the negative side effect profile that other drugs currently used for SIB have, e.g. antipsychotic drugs. It would be interesting to see if it has specific inhibitory effects on SIB in humans.

3. Animal Models of Prevention of SIB 3.1. Environmental enrichment Anatomical and biochemical changes in rodents associated with enriched environmental rearing conditions were noted over 30 years ago: greater cortical depth, increased cortical weight, more glial proliferation, more dendritic branching, increased acetylcholinesterase levels, increased complexity of the hippocampus in rats. Animals also performed better on learning tasks, had reduced cognitive rigidity, and emitted reduced abnormal repetitive behaviors, some of which are self-injurious. (See Dong & Greenough, 2004; Greenough, 1976; Lewis, 2004; Lewis et al., 2007; Rosenzweig & Bennett, 1976 for reviews.) This enrichment did not require long periods of exposure or extreme conditions in order to produce these anatomical, biochemical, and behavioral effects. Lewis et al. (2007) recently summarized work an environmental enrichment model in deer mice, showing that early enriched rearing can prevent or attenuate later repetitive, stereotyped behaviors. They have suggested that environmental enrichment and complexity may help to prevent the restrictive repetitive behaviors observed in people with autism. They proposed a model of the cortical-basal ganglia circuitry involved in the development of repetitive behavior. They postulated that stereotyped behavior is expressed as a consequence of abnormal facilitation of selected motor programs due to imbalanced activity between the direct (or nigrostriatal) pathway and the indirect (or striatonigral) pathway and the indirect (or striatopallidal) basal ganglia pathway. This is the first testable heuristic neural model for stereotyped behavior of which we are aware. How much of it can be generalized to SIB in humans in its many forms and functions remains to be seen, but it is a starting point. Recent studies have shown relatively specific dose effects of operant training on local recovery of brain tissue and neurotransmitters after localized brain lesions. For instance, Nudo, Wise, SiFeuentes, and Milliken (1996) showed that, by mapping the motor cortex of the squirrel monkey before and after small ischemic lesions in the hand territory, the subsequent loss of hand representation around the lesion can be prevented by intensive

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operant retraining of hand skills if started 5 days after injury. Starting too soon or too late does not work and may worsen the damage. Highly stereotyped, repetitive training of the same movement is superior to conventional physiotherapy. The rhythmic proprioceptive and cutaneous input of repetitive training induces long-term potentiation in the sensorimotor cortex, a possible mechanism for motor learning.

4. Animal Models of Recovery from SIB 4.1. Training-induced recovery from SIB The remaining sections of this review summarize a 10-year program of research on training-induced recovery from SIB conducted by the authors at the University of Kansas. Our program began in 1990 as part of a program project to study severe chronic aberrant behavior (CAB) in IDD from the standpoint of its antecedents and the specificity of psychopharmacological interventions for CAB. After many years of research on this topic, we found that three classes of aberrant behaviors, i.e. SIB, stereotyped behavior, and aggression, overlap in the DD population, but not completely. In an effort to tease out the sources of this overlap, we compared three separate animal models: (1) an animal model for SIB, accompanied by aggression and stereotyped behavior, i.e. the Breese et al. (1984) 6-OHDA model; (2) a model for stereotypy, with no SIB or aggression, i.e., a model for microencephaly based on prenatal injection of the antimitotic agent, methylazoxymethanol (MAM), Loupe, Schroeder, & Tessel (1995); (3) and a model for aggression, with no SIB or stereotyped behavior, i.e. the spontaneously hypertensive rat (SHR, Stodgell, Loupe, Tessel,1992). For each of these models, we also had an enriched vs. an impoverished group. Our first studies attempted to induce sensitization in the three different models using behavioral interventions alone and in combination with pharmacological dopamine challenges, to see whether we could produce SIB, stereotyped behavior, and/or aggression. We found that after periodic sessions of inescapable footshock and amphetamine injections, the 6-OHDA model exhibited self-injurious behavior, SHR model displayed aggressive and freezing behaviors and the MAM model displayed stereotyped behaviors. Neither the SHR nor the MAM model exhibited SIB. Together these data suggest that there were specific aberrant behavioral sensitization patterns associated with these different animal models. Now the question occurred, would drug or other treatments serve to reduce the aberrant behavior associated with these various models? A serendipitous set of findings emerged at this point from our observations related to fixed ratio discrimination training (FRDT). This task was used as a control, to also assess the effects of various treatments on the

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cognitive performance of animals in addition to their aberrant behaviors in the different animal models. Analysis of brain structures and chemicals, however, yielded the most exciting findings. The neonate-lesioned 6-OHDA animals that had been given FRDT showed a reversal of cerebral and striatal dopamine depletion. Similarly, MAM animals that had been given FRDT showed a partial reversal of hippocampal hypoplasia (reversal of MAM-induced hippocampal weight and protein concentration reduction). These observations suggested the possibility that susceptibility to chronic aberrant behavior and the presence of cognitive deficits may not only be amenable to prevention, they may also be amenable to reversal. While past research has shown that changes in behavior are be associated with changes in the brain, as discussed previously in the section on environmental enrichment studies, the present studies showed specific and massive changes related to standard laboratory operant training. Moreover, the fact that changes were in the direction of normality for animals with specific lesions was totally unexpected. These results raised a number of important questions. First, are these changes in brain function related to a specific kind of training involving progressive increase in task difficulty, or does simple training on a repetitive task result in these brain changes? Second, are such changes restricted to rats, or do they occur in other animals, including humans? Are these changes in brain structure and chemistry accompanied by more generalized changes in behavior? For example, do MAM animals that have been through FRDT engage in less stereotyped rearing or do 6-OHDA animals after training no longer engage in self-biting when administered challenges with apomorphine and electric shock? Is it possible that such training will have a more generalized effect? Training-induced recovery promises to be a fruitful line of research for the future. Almost all behavioral interventions in human SIB studies have been aimed at modifying specific behaviors under specific conditions using operant techniques, but the present experiments suggest that regular engagement in structured operant training that is complex and difficult, even if not specifically targeted at SIB, may help to reduce SIB.

4.2. Parametric studies of the training-induced recovery effect 4.2.1. Replication study In the first Tessel, Schroeder, Loupe, & Stodgell (1995) study, when striatal concentrations of DA and its metabolites were measured in trained 9.5 month-old 6-OHDA rats, these concentrations were not only not depleted, they were markedly greater than those in either untrained or trained controls. Similar effects were obtained in cortical concentrations as well. In trained control animals compared to untrained controls concentrations of the DA metabolites 3,4-dihydroxyphenylacetic acid (DOPAC),

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homovanillic acid (HVA) and 3-methoxytyramine (3MT) were unchanged. Since 6-OHDA-induced depletions have generally been regarded up to now as being irreversible (e.g., Oke, Keller, & Adams,1978), these findings were surprising to say the least. We, therefore, performed a replication of this study in another group of neonatal vehicle (control) and 6-OHDAtreated animals but added a group of age-matched, food-deprived but untrained neonatal 6-OHDA-treated rats as additional control groups (Stodgell, Schroeder, & Tessel, 1996). DA concentrations were over 5.5fold greater than those in the untrained 6-OHDA-treated group in this replication of the preceding study but less than those in trained controls. In addition, DA concentrations in untrained, food-deprived, age-matched 6-OHDA-treated animals were slightly greater than those in non-food deprived 3-month-old neonatal 6-OHDA-treated animals prior to the initiation of training. Qualitatively similar changes occurred in DA metabolites except that striatal 3MT concentrations in trained 6-OHDA-treated animals were equal to or greater than those in trained controls. Thus, the magnitude of effect observed in the replication was significant but smaller than that which we initially observed. The reasons for this difference are unclear, particularly since learning rates in the trained 6-OHDA-treated animals (as well as controls) were essentially identical to the first study. Nevertheless, the findings of the replication confirm that training is associated with a marked reversal of neonatal 6-OHDA-induced striatal DA depletion and that this effect is not attributable to age or food deprivation. 4.2.2. Amount of FRDT training on the duration of training-induced recovery1 In the present series of studies we evaluated whether there was a difference in the amount of dopamine recovery due to the post-training assessment time, that is, the amount of elapsed time after training when dopamine concentrations were measured (2 weeks vs. 2 months). We also determined whether there were differences in dopamine concentration recovery due to the length of the training period by comparing concentrations in animals trained for 25 sessions to animals trained for 90 sessions. In assessing the amount of time since the end of training when rats were assayed (2 weeks vs. 2 months), no difference was found in dopamine concentrations. So the training effect lasted at least 2 months. This is a significant amount of a rat’s life span. There was a slight increase in dopamine concentration due to the amount of time spent training (25 vs.90 sessions) in the 6-OHDA animals, but not in control animals. It appears that the training effect reached asymptote by 25 sessions.

1

Unpublished experiments available from the senior author.

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4.2.3. Degree of dopamine depletion on training-induced recovery1 Subsequent analyses of animals with 99% depletion of dopamine that were trained for 25 sessions showed no difference in dopamine concentration as compared to untrained littermates. In looking at the performance of the 6-OHDA treated animals, there was a significant difference in the percent error rate between animals who were depleted between 80% and 90% of dopamine and those were depleted of 99% of their dopamine neurons. It is possible that the animals that were 99% depleted of their dopamine and exhibited a poorer performance in the FRD task were unable to show a recovery of dopamine concentrations due to training. Indeed, there was a trend within the 99% depletion group indicating that the level of dopamine concentration greatly determined whether the animal would be able to perform the FRD task at all. The mean concentration of dopamine was lower in the tissue of animals that could not perform the task while the mean concentration of those that could was higher in their striatal tissue. In the 99% depleted group, 47% were unable to perform the FRD task and were excluded from analyses. Thus the degree of depletion with 6-OHDA affected the recovery of dopamine concentrations and FRD performance related to SIB in a curvilinear fashion. The latter supports the findings of Luthman, Bassen, Fredriksson, & Archer (1997), who found an effect between dose of 6-OHDA on discrimination performance on several tasks in rats. 4.2.4. Changes in density and distribution of DA receptors in neonate-lesioned 6-OHDA rat1 In addition to assessing dopamine concentrations, measures were conducted on the binding of radioactive 3H WIN 35,428 to dopamine transporters. In these analyses, we looked at differences in binding due to the use of different training schedules (incremental FRDT, FR16 or FRDT, 4v16) and different post training assessment times. There was a significant increase in binding to dopamine transporters in animals who were trained in FR16 or trained in FR4v16 as compared to Incremental FRDT when assessments were conducted two weeks after training procedures. In comparing WIN 35, 428 binding to dopamine transporters in neonatal 6-OHDA and vehicle treated animals trained in Incremental FRDT for 25 sessions to those trained for 90 sessions, there was a significant increase in binding in those trained for 25 sessions. As expected, there was a significant decrease in binding to dopamine transporters in the 6-OHDA treated compared to vehicle treated animals. Interestingly, there was a significant correlation between the dopamine striatal tissue concentrations and WIN 35,428 binding in the 6-OHDA treated animals but not in the vehicle treated animals. There were no significant differences in the binding of 3H-SCH 23390 to Dopamine D1 receptors and 125I-Iodosulpiride to Dopamine D2 receptors between the 6-OHDA treated and vehicle treated animals, or

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between animals trained in various operant schedules in varying session lengths. Thus there was a differential training effect, but it was not related selectively to D1 vs. D2 dopamine receptors in 6-OHDA neonatally depleted rats, as might be expected by the Breese et al. (1984) model. As Breese et al. (2005) noted, the underlying basis of the adaptation responsible for the persistent change in D1 vs. D2 receptors in behavioral sensitization remains to be identified. It may be modulated upstream by NMDA receptor antagonism and could be a type of ‘‘neuronal learning’’. 4.2.5. Age of lesion effects on training-induced recovery in 6-OHDA rats Another of our papers (Van Keuren et al., 1998) demonstrated that, in contrast to the effects that we found in Breese neonate-lesioned rat model of Lesch–Nyhan disease as a consequence of prolonged fixed-ratio discrimination training (FRDT; e.g., Stodgell et al., 1996), this same training failed to induce such neostriatal dopamine (and metabolite) repletions in adultlesioned rats, despite the fact that both models were generated through use of intracranial injections of the neurotoxin 6-hydroxydopamine. This finding suggests that the animal’s age at which 6-hydroxydopamine is administered is crucial in determining the capacity of FRDT to reverse the neostriatal catecholamine depletion induced by the neurotoxin. Nevertheless, in this same paper, we demonstrated for the first time that FRDT by itself did reverse the behavioral supersensitivity of Parkinson’s model rats to the dopamine agonist apomorphine. 4.2.6. Effects of unilateral 6-OHDA depletion on tongue force and rhythm during licking To quantitatively assess the subtler orolingual dysfunctions produced by striatal dopamine depletions, rats first received unilateral 6-hydroxydopamine injections into the nigrostriatal bundle and were then trained to lap water from a force-sensing disk in 2-min sessions (Skitek, Fowler, & Tessel, 1999). Compared with controls and rats with moderate (<75%) dopamine depletions, subjects with substantial (>75%) dopamine depletions showed decreases in number of licks, lick rhythm, and lick peak force, but not SIB. Rats with substantial lesions were also impaired in making initial, withinsession adjustments in lick peak force but not in lick rhythm The results confirm the presence of Parkinson-like deficits in tongue dynamics during consummatory licking behavior in rats. The methods used here should prove useful in providing quantitative measures of the efficacy of experimental therapies in this rodent model of Parkinson’s disease and the 6-OHDA neonatal dopamine depletion model. These subtler effects may appear as a result of a smaller lesion in 6-OHDA rats than the one required to produce SIB.

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4.2.7. In vivo microdialysis studies of neonate-lesioned 6-OHDA rats Because there was concern about the effect of the 6-OHDA lesion on loss of brain tissue, we were interested to see if the TIR effect could actually be demonstrated while rats were learning the FRDT. Data using continuous monitoring microdialysis measures were collected on changes in dopamine and its metabolites immediately following intense periods of operant training in 6-OHDA and vehicle-treated animals (Loupe, Xiao, Davies, Schroeder, Tessel, & Lunte, 2002). Results of this work indicate that there is an increase in dopamine in these animals as they were trained over a 3-week period. At 3 months of age, 6-OHDA and vehicle-treated rats were weight-reduced and implanted with a microdialysis guide cannula. On the third day after surgery, a microdialysis probe was inserted into a guide cannula, and pre-training or basal dialysate samples were collected on the extracellular concentrations of dopamine, DOPAC, HVA, and a metabolite of serotonin, 5-HIAA. Samples were assessed by high performance liquid chromatograph (Zhou, Zuo, Stobaugh, Lunte, & Lunte, 1995). Following collection of the pre-training concentrations, the animals were divided into training or non-training groups. Animals in the training group received three periods of massed operant training sessions, each period lasting for approximately 3 days/3 h per day for a total of 9 h of training. During training periods 1 and 2, animals were taught training steps to perform the FRDT task. During training period 3, the animals performed FRDT. Untrained animals were handled as much as the trained animals and received the food reinforcement pellets in their home cages. Microdialysis samples were collected between each period of training for the trained group and every 3 days for the non-trained group. The estimated extracellular concentrations for dopamine and its metabolites for the vehicle trained, vehicle untrained, 6-OHDA trained, and 6-OHDA untrained groups at each of the four sample times showed an increase in the 6-OHDA trained group. Statistical analyses indicated that there was a significant increase in dopamine concentration in the 6-OHDA trained animals as compared to the untrained 6-OHDA animals at sample time 3 and sample time 4. Dopamine concentration substantially increased in the trained 6-OHDA animals over and above that of the trained and untrained vehicle animals and in particular, the untrained 6-OHDA animals. One difficulty encountered in this study was that the levels of dopamine concentration in the untrained 6-OHDA animals were so low that, by the third sample, it was below our detection limit threshold. Previous studies using microdialysis techniques have shown that catecholamine samples decrease slightly in concentration over time and repeated sampling (decreased by 20% in 23 days in Martin-Fardon et al., 1997). What is interesting to us, is that, despite this normal decrease in dopamine

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concentration over time, in the trained 6-OHDA animals, the levels of dopamine concentration increased after periods of operant training. Additionally, a metabolite of dopamine, DOPAC, was elevated in the microdialysis samples of the trained 6-OHDA and in the trained vehicle animals following the third training period. The results on the concentration of another dopamine metabolite, HVA, are not as clear due to the variability within each of the groups and the relatively small differences between the groups. Results for the metabolite of serotonin, 5-HIAA, indicate that unlike the effects seen with the dopamine and its metabolites, training appears to have either a decreasing or no effect on the levels of 5-HIAA. There have been some data which suggest that there is an inverse relationship in the neonatally-6-OHDA treated animals between serotonin and dopamine concentrations, thus our results are consistent with these previous data (Stachowiak, Bruno, Snyder, Stricker, & Zigmond, 1984). During this study, we modified our training methods, using massed training, to intensify the amount of training each animal received on a daily basis and to accelerate the rate at which the animals acquired performance accuracy in a rather complex operant training task. These animals exhibited response rates similar to animals measured in our previous studies (Loupe et al., 1995; Tessel et al., 1995). During performance in the third training period, the 6-OHDA animals and the controls completed on average 174 and 148 trials, respectively, out of 180 possible trials per day successfully but their level of errors did not improve beyond chance levels (40%–50% error). It normally takes 12 daily sessions (total of 720 trials) for our vehicle animals to show a reduction in error rates below chance rates. Thus it is important to note that the increases in dopamine concentration in these animals were detected while they were in the process of learning to perform a complex operant task, and their performance levels had not yet reached asymptotic levels. These results are similar to those of Hollerman and Schultz (1998) who found that there was increased activation of dopamine neurons in the ventral tegmental area and substantia nigra of monkeys when error rates were high and rewards were unpredictable on an operant task performance. 4.2.8. Effects of GBR12909, a presynaptic dopamine uptake inhibitor, in adult 6-OHDA depleted rats According to Breese et al. (2005) the neonate lesioned 6-OHDA model produces post-synaptic dopamine supersensitivity, which leads to SIB upon dopamine challenge. What about presynaptic dopamine activity? In this study (Loupe, Bredemier, Schroeder, & Tessel, 2002), two animal models were evaluated for behavioral responsiveness to the presynaptic dopamine uptake blocker, GBR12909. GBR12909 is a highly selective presynaptic dopamine uptake blocker (Sivam 1995). By inhibiting presynaptic uptake, more dopamine is available at postsynaptic sites. One of the animal models

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was a model of dopamine hypoinnervation. Dopamine hypoinnervation was achieved by administering 6-OHDA to neonatal rat pups. The animal model of dopamine hyperinnervation was prenatal MAM treatment. MAM when given on gestation day 15, severely depletes tissue weight in the basal ganglia without reducing dopaminergic projections thereby causing a relative hyperinnervation of dopamine. These animals also have reduced cortical and hippocampal brain weights (Loupe et al., 1995). Adult female rats given neonatal treatments of 6-OHDA or vehicle or prenatal treatments of MAM were evaluated. Within each treatment group half received GBR12909 and half received the vehicle for GBR12909 for 5 days (one injection per day). The behaviors of the animals were videotaped immediately following injections and 6 h after injection. There were significant changes in the behaviors of the 6-OHDA, MAM and vehicle-treated animals when given GBR12909. There was an increase in grooming behavior in the vehicle animals as compared to the 6-OHDA and MAM treated animals. There was an increase in nose poke behavior in the MAM-treated animals and a decrease nose poke behavior in the 6-OHDA treated animals as compared to vehicle-treated animals. Immediately following a GBR12909 injection, there was a significant increase in licking behavior in all the animal groups that decreased during the measurements 6 h after the injection. However, self-biting increased in all the groups when measured 6 h after the GBR12909 injection. Following assessment of GBR12909 induced behaviors, HPLC analyses of catecholamine concentrations in the striatal tissue of these animals (6OHDA, MAM, and control) were determined. There was a significant increase in dopamine concentration in the MAM animals as compared to controls or 6-OHDA animals. There was a significant decrease in dopamine concentrations in the 6-OHDA animals as compared to either of the two groups. Thus presynaptic as well as post-synaptic increases in dopamine may induce SIB, but presynaptic dopamine acts in a less selective manner across different animal models. 4.2.9. Preventive effects of FRDT on SIB in neonate-lesioned 6-OHDA rats Does training-induced recovery actually inhibit SIB? To answer this question, we conducted a study on the effects of operant training on preventing the occurrence of self-injurious behaviors in 6-OHDA depleted animals (Schroeder, Loupe, & Tessel, 2006). In the present study, we evaluated whether or not performance in the FRDT task effectively alters dopamine levels such that injections of L-DOPA will not cause the occurrence of selfinjurious behaviors typically found in neonatally depleted 6-OHDA animals. In this study, animals were given dose-effect curves of L-DOPA prior to and following performance in the FRDT task. It was hypothesized that

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there should be a decrease in the occurrence of self-injurious behaviors after training during the second dose effect curve administration of L-DOPA. Neonate-lesioned 6-OHDA treated adult animals and vehicle adult animals were primed with up to four injections of L-DOPA (1 injection every 3– 4 days) induce self-injurious behaviors. Benserazide was given 60 min prior to L-DOPA injections to prevent the peripheral breakdown of L-DOPA. Following each injection, animals were videotaped for 4 h. Once the animals exhibited SIB, the animal was given a sedative injection of pentobarbital, treated for wounds, and placed back into the home cage. All animals then were given a dose-effect curve of L-DOPA which included giving the following doses (3.2, 10, 32, 100, and 100 mg/kg) at 30-min inter-injection intervals. The animals were continuously observed and were videotaped during the injections and for 4 h following the last injection. Tapes were coded for the occurrence of stereotypic behaviors and self-injurious behaviors including self-biting (SB; biting without skin breakage), self-injurious behavior (SIB; biting with skin breakage, bleeding) and self-mutilation behaviors (SMB; biting causing loss of digit). Thirty-eight of the 6-OHDA animals exhibited self-injurious behaviors and were divided into training and nontraining groups. None of the vehicle animals exhibited stereotypic or selfinjurious behaviors and they were excluded from the remainder of the study. During the next phase of the study, 6-OHDA animals that had exhibited SIB were trained to perform the FRDT task. Most of these animals had a difficult time performing the FRDT task. The 6-OHDA animals completed 90 sessions of FRDT performance. They and their untrained cohort group were given a second dose effect curve of L-DOPA. Tapes of these dose effect curves were coded for the occurrence of stereotypic behaviors and selfinjurious behaviors (SB, SIB, and SMB). It was found that FRDT training postponed the latency to first SIB following L-DOPA challenge in 6-OHDAlesioned animals. Training shifted the second dose effect curve down and to the right. Training also raised the dose of L-DOPA required to induce SIB. While these results are encouraging, they should be interpreted conservatively until replicated. Operant training postponed the onset of SIB and raised the dose of L-DOPA required to produce SIB, but did not inhibit it completely.

4.3. Implications of training-induced recovery in rats for humans with SIB Our research on training-induced recovery in the neonate-lesioned 6-OHDA rat suggests that stressful events, such as aversive procedures, sensitize rats in the Breese et al. (1984) neonate lesioned 6-OHDA model, priming them to be more susceptible to SIB (Stodgell et al., 1998), whereas appetitive operant training appears to desensitize them, protecting them from susceptibility to SIB. This finding is different from the large body of behavioral literature that has shown that SIB responds to specific behavioral

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intervention procedures contingent upon occurrence of SIB. In the current experiments the training is not necessarily contingent upon the substitution of appropriate alternatives to SIB. Rather FRDT is believed to stimulate the release of dopamine in the striatum of the supersensitive neonatally 6-OHDA depleted rat. Such stimulation would be more analogous to the type of general engagement in human behavioral intervention programs. Because this effect appears to be related to age of onset of susceptibility to SIB, it emphasizes the potential importance of programs for early identification and early intervention with SIB (Berkson & Tupa, 2002; Schroeder, Mulick, & Rojahn,1991). We have reviewed the literature on early intervention with SIB (Rojahn et al., 2008) which suggests that SIB indeed can be prevented by early intervention in many cases if detected early. The neural mechanism for training-induced recovery in the neonatal 6-OHDA dopamine depletion model of SIB is unknown at this time. It is believed to be related to the increase in dopamine produced by training in the nigrostriatal pathway in the basal ganglia of 6-OHDA depleted rats. The source of this unexpected dopamine production is uncertain. It may be related to an enhancement of second messenger systems or increased dopamine synthesis and release by surviving dopamine neurons, or involvement of neurotrophic-factor-induced increases in dopaminergic neuronal activity and/or reinnervation (Tessel, Schroeder, Stodgell, & Loupe,1995a). It may also be related to other neural systems that are closely involved in dopamine regulation, e.g. the glutamate receptor system. The neural mechanism for L-DOPA-induced SIB in the neonatal 6-OHDA rat model of SIB also remains to be clarified. Breese, Criswell, Duncan (1995) attribute it to post-synaptic dopamine receptor sypersensitivity. Through extensive neuropharmacological study of dopamine agonists and antagonists which block L-DOPA induced SIB, he has hypothesized that D1 dopamine receptor blockade is the critical factor in blocking self-biting. Thus, SCH 23390, a D1 antagonist, and clozapine, a multiple receptor antagonist, block SIB in the Breese model (Breese et al., 1995, Criswell, Mueller, & Breese, 1989), whereas haloperidol a D2 antagonist, does not. A similar result has been found in humans. Classical antipsychotics have been much less successful in treating SIB than the newer atypical antipsychotics (Aman & Madrid, 1999; Napolitano et al.,1999; Rojahn et al., 2008). But the generality of these findings to various dopamine and serotonin modulators remains to be explored both in the Breese model and among humans with various behavioral phenotypes of SIB. For instance, Allen, Freeman, and Davis (1998) published a study in which risperidone, a 5HT2A and D2 blocker inhibited self-biting in the neonatal 6-OHDA depleted rat nearly as well as SCH23390, a selective D1 blocker. Allen et al., (1998) point out that both clozapine and risperidone also have a very high affinity for the 5-HT2c receptor. Blockade of this receptor may have a similar effect as D1 receptor blockade in the striatum.

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There is extensive research not using the Breese model which shows differential involvement of dopamine, serotonin, and other receptors blocked by clozapine, risperidone, and olanzapine in the rat striatum, as well as prefrontal cortex, nucleus accumbens, and related structures (Grimm & See, 1998; Hertel, Nomikos, Iurlo, & Svensson,1996; Kuroki, Meltzer, & Itchikawa, 1999). The exploration of the interrelationships of these neurotransmitter systems would be a highly desirable project for the future. Naltrexone, to our knowledge, has not been tried in the L-DOPA induced 6-OHDA neonatal dopamine depleted model. The role of opioid receptor subtypes and their interaction with dopamine receptors in SIB needs to be considered (Thompson et al., 1995). Naturally occurring opioids modulate dopamine neurons with axons terminating in the nucleus accumbens. Mu and delta receptor agonists increase baseline dopamine levels in the VTA; kappa receptor agonists decrease baseline dopamine levels within the nucleus accumbens (Spanagel, Herz, & Shippenberg, 1991). Nonpharmacologic manipulations, such as training stress or self-injury that result in activation of opioid systems could increase dopamine levels in the mesolimbic and striatal dopamine systems. Another role is a possible opioid mechanism involved in clozapineinduced antinociception. Using a mouse tail-flick assay, Schreiber, Getslev, Backer (1999) showed that clozapine had a potent antinociceptive effect, while olanzapine had a much lesser effect. Both were blocked by the administration of naloxone. Atypical antipsychotics appear to interact with the opioid system as well as with dopamine, serotonin, adrenergic, muscarinic receptor systems. Studying these interactions in the Breese model would be very interesting.

5. Overall Summary and Future Directions Why are these studies important to our understanding of SIB? Is it even feasible to have a valid animal model of such a complex multifaceted disorder as SIB? The answer is that there are several models of the behaviors and neural systems related to the development of SIB which have been very informative in our conceptualization of SIB in humans. We will consider several of these contributions from different animal models below. Just as the linking of ferocious self-biting to a specific genetic etiology in Lesch–Nyhan Syndrome and the subsequent discovery of dopamine depletion in the corpus striatum led to a greater understanding of the pathogenic processes involved in a wider variety of forms of SIB, so has the Breese et al. (1984) model of neonatal dopamine supersensitivity as a model of Lesch–Nyhan Syndrome also been a generative model for studying the early development of SIB. Breese and colleagues also have shown

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how the 6-OHDA model has been useful in a variety of other areas of clinical significance, e.g. hyperactivity, schizophrenia, all of which may be linked to SIB in future studies in humans. In general, chemical induction models of SIB among intact normal animals, although different in their involvement of different cortical and subcortical pathways, still support the Breese et al. (1984) 6-OHDA neonate lesion model. The fact that, at the biochemical level, striatal dopamine receptors are coupled with L-type calcium channels, as shown in Kasim and Jinnah (2003) work on the BayK8644 mouse model for SIB, suggests that these channels might serve as a common mechanistic link for expression of SIB. The recent multi-site study with four different lab models for SIB by Blake et al. (2007) which showed that nifedipine, a calcium channel blocker, blocked SIB, attests to their concurrent validity as models for SIB. In the future, this type of collaboration among laboratories will be very important in beginning to triangulate the various neural pathways at different levels of the central nervous system which are involved in SIB. The early work of Kraemer and colleagues on an isolate-rearing primate model demonstrated how social deprivation in primates can also cause the decoupling of brain neurotransmitter functions, especially norepinephrine, dopamine, serotonin, GABA, and the hypothalamic-pituitary-adrenal (HPA) axis, which can lead to behavioral sensitization and SIB. The more recent work of Novak and colleagues has developed this model even further (Tiefenbacher, Novak, Lutz, & Meyer, 2005). They have postulated that their SIB monkeys can be classified into two subpopulations, i.e. those who reflect lifetime stressful experiences due to isolation and stress in which SIB emerges and is responsive to anxiolytic drugs, and another population in which SIB is more strongly related to other factors, e.g. genetics, and is not responsive to anxiolytic treatment. The former group shows a number of similarities to self-mutilators found among people with borderline personality that may be related to uncoupling of the HPA axis. This is a very interesting hypothesis which may help to reconcile the disparate literatures of SIB and self-mutilation in humans with and without IDD. In the future, the use of primate models in assays too invasive to use with humans may help to delineate the different neural systems underlying susceptibility to SIB, aggression, and stereotyped behavior among these different populations with differing behavior phenotypes and with clinically useful drugs for SIB modulate various receptor systems relevant to SIB. Sandman et al.’s (1983) opioid peptide model of altered pain sensitivity in some SIB cases and its related animal models initiated a different but complementary model for investigating pain sensitivity and SIB. His addiction hypothesis, expanded by the animal models of addiction elaborated by Thompson et al. (1995), provided methods to study the compulsive addictive nature of some SIB. Their research showing that some types of SIB, especially repetitive self-hitting and self-slapping, tend to be site-specific led

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Symons and colleagues to study these peripheral skin sites more carefully, as discussed previously. Their findings of altered skin temperature, Substance P, and decrease in mast cells near these SIB sites on the skin are a new area for future research on the pain hypothesis that is very promising. It could be a fertile ground for future animal modeling. In his review of environmental enrichment studies in deer mice, Lewis et al. (2007) have conceptualized and investigated the role of complex and engaging environments on the developing brain and the central nervous system circuitry critical to prevention of repetitive behavior and some forms of SIB. There is now a very extensive body or research on neuroplasticity and training-induced recovery of brain function which is too large to review here. Another research program on neuroplasticity relevant to SIB is the extensive 25-year research program on training-induced recovery in Parkinson Disease using the adult 6-OHDA rat model by Zigmond and colleagues. In a recent review of their work, Smith and Zigmond (2003) claim that the brain in Parkinson Disease can be protected by motor training and exercise. Using unilateral 6-OHDA lesions in adult rats and then immobilizing the affected side of their bodies, they showed that forced exercise brings about some motor recovery and can reduce the vulnerability of dopamine neurons to 6-OHDA. Their results appear to be due in part to the increased availability of glial cell derived neurotrophic factor (GDNF), which can stimulate the signaling of growth of neurons to protect against a variety of degenerative conditions. This is a hypothesis similar to the one suggested by Tessel and colleagues as a potential mechanism for operant training-induced recovery in the neonate 6-OHDA model of SIB. The work of Tessel, Loupe, & Schroeder (2002) on training-induced recovery from SIB in the neonate-lesioned 6-OHDA rat showed that intensive operant training interventions may also facilitate recovery of brain functions and help to desensitize the animal to future SIB challenges. Their lesson appears to be not only, ‘‘Use it or lose it,’’ but also, ‘‘Even if you lose it and then try to use it again, you may be able to get some of it back.’’ Furthermore, if you catch SIB early, you may be able to prevent it through early intervention. The accumulating findings from studies on animal models of SIB suggest that there is potential for behavioral and drug therapies to modulate the neurochemical interactions responsible for SIB and to facilitate the normal reparatory processes in the CNS. Apparently the brain continues to try to repair itself over the life span. This is a very hopeful prospect for the future of this devastating disorder.

5.1. Future directions What are the next steps in solving the Chinese puzzle that SIB represents? We have often written that SIB is a heterogeneous set of response classes multiply caused and multiply affected (Schroeder, Mulick, & Rojahn, 1980).

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The research on animal models bears out this heterogeneity, but it also shows us some of the tools we can use to tease out commonalities and differences among potential subtypes of populations with different patterns of stimuli that evoke SIB. For instance, the Tiefenbacher, Novak, Lutz, & Meyer, (2005) model previously cited posits two populations of isolate-reared rhesus monkeys with aggression and with or without SIB who respond differentially to serotonergic drugs similar to the human self-mutilation affiliated to borderline personality. Among humans with SIB, Symons and Thompson (1997) have observed that persons whose SIB is specific to acupuncture sites also tend to be repetitive self-hitters who are more likely to have abnormal pain sensitivity and are more likely to respond to naltrexone. Research on animal models of pain sensitivity and SIB may be able to help us to fine tune our treatments for different subtypes of SIB among humans. As among humans, SIB among animals appears to involve complex combinations of several aberrant behaviors. Different animal models have different patterns of stereotyped behavior, aggression, and SIB, as well as some commonalities. For instance, in the Blake et al. (2007) study previously reviewed, pretreatment with nifedipine blocked self-biting in four different rodent models of SIB, even though each had a different history, a different latency to induction, and a different combination of SIB, aggression, and stereotyped behavior. This result suggests an opportunity to study the potential brain circuitry involved in SIB subtypes at different levels of the nervous system. Such a biobehavioral approach to the study of SIB will likely increase our understanding of the causes and functions of SIB. Studying the commonalities and differences among different subsets of SIB cases among humans is also important. Some SIB is repetitive and stereotyped, but some is not. Some is accompanied by aggression and some is not, as we (Schroeder et al., 1980) and others (Rojahn, Matson, Lott, Esbensen, & Smalls, 2001; McClintock, Hall, & Oliver, 2003) have shown. Future studies of the overlap and differences among these subtypes may improve our approaches to intervention. Finally, in our recent book (Rojahn et al., 2008), we have given a genebrain-behavior model for SIB which incorporates its phylogenetic and ontogenetic history, including biological predispositions, learning, development, as well as cultural practices, traditions, and values of the social environment in which a person lives. Noteworthy research contributions have been made at all of these levels of analysis over the past 50 years. Such a multidimensional approach is required if we are ever to solve the complex puzzle we call SIB among humans.

ACKNOWLEDGMENTS We wish to acknowledge NICHD grants HD02528, HD26927, and HD33896 for support of this research.

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C H A P T E R

S E V E N

Theoretical and Methodological Issues in Sibling Research J. Carolyn Graff,* Susan Neely-Barnes,† and Heather Smith‡ Contents 234 235 235 240 240 241 241 242 243 244 245 245 260 262 264 265 266 267 268 269 271

1. Introduction 2. Themes in Sibling Research 2.1. Sibling relationship 3. Theoretical Approach 3.1. Family systems theory 3.2. Ecological systems theory 3.3. Family stress theory: Adaptation and coping 3.4. Genetics and etiology 3.5. Life-course theory 3.6. Social construction approach 3.7. Social modeling theory 4. Research Method 4.1. Sampling 4.2. Design 4.3. Measurement 5. Frontiers and Directions for Sibling Research 5.1. Theoretical perspectives 5.2. Measures and designs 5.3. Advanced statistical techniques 6. Conclusion References

Abstract Interest in the impact and influence of having a brother or sister with a disability has increased over the past 40 years as evidenced by the recent larger number of publications on siblings of persons with disabilities. However, as an area of

* { {

University of Tennessee Health Science Center, College of Nursing, Boling Center for Developmental Disabilities, Memphis, Tennessee 38105 University of Tennessee, College of Social Work, Memphis, Tennessee 38103 University of North Carolina, North Carolina 27599

International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00007-4

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2008 Elsevier Inc. All rights reserved.

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research, qualitative and quantitative inquiry into siblings and sibling relationships is in its infancy. In this chapter, we review some of the major issues that have been raised in the literature on siblings, addressing theoretical approaches, research designs, measures, and statistical methods used in sibling research. Finally, we examine the many frontiers into which sibling research can and should expand.

1. Introduction The dominant views guiding sibling research have changed in the past 40 years. They have evolved from assuming that siblings of persons with disabilities are at great risk for psychological distress to recognizing that growing up with a child with a disability can have both positive and negative effects. Siblings were thought to be at risk because (a) their parents’ attention was directed to the child with a disability, (b) their interactions with others were affected by their brother or sister with a disability, (c) they were isolated from other children, and (d) they assumed or were given additional household and caregiving responsibilities (Rossiter & Sharpe, 2001). Research studies on siblings have produced mixed results giving an ‘‘overwhelming impression . . . of contradiction and confusion’’ (Cuskelly, 1999, p. 111). Early accounts of siblings experiencing psychological distress such as those by Kaplan (1969) and Poznanski (1969) were not empirically based, yet the essence of their claims was accepted by many clinicians and researchers (Cuskelly, 1999). Subsequent efforts have been directed to determining which siblings of children with disabilities are the most vulnerable and identifying the resources and support siblings need. Just as professionals have helped identify and create appropriate resources and supports for parents of children and adults with disabilities, professionals must direct their attention and efforts to identifying and creating appropriate resources and supports for siblings of persons with disabilities. The purpose of this chapter is to address our need to know more about siblings of children with disabilities and their families and find better ways to support them. We begin with a review of what has been established in this area of sibling research and consider what remains to be established. We address sibling research from the perspectives of research themes, theoretical approaches, research designs, measures, and statistical methods and we examine the many frontiers into which sibling research can and should expand. In this chapter, sibling, not typical sibling or brother or sister, has been used consistently to describe the brother or sister of the child or adult with a disability.

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2. Themes in Sibling Research This review to establish what we know focuses on the sibling relationship, sibling outcomes, differential parenting, and supportive parenting. Most of the research themes identified by Stoneman (2005) in her reflections on the state of knowledge in sibling research are considered here. Subsequent sections of this chapter will build and expand on these reflections. We present findings established by sibling researchers knowing that recognition and acceptance of these findings by researchers does not translate into recognition and acceptance by family members, professionals, and others in the community.

2.1. Sibling relationship The sibling relationship is typically long lasting and may well outlast the parent–child relationship. The quality of the sibling relationship has been described in terms of degree of sibling warmth, positivity, time spent together, and conflict. Characteristics of the sibling relationship are influenced and determined partly by sibling roles. 2.1.1. Positive sibling relationships Although researchers have hypothesized that the relationships between siblings and the child with a disability are less warm and less positive that relationships between typical siblings, their findings support the opposite. Parent reports, sibling reports, and observations of sibling interactions have revealed positive aspects of this intimate and enduring relationship. Positive relationships have been found between siblings and their brother or sister with autism (Bagenholm & Gillberg, 1991; Hodapp & Urbano, 2007; Kaminsky & Dewey, 2002; Rivers & Stoneman, 2003; Roeyers & Mycke, 1995), Down syndrome (Abramovitch, Stanhope, Pepler, & Corter, 1987; Fisman et al., 1996; Fisman, Wolf, Ellison, & Freeman, 2000; Hodapp & Urbano, 2007), and mental retardation (Bagenholm & Gillberg, 1991; Brody, Stoneman, Davis, & Crapps, 1991; McHale & Gamble, 1989; Roeyers & Mycke, 1995; Stoneman, Brody, Davis, & Crapps, 1987; Stoneman, Brody, Davis, & Crapps, 1989). Sibling relationships have been found to vary depending on the type of disability. For example, Hodapp and Urbano (2007) found that adult siblings had a more positive relationship with their brother or sister with Down syndrome compared to adult siblings with a brother or sister with autism. 2.1.2. Sibling interactions Sibling interactions with each other develop and change over time. High levels of interaction between siblings and children with disabilities have been found (Abramovitch et al., 1987; Lobato, Miller, Barbour,

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Hall, & Pezzullo, 1991; McHale & Gamble, 1989) along with more varied interactions between siblings and children with disabilities and sibling pairs in a comparison group (McHale, Sloan, & Simeonsson, 1986). Dallas, Stevenson, and McGurk (1993) found that as the severity of the child’s disability increased the engagement between siblings and children with cerebral palsy decreased. Hodapp and Urbano (2007) found that sibling perception of closeness and positiveness in their relationship with their brother or sister with autism or Down syndrome was lower as sibling age increased. That is, older adult siblings (45 years and older) had fewer numbers of contacts and spent less time with their brother or sister with a disability than adult siblings who were younger (i.e.,<30 years; 30–45 years). Stoneman (2001) proposed that the amount of time siblings choose to spend together is one way to examine the quality of sibling relationships. Strategies have been used to successfully increase interactions between siblings and their brother or sister with a disability when interactions rarely or never occur (Belchic & Harris, 1994; Strain & Danko, 1995) and to teach siblings how to increase their interaction and communication with their brother or sister with a disability (Celiberti & Harris, 1993; James & Egel, 1986). 2.1.3. Sibling conflict Findings about sibling conflict are mixed. Mash and Johnson (1983) found that sibling conflict was greater between siblings and their brother or sister with hyperactivity than between siblings in a comparison group. Other research findings showed no differences in conflict between siblings of children with disabilities and siblings of typically developing children (Abramovitch et al., 1987; Brody et al., 1991; Stoneman et al., 1987, 1989). Relationships between adult siblings and persons with autism were less positive than relationships between adult siblings of persons with Down syndrome (Hodapp & Urbano, 2007). Stoneman (2001) points out that although levels of conflict do not differ between a group of siblings of children with a disability and a comparison group of siblings of typical children, the variability of conflict and negativity is large in both sibling groups. Stoneman notes that ‘‘the issue of sibling conflict is quite complex’’ (p. 137) and is likely related to differences in disabilities, temperaments, characteristics of the family context, and parenting behaviors. 2.1.4. Sibling roles Role asymmetry and sibling childcare responsibilities may be greater when a child has a disability. Siblings may help provide childcare, teach, and assist with managing the care and behavior of their brother or sister with a disability. As siblings take on these responsibilities, their relationship with their brother or sister with a disability becomes more asymmetrical than sibling relationships

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in a comparison group. Whereas these sibling relationships gradually become more asymmetrical, relationships between siblings without a disability tend to become more symmetrical over time (Stoneman, 2005). Role crossover occurs when younger siblings surpass their older brother or sister with a disability. Brody et al. (1991) found role asymmetries between older children with a disability and their younger typical siblings that were characterized by younger sibling dominance. In a comparison group of typical children, they found older sibling dominance. Minimal gender differences were found in sibling roles and behavior, and no differences in affect were found between these two groups. The capacity and skills of the child with a disability and the context of the sibling–child interaction influenced sibling behavior. Siblings of children with a disability may experience a wide variety of roles that can have both positive and negative effects for the sibling. Siblings can benefit from these experiences by gaining new skills and assuming responsibilities that may serve to boost their self-concept. Cuskelly and Gunn (2003) found that siblings who were more involved in chores and provided care for their brother or sister with Down syndrome had greater empathy. In a subsequent study, Cuskelly and Gunn (2006) examined sibling adjustment and responsibility for chores and caregiving in families of children with Down syndrome and typical children. The relationship between sibling adjustment in families having a child with Down syndrome and sibling responsibility for chores and caregiving was not significant in either the Down syndrome or the comparison group. Although sibling behavior problems have been reported when siblings have household or caregiving responsibilities (Cuskelly, Chant, & Hayes, 1998), McHale and Gamble (1989) noted that the relationship between sibling caregiving and negative outcomes may not be present when family characteristics are controlled. Engagement in activities outside of their home, relationships with peers, and academic performance did not differ between siblings of children with Down syndrome and a comparison group (Cuskelly & Gunn, 2006). In other words, siblings of children with Down syndrome ‘‘do not seem to be penalized in their opportunities to participate in a normal childhood’’ (Cuskelly & Gunn, p. 924). Stoneman (2005) points out that some siblings have major responsibilities in their home that restrict their ability to participate in normal childhood activities. For example, the sibling may be expected to socialize with the child with a disability because their brother or sister has few friends of their own. The sibling’s friends also may be asked or expected to engage in socializing activities with the child with a disability. 2.1.5. Sibling outcomes Implied in much sibling research has been the notion that children with a disability create stress or place families and family members at increased risk for stress. This emphasis on the negative effects of a disability on the sibling,

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family, and family members is being replaced with an understanding that there are both positive and negative effects for the sibling. In their metaanalysis of studies of siblings conducted between 1972 and 1999, Rossiter and Sharpe (2001) found a small negative effect for having a brother or sister with an intellectual disability. There is an increasing understanding that it is possible to experience both positive and negative developmental outcomes simultaneously (Fraser, Kirby, & Smokowski, 2004). Siblings face a multiplicity of both risk and protective factors. The sources of risk and protection include sibling biological attributes, sibling personality traits, characteristics of the child with a disability, family relationships, and community environments. The impact of having a brother or sister with a disability is multidimensional including variables that promote both positive and negative outcomes. The following review of sibling self-concept, behavior problems, depression, loneliness, locus of control, and self-efficacy provides support for this notion that siblings have both positive and negative outcomes related to having a brother or sister with a disability. 2.1.5.1. Self-concept Researchers have often hypothesized that the selfconcept of a sibling of a child with a disability would be negative. The assumption that having a brother or sister with a disability will negatively impact a sibling’s self-concept has not been supported by studies that compared siblings who have and do not have a brother or sister with a disability (Bagenholm & Gillberg, 1991; Burton & Parks, 1994; Dyson, 1996; Fisman et al., 2000; Hannah & Midlarsky, 1999; McMahon, Noll, Michaud, & Johnson, 2001; Rodrigue, Geffken, & Morgan, 1993; Singhi, Malhi, & Dwarka, 2002). For example, Verte, Roeyers, and Buysse (2003) found that sisters of children with high-functioning autism had a more positive self-concept than sisters in a comparison group. 2.1.5.2. Behavior problems The notion that siblings will have increased behavior problems has not been consistently supported by research. In studies of siblings of children with varying disabilities, no differences in behavior problems were found between siblings of children with and without a disability (Benson, Gross, & Kellum, 1999; Cuskelly et al., 1998; Gold, 1993; Kaminsky & Dewey, 2002; McMahon et al., 2001; Pilowsky, Yirmiya, Doppelt, Gorss-Tsur, & Shalev, 2004). In other studies, more behavior problems were present in siblings of children with disabilities yet these behavior problems were neither clinically significant nor did they reflect a need for intervention (Coleby, 1995; Cuskelly & Dadds, 1992; Cuskelly & Gunn, 1993; Fisman et al., 1996, 2000; Hastings, 2003; Nixon & Cummings, 1999; Rodrigue et al., 1993; Verte et al., 2003).

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2.1.5.3. Depression Findings on sibling depression are variable with some researchers finding greater depression among siblings of children with a disability and others finding no difference. For example, Gold (1993) found greater depression among siblings of children with autism and McMahon et al. (2001) found no difference between siblings of children with acquired brain injury and a comparison group of classmates. Hodapp and Urbano (2007) found that adult siblings of persons with autism reported more depressive symptoms than siblings of persons with Down syndrome. 2.1.5.4. Locus of control and self-efficacy College students who were siblings of persons with disabilities were found to have higher internal locus of control than their peers (Burton & Parks, 1994). This difference was thought to be related to siblings benefiting from growing up with a brother or sister with a disability. Grissom and Borkowski (2002) found no difference in self-efficacy in adolescents having a brother or sister with a disability and a comparison group of adolescents. 2.1.5.5. Differential parenting Differential parenting or ‘‘differences in parenting experienced by siblings’’ (Stoneman, 2005, p. 342) occurs as parents attend to their child with a disability and assure that their child’s needs are being met. Some researchers have described the effects of differential parenting on siblings as negative (Brody, Stoneman, & Burke, 1987; McHale & Gamble, 1989; Stocker, Dunn, & Plomin, 1989; Wolf, Fisman, Ellison, & Freeman, 1998). McHale and Pawletko (1992) described this differential treatment of siblings as a ‘‘complex and multifaceted phenomenon’’ (p. 78) that varied depending on the type of differential treatment, the potential consequences of the differential treatment, and the family context. They found positive effects for older siblings whose mothers spent more time with them than mothers in a comparison group. They posited that mothers of children with a disability may compensate for the time they spend with the child with a disability by spending more time with the older siblings. The positive effect for older siblings may result from their awareness of the obvious needs of their brother or sister with a disability and what they perceive as ‘‘the legitimacy of (parent’s) differential treatment’’ (McHale & Pawletko, 1992, p. 79) toward the child with a disability. 2.1.5.6. Supportive parenting Stoneman (2005) discusses supportive parenting of siblings in terms of ‘‘how parents socialize sibling relationships’’ (p. 342) and notes that few researchers have focused on this area. In McHale and Gamble’s (1989) study ‘‘linking parent and sibling behavior’’ (Stoneman, 2005, p. 342), they found that siblings who had more frequent negative interactions with their mothers also had more frequent conflicts with their brother or sister with a disability. Maternal negativity was

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associated with greater depression, anxiety, and low self-esteem among siblings of children with a disability.

3. Theoretical Approach Most sibling researchers have moved away from the pathological model to new theoretical approaches that encompass the sibling’s style of coping, the dynamics of the sibling relationship, consideration of the etiology of the disability, and the sibling’s social environment. Our review of studies of siblings found little evidence of integration or consideration of a theory in most research. Stoneman (1993) noted that research on siblings of children with disabilities is often atheoretical or conducted without a theoretical framework or model. This missing component in most sibling research reflects the challenges researchers face in identifying and clarifying theoretical perspectives related to siblings of a child or adult with a disability. In this section, theories relevant to sibling research are presented along with brief descriptions of how they have been or might be integrated into sibling research.

3.1. Family systems theory Application of general systems theory (Parsons, 1951; von Bertalanffy, 1950) to families led to the generation of family systems theory as an approach to families. According to family systems theory, the family is a living social system that is organized further into subsystems (e.g., parent– child subsystem, sibling–sibling subsystem). Relationships within the family exist within subsystems. Researchers focusing on families of children with disabilities have found family systems theory a workable framework for examining sibling–sibling relationships and parent–child relationships (Kahn & Lewis, 1988). Rivers and Stoneman (2003) used family systems theory in their study of marital stress and coping and siblings of children with autism. They noted the usefulness of this theory in explaining within-group variability of sibling relationships in families having a child with autism. Acknowledging that the sibling–sibling subsystem exists within multiple other systems that influence the sibling behavior, they examined the influence of marital stress and informal social support on the sibling relationship. Researchers examine the sibling–sibling subsystem and parent–sibling subsystem to increase our understanding of sibling relationships, interactions, conflict, roles, differential parenting, and supportive parenting, yet rarely acknowledge an association to family systems theory.

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3.2. Ecological systems theory Bronfenbrenner (1979) is credited with formulating ecological systems theory which recognizes that human beings can only be understood within their context (Germain, 1991). He identified five systems that influence human development. These include the (a) microsystem or immediate environment that involves person-to-person interaction such as the family, (b) mesosystem or those relationships between microsystems or immediate environments such as between the family and school, (c) exosystem or external environments that indirectly influence the child’s development such as a parent’s work setting, (d) macrosystem or the larger cultural context such as societal values and norms, and (e) chronosystem or the change in patterns of person–context interaction over time and their effects on development (Bronfenbrenner, 1986; Demo, Aquilino, & Fine, 2005). Stoneman (2005) recognized the important influence of the family, community, and culture to sibling research and included them in her own model. Researchers have knowingly or unknowingly designed their studies and interpreted findings using the ecological systems theory. For example, McHale and Pawletko (1992) relied on aspects of this theory to design their study of differential treatment of siblings. Others have used this theory to explain and further examine the findings from their research (Giallo & Gavidia-Payne, 2006; McHale & Gamble, 1989).

3.3. Family stress theory: Adaptation and coping Ecological systems theory recognizes that human beings can be best understood in their context (Germain, 1991). When this context includes a stressor, a response occurs. Much sibling literature has focused on sibling adaptation to the perceived or anticipated stress of having a brother or sister with a disability. Two family stress theories, the ABCX Model and the Resiliency Model of Family Stress, Adjustment, and Adaptation, are considered. The ABCX Model (Hill, 1965; McCubbin & McCubbin, 1987, 1989; McCubbin & Patterson, 1983) is a commonly used conceptual approach to understanding stress, adaptation, and coping in families. This model of family stress considers family adaptation as a product of the child’s disability, the family’s resources for dealing with the disability, the family’s perception of the experience of having a child with a disability, and the family’s coping strategies. The Resiliency Model of Family Stress, Adjustment, and Adaptation (McCubbin & McCubbin, 1993) builds on the ABCX Model by emphasizing family adjustment and adaptation to stressful situations. The emphasis of this model is on family resiliency, ability to positively recover from stressful

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events, and the strengths and capabilities that influence their response. In the Resiliency Model, families respond to stressful events in two phases, adjustment and adaptation, that occur over time. The Resiliency Model was used by Giallo and Gavidia-Payne (2006) in their examination of predictors of sibling adjustment and by Mandleco, Olsen, Dyches, and Marshall (2003) in their study of parent perception of family functioning, sibling social skills, and behavior problems. Cox, Marshall, Mandeleco, and Olsen (2003) identified four modes siblings of children with a disability use to cope with stressful situations. These modes of sibling coping are proactive, interactive, internally reactive, and nonactive responses. They point out the need to expand our knowledge of sibling response to stress and its relationship to sibling adjustment. Opperman and Alant (2003) examined the coping responses of adolescent siblings and resources available to assist them. Sibling ambivalence toward their brother or sister with a disability, unexpressed emotion, lack of support from parents, reliance on peer support, and limited family interaction were found. Although the researchers for these two studies did not identify a theoretical framework for their studies, findings from both studies could be examined from the perspectives of family stress theory. Nixon and Cummings (1999) examined sibling responses to family conflict. Siblings responded to family conflict and stress with more involved and proactive rather than avoidant coping strategies. Siblings’ short-term responses to stress appeared to be adaptive from the sibling’s point of view yet ‘‘chronic experience of stress, hypervigilance, and overinvolvement in family difficulties’’ (Nixon & Cummings, 1999, p. 282) may not be adaptive over time. Roeyers and Mycke (1995) integrated the transactional model of stress and coping (Lazarus, 1966; Lazarus & Folkman, 1984) into their study of stress and sibling relationships. Although Nixon and Cummings (1999) did not identify a theoretical framework in their study, their findings could be considered in the context of the transactional model of stress and coping to examine sibling ‘‘perception of imbalance between coping capacity and the environment’’ (Hobfoll & Schumm, 2002, p. 286).

3.4. Genetics and etiology A set of theoretical approaches to sibling research take into consideration the biological aspects of childhood disability. In most families, siblings are genetically related to their brother or sister with a disability, so siblings may share some of the same genes that cause the disorder and may have symptoms of the disorder. For example, in families of children with autism, siblings may demonstrate behaviors that are on the autism spectrum (Bolton et al., 1994). The presence of a sibling might provide researchers the opportunity to do a comparative study of two children with some shared genes in a shared environment. Thus, sibling research holds promise for

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behavioral geneticists who seek to understand how different expressions of genes influence the presence of a given condition (Hodapp, Glidden, & Kaiser, 2005). In addition, researchers might consider the biological basis of the child’s disability when considering how that might impact the sibling dyad. Stoneman (1998) proposes that variations in temperament and personality associated with different developmental disabilities may influence the sibling relationship. She postulates that since fragile X syndrome is associated with low sociability and active, impulsive, and emotional temperaments, sibling relationships in which one sibling in the dyad has fragile X syndrome might show higher levels of conflict. However, children with Down syndrome exhibit a range of temperament styles and tend to be sociable and have easy temperaments. Thus, the sibling relationships in families of children with Down syndrome might be similar to those in families with typical children. Both of these approaches emphasize the importance of the link between genotype/phenotype and the environment in theorizing about the sibling relationship. Molecular genetics is increasing our understanding of parent and child behavior by examining the contributions of genetics and the environment to the link between temperament and parenting and to the link between temperament and sibling relationships (Lemery & Goldsmith, 2002; Pike & Atzaba-Poria, 2003; Saudino, 2005). Variation in the dopamine receptor D4 (DRD4) gene and its influence on child temperament and quality of parenting was examined by Sheese, Voelker, Rothbart, and Posner (2007). Children with the DRD4 variation were influenced by the quality of parenting they received, while children without the DRD4 variation were not influenced by parenting quality. Indeed, a future study of differential parenting or supportive parenting of siblings might include a measure of genetic variations such as the DRD4 variation. This genetic information, along with other measures of child temperament could lead to the design of more effective parent training and other behavioral interventions (Sheese et al., 2007). Recognizing the potential influence of genetics on parent– sibling and sibling relationships and appropriate use of genetic information is critical as we seek to understand and support siblings and their families.

3.5. Life-course theory Another important consideration in sibling research is that changes in the sibling relationship may occur over the life course. As both the sibling and the child with a disability mature, their relationship will naturally change over time as their family changes and social events take place. The themes of the life-course theory are ‘‘(a) the interplay of human lives and changing historical times and places, (b) human agency in choice making and social constraints, (c) the timing of lives, and (d) linked, or interdependent lives’’

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(Elder, 1996, p. 36). The focus is on the individual, family, and sociohistorical events and transitions that change lives over time. Researchers can then study how these transitions and their paths are linked across family members (Bengston & Allen, 1993). Seltzer, Greenberg, Orsmond, and Lounds (2005) conducted a review of life-course studies related to siblings of persons with disabilities, which lends strong support to the importance of ongoing research in this area and points out the issues that need to be addressed in future research. Although the importance of longitudinal studies seems evident, cross-sectional studies such as the study by Hodapp and Urbano (2007) provide useful and relevant information about sibling experiences. Cross-sectional studies with different individuals at different points allow for inference of processes or changes that are occurring over time.

3.6. Social construction approach According to the social constructionist approach, there is no single view of reality. A social construct is a concept that is an invention of a particular society or culture even though it appears to be obvious to those persons who accept it as reality (Gergen, 1999). This approach ‘‘requires us to employ a wide-angle lens, to consider margins, groups, topics, and issues that have been ignored’’ (Walker, Allen, & Connidis, 2005, p. 170) as the social and historical contexts in which persons live are constantly changing. The experience of having a sibling with a disability raises one’s awareness about the ways that the disability experience is socially constructed. In their qualitative study of siblings, Opperman and Alant (2003) found that siblings felt that there was prejudice toward their brother or sister with a disability and reported that other people did not know how to act in the presence of their brother or sister. Sibling researchers have also noted the ways in which disability discrimination and oppression are understood and experienced by siblings. Dowling and Dolan (2001) noted that siblings may miss out on experiences such as going to the movies or out to eat because of public discrimination toward the child with a disability. This awareness and experience of discrimination and sense of oppression lead some siblings to push for social change. Marks, Matson, and Barraza (2005) found that the career choices of adult siblings enrolled in special education programs were motivated by a strong desire to improve services and challenge existing discrimination against people with disabilities. Findings from this qualitative study showed that the students were motivated to pursue administrative and policy-level positions to have a greater impact on the service delivery system. Thus, the sibling experience may play a key role in improving the lives of people with disabilities.

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3.7. Social modeling theory According to social modeling theory, a child learns by actively imitating or modeling what is seen and heard. The child learns whether or not the child’s own actions are reinforced or the child observes another child being reinforced (Bandura, 1969). Incidental learning occurs as a child sees or hears something that is not reinforced or desired by the child. In other words, ‘‘children acquire new behaviors by observing models in their environment’’ (Thomas, 2005). Social modeling has been examined in both directions in the sibling dyad: the sibling as a model for the child with a disability and the child with a disability as a model for the sibling. For example, James and Egel (1986) examined the reciprocal interactions between school-aged siblings and their brother or sister with a disability that resulted from direct prompting of the child with a disability. Children with a disability increased initiation of interactions with their siblings. Toth, Dawson, Meltzoff, Greenson, and Fein (2007) examined the social, imitation, play, and language abilities of 1.5- to 2-year-old nonautistic siblings and found siblings were functioning at a lower level in social communication and language than a comparison group. Hannah and Midlarsky (1999) examined mother and teacher ratings of social competence to look for differences between siblings who did and did not have a brother or a sister with a disability. Fussell, Macias, and Saylor (2005) studied families of children with attention-deficit hyperactivity disorder and learning problems to determine the influence of sibling behavior on the children. No difference in social skills was found for children who had and did not have typical siblings.

4. Research Method Research on siblings of children and adults with disabilities is in its infancy. This notion is supported when looking at sibling research from a methodological perspective. The following section addresses sampling, design, and measurement issues in sibling research. A review of the literature was conducted to identify sibling research conducted between 1980 and 2007. Studies having a majority of participants who were siblings of persons with intellectual or developmental disabilities were examined. Information extracted from the studies included diagnoses of the child or adult with a disability, sample size, source of information (parent, sibling, and teacher), sibling age (mean or range), and respondent’s race or ethnicity (Tables 7.1–7.3). Additionally, the instruments administered in each study were identified and are presented in Tables 7.4–7.6.

246

Table 7.1 Sibling research publications (1980 through 1989)

Author (date)

Diagnoses

Respondents

Breslau et al. (1981)

Cerebral palsy, myelodysplasia, multiple disabilities, cystic fibrosis (disability); children from New York city (no disability) DS; ID similar to DS

239 parents (disability) 1034 (no disability)

Gath and Gumley (1986)b James and Egel (1986) Abramovitch, Stanhope, Pepler, and Corter (1987) Lobato, Barbour, Hall, and Miller (1987)

Cerebral palsy, intellectual disability DS

Cerebral palsy, nonspecific global developmental delay, DS, spina bifida, blindness, hearing loss, hydrocephalus, severe head injury, William syndrome (disability)

Sibling mean (M) age by group

Race (%)a

Range (6–18 yr)

White (77)

192 parents (DS) 147 parents (ID) 3 siblings

White (93) [United Kingdom] Range (6–8 yr)

31 parents/siblings (DS)

Range (12–132 mo)

24 parents/siblings (disability) 22 parents/ siblings (no disability)

Disability (4.9 yr) No disability (4.6 yr)

[Canada]

Stoneman et al. (1987)

McHale and Gamble (1989)c

a

DS, organic brain syndrome, intellectual disability DS, spina bifida, cerebral palsy, brain damage, rare syndromes (disability)

16 siblings (disability) 16 siblings (no disability) 31 mothers/siblings (disability) 31 mothers/siblings (no disability)

Study participants from United States, unless country indicated in []. Sibling closest in age to child with disability chosen to be the focus of parent report. Sibling older than child with disability participated in study and was the focus of parent report. DS, Down syndrome; ID, intellectual disability b c

Disability (9.7 yr) No disability (9.4 yr) Disability (12.0 yr) No disability (12.1 yr)

White (100)

247

248

Table 7.2

Sibling research publications (1990 through 1999)

Author (date)

Diagnoses

Respondents

Sibling mean (M) age by group

Mates (1990)b

Autism

33 parents/ siblings (autism)

Range (15–17 yr)

McHale and Pawletko (1992)c

IDs related to DS, spina bifida, cerebral palsy, brain damage, rare syndromes. DS

31 mothers/siblings (disability) 31 mothers/siblings (no disability)

Disability (12.0 yr) No disability (12.1 yr)

70 mothers (DS) 67 mothers (no disability) 22 parents/siblings (autism) 34 parents/sibling (no disability) 19 mothers/siblings (autism) 20 mothers/siblings (DS) 20 mothers/siblings (no disability) 41 parents/siblings (LD) 41 parents/siblings (no disability) 20 siblings (autism) 20 siblings (ID) 20 siblings (no disability)

Range (6–13 yr)

[Australia]

Range (7–17 yr)

[Canada]

Autism (10.2 yr) DS (11.0 yr) No disability (9.4 yr) Range (5–16 yr)

White (90)

Cuskelly and Gunn (1993) Gold (1993)

Autism

Rodrigue et al. (1993)

Autism, DS

Coleby (1995)

Severe LD

Roeyers and Mycke (1995)

Autism; ID

Dyson (1996)

Severe LD

19 children/parents/siblings (LD) 55 parents/siblings (typical)

Autism (10.3 yr) ID (11.1 yr) No disability (10.8 yr) LD (9.8 yr) Typical (9.8 yr)

Race (%)a

White (76) Non-white (24) White (100)

[United Kingdom] [Belgium]

White (100) [Canada]

Fisman, Wolf, Ellison, Gillis, Freeman, and Szatmari (1996)d,e Krauss et al. (1996) Cuskelly et al. (1998) Eisenberg, Baker, and Blacher (1998)

Stores, Stores, Fellows, and Buckley (1998) Wolf et al. (1998)

PDD; DS

46 parents/siblings (PDD) 45 parents/siblings (DS) 46 parents/siblings (no disability)

Range (8–16 yr)

ID

140 siblings

Range (23–60 yr)

DS

45 parents (DS) 88 parents (no disability)

Intellectual disability living in home (ID-home) Intellectual disability living out of home (ID-placed) DS, ID

25 siblings/mothers (ID-home) 20 siblings/mothers (IDplaced) 28 siblings/mothers (no disability)

DS (11.4 yr) No disability (10.3 yr) ID-home (14.0 yr) ID-placed (13.3 yr) No disability (13.0 yr) Disability (11.6 yr) No disability (9.4 yr) Range (4–18 yr)

PDD; DS

54 mothers (disability) 78 mothers (no disability) 46 parents/siblings (PDD) 45 parents/siblings (DS) 46 parents/siblings (no disability)

[Canada]

[Australia]

White (80)

[United Kingdom] [Canada]

(continued)

249

Table 7.2

(continued)

250 Diagnoses

Respondents

Benson et al. (1999)e

CFA

60 parents (visible CFA) 60 parents (no visible CFA)

CFA (6.0 yr)

Greenberg et al. (1999) Hannah, Midlarsky (1999)d

MI; ID

61 siblings (MI) 119 siblings (ID)

MI (41.8 yr)

ID (IQ<55)

50 mothers/siblings (ID) 50 mothers/siblings (no disability)

ID (12.1 yr) No disability (11.6 yr)

DS, spina bifida, cerebral palsy, muscular dystrophy, osteogenesis imperfecta, blindness, deafness, ID, learning disability, seizure disorder, speech language delay.

30 parents/siblings (disability) 30 parents/siblings (no disability)

Disability (10.8 yr) No disability (10.4 yr)

Nixon and Cummings (1999)c

a

Sibling mean (M) age by group

Author (date)

Race (%)a

African American (11) Asian (1) White (77) Hispanic (11)

White (91) African American (9) White (100)

Study participants from United States, unless country indicated in []. Oldest sibling in the family participated in the study or was the focus of parent report. c Sibling older than child with disability participated in study or was the focus of parent report. d Sibling’s teacher provided data. e Sibling closest in age to child with disability chosen to be the focus of parent report and/or to participate in study. DS, Down Syndrome; ID, intellectual disability; LD, learning diability; PDD, pervasive developmental disorder; MI, mental illness; CFA, craniofacial anomalies. b

Table 7.3

Sibling research publications (2000 through 2007)

Author (Date)

Diagnoses

Respondents

Fisman, Wolf, Ellison, and Freeman (2000)b,c

PDD; DS

Lardieri, Blacher, and Swanson (2000)

LD, BP

Orsmond and Seltzer (2000) Pit-Ten Cate and Loots (2000)

ID

Time 1: 46 parents/siblings (PDD) 45 parents/siblings (DS) 46 parents/siblings (no disability) Time 2: 42 parents/siblings (PDD) 42 parents/siblings (DS) 43 parents/siblings (no disability) 18 parents/siblings (LD) 11 parents/ siblings (BP) 19 parents/siblings (LD & BP) 19 parents/siblings (no disability) 245 mothers/siblings

Van Riper (2000)c McMahon et al. (2001)b,c Rimmerman and Raif (2001)c Seltzer et al. (2001)

Spina bifida, cerebral palsy, multiple disabilities DS

43 parents/siblings

41 mothers/siblings

Severe pediatric traumatic brain injury ID

12 parents/siblings

ID

117 mothers 26 siblings

76 siblings (ID) 69 siblings (no disabilities)

Sibling mean (M) age by group

Race (%)a

Time 1: Range (8–16 yr) Time 2: Range (11–19 yr)

[Canada]

Range (10–18 yr)

White (72) African American (4) Hispanic (24)

(39.0 yr) Range (21–59 yr) (14.1 yr)

(11.5 yr) Range (7–18 yr) (13.1 yr)

251

ID (48.9 yr) No disabilities (46.7 yr) (38.2 yr) Range (22–56 yr)

[Netherlands]

White (93) White (100)

[Israel]

White (99) (continued)

Table 7.3 (continued) 252 Respondents

Sibling mean (M) age by group

Race (%)a

62 mothers/siblings

(12.3 yr)

White (81)

27 mothers/siblings (DD) 27 mothers/siblings (no disability) 30 parents/siblings (autism) 30 parents/siblings (DS) 30 parents/siblings (no disability) 252 parents/siblings

DD (14.7 yr) No disabilities (15.2 yr) Range (11–12 yr)

White (94)

46 siblings

(10.7 yr)

Cuskelly and Gunn DS (2003)c Autism Hastings (2003)c

54 parents/siblings (DS) 53 parents/siblings (no disability) 78 mothers (autism)

Range (7–14 yr)

Mandleco et al. (2003)b,c

39 parents (disability) 39 parents (no disability)

Author (Date)

Diagnoses

Taylor, Fuggle, and Cancer, spina bifida, Charman (2001)c other chronic conditions DS, autism, IDs, Grissom, and physical disabilities Borkowski (DD) (2002) Kaminsky and Autism, DS Dewey (2002)c Williams et al. (2002)b,c

Cancer, cystic fibrosis, diabetes, spina bifida, developmental disabilities

Cox et al. (2003)

Multiple disabilities

Speech disorder, developmental delay, DS, ID, physical disability, autism

(11 yr)

(6.7 yr) (7.4 yr)

[Canada]

White (86) African American (4) Native American (2) Hispanic (1) Asian (1) Other (6) White (94) Other (6) [Australia] [United Kingdom] White (90)

Opperman and Severe disabilities Alant (2003) Autism Rivers and Stoneman (2003)

19 siblings

Range (12–16 yr)

[South Africa]

50 parents/siblings

Range (7–12 yr)

HFA (11.1 yr) No disabilities (11.3 yr) (11 yr)

White (92) African American (6) Hispanic (2) [Belgium]

Verte et al. (2003)

HFA

29 parents/siblings (HFA) 29 parents/siblings (no disability)

Williams et al. (2003)b,c

Cancer, cystic fibrosis, diabetes, spina bifida, developmental disabilities

252 parents/siblings

Guite, Lobato, Kao, and Plante (2004)

Physical disability, PDD, developmental disability, chronic illness Autism, ID, DLD

45 parents/51 siblings (6 siblings in same family)

(9.9 yr)

30 parents/siblings (autism) 28 parents/siblings (ID) 30 parents/siblings (DLD)

Autism (9.7 yr) ID (9.9 yr) DLD (9.1)

Pilowsky et al. (2004)

White (86) African American (4) Native American (2) Hispanic (1) Asian (1) Other (6) White (88) African American (6) Hispanic (4) Other (2) [Israel]

(continued) 253

Table 7.3

(continued)

Author (Date)

Lobato and Kao (2005)

Diagnoses

Autism spectrum disorder, ID, physical disability, chronic health condition, psychiatric/ learning disorder Cuskelly and Gunn DS (2006)c Giallo and Gavidia- Intellectual, sensory, Payne (2006) physical, developmental disabilities Ross and Cuskelly ASD (2006) Hodapp and Autism; DS Urbano (2007) Orsmond and Autism; DS Seltzer (2007) a

Sibling mean (M) age by group

Race (%)a

40 parents/43 siblings (3 siblings in same family)

(5.7 yr)

White (100)

53 parents/siblings (DS) 53 parents/ siblings (no disability) 49 parents/siblings

Range (7–14 yr)

[Australia]

Range (7–16 yr)

[Australia]

25 mothers/siblings

(11.2 yr) Range (6–16 yr) Range (18 – 85)

[Australia]

Respondents

284 siblings (DS) 176 (autism) 77 siblings (autism) 77 siblings (DS)

White (91)

Autism (38.2 yr) DS (38.2 yr)

Study participants from United States, unless country indicated in []. Sibling’s teacher provided data. Sibling closest in age to child with disability participated in study or was the focus of parent report. DS, Down syndrome; ID, intellectual disability; LD, learning disability; BP, behavior problem; PDD, pervasive developmental disorder; DLD, developmental language disorder; HFA, high-functioning anomalies; ASD, autism spectrum disorder. b c

255

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Table 7.4

Sibling variables and instruments measuring those variables

Variable

Instrument (Author)

Respondent

Acceptance

Voeltz Acceptance Scale (Voeltz, 1980)a Psychiatric Screening Inventory (Langner et al., 1976)b Strengths and Difficulties Questionnaire-Parent Version (Goodman, Metlzer, & Bailey, 1998)c Weinberger Adjustment Inventory (Weinberger, 1996)c Children’s Depression Inventory (Kovacs, 1981; 1992)b General Positive Affect Scale (Viet & Ware, 1983)a Revised Children’s Manifest Anxiety Scale (Reynolds & Richmond, 1979)b Aberrant Behavior Checklist (Aman, Singh, Stewart, & Field, 1985)a Child Behavior Checklist (Achenbach, 1991)b,c,a Child Behavior Checklist— Youth Self-Report (Achenbach, 1991)c Conners’ Parent Rating Scale (Goyette, Conners, & Ulrich, 1978)b Eyberg Child Behavior Inventory (Eyberg & Robinson, 1983)c Revised Behavior Problem Checklist (Quay & Peterson, 1996)a Rutter A Scale: Questionnaire for Parents (Rutter, Tizardo, & Whitmore, 1970)b,a

Sibling

Adjustment

Anxiety/ depression

Behavior

Reliability estimates

Parent

.62–.93

Parent

.67–.82

Sibling

.89–.94

Sibling

.83

Sibling

.62–.92

Sibling

.82

Parent

Parent

.56–.81

Sibling

.83–.87

Parent

.79

Parent

.95–.98

Parent

.68–.95

Parent

.81

(continued)

256 Table 7.4 Variable

J. Carolyn Graff et al.

(continued) Instrument (Author)

Rutter B Scale: Questionnaire for Teachers (Rutter et al., 1970)b,a Sibling Inventory of Behavior (Schaeffer & Edgerton, 1981)b,c Survey Diagnostic Instrument (Cadman, Boyle, & Offord, 1988)c,a Competence Adolescent Interpersonal Competence Questionnaire (Buhrmester, 1990)c Perceived Competence Scale for Children (Harter, 1982)b,a Pictorial Scale of Perceived Competence and Social Acceptance (Harter & Pike, 1983)b,c,a Perceived Self-Efficacy Scale (Cowen et al., 1991)c Coping Coping Response InventoryYouth Form (Moos, 1993)c Kidcope (Spirito, Stark, & Williams, 1988)c Self-Report Coping Scale (Causey & Dubow, 1992)c Sibling Stress and Coping Inventory (Gamble & McHale, 1989)a Household Children’s Task Participation tasks Scale (Bird & Ratcliffe, 1990)a Impact of Sibling Impact Questionnaire disability (Eisenberg et al., 1998)c,a Relationships Empathy Scale (Borke, 1971)b Greensboro Instrument (Adams, 1968)c Loneliness and Social Dissatisfaction Questionnaire (Asher, Hymel, & Renshaw, 1984)c

Respondent

Reliability estimates

Teacher

.70

Sibling

.68–.90

Parent

.74

Sibling

.79–.80

Sibling

.70–.80

Sibling

.53–.83

Sibling

.84–.87

Sibling

.55–.70

Sibling

.41–.83

Sibling

.65–.89

Sibling

Parent

.73–.83

Sibling

.64–.84

Sibling Sibling

.82–.94

Sibling

.90

x

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Table 7.4

(continued)

Variable

Self-concept

Social skills

Stress

Support

a b c

Instrument (Author)

Respondent

Reliability estimates

Satisfaction with the Sibling Relationship Scale (McHale & Gamble, 1989)c Sibling Perception Questionnaire (Sahler & Carpenter, 1989)c Sibling Relationship Inventory (Schaeffer & Edgerton, 1981)a Sibling Relationship Questionnaire-Brief Version (Furman & Buhrmeister, 1985)c,a Sibling Relationship Questionnaire (Furman & Buhrmeister, 1985)c Piers-Harris Children’s SelfConcept Scale (Piers, 1984)a Self-Description Questionnaire I & II (Marsh, 1988)c Self-Esteem Inventory (Coopersmith, 1987)a Self-Perception Profile for Children (Harter, 1985)c,a Matson Evaluation of Social Skills with Youngsters (Matson, Rotatori, & Helsel, 1983)c Social Skills Rating System (Gresham & Eliot, 1990)c Sibling Daily Hassles and Uplifts Scale (Giallo & Gavidia-Payne, 2006)c Perceived Effect on Sibling Scale (Breslau et al., 1981)b Social Support Scale for Children (Harter, 1986)c,a

Sibling

.80

Sibling

.30–.77

Sibling

.80–.90

Sibling

>.70

Sibling

.58–.86

Sibling

.71–.77

Sibling

.60–.94

Sibling

.70–.83

Sibling

.71–.86

Sibling

.64–.80

Teacher

.72–.87

Sibling

.88–.93

Parent

.75

Sibling

.72–.88

Instrument used in one or more studies published from 1990 through 1999. Instrument used in one or more studies published from 1980 through 1989. Instrument used in one or more studies published from 2000 through 2007.

258 Table 7.5

Variable

Burden

J. Carolyn Graff et al.

Parent variables and instruments measuring those variables

Instrument (Author)

Perceived Burden Scale (Zarit, Reever, & BachPeterson, 1980)a Depression Beck Depression Inventory (Beck, Rush, Shaw, & Emery, 1979)b,a Profile of Mood States (McNair, Lorr, & Droppleman, 1992)a Emotional Malaise Inventory (Rutter distress et al., 1970)a Marital Dyadic Adjustment Scale adjustment (Spanier, 1979)b,a Locke-Wallace Short Marital Adjustment Test (Locke & Wallace, 1959)b Porter-O’Leary Scale (Porter & O’Leary, 1980)b,a Parenting Parent Behavior skills Questionnaire (Gordon, 1994)a Pessimism Beck Hopelessness Scale (Beck, Weissman, Lester, & Trexler, 1974)b Psychological Brief Symptom Inventory distress (Derogatis, 1993)a Stress Parenting Stress Index (Abidin, 1990)b Perceived Stress Scale (Cohen, Kamarck, & Mermelstein, 1983)a Social support Inventory of Parent Experiences: Social Support Scale (Crnic & Greenberg, 1983)a Social Support Questionnaire-Revised (Sarason, Levine, Basham, & Sarason, 1983)b

a b

Respondent

Reliability estimates

Parent

.87

Parent

.81

Parent

.80–.91

Parent

.70–.80

Parent

.58–.96

Parent

.81–.91

Parent

.86

Parent

.83

Parent

.82–.93

Parent

.71–.85

Parent

.70–.84

Parent

.84

Parent

.60–.77

Parent

.75

Instrument used in one or more studies published from 2000 through 2007. Instrument used in one or more studies published from 1990 through 1999.

259

Issues in Sibling Research

Table 7.6 Family variables and instruments measuring those variables

Variable

Adaptability, cohesion

Instrument (Author)

Family Adaptability and Cohesion Evaluation Scale (Olson et al., 1985)a,b Family Time and Routines Index (McCubbin, Thompson, & McCubbin, 1996)b Burden of care Clinician’s Overall Burden of Care Index (Stein & Jessop, 1982)b Impact on Family Scale (Stein & Jessop, 1985; Stein & Riessman, 1980)b Questionnaire on Resources and StressShort Form (Friedrich, Greenberg, & Crnic, 1983)a Communication Family Environment Scale-Form R (Moos & Moos, 1981)a Family Problem Solving Communication Index (McCubbin et al., 1996)b Family Bloom’s Family functioning Functioning Instrument (Bloom, 1985; Bloom & Naar, 1994)b Family Environment Scale-Form R (Moos & Moos, 1981)a Hardiness Family Hardiness Index (McCubbin et al. 1996)b Quality of Children’s Version of the family life Family Environment Scale (Moos & Moos, 1981)a

Respondent

Reliability estimates

Parent/ sibling

.80–.83

Parent

.79

Parent

Parent

.60–.86

Parent

.79–.85

Parent

.77–.83

Parent

.86

Parent

.58–.76

Parent

.77–.83

Parent

.87

Sibling

.80

(continued)

260

J. Carolyn Graff et al.

Table 7.6 (continued) Variable

Instrument (Author)

Respondent

Reliability estimates

Resources

Family Life Inventory of Resources for Management (McCubbin, Comeau, & Harkins, 1991)b Family Support Scale (Dunst, Jenkins, & Trivette, 1984)b Daily Hassles and Uplifts (Kanner, Coyne, Schaefer, & Lazarus, 1981)b Family Crisis-Oriented Personal Evaluation Scales (McCubbin, Olson, & Larsen, 1987)b Family Inventory of Life Events (McCubbin, Patterson, & Wilson, 1983)b Family Inventory of Life Events and Changes (McCubbin et al., 1996)b

Parent

.62–.80

Parent

.75–91

Parent

.60–.79

Parent

.71–.84

Parent

.81

Parent

.72

Social support

Stress and coping

a b

Instrument used in one or more studies published from 1990 through 1999. Instrument used in one or more studies published from 2000 through 2007.

4.1. Sampling That most sibling research studies include small numbers of participants, usually 20–50 per group (Hodapp et al., 2005), is supported by the data in Tables 7.1 through 7.3. Exceptions have been studies in which participants (a) represented multiple clinical sites (Breslau, Weitzman, & Messenger, 1981), (b) were recruited through schools in one health region (Gath & Gumley, 1986), (c) were engaged in a large longitudinal study (Greenberg, Seltzer, Orsmond, & Krauss, 1999; Krauss, Seltzer, Gordon, & Friedman, 1996; Orsmond & Seltzer, 2000; Seltzer, Krauss, Hong, & Orsmond, 2001), and (d) were recruited through national and state disability-related organizations and networks (Hodapp & Urbano, 2007). Hodapp et al. (2005) raised additional concerns about how representative sibling research samples really are. They note that participants in sibling research may often be volunteers from clinics, health facilities, and parent

Issues in Sibling Research

261

groups. The characteristics of persons served by clinics and health facilities may vary greatly and vary from persons with disabilities who do not attend and do not need to seek out medical and health attention. Some disabilities require more medical attention and ongoing health care than other disabilities. Persons who participate in support groups may have different needs and characteristics than persons who do not participate in these groups. Researchers who are sensitive to family members’ busy lives may seek to minimize their intrusion on the family by accepting only those individuals who are eager to participate. Interestingly, many of our conclusions about siblings of children with disabilities have evolved from studies with relatively small numbers of participants. Other issues that need to be considered relate to which sibling participates in research. Siblings are selected to participate in research studies or serve as the focus of parent responses based on the sibling being (a) available and willing to participate, (b) closest in age to the child with a disability, (c) immediately older than the child with a disability, (d) the oldest sibling in the family, and (e) the most involved with the child or adult with a disability. These differences make comparison of studies challenging and information from one study of siblings with one set of characteristics cannot readily be generalized to siblings with different characteristics. Recognizing this limitation, Hodapp et al. (2005) offered the following suggestions to improve the generalizability of the sibling research findings: (a) study more than one sibling of the person with a disability, (b) systematically sample older and younger siblings, (c) consider the effects of gender, size of the sibling group, and age differences between sibling and person with the disability on outcomes during childhood and adulthood. Sibling research has gradually moved from including only parents or siblings as participants to including parent and sibling participants. This shift may have been guided by theoretical perspectives such as the family systems and ecological theories or researchers’ findings that supported a need to expand their inquiry to the sibling. Despite this broadening of participation, it is mostly mothers who have participated in sibling research. However, research that includes siblings as the only participants seems to be increasing with our growing interest in adult siblings and our aging population. Other relevant individuals such as the teachers of siblings are rarely studied. Although participant race and ethnicity are not identified in many published reports, of the participants identified, most are white, with smaller numbers of siblings from African American and Hispanic families (Tables 7.1–7.3). Globally, researchers are publishing their findings about siblings and their parents who live in Australia, Belgium, Canada, Israel, the Netherlands, South Africa, the United Kingdom, and the United States. Another shift has occurred as sibling researchers increasingly focus on siblings of persons with one type of disability. Stoneman (1998) raised important questions about sample parameters in sibling research and

262

J. Carolyn Graff et al.

whether sibling research should be conducted using homogeneous or heterogeneous groupings. The genetic and genomic explosion is likely one of several factors that has contributed to our interest in homogeneous groupings. Although there is known variation within a disability, there are several reasons to examine the sibling experience by type of disability. Many support groups and intervention programs are tailored to address the unique needs of a child or adult with a certain type of disability. A child with a genetic disorder may demonstrate behaviors and characteristics that are unique to most persons with the genetic disorder. Examining sibling relationships in a group of persons with one type of genetic disorder can provide insights into ways to support and nurture the sibling relationship. At the same time, siblings will have many of the same experiences that siblings have in families of persons with a different disability. And, siblings will also have the same experiences that siblings have in families of persons without a disability. Studies of adult siblings of persons with autism and Down syndrome have pointed to differences and similarities by type of disability (Hodapp & Urbano, 2007; Orsmond & Seltzer, 2007). These findings offer support for examining siblings according to disability type and comparing findings across disability groups.

4.2. Design Although sibling researchers have employed designs using two or more groups, these comparisons are not problem-free. Stoneman (2001) notes that there are ‘‘numerous challenges involved in defining and recruiting appropriate comparison groups in family research’’ (p. 140). When siblings of children with disabilities are found to have different relationships with their brother or sister compared to siblings of typical children, the utility of this information must be determined. Stoneman goes on to point out that relationships that are different do not imply pathological or problematic relationships. Hodapp et al. (2005) remind us that the design of a study is dependent on the question being asked. Numbers of studies have been conducted to compare siblings of children with disabilities to siblings of typically developing children. They support use of a three group design as suggested by Seltzer, Abbeduto, Krauss, Greenberg, and Swe (2004). The influence of differing characteristics of a child with a disability on the sibling relationship is measured. Comparing and contrasting three groups of siblings whose brother or sister has a different disability could provide useful information as the presence of a disability in each group might serve to ‘‘control’’ for common aspects across disabilities.

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In designing a study, sibling researchers should take into account mediating and moderating variables. Stoneman (2005) reminds us of the complexity of family systems and that ‘‘the most influential family processes are interactive’’ (p. 346). One variable may influence an observable outcome by acting through an intermediate or mediating variable. For example, extra time spent by a mother with her child with a disability creates anger and resentment in the younger sibling. The sibling, in turn, acts out to gain his mother’s attention. The emotional reaction mediates the relation between maternal time and the outcome of acting out. Moderating variables, in contrast, influence the degree to which an effect is manifested dependent on the presence, absence, or level of another variable. For example, sibling disagreements occur at mealtime but their frequency and intensity may vary depending on parental behavior, the moderating behavior. When the parent uses effective strategies, the disagreements are diminished or averted. Hodapp et al. (2005) noted that more needs to be known about moderating variables such as sibling gender and ethnicity on sibling relationships and outcomes. Intervention studies in sibling research are rare, but two recent studies demonstrated that they can be effective. Lobato and Kao (2005) conducted a quasi-experimental study with parents and siblings of children with developmental disabilities and chronic illnesses. The intervention consisted of six sessions with parents and siblings. Sessions focused on improving sibling knowledge and family discussions about the child’s disability, identifying and managing sibling emotions and problem solving, and identifying sibling strengths and needs within the family. Data on sibling knowledge, sibling sense of connectedness, and sibling behavior were collected at pretest, within 2 weeks after the intervention, and 3 months following the intervention. Sibling knowledge of their brother or sister’s condition, connectedness with other siblings, and perception of self-competence increased following the intervention. Although parents reported no change in sibling behavior (based on the Child Behavior Checklist), their satisfaction with the intervention program was high. Williams et al. (2003) conducted a three-group intervention study with siblings of children with developmental disability and chronic illness. Their three-group design included a full intervention group (i.e., structured teaching and psychosocial sessions at a 5-day residential summer camp), a partial intervention group (i.e., 5-day residential summer camp only), and a control group. Siblings in the full intervention group showed significant improvements in knowledge of the illness or disability, social support, selfesteem, and attitude up to 12 months after their intervention. Siblings receiving the partial intervention showed significant improvements in social support and self-esteem up to 12 months after the intervention. Siblings in the control group showed significant improvements only in attitude at all points of data collection over 12 months.

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4.3. Measurement Instruments used in sibling research studies between 1980 and 2007 are shown in Tables 7.4 through 7.6. Each instrument was categorized as measuring a sibling, parent, or family variable. Although an instrument may have measured more than one variable or construct, for ease of presentation and review, the authors assigned each instrument to one variable. Instruments were used at least once in a study published between 1980 and 2007. The research participant responding to the instrument is noted in the respondent column. Reliability estimates were obtained from the published studies or sources referenced by the researcher. 4.3.1. Sibling instruments Instruments measured a variety of domains to include sibling adjustment, behavior, competence, coping, relationships, and self-concept (Table 7.4). The number of sibling instruments reported to have been used at least once in studies published between 1980–1989, 1990–1999, and 2000–2007 were 12, 18, and 26, respectively. The Child Behavior Checklist (Achenbach, 1991) and the Pictoral Scale of Perceived Competence and Social Acceptance (Harter & Pike, 1983) were used in one or more studies conducted during all three time periods. Most instruments were completed by siblings; however, 11 of the 44 instruments were completed by parents and 2 were completed by teachers. The variables having the most instruments were sibling behavior and sibling relationships. 4.3.2. Parent instruments Instruments measured parent variables such as perceived burden, depression, emotional distress, marital adjustment, stress, and social support (Table 7.5). All instruments were completed by the parent. The number of parent instruments reported to have been used at least once in studies published between 1980–1989, 1990–1999, and 2000–2007 were 0, 7, and 10, respectively. 4.3.3. Family instruments Instruments measuring aspects of the family or family related variables such as adaptability, burden of care, social support, and stress and coping are shown in Table 7.6. All but 2 of the 18 instruments were completed by parents. Siblings completed the Children’s Version of the Family Environment Scale (Moos & Moos, 1981) and siblings and parents completed the FACES or Family Adaptability and Cohesion Evaluation Scale (Olson, Portner, & Lavee, 1985). The number of family instruments reported to have been used at least once in studies published between 1980–1989, 1990–1999, and 2000–2007 were 0, 5, and 13, respectively.

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4.3.4. Child with a disability instruments The degree and severity of the child’s disability and the adaptive skills and functioning of the child with a disability were the variables measured in studies listed in Tables 7.1–7.3. The Adaptive Behavior Scales (Nihira, Foster, Shellhaas, & Leland, 1974) were used in two studies to measure the degree of the child’s disability (Gath & Gumley, 1986; Grissom & Borkowski, 2002). The severity of autism was measured by the Gilliam Autism Rating Scale (Gilliam, 1995) in a study by Ross and Cuskelly (2006) and by the Autism Behavior Checklist (Krug, Arick, & Almond, 1980) in a study conducted by Hastings (2003). In their study of the behavioral adjustment of siblings of children with craniofacial anomalies, Benson et al. (1999) measured the severity of a craniofacial impairment using the Revised Denver Developmental Screening Test or RDDST (Frankenburg, Frandal, Sciarillo, & Burgess, 1981). In children with a traumatic brain injury (TBI), McMahon et al. (2001) used the Glasgow Coma Scale (Teasdale & Jenett, 1974) to measure the severity of the TBI and the Wee-FIMTM (Wee-FIMTM System Clinical Guide, 1998) to measure functional outcome of the injured children. The Normative Adaptive Behavior Checklist (Adams, 1984) was used by Fisman et al. (1996) to measure the characteristics and adaptive ability of children with disabilities. Various instruments are being used in sibling research to measure the adaptive skills of children with disabilities and the severity of their disability. Several points should be made. First, the child’s degree of independence and ability to participate in activities of daily living are likely to be more significant to the sibling and parents than the severity of the child’s disability. Second, measuring severity alone will not capture the functioning ability of the child with a disability. Third, using an instrument that measures specific aspects of a disability paired with a measure of adaptive skills and functioning ability may be warranted. For example, the Glasgow Coma Scale which is an indirect measure of a child’s ability to function, paired with the WeeFIMTM which is a direct measure of a child’s ability to function, will provide a more complete view of the impact of the child’s disability. Use of a screening instrument such as the RDDST provides an incomplete and possibly inaccurate view of the child’s functioning abilities, strengths, and needs.

5. Frontiers and Directions for Sibling Research Potential directions for the future of sibling research include examining new theoretical perspectives, measures and designs, and the use of advanced statistical techniques. Theoretical avenues yet to be explored

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include the use of empowerment theory and complexity theory. Currently, we know of no studies or theoretical models of sibling empowerment.

5.1. Theoretical perspectives Future sibling research should start with researchers stating their theoretical approach. Few sibling researchers identify their theoretical approach; however, theoretical orientations can be identified in some studies from the researcher’s assumptions and hypotheses. Similarly, the review of literature reveals a researcher’s perspectives of what is and is not important when studying siblings. Claiming their theoretical approach can help researchers (a) gain a more complete and thorough understanding of the factors influencing siblings; (b) develop appropriate strategies and interventions to guide and support siblings; (c) accept, reject, or modify theories related to siblings. 5.1.1. Empowerment Empowerment has been defined as inclusive of choice (Renz-Beaulaurier, 1998) and self-determination (Weiman, Doseland-Hasenmiller, & O’Melia, 2002) and as a process of gaining knowledge and skills and thereby gaining positive control over life (Singh, 1995). Siblings play an important role in the lives of adults with disabilities (Seltzer et al., 2005). In thinking about siblings and empowerment, there are two important considerations: (a) What contributes to the empowerment of siblings themselves, and (b) How can siblings facilitate the empowerment of their family member with a disability? A research agenda on empowerment for the siblings themselves, might include the examination of siblings’ self-efficacy, locus of control, and perceptions of whether they have adequate knowledge and skills related to the disability as these constructs have all been defined as essential components of empowerment (Rappaport, 1981). Further examination of these constructs and their relationship to siblings’ experience of empowerment might be a good starting place for research on this topic. In order to begin a research agenda on sibling empowerment, a scale would need to be developed. Two scales have been created to measure parent empowerment: the Psychological Empowerment Scale (Akey, Marquis, & Ross, 2002) and the Family Empowerment Scale (Koren, DeChillo, & Friesen, 1992). These parent-focused scales could be used as a guide for creating a measure of sibling empowerment. One of the challenges in beginning a research agenda on empowerment would be distinguishing between empowerment of the siblings and that of the person with the disability. Abery and Stancliffe (1996) point out that family members play a key role in either promoting self-determination and empowerment for people with disabilities or in becoming overprotective and hindering it. There is the possibility that strategies that are aimed at

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empowering the sibling might hinder the empowerment of the person with the disability. This issue should be carefully considered in a research agenda around empowerment. 5.1.2. Complexity theory Complexity theory and its application to development (Andrews, Halford, Bunch, Bowden, & Jones, 2003) and our approach to systems (West, 2005) deserves the attention of sibling researchers. Evolving from systems theory and nonlinear dynamic systems theory, complexity theory views systems as nonlinear and complex with diverse individuals interacting with each other and capable of spontaneous self-organization (Cilliers, 1998; Waldrop, 1992). In complexity theory, the key to understanding the family system is in understanding the patterns of relationships and interactions among the family members or others important to the family. The family is a complex adaptive system. Family members exchange information with others in their environment and adjust their behavior, accordingly. One family member can influence all others in the family through a network of connection. Interactions among family members lead to development of global patterns. Since family members interact with each other, no one member of the family can know the system as a whole. Because interactions are nonlinear, small events can have large effects and large events can have small effects. Self-organization is a central tenet of complexity theory and is a characteristic of the family. Self-organization occurs as family members mutually adjust their behaviors and create new behaviors to meet the demands of the relationships they have with each other and their environment (Cilliers, 1998; Prigogine, 1997). Family systems theory has served as the theoretical approach for many sibling studies and may have promoted a simplistic assumption that one family member’s difficulties will have a negative impact on all family members. Examining sibling relationships from the perspective of complexity theory could offer researchers new insights into the complexity and confusion surrounding these relationships. The diversity within relationships between siblings and their brother or sister with a disability could be respected and better understood. Having evolved from systems theory, complexity theory merits the consideration of sibling researchers.

5.2. Measures and designs As sibling research expands due to new theoretical perspectives, new measurement techniques will need to be considered. As discussed above, concepts such as empowerment will require new measures that are adapted to be relevant to siblings. Sibling behaviors such as the amount of time spent with the brother or sister with a disability may be measured along with

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quality of interactions to provide insights into the sibling relationship. Sibling research could also benefit from measures designed to include multiple respondents. Future sibling research should include larger samples, longitudinal studies, use of multiple respondents, and studies of more diverse populations. The sample size of most studies we reviewed (Tables 7.1–7.6) was less than 60 parents or siblings per group. Most studies interviewed white US mothers of children with autism or pervasive developmental disorder and Down syndrome. To increase our knowledge of siblings, it will be beneficial to include more diverse populations in our research. Although sibling research has included investigation of the sibling relationship in both childhood and adulthood, most of these studies are cross-sectional, gathering of data at only one point in time. More longitudinal research on sibling relationships is needed.

5.3. Advanced statistical techniques Advances in technology in recent years have made new types of statistical techniques available that create new opportunities in sibling research. Perhaps one of the best known advanced statistical techniques is structural equation modeling (SEM). SEM is a set of techniques that affords researchers the opportunity to model latent variables and to examine the covariance between latent and observed variables. SEM can additionally be used to model causal relationships given an appropriate dataset (Kline, 2005). In sibling research, SEM has been used by Williams et al. (2002) to examine the interrelationships among variables such as sibling self-esteem, mood, knowledge, behavior, attitude, and social support as well as the relationship of these variables to child and parent variables. SEM has also been used in studies of parents to examine the validity of the ABCX Model in explaining caregiver strain and burden (Brannan & Heflinger, 2001). There are two ways in which the use of SEM could be expanded to advance the field of sibling research. The first would be to test theory. For example, SEM could be used to test the double ABCX Model in sibling research similar to the way it was used in the Brannan and Helflinger (2001) study in parents. In addition, SEM could be used in causal modeling to test the longitudinal outcomes for siblings. Another relatively recently developed statistical technique available to researchers is multilevel modeling or hierarchical lineal modeling (HLM). HLM is a technique used to examine nested data. HLM allows researchers to control for covariates when individual observations are not independent. It is particularly useful to social science researchers when studying individuals who are nested in contexts such as families, schools, or communities (Luke, 2004). HLM could be particularly useful to sibling researchers when examining data sets of siblings in which several of the siblings belong to the

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same family. Using this technique, characteristics of the sibling could be examined as well as characteristics of the family. To our knowledge, HLM has not yet been used in sibling research. Finally, statistical techniques that examine clusters within the data are available to researchers such as cluster analysis or latent class analysis (LCA). These are person-centered techniques that examine whether there is a typology within the data set. All cluster analysis techniques seek to minimize the within cluster differences and maximize between cluster differences. K-means clustering is the simplest and probably the most well-known technique for examining underlying typologies which minimize the sum of distances from the data points to the centroid (Vermunt & Magison, 2002). LCA is a model-based technique that uses maximum likelihood estimation. LCA uses a set of measured variables to estimate a latent typology. An advantage of LCA over standard cluster analysis is that fit indices can be used to decide which model best explains the underlying typology in the data (Muthen & Muthen, 2004). LCA can be used either as an exploratory technique to find subgroups in a data set or as a confirmatory technique to substantiate the presence of subgroups that have been previously hypothesized (McCutcheon, 1987). There are many questions in sibling research that could be addressed using either latent class or cluster analysis. For example, these techniques could be used to identify clusters of siblings based on coping styles or based on the strength and closeness of the sibling relationship. Identification of clusters could be useful in tailoring interventions to meet the needs of specific siblings.

6. Conclusion Many siblings adapt well, have positive relationships with their brother or sister with a disability, and benefit from assuming increased caregiving or household responsibilities. Concern that some siblings are more vulnerable than others persists. This worried interest in siblings comes from parents of children with disabilities, the professionals working with families having a child with a disability, and adult siblings. Researchers also recognize differences in sibling responses to having a brother or sister with a disability and the importance of describing the sibling experience, identifying resources and supports for siblings, and implementing strategies to meet their needs. Based on this research review, some of the challenges of conducting sibling research have become evident. Siblings who are research participants or the focus of research are most often school-aged children and adolescents. The ability of children to recognize and articulate their perspectives to researchers has appropriately been questioned. Few studies of adult siblings and even fewer studies of preschool siblings have been conducted.

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Numerous instruments have been used to measure characteristics and attributes of siblings, parents, children with disabilities, and families. Consistent use of instruments across studies could assist researchers in identifying instruments that should be retained, instruments that should be revised or replaced, and constructs that need to be measured. Just as sibling concerns may go unnoticed, their contributions to the child with a disability and the family may go unrecognized by parents and professionals. Siblings’ contributions begin to be recognized when parents question their own abilities to continue as the responsible caregiver for their child with a disability. As described by Bluebond-Langner (1996) in her book, In the Shadow of Illness: Parents and Siblings of the Chronically Ill Child, siblings may remain in the shadow of their brother or sister and the disability. Efforts to identify and develop supports and resources for siblings should be analogous to our efforts to identify and develop supports and resources for parents of children with disabilities. The increased volume of research on siblings of persons with disabilities appears to be associated with improved rigor. While there has been improvement in the design of sibling research, the generalizability of most sibling research is limited by small sample sizes and insufficient power. Limited funding and efforts to minimize the burden on the siblings, parents, family members, and the researcher tend to result in small sample sizes, fewer respondents per family, and use of fewer instruments. Use of heterogeneous groups may have resulted in increased sample size because of researchers’ easy access to parents and siblings in clinical settings, yet this approach has resulted in within group differences that were overlooked. Although longitudinal designs can improve the reliability of findings, developmental changes in the sibling and the child with a disability, changes within the family and members of the family, and events occurring outside the family must be taken into account. Researchers interested in studying siblings and their families face the challenge of limited funding. The Sibling Research Consortium was begun in 2003 to focus research on life span experiences for siblings and their families, build capacity for conducting sibling research, and influence policy and practice using these findings (Vanderbilt University, 2008). Similar collaborative efforts that bring together researchers, clinicians, family members, and advocates can result in greater knowledge of siblings of children with disabilities. In summary, sibling research is truly in its infancy. A theory or model should drive the research design, selection of instruments, and statistical analysis (Cairns, Costello, & Elder, 1996). Research designs that are experimental, longitudinal, and comparative are desirable. Multivariate analytic techniques that compare groups may need to be replaced or supplemented with statistical techniques such as cluster analysis and latent profile analysis to help identify and form sibling groups. Unique characteristics within or

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between diagnostic or other groupings can be determined. Qualitative research may be needed to identify topics or variables that need to be examined and instruments to measure these variables of interest. Triangulation of research methods and theories can increase the likelihood of identifying potential confounders and lead to more substantiated conclusions (Janesick, 1994). Research funding, research-related costs to siblings and families, and the researcher’s time must be weighed against the long-term benefits to siblings, persons with disabilities, and families.

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Understanding Individual Differences in Adaptation in Parents of Children with Intellectual Disabilities: A Risk and Resilience Perspective Malin B. Olsson* Contents 1. Introduction 2. Risk and Protective Factors in the Field of Families with a Child with ID 2.1. Critical evaluation of Wallander and Varni’s risk and resistance model 2.2. Three broad areas of risk and protective factors in families of children with ID 3. Risk Factors 3.1. Child and disability risk factors 3.2. Socio-ecological risk factors 3.3. Intrapersonal risk factors 3.4. Summary: Risk factors 4. Protective Factors 4.1. Child and disability protective factors 4.2. Socio-ecological protective factors 4.3. Intrapersonal protective factors 4.4. Summary: Protective factors 5. Outcomes 5.1. Depression in parents of children with ID 5.2. Family quality of life 6. Discussion 6.1. Design improvements 6.2. Why study resilience? 7. Conclusion References

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Abstract In this chapter, I focus on the theoretical perspective of risk and resilience as a framework for studying the processes leading to individual variation in adaptation of parents with children with intellectual disabilities (ID). Relevant literature related to parental adaptation to a child with ID is reviewed, organized, and discussed. The challenge of conceptualizing risk and protective factors as well as resilience is examined, and designs to improve future research are suggested. I argue that to understand the processes leading to individual variation in well-being in parents of children with ID, we need to do more within-group analyses and address the complex interplay of cumulative risk and protective factors.

1. Introduction Two different views of parents of children with an intellectual disability are extant in research and in society at large. These parents are either pitied or seen as exceptionally strong and competent. In contrast, Mary Jo Herbert, a mother of a child with disabilities, expressed the importance of a balanced view of parents of children with disabilities in her essay in the American Association on Mental Retardation News & Notes in 2001. She wrote: Parents of children with disabilities have a serious image problem . . . The image that I am referring to is that of the Exceptional Parent. But the idea that parents of children who are developmentally disabled are exceptional is a myth. The hard truth is that parents of kids with disabilities bring no inherent exceptional qualities to their role. What they bring is the same amount of patience, intuition, energy, and enthusiasm as any other parent gets. . . If there is anything exceptional about our lives it is the exceptional conditions under which we live them. We are ordinary parents trying to live ordinary lives under extraordinary circumstances. . .(pp. 7–8).

The focus of this chapter is on understanding the individual differences in adaptation to these extraordinary circumstances. That is, what happens when parents with their individually different lives and experiences meet the extraordinary circumstances involved in caring for a child with intellectual disabilities (ID)? Parents of children with disabilities often raise their children within the context of a powerful societal discourse that devalues disabilities and they are therefore expected to feel emotionally burdened (Green, 2007). Parents with positive attitudes toward raising a child with a disability are often pathologized as being unrealistic, in denial, and failing to accept their ‘‘tragic’’ circumstances since professionals often view acceptance of the

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child’s disability as the first step in a healing process (Green). But simple terms such as acceptance and denial do not capture parents’ experiences of raising a child with disabilities (Larson, 1998). Being a parent of a child with a disability does not only include a loss, as there is also the joy of having become a parent. Parents may be able to find benefits in having a child with a disability, and family, friends, and professionals who discourage them from doing so may be impeding the development of the positive aspects of caring. Larson argues that acceptance as borrowed from the conceptualization of the stages of grieving is not accurate in this instance, where instead of a certain future, parents face an indeterminate future for their child with a disability. She found that when mothers were asked what would improve their well-being, all of them wished for miraculous cures—that the child would walk and talk, that the child would be normal. Yet at the same time, they expressed a deep love and affection for their children just as they were. While embracing their child despite the disability, mothers simultaneously rejected the limitations of the disability, continuing to aspire to more typical mothering. There is no doubt that complex emotions and experiences are set in motion when a child with disabilities is born, but parents do not describe their child, per se, as the reason for increased stress or depression. Rather, it is societal expectations and the exceptional life situation that can lead to these experiences. Much research has focused on negative outcomes such as parental stress and depression in parents (mostly mothers) of children with disabilities. In a meta-analysis, Singer (2006) found consistent evidence of a 10% increase in the prevalence of depression in mothers of children with ID compared to control mothers. The greater risk of depression has traditionally been attributed to the emotional burdens of having a child with ID, rather than on the burdens imposed by negative public attitudes toward disability and inadequate support for the expensive and time-consuming task of caring for a child with special needs (Green, 2007). Even though there is an increased risk for a lower level of well-being, most parents adapt well to the challenge of raising a child with ID (Emerson, Hatton, Llewllyn, & Graham, 2006; Olsson & Hwang, in press; Hassall & Rose, 2005). A child with ID does not inevitably cause stress and depression in parents; the individual variation in parental well-being is great and depends upon a number of factors. Rather than focusing on the depressed or the competent parent it is important to learn more about the processes leading to different outcomes. Several researchers in the field of parenting a child with disabilities have asked for a greater focus on the positive aspects of caring for a child with ID (Hassall & Rose, 2005; Ylve´n, Bjro¨ck-A˚kesson, & Grandlund, 2006). Positive psychology is a fairly new trend in psychology (Gillham, 2000; Snyder & Lopez, 2002) and has influenced recent work in the study of parents of children with ID (Green, 2007; Scorgie & Sobsey, 2000;

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Stainton & Besser, 1998; Ylve´n et al., 2006). A greater focus on positive aspects of caring for a child with ID is, of course, welcome, but the positive and negative aspects and outcomes of caring for a child with ID should preferably be addressed simultaneously. Having a child with a disability involves both joy and challenges, both rewards and stress [as in any other parenthood (Deater-Deckard, & Scarr, 1996)] and no benefit can be gained from neglecting either the positive or the negative impact that the parenting experience can have on the well-being of parents. Individual variation in the experience of positive and negative aspects is evident as well as individual variation in outcome (e.g., well-being), but we know very little about the processes leading to these differences. It is clear that some people extract positive psychological growth from difficult life experiences, not as a result of magic but as a result of determination to cope with stress and adversity as well as possible (Lazarus, 2003). Why psychological growth and good adaptation takes place in some parents of children with ID while others are more troubled is a complex question. A relevant theoretical construct to understand individual differences in reaction to stressful life conditions is resilience. Resilience means that some individuals have a relatively good psychological outcome despite suffering risk experiences that might be expected to bring about poorer outcomes. Resilience is an interactive concept that refers to a relative resistance to environmental risk experiences, or the overcoming of stress or adversity. It differs from traditional concepts of risk and protection in its focus on individual variation in response to comparable experiences (Rutter, 2006). Risk and protection both start with a focus on variables, with the implicit assumption that the impact of risk and protective factors will be comparable in everyone, and that outcomes will depend on the mix and balance between risk and protective influences. Resilience, by contrast, starts with the recognition of the individual variation in people’s response to the same experiences. The two perspectives do, however, go together since there is evidence that much of the variation in psychological outcomes can be accounted for by the summative effects of risk and protective factors. Resilience can only be studied if there is a thorough measurement of risk and protective factors. The aim of the present chapter is to discuss and organize results of a review of empirical research on parental adaptation to a child with ID within the theoretical framework of resilience and risk and protective factors. With increased knowledge about risk and protective factors in parents of children with ID, we can do more to minimize the risks and to strengthen the protective factors and thereby enhance the life situation of parents of children with ID and in the longer run even improve the well-being of the children themselves, whom we know are at markedly increased risk for poor psychological health (Emerson, 2003).

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2. Risk and Protective Factors in the Field of Families with a Child with ID Several theoretical models have been used in research to facilitate the understanding of how different factors contribute to parental adaptation in families with children with ID. However, the concept of resilience is seldom used. There is agreement that a child with ID results in heightened stress in parents (Beckman, 1991; Cameron, Dodson, & Day,1991; Dumas, Wolf, Fisman, & Culligan, 1991; Dyson, 1991, 1993; Innocenti, Huh, & Boyce, 1992; Most, Fidler, Laforce-Booth, & Kelly, 2006; Plant & Sanders, 2007; Reddon, McDonald, & Kysela, 1992; Singer, 2006), and I use this consistent finding as a starting point for viewing this group as being exposed to stress which can be expected to lead to an increase in adverse outcomes. I further use the consistent finding of individual differences in adaptation (usually measured as depression) as a sign of resilience in many parents. Researchers have found that stress scores do not reliably predict the outcome (depression) for an individual parent. There are no objective stressors that affect everybody the same way, and whether a stressor will cause a stress reaction in the person exposed to it depends on the interplay between the stressful stimulus condition and the vulnerability/resiliency of the individual (Lazarus, 1999). Wallander and Varni (1998) have formulated a model in which the risk and protective factors are specific to the life situation of parents of children with disease/disability. They proposed the following risk factors for parental adjustment to childhood chronic illness/disability: a. Disability (they call it disease) parameters (type of diagnosis, severity, and prognosis) and care strain (the burden associated with caring for the child and extensive or frustrating contact with professionals) b. Psychosocial stress (factors directly or indirectly related to the child’s disability socioeconomic stress, loss of career opportunity, daily life stressors) They also proposed the following resistance factors: c. Parental stress-processing abilities (i.e., coping strategies, cognitive appraisals, problem-solving ability) d. Intrapersonal factors (general cognitive and affective patterns of behavior, or personality, i.e., dispositional optimism, self-perception, hope) e. Socio-ecological factors (i.e., social support, good family relations, marital satisfaction, formal support, and aspects of the broader community)

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2.1. Critical evaluation of Wallander and Varni’s risk and resistance model I see at least four problems with Wallander and Varni’s model. The first problem concerns the appropriate placement of different factors. Wallander and Varni offer specification of risk and protective factors, but the research on families of children with ID arch over a larger area than defined in their model. Socioeconomic situation and demographic factors are, for example, hard to place in the model. The second difficulty has to do with discriminating between stress-processing abilities and intrapersonal factors, as those concepts are very closely linked. The third difficulty is that risk and protective factors are not easily separated, but are rather better understood as a continuum where high scores can mean protection and low scores risk. For example, SES may be a risk factor if the family does not have the tangible resources, but a resilience factor if the family is economically welloff, can buy good medical and support care, etc. Similarly, Wallander and Varni view intrapersonal factors as sources of resilience, but they can be risk factors as well. Personality is a good example of this, where dispositional optimism can be a protective factor, but neuroticism can mean risk. Rather than trying to classify entire concepts such as socioeconomic status SES or personality as either risk or protective factors, it is important to study the level at which something goes from being a risk to having protective functions. The fourth problem has to do with outcome. Wallander and Varni (1998) simply call the outcome adaptation, but do not discuss or specify what that could be. An individual’s resilience or adaptation can be assessed with regard to many different outcomes as long as these are related to whether the individual functions in an adaptive or expected way despite having been challenged by risk/stress.

2.2. Three broad areas of risk and protective factors in families of children with ID The literature on parents of children with ID arches over many aspects and is not easy to summarize into risk and protective factors. On the basis of the model of Wallander and Varni and my objections to it, I suggest that risk and protective factors for parental adaptation to a child with ID can be categorized in three broad areas (child and disability related issues, intrapersonal, and socio-ecological as depicted in Fig. 8.1), with further subcategories. I have organized the findings from the literature review in this chapter into a section on studied risk factors within each of the broad areas and a section on studied protective factors within each of the broad areas.

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Child and disability related issues

Intrapersonal factors

Outcome

Socioecological factors

Figure 8.1 Risk and protective factors affecting parental outcome to a child with intellectual disabilities, categorized in three broad areas.

3. Risk Factors 3.1. Child and disability risk factors 3.1.1. Child behaviors Children’s behavior problems influence parental stress levels more than children’s level of cognitive functioning or extent of physical disability (Baker et al., 2003; Blacher & McIntyre, 2006; Emerson, 2003; Eisenhower, Baker, & Blacher, 2005; Hastings, 2003; Herring et al., 2006; Lecavalier, Leone, & Wiltz, 2006; Lewis et al., 2006; Saloviita, Ita¨linna, & Leinonen, 2003). Communication difficulties, impaired social ability, difficult temperament, repetitive behavior, demanding patterns of behavior, and clinging are all child characteristics that have been found to increase parental stress (Hassall, Rose, & McDonald, 2005; Hodapp, Dykens, & Masino, 1997; Most et al., 2006; Plant & Sanders, 2007; Wheeler, Hatton, Reichardt, & Bailey, 2007). These are also symptoms found in most children with autism, which can explain why some studies investigating the impact of different diagnoses on stress levels have found that parents of children with autism experience more stress than parents of children with mental retardation without autism (Blacher & McIntyre, 2006; Dale, Jahoda, & Knott, 2006; Eisenhower et al., 2005; Sanders & Morgan, 1997; Siklos & Kerns, 2007). Maladaptive child behavior and parenting stress have been found to have mutually escalating effects on each other (Baker et al., 2003). Children’s behavior problems lead to stress in parents, and parents under stress adopt certain parenting behaviors that tend to reinforce the child’s behavior problems (Hastings, 2003; Wheeler et al., 2007). The parenting environment interacts with the characteristics of the child (in this case, child problem behavior) and the child’s behaviors

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have critical impact on the parenting environment. It has also been found that parenting behaviors have a greater impact on children at developmental risk (Paczkowski & Baker, 2007), so that when mothers of children with ID are high in nonsupportive reactions their children have much higher levels of problem behavior than those in a nondelayed group (Paczkowski & Baker, 2007). 3.1.2. Different diagnoses Both fathers and mothers rate their children with Down syndrome (DS), as compared to those with other types of ID, as having more positive personality traits and fewer maladaptive behaviors (Ricci & Hodapp, 2003). Families of children with DS consistently appear to cope better than families with children with other diagnoses (Dykens & Hodapp, 2001) at least when the child is young (Most et al., 2006). This DS advantage, although not demonstrated in all samples (Cahill & Glidden, 1996; Glidden & Cahill 1998), is usually explained by DS being the most common chromosomal cause of mental retardation that is diagnosed at birth; it is a reasonably wellknown condition, with networks of parent-groups quite prevalent. Further, children with DS are often perceived to have easy temperaments and agreeable personalities and are sometimes reported as easier to bring up than are children with other ID (Dykens & Hodapp, 2001). Other explanations for the DS advantage involve older mothers being more mature and experienced and children with DS exhibiting higher levels of adaptive behavior than children with other ID etiologies (Corrice & Glidden, 2008). Different diagnoses may involve changes in the nature of the stress variable which, in turn, can influence the appraisal of stress. Lazarus suggests that familiarity, predictability, and clarity favor challenge, and unfamiliarity and long duration favor threat. This may help to understand why parents of children with DS are often found to experience less distress than parents of children with autism. DS is a well-known condition to most people, the cause is known, there is much information on prognosis, and homogenous parent support groups are available. Time of diagnosis and the diagnostic procedure also seem important for parental stress, where a lengthy period with uncertainty and a delayed diagnosis seem to make parents more stressed (Graungaard & Skov, 2006). Parents of children with autism have been found to experience higher levels of stress and depression than parents of children with other diagnoses (Blacher & McIntyre, 2006; Dale et al., 2006; Eisenhower et al., 2005; Sanders & Morgan, 1997; Siklos & Kerns, 2007; Olsson & Hwang, 2001). 3.1.3. Objectively and subjectively measured burden Objective measures of caring demands and impairment severity (e.g., test results and clinical judgments) are typically not related to parents’ experience of stress (Hassall et al., 2005; Lecavalier et al., 2006; Luescher, Dede,

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Gitten, Fennell, & Maria, 1999; Noojin & Wallander, 1997). In contrast, parents’ own subjective estimates of the impact of the child’s disability on daily life are typically related to parental stress and adaptation (Beckman, 1991; Fisman, Wolf, & Noh, 1989; Plant & Sanders, 2007; Wallander & Venters, 1995). The more negative impact the child’s disability is perceived to have in their life, the more stress is likely to be felt by the parents. This supports the relational stress-processing model of Lazarus (Lazarus, 1999, 2000; Lazarus & Folkman, 1984). They propose that there are no objective stressors, only potential stressors and the potential stressors are mediated through an appraisal process. Appraisal connotes an evaluation of the personal significance of what is happening. If we make the appraisal that what is occurring is a condition of stress, we define the situation as constituting harm/loss, threat, or challenge. In support of this, Plant and Sanders (2007) and Hassall et al. (2005) showed that psychological variables such as parental locus of control, parenting satisfaction, and parental cognitive appraisal of caregiving responsibilities had mediating effects on the relation between child’s level of disability and parenting stress. 3.1.4. Daily hassles, time demands, and disruption of daily life Time is described as the factor most affected by caring for a child with ID. Time restrictions and the disruption of daily life are more frequent in parents of children with ID than in control families (Bristol, Gallagher, & Scholper, 1988; Carpiniello, Piras, Pariante, & Carta, 1995; Green, 2007; Gustavsson, 1989; Herman & Thompson, 1995; Sloper, 1999), and are related to adjustment problems in parents (Harris & McHale, 1989). Families with children with ID devote more time to childcare and spend less time in social activities and enjoy less active free time than parents of developmentally typical children (Barnett & Boyce, 1995; Green, 2007; Mactavish & Schleien, 2004; Sanders & Morgan, 1997). Parents also have much more contact with professionals and contrary to the intention, contact with professionals is often perceived as an additional source of stress if it is extensive or frustrating (Olsson & Hwang, 2003). 3.1.5. Restrictions in life due to care demands As a result of the demands of caring, mothers of children with ID often report role restriction and limitations in pursuing a career (Barnett & Boyce, 1995; Gustavsson, 1989; Herman & Thompson, 1995; Olsson & Hwang, 2003, 2006; Reddon et al., 1992; Wallander & Venters, 1995). The more restricted the mother feels, the more likely she is to experience motherhood as frustrating, unhappy, and wearing (Breslau, Staruch, & Mortimer, 1982). One major obstacle for mothers’ employment is the difficulty in finding suitable daycare for their child with ID (Shearn & Todd, 2000) and reoccurring ill health and appointments. Hedov, Wikblad, and Annere´n (2006) found that mothers of children with DS stayed home to care for their child

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because of illness three times more often than control parents did for their nondisabled children. 3.1.6. Difference in care strain in mothers and fathers Many studies of parents of children with ID have been conducted with mothers as sole informants, but among those involving both mothers and fathers, the results are mixed. Some report that mothers and fathers experience the same amount of stress as a result of bringing up a child with disabilities (Dyson, 1997; Fisman et al., 1989; Hadadian, 1994; Hastings, 2003; Reddon et al., 1992; Wyngaarden Krauss, 1993), while some find that mothers experience more stress than fathers (Dumas et al., 1991; Gustavsson, 1989). A reduced level of responsibility has usually explained the lower stress levels in fathers. Compared to mothers, fathers are also typically less restricted by having a child with disabilities, and more often continue their involvement in professional life (Bristol et al., 1988; Gustavsson, 1989; Heller, Hsiesh &Rowitz, 1997; Olsson & Hwang, 2006).

3.2. Socio-ecological risk factors 3.2.1. Family functioning Poorer family functioning has been found to be associated with higher levels of stress in families with children with disabilities (Dyson, 1997; Sanders & Morgan, 1997; Wyngaarden Krauss, 1993). Some studies have found parents of children with disabilities to be at risk for marital and family conflict (Bristol et al., 1988; Fisman et al., 1989), while others do not (Dyson, 1991; Reddon et al., 1992; Sanders & Morgan, 1997; Van Riper, Ryff, & Pridham, 1992). In a meta-analytic review, Risdal and Singer (2004) concluded that there was an increase in divorce of about 6% in families of children with ID. Research in typical populations has found that when experiences of parenthood were not as positive as expected, there was a decline in marital satisfaction (Harwood, McLean, & Durkin, 2007). One hypothesis about the rather small increase in divorce rate for parents of children with ID is that for some parents, with weaker relations before the birth of the child with disability, the extra burden of a child with disability is an additional risk factor that further increases stress and marital tension and may lead to divorce. For other parents, with good relations before the birth of the child, the support the partners can give one another can serve as a protective factor that can actually bring the couple closer together. 3.2.2. Social support Receiving unsatisfactory social support is strongly associated with difficulties in family functioning and parental mental health (Gowen, JohnsonMartin, Goldman, & Appelbaum, 1989; Gray & Holden, 1992; Reddon

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et al., 1992). Parents of children with ID have been found to have more limited social networks then parents of typically developing children. They have more contact with family members and less contact with friends than parents of developmentally typical children (Herman & Thompson, 1995). Help from grandparents for informal childcare is valued and often necessary for mothers to be engaged in paid work outside the home (Mitchell, 2007). Participation in social and leisure activities is often restricted in parents of children with ID, in part due to lack of time and energy and accessibility (Mactavish & Schleien, 2004; Olsson & Hwang, 2003). 3.2.3. Socioeconomic situation Poverty and single parenthood (Beckman, 1983; Olsson & Hwang, 2001) have been found to constitute risk factors for parental well-being. Financial difficulty is sometimes caused by the additional costs of caring for a disabled child in combination with decreased possibilities for both parents to take part in paid work (Beresford, 1996; Emerson, 2003; Harris & McHale, 1989; Herman & Thompson, 1995; Sloper, 1999). Several studies have found poverty and parental unemployment to be related to stress in parents of children with ID (Birenbaum, 2002; Ellis, Luiselli, & Amerault, 2002; Emerson et al., 2006; Eisenhower & Blacher, 2006). Emerson et al. (2006) argued that the increased risk for poorer well-being among parents of children with ID could be attributed to their increased risk of exposure to poorer socioeconomic circumstances, such as poverty and poor housing quality. They suggested that failure to address socioeconomic position is likely to reinforce an overly pathological orientation in which children with ID are assumed to be a ‘‘burden’’ and in themselves a cause of maternal distress when it is actually the social circumstances that constitute the risk. 3.2.4. Formal support Many families perceive that they do not receive the service and support to which they are entitled. The advocacy activities, including negotiations and paperwork necessary to provide children with the services needed, can be an additional draw on parental energy and time (Green, 2007; Olsson & Hwang, 2003). Areas of need that are often reported by parents as being unmet are as follows: information and advice about services, the child’s diagnosis and prognosis, how to help the child, financial and material support with housing and transportation, family support and practical help with respite care (Baxter, Cummins, & Polak, 1995; Douma, Dekker, & Koot, 2006; Herman & Thompson 1995; La¨rka Paulin, Berneha¨ll Claesson, & Brodin, 2001; Olauson & Hvalstedt, 2001; Sloper, 1999; Stallard & Lenton, 1992; Summers et al., 2007). Research suggests that there exist inequalities in the extent to which people with disabilities and their families get access to benefits and support. Robertson et al. (2007) found that those with mental health, emotional or behavior problems, autism or multiple

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health problems were less likely to receive a person-centered plan, and they were also less likely to benefit if they received a plan.

3.3. Intrapersonal risk factors Lazarus (1999) suggested that the experience of stress can create a negative stress reaction, but only if the person does not have the possibility to cope successfully with the stress. The experience and consequences of stress are therefore dependent on the interplay of the environment (the potential stressors present) and the resources available to the individual to cope with the stressor. Parents of children with ID with high neuroticism have been found to use more of the coping strategies of escape-avoidance and accepting responsibility (which has a self-blame component). Both of these strategies are strongly related to poorer well-being (Glidden, Billings, & Jobe, 2006). Mothers who report high levels of stress often describe a tendency to avoid problems and feel out of control of their emotions. Possibly as a consequence of their higher levels of overall negative affectivity, these mothers tend to select strategies focusing on the regulation of emotions rather than on active problem solving (Noojin & Wallander, 1997). Passive, emotion-focused coping, such as wishful thinking, selfblame, distancing, and self-control, have been found to have a negative relation to adaptation (Dykens & Hodapp, 2001; Noojin & Wallander, 1997; Sloper & Turner, 1993).

3.4. Summary: Risk factors Several risk factors for parental adaptation to a child with ID have been studied but often in isolation; that is, studies have looked at the impact of one or two of the risk factors on adaptation. With the exception of child behavior problems and poverty the relation between the proposed risk factors and parental adaptation is not very strong. Because risk factors tend to cluster in the same individuals (Sameroff & Rosenblum, 2006), focusing on a single risk factor or challenge does not address the reality of most people’s lives. One way of improving predictive power could be to count the number or assess the cumulative effect of risk factors in an individual’s life in relation to adaptation (Sameroff & Rosenblum, 2006). It is then important to consider not only risk factors associated with the disability but also other general risk factors such as socioeconomic circumstances and major life events or parental adaptation. The length of time that individuals have been exposed to a risk is also important since stress initiates a series of biological and psychological processes called allostatic load. Allostatic load, or the cost of wear and tear on the body produced by repeated activation of biological stress response systems, contributes to physical disease and emotional and behavioral

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disorder (Sameroff & Rosenblum, 2006). For this reason, it is important to measure not only the exposure to possible risk factors but also the duration under which parents have been experiencing them. Therefore, child age and time since diagnosis may be important for the understanding of risk factors over time. Stress sets in motion complex biological processes that form the basis for adaptation and survival in the face of challenge. The human stress response shows high levels of specificity in reactivity to and recovery from stress. To determine the role of stress in processes of resilience (and vulnerability), careful attention must be given also to the type of stress that an individual encounters (Sameroff & Rosenblum, 2006). We need more careful work to differentiate, define, and operationalize the different risk factors that are common and salient in the lives of parents with children with ID. It may, for example, be that stressors related to the relationship with the child (such as behavior problems) have more adverse effect on parental health than time demands and daily hassles because they threaten more salient processes.

4. Protective Factors 4.1. Child and disability protective factors Beresford (1996) found that the positive aspects of caring for a child with disabilities involved the feelings of rewards and pleasures of parenthood, as well as a sense of moral responsibility. Parents who enjoyed their role and found it a satisfying experience viewed caring for their child as a challenge, something they enjoyed responding to. This strong feeling of meaningfulness is probably extremely positive for both the parents’ and the children’s wellbeing. There is anecdotal evidence that the emotional bond between the parent and the child with ID is the strongest protective factor of all, and supporting moments of joyful interaction between the parent and the child is probably a powerful way of supporting well-being in both parents and children (Beresford, 1996). Beck, Hastings, and Daley (2004) found that child pro-social behavior independent of behavior problems predicted maternal health, indicating the possible buffering effect of moments of joy and connection. Most parents are able to develop a secure and rewarding relationship with their child, even when the child has extreme social atypical behaviors as is the case with some children with autism (Biringen, Fidler, Barrett, & Kubicek, 2005) but the risk of an insecure attachment increases with degree of intellectual disability and severity of autistic symptoms.

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4.2. Socio-ecological protective factors An essential question related to adversity and resilience is the individual’s development of an effective set of responses to stress. Central components of the stress response include the initial appraisal of the event and its emotional meaning, the ability to sufficiently regulate one’s emotions and arousal to initiate problem solving and gather more information, the fuller cognitiveaffective interpretations of the event, and one’s behavioral response (Greenberg, 2006). Masten and Obradovic (2006) have noted that among the most important resilience factors are these very cognitive and emotion regulation skills. 4.2.1. Coping Upon exposure to stress, complex cognitive, behavioral, emotional, and biological processes are set in motion that serve the purpose of adaptation through either avoiding/withdrawing from the source of stress, acting on the source of stress to reduce its effects, or adjusting to the source of stress when neither escape nor confrontations are possible (Compas, 2006). Two fundamental processes are involved in self-regulation in response to stress. First, there is a set of automatic processes that are activated in response to stress that are related to but distinct from coping. Second, individuals initiate a set of controlled, volitional responses to stress. It is these voluntary responses to stress that are included in the concept of coping. Compas defined coping as a ‘‘conscious volitional effort to regulate emotion, cognition, behavior, physiology, and the environment in response to stressful events or circumstances.’’ These regulatory processes both draw on and are constrained by the biological, cognitive, social, and emotional development of the individual. According to Compas, coping includes three primary subtypes: primary control coping (problem solving, emotional expression, emotional modulation); secondary control coping, or efforts to adapt to the source of stress (acceptance, distraction, cognitive restructuring, positive thinking); and disengagement coping, or efforts to withdraw from the source of stress and one’s emotions (avoidance, denial, wishful thinking). Effective coping depends on being flexible (Lazarus, 1999). The best coping should be responsive to the requirements of the stressful situation. Some coping strategies are tied to personality variables, whereas others are tied to the social context. Certain coping strategies show significant within-subject consistency from encounter to encounter. For example, if positive reappraisal were employed by a person in one encounter, it is likely that the person would use it again in another encounter. However, other coping strategies, such as seeking social support, are used very inconsistently across different encounters. When conditions of stress are appraised as changeable—that is when they are viewed as falling within the person’s control—problem-focused coping

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predominates. However, when the conditions are appraised as unchangeable, emotion-focused coping predominates (Lazarus, 1999). 4.2.2. Coping in parents of children with ID The majority of parents with children with ID employ a variety of coping behaviors in their efforts to deal with the demands facing them (Beresford, 1996; Reddon et al., 1992) and a larger repertoire and more use of coping is related to more positive adaptation (Taanila, Syrja¨la¨, Kokkonen, & Ja¨rvelin, 2002). The use of active or problem-focused coping strategies which emphasize efforts to seek social support, actively solve the problem, and maintain a positive outlook on life, appear to be recorded more frequently and to have a favorable effect on parental well-being (Dykens & Hodapp, 2001; Glidden et al., 2006; Judge, 1998, Kim, Greenberg, Seltzer, & Krauss, 2003; Luescher et al., 1999). Parents of children with ID are often reported to use denial and wishful thinking and this has usually been considered a negative coping strategy. But since the disability is an unchangeable condition, emotion-focused coping is theoretically likely to occur regularly. 4.2.3. Personality The stress-processing abilities (coping) described above have been shown to be linked to personality factors which, in turn, have been shown to be strongly related to levels of well-being in parents of children with ID (Glidden & Schoolcraft, 2003; Baker, Blacher, & Olsson, 2005; Glidden et al., 2006; Hastings, 2002; Hassall & Rose, 2005; Oelofsen & Richardson, 2006; Olsson & Hwang, 2002; Ylve´n et al., 2006). The route from personality to well-being is thought to advance via the process of appraisal and coping. Parents with more optimistic outlooks, higher sense of coherence (SOC), more internal locus of control, and lower neuroticism may appraise a potential stressor as a challenge instead of a threat (or reappraise the situation all together), have more confidence in their ability to alter the source of stress and therefore use more active coping strategies (problem solving and social support). Noojin and Wallander (1997) found confidence in problemsolving ability to increase the likelihood of selecting more active strategies when faced with disability-related stress. Mothers who perceived themselves as effective problem solvers generally reported less distress. Mothers who reported better psychological adjustment described themselves as having high levels of confidence in their problem-solving abilities. The definition of personality is that it is a global and rather stable characteristic of the individual, whereas coping strategies, although linked to personality, are more variable across situations.

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4.2.4. Positive view of life and self Research has indicated that despite the increased demands of parenting a child with a disability, many parents are able to report positive changes in themselves, their family or their lives because of the child with disabilities (Erwin & Soodak, 1995; Scorgie & Sobsey, 2000; Stainton & Besser, 1998). Some of the findings from parents who adapt and cope effectively suggest that positive reframing of thoughts and attitudes about their circumstances is important for adaptive parental coping (Hastings & Taunt, 2002). Personality factors influence this appraisal process. It has been shown that hardiness (Weiss, 2002), parental self-efficacy (Hastings & Brown, 2002), and parental SOC about their lives (Hedov, Anneren & Wikblad, 2002; Olsson & Hwang, 2002) are associated with fewer parental mental health problems in parents of children with ID. Parents who manage their lives effectively seem to show evidence of such personal traits as patience, flexibility, hopefulness, positive outlook, determination, and good problem solving skills (Beresford, 1994; Kwai-sang Yau & Li-Tsang, 1999; Noojin & Wallander, 1997; Tunali & Power, 1993). 4.2.5. Sense of coherence There has been an increased interest in positive outcomes in parents and factors that contribute to ‘‘bonadaptation’’ (Erwin & Soodak, 1995; Scorgie & Sobsey, 2000). The salutogenic perspective of Antonovsky (1987) combines the interest of personality with the interest of positive adaptation. Antonovsky’s theory of SOC was developed to understand what makes people manage their lives despite high levels of stress, very similar to the concept of resilience but with a strong focus on intrapersonal protective factors. I will discuss the concept of SOC at some length as it is highly relevant to resilience. Antonovsky suggested that resistance resources all have one thing in common: They contribute to make stressors understandable. The cumulative experience of stressors as understandable will, with time, create a strong SOC defined as ‘‘a global orientation that expresses the extent to which one has a pervasive, enduring though dynamic feeling of confidence that (1) the stimuli deriving from one’s internal and external environments in the course of living are structured, predictable, and explicable; (2) the resources are available to meet the demands posed by these stimuli; and (3) these demands are challenges, worthy of investment and engagement’’ (Antonovsky, 1987 ). The strength in people with a high SOC is not that they are especially successful in using one or the other kind of coping strategy, but that they approach the world with the generalized expectation that stressors are meaningful and comprehensible. Instead of rigidly relying on one coping strategy, people with a strong SOC are characterized by flexibility. High SOC has been shown to be related to high well-being in both mothers and fathers of children with ID (Olsson & Hwang, 2002;

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Oelofsen & Richardson, 2006). But parents of children with ID have also been shown to have lower SOC than control parents (Olsson & Hwang; Oelofsen & Richardsson) with mothers having lower SOC than fathers. A strong relation between SOC and health has been reported in many different areas, and one study found that parents of children with ID with higher SOC levels had fewer registered days of sickness absence (Hedov et al., 2006). The first of the three central components of SOC, comprehensibility, refers to an experience of the confronted stimuli as making cognitive sense, as information that is ordered, consistent, structured, and clear, rather than chaotic, disordered, random, or accidental (Antonovsky, 1987). The fact that insufficient information about services, the child’s conditions and prognosis are some of the most common unmet needs mentioned by parents of children with ID (Granlund, Roll-Pettersson, Steensson, & Sundin, 1994; Sloper, 1999), suggests that the feeling of comprehensibility is perceived as essential but often threatened in these parents. The theory can also help understand the result by Green (2004) who found that mothers with a high internal locus of control who also believed in chance reported less stress. In contrast, belief in chance without a strong internal locus of control related to increased subjective burden, as mothers may feel overwhelmed by the uncontrollable nature of life events. The positive results of psychoeducational interventions also suggest that increasing the mother’s knowledge about her child’s condition and strategies to handle difficult behavior can increase feelings of comprehensibility (Bristol et al., 1993; McIntyre, in press). Advice on how to handle difficult child behavior is probably also related to the second central concept of SOC namely, manageability. Manageability is the experience that one is in possession of resources adequate to meet the demands posed by the stimuli, the resources may be under one’s own control or controlled by others whom one feels one can count on. The support offered to parents in the above-mentioned studies helped parents to decrease difficult child behavior, probably with an increased sense of manageability as a consequence. The cognitive strategies described by parents who maintained a positive outlook on life, in a study by Beresford (1996), were clearly directed at increasing their feeling of manageability. These parents took one day at a time, did not dwell on difficulties, hoped for improvement and compared themselves to others worse off. Glidden and collaborators have demonstrated that the depression trajectories for mothers rearing children with ID were quite different depending on whether the child had been born into the family or had been knowingly adopted by it (Flaherty & Glidden, 2000). If the parents had knowingly adopted a child with disabilities they probably believed in their ability to manage the situation, and they also showed lower levels of depression initially. The feeling of mastery seems to be important for the feeling of manageability. In a study by Grant (1998), parents noted that the

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moments they found to be most positive emerged as a result of developing strategies for coping with the challenge of raising their child. The third core concept of SOC, meaningfulness refers to an experience of shaping one’s destiny as well as one’s daily experience. This includes the extent to which one feels that life makes sense emotionally, that at least some of the problems and demands posed by living are worth an investment of energy. Not being able to pursue personal interests and goals in life may severely threaten the feeling of meaningfulness in life. Antonovsky proposes that the feeling of meaningfulness is the most central aspect of a strong SOC. The issue of meaningfulness can be illustrated by the study of Tunali and Power (1993), in which they found mothers’ abilities to redefine their goals in life to suit the actual circumstances and limitations of their daily lives had a strong relation to their well-being. If reaching one’s personal goals is prevented by the life situation, then either the situation itself or one’s goals must be changed to increase the feeling of meaningfulness. For many parents of children with ID, it is hard to change the life situation substantially enough to reach the personal ideals held before the birth of the child (Gustavsson, 1989). The ability to undertake, and support for, changing personal goals, is important for parents of children with ID, but may not be easy in an industrialized society where personal value is often based on achievement, career involvement, and an active leisure-time (Olsson & Hwang, 2006).

4.3. Intrapersonal protective factors 4.3.1. Social support Mothers of children with ID who experience support from their partner and from social networks experience less stress and depression (Gowen et al., 1989; Plant & Sanders, 2007; Reddon et al., 1992; Sharpley & Bitsika, 1997; Shin, 2002; Wallander & Venters, 1995; Weiss, 2002). Overall, parents seem to be quite content with the size, availability, and emotional support provided by their social networks (Baxter et al., 1995; Reddon et al., 1992). Many parents engage in parenting groups and parents report that quality of life can be enhanced through participation in social outlets that are accepting of the child’s disability (Mactavish & Schleien, 2004; Poston & Turnbull, 2004). 4.3.2. Formal support Some studies have demonstrated the positive impact of service supports on families (Cowen & Reed, 2002; Ellis et al., 2002; Romer & Richardson, 2002). In a Norwegian study, parents indicated that the formal support they received for themselves and their child was one of the most important factors for their coping with the situation (Kvande & Knutheim, 1995). Families appear to emphasize the interpersonal aspects of their relationships with providers as much as they emphasize the services themselves (Summers et al., 2007).

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When parents are asked about important factors for good support they place much emphasis on flexibility, individuality, and partnership. It is important for parents that service providers view every family as unique and consider and respect that which the parents think is best for their child (La¨rka Paulin et al., 2001). The more control families perceive themselves to have over the care and management of the services the more satisfied they are with the service (Blacher, Neece, & Paczkowski, 2005; Caldwell & Heller, 2003; Dunst & Dempsey, 2007; Nachshen & Minnes, 2005). Unfortunately, parents also indicate that they have to fight for the cooperation from, and control over, support services. Stronger and more persistent parents get more resources and more control (Knox, Parmenter, Atkinson, & Yazbeck, 2000; La¨rka Paulin et al., 2001), which may explain the positive effect of confrontive coping strategies (Glidden et al., 2006). The rates of satisfaction by parents can be increased with improved service. Parents have, for example, evaluated centers that have models based on partnership, with recognition of the complementary knowledge and expertise of parents and professionals, as being very helpful and supportive (Sloper, 1999). Even if the support system could never totally eliminate the extra care associated in caring for a child with ID, it can facilitate the family’s situation and increase the family’s ability to choose the best way for families to live life with their child with ID. Not all parents need or want the same kind of services. Therefore, support programs should preferably be flexible enough to offer support that matches families’ actual needs (Granlund et al., 1994). It is also important to acknowledge that the needs change over time. Todd and Sheam (1996) suggested that support services should have two phases. The first phase should involve support to parents through sharing the parental workload, such as respite care. The second phase should involve supporting the parent and his/her personal aspirations and interests. Families who have a coordinator who can provide an overview and coordinate the family’s different needs, report better relationships with professionals. Those who do not have a coordinator report significantly more unmet needs (Sloper, 1999). 4.3.3. Parenting support Support for families in the management of their children’s challenging behavior is imperative and should be provided before the behavior becomes so well established that intensive intervention from specialist service providers is required (Hudson et al., 2003; Soresi, Nota, & Ferrari, 2007). Parents who are helped to understand their children’s disability and to manage their child’s learning and behavior problems have been shown to have lower stress levels and better well-being (Hudson et al., 2003; Soresi et al., 2007). The weight of evidence suggests that cognitive behavioral treatment and interventions which bring parents together in groups with psychoeducational material reduce maternal distress (Singer, 2006). These interventions

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are designed to strengthen confidence in problem-solving, and directed at supporting adequate coping, and have been proven useful (Bristol et al., 1993; McIntyre & Phaneuf, 2008; Sloper, 1999). Apart from dealing explicitly with challenging behavior, families may need: (a) assistance with establishing structure in home routines; (b) assistance with dealing with stress; (c) aid with provision of respite care; and (d) assistance with engaging in advocacy (Soresi et al., 2007; Turnbull & Ruef, 1996; Williams & Wishart, 2003). Management strategies for children’s problem behavior may be affected by parents’ explanations of that behavior and their associated emotional reactions. If the children’s behavior is thought to be a consequence of the disability, then it may not be viewed as changeable. Consequently, interventions might aim to help parents generate alternative explanations for their child’s behavior, particularly to include consideration of environmental factors, and to enhance the emotional quality of parent– child relationships (Hassall & Rose, 2005). Hastings and Johnson (2001) showed that parents of children with autism reported lower levels of stress and pessimism when they had positive beliefs in the efficacy of an intensive behavioral intervention they were conducting. They, therefore, suggest that attention to parents’ efficacy beliefs about interventions is important if these interventions are to achieve their intended results.

4.4. Summary: Protective factors Personality factors, cognition, and coping are the concepts so far studied most in relation to positive adaptation. Positive child characteristics and the impact of positive parent–child relationships are understudied area. Most studies reviewed have used lack of negative outcome (e.g., no depressive symptoms or low stress) as measures of positive adaptation. The absence of depression is obviously not a measure of good adaptation and more studies using outcome measures with the possibility of detecting variation in the positive end of the adaptation continuum are needed. Without an outcome measure allowing for variation in the positive end, it is difficult to actually assess resilience or protection. An example from developmental psychology can serve to illustrate: In a study of children of mothers with major mental illness a positive link was found between maternal warmth and child competence (Luthar, Sawyer, & Brown, 2006). This might logically suggest that mothers’ warmth served as a protective factor. However, when the distributions of children’s scores were examined, that was not what was found. The children experiencing high maternal warmth had competence scores close to the national average; they did not show ‘‘superior’’ competence. In contrast, those experiencing low warmth had very low competence. In this case, therefore, high warmth was not particularly promotive—rather, low maternal warmth connoted significant vulnerability. Examining the

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distribution of scores vis-a`-vis norms can be critical in illuminating whether the construct connotes exceptional well-being at one end, or exceptional dysfunction at the other.

5. Outcomes Resilience is quintessentially inferential: Judging the resilience of a system requires criteria for identifying whether the system is doing whatever it is supposed to be doing (Masten & Obradovic, 2006). Important questions to ask in resilience research are as follows: Who decides or defines the criteria for judging good adaptation? Does resilience refer to positive internal adaptation, positive external adaptation, or both? In the literature on resilience in adults, the focus is usually on how the person herself feels. Prominent are indices such as subjective well-being, happiness, selfreported absence of distress, and so on. Few, if any, studies on resilience among adults have defined ‘‘doing well’’ in terms of others’ ratings of them, such as if they functioned as good spouses or parents (Luthar et al., 2006). In research on adaptation of families with children with ID the outcome variable most commonly discussed is parenting stress. From a resilience perspective, stress is not an outcome but a prerequisite for resilience. The second most frequently measured outcome is depression. Considering that there is agreement that a system has experienced serious risk (stress), positive mental health can be an accetable outcome measure of resilience. Depression, however, hardly meets this criterion, since there is no possibility of detecting any functioning better than no depression. Studies of family quality of life have a focus on positive functioning that fits well with the concept of resilience. Other adaptive adult behaviors such as positive parenting, participation in work and social life, and marital satisfaction should also be relevant as outcomes.

5.1. Depression in parents of children with ID Depression is a normal response to certain life situations. One life event that sometimes leads to parental depression is the diagnosis of a child with a disability. Initially, there appears to be a grief reaction that is often intense at the time of diagnosis. The feelings of grief initially described by parents are similar to those experienced in loss situations and can include shock, disbelief, and anger (Baxter et al., 1995; Cameron et al., 1991) but are not present in all parents. It was previously thought that parents went through sequential stages of sorrow after learning about their child’s diagnosis, finally reaching a stage of acceptance (Blacher, 1984; Shapiro, 1983). Recent research suggests, however, that feelings of grief, disbelief, and shock associated with the diagnosis may not be finally resolved by all parents,

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but may reoccur throughout the child’s and parent’s life (Baxter et al., 1995; Pianta, Marvin, Britner, & Borowitz, 1996). In addition, some parents experience mourning for the loss of the expected ‘‘perfect child’’; others experience feelings of guilt for not being a good-enough parent to the child and his/her siblings, anxiety over the child’s welfare and future, and/or sorrow over lost possibilities in the parent’s own personal life (Gustavsson, 1989; Harris & McHale, 1989). These emotions and concerns can be found to a greater or lesser degree in all parents. Depression experienced by birth parents is not trivial and may lead to lifelong consequences. For example, two studies have reported that 20% of parents decided not to raise their child with DS, but instead to relinquish the infant for adoption (Dumaret, De Vigan, Julian Reynier, Goujars, & Ayme´, 1998; Sadetzki et al., 2000). Although these studies did not specifically report parental depression scores, it is likely that parents who experience negative emotional reactions to their child’s diagnosis are more likely to make this decision (Glidden & Schoolcraft, 2003; Gustavsson, 1989). Most studies investigating the mental health of parents with children with disabilities have initially found higher scores for maternal depression compared to norms or to control groups (e.g., Blacher & Baker, 2002; Blacher & Lopez, 1997; Olsson & Hwang, 2001; Seltzer, Floyd, & Hindes, 2004; Singer, 2006; White & Hastings, 2004; Veisson, 1999). There are, however, some studies, mostly involving parents of children with DS, that have not found differences in depression scores (Glidden & Schoolcraft, 2003; Scott, Atkinson, Minton, & Bowman, 1997; Van Riper et al., 1992). Maternal reports of depression have usually been generalized to parental depression, and the very few studies which have included fathers have usually found normal depression scores or far fewer symptoms of depression in fathers of children with disabilities than in mothers (Dumas et al., 1991; Fisman et al., 1989; Gray & Holden, 1992; Olsson & Hwang, 2001, 2006; Veisson, 1999). Studies of parents with children with disabilities suggest that 30% of mothers with children with disabilities score above the cut-off for depression compared to 20% in large samples of women of child-bearing age (Olsson & Hwang, 2001; Singer, 2006; White & Hastings, 2004; Veisson, 1999). Since mothers of children with ID are at higher risk for depression, the existing social service system for children with ID should specifically target this problem (Singer, 2006).

5.2. Family quality of life Family quality of life has been proposed as an appropriate outcome for families of young children with disabilities. The construct implies a family’s (so far usually the mother’s) personal interpretation of well-being, life satisfaction, and interpersonal relationships (Summers et al., 2007). The few studies in the literature that have used family quality of life as an

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outcome have found high ratings, suggesting that 39% rate their quality of life as excellent. Almost 65% of parents rate their family quality of life as moderate to very good (Summers et al., 2007). These figures actually correspond to the studies using depression as the outcome, which usually find that 65% of parents do not report elevated levels of depression.

6. Discussion Several conclusions derive from this review. First, the good news is that it seems that studies using depression as well as studies using quality of life as outcomes agree that at least 65% of parents show resilience to being a parent of a child with ID, and 30% show adverse outcomes. Second, many different factors, concepts and measures are studied in the research on families of children with ID; and third, much of the research on parental adaptation to a child with ID lacks explicit conceptual definitions and theory. Without a theoretical framework, it will be difficult, if not impossible, to understand and empirically test the processes leading to individual differences in adaptation. It seems that some factors are studied over and over again (e.g., the impact of behavior problems, and the importance of marital support) without an explicit theoretical foundation but more as a result of positive findings and a match with hypotheses. But are there other important risk and resistance factors or processes leading to resilience that we are not studying? In a review of findings from resilience research primarily in developmental psychology, Rutter (2006) suggests that resistance may derive from several different sources. One of these could be controlled exposure to risk (rather than the total avoidance of risk). It seems as if the key element is some form of prior successful coping with a similar challenge. Is this process of resilience relevant in parents of children with ID? Perhaps having made a successful transition to parenthood before having a child with a disability could be related to resilience. Parents with a child with ID as a second or later child may be more resilient than first time parents with a child with ID. Relatedly, having previous exposure to disability such as the experience of a close relative, friend or neighbor experiencing disability could also be a resilience factor. Rutter (2006) further suggests that resistance may derive from traits or circumstances that are without major effects in the absence of the relevant risk or stress. The ability to be focused, organized, and able to work a way through the service system may be a skill that proves more useful to parents of children with ID than to their counterparts rearing typically developing children. Thus, it may be a protective factor and related to better adaptation in parents who need this skill than in those who do not.

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Resistance may also derive from physiological or psychological coping processes rather than external risk or protective factors. Research needs to move away from a focus on external risks to a focus on how these external risks are dealt with by the individual in the form of coping mechanisms, mental sets, and the operation of personal agency. Studies suggest that personal agency and a concern to overcome adversity, a self-reflective style and a commitment to relationships are important features in resilient people. Parents who report positive aspects of having a child with ID usually mention a positive focus on their close relationships and having met new and interesting people whom they would not have met without their child with ID. Delayed resilience may also occur, deriving from ‘‘turning point’’ experiences in life, sometimes long after the initial risk experience. Such transformational experiences have been described in the literature on parents of children with ID by Wilgosh and Scorgie (2006). As already mentioned, judging the resilience of a system requires criteria for identifying whether the system is doing whatever it is supposed to be doing. In research on resilience in parents and families, it is important to critically ask what a resilient outcome is. Good parental mental health and well-being might be a relevant measure of resilience, as can quality of life. Parenting behaviors, parent–child attachment, or parental involvement in different life spheres might be just as relevant as would be a combination of several of these. Studies on resilience beyond the traditional well-being paradigm are necessary. A resilience approach requires researchers to develop methods of assessment and analyses of competence, assets, resources, promotive, and protective factors, and the diagnosis of resilience in addition to depression, risk, vulnerability, and stressors.

6.1. Design improvements Several research designs and statistical methods have been used in resilience research in general (see Masten & Obradovic, 2006, for a review), but only a few have dominated in the field of families with children with ID. The following designs should be considered to improve research on resilience in parents of children with ID. Interaction findings (adversity a moderating variable) are by far the most commonly used ways of studying risk and protective factors in families of children with ID. Interaction findings highlight the striking exception of individuals with high adversity scores whose adaptive success appeared to be ‘‘off the gradient’’ (better than predicted by their level of risk). This method is, for example, used in a study by Baker et al. (2005) where it was found that maternal dispositional optimism moderated the relationship between child behavior problems and maternal depression. Interaction effects are conceptually very intriguing; in contrast, searching for them by using contrasting control groups can sometimes be counter productive

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(Luthar et al., 2006). There is a need for more within-group analyses with discrete groups of people at (the same level of ) risk. When researchers work with particular at-risk populations, they seek to illuminate what makes a difference for these people—not whether these factors also affect comparison groups (Luthar et al., 2006). Comparative approaches that document group differences need to be complemented by within-group analyses illuminating the particularly critical process for individuals from given subgroups. Classic studies of resilience often identified a large risk group (such as parents of children with ID) and then compared a subgroup of individuals doing well across multiple criteria of positive adaptation to another subgroup in the sample that shares similar high-risk levels but is doing poorly in multiple ways. Comparisons of this nature often find strong similarities in the high competence groups, despite divergent adversity exposure, and striking differences between the resilient and maladaptive groups, despite shared risks or adversity exposure. As levels of adversity increase, the differences in the resources of resilient versus maladaptive individuals can be even greater. There is also a notably ‘‘empty cell’’ effect in such studies, suggesting that cases of low risk and poor adaptation are much less common than cases of high-risk and good adaptation (Masten & Obradovic, 2006). There are different ways of analyzing the impact of individual or cumulative effect of risk factors (Klebanov & Brooks-Gunn, 2006). Samples can be divided based on single risk factors known to be a strong predictor of poor adaptation, such as poverty or child behavior problems. The effects of risk can then be considered separately for poor and more affluent families because of the greater risk experienced as a result of poverty. Otherwise, the effects of the studied risk factor may be obscured. Single case studies are seldom used but can serve as powerful heuristic and communication tools, illustrating dramatic turning points in a process when powerful risk factors are eliminated or protective factors are boosted as, for example, in interventions. If they are used sparingly and with full recognition of their limitations they can enrich the more usual quantitative approaches. Rutter (2007) argues that theory driven research is the key for beginning to address causality. Causal graphs spelling out the implications of the background knowledge or theory can lead to statistical modeling that can increase or decrease the likelihood of the causal inference being correct. Rutter (2007) also discusses the use of propensity scores to equate groups on the basis of likelihood of exposure to risk rather than controlling for differences in risk. Sensitivity analyses to quantify how strong a confounder would have to be to overturn a causal inference may also be very helpful. He further proposes the use of regression discontinuity as a quasiexperimental design that could be very useful for making causal inferences.

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6.2. Why study resilience? There is consensus that parents (or at least mothers) of children with ID constitute a risk group in terms of depression and poor well-being (Singer, 2006). At the same time, there is also consensus that the majority of parents are doing well. To understand the individual differences and the processes leading to these different outcomes, we need to better understand the factors associated with positive outcomes and resilience. This is also the route toward designing and studying the effect of interventions aimed at improving the lives of families of children with ID. With very few exceptions, there is no such thing as a single necessary and sufficient cause (Rutter, 2007). Even though mothers of children with ID are at higher risk for depression, the birth of a child with ID does not ‘‘cause’’ depression in mothers. It is not just that depression is only one of several possible outcomes for parents, but also that several different causal pathways may all lead to depression. Furthermore, almost all causal pathways involve several different phases. For example, the pathway to depression does not begin with a causal risk factor, but it must be preceded by the pathway leading to exposure to the risk factor. Thus, if the hypothesized cause is, say a child with ID in the family, the risk may lie in either genetic, societal influences or individual propensities or often a complex mixture of all. This complexity is further exacerbated because it is also the case that influences are often reciprocal, with the causal arrow running in both directions. Luthar et al. (2006) proposed four guidelines for the selection of risk and protective processes in future resilience research. First, given a particular atrisk condition (such as a child with ID), there must be concerted attention to factors that are salient in that particular life context, those that affect a relatively large number of people in that group (e.g., daily hassles, service provision, or child behavior problems). Second, we should prioritize attention to indices that are relatively malleable—risk modifiers amenable to change via external interventions or ‘‘modifiable modifiers’’ (e.g., child behavior problems may be modified by parenting practices). Third, focus should be afforded to indices that tend to be relatively enduring in the life situation (parenting practices). Finally, it is critical to attend to indices that are generative of other assets, those that set into motion ‘‘cascades’’ wherein they catalyze other protective processes (if behavior problems are prevented or minimized the child will have less negative impact on the family and all family members can have more possibilities of engaging in positive interactions and activities). Luthar et al. concluded that close supportive family relationships clearly meet all these four criteria, as do probably other aspects such as the formal support system in the lives of families of children with ID. The one-sided focus on maladjustment in literature on families of children with ID is addressed by Glidden (1993) in which she challenged

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the notion that families with a child with ID are always strained. She argued that the persistence of the maladjustment hypothesis has continued despite substantial methodological problems with the research on which the belief is based. Overall adjustment or maladjustment is dependent not only on the presence or absence of stress but also on the presence or absence of positive outcomes. Positive outcomes can coexist with negative outcomes but may never get measured because investigators are not hypothesizing that they are present. The discourse of disability as a tragedy has been reproduced by researchers by the focus on maladjustment. The resilience perspective offers a possibility of acknowledging the extra stress and strain in families of children with ID at the same time as it puts the focus on the factors that contribute to positive outcomes in a majority of the parents.

7. Conclusion In this chapter, I have proposed a theoretical model of resilience to help interpret past findings and guide future research on families of children with ID. Thus, far most family research has zoomed to a narrow focus on factors important to understand the 30% of mothers with depressive symptoms. I think we need to zoom out to see the bigger picture. Risk and protective factors should be addressed simultaneously with robust outcome measures that allow for variation in the negative as well as in the positive end of the well-being spectrum, in both parents. We need to do more within subgroup analyses on parents who are doing well and those doing less well. To do this, we need bigger samples. We also need to include fathers in research since there is consistent evidence that the experience and outcomes are sometimes different for mothers and fathers. Also essential is more research on the importance of positive relations between the child with ID and his or her parents, and intervention studies designed to strengthen this relationship.

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C H A P T E R

N I N E

‘‘What do you Think if . . .’’: Using Vignettes to Study Attitudes Toward Adult Sibling Caregiving and Competence of Parents of Children with Disabilities Brian M. Jobe* and Laraine M. Glidden† Contents 1. Introduction 2. Topic 1: Young Adults’ Levels of Caregiving for Hypothetical Siblings 2.1. Methodological considerations 2.2. Results and discussion 2.3. Follow-up research 3. Topic 2: Stereotypic Views of Parental Competence and Family Expansion 3.1. Methodological considerations 3.2. Results and discussion 4. Summary and General Discussion 4.1. Theoretical and applied value of the research 4.2. Didactic value of the research Appendix Acknowledgments References

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Abstract Providing research participants with hypothetical situations in a vignette format can be a useful methodology in many contexts, including those in which live situations are difficult to study and timelines for the conduct of the research are limited, as is frequently true when students are active research investigators. In the current chapter, we describe two programs of research using vignettes in situations involving individuals with intellectual/developmental disabilities

* {

University of Maryland, Baltimore County, Maryland 21250 St. Mary’s College of Maryland, Maryland 20686

International Review of Research in Mental Retardation, Volume 36 ISSN 0074-7750, DOI: 10.1016/S0074-7750(08)00009-8

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2008 Elsevier Inc. All rights reserved.

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(IDD): adult sibling caretaking of a brother or sister with a disability, and judged competence of parents raising children with disabilities and/or behavior problems. The uses and limitations of the vignette methodology are discussed in terms of its research and didactic utility.

1. Introduction Despite the desirability of measuring behavior directly, a variety of obstacles complicate doing so. Some topics are of a sensitive nature and respondents may feel pressured to react in a manner incongruent with their actual experiences and beliefs. This phenomenon of social desirability, not wanting to endorse that which is not typically endorsed or approved of by the general population, is one obstacle faced by researchers (Sudman & Bradburn, 1974) and thus, investigation of topics highly susceptible to social desirability may require alternative methods of inquiry that reduce the demand characteristics of the experimental or interview context. Another obstacle to direct measurement results from difficulties of access to appropriate samples to study certain phenomena. For example, in the disability field, family members of individuals with disabilities, especially individuals with low incidence disabilities, may be dispersed geographically, and access to them, even with the possibility of telephone, mail, and internet responding, is limited. Moreover, those who do respond may be unrepresentative of the larger population, thereby limiting the generalizability of obtained results. The difficulty posed by limited access is exacerbated for investigators with minimal resources and a short timeframe such as students, either undergraduate or graduate, who typically have to complete research within a semester or a year, as is the case for some courses or for thesis requirements. Increasingly, however, even undergraduate curricula in the sciences and social sciences emphasize and even require an empirical research experience, as this is a strong predictor of future graduate-level admission and eventual success as a scientist (Pate, 2001). To overcome the obstacles of social desirability and of access, investigators have developed study analogues that allow the measurement of constructs that may be susceptible to censored reporting or that represent situations and samples that are relatively unavailable. The use of vignettes in these circumstances is one alternative. Vignettes are hypothetical narrative situations that allow researchers to manipulate contextual variables experimentally (Finch, 1987). Written vignettes have been used in the past as convenient and ethical ways of exposing participants to situations that would otherwise be challenging to duplicate in reality (Sleed, Durrheim, Kriel, Solomon, & Baxter, 2002). Vignettes frequently deal

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with beliefs and attitudes rather than directly with behaviors and as such, ask and attempt to answer a different research question. The field of intellectual and developmental disabilities (IDD) is one in which vignettes have been used because of both sensitivity and relative inaccessibility of samples. Using vignettes to study attitudes about intellectual disabilities (ID) can avoid participants responding negatively about family members, friends or acquaintances who actually have ID. Moreover, although 1% of the population has ID (Fujiura & Yamaki, 1997), most of these have only mild impairments and may not be recognizable as intellectually disabled to the average person. Whereas respondents may have few personal interactions with persons with IDD, their attitudes toward this population can still be assessed by the use of vignettes that describe the population of interest. The vignette method of studying subject reactions to individuals with intellectual or other developmental disabilities has been used across a large age range, with samples of preschoolers (Diamond, 2002), elementary school age children (Bak & Siperstein, 1987; Diamond, 2002; Manetti, Schneider, & Siperstein, 2001; Spitzer & Cameron, 1995), and adolescents in high school (Karnilowicz, Sparrow, & Shinkfield, 1994). Adults have also been subjects (Marteau & Drake, 1982; Shinde & Symons, 2007; Staal & Norman, 2000). Not only is the age of samples diverse but also the constructs that have been measured. For example, Spitzer and Cameron (1995) investigated whether young children were able to distinguish between mental illness and intellectual disability and Siperstein and his colleagues have studied social acceptance of peers with and without disabilities (Bak & Siperstein, 1987; Manetti et al., 2001). Attitudes toward refusal of genetic detection of Down syndrome (Marteau & Drake, 1982), acceptance of the school practice of inclusion by parents (Staal & Norman, 2000), the ability of teachers to detect pain in children with developmental delay (Shinde & Symons, 2007), and care staff’s reaction to the challenging behaviors of person with ID (Bailey, Hare, Hatton, & Limb, 2006) are examples of the broad range of domains that have been studied. In the current chapter, we describe two programs of research, both involving vignettes. Topic 1, Young Adults’ Levels of Caregiving for Hypothetical Siblings, originated as the senior thesis of a team of undergraduate students, Kristin Coffey and Heather Wasson, and was completed in 2004. Their original method called for identifying and recruiting actual siblings of brothers and sisters, but after several months of recruiting with little success, they reconsidered their design. The use of vignettes in this study, therefore, was motivated primarily by the lack of accessibility to the original sample of interest. Topic 2, Stereotypic Views of Parental Competence and Family Expansion, was a project that also involved students but it originated with the authors of this chapter as an adjunct to longitudinal research that directly studied parenting of children with developmental

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disabilities (Glidden & Jobe, 2006; Glidden & Schoolcraft, 2003). The use of vignettes in Topic 2 was motivated both by the sensitivity of the subject matter (i.e., parenting competence) and by the difficulty of recruiting participants given available resources. In this chapter, we will describe these two programs of research, focusing on how their results have contributed to the understanding of attitudes toward individuals with IDD and their families. For each, we will focus on the findings, their value, and their limitations. One of our goals is to encourage the inclusion of undergraduates in the IDD research community, even as principal investigators as they were in Topic 1.

2. Topic 1: Young Adults’ Levels of Caregiving for Hypothetical Siblings Children with disabilities are often cared for by their parents, and, when present, siblings almost always offer some level of help to the parental caregivers. This sibling support could be either direct or indirect and passive or active (Szinovacz, 2008). To date, most investigators have focused on the experiences of young siblings as caregiving helpers (Midlarsky, Hannah, Shvil, & Johnson, 2008; Stoneman, 1998). Relatively little is known about what happens when the primary caregivers for the sibling with disabilities are no longer able to care for the child, although this issue has generated recent interest (Hodapp, Glidden, & Kaiser, 2005), catalyzed by the increased life expectancy of many persons with ID who are more likely to survive their parents than they were in earlier decades. Most adults with IDD in the United States live at home with their families of origin and more than 25% of these family caregivers are older than 60 years (Braddock, Hemp, & Rizzolo, 2008). This percentage is likely to increase in the next several decades, making the issue of sibling caretaking more paramount than it once was. During adulthood, sibling involvement tends to include regular contact and emotional support (Harland & Cuskelly, 2000). Seltzer, Greenberg, Orsmond, and Lounds (2005) reviewed their data on the life course of siblings of person with IDD, and found that at least weekly contact by visit or by phone was quite common, with 41% of the sample reporting in-person contact at least once a week. Nonetheless, a minority, only 19%, expected to actually live with the brother or sister with IDD when the parental home was no longer a residential option. In our own research (Glidden, Corrice, & Natcher, 2008), we found that among families who had children with disabilities who were transitioning into adulthood, 60% had not yet designated a caretaker to assume responsibilities following the relinquishment of caretaking duties by the parents. However, of the remaining 40% who had, a majority (73%) had

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named a sibling as the caretaker. The sibling was more often a female, and always older than the brother or sister with IDD. We did not, however, collect information on the details of this anticipated caretaking. Some designated caretakers might have total responsibility for both instrumental and affective support, whereas others might be minimally involved with only token guardianship tasks. Given the limited understanding of the process by which adult siblings assume the care of their brothers and sisters with disabilities, Coffey and Wasson hoped to learn more about this role, the transition into the role, and its impact on the nondisabled siblings. They initially designed an interview study of siblings who had already assumed primary caretaking roles, or were intending to do so after their parents were no longer able to maintain their caregiving responsibilities. However, unable to recruit more than a few participants, they adopted a different strategy and used vignettes in an experimental and quasi-experimental design.

2.1. Methodological considerations 2.1.1. Hypotheses and the development of vignettes Based on existing research findings or the lack of them, Coffey and Wasson manipulated three variables as part of the experimental treatment. The generic vignette was as follows: You have a younger [brother, sister] who lives in St. Mary’s City. You have always enjoyed spending time together; you talk to each other on the phone once a week and visit each other several times a month. You have just learned that your sibling has been involved in a devastating car accident that has caused severe physical and cognitive disabilities. Your [brother, sister] is no longer able to live independently and will need to be cared for. Your parents are in ill health and are unable to physically care for your [brother, sister]. Although there is community assistance available, some family help will be necessary.

After the presentation of this general vignette, the participants received additional vignette details involving employment status and sibling lifespan. The employment conditions were Current, whereby the accident had just taken place the previous day (i.e., still in college) and Future, whereby the accident happened 5 years after college graduation and the participant had a full time job (40 h per week). Participants also received two lifespan conditions: Short, the brother or sister was not expected to live more than 2 years and Nearly average, the brother or sister was expected to have a nearly average lifespan. The participants received either a brother or a sister vignette. We formulated hypotheses about each of these variables. Harland and Cuskelly (2000) had found that siblings increase contact and intimacy as they grow older, so we predicted our participants would report more

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caregiving in the Future condition than in the Current condition. Although no available research about caretaking led to a prediction about lifespan, help is more likely to occur when the cost to the helping individual is less (Lee & Murnighan, 2001). Thus, we expected that more help would be pledged in the Short than in the Nearly average lifespan condition. Finally, much of the research on caretaking has found that females are more likely to take on this role (Glidden et al., 2008; Seltzer, Begun, Seltzer, & Krauss, 1991) and that siblings were more likely to be helpful with a brother or sister of the same sex. Thus, we predicted that sex of caregiver would interact with sex of brother or sister with disability such that sister–sister dyads would be most involved. 2.1.2. Additional independent variables The remaining independent variables of interest were quasi-experimental and related to participant characteristics, all of which were measured by participant self-report. They included sibling sex, adult roles, attitudes toward persons with disabilities, self-esteem, and personality. Participants self-identified as male or female as well as for adult roles, indicating which activities they took part in from a list and how many hours per week they typically spent in those activities, for example, work, school, family, recreation, as well as how many hours per week were unscheduled. Based on the work of Greenberg, Seltzer, Orsmond, and Krauss (1999) and Horwitz, Tessler, Fisher, and Gamache (1992), we predicted that as time allotment to adult roles increased, involvement in sibling caretaking would decrease. Participants’ attitudes toward people with disabilities were measured using Antonak’s (Antonak & Livneh, 1988) Scale of Attitudes toward Disabled Persons (SADP). This scale consists of 24 stereotyped statements about people with disabilities; 12 are worded positively (e.g., ‘‘People with disabilities are not more accident prone than other people’’) and 12 are worded negatively (e.g., ‘‘Children with disabilities should not be provided with a free public education’’). The participants rated how they felt about each statement on a 6-point scale that ranged from verbal anchors of ‘‘I disagree very much’’ to ‘‘I agree very much.’’ Scores could have ranged from 0 to 144 with higher scores indicating positive attitudes. We predicted that participants with more negative attitudes would be less likely to involve themselves in caretaking activities. 2.1.2.1. Self-esteem and personality Participants’ self-esteem was measured using the Rosenberg Self-esteem scale (RSE; Rosenberg, 1979), a 10-item Guttman scale consisting of 5 positively worded items (e.g., ‘‘On the whole, I am satisfied with myself ’’) and 5 negatively worded items (e.g., ‘‘At times I think I am no good’’), rated on a 4-point scale. Participants also self-reported personality characteristics using the NEO Five Factor Inventory (Costa & McCrae, 1992), which consists of 60 multiple-choice items

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divided into one of five dimensions or personality traits: neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. We predicted a positive correlation between self-esteem and caregiving involvement based on the findings of Burton and Parks (1994). With regard to personality, we predicted that agreeableness and conscientiousness would be positively related to involvement in caretaking and that neuroticism would be negatively related. We had no predictions for the personality factors of openness or extraversion. 2.1.3. Dependent variables 2.1.3.1. Levels of sibling caregiving involvement We combined items measuring activities of daily living from the Functional Independence Measure (FIM; Cotter, Burgio, Stevens, Roth, & Gitlin, 2002) and the Amount of Care scale, a modified version of Tessler, Fisher, and Gamache’s (1992) Care Scale. A factor analysis of responses to 10 items indicated a twofactor structure, each with 5 items. One factor included caregiving tasks such as toileting and bathing that required physical contact or proximity for helping. The other factor included caregiving tasks such as financial management and transportation that could be completed without physical closeness. These two factors were treated as separate dependent variables—proximal caregiving and distal caregiving. Participants rated their willingness/ability to aid their sibling with each activity on a five-point scale. They also indicated for how long they could provide assistance from none to as long as needed. The scores on the involvement and duration sections were multiplied for each item to yield composite item scores. 2.1.3.2. Participants Participants were 100 undergraduate students enrolled in Introduction to Psychology who participated in this study for class credit. The sample was 74% female, ranged in age from 17 to 23 years (M ¼ 18.20), and were mostly first-year students. The sample was somewhat ethnically and racially diverse with 22% reporting an ethnic/racial identity other than Anglo-European/Caucasian. Of the participants, 91% had at least one sibling and 6.4% of the participants with siblings (7% of all participants) had siblings with physical or cognitive disabilities.

2.2. Results and discussion Table 9.1 presents the means for both proximal and distal caregiving for Current and Future conditions and for the Short and Average lifespan conditions. Across all conditions, participants reported significantly higher caregiving scores for distal than for proximal tasks. For proximal caregiving, participants reported that they would provide higher levels of caregiving when the sibling would live for no more than 2 years than when a sibling

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Table 9.1 Self proximal and distal caregiving ratings for time (current/future) and lifespan (short/average) conditions Proximal caregiving

Distal caregiving

Experimental condition

Mean

S.D.

Mean

S.D.

Current, short lifespan Current, average lifespan Future, short lifespan Future, average lifespan

15.39 12.30 15.55 12.47

6.47 5.81 6.08 5.81

17.74 15.46 18.15 15.55

6.46 5.85 5.14 5.82

Note: Caregiving is assessed on a 10-item measure, with involvement and duration components multiplied together to get a composite score, ranging from 0 to 25.

had a nearly average lifespan. Also, females reported higher levels of proximal caregiving than males. A similar result was found with distal caregiving, whereby participants reported that they would provide higher levels of caregiving when the sibling would live for no more than 2 years than when a sibling had a nearly average lifespan. Also, as with proximal caregiving, females scored marginally higher than males on distal caregiving. For both proximal and distal caregiving, brothers and sisters were cared for equally and the sex of brother or sister did not interact with participant sex. Also, none of the psychological characteristics of attitudes, self-esteem, personality, the number of adult roles, or amount of time allotted in adult roles correlated to caregiving.

2.3. Follow-up research The results of this vignette study were consistent with some of the findings from studies of actual sibling caretakers. Most notably, females endorsed more caretaking than did males, especially for proximal tasks. This gendered finding is consistent with the results of Seltzer et al. (1991) and Lawrence, Goodnow, Woods, and Karantzas (2002). The preference for distal tasks is consistent with the finding that siblings tend to provide higher levels of affective than of instrumental support, and that shared activities tend to be distal tasks such as eating out, shopping, and movie-watching (Seltzer et al., 2005). On the other hand, we did not confirm that same-sex, especially sister– sister pairs, would be most involved, nor that future caretaking would be more frequently endorsed than current caretaking. Moreover, because participants were asked about themselves, we believed that they might be exhibiting a self-enhancement bias (Krueger, 1998). In a study of siblings of individuals with IDD following placement out of the parental home, a much smaller percentage moved in with siblings than had been predicted

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by earlier sibling report (Freedman, Krauss, & Seltzer, 1997; Seltzer et al., 2005). To test this interpretation, we designed a follow-up study that explored the possibility of a self-enhancement bias by altering the vignette so that respondents were answering for a friend rather than for themselves. The results of this study (means and S.D.s displayed in Table 9.2) replicated the main effects of proximal and distal caretaking and length of lifespan from the first study. A direct comparison of matched pairs of respondents from the two studies indicated a significant main effect for Self versus Other as caretaker with participants predicting more caretaking for themselves than for others. This self-enhancement bias is an important finding that has relevance for service planning. Even though siblings may have the best of intentions in ‘‘promising’’ involvement in caretaking, they are likely to overestimate their commitment because of self-enhancement. Service providers who acknowledge this probability can plan accordingly. Despite the value of these findings, these studies also have limitations. The vignettes described a car accident when the brother or sister was a young adult. In comparison, most research on siblings of brothers and sisters with IDD utilizes samples in which the cognitive impairments are present from a young age. For example, intellectual disability is usually diagnosed before or soon after school entry. Thus, siblings of people with IDD grow up with the disability being a chronic feature of the family, and future planning of care may be a more prominent part of the family, as compared to the sudden change in the presented vignette. We used this particular scenario so that college students might be able to imagine themselves in this situation, because they could conceivably experience the debilitating accident of an adult brother or sister. Another limitation of these findings is the use of the convenience sample of undergraduate students, mostly 18-year-olds in their first year in college. This sort of homogeneous sample may be quite adequate when the variables being manipulated are ones which vary little by age and life experience. However, attitudes about disability in general and sibling caretaking, in Table 9.2 Other proximal and distal caregiving ratings for time (current/future) and lifespan (short/average) conditions Proximal caregiving

Distal caregiving

Experimental condition

Mean

S.D.

Mean

S.D.

Current, short lifespan Current, average lifespan Future, short lifespan Future, average lifespan

14.18 9.55 11.22 9.06

4.90 4.62 4.85 4.94

15.19 12.35 14.41 13.11

5.47 4.58 5.43 5.45

Note: Caregiving is assessed on a 10-item measure, with involvement and duration components multiplied together to get a composite score, ranging from 0 to 25.

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particular, are likely to vary greatly based on both age and life experience. Thus, we would advise only very cautious generalization toward the actual population of siblings of brothers or sisters with IDD. Nonetheless, the results are relevant to issues that are being examined with real-life methodologies and the findings can serve as a baseline for future examination of siblings’ caregiving behavior and general sibling caregiving attitudes. Furthermore, the research had substantial didactic value in that it provided exceptionally good experimental training to students who were interested in disability issues. By using vignettes, these student researchers were able to surmount the obstacles of subject recruitment and design, implement, and complete a valuable study. They presented their results at a national conference (Coffey, Wasson, Glidden, & Jobe, 2005), an experience that was also a valued outcome of the next set of experiments.

3. Topic 2: Stereotypic Views of Parental Competence and Family Expansion Three studies were designed to collect auxiliary data to an ongoing longitudinal research project studying families who were rearing children with intellectual and other developmental disabilities. A common initial reaction to the diagnosis of a child with a disability is guilt, and parents sometimes report that they believe that others judge them as less competent when they have a child with a disability ( Johnson & Renaud, 1997). This parental belief is fueled by teachers who sometimes blame parents for their child’s poor achievement (Thompson, Warren, & Carter, 2004). Other human service professionals have made substantial contributions to the culture of blame, targeting parents in general ( Johnson, Renaud, Schmidt, & Stanek, 1998) and mothers, in particular. In addition, it is well documented that children with developmental disabilities are also at substantial risk for behavior problems (Einfeld & Tonge, 1996a,b) with some estimates of their co-occurrence as high as 60% for those with moderate to severe ID (Schuengel & Janssen, 2006, p. 229). Because of this comorbidity, it is difficult to disentangle and deconstruct the attitudes of individuals about children with disabilities and their families. The importance of doing so, however, was a primary motivation for the research described in the experiments on this topic. We used vignettes to explore the influence of two different child characteristics— intellectual functioning (disabled or typically developing) and behavioral functioning (negative or positive)—on the assessment of parental competence directly, and also indirectly, via a judgment as to whether the parents should plan to have additional children. We chose to use ratings of parental competence as a measure of the observed biases held by respondents,

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assuming that negative biases would be related to lower ratings of parental competence, reflecting attribution of greater blame to the parents because of the child’s characteristics. Initially, based on the published research, we hypothesized that parents would be judged as less competent if they had a child with disabilities (Levinson & Starling, 1981; Parish, Dyck, & Kappes, 1979) or if they had a child with behavior problems (Anderson, Lytton, & Romney, 1986; Gray, 2002). We also hypothesized that these effects might be stronger for mothers than for fathers given the research evidence that shows that more blame is attributed to the mothers of children with IDD (Caplan & HallMcCorquodale, 1985; Der-Karabetian & Preciado, 1989; Gray, 2002; Jackson & Mannix, 2004). Finally, we also predicted overall respondent sex effects with female respondents providing higher competence ratings than male respondents based on previous research demonstrating that women score higher on Agreeableness than males, and therefore, usually are more positive in assessing others (Costa, Terracciano, & McCrae, 2001).

3.1. Methodological considerations In all three studies, we manipulated the level of intellectual functioning and behavioral functioning of the children. In one study, we also manipulated the age of the children described in the vignettes. Participants provided ratings for either a mother or a father, but not both, for each vignette. Sample vignettes for preschoolers with Down syndrome are provided in the appendix. The vignettes describe important developmental, environmental, and behavioral issues that we expected would influence the perception of parental competence. We chose two levels of Intellectual Functioning in each experiment; one level was either intellectually gifted or average depending on the experiment, and the other level was always ID with Down syndrome. Because few differences in the patterns of results emerged between gifted and average, we have combined them in our summary descriptions in this chapter ( Jobe & Glidden, 2007). Two levels of behavioral functioning, either positive as in the Max Fletcher vignette, or negative, as in the Laurie Sprey sample were counterbalanced with the levels of intellectual functioning. Respondents received vignettes with Child Age (2), Intellectual Functioning (2), and Behavioral Functioning (2) manipulated as within-subject variables. In the experiment in which we manipulated child age, half of the vignettes described an infant who was 11–12 months old, and in the other half of the vignettes the child age was 4 years. Across all vignettes, details on the parents were kept to a minimum. In each vignette, positive parenting behavior was expressed for both mothers and fathers. The description of parenting practices was framed positively and equally for mother and fathers. We reasoned that by providing very limited information about the parents,

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and instead relying on the description of the child, that this would facilitate the biases of participants to influence their response choices with regard to parental competence. Parental competence was assessed by a 20-item questionnaire adapted from 2 existing instruments, the Family Empowerment Scale (FES; Koren, DeChillo, & Friesen, 2000) and the Index of Parental Attitudes (IPA; Hudson, 2000). Items derived from the FES centered on positive aspects of parental competence (‘‘This mother [father] has her [his] family life under control.’’), whereas negative aspects of parental competence were assessed with items from the IPA (‘‘This mother [father] wishes she [he] didn’t have this child.’’). All items were scored on a 1 (‘‘Not true at all’’) to 5 (‘‘Very true’’) scale, with the negatively worded items from the IPA reverse scored. Scores could range from 0 to 100 with higher scores representing higher levels of perceived parental competence. For each vignette, the respondents reported on either a mother or a father. The family expansion variable was assessed by the question, ‘‘Do you think this couple should add another child to their family?’’ A score of 1 represented, ‘‘Definitely Not’’ and 5 ‘‘Definitely.’’ A total of 223 mostly first-year college students, 65% female, 84% Anglo-European Caucasian, mean age 18 years served as participants in the three experiments. For one of the studies, participants reported on their exposure to individuals with disabilities and experiences with children with problem behavior. Only 7% of the sample reported extensive exposure to individuals with disabilities and only 5.2% had exposure to problematic children’s behavior. However, 83% of the participants had some experience with either individuals with disabilities, with problematic behavior, or both.

3.2. Results and discussion 3.2.1. Behavioral functioning The results for the behavioral functioning variable were unequivocal and replicated across all three studies for both parental competence and family expansion. As displayed in Table 9.3, both mothers and fathers were rated as more competent when the vignette child’s behavior was described positively rather than negatively. This result was generally large and consistent, regardless of intellectual level or age of child. Indeed, the positive behavior ‘‘advantage’’ (percent higher for positive behavior compared to negative behavior ratings) ranged from 19% to 55% for the parental competence variable. The advantage for the family expansion showed greater variability, from a low of 8% to a high of 129%. 3.2.2. Intellectual functioning In contrast to the behavioral functioning variable, the influence of intellectual functioning differed for the ratings of parental competence and family expansion. In all three experiments, the parents of children with Down

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Table 9.3 Parental competency ratings for mothers and fathers by child’s intellectual functioning and child’s behavioral functioning Child level of intellectual functioning Disabled

Typical

Behavioral functioning

Parent

Positive

Negative

Positive

Negative

Mean

S.D.

Mean

S.D.

Mothers of infant Parental 89.73 (10.31) 66.67 (11.13) 89.23 (8.81) competency Family 3.70 (0.82) 2.11 (1.21) 4.33 (1.00) expansion Mothers of preschooler Parental 88.08 (6.19) competency Family 3.73 (0.96) expansion Fathers of infant Parental 89.90 (8.95) competency Family 3.58 (1.03) expansion Fathers of preschooler Parental 87.73 (8.86) competency Family 3.90 (0.89) expansion

64.74 (11.05) 2.41 (1.12)

76.00 (8.71)

92.00 (6.47)

59.23 (10.78)

2.85 (1.06)

4.22 (1.01)

2.33 (1.04)

69.03 (11.61) 90.74 (8.64)

65.65 (11.19)

2.23 (1.18)

4.35 (0.92)

2.39 (0.99)

72.03 (11.39) 90.71 (7.73)

61.65 (12.81)

3.26 (0.97)

4.50 (0.78)

2.53 (1.04)

Note: Parental competency is assessed on a 0–100 scale, with higher scores representing higher competency. Family expansion is assessed on a 0–5 scale, with higher ratings indicating more endorsement for adding children to the family.

syndrome were actually rated as more competent, but the endorsement for their family expansion was lower, as can be seen in Table 9.3. Moreover, in both experiments in which an interaction between intellectual and behavioral functioning could be tested, it resulted in similar significant results in that parents who had typically developing children who behaved negatively were penalized more in competence ratings than parents who had Down syndrome children who behaved negatively. This penalty was especially true for the preschool children in contrast to the infants, exemplified by a significant three-way interaction for Intellectual Functioning Behavioral Functioning Age.

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These results were expected, but also surprising. We had accurately predicted the impact of problem behavior in the judgment of parental competence and endorsement of family expansion, although the size of the effect was greater than we had anticipated. However, in contrast to a frequently held belief that families who have children with IDD are stigmatized, the current findings suggest that parents actually are viewed as more competent if their child has Down syndrome, and, moreover, are blamed less than parents of children without IDD if those children exhibit problem behaviors. One interpretation of this finding is that respondents believed that children with Down syndrome were more likely to exhibit negative behaviors because of their disabilities, and therefore, the parents were not as likely to be faulted. A related interpretation is that because of the learning difficulties associated with Down syndrome, respondents did not expect that it was possible that the children with Down syndrome would learn appropriate behaviors at a comparable chronological age as would typically developing children. In these three experiments, the vignettes matched the different levels of intellectual ability on chronological age rather than mental age. Follow-up studies might try mental-age matching to determine whether the Down syndrome parental competence advantage would remain. Important, too, was the difference in the findings for parental competence and family expansion. Even though parents of children with Down syndrome were viewed as more competent, respondents did not think that they should have more children. Thus, the stigma may exist, but be expressed not in terms of parental incompetence, but in terms of whether parents should take on the additional challenges of more children. Several interpretations of this effect are possible. Respondents may have believed that a child with Down syndrome was more difficult to raise, more expensive, less desirable for a sibling, and so forth. They also might have thought that the parents were at risk for conceiving a second child with Down syndrome, thus exacerbating these difficulties. We did not ask respondents to explain their choices, but other investigators could do so in their experimental designs. As seen in the results, people hold complex, conditional views of families with and without children with disabilities. Using vignettes to create an experimental situation allowed the assessment of the attitudes in vitro rather than in vivo. We obtained consistent results across studies which should have heuristic value as the findings raised as many questions as they provided answers. If the attitudes we found in these data are reflected in the society at large, it suggests that the biases that exist about parents of children with IDD may be positive as well as negative. Sometimes persons with disabilities overcome what seem to be insurmountable obstacles and achieve success and fame as actors, artists, or athletes (Katz, 1994). More often, persons with IDD who overcome significant challenges and accomplish the tasks of typical development serve as inspiration to those who know them (Brown, Shiraga, & Kessler, 2006). Our data suggest that their parents may be viewed similarly.

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4. Summary and General Discussion 4.1. Theoretical and applied value of the research The two topics that were central to the research described in this chapter addressed issues about IDD that have received little attention in the disability field. Adult sibling caregiving was of less interest decades ago when many individuals with disabilities had shorter life expectancies and lived much of their lives outside of their family homes. Moreover, for those individuals with disabilities who did survive to adulthood, there was often little choice of residential options. Either they lived in institutions or in the home of a family member. It was only in the 1960s and later when normalization and deinstitutionalization became national and international policy for many countries that residential choices began to be offered, and families had to make decisions about adult caretaking. Similarly, historically, research on parents of children with disabilities adopted a medical and pathological view of the impact, and there was an assumption of negative effects. The prevailing framework led to demonstrating that stress and burden was the outcome for parents of children with disability. It is only recently that investigators have begun to focus on the characteristics of children with IDD that may be most difficult for parents to adapt to, as well as the characteristics that are most rewarding. In the past 10 years, child behavior problems have been identified as most challenging for parents, typically more so than intellectual disability per se (Feldman et al., 2007; Glidden & Schoolcraft, 2007; Hassall, Rose, & McDonald, 2005), a finding underscored by our vignette research on parental competence. In addition to historical context, we have identified and discussed other factors that result in neglect of some research topics. Difficulty of implementation of required methods, limited resources, lack of guiding theory, and general inapplicability of potential findings have all been addressed. These factors are not mutually exclusive. In fact, they may be related and interactive. For example, resources for research may be scarce for topics that are believed to have little applied value. Increasingly, researchers are involving stakeholders other than scientists in their research enterprise, a participatory action research model. Adopting a participatory action research model entails the consideration of those directly and indirectly affected by the research being conducted. Different stakeholders have legitimate interests in being included in research and participants may be representative persons with disabilities, their families, friends, employers, teachers, coworkers, or policymakers. A framework for the level of family involvement has been outlined from level 1 (no family involvement) to level 6 (families serve as advisors to research team, Turnbull, Friesen, & Ramirez, 1998). In applying this approach specifically to research

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on disabilities, Robison and Krauss (2003) reported their recommendations based on the components of participatory action research that have worked for them. Researchers planning to implement a participatory action model would be well served to review their recommendations and adapt them to the unique circumstances of their own research. The impetus for Topic 2 arose from a participatory research agenda. In a 20-year longitudinal research project on parents rearing children with IDD (Flaherty & Glidden, 2000; Glidden & Jobe, 2006; Glidden, Kiphart, Willoughby, & Bush, 1993), we interviewed parents about many experiences related to both the rewards and the problems they had experienced. From those interview narratives, we learned that some parents felt that they were blamed for their child’s disability. These feelings, however, were far from universal, and they were generally uncorroborated. The Topic 2 research does not deal with blame for the disability directly, but does suggest that parents are viewed as equally competent regardless of the intellectual functioning of their child. Limitations to the vignette technique do, of course, need to be acknowledged. Directly assessing the variable of interest through behavioral observations or self-report can sometimes differ from how other people report they think and feel about a subject. This discrepancy has been demonstrated in, for example, research on discrimination. There is ample evidence that prejudicial attitudes do not predict actual discrimination practices (Ehrlich, 1969; Warner & Dennis, 1970; Frazer & Wiersma, 2001), and as such, the two represent related but not equivalent phenomena. How someone says he or she feels about a matter does not necessarily predict how that person will behave when placed in that situation. This gap between attitudes and behavior does not invalidate data from vignettes nor should it dismiss their use in experimental protocols. Instead, it serves as a reminder to the investigator to be aware of what question is actually being asked and, therefore, what the results mean and how they should be interpreted. Attitudinal bias does not always translate into discriminative behavior, nor does lack of reported bias mean that discrimination will not occur. Many variables both mediate and moderate between biased thoughts and discriminative behaviors. Researchers must be aware of this difference when drawing conclusions about their findings. Attitudes should not be used as an approximation of behavior, as these are different processes. Understanding the thinking and biases of individuals is a necessary step in fully understanding and preventing discrimination, and the limitations imposed by the vignette methodology should not be overstepped in generalizing the findings. One of the key features of a vignette is that it exposes a respondent to a condition he or she may have not encountered in daily living. As familiarity with disability can relate to attitudes toward disability (Zetlin, 1986), an assessment of familiarity with the experimental condition is necessary.

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Knowing that your sample has extensive exposure to individuals with disabilities will change how the results are interpreted as compared to a sample of respondents that have limited experiences with individuals with disabilities. Research designs like the ones utilized in Topic 2, can help circumvent the issues of biased reporting due to social desirability. By providing multiple vignettes to respondents and varying the conditions in each vignette, a within-subject comparison can examine for subtle differences in responding. By keeping all other variables constant, or as near constant as possible (i.e., similar family structure and circumstances), and just varying the conditions of interest, these differences can be teased apart. When actual manipulation of these conditions is not possible, the vignette methodology provides a useful assessment tool. In research, it is often a challenge to obtain the ideal sample for examination, and as such, alternatives need to be explored. When conducting research on ID, the low prevalence of disability coupled with the additional stressors associated with caring for a person with disabilities makes it difficult to find adequate numbers of respondents that are willing to participate in research studies despite the desirability of their participation. Further, some questions are best answered by persons outside the particular families of interest, especially when understanding the attitudes and biases of the general population is desired. Researchers need to be aware of the strengths and limitations of the vignette methodology in order to avoid the pitfalls of its use while still furthering the field’s understanding of the topics.

4.2. Didactic value of the research In addition to their contribution to the corpus of research about families and children with IDD, the studies described in this chapter used a methodology that provided opportunities for undergraduate students to experience involvement in every stage of the research enterprise. These students participated in the framing of hypotheses, operationalizing variables and designing the method, preparing materials, collecting, scoring, checking, and analyzing data, interpreting results, and disseminating information about completed projects both in oral and written form. As such, they learned a great deal about research methodology and about IDD. As part of their education in research methods, they had to become familiar with past and current theories, constructs, and empirical findings. Many of them were co-authors, including lead author, on conference presentations (Corrice, Glidden, & Black, 2007; Coster, Jobe, & Glidden, 2007) and on published articles and book chapters (Glidden, Dulan, & Hill, 1999; Lazarus, Evans, Glidden, & Flaherty, 2002; Willoughby & Glidden, 1995). These experiences conformed to the learning outcomes proposed by the American Psychological Association (APA) in their Guidelines for the

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Undergraduate Major (2007). These guidelines recommend that students majoring in psychology engage in the design and conduct of research, including planning, conducting, and interpreting the results of their own research studies. The APA encourages students to report their data, and although the guidelines are not specific as to whether the report should be written or spoken, both are important skills that should be practiced. In our own experience, the direct involvement and sense of ownership that students felt were two elements that encouraged them to pursue graduate degrees in IDD or closely related fields such as clinical psychology or social work. Moreover, the opportunity to work closely with a mentor was a fulfilling experience for our students. We concur with Richard Light (2001) who concluded from more than 1,600 interviews with undergraduate students that the experience of establishing a close working relationship with a faculty member was one of the most influential aspects of their college years. In addition, we believe that the research enterprise is an excellent vehicle for achieving this close working relationship.

Appendix

Sample Vignette of a Child with Down Syndrome and Positive Behavior Case Study: Max Fletcher Max Fletcher is touching the lives of many, and this is quite impressive considering he is just 4 years old. Max was born to Marcia and Richard Fletcher in the quaint town of Wooster, Ohio. Although the birth was not difficult, doctors diagnosed Max with Down syndrome soon after, and advised the Fletchers of the typical characteristics of the syndrome so that they would have appropriate expectations. When Mr. and Mrs. Fletcher reflected on that day, they realized how little they had expected. He has brought great joy to them, and provided an unusual perspective on life. Nonetheless, adjusting to Max’s needs has at times been an uphill battle for the Fletchers, but the progress has been substantial. The Fletchers’s neighbors had not known many people with disabilities, but Max’s lovable nature allowed him to make playmates among the neighborhood children. Max’s disability does prevent him from playing like the other children because he is often slower and less coordinated, but instead of excluding him the children often help him. It has also been a challenge to meet Max’s needs because services are not always available or oriented to a child like

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Max. Various therapists, however, have been creative in adapting their techniques, and Max has made it easy because he is so affectionate. Max is kind to almost everyone he meets. Last Saturday when he was grocery shopping with his parents, a little girl in the checkout line was crying. Max reached over to her and gave her a big hug. It is Max’s unconditional trust and love for people that makes him so special. The Fletchers have gained a lot of insight from their son because he is very aware of the feelings of others. Max is especially close to his grandparents and they take comfort in his presence. When Max’s grandfather became very sick recently, Max’s weekend visits were uplifting. Max is currently enrolled in preschool and comes home bubbling with excitement about the day’s events. Teachers are pleased with Max and frequently comment on his caring nature. He is the only child with a disability in his class and he has a helper who assists him with his tasks. His favorite activity is art and he is learning the primary colors. His favorite colors are red and blue because they are the colors of his favorite cartoon character, Spiderman. Max is not ostracized by other students, but they do recognize that he is different from them. Max’s teacher recently commented on what a positive experience it is for the other children to know a child with special needs. Max has some difficulty falling asleep at night. He becomes frightened at bedtime and does not want to sleep in his bedroom alone. Sometimes this leads to an upsetting episode of crying and yelling. The Fletchers usually give in to their son and allow him to sleep with them. Max picked out a Spiderman nightlight and stuffed animal and this has eased his bedtime tantrums. Mr. and Mrs. Fletcher recently bought Max a children’s watercolor set. This has been really wonderful because Max is actually quite creative with colors. His preschool curriculum emphasizes arts and crafts, and Max really enjoys this. When he brings home a painting, his parents praise him and add it to the refrigerator collection. Max recently told his mom and dad that he would like to be a painter when he grows up. The Fletchers are not certain whether or not he will be able to reach this goal because of his disability, but they are confident that their son’s outlook will take him far in life.

Sample Vignette of a Child with Down Syndrome and Negative Behavior Case Study: Laurie Sprey Kathy and Roger Sprey gave birth to their daughter, Laurie, less than a week before Christmas and they had excitedly anticipated Laurie’s birth as the best Christmas gift ever. Within moments after her birth, it was apparent that Laurie was born with Down syndrome, and although her parents were

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suddenly faced with new challenges they loved their daughter nonetheless. However, Laurie is now 4 years old, and they are becoming increasingly concerned about her temperamental behavior. The Spreys are an active family. They live on a large wooded lot in Montana and enjoy hiking and fishing together as a family. During the summer, the Sprey family enjoys swimming in the lake that is near the edge of their property and they frequently have picnics as well. The cold weather generally keeps the family indoors during the winter, but Mr. and Mrs. Sprey are avid readers and, along with Laurie, enjoy reading by the fireplace. After dinner Laurie gets to pick her three favorite books and her parents take turns reading to her. Unfortunately, this peaceful activity is rare, because Laurie’s behavioral problems are usually the focus of attention during family gatherings. Laurie is also having difficulty adjusting to her preschool environment. She is easily frustrated and does not express her feelings in an appropriate manner. Often times, if Laurie becomes agitated she will spit or flail her arms while making loud noises. Recently, one of Laurie’s disruptive tantrums prematurely ended a preschool day trip to the local theatre because Laurie’s helper was unable to calm her. Laurie’s preschool instructors have not had success in helping her control her behavior in the classroom. On a few occasions, Laurie has become very angry and as a result has wet her pants, even though she successfully toilets most of the time. Her teachers were sympathetic, as accidents are frequent at this age, but it is becoming increasingly apparent that Laurie is expressing her anger in inappropriate ways. The neighborhood children are often frightened by Laurie’s outbursts. In one incident, Laurie became upset with her playmate Michelle for tapping her in their game of duck–duck–goose. Laurie screamed at Michelle and slapped her on the arm and face. Mrs. Sprey witnessed the event from the kitchen window and immediately ran outside. The whole ordeal ended with Laurie having to go to her bedroom for the rest of the night. The Spreys and Michelle’s parents decided that it would not be a good idea for Laurie to play alone with other children until she learns to control her temper. Mr. and Mrs. Sprey recently bought Laurie an art kit designed for children, which they hoped might provide an outlet for expressing her emotions. Mrs. Sprey invited Laurie’s cousin Michael over to try out the new kit with Laurie. The day ended at the emergency medical clinic with Michael having a black and blue eye. Evidently, Laurie became frustrated and took one of the new, sharpened crayons and jabbed her cousin in the eye with it. Mr. and Mrs. Sprey do not believe that Laurie intentionally wants to hurt other children, but they realize that her behavior is unacceptable and poses a threat to her playmates. Kindergarten is approaching and the Spreys

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are faced with the decision of choosing an environment that will be positive for Laurie and safe for the other students. Both parents want Laurie to be in an inclusive educational environment, but they are concerned that her current behavior is not suitable for this setting. They are considering consulting with a child psychologist to help determine ways for Laurie to communicate more appropriately.

ACKNOWLEDGMENTS This work was supported, in part, by Grant # HD21993 from the National Institute of Child Health and Human Development, and by faculty development grants from St. Mary’s College of Maryland, all to the second author.

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Index

A AAVI. See Adult and adolescent vulnerability index ABCX model, family stress theory, 245 Acute myeloid leukemia (AML), 81 Adaptive behavior, 148 ADHD. See Attention deficit-hyperactivity disorder Adult and adolescent vulnerability index (AAVI), 184 Agency beliefs. See Self-efficacy Aging, 120–121 Alzheimer’s disease characteristics, 105 classification and diagnosis, 111–115 diagnostic overshadowing, 108 mortality rates, 106 and neuropathology, 123–125 American Psychological Association (APA), 333–334 AML. See Acute myeloid leukemia b-amyloid protein apolipoprotein E, 129 biomarkers, 132–133 neuropathology, 124 sex differences and estrogen, 127 Animal models chemical induction Bay K 8644, 208–209 clonidine, 207–208 methylxanthines, 207 psychostimulants, 206–207 environmental restriction isolate rearing, 202–204 stereotyped behaviors, 202 future directions chemical induction models, 221 genebrain-behavior model, 223 isolate-rearing primate model, 221 Lesch–Nyhan syndrome generative model, 220 6-OHDA rat model, 222 opioid peptide model, 221

induction types environmental restriction, 199 genetic mouse models, 205–206 lesion models, 206–209 limitations, 200–202 prevention of SIB, 209–210 recovery from SIB age of lesion effects, 214 DA receptors, 213–214 dopamine depletion, 214 FRDT preventive effects, 217–218 FRDT training, 212 GBR12909 effects, 216–217 implications, 218–220 neural mechanism, 219 replication study, 211–212 training-induced recovery, 212–218 unilateral 6-OHDA depletion, 214 in vivo microdialysis, 215–216 Apolipoprotein E, 129–130 Attention deficit-hyperactivity disorder (ADHD), 161 B Biobehavioral etiological hypothesis, 197 Biological disequilibrium factors, 153 Bisphenol A (BPA), 70–71 C Chemical induction animal models Bay K 8644, 208–209 clonidine, 207–208 methylxanthines, 207 psychostimulants, 206–207 Child disability instrument, 269 Cholesterol and statins, 131–132 Chromosome 21 nondisjunction advanced maternal age, 66–67 candidate gene cumulative meta-analysis, 72 folate pathway, 71 environmental influences 343

344

Index

Chromosome 21 nondisjunction (cont.) alcohol, 70 bisphenol A (BPA), 70–71 smoking, 69–70 recombination patterns, 68–69 Clonidine, 207–208 Coercive method, 181 Cognitive impairments, 109–110 Cognitive processes, 117–122 Cognitive reserve, 128–129 Complexity theory, sibling research, 271 Crystallized intelligence, 157 D DA receptors, 213–214 Dementia adaptive behavior, 116–117 assessment methods, 112 causes, 105, 108 characterization, 106 classifications, 111–115 clinical diagnosis, 109–110 definition, 106 maladaptive behavior, 122–123 memory processes, 118–120 neuropathology, 124 program description, 117–118 risk factors, 106, 125–132 Dementia Questionnaire for Mentally Retarded Persons (DMR), 110 Didactic value, vignette methodology APA, 333–334 clinical psychology or social work, 334 research methodology, 333 Dopamine depletion, 214 Down syndrome (DS) aging, 117–122 causes, 104 cognitive processes, 117–122 dementia, 117–122 adaptive behavior, 116–117 assessment methods, 112 causes, 105, 108 characterization, 106 classifications, 111–115 clinical diagnosis, 109–110 definition, 106 maladaptive behavior, 122–123 memory processes, 118–120 neuropathology, 124 program description, 117–118

risk factors, 106, 125–132 maladaptive behavior, 122–123 meiotic chromosomal nondisjunction, 63–64 mortality rates, 106 neurodevelopmental outcomes congenital heart defects, 84–85 hearing loss, 87 leukemia, 85 obstructive sleep apnea syndrome, 85–86 seizure disorder, 86–87 neuropathology, 123–125 presenile dementia, 105 psychiatric and neurobehavioral issues acute lymphoblastic leukemia, 85 autism spectrum disorder, 89 diagnostic overshadowing, 88 risks for depression, 89 Down syndrome/Alzheimer’s disease research program adaptive behavior, 116–117 biomarkers amyloid b peptides, 132–133 telomere shortening, 133 classification and diagnosis dementia assessment methods, 112 DMR-SCS, 112–113 FSIQ, 114–115 IBREMS, 113–114 cognitive impairments, 109–110 cognitive processes, aging, and dementia case studies, 121–122 memory processes, 118–120 other processes, 120–121 dementia causes, 108 dementia status classifications, 111 future research strategies, 133–135 informant-based assessments, 110 maladaptive behavior, 122–123 neuropathology, 123–125 risk factors age, 126 apolipoprotein E, 129–130 atypical karyotypes, 130–131 cholesterol and statins, 131–132 cognitive reserve, 128–129 sex differences and estrogen, 127–128 shared genetic susceptibility, 126–127 tests, 110–111 DRD4 variation, molecular genetics, 247 Drug intoxication, 159

345

Index

E Ecology systems theory, 245 Emotional intelligence, 160 F Family adaptability and cohesion evaluation scale (FACES), 268 Family empowerment scale, 270 Family systems theory, sibling reaearch, 244 Fetal alcohol spectrum disorders (FASD) diagnosing ID, 179 and foolish acts, 181–183 in young adults criminal victimization, 180 false confession behavior, 181 health mistakes, 182 household accidents, 181 incompetent parenting, 181 poor driving decisions, 182 Fixed ratio discrimination training (FRDT) preventive effects, 219–220 training, 214 Fluid intelligence, 157 Follicle stimulating hormone (FSH), 67 Foolish action, adults with ID adaptive behavior, 151 by adults with average IQ analysis, 172–175 factors involved, 175 list of acts, 173–174 research questions, 176 social foolish action, 175 by adults with ID analysis, 167–168 list of acts, 162–164 research questions, 176 social foolish action, 175 social-non induced, 169, 173 affective and state disequilibrium, 160–162 brain damage, 176–179 cognition fluid and crystallized intelligence, 157 practical and social intelligence, 157 and FASD diagnosing ID, 179 in young adults, 180–182 four-factor model factors involved, 152 gullibility, 149 psychology, 152

IQ score and policy implications, 186–188 by normally developing youths analysis, 171–172 cognitive and situation factors, 173, 175 list of acts, 169–170 research questions, 176 social foolish action, 175 paradigm shift, 151 personality, 162–164 research implications frequency measurement, 186 obstacles involved, 183 risk awareness measurement, 184–186 social and practical risk ratings, 183–184 situational problem novelty and ambiguity, 156 social pressure, 155–156 time pressure, 155 types practical, 149–150 social, 150–151 Four-factor model and foolish action factors involved, 152 gullibility, 149 psychology, 152 FSH. See Follicle stimulating hormone Full scale intelligence quotient test scores (FSIQ), 112, 114–115 G GBR12909 effects, 216–217 Genebrain-behavior model, 223 Gilliam austism rating scale, 269 H Hierarchical lineal modeling (HLM), 272 I IBR evaluation of mental status (IBREMS), 111, 113–114 Institute for Basic Research in Mental Retardation (IBR), 106–107 Intellective module, 158 Intellectual and developmental disabilities (IDD), 319, 339 parental competence and family expansion chronological age, 330

346

Index

Intellectual and developmental disabilities (IDD) (cont.) Down syndrome, 319, 327, 329–330, 334–335, 337–338 Family Empowerment Scale, 328, 339 vignette methodology, 318–319, 332–333, 340 young adult sibling caregiving proximal and distal, 323–325 real-life methodologies, 326 self-enhancement bias, 324–325 vignette methodology, 332–333 Intellectual disabilities (ID), parental adaptation to children depression, 303–304 family quality, 304–305 interaction findings, 306–307 positive attitudes, 284–286 protective factors, 295–302 resilience, 286, 308–309 risk and resistance model, 287 SES and demographic factors, 288 stress and depression, 285 Isolate-rearing primate model, 221 L Latent class analysis (LCA) advanced statistical techniques, 272–273 model-based techniques, 273 Lesch–Nyhan syndrome generative model, 220 Life course theory, sibling dyad, 247–248 M Measurement, sibling research studies child disability, 269 instruments, 268–269 Medium-chain acyl-CoA dehydrogenase (MCAD) autosomal recessive disease, 6 in PKU model, 18 Methylxanthines, 207 N Naive offender, 180 Naltrexone, 220 Neurodevelopmental outcomes, Down syndrome congenital heart defects, 84–85 hearing loss, 87

leukemia, 85 obstructive sleep apnea syndrome, 85–86 seizure disorder, 86–87 Neuropathology, 123–125 Newborn screening advantages changing concepts, 17–19 for children and families, 16–17 treatment efficacy and availability, 15 condition evaluation tool features carrier status, 13 clinically obvious phenotype criterion, 10 cystic fibrosis, 12–13 disease burden consequences, 10–13 fragile X syndrome, 10 genetic varient, 12 incidence rate, 8–10 3-methylcrotonylglycinuria, 11 current issues, 8 future directions genomics, 19 population health, 20 practical clinical trials, 21 public health emergency model, 19 guidelines and practices conditions, 5 core standards, 4–5 MCAD deficiency, 6 Newborn Screening Condition Evaluation Tool, 6–8 scoring system, 6 tandem mass spectrometry, 5 phenylketonuria, intellectual disability, 2 public health programs, 5–8, 13, 15 test characteristics diagnostic test, 13 false-positive screen, 14–15 oligonucleotide microarrays and DNA-based testing, 14 O Obstructive sleep apnea syndrome (OSAS), 85 Opioid peptide model, 221 P Paradigm shift, 151 Parental adaptation and ID child and disability protective factors, 295 child and disability risk factors

347

Index

caring difference, 292 caring restrictions, 291–292 children’s behavior, 289–290 formal support, 293–294 objective measures, 290–291 depression, 303–304 family quality, 304–305 interaction findings, 306–307 intra personal protective factors, 300–302 intra personal risk factors, 294 positive attitudes, 284–286 resilience developmental psychology, 305 identification, 303 relative resistance, 286 risk and protective processes, 308–309 resistance, 305–306 risk and resistance model, 287 SES and demographic factors, 288 socio-ecological protective factors coping, 296–297 personality, 297 positive approach, 298 sense of coherence, 298–300 socio-ecological risk factors family functioning, 292 social support, 292–293 socioeconomic position, 293 time restrictions, 291 stress and depression, 285 Parental competence and family expansion chronological age, 330 Down syndrome, 330 Family Empowerment Scale, 328 vignette methodology behavioral functioning, 326–329 intellectual function, 326–329, 332 Phenylketonuria diseases, 1 intellectual disability, 2 Phenylketonuria (PKU), 107 Pictoral scale of perceived competence and social acceptance, 268 Practical foolish action, 150–152 Practical intelligence, 154, 160 Predicted behavior scale, 184 Presenile dementia, 105 Presynaptic dopamine uptake inhibitor, 216–217 Protective factors, parental adaptation and ID

child and disability, 295 intra personal formal and parental support, 300–301 parental support, 301–302 social support, 300 socio-ecological coping, 296–297 personality, 297 positive approach, 298 sense of coherence, 298–300 types, 288–289 Psychiatric and neurobehavioral issues, Down syndrome acute lymphoblastic leukemia, 85 autism spectrum disorder, 89 diagnostic overshadowing, 88 Psychological empowerment scale, 270 Psychostimulants, 206–207 Public health program, newborn screening Institute of Medicine, 13 March of Dimes, 5 National Newborn Screening and Genetics Resource Center, 7–8 newborn screening condition evaluation tool, 6 World Health Organization, 15 Q Quick and inflexible (Q&I) module, 158 R RDDST. See Revised Denver Developmental Screening Test Resilience developmental psychology, 305 identification, 303 relative resistance, 286 risk and protective processes, 308–309 sense of coherence, 298 Resiliency model, family stress theory, 245–246 Revised Denver Developmental Screening Test, 269 Risk and resistance model. See Wallander and Varni model Risk factors, parental adaptation and ID child and disability caring demands, 291–292 caring difference, 292 children’s behavior, 289–290

348

Index

Risk factors, parental adaptation and ID (cont.) objective measures, 290–291 time restrictions, 291 intra personal, 294 socio-ecological family functioning, 292 formal support, 293–294 social support, 292–293 socioeconomic position, 293 S Sampling, sibling research studies participants in, 264–265 type of disability, 266 Self-efficacy, 160 Self-injurious behavior (SIB) animal models chemical induction, 207–209 induction, 199–204 lesion models, 206–209 prevention, 209–210 recovery, 210–222 biobehavioral etiological hypotheses, 197 future directions chemical induction models, 221 genebrain-behavior model, 223 isolate-rearing primate model, 221 Lesch-Nyhan syndrome generative model, 220 6-OHDA rat model, 222 opioid peptide model, 221 genetic mouse models, 205–206 opioid peptide hypothesis, 198 prevalence estimates, 196 psychopharmacological interventions, 201 Self-organizing criticality, 155 Self regulatory depletion, 159 SEM. See Structural equation modeling Sense of coherence (SOC) comprehensibility, 299 definition, 298 manageability, 299–300 Shared genetic susceptibility, 126–127 Sibling research conflict, 240 contributions, 274–275 ecological systems theory, 245 family stress theory ABCX model, 245 molecular genetics, DRD4 variation, 247

resiliency model, 245–246 family systems theory, 244 interactions, 239–240 life course theory, 247–248 measurement disability instrument, 269 instruments, 268 parent and family instruments, 268 outcomes behaviour problems, 242 control locus and self-efficacy, 243 depression, 243 differential parenting, 243 self-concept, 242 supportive parenting and maternal negativity, 243–244 publications, 250–258 research participants, 273 roles children with Down syndrome, 241 role asymmetry and sibling childcare responsibilities, 240–241 sampling methods design, 266–267 intervention studies, 267 parent and sibling participants, 265 type of disability, 266 social construct concept, 248 social modeling theory, 249 theoretical perspectives complexity theory, 271 empowerment, 270–271 measurement techniques and design, 271–272 statistical techniques, 272–273 variables and instruments, 259–264 SOC. See Sense of coherence Social foolish action, 152–153 Social intelligence, 157 Social modeling theory, 249 Social vulnerability scale (SVS), 184 Socioeconomic status (SES), 288 Sortilin-related receptor gene (SORL1), 130 Structural equation modeling (SEM), 272 Sum of cognitive scores (SCS), 112 SVS. See Social vulnerability scale T Tacit knowledge, 152, 157 Tandem mass spectrometry new born screening, 5

349

Index

screening criterion, 9 Telomere shortening, 133 Test of Practical and Social Intelligence (TOPSI), 185 TMD. See Transient myeloproliferative disorder Tongue force and rhythm, 214 TOPSI. See Test of Practical and Social Intelligence Training-induced SIB recovery, 210–220 Transient myeloproliferative disorder (TMD), 81 Trisomy 21 active-case finding methods, 76 advance maternal age, 66–67 behavioral disorders, 88 California Birth Defects Monitoring Program, 78 categorization of race/ethnicity, 77 chorionic villus sampling, 73 chromosome 21 nondisjunction errors, 64–65 cognitive phenotype overview, 83–84 congenital heart defects, 74, 79–81 cumulative meta-analysis of MTHFR C677T, 72 death causes, 74 depression risk, 89 Disability Services Commission, 75 environmental influences, 69–71 folate pathway of candidate gene studies, 71–72 follicle stimulating hormone, 67 gene profiles, 69 leukemia association of, 81–82 maternal age-adjusted prevalence rates, 76 medical disorders, 78–79 meiotic chromosomal nondisjunction errors, types of, 63 mortality and morbidity, 73–75 National Down Syndrome Project (NDSP), 65 National Institutes of Health, 83 neurodevelopmental outcome, 84–87 origin, 65 parental age, 63 prevalence estimates, 75–77

recombination patterns, 68–69 risk factor for MI and MII, 66 survival prospect of individuals, 73 survival rates, 77 telomeric exchange, 69 U Unilateral 6-OHDA depletion, 214 V Vignette methodology behavioral functioning parental competence and family expansion, 328 positive and negative, 326 didactic value APA, 333–334 clinical psychology/social work, 334 research methodology, 333 hypotheses and development sister–sister dyads, 322 three variables, 321 intellectual function Down syndrome, 330–331 levels, 326 involvement levels, 323 self-esteem and personality agreeableness and conscientiousness, 323 Rosenberg self-esteem scale, 322 W Wallander and Varni model, 288 Y Young adult sibling caregiving proximal and distal, 324–325 real-life methodologies, 326 self-enhancement bias, 324–325 vignette methodology hypotheses and development, 321–322 involvement levels, 323 self-esteem and personality, 322–323

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Contents of Previous Volumes

Volume 1

HERMAN H. SPITZ

A Functional Analysis of Retarded Development SIDNEY W. BIJOU

Autonomic Nervous System Functions and Behavior: A Review of Experimental Studies with Mental Defectives RATHE KARRER

Classical Conditioning and Discrimination Learning Research with the Mentally Retarded LEONARD E. ROSS

Learning and Transfer of Mediating Responses in Discriminating Learning BRYAN E. SHEPP AND FRANK D. TURRISI

The Structure of Intellect in the Mental Retardate HARVEY F. DINGMAN AND C. EDWARD MEYERS

A Review of Research on Learning Sets and Transfer or Training in Mental Defectives MELVIN E. KAUFMAN AND HERBERT J. PREHM

Research on Personality Structure in the Retardate EDWARD ZIGLER

Programming Perception and Learning for Retarded Children MURRAY SIDMAN AND LAWRENCE T. STODDARD

Experience and the Development of Adaptive Behavior H. CARL HAYWOOD AND JACK T. TAPP A Research Program on the Psychological Effects of Brain Lesions in Human Beings RALPH M. REITAN Long-Term Memory in Mental Retardation JOHN M. BELMONT

Programming Instruction Techniques for the Mentally Retarded FRANCES M. GREENE Some Aspects of the Research on Mental Retardation in Norway IVAR ARNIJOT BJORGEN Research on Mental Deficiency During the Last Decade in France R. LAFON AND J. CHABANIER

The Behavior of Moderately and Severely Retarded Persons JOSEPH E. SPRADLIN AND FREDERIC L. GIRARDEAU

Psychotherapeutic Procedures with the Retarded MANNY STERNLIGHT

Author Index-Subject Index

Author Index-Subject Index

Volume 2

Volume 3

A Theoretical Analysis and Its Application to Training the Mentally Retarded M. RAY DENNY

Incentive Motivation in the Mental Retardate PAUL S. SIEGEL

The Role of Input Organization in the Learning and Memory of Mental Retardates

Development of Lateral and Choice-Sequence Preferences

351

352 IRMA R. GERJUOY AND JOHN J. WINTERS, JR. Studies in the Experimental Development of Left-Right Concepts in Retarded Children Using Fading Techniques SIDNEY W. BIJOU Verbal Learning and Memory Research with Retardates: An Attempt to Assess Developmental Trends L. R. GOULET Research and Theory in Short-Term Memory KEITH G. SCOTT AND MARCIA STRONG SCOTT Reaction Time and Mental Retardation ALFRED A. BAUMEISTER AND GEORGE KELLAS Mental Retardation in India: A Review of Care, Training, Research, and Rehabilitation Programs J. P. DAS Educational Research in Mental Retardation SAMUEL L. GUSKIN AND HOWARD H. SPICKER Author Index-Subject Index

Volume 4 Memory Processes in Retardates and Normals NORMAN R. ELLIS A Theory of Primary and Secondary Familial Mental Retardation ARTHUR R. JENSEN Inhibition Deficits in Retardate Learning and Attention LAIRD W. HEAL AND JOHN T. JOHNSON, JR. Growth and Decline of Retardate Intelligence MARY ANN FISHER AND DAVID ZEAMAN

contents of previous volumes WARNER WILSON Mental Retardation in Animals GILBERT W. MEIER Audiologic Aspects of Mental Retardation LYLE L. LLOYD Author Index-Subject Index

Volume 5 Medical-Behavioral Research in Retardation JOHN M. BELMONT Recognition Memory: A Research Strategy and a Summary of Initial Findings KEITH G. SCOTT Operant Procedures with the Retardate: An Overview of Laboratory Research PAUL WEISBERG Methodology of Psychopharmacological Studies with the Retarded ROBERT L. SPRAGUE AND JOHN S. WERRY Process Variables in the Paired-Associate Learning of Retardates ALFRED A. BAUMEISTER AND GEORGE KELLAS Sequential Dot Presentation Measures of Stimulus Trace in Retardates and Normals EDWARD A. HOLDEN, JR. Cultural-Familial Retardation FREDERIC L. GIRARDEAU German Theory and Research on Mental Retardation: Emphasis on Structure LOTHAR R. SCHMIDT AND PAUL B. BALTES Author Index-Subject Index Volume 6

The Measurements of Intelligence A. B. SILVERSTEIN

Cultural Deprivation and Cognitive Competence J. P. DAS

Social Psychology and Mental Retardation

Stereotyped Acts

contents of previous volumes ALFRED A. BAUMEISTER AND REX FOREHAND Research on the Vocational Habilitation of the Retarded: The Present, the Future MARC W. GOLD Consolidating Facts into the Schematized Learning and Memory System of Educable Retardates HERMAN H. SPITZ An Attentional-Retention Theory of Retardate Discrimination Learning MARY ANN FISHER AND DAVID ZEAMAN Studying the Relationship of Task Performance to the Variables of Chronological Age, Mental Age, and IQ WILLIAM E. KAPPAUF Author Index-Subject Index Volume 7 Mediational Processes in the Retarded JOHN G. BORKOWSKI AND PATRICIA B. WANSCHURA The Role of Strategic Behavior in Retardate Memory ANN L. BROWN Conservation Research with the Mentally Retarded KERI M. WILTON AND FREDERIC J. BOERSMA Placement of the Retarded in the Community: Prognosis and Outcome RONALD B. MCCARVER AND ELLIS M. CRAIG Physical and Motor Development of Retarded Persons ROBERT H. BRUININKS Subject Index

Volume 8

353 Self-Injurious Behavior ALFRED A. BAUMEISTER AND JOHN PAUL ROLLINGS Toward a Relative Psychology of Mental Retardation with Special Emphasis on Evolution HERMAN H. SPITZ The Role of the Social Agent in Language Acquisition: Implications for Language Intervention GERALD J. MAHONEY AND PAMELA B. SEELY Cognitive Theory and Mental Development EARL C. BUTTERFIELD AND DONALD J. DICKERSON A Decade of Experimental Research in Mental Retardation in India ARUN K. SEN The Conditioning of Skeletal and Autonomic Responses: Normal-Retardate Stimulus Trace Differences SUSAN M. ROSS AND LEONARD E. ROSS Malnutrition and Cognitive Functioning J. P. DAS AND EMMA PIVATO Research on Efficacy of Special Education for the Mentally Retarded MELVINE E. KAUFMAN AND PAUL A. ALBERTO Subject Index

Volume 9 The Processing of Information from Short-Term Visual Store: Developmental and Intellectual Differences LEONARD E. ROSS AND THOMAS B. WARD Information Processing in Mentally Retarded Individuals KEITH E. STANOVICH

354 Mediational Process in the Retarded: Implications for Teaching Reading CLESSEN J. MARTIN

contents of previous volumes FERIHA ANWAR Rumination NIRBHAY N. SINGH

Psychophysiology in Mental Retardation J. CLAUSEN

Subject Index

Theoretical and Empirical Strategies for the Study of the Labeling of Mentally Retarded Persons SAMUEL L. GUSKIN

Volume 11

The Biological Basis of an Ethic in Mental Retardation ROBERT L. ISAACSON AND CAROL VAN HARTESVELDT Public Residential Services for the Mentally Retarded R. C. SCHEERENBERGER Research on Community Residential Alternatives for the Mentally Retarded LAIRD W. HEAL, CAROL K. SIGELMAN, AND HARVEY N. SWITZKY Mainstreaming Mentally Retarded Children: Review of Research LOUIS CORMAN AND JAY GOTTLIEB Savants: Mentally Retarded Individuals with Special Skills A. LEWIS HILL Subject Index Volume 10 The Visual Scanning and Fixation Behavior of the Retarded LEONARD E. ROSS AND SUSAM M. ROSS Visual Pattern Detection and Recognition Memory in Children with Profound Mental Retardation PATRICIA ANN SHEPHERD AND JOSEPH F. FAGAN III Studies of Mild Mental Retardation and Timed Performance T. NETTELBECK AND N. BREWER Motor Function in Down’s Syndrome

Cognitive Development of the Learning-Disabled Child JOHN W. HAGEN, CRAIG R. BARCLAY, AND BETTINA SCHWETHELM Individual Differences in Short-Term Memory RONALD L. COHEN Inhibition and Individual Differences in Inhibitory Processes in Retarded Children PETER L. C. EVANS Stereotyped Mannerisms in Mentally Retarded Persons: Animal Models and Theoretical Analyses MARK H. LEWIS AND ALFRED A. BAUMEISTER An Investigation of Automated Methods for Teaching Severely Retarded Individuals LAWRENCE T. STODDARD Social Reinforcement of the Work Behavior of Retarded and Nonretarded Persons LEONIA K. WATERS Social Competence and Interpersonal Relations between Retarded and Nonretarded Children ANGELA R. TAYLOR The Functional Analysis of Imitation WILLIAM R. MCCULLER AND CHARLES L. SALZBERG Index

Volume 12 An Overview of the Social Policy of Deinstitutionalization

contents of previous volumes BARRY WILLER AND JAMES INTAGLIATA Community Attitudes toward Community Placement of Mentally Retarded Persons CYNTHIA OKOLO AND SAMUEL GUSKIN Family Attitudes toward Deinstitutionalization AYSHA LATIB, JAMES CONROY, AND CARLA M. HESS Community Placement and Adjustment of Deinstitutionalized Clients: Issues and Findings ELLIS M. CRAIG AND RONALD B. MCCARVER Issues in Adjustment of Mentally Retarded Individuals to Residential Relocation TAMAR HELLER Salient Dimensions of Home Environment Relevant to Child Development KAZUO NIHIRA, IRIS TAN MINK, AND C. EDWARD MEYERS Current Trends and Changes in Institutions for the Mentally Retarded R. K. EYMAN, S. A. BORTHWICK, AND G. TARJAN Methodological Considerations in Research on Residential Alternatives for Developmentally Disabled Persons LAIRD W. HEAL AND GLENN T. FUJIURA A Systems Theory Approach to Deinstitutionalization Policies and Research ANGELA A. NOVAK AND TERRY R. BERKELEY Autonomy and Adaptability in Work Behavior of Retarded Clients JOHN L. GIFFORD, FRANK R. RUSCH, JAMES E. MARTIN, AND DAVID J. WHITE Index

Volume 13

355 Sustained Attention in the Mentally Retarded: The Vigilance Paradigm JOEL B. WARM AND DANIEL B. BERCH Communication and Cues in the Functional Cognition of the Mentally Retarded JAMES E. TURNURE Metamemory: An Aspect of Metacognition in the Mentally Retarded ELAINE M. JUSTICE Inspection Time and Mild Mental Retardation T. NETTELBECK Mild Mental Retardation and Memory Scanning C. J. PHILLIPS AND T. NETTELBECK Cognitive Determinants of Reading in Mentally Retarded Individuals KEITH E. STANOVICH Comprehension and Mental Retardation LINDA HICKSON BILSKY Semantic Processing, Semantic Memory, and Recall LARAINE MASTERS GLIDDEN Proactive Inhibition in Retarded Persons: Some Clues to Short-Term Memory Processing JOHN J. WINTERS, JR. A Triarchic Theory of Mental Retardation ROBERT J. STERNBERG AND LOUIS C. SPEAR Index

Volume 14 Intrinsic Motivation and Behavior Effectiveness in Retarded Persons H. CARL HAYWOOD AND HARVEY N. SWITZKY The Rehearsal Deficit Hypothesis NORMAN W. BRAY AND LISA A. TURNER Molar Variability and the Mentally Retarded

356 STUART A. SMITH AND PAUL S. SIEGEL Computer-Assisted Instruction for the Mentally Retarded FRANCES A CONNERS, DAVID R. CARUSO, AND DOUGLAS K. DETTERMAN Procedures and Parameters of Errorless Discrimination Training with Developmentally Impaired Individuals GIULO E. LANCIONI AND PAUL M. SMEETS Reading Acquisition and Remediation in the Mentally Retarded NIRBHAY N. SINGH AND JUDY SINGH Families with a Mentally Retarded Child BERNARD FARBER AND LOUIS ROWITZ Social Competence and Employment of Retarded Persons CHARLES L. SALZBERG, MARILYN LIKINS, E. KATHRYN MCCONAUGHY, AND BENJAMIN LINGUGARIS/KRAFT Toward a Taxonomy of Home Environments SHARON LANDESMAN Behavioral Treatment of the Sexually Deviant Behavior of Mentally Retarded Individuals R. M. FOXX, R. G. BITTLE, D. R. BECHTEL, AND J. R. LIVESAY Behavior Approaches to Toilet Training for Retarded Persons S. BETTISON Index

Volume 15 Mental Retardation as Thinking Disorder: The Rationalist Alternative to Empiricism HERMAN H. SPITZ Developmental Impact of Nutrition on Pregnancy, Infancy, and Childhood: Public Health Issues in the United States

contents of previous volumes ERNESTO POLLITT The Cognitive Approach to Motivation in Retarded Individuals SHYLAMITH KREITLER AND HANS KREITLER Mental Retardation, Analogical Reasoning, and the Componential Method J. MCCONAGHY Application of Self-Control Strategies to Facilitate Independence in Vocational and Instructional Settings JAMES E. MARTIN, DONALD L. BURGER, SUSAN ELIAS-BURGER, AND DENNIS E. MITHAUG Family Stress Associated with a Developmentally Handicapped Child PATRICIA M. MINNES Physical Fitness of Mentally Retarded Individuals E. KATHRYN MCCONAUGHY AND CHARLES L. SALZBERG Index

Volume 16 Methodological Issues in Specifying Neurotoxic Risk Factors for Developmental Delay: Lead and Cadmium as Prototypes STEPHEN R. SCHROEDER The Role of Methylmercury Toxicity in Mental Retardation GARY J. MYERS AND DAVID O. MARSH Attentional Resource Allocation and Mental Retardation EDWARD C. MERRILL Individual Differences in Cognitive and Social Problem-Solving Skills as a Function of Intelligence ELIZABETH J. SHORT AND STEVEN W. EVANS Social Intelligence, Social Competence, and Interpersonal Competence

contents of previous volumes JANE L. MATHIAS Conceptual Relationships Between Family Research and Mental Retardation ZOLINDA STONEMAN Index Volume 17 The Structure and Development of Adaptive Behaviors KEITH F. WIDAMAN, SHARON A. BORTHWICK-DUFFY, AND TODD D. LITTLE Perspectives on Early Language from Typical Development and Down Syndrome MICHAEL P. LYNCH AND REBECCA E. EILERS The Development of Verbal Communication in Persons with Moderate to Mild Mental Retardation LEONARD ABBEDUTO Assessment and Evaluation of Exceptional Children in the Soviet Union MICHAEL M. GERBER, VALERY PERELMAN, AND NORMA LOPEZ-REYNA Constraints on the Problem Solving of Persons with Mental Retardation RALPH P. FERRETTI AND AL R. CAVALIER Long-Term Memory and Mental Retardation JAMES E. TURNURE Index Volume 18 Perceptual Deficits in Mildly Mentally Retarded Adults ROBERT FOX AND STEPHEN OROSS, III Stimulus Organization and Relational Learning SAL A. SORACI, JR. AND MICHAEL T. CARLIN

357 Stimulus Control Analysis and Nonverbal Instructional Methods for People with Intellectual Disabilities WILLIAM J. MCILVANE Sustained Attention in Mentally Retarded Individuals PHILLIP D. TOMPOROWSKI AND LISA D. HAGER How Modifiable Is the Human Life Path? ANN M. CLARKE AND ALAN D. B. CLARKE Unraveling the ‘‘New Morbidity’’: Adolescent Parenting and Developmental Delays JOHN G. BORKOWSKI, THOMAS L. WHITMAN, ANNE WURTZ PASSINO, ELIZABETH A. RELLINGER, KRISTEN SOMMER, DEBORAH KEOUGH, AND KERI WEED Longitudinal Research in Down Syndrome JANET CARR Staff Training and Management for Intellectual Disability Services CHRIS CULLEN Quality of Life of People with Developmental Disabilities TREVOR R. PARMENTER Index

Volume 19 Mental Retardation in African Countries: Conceptualization, Services, and Research ROBERT SERPELL, LILIAN MARIGA, AND KARYN HARVEY Aging and Alzheimer Disease in People with Mental Retardation WARREN B. ZIGMAN, NICOLE SCHUPF, APRIL ZIGMAN, AND WAYNE SILVERMAN Characteristics of Older People with Intellectual Disabilities in England JAMES HOGG AND STEVE MOSS

358 Epidemiological Thinking in Mental Retardation: Issues in Taxonomy and Population Frequency TOM FRYERS Use of Data Base Linkage Methodology in Epidemiological Studies of Mental Retardation CAROL A. BOUSSY AND KEITH G. SCOTT Ways of Analyzing the Spontaneous Speech of Children with Mental Retardation: The Value of Cross-Domain Analyses CATHERINE E. SNOW AND BARBARA ALEXANDER PAN Behavioral Experimentation in Field Settings: Threats to Validity and Interpretation Problems WILLY-TORE MRCH Index

Volume 20

contents of previous volumes CLAUSSEN, AND LOIS-LYNN STOYKO DEUEL Employment and Mental Retardation NEIL KIRBY Index

Volume 21 An Outsider Looks at Mental Retardation: A Moral, a Model, and a Metaprincipal RICHARD P. HONECK Understanding Aggression in People with Intellectual Disabilities: Lessons from Other Populations GLYNIS MURPHY A Review of Self-Injurious Behavior and Pain in Persons with Developmental Disabilities FRANK J. SYMONS AND TRAVIS THOMPSON

Parenting Children with Mental Retardation BRUCE L. BAKER, JAN BLACHER, CLAIRE B. KOPP, AND BONNIE KRAEMER

Recent Studies in Psychopharmacology in Mental Retardation MICHAEL G. AMAN

Family Interactions and Family Adaptation FRANK J. FLOYD AND CATHERINE L. COSTIGAN

Methodological Issues in the Study of Drug Effects on Cognitive Skills in Mental Retardation DEAN C. WILLIAMS AND KATHRYN J. SAUNDERS

Studying Culturally Diverse Families of Children with Mental Retardation IRIS TAN MINK Older Adults with Mental Retardation and Their Families TAMAR HELLER A Review of Psychiatric and Family Research in Mental Retardation ANN GATH A Cognitive Portrait of Grade School Students with Mild Mental Retardation MARCIA STRONG SCOTT, RUTH PEROU, ANGELIKA HARTL

The Behavior and Neurochemistry of the Methylazoxymethanol-Induced Microencephalic Rat PIPPA S. LOUPE, STEPHEN R. SCHROEDER, AND RICHARD E.TESSEL Longitudinal Assessment of Cognitive-Behavioral Deficits Produced by the Fragile-X Syndrome GENE S. FISCH Index

Volume 22

contents of previous volumes Direct Effects of Genetic Mental Retardation Syndromes: Maladaptive Behavior and Psychopathology ELISABETH M. DYKENS Indirect Effects of Genetic Mental Retardation Disorders: Theoretical and Methodological Issues ROBERT M. HODAPP The Development of Basic Counting, Number, and Arithmetic Knowledge among Children Classified as Mentally Handicapped ARTHUR J. BAROODY The Nature and Long-Term Implications of Early Developmental Delays: A Summary of Evidence from Two Longitudinal Studies RONALD GALLIMORE, BARBARA K. KEOGH, AND LUCINDA P. BERNHEIMER Savant Syndrome TED NETTELBECK AND ROBYN YOUNG The Cost-Efficiency of Supported Employment Programs: A Review of the Literature ROBERT E. CIMERA AND FRANK R. RUSCH Decision Making and Mental Retardation LINDA HICKSON AND ISHITA KHEMKA ‘‘The Child That Was Meant?’’ or ‘‘Punishment for Sin?’’: Religion, Ethnicity, and Families with Children with Disabilities LARAINE MASTERS GLIDDEN, JEANNETTE ROGERS-DULAN, AND AMY E. HILL Index Volume 23 Diagnosis of Autism before the Age of 3 SALLY J. ROGERS The Role of Secretin in Autistic Spectrum Disorders AROLY HORVATH AND J. TYSON TILDON

359 The Role of Candidate Genes in Unraveling the Genetics of Autism CHRISTOPHER J. STODGELL, JENNIFER L. INGRAM, AND SUSAN L. HYMAN Asperger’s Disorder and Higher Functioning Autism: Same or Different? FRED R. VOLKMAR AND AMI KLIN The Cognitive and Neural Basis of Autism: A Disorder of Complex Information Processing and Dysfunction of Neocortical Systems NANCY J. MINSHEW, CYNTHIA JOHNSON, AND BEATRIZ LUNA Neural Plasticity, Joint Attention, and a Transactional Social-Orienting Model of Autism PETER MUNDY AND A. REBECCA NEAL Theory of Mind and Autism: A Review SIMON BARON-COHEN Understanding the Language and Communicative Impairments in Autism HELEN TAGER-FLUSBERG Early Intervention in Autism: Joint Attention and Symbolic Play CONNIE KASARI, STEPHANNY F. N. FREEMAN, AND TANYA PAPARELLA Attachment and Emotional Responsiveness in Children with Autism CHERYL DISSANAYAKE AND MARIAN SIGMAN Families of Adolescents and Adults with Autism: Uncharted Territory MARSHA MAILICK SELTZER, MARTY WYNGAARDEN KRAUSS, GAEL I. ORSMOND, AND CARRIE VESTAL Index

Volume 24 Self-Determination and Mental Retardation MICHAEL L. WEHMEYER

360 International Quality of Life: Current Conceptual, Measurement, and Implementation Issues KENNETH D. KEITH Measuring Quality of Life and Quality of Services through Personal Outcome Measures: Implications for Public Policy JAMES GARDNER, DEBORAH T. CARRAN, AND SYLVIA NUDLER Credulity and Gullibility in People with Developmental Disorders: A Framework for Future Research STEPHEN GREENSPAN, GAIL LOUGHLIN, AND RHONDA S. BLACK Criminal Victimization of Persons with Mental Retardation: The Influence of Interpersonal Competence on Risk T. NETTELBECK AND C. WILSON The Parent with Mental Retardation STEVE HOLBURN, TIFFANY PERKINS, AND PETER VIETZE Psychiatric Disorders in Adults with Mental Retardation STEVE MOSS Development and Evaluation of Innovative Residential Services for People with Severe Intellectual Disability and Serious Challenging Behavior JIM MANSELL, PETER MCGILL, AND ERIC EMERSON The Mysterious Myth of Attention Deficits and Other Defect Stories: Contemporary Issues in the Developmental Approach to Mental Retardation JACOB A. BURACK, DAVID W. EVANS, CHERYL KLAIMAN, AND GRACE IAROCCI Guiding Visual Attention in Individuals with Mental Retardation RICHARD W. SERNA AND MICHAEL T. CARLIN Index

contents of previous volumes Volume 25 Characterizations of the Competence of Parents of Young Children with Disabilities CARL J. DUNST, TRACY HUMPHRIES, AND CAROL M. TRIVETTE Parent–Child Interactions When Young Children Have Disabilities DONNA SPIKER, GLENNA C. BOYCE, AND LISA K. BOYCE The Early Child Care Study of Children with Special Needs JEAN F. KELLY AND CATHRYN L. BOOTH Diagnosis of Autistic Disorder: Problems and New Directions ROBYN YOUNG AND NEIL BREWER Social Cognition: A Key to Understanding Adaptive Behavior in Individuals with Mild Mental Retardation JAMES S. LEFFERT AND GARY N. SIPERSTEIN Proxy Responding for Subjective Well-Being: A Review ROBERT A. CUMMINS People with Intellectual Disabilities from Ethnic Minority Communities in the United States and the United Kingdom CHRIS HATTON Perception and Action in Mental Retardation W. A. SPARROW AND ROSS H. DAY Volume 26 A History of Psychological Theory and Research in Mental Retardation since World War II DONALD K. ROUTH AND STEPHEN R. SCHROEDER Psychopathology and Intellectual Disability: The Australian Child to Adult Longitudinal Study BRUCE J. TONGE AND STEWART L. EINFELD

contents of previous volumes Psychopathology in Children and Adolescents with Intellectual Disability: Measurement, Prevalence, Course, and Risk JAN L. WALLANDER, MARIELLE C. DEKKER, AND HANS KOOT Resilience, Family Care, and People with Intellectual Disabilities GORDONGRANT, PAULRAMCHARAN, AND PETER GOWARD Prevalence and Correlates of Psychotropic Medication Use among Adults with Developmental Disabilities: 1970–2000 MARIA G. VALDOVINOS, STEPHEN R. SCHROEDER, AND GEUNYOUNG KIM Integration as Acculturation: Developmental Disability, Deinstitutionalization, and Service Delivery Implications M. KATHERINE BUELL Cognitive Aging and Down Syndrome: An Interpretation J. P. DAS Index

361 CARMICHAEL OLSON, AND GERALYN R. TIMLER Memory, Language Comprehension, and Mental Retardation EDWARD C. MERRILL, REGAN LOOKADOO, AND STACY RILEA Reading Skills and Cognitive Abilities of Individuals with Mental Retardation FRANCES A. CONNERS Language Interventions for Children with Mental Retardation NANCY C. BRADY AND STEVEN F. WARREN Augmentative and Alternative Communication for Persons with Mental Retardation MARYANN ROMSKI, ROSE A. SEVCIK, AND AMY HYATT FONSECA Atypical Language Development in Individuals with Mental Retardation: Theoretical Implications JEAN A. RONDAL Index

Volume 27

Volume 28

Language and Communication in Individuals with Down Syndrome ROBIN S. CHAPMAN

Promoting Intrinsic Motivation and Self-Determination in People with Mental Retardation EDWARD L. DECI

Language Abilities of Individuals with Williams Syndrome CAROLYN B. MERVIS, BYRON F. ROBINSON, MELISSA L. ROWE, ANGELA M. BECERRA, AND BONITA P. KLEIN-TASMAN Language and Communication in Fragile X Syndrome MELISSA M. MURPHY AND LEONARD ABBEDUTO On Becoming Socially Competent Communicators: The Challenge for Children with Fetal Alcohol Exposure TRUMAN E. COGGINS, LESLEY B. OLSWANG, HEATHER

Applications of a Model of Goal Orientation and Self-Regulated Learning to Individuals with Learning Problems PAUL R. PINTRICH AND JULIANE L. BLAZEVSKI Learner-Centered Principles and Practices: Enhancing Motivation and Achievement for Children with Learning Challenges and Disabilities BARBARA L. MCCOMBS Why Pinocchio Was Victimized: Factors Contributing to Social Failure in People with Mental Retardation STEPHEN GREENSPAN

362 Understanding the Development of Subnormal Performance in Children from a Motivational-Interactionist Perspective JANNE LEPOLA, PEKKA SALONEN, MARJA VAURAS, AND ELISA POSKIPARTA Toward Inclusion Across Disciplines: Understanding Motivation of Exceptional Students HELEN PATRICK, ALLISON M. RYAN, ERIC M. ANDERMAN, AND JOHN KOVACH Loneliness and Developmental Disabilities: Cognitive and Affective Processing Perspectives MALKA MARGALIT The Motivation to Maintain Subjective Well-Being: A Homeostatic Model ROBERT A. CUMMINS AND ANNA L. D. LAU Quality of Life from a Motivational Perspective ROBERT L. SCHALOCK Index Volume 29 Behavioral Phenotypes: Going Beyond the Two-Group Approach ROBERT M. HODAPP Prenatal Drug Exposure and Mental Retardation ROBERT E. ARENDT, JULIA S. NOLAND, ELIZABETH J. SHORT, AND LYNN T. SINGER Spina Bifida: Genes, Brain, and Development JACK M. FLETCHER, MAUREEN DENNIS, HOPE NORTHRUP, MARCIA A. BARNES, H. JULIA HANNAY, SUSAN H. LANDRY, KIM COPELAND, SUSAN E. BLASER, LARRY A. KRAMER, MICHAEL E. BRANDT, AND DAVID J. FRANCIS The Role of the Basal Ganglia in the Expression of Stereotyped, Self-Injurious Behaviors in Developmental Disorders HOWARD C. CROMWELL AND BRYAN H. KING

contents of previous volumes Risk Factors for Alzheimer’s Disease in Down Syndrome LYNN WARD Precursors of Mild Mental Retardation in Children with Adolescent Mothers JOHN G. BORKOWSKI, JULIE J. LOUNDS, CHRISTINE WILLARD NORIA, JENNIFER BURKE LEFEVER, KERI WEED, DEBORAH A. KEOGH, AND THOMAS L. WHITMAN The Ecological Context of Challenging Behavior in Young Children with Developmental Disabilities ANITA A. SCARBOROUGH AND KENNETH K. POON Employment and Intellectual Disability: Achieving Successful Employment Outcomes KAYE SMITH, LYNNE WEBBER, JOSEPH GRAFFAM, AND CARLENE WILSON Technology Use and People with Mental Retardation MICHAEL L. WEHMEYER, SEAN J. SMITH, SUSAN B. PALMER, DANIEL K. DAVIES, AND STEVEN E. STOCK Index

Volume 30 Neurodevelopmental Effects of Alcohol THOMAS M. BURBACHER AND KIMBERLY S. GRANT PCBs and Dioxins HESTIEN J. I. VREUGDENHIL AND NYNKE WEISGLAS-KUPERUS Interactions of Lead Exposure and Stress: Implications for Cognitive Dysfunction DEBORAH A. CORY-SLECHTA

contents of previous volumes Developmental Disabilities Following Prenatal Exposure to Methyl Mercury from Maternal Fish Consumption: A Review of the Evidence GARY J. MYERS, PHILIP W. DAVIDSON, AND CONRAD F. SHAMLAYE Environmental Agents and Autism: Once and Future Associations SUSAN L. HYMAN, TARA L. ARNDT, AND PATRICIA M. RODIER Endocrine Disruptors as a Factor in Mental Retardation BERNARD WEISS The Neurotoxic Properties of Pesticides HERBERT L. NEEDLEMAN Parental Smoking and Children’s Behavioral and Cognitive Functioning MICHAEL WEITZMAN, MEGAN KAVANAUGH, AND TODD A. FLORIN Neurobehavioral Assessment in Studies of Exposures to Neurotoxicants DAVID C. BELLINGER From Animals to Humans: Models and Constructs DEBORAH C. RICE

363 Individual Differences in Interpersonal Relationships for Persons with Mental Retardation YONA LUNSKY Understanding Low Achievement and Depression in Children with Learning Disabilities: A Goal Orientation Approach GEORGIOS D. SIDERIDIS Motivation and Etiology-Specific Cognitive–Linguistic Profiles DEBORAH J. FIDLER The Role of Motivation and Psychopathology in Understanding the IQ–Adaptive Behavior Discrepancy ´ AND MARC J. TASSE SUSAN M. HAVERCAMP Behavior-Analytic Experimental Strategies and Motivational Processes in Persons with Mental Retardation WILLIAM V. DUBE AND WILLIAM J. MCILVANE A Transactional Perspective on Mental Retardation H. CARL HAYWOOD Index

Index

Volume 32

Volume 31

Research on Language Development and Mental Retardation: History, Theories, Findings, and Future Directions LEONARD ABBEDUTO, YOLANDA KELLER-BELL, ERICA KESIN RICHMOND, AND MELISSA M. MURPHY

The Importance of Cognitive–Motivational Variables in Understanding the Outcome Performance of Persons with Mental Retardation: A Personal View from the Early Twenty-First Century HARVEY N. SWITZKY Self-Determination, Causal Agency, and Mental Retardation MICHAEL L. WEHMEYER AND DENNIS E. MITHAUG The Role of Motivation in the Decision Making of Adolescents with Mental Retardation ISHITA KHEMKA AND LINDA HICKSON

Residential Services Research in the Developmental Disabilities Sector STEVE HOLBURN AND JOHN W. JACOBSON The Measurement of Poverty and Socioeconomic Position in Research Involving People with Intellectual Disability ERIC EMERSON, HILARY GRAHAM, AND CHRIS HATTON

364 The Influence of Prenatal Stress and Adverse Birth Outcome on Human Cognitive and Neurological Development LAURA M. GLYNN AND CURT A. SANDMAN Fluid Cognition: A Neglected Aspect of Cognition in Research on Mental Retardation CLANCY BLAIR AND MEGAN PATRICK Dietary Supplementation with Highly Unsaturated Fatty Acids: Implications for Interventions with Persons with Mental Retardation from Research on Infant Cognitive Development, ADHD, and Other Developmental Disabilities NATALIE SINN AND CARLENE WILSON Screening for Autism in Infants, Children, and Adolescents KYLIE M. GRAY, BRUCE J. TONGE, AND AVRIL V. BRERETON People with Mental Retardation and Psychopathology: Stress, Affect Regulation and Attachment: A Review CARLO SCHUENGEL AND CEES G. C. JANSSEN Diagnosis of Depression in People with Developmental Disabilities: Progress and Problems ANN R. POINDEXTER Index Volume 33 Developmental Epidemiology of Mental Retardation/Developmental Disabilities: An Emerging Discipline ROBERT M. HODAPP AND RICHARD C. URBANO Record Linkage: A Research Strategy for Developmental Epidemiology RICHARD C. URBANO Second-Order Linkage and Family Datasets SHIHFEN TU, CRAIG A. MASON, AND QUANSHENG SONG

contents of previous volumes Incorporating Geographical Analysis into the Study of Mental Retardation and Developmental Disabilities RUSSELL S. KIRBY Statistical Issues in Developmental Epidemiology and Developmental Disabilities Research: Confounding Variables, Small Sample Size, and Numerous Outcome Variables JENNIFER URBANO BLACKFORD Economic Perspectives on Service Choice and Optimal Policy: Understanding the Effects of Family Heterogeneity on MR/DD Outcomes STEPHANIE A. SO Public Health Impact: Metropolitan Atlanta Developmental Disabilities Surveillance Program RACHEL NONKIN AVCHEN, TANYA KARAPURKAR BHASIN, KIM VAN NAARDEN BRAUN, AND MARSHALYN YEARGIN-ALLSOPP Using GIS to Investigate the Role of Recreation and Leisure Activities in the Prevention of Emotional and Behavioral Disorders TINA L. STANTON-CHAPMAN AND DEREK A. CHAPMAN The Developmental Epidemiology of Mental Retardation and Developmental Disabilities DENNIS P. HOGAN, MICHAEL E. MSALL, AND JULIA A. RIVERA DREW Evolution of Symptoms and Syndromes of Psychopathology in Young People with Mental Retardation STEWART L. EINFELD, BRUCE J. TONGE, KYLIE GRAY, AND JOHN TAFFE Index Volume 34 Historical Overview of Assessment in Intellectual Disability STEPHEN R. SCHROEDER AND R. MATTHEW REESE Assessing Mental Retardation Using Standardized Intelligence Tests

contents of previous volumes BARBARA TYLENDA, JACQUELINE BECKETT, AND ROWLAND P. BARRETT Adaptive Behavior Scales DENNIS R. DIXON Educational Assessment MARK F. O’REILLY, BONNIE O’REILLY, JEFF SIGAFOOS, GIULIO LANCIONI, VANESSA GREEN, AND WENDY MACHALICEK Autism and Pervasive Developmental Disorders BART M. SEVIN, CHERYL L. KNIGHT, AND SCOTT A. BRAUD Psychopathology: Depression, Anxiety, and Related Disorders PETER STURMEY Psychotropic Medication Effect and Side Effects ERIK A. MAYVILLE Memory Disorders HEATHER ANNE STEWART AND HOLLY GARCIE-MERRITT Assessment of Self-Injurious and Aggressive Behavior JOHANNES ROJAHN, THEODORE A. HOCH, KATIE WHITTAKER, ´ LEZ AND MELISSA L. GONZA Social Skills JONATHAN WILKINS AND JOHNNY L. MATSON Self-Care Skills REBECCA L. MANDAL, BRANDI SMIROLDO, AND JOANN HAYNES-POWELL Feeding Disorders DAVID E. KUHN, PETER A. GIROLAMI, AND CHARLES S. GULOTTA

365 Volume 35 Theory and Research on Autism: Do We Need a New Approach to Thinking About and Studying This Disorder? THOMAS L. WHITMAN AND NAOMI EKAS Social Cognition in Children with Down Syndrome KATIE R. CEBULA AND JENNIFER G. WISHART The Development of Social Competence Among Persons with Down Syndrome: From Survival to Social Inclusion GRACE IAROCCI, JODI YAGER, ADRIENNE ROMBOUGH, AND JESSICA MCLAUGHLIN The Flynn Effect and the Shadow of the Past: Mental Retardation and the Indefensible and Indispensable Role of IQ JAMES R. FLYNN AND KEITH F. WIDAMAN Remaining Open to Quantitative, Qualitative, and Mixed-Method Designs: An Unscientific Compromise, or Good Research Practice? KEITH R. MCVILLY, ROGER J. STANCLIFFE, TREVOR R. PARMENTER, AND ROSANNE M. BURTON-SMITH Active Support: Development, Evidence Base, and Future Directions VASO TOTSIKA, SANDY TOOGOOD, AND RICHARD P. HASTINGS Child Abuse Among Children with Disabilities: What We Know and What We Need to Know MARISA H. FISHER, ROBERT M. HODAPP, AND ELISABETH M. DYKENS

Pain Assessment FRANK ANDRASIK AND CARLA RIME

Siblings of Children with Mental Retardation: The Role of Helping ELIZABETH MIDLARSKY, MARY ELIZABETH HANNAH, EREL SHVIL, AND AMANDA JOHNSON

Index

Index