International Review of Research in Mental Retardation, Volume 29

International Review of RESEARCH IN MENTAL RETARDATION VOLUME 29 Board of Associate Editors Philip Davidson UNIVERSIT...

Author: Laraine Masters Glidden

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International Review of RESEARCH IN MENTAL RETARDATION VOLUME 29

Board of Associate Editors Philip Davidson UNIVERSITY OF ROCHESTER MEDICAL CENTER

Elisabeth Dykens VANDERBILT UNIVERSITY

Michael Guralnick UNIVERSITY OF WASHINGTON

Linda Hickson COLUMBIA UNIVERSITY

Rathe Karrer UNIVERSITY OF KANSAS MEDICAL CENTER

Connie Kasari UNIVERSITY OF CALIFORNIA, LOS ANGELES

William McIlvane E. K. SHRIVER CENTER

Glynis Murphy LANCASTER UNIVERSITY

Ted Nettelbeck UNIVERSITY OF ADELAIDE

Marsha M. Seltzer UNIVERSITY OF WISCONSIN-MADISON

Jan Wallander SOCIOMETRICS CORPORATION

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

VOLUME 29

Elsevier Academic Press 525 B Street, Suite 1900, San Diego, California 92101-4495, USA 84 Theobald’s Road, London WC1X 8RR, UK

This book is printed on acid-free paper. Copyright ß 2004, Elsevier Inc. All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the Publisher. The appearance of the code at the bottom of the first page of a chapter in this book indicates the Publisher’s consent that copies of the chapter may be made for personal or internal use of specific clients. This consent is given on the condition, however, that the copier pay the stated per copy fee through the Copyright Clearance Center, Inc. (www.copyright.com), for copying beyond that permitted by Sections 107 or 108 of the U.S. Copyright Law. This consent does not extend to other kinds of copying, such as copying for general distribution, for advertising or promotional purposes, for creating new collective works, or for resale. Copy fees for pre-2004 chapters are as shown on the title pages. If no fee code appears on the title page, the copy fee is the same as for current chapters. 0074-7750/2004 $35.00 Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone: (þ44) 1865 843830, fax: (þ44) 1865 853333, E-mail: [email protected]. You may also complete your request on-line via the Elsevier homepage (http://elsevier.com), by selecting ‘‘Customer Support’’ and then ‘‘Obtaining Permissions.’’ For all information on all Academic Press publications visit our Web site at www.academicpress.com ISBN: 0-12-366229-X PRINTED IN THE UNITED STATES OF AMERICA 04 05 06 07 08 9 8 7 6 5 4 3 2 1

Contents

Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Behavioral Phenotypes: Going Beyond the Two-Group Approach Robert M. Hodapp I. II. III. IV.

How do Persons with Mental Retardation Differ from One Another? . . . . . . . . . . Behavioral Phenotypes: Current Definitions and Findings . . . . . . . . . . . . . . . . . . . . . . The Future: Five Unresolved Issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 6 11 24 25

Prenatal Drug Exposure and Mental Retardation Robert E. Arendt, Julia S. Noland, Elizabeth J. Short, and Lynn T. Singer I. II. III. IV. V. VI.

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Findings from Early Prenatal Cocaine Exposure Studies . . . . . . . . . . . . . . . . . . . . . . . Direct and Indirect Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prenatal Drug Exposure and the Etiology of Mental Retardation . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

v

31 35 37 41 52 53 56

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contents Spina Bifida: Genes, Brain, and Development Jack M. Fletcher, Hope Northrup, Susan H. Landry, Larry A. Kramer, Michael E. Brandt, Maureen Dennis, Marcia A. Barnes, Susan E. Blaser, H. Julia Hannay, Kim Copeland, and David J. Francis

I. II. III. IV.

Nature of Spina Bifida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A Multi-Disciplinary Research Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overall Outcomes in School-Age Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neural Phenotype of SBM: Relationships with Cognitive and Motor Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Developmental Factors: A Life Span Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65 69 80 86 95 109 111

The Role of the Basal Ganglia in the Expression of Stereotyped, Self-Injurious Behaviors in Developmental Disorders Howard C. Cromwell and Bryan H. King I. II. III. IV.

The BG System: Function and Dysfunction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . BG Pathology and Developmental Disorders. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Animal Models of Stereotyped Self-Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Directions and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

120 130 132 141 144

Risk Factors for Alzheimer’s Disease in Down Syndrome Lynn Ward I. II. III. IV. V.

Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Apolipoprotein E Genotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Brain Reserve Capacity Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gender and Estrogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Folate Metabolism, B-Group Vitamins, and Risk of AD In DS: A Hypothesis in Search of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

161 164 170 177 184 186 187

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contents 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 I. II. III. IV. V.

Developmental Delays during Infancy and Early Childhood. . . . . . . . . . . . . . . . . . . . The Emergence of Mild Mental Retardation and Learning Disabilities . . . . . . . . . The Importance of Early Parenting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pathways to Developmental Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

199 203 206 210 223 225

The Ecological Context of Challenging Behavior in Young Children with Developmental Disabilities Anita A. Scarborough and Kenneth K. Poon I. II. III. IV. V. VI.

Challenging Behavior and Children with Developmental Disabilites . . . . . . . . . . . . The Ecological Context of Challenging Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Environtype: The Ecological Context of Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interaction: Transactional Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . An Ecological Model of Intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

229 232 235 239 245 252 253

Employment and Intellectual Disability: Achieving Successful Employment Outcomes Kaye Smith, Lynne Webber, Joseph Graffam, and Carlene Wilson I. Perceptions of Disablity Including Intellectual Disability at the Macro Level and Implications for Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Practices that Promote Successful Employment Outcomes for People with Intellectual Disability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Maximizing the Achievement of Successful Employment Outcomes: Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

263 269 281 282 283

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contents Technology Use and People with Mental Retardation Michael L. Wehmeyer, Sean J. Smith, Susan B. Palmer, Daniel K. Davies, and Steven E. Stock

I. Importance of Technology Use to People with Mental Retardation. . . . . . . . . . . . . II. User Characteristics Associated with Mental Retardation that Impact Technology Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Technology Use By People with Mental Retardation . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

293

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contents of Previous Volumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

339

300 311 330

353

Contributors

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

Robert E. Arendt (31), The Buckeye Ranch, Grove City, Ohio 43123 Marcia A. Barnes (63), Department of Psychology, The Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada Susan E. Blaser (63), Department of Psychology, The Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada John G. Borkowski (197), Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556 Michael E. Brandt (63), Department of Pediatrics, University of Texas Health Science Center at Houston, Houston, Texas 77030 Kim Copeland (63), Department of Psychology, University of Houston, Houston, Texas 77030 Howard C. Cromwell (119), Department of Psychology, Bowling Green State University, Bowling Green, Ohio 43403 Daniel K. Davies (291), Ablelink Technologies Colorado Springs, Colorado Maureen Dennis (63), Department of Psychology, The Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada Jack M. Fletcher (63), Department of Pediatrics, University of Texas Health Science Center at Houston, Houston, Texas 77030 David J. Francis (63), Department of Psychology, University of Houston, Houston, Texas 77030

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x

contributors

Joseph Graffam (261), School of Health Sciences, Deakin University, Burwood, 3125 Victoria, Australia H. Julia Hannay (63), Department of Psychology, University of Houston, Houston, Texas 77030 Robert M. Hodapp (1), John F. Kennedy Center for Research on Human Development, Vanderbilt University, Nashville, Tennessee 37203 Deborah A. Keogh (197), Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556 Bryan H. King (119), Dartmouth Medical School, Lebanon, New Hampshire 03756 Larry A. Kramer (63), Department of Pediatrics, University of Texas Health Science Center at Houston, Houston, Texas 77030 Susan H. Landry (63), Department of Pediatrics, University of Texas Health Science Center at Houston, Houston, Texas 77030 Jennifer Burke Lefever (197), Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556 Julie J. Lounds (197), Waisman Center, University of WisconsinMadison, Madison, Wisconsin 53705 Julia S. Noland (31), School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106 Christine Willard Noria (197), Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556 Hope Northrup (63), Department of Pediatrics, University of Texas Health Science Center at Houston, Houston, Texas 77030 Susan B. Palmer (291), Department of Special Education, University of Kansas, Lawrence, Kansas 66045 Kenneth K. Poon (229), Child Development Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 Anita A. Scarborough (229), Child Development Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 Elizabeth J. Short (31), School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106

contributors

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Lynn T. Singer (31), School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106 Kaye Smith (261), School of Health Sciences, Deakin University, Burwood, 3125 Victoria, Australia Sean J. Smith (291), Department of Special Education, University of Kansas, Lawrence, Kansas 66045 Steven E. Stock (291), Ablelink Technologies Colorado Springs, Colorado Lynn Ward (159), Department of Psychology, University of Adelaide, Adelaide 5005, Australia Lynne Webber (261), School of Health Sciences, Deakin University, Burwood, 3125 Victoria, Australia Keri Weed (197), Department of Psychology, University of South Carolina, Aiken, Aiken, South Carolina Michael L. Wehmeyer (291), Department of Special Education, University of Kansas, Lawrence, Kansas 66045 Thomas L. Whitman (197), Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556 Carlene Wilson (261), Department of Psychology, University of Adelaide, Adelaide 5005, Australia

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Preface

Volume 29 follows two themed volumes, #27 on Language and #28 on Motivation. It is meant to be wide-ranging, and it fulfills that intention with chapters that extend from a focus on the role of basal ganglia in stereotyped and self-injurious behaviors (Chapter 4) to factors relating to successful employment outcomes (Chapter 8). Volume 29 is also the first of several volumes in which one or more lead chapters will assume a historical approach to understanding the development and trajectory of different research domains. This feature was stimulated by the 2003 theme of the Gatlinburg Conference on Research and Theory in Intellectual and Developmental Disabilities. In that year, keynote speakers were asked to address the past, present and future of research in their respective research areas. Chapter 1 in the current volume is developed from an address by Bob Hodapp, Behavioral Phenotypes: Going Beyond the Two-group Approach, delivered at the Gatlinburg, 2003 conference. In this chapter, he traces the origins of the current explosion of research in behavioral phenotypes, documenting its seeds in the recognition that there were at least two ‘‘types’’ of mental retardation, a type with and a type without obvious organic etiology. Importantly, Hodapp points out that with the recognition of more than 1000 known genetic mental retardation syndromes, it is essential that we integrate what we know across conditions and with knowledge of genebrain-behavior connections. In Chapter 2, authors Bob Arendt, Julia Noland, Elizabeth Short, and Lynn Singer focus on a related behavioral phenomenon—behavioral teratology—the effect of prenatal drug exposure on postnatal behavior. Following a review of recent research on the effects of prenatal cocaine exposure on postnatal behavior, they conclude that cocaine is likely a behavioral teratogen, but that both prenatal and postnatal environments can moderate its influence, and must enter any model of cocaine’s effects.

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Genes, brain and development are also a focus in Chapter 3, with particular attention to spina bifida. Jack Fletcher and co-authors Maureen Dennis, Hope Northrup, Marcia Barnes, H. Julia Hannay, Susan Landry, Kim Copeland, Susan Blaser, Larry Kramer, Michael Brandt, and David Francis focus on describing developmentally a modal profile of persons with spina bifida. They examine cognitive strengths as well as impairments, and conclude that both are stable over the lifespan. A fascinating finding and one that is likely to generate extensive additional investigation is that longknown motor deficits of persons with spina bifida may not be exclusively movement disorders, but also impairments of timing. Chapter 4, co-authored by Howard Cromwell and Bryan King, like Chapter 3, is concerned with brain-behavior relations. Using data from both animal and human studies, the authors conclude that the basal ganglia system is critical in a broad spectrum of developmental disorders that lead to self-injurious behaviors. They convince us (as if we needed to be convinced) that animal models are an essential tool in leading to our understanding of how the timing and location of damage to neural systems results in specific self-injurious behaviors. Although there is an animal model of Down syndrome, Lynn Ward, in her chapter on Risk Factors for Alzheimer’s Disease in Down Syndrome, reviews almost exclusively the results of research with humans. She concludes that findings strongly support the role of age and the role of the ApoE genotype. One allele is associated with increased risk and another allele with decreased risk. In addition, Ward notes that there are other hypotheses, such as altered folate metabolism and individual differences in vulnerability to oxidative damage that have not yet received adequate examination. Thus, we still have much research to do before we can identify treatment approaches that might actually alter the risk of Alzheimer’s in persons with Down syndrome. Chapters 1–5 rely heavily on biobehavioral models and research in their investigation of mental retardation and developmental disability. Chapters 6–9, on the other hand, identify social, educational, and economic environments as important components of the dimensions of mental retardation that their research reviews summarize. For example, in Chapter 6, Precursors of Mild Mental Retardation in Children with Adolescent Mothers, John Borkowski, Julie Lounds, Christine Willard Noria, Jennifer Lefever, Keri Weed, Deborah Keogh, and Tom Whitman, describe a decade of research on cognitive and socioemotional outcomes for first-born children of adolescent mothers. They demonstrate that these children are likely to experience poor parenting from their cognitively ill-prepared mothers. This poor parenting is associated with developmental delays in cognitive,

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emotional and adaptive behavior domains, and in elementary school, these children are at risk for academic failure. Borkowski et al. conclude with suggestions about how intervention programs should be designed to reduce their risk of intellectual disability. Anita Scarborough and Kenneth Poon are also interested in the efficacy of early intervention in their chapter on The Ecological Context of Challenging Behavior in Young Children with Developmental Disabilities. And, like Borkowski et al., they reinforce the importance of the early interactions between child and caregiver as critical in trying to reduce the likelihood of challenging behavior in children with developmental disabilities. Although they acknowledge the role of innate or genotypic factors in the development of these behaviors, they focus on learned behaviors and behavioral patterns that reflect the transaction between inherent and learned behaviors. Chapters 8 and 9 reach out to environments that are extraordinarily varied and complex. In their chapter on Employment and Intellectual Disability: Achieving Successful Employment Outcomes, Kaye Smith, Carlene Wilson, Lynne Webber, and Joseph Graffam tackle a critical lifespan issue. Using Bronfenbrenner’s Ecological Systems Theory, they argue that in order to achieve successful employment outcomes, supports must be provided at all levels from the microsystem to macrosystem. They also conclude that, for the most part, low rates of employment are typical for persons with intellectual disability. Improvement will likely require changes at all levels of the system. Michael Wehmeyer, Sean Smith, Susan Palmer, Daniel Davies, and Steven Stock, in their chapter, Technology Use and People with Mental Retardation, provide suggestions as to how various outcomes (including employment) may be facilitated by technology. However, after a thorough review of the literature on technology and developmental disability, they conclude that much of its potential is yet to be realized. They suggest that technology developers and users as well as policy makers will all need to contribute to convert more of the potential into actual benefit. As usual, the publication of an edited volume is the work of the visible and the not so visible. The visible are those whose names appear on chapters as contributors, and next to the title page, identified as Associate Editors, and, of course, the Editor. But both I as Editor, and the Associate Editors, who invited and oversaw the review of several chapters, are reliant on the invisible, those individual reviewers whose dedication and expertise were essential for the production of this volume. The following individuals, listed alphabetically, all contributed invaluable commentary that helped make these chapters as good as they are: Kaarin Anstey, Clancy Blair, Sharon Borthwick-Duffy, Josephine Brown, Janet Bryan, Mike Guralnick,

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Sandra Jacobson, Tom Keating, Neil Kirby, Michael Levine, Mark Lewis, Edmund LoPresti, Trevor Parmenter, Karen Wills, and Keith Yeates. Thank you, all. LARAINE MASTERS GLIDDEN

Behavioral Phenotypes: Going Beyond the Two-Group Approach ROBERT M. HODAPP JOHN F. KENNEDY CENTER FOR RESEARCH ON HUMAN DEVELOPMENT VANDERBILT UNIVERSITY NASHVILLE, TENNESSEE

Examined by almost any indicator, research on behavioral phenotypes is exploding. Over the past few years, articles on behavioral phenotypes have appeared in journals of psychiatry (McElwee & Bernard, 2002), child psychiatry (Dykens & Hodapp, 2001), special education (Hodapp & Fidler, 1999), and medical genetics (Finucane et al., 2003). Recent meetings of the Gatlinburg Conference on Research in Mental Retardation have featured behavioral phenotypes as their theme, and the British-based Society for the Study of Behavioural Phenotypes has been thriving for many years. In 2002, O’Brien edited the ﬁrst book devoted to clinical issues for persons with diVerent genetic disorders; previously, two other books examined the behavioral eVects of such disorders (Dykens et al., 2000; O’Brien & Yule, 1995). Finally, funding patterns of agencies such as the National Institute of Child Health and Human Development (NICHD) may favor more ‘‘etiology-based’’ approaches to behavioral research (Baumeister et al., 1997). Therefore, in many ways, behavioral phenotypes are ‘‘in the air.’’ Often obscured in this excitement are questions of history, deﬁnition, and future potential. Speciﬁcally, how did research on behavioral phenotypes come about and what, exactly, is the meaning of this term? How might such research proceed in the future, and what might we learn as a result? This chapter attempts to ﬁll these gaps. Beginning with a brief history of the attempts to diVerentiate by etiology, I will then tackle the diVering deﬁnitions of behavioral phenotypes and provide a few examples. The remainder of the chapter will discuss ﬁve directions for future behavioral phenotypic research. Although at present it is barely outlined, the picture is rapidly becoming clearer of what we may be able to understand in the next 20 or 30 years. # 2004 Elsevier Inc. INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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Copyright 2004, Elsevier Inc. All rights reserved.

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Robert M. Hodapp I.

HOW DO PERSONS WITH MENTAL RETARDATION DIFFER FROM ONE ANOTHER?

Discussions of behavioral phenotypes begin with the observation that persons with mental retardation diVer from one another. To anyone dealing with persons with mental retardation, this statement is obvious. The more diYcult—and contested—question concerns how they diVer. What is the best way to categorize persons with mental retardation? Historically, two general strategies have been attempted (Hodapp & Dykens, 1994). In the ﬁrst strategy, persons with mental retardation are grouped according to their degrees of intellectual impairment. Thus, we see the mild, moderate, severe, and profound levels of mental retardation found in most behavioral research. Even today, most studies published in the American Journal on Mental Retardation (AJMR), Mental Retardation, and the Journal of Intellectual Disability Research examine groups of individuals who have similar degrees of intellectual impairment. The second strategy is the focus of this chapter. In contrast to the degreeof-impairment perspective, this strategy diVerentiates by the cause of a person’s mental retardation. Although an etiology-based approach remains less common in mental retardation behavioral research, its popularity is growing. A.

History

In one form or another, etiology-based approaches have existed for over a century. In his initial paper, Langdon Down (1866; Dunn, 1991) pointed to several behavioral characteristics of individuals with Down syndrome. He noted that persons with Down syndrome ‘‘have a considerable power of imitations,’’ that speech is oftentimes ‘‘thick and indistinct,’’ and that many persons show a tendency to regress in development. Although remembered for identifying features of the syndrome that were physical (epicanthal folds) and medical (shortened life expectancy), Down’s reports also emphasized several of the syndrome’s behavioral aspects. In a more global sense, for many years researchers have pointed to diVerences between those with ‘‘organic’’ forms of mental retardation and those without (Burack, 1990). As early as 1914, Pearson and Jaederholm noted how the IQ scores of children considered to be ‘‘feebleminded’’ (i.e., to have mild mental retardation) showed considerable overlap with children in the normal range. In subsequent years, Lewis (1933), Strauss and Lehtinen (1947), and Penrose (1949) all considered the possibility that mental retardation might consist of two distinct types. In the early 1960s, Dingman and Tarjan (1960) further expanded on this idea by noting that by the laws of

BEHAVIORAL PHENOTYPES

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Gaussian distributions alone, there were ‘‘too many’’ persons with mental retardation at the lowest IQ levels. By the mid-1960s, researchers had long discussed two groups of persons with mental retardation. Proponents of this perspective held that one type of mental retardation featured persons who showed no identiﬁable cause for their mental retardation. These persons were akin to Pearson and Jaederholm’s feebleminded subjects, in that they were oftentimes more mildly impaired, and tended to blend in with other, non-retarded persons. To this day, no one knows what causes mental retardation in this group, although causes probably range from polygenetic inheritance to environmental deprivation (or over-stimulation) (Hodapp, 1994). DiVerent persons also may have diVerent polygenic or environmental causes, or there may be an interplay between the two. This type of mental retardation has been referred to as: familial, cultural-familial, or sociocultural familial; non-organic, non-speciﬁc, or undiVerentiated; and mental retardation due to environmental deprivation. Even this listing of names hints at the wildly discrepant beliefs about the causes of mental retardation in these individuals. In contrast to those with cultural-familial mental retardation, other individuals show one or more organic causes for their mental retardation. Such causes include hundreds of separate organic insults. These insults can occur prenatally, perinatally, or postnatally. Prenatal causes include all of the 1000þ genetic mental retardation disorders, fetal alcohol syndrome (FAS), fetal alcohol eVects (FAE), and rubella, as well as all accidents in utero. Perinatal causes include prematurity, anoxia at birth, and other birthrelated complications. Postnatal causes range from sicknesses (meningitis) to head trauma. But for each person in this group, a clear, organic cause is present. In addition, those with organic mental retardation are more likely to show greater degrees of intellectual impairments; in most surveys, as IQ levels decrease, increasingly higher percentages of persons show an identiﬁable organic cause (Stromme & Hagberg, 2000). B.

Zigler’s Two-Group Approach

Seen in this light, Edward Zigler’s two-group approach followed in a clear historical line. Zigler (1967, 1969) argued that the population with mental retardation was comprised of two distinct types of individuals—those whose mental retardation was caused by a speciﬁc organic etiology, and those in which the ‘‘usual’’ (genetic and environmental) causes were operating. This latter group, which Zigler referred to as having familial mental retardation, could be considered to constitute the lower portion of the normal or Gaussian distribution of intelligence.

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Although various workers had noted the existence of the two groups of persons with mental retardation, Zigler was the ﬁrst to make clear behavioral distinctions. In terms of behavioral development, children with familial—but not necessarily with organic—mental retardation were predicted to show both sequences and structures similar to those shown by typically developing children. Thus, the so-called similar-sequence hypothesis predicted that children with (familial) mental retardation should, like typically developing children, proceed in order through Piagetian or other normative stages of development. For the most part, this similar sequence hypothesis has held true, even with children with various organic forms of mental retardation (e.g., Weisz & Zigler, 1979). The second prediction—the similar structure hypothesis—concerned the structure of cognitive-linguistic abilities from one domain to another. Speciﬁcally, Zigler held that familial mental retardation was not caused by any ‘‘defect’’ or ‘‘deﬁcit’’ related to a single area of functioning. Instead, children with familial mental retardation were predicted to show a more generalized delay—aVecting all areas of development to similar degrees—as evidenced by even or ﬂat developmental proﬁles (at the child’s mental-age level). Substantial contradictory evidence exists concerning the similar structure hypothesis, some even for children with familial mental retardation (e.g., Mundy & Kasari, 1990; Weiss et al., 1986; Weisz, 1990). And what about children with organic mental retardation? Here Zigler hedged his bets, feeling that children with organic mental retardation might not follow universal sequences (similar sequence hypothesis) or show ﬂat or even developmental proﬁles (similar structure hypothesis). To quote Zigler (1969): If the etiology of the phenotypic intelligence (as measured by IQ) of two groups diVers, it is far from logical to assert that the course of development is the same, or that even similar contents in their behaviors are mediated by exactly the same cognitive processes (p. 533; italics added).

Examined with today’s standards, one could criticize several aspects of this two-group approach. First, the approach assembles into a single organic group individuals with many diVerent types of mental retardation. In Zigler’s defense, his Science article appeared in 1967, a scant eight years after Lejeune et al. (1959) discovered that Down syndrome was caused, in most cases, by a third chromosome 21. Genetic knowledge and technology were then in their infancy, and the identiﬁcation of most genetic disorders was decades away. By the late 1980s, however, Zigler and his colleagues were beginning to question the utility of classifying so many separate etiologies into a single

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organic group. Noting diVerent IQ trajectories in children with Down syndrome, cerebral palsy, and boys with fragile X syndrome, Burack et al. (1988) suggested diVerentiating the organic category. Not only was the organic group comprised of children with many separate etiologies, but these etiologies might also lead to diVerent, etiology-related behaviors. C.

Negative Reactions to Etiology-Based Classifications

In considering the history of the two-group approach, it is important to not lose sight of the wider ﬁeld of behavioral research in mental retardation. In contrast to adherents of the two-group approach, until recently most behavioral researchers did not believe that etiology matters for the behavior of persons with mental retardation. Such inattention to etiology shows itself in two ways: 1) from writings of prominent researchers, and 2) from content surveys of behavioral research. Citing just a few representative comments is illustrative. Over 30 years ago, Ellis (1969) concluded that: ‘‘Rarely have behavioral diVerences characterized diVerent etiological groups’’ (p. 561). In the early 1980s, MacMillan (1982) asserted that: ‘‘There is now considerable skepticism as to the usefulness of classifying mental retardation by form . . . ’’ (p. 60). More recently, in regard to etiology’s role in educational practice, Kahn (1988), Blackhurst and Berdine (1993), and Hallahan and KauVman (2000) have all argued against the importance of genetic etiology. More telling, perhaps, are the ways in which behavioral research studies are performed in mental retardation. Figure 1 displays the results of classifying articles in the AJMR (until 1987 called the American Journal of Mental Deﬁciency) at three time points: from 1975–1980, from 1985–1990, and from 1995–2000. For each ﬁve year span, the ﬁgure shows the percentage of behavioral research articles that examined individuals with ‘‘mixed mental retardation.’’ All of the other studies were considered to be ‘‘etiologyoriented.’’ Such studies included any in which at least one of its research groups was described as having organic mental retardation, Down or other genetic syndrome, or phenylketonuria (PKU), FAS, or other organic condition. In examining Figure 1, a few matters become clear. First, the two earlier periods show relatively small percentages of etiology-related articles—<10% from 1975 to 1980, 13% from 1985 to 1990. In contrast, more recent years have seen greater attention to etiology. By the 1995–2000 period (and continuing until today), almost one-third of AJMR articles examined persons with one or another organic condition. In addition, and not observable in the ﬁgure itself, much of this recent interest in etiology relates to behavioral studies on persons with a wider variety of genetic and non-genetic disorders. In contrast to the earlier focus on Down syndrome and PKU, researchers in

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FIG. 1. Percentage of articles, by type, in the American Journal on Mental Retardation, 1975–1980, 1985–1990, and 1995–2000.

recent years have produced studies on many genetic syndromes, as well as on FAS, FAE, and other organic-but-not-genetic conditions. The number of articles on fragile X, Prader-Willi, Williams, Rett, and Down syndromes has increased markedly from the 1980s to the 1990s (Dykens & Hodapp, 2001). With this explosion of interest and broader research focus, it has become increasingly important to highlight current issues in behavioral studies of persons with genetic mental retardation disorders.

II. BEHAVIORAL PHENOTYPES: CURRENT DEFINITIONS AND FINDINGS First coined by Nyhan (1972), the term ‘‘behavioral phenotype’’ refers to the behavioral outcomes of diVerent genetic mental retardation disorders. In Nyhan’s original address to the Society for Pediatric Research, he used the term in reference to self-mutilation in both Lesch-Nyhan and Cornelia de Lange syndromes. More recently, Nyhan (1995) noted that: ‘‘Behavioral phenotypes are recognizable patterns of behavior—syndromes, if you will, of behavior’’ (p. ix). He further stated that: ‘‘The importance of the recognition that a stereotyped or reproducible pattern of behavior accompanies a disease deserves emphasis’’ (Nyhan, 1995, p. ix). Such a deﬁnition is both helpful and unhelpful. On one hand, it emphasizes the importance of genetic disorders on behavioral outcomes. Just as diVerent

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genetic anomalies produce physical or medical outcomes, there are also phenotypes related to behavior. But in another sense, Nyhan’s deﬁnition never explains what constitutes a behavioral phenotype. Thus, even though the term behavioral phenotype has been widely used over many years, its exact meaning remains vague to many behavioral researchers. A.

Definitions and Issues

One way to understand behavioral phenotypes is to contrast two competing deﬁnitions. The ﬁrst, more deterministic deﬁnition is provided by Flynt and Yule (1994), who argue that: ‘‘a behavioural phenotype should consist of a distinct behavior that occurs in almost every case of a genetic or chromosomal disorder, and rarely (if at all) in other conditions’’ (p. 666). In contrast, Dykens (1995) proposes a more probabilistic deﬁnition. According to this second deﬁnition, a behavioral phenotype involves: ‘‘the heightened probability or likelihood that people with a given syndrome will exhibit certain behavioral and developmental sequelae relative to those without the syndrome’’ (p. 523). Table I compares these deﬁnitions on two key dimensions. This comparison highlights the advantages of the probabalistic deﬁnition for both research and intervention. A probabilistic view better accounts for the complex movement from genes, to brain, to behavior over development (and considering transactions with the environment). Three main aspects of this probabilistic deﬁnition deserve recognition. 1. Many, but not all, individuals with a given syndrome will show the syndrome’s ‘‘characteristic’’ behaviors. Rarely are etiology-related behaviors found in every person with a particular syndrome. Consider the case of Down syndrome. Even compared to their overall mental ages, children and adults with Down syndrome generally show deﬁcits in linguistic grammar TABLE I Contrasts Between the Two Major Denitions of the Term ‘‘Behavioral Phenotype’’ Deterministic Genetic disorders aVect behavior ‘‘in almost every case’’

Behavior(s) is unique to one syndrome

Probabilistic Genetic disorders predispose individuals to certain behavior(s)—not every individual shows the disorder’s ‘‘characteristic’’ behavior(s) Behavior(s) is sometimes unique to a single syndrome; behaviors often seen in more than one syndrome

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(Chapman & Hesketh, 2000; Fowler, 1990) and often show receptive language abilities in advance of expressive abilities (Miller, 1999). In addition, approximately 95% of mothers of children with Down syndrome report that others have diYculty in understanding their child’s articulation of words and phrases (Kumin, 1994). Despite such commonly observed deﬁcits, not every person with Down syndrome shows particular diYculties in grammar, articulation, or expressive language. Rondal (1995) reported the case of Franc˛oise, a 32-year old woman with Down syndrome whose IQ was 64. Even though Franc˛oise has trisomy 21, she nevertheless utters such long and complex sentences as: ‘‘And that does not surprise me because dogs are always too warm when they go outside’’ (‘‘Et c˛a m’etonne´ pas parce que les chiens ont toujours trop chaud quand ils vont a` la port’’; Rondal, 1995, p. 117). Although grammatical, articulatory, and expressive language problems may be common in Down syndrome, not every person with the syndrome shows such behavioral characteristics. 2. Some etiology-related behaviors will be unique to a single syndrome, whereas others are common to two or more syndromes. The second question considers whether, as asserted by Flynt and Yule (1994), an etiology-related distinctive behavior should occur ‘‘rarely (if at all) in other conditions.’’ In fact, connections between genetic syndromes and speciﬁc outcomes appear to be of at least two types. In the ﬁrst, unique pattern, a genetic syndrome results in a particular outcome that is seen in no other genetic disorders. At present, the following seem unique to a single syndrome: In Prader-Willi syndrome, extreme hyperphagia (over-eating; Dykens, 1999); In 5p-syndrome, the ‘‘cat-cry’’ (Gersh et al., 1995); In Lesch-Nyhan syndrome, extreme self-mutilation (Anderson & Ernst, 1994); In Rett syndrome, stereotypic ‘‘hand-washing’’ or ‘‘hand-wringing’’ (Van Acker, 1991); and In Smith-Magenis syndrome, body ‘‘self-hugging’’ (Finucane et al., 1994) and putting objects into bodily oriﬁces (Greenburg et al., 1996). Obviously, this list is quite short; there are probably only a few instances in which a genetic disorder is unique in its behavioral eVects. Flynt and Yule (1994) also noted this peculiarity, nominating as unique (by their deﬁnition, as examples of a behavioral phenotype) only the self-mutilating behaviors in Lesch-Nyhan syndrome, overeating and abnormal food-seeking behavior in Prader-Willi syndrome, and the hand-wringing in Rett syndrome (p. 667). Although Flynt and Yule also propose a few other examples in which a

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behavior might be unique to one syndrome, such 1:1 correspondences seem relatively rare. Rather, in most cases, two or more syndromes show a particular behavior more than in most persons with mental retardation (Hodapp, 1997). To give a few examples of such ‘‘partial speciﬁcity,’’ a particular advantage in simultaneous (i.e., holistic, Gestalt-like) processing compared to sequential (step-by-step) processing occurs in children with Prader-Willi syndrome (Dykens et al., 1992) and in boys with fragile X syndrome (Dykens et al., 1987; Kemper et al., 1988). Similarly, compared to groups with mental retardation in general, hyperactivity is more frequently found in children with 5p-syndrome (Dykens & Clarke, 1997) and in boys with fragile X syndrome (Baumgardner et al., 1995). In both instances, a pattern of strength and weakness or a particular type of maladaptive behaviorpsychopathology is noted in several genetic disorders to much greater degrees (or in higher percentages of individuals) than is found among others with mental retardation. Finally, the idea of partially speciﬁc behavioral eVects seems more in line with current thinking in many areas of genetics, child psychiatry, and psychiatry. Across these diVerent disciplines, researchers are now discussing the multiple pathways—both genetic and environmental—by which one comes to have a particular psychiatric disorder. For example, it now appears that no single gene nor any single environment will cause depression, or autism, or any psychiatric condition. Instead, many diVerent pathways—involving both multiple genes and multiple environments (acting together and separately, over development)—will all result in a single outcome (e.g., depression). There will not, in short, be one route to depression, but many routes. Or, as the clinical geneticist John Opitz (1985) noted: ‘‘The causes are many, but the common developmental pathways are few’’ (p. 9). 3. Etiology-related behaviors occur across many behavioral domains. Behavioral phenotypes can be found in many diVerent domains. Although to date most work has focused on either maladaptive behavior-psychopathology or language, behavioral manifestations of genetic mental retardation disorders are also apparent in many other domains. Proﬁles of cognition and language, of adaptive behavior, of personality, and of social behaviors, all fall within the purview of behavioral outcomes that often result in persons with a particular genetic syndrome. Sometimes such outcomes can even include a single, individual behavior such as the self-hug in Smith-Magenis syndrome or the cat-cry in 5p-syndrome. At times what is of interest is not a single behavior per se, but a pattern of strengths and weaknesses, connected or disconnected behaviors, or other patterns seen in one or a few syndromes more often than in others with mental retardation.

10 B.

Robert M. Hodapp A Modern Example: Cognitive-Linguistic Profiles in Prader-Willi Syndrome and Williams Syndrome

Although a comprehensive review of etiology-related behaviors is beyond the scope of this chapter (Dykens et al., 2000), a single example will suYce. This example contrasts the cognitive-linguistic proﬁles of two disorders: Prader-Willi syndrome and Williams syndrome. 1. HIGH VISUAL-SPATIAL SKILLS IN PRADER-WILLI SYNDROME

Prader-Willi syndrome has long been known for its maladaptive behavior. Most individuals with the syndrome show hyperphagia; the most common cause of death is diabetes and heart and other medical problems often associated with extreme obesity (Butler et al., 2002). But most individuals with Prader-Willi syndrome also show an etiologyrelated cognitive proﬁle. More than a decade ago, Dykens et al. (1992) identiﬁed the relative strengths in adolescents and young adults with Prader-Willi syndrome using the Kaufman Assessment Battery for Children, or K-ABC. In contrast to other IQ tests, the K-ABC divides intelligence into two domains: simultaneous (or Gestalt) processing and sequential (or step-by-step) processing. Testing a small group of adolescents and young adults, Dykens et al. (1992) found that age-equivalent levels of simultaneous processing were almost two years higher than levels of sequential processing. In addition to this relative strength in simultaneous processing, children with Prader-Willi syndrome are often reported to be adept at jigsaw puzzles. In the early 1990s before the development of ﬂourescent in situ hybridization (FISH) and other molecular genetic techniques, Holm et al. (1993) even included high-level abilities in jigsaw puzzles as one of several supportive criteria leading to the diagnosis of Prader-Willi syndrome. Recently, Dykens (2002) examined the jigsaw puzzle abilities of children with Prader-Willi syndrome. In one part of the study, children with PraderWilli syndrome were compared to mental age-matched children with heterogeneous causes for their mental retardation. In a second part, the Prader-Willi group was compared to typically developing children of the same chronological age (typical chronological age-matches). As might be expected, children with Prader-Willi syndrome outperformed children with mental retardation of similar mental ages. More surprising, however, was the comparison to typically developing children of the same chronologic age. Subjects in the Prader-Willi group placed together almost three times as many puzzle pieces as their typically developing age-mates (28 vs. 10 pieces, respectively). Children with Prader-Willi syndrome seem spared in—even exceptionally good at—assembling jigsaw puzzles.

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2. LOW VISUAL-SPATIAL SKILLS IN WILLIAMS SYNDROME

Starting in the late 1980s, Williams syndrome began to be known for a pattern of relatively spared language abilities (Bellugi et al., 1988). Certain individual cases even led some investigators to imply that all (or most) children with Williams syndrome might be spared in their linguistic skills, functioning at or above levels predicted by their chronological ages. More recent studies have questioned this view. It now appears that some children do show language levels consistent with their chronological ages, but this percentage is only about 5% of all children with Williams syndrome (Bishop, 1999). For the population as a whole, relative strengths are noted compared to overall mental ages, but such relative strengths are much below children’s chronological ages. In one study of 127 children and adults with Williams syndrome, Mervis et al. (1999) noted that the average Peabody Picture Vocabulary Test-Revised (PPVT-R) (i.e., vocabulary) standard score for their entire sample was 66.50. This score was much below a standard score of 100. In contrast, children with Williams syndrome show a relative weakness in the various aspects of visuospatial functioning. These children have particular diYculties in drawing (Bihrle et al., 1989; Dykens et al., 2001) and in reproducing patterns of blocks or other patterns on IQ tests. In the Mervis et al. (1999) studies using the pattern construction subtest of the DiVerential Abilities Scales (DAS) (Elliott, 1990), 88% of individuals with Williams syndrome scored at the ﬁrst percentile. Children and adults with Williams syndrome show particular diYculties on any task that requires them to construct a visuospatial array. Although other examples could be chosen, the contrast between cognitivelinguistic proﬁles in Prader-Willi syndrome and Williams syndrome provides an essence of the recent etiology-related studies. At this point, one could argue that the ﬁeld has identiﬁed at least the major behavioral characteristics of Prader-Willi, Williams, Down, fragile X, and a few other syndromes. For these syndromes, then, studies exist on maladaptive behavior-psychopathology, cognitive-linguistic strengths and weaknesses, and a few basic developmental issues (sequences, changing rates of development at diVerent ages). But even in these syndromes, many additional behavioral ﬁndings and approaches remain relatively unexplored. We now turn to ﬁve such unresolved issues for future etiology-based behavioral research. III.

THE FUTURE: FIVE UNRESOLVED ISSUES

To complete the vision of past, present, and future work, it is necessary to identify particular areas of interest concerning behavioral phenotypes. Many

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of these areas have already attracted preliminary work. They are all the focus of what one might call the next generation of behavioral phenotypic research. Indeed, beyond simply contrasting a particular genetic syndrome to others with mental retardation, the future holds promise for making genebrain-behavior connections, more in-depth developmental understandings, better conceptualizations of environmental eVects, better speciﬁcations of indirect eVects, and more tailored, better tested interventions based on the child’s speciﬁc etiology of mental retardation. For each of these issues, the following sections explain the basic issues and provide examples of preliminary, illustrative work. A.

Making Gene-Brain-Behavior Connections

To many researchers, the connection of genes to brain to behavior has achieved the status of the Holy Grail. With a conﬁrmed diagnosis of a genetic disorder, one can, in theory, go from the genetic disorder and the proteins aVected by that disorder, to brain changes and functioning aVected by altered protein production or regulation, to behavioral outcomes. In short, one can extend from gene, to brain, to behavior. However, it is becoming increasingly clear that this movement from gene to brain to behavior is not straightforward. Many intervening steps participate, as well as the speciﬁc type or characteristic of the genetic anomaly involved. Thus, it now appears that children with Prader-Willi syndrome diVer slightly in their behaviors based on their speciﬁc type of Prader-Willi syndrome. In about 70% of cases, individuals receive a chromosome 15 from their father that has a deletion (or missing material). These deletion cases contrast with individuals who receive two chromosome 15 s from their mother (and none from their father), the so-called uniparental disomy (UPD) form of Prader-Willi syndrome. Although in both cases paternallyderived genetic material on chromosome 15 is missing, individuals with the deletion form of Prader-Willi syndrome diVer slightly from those with the UPD form in verbal IQ and in the nature and prevalence of maladaptive behaviors (Dykens et al., 1999; Roof et al., 2000). Despite complications due to genetic subtype in certain syndromes, we are slowly beginning to move from genes to brain to behavior, as the following example involving Down syndrome illustrates. For many years, it has been known that children with Down syndrome show particular deﬁcits in linguistic grammar, articulation, and expressive language. In contrast, children with Down syndrome show relative strengths in visual as opposed to auditory short-term memory, particularly when one uses various auditory and visual short-term memory measures from diVerent IQ tests (Hodapp et al., 1999; Pueschel et al., 1986). So far, such strengths and weaknesses have not been linked to neurological functioning.

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In contrast, a recent study has speciﬁcally linked one aspect of the Down syndrome proﬁle to brain functioning. For many years, Nadel (1996, 1999) has argued that, in addition to their linguistic deﬁcits and visuospatial strengths, children with Down syndrome are deﬁcient in tasks that utilize hippocampal functioning. In a recent study, Pennington et al. (2003) directly compared these children to mental age-matched typically developing children on two sets of tasks. The ﬁrst set related to functioning of the prefrontal cortex, which involves holding information in active or working memory. The second set examined hippocampal functioning, which relates to the storage of episodic information into long-term memory. As predicted, children with Down syndrome performed more poorly than mental age matches on tasks involving the hippocampus and equivalently on tasks relating to the prefrontal cortex. Although these results derive from a single study, Pennington et al. (2003) make several noteworthy contributions. First, they began their study with a clear neurological hypothesis: Children with Down syndrome will do worse on tasks related to the hippocampus, whereas tasks related to the prefrontal cortex will more closely conform to the child’s overall mental age. Using such hypotheses, the authors then grouped together many seemingly unrelated tasks. Hippocampal measures, all of which require long-term memory, included the long-term recall of a list of 15 words presented ﬁve times, learning a visual map, learning visual patterns, and learning paired associates (linking an abstract visual pattern and its location). Prefrontal tasks included planning, ‘‘stopping’’ (i.e., inhibiting one’s actions), verbal and non-verbal ﬂuency, and spatial and verbal working memory. Through functional magnetic resonance imaging (MRI), position emission tomography (PET) or computed tomography scans, these tasks had previously been linked to either the hippocampus or prefrontal cortex, respectively. It is also noteworthy that, from a ‘‘face validity’’ perspective, several prefrontal tasks seem to relate to domains of weakness in Down syndrome (e.g., verbal ﬂuency), whereas some of the hippocampal measures seemingly tapped relative strengths (e.g., learning a visual map). Even so, children with Down syndrome still showed relative weaknesses in hippocampal tasks, illustrating one of the ﬁrst etiology-related deﬁcits that has been so tightly tied to neurological functioning. In future years, it seems likely that this type of study will become more prevalent. To perform such studies, however, one needs to have an explicit sense of areas of strength or weakness, in addition to a well-established battery of experimental tasks that taps into speciﬁc neurological functioning. Furthermore, greater widespread use of functional MRI, PET scans, and other imaging techniques should allow one to conﬁrm, for example, that a ‘‘hippocampal task’’ does indeed relate to hippocampal functioning for persons with the particular disorder. These conditions—etiology-related neurological

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hypotheses; neurologically-linked tasks; and knowledge that tasks mostly relate to a single area of the brain (and single type of neurological functioning)—have all rarely been achieved in most current work on behavioral phenotypes. B.

Developmental Changes in Etiology-Related Profiles

Although research linking gene, brain, and behavioral functioning is vitally important, such studies tell us nothing about how such proﬁles arise. To say that children with Down syndrome show relative weaknesses in hippocampal functioning, grammar, or expressive language, or that most of these children show relative strengths in visual short-term memory, tells us nothing about when such strengths-weaknesses ﬁrst appeared or how they change with increasing age. One wants to know the age-related course of cognitive-linguistic proﬁles. Once etiology-related proﬁles are examined as a function of age, one sees that proﬁles of strengths and weaknesses often become more pronounced over time. Put another way, as children get older, the strong area becomes relatively stronger relative to the weak area. In cross-sectional studies, children with Down syndrome show more pronounced patterns of visual-over-auditory short-term memory during the late adolescent years (15 to 21) versus the years from 5 through 15 (Hodapp & Ricci, 2002). Similarly, boys with fragile X syndrome show more pronounced patterns of weakness in sequential processing (vs. simultaneous processing or achievement) after age 10 than earlier (Hodapp et al., 1991). In Williams syndrome, the verbal-over-visuospatial proﬁle becomes more pronounced as children get older (Bellugi et al., 1999). The few longitudinal studies on this issue may illuminate the processes leading to such proﬁle intensiﬁcation. In a study examining children with Williams syndrome six times over a four-year period, Jarrold et al. (2001) plotted rates of development in the stronger versus weaker areas. Figure 2 shows these discrepant slopes, with the weak area of visuospatial skills (exempliﬁed by the pattern construction task on the DAS) developing only slightly over the study period. This slow growth in visuospatial skills is contrasted by the much steeper slope in language (i.e., DAS vocabulary) skills. As a result of these two divergent slopes, an already weak area becomes progressively weaker and an already strong area becomes even stronger. Although no studies longitudinally examine proﬁles in children with Down or fragile X syndrome, one suspects that faster-developing strengths and slower-developing weaknesses also account for the intensiﬁcation of already-existing proﬁles in these syndromes. It is also important to consider the methodological implications of this ﬁnding. If indeed children with various syndromes become more pronounced in their proﬁles as they get older, how should one perform etiology-based behavioral research? In the past, developmentally-oriented

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FIG. 2. Average vocabulary and pattern construction ages at six time points (average best ﬁt lines), from Jarrold et al., 2000.

researchers have favored comparisons (to either typical children or children with heterogeneous causes for their mental retardation) that were equated on overall mental ages (mental age matches). Conversely, defect or deviance theorists have generally favored comparisons to typically developing children of the same chronological age (chronological age-matches). Now, however, we may be entering a stage in which one needs to be aware of both the child’s mental and chronological ages (Hodapp & Dykens, 2001). This dual strategy of matching on both mental and chronological age has long been advocated but, until now, only rarely followed. However, such a dual-matching strategy now seems necessary. For example, if two children with Down syndrome have mental ages of 5 years–but one is 8 years old, the other 16—one would expect that visual short-term memory skills might be more of a relative strength in the older as opposed to the younger child. If etiology-related proﬁles oftentimes become more salient with increasing chronological age, both mental and chronological age must be considered. C.

Understanding Effects of the Environment

Examining the course of etiology-related proﬁles tells one whether strengths and weaknesses diverge over age, but not why. Here one assumes that some type of interaction occurs between the child and that child’s

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environment. Such child-environment transactions over time presumably help to strengthen or weaken already-existing proﬁles. Borrowing from behavior geneticist Sandra Scarr (1993), one can conceptualize environmental eVects in three diVerent ways. First, there is the idea that the environment is a strong, active force that inﬂuences an essentially passive organism. For example, when researchers examine the eVects of daycare on a child’s development, or of inclusive classrooms on the school achievement or self-image of children with disabilities, the predominant model is one in which the environment is aVecting the child. But two other views are also possible. In the second, opposing view, one chooses one’s own environment. Particularly as children get older, they increasingly choose their friends, their interests, and their levels of achievement (and in which areas). As adults, we choose with whom and where we will live, as well as what we will do with our lives. Finally, a third view relates to the ‘‘eliciting’’ nature of child and adult behaviors. Although described in more detail in the following text, this third perspective emphasizes the ways in which people often bring about diVerent environments by attracting or repelling interactions, help, and other behaviors from others. Although the development of etiology-related cognitive-linguistic proﬁles probably relates to all three senses of person-environment interactions, we have recently been intrigued by the degree to which children with diVerent, etiology-related strengths and weaknesses choose to perform certain activities. Rosner et al. (in press) compared the everyday leisure activities engaged in by children with Williams syndrome (N ¼ 58), Prader-Willi syndrome (N ¼ 54), and Down syndrome (N ¼ 65). Using parents’ reports of leisure-time behavior from Achenbach’s (1991) Child Behavior Checklist, behaviors were grouped into those involving music, reading, visual-motor activities, athletics, pretend play, and focused interests. As expected, children with Williams syndrome were more likely to engage in musical activities, especially when such activities included higher-level behaviors such as playing a musical instrument. Similarly, whereas a full 50% of children with Prader-Willi syndrome played with jigsaw puzzles, only 9% and 2% of persons with Down or Williams syndrome, respectively, engaged in this activity. Most striking, however, were the ways in which particular groups did not perform certain activities. In the overall category of visual-motor activities, 76% and 60% of persons with Prader-Willi and Down syndromes, respectively, participated in visual-motor activities, compared to only 31% of the sample with Williams syndrome. Speciﬁcally, arts-and-crafts activities were listed in 35% of the group with Down syndrome, 30% of individuals with Prader-Willi syndrome, and only 7% of those with Williams syndrome.

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Persons with Williams syndrome, therefore, seem to avoid engaging in activities that may be diYcult for them to perform. Such ﬁndings generate additional questions. Who, for example, is choosing the child’s everyday activities? We assumed that children choose their own activities, but cannot rule out the possibility that parents dictate the child’s leisure activities. If so, what do parents know about their child’s syndrome? From earlier studies, parents seem reasonably well-informed about cognitive-linguistic proﬁles when their child has Down syndrome and less informed when children have Prader-Willi or Williams syndromes (Fidler et al., 2002). An additional, intriguing issue relates to changes in these choices over time. In an ongoing, follow-up study of children’s everyday activities, we found no relation (r ¼ 0.05) between the child’s age and amount of visual-spatial activities (Reisbaum et al., in preparation). Do children with Williams syndrome know about their relative visual-spatial weaknesses at early ages? How do they know? In addition, what is the eVect on development of visuospatial skills of children not performing arts-and-crafts and other visual-spatial leisure activities? As these questions illustrate, the mental retardation ﬁeld has barely begun to explore the long-term eVects of such child-environment transactions. Nonetheless, it is becoming clear that etiology-related strengths and weaknesses rarely appear fully formed at birth; at an early age, children should be examined for propensities or small inclinations that gradually become more pronounced as they develop. Currently, we have only a preliminary sense of how the child’s choice and use of the environment might aVect these beginning patterns of cognitive-linguistic strengths and weaknesses. D.

Specifying Genetic Disorders’ Indirect Effects

In discussing child-environment transactions, thus far we have considered the ﬁrst two senses of the environment—how the environment aVects the (relatively passive) child and, conversely, how the active child chooses and uses a relatively passive environment. But a third perspective is also possible, one in which children elicit reactions from others. In this sense, children perform certain behaviors or possess certain characteristics that may, in turn, elicit particular behaviors from others. This idea of child elicitation has deep roots in the typical child development literature. Reacting to the then-predominant view that mothers socialize children (i.e., that the direction of eVects goes from mothers to their children), Bell (1968) noted that, in many socialization studies, one could equally argue that children were aVecting adults. This view of bidirectional eVects, which

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has profoundly inﬂuenced parent-child work on typically developing children from the early 1970s until today, has also been successfully applied to socalled ‘‘resilient children’’ in Werner’s (1993) decades-long study of children into adulthood. Following all children born on the island of Kauai during the year 1955, Werner (1993) noted that some children, although they came from broken and troubled families and extreme poverty, nevertheless adjusted well by early adulthood. In more closely examining these resilient adults, Werner (1993) noted that they showed several personal characteristics along the way. Even as toddlers, these resilient children were more likely to exhibit a positive social orientation and to be alert and autonomous. During grade school, teachers reported that these children related well with their peers. As high-schoolers, these children developed a positive self-concept and an internal locus of control. At various ages, these children were also able to attract the individualized care and attention of a teacher, coach, minister, Girl or Boy Scout leader, or other adult ﬁgure. Through their own personalities and highly social behaviors, these children were able to elicit the individualized adult caregiving that they needed in order to optimally develop. From the opposite perspective, child (and adult) eVects can be seen in the downward spiral of parent-child interactions noted in children with conduct disorders. Children are more likely to show later conduct disorders when they show a diYcult temperament (i.e., being fussy, whiny, less adaptable to change) during the preschool years (Loeber et al., 1991). Teacher and peer ratings of the ‘‘troublesome’’ behaviors of 8- and 10-year-old children also signiﬁcantly predict later delinquency (West & Farrington, 1973). Parental reactions to such child behaviors can also be shown over long periods. Using a longitudinal path analysis, Olweus (1980) showed that mothers of boys who were aggressive and strong-willed during infancy become more permissive of their child’s aggression, which led to their boys’ further aggression as time progressed. Similarly, conduct-disordered children react diVerently to punishment than non-conduct disordered children. Whereas normal children suppress their hostile and aggressive behaviors in response to parental physical and verbal punishment, children with conduct disorders are twice as likely as non-conduct disordered children to persist in their problem behaviors after punishment (Patterson, 1976). Both child and adult eVects are operating over time (Lytton, 1990). This perspective of children eliciting adult behaviors has recently been applied to the interactions and reactions of parents of children with diVerent genetic disorders (Hodapp, 1999). In this case, a genetic disorder leads to both direct and indirect eVects. Direct eVects predispose children to show speciﬁc cognitive, linguistic, adaptive, or maladaptive behaviors, proﬁles, or trajectories. But these direct behavioral eVects, in turn, may elicit particular

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behaviors from mothers, fathers, siblings, and others in the child’s surrounding environment. 1. THE DOWN SYNDROME ADVANTAGE

Two examples illustrate the indirect eVects of genetic disorders. The ﬁrst concern has been referred to as the ‘‘Down syndrome advantage’’ (Hodapp et al., 2001). Compared to parents and families of children with other types of mental retardation, autism, or in- or out-patients with psychiatric disorders, parents and families of children with Down syndrome generally report less stress. These parents also usually feel more rewarded by their child, and generally see their child as more acceptable than parents of children with other disabilities. Why this Down syndrome advantage exists is less clear. Cahill and Glidden (1996) note that parents of children with Down syndrome are often older, have longer work histories, and oftentimes have greater family incomes. As older parents, they are also more likely to have parented one or more prior children. In addition, parents of children with Down syndrome are parenting children with a disability that feels ‘‘known’’ to professionals and non-professionals alike, one that parents do not need to teach others about. Although such associated characteristics may partially account for the Down syndrome advantage, this may not be the entire story. In interactive work, beginning at toddlerhood children with Down syndrome look to others (as opposed to objects) more often (Kasari et al., 1990; Ruskin et al. 1994). While performing problem-solving tasks at later ages, these children tend to look to adults and engage in social behaviors (Kasari & Freeman, 2001; Pitcairn & Wishart, 1994). Children with this syndrome are also considered to be exceptionally sociable and cheerful by both their fathers (Hornby, 1995) and their mothers (Hodapp et al., 2003; Wishart & Johnston, 1990). Although associated child or parental characteristics may partially account for the Down syndrome advantage, child behaviors and characteristics are also likely at play. Parental reactions may even be due to a combination of what parents know about Down syndrome and of their child’s (perceived) personality. In one study, Ly and Hodapp (2002) asked parents of children with Down syndrome (versus parents of children with other forms of mental retardation) to rate causal attributions in response to why their child performed two common, non-compliant behaviors. Parents of children considered more sociable and outgoing attributed their child’s non-compliant behaviors to normative patterns (‘‘my child is acting like other children his/her age’’). But such connections between child personality and normalizing behaviors were found only within the Down syndrome group. Speciﬁcally, those parents who saw their child as more sociable and upbeat, rated normalizing more highly as the reason for their

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child’s non-compliance (r ¼ 0.43, p < 0.01). Among parents of children with mixed forms of mental retardation, no such connections existed between child personality and parental ratings of normalizing attributions (r ¼ 0.05, ns). Parental reactions seemed due to both the child’s behaviors and to parental expectations about how children with Down syndrome should behave. 2. MATERNAL BEHAVIORS WITHIN INTERACTIONS TAPPING ETIOLOGY-RELATED HIGH VERSUS LOW ABILITIES

A second example of indirect eVects can be seen in parental behaviors within a speciﬁc interaction—jointly assembling a novel jigsaw puzzle. Children with Prader-Willi syndrome versus children with Williams syndrome have visuospatial skills (including puzzles) that are either exceptionally strong (Prader-Willi syndrome; Dykens, 2002) or exceptionally weak (Williams syndrome; Mervis et al., 1999). In one recent study, Ly and Hodapp (2004) examined child eVects on parents’ behaviors in parent-child dyads of 20 children with Prader-Willi syndrome and 21 children with Williams syndrome. We measured the parents’ amount of help and reinforcement behaviors in interactions with their child to complete a jigsaw puzzle task. Prior to the mother-child interaction, children completed a jigsaw puzzle independently in order to obtain an objective measure of the child’s puzzle abilities. Although on average children with Prader-Willi syndrome completed more jigsaw puzzle pieces than children with Williams syndrome, each group also showed a fair amount of within-syndrome variability. Then, regardless of syndrome, two groups were created—those with low puzzle ability versus those with high puzzle ability. Compared to parents of children with Prader-Willi syndrome, parents of children with Williams syndrome provided more help and reinforcement behaviors. Within the 5-minute interaction session, parents of children with Williams syndrome helped their child 49 times, compared to slightly <24 times for the Prader-Willi parents. Similarly, parents of children with Williams syndrome reinforced their children over twice as often (14.14 and 5.75 for Williams and Prader-Willi syndromes, respectively). Although parents of children with high versus low puzzle abilities did not diVer in their frequencies of reinforcement, parents did provide more help when their children had low (X ¼ 45.89) versus high (X ¼ 25.89) puzzle abilities. But what, exactly, were parents reacting to in their help-giving and reinforcement behaviors? Since we measured the child’s independent puzzle ability, we could contrast reactions based on the child’s puzzle ability and the etiology. When looking at parents’ helping behaviors, the child’s etiology accounted for 28% of the variance, with the child’s puzzle ability accounting

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for an additional 12%. For reinforcement behaviors, only the child’s etiology emerged as a signiﬁcant predictor, accounting for 27% of the variance. Therefore, parents considered both the child’s level of puzzle ability and the child’s etiology group to be important—or the mother’s sense of what ‘‘children with Prader-Willi syndrome [or with Williams syndrome] do.’’ In this instance, parental perceptions might even be more important than the child’s behaviors per se. Considering both the Down syndrome advantage and puzzle-playing in Prader-Willi versus Williams syndromes, then, genetic disorders show indirect eVects on others, but these indirect eVects may be more complicated than we had originally thought. Ironically, Bell’s own work also shifted from emphasizing the child’s behavior alone to one focused more on the child’s behavior within parental expectations and knowledge. Thus, whereas Bell’s 1968 piece focused on parental behaviors in response to the child’s behaviors, Bell’s (1979) American Psychologist article championed child eVects within the context of a ‘‘thinking parent.’’ Parents of children with diVerent genetic disorders are also thinking parents, and how child behaviors and parental knowledge-perceptions interact is only dimly understood. E.

Developing Etiology-Related Strategies of Intervention

If we know that persons with diVerent genetic syndromes show diVerences in behavior, can we then use that knowledge to develop more targeted programs of intervention? Although no clear answer to this question currently exists, a few general themes have arisen. Theme 1: Etiology-related interventions will not relate to every person with a particular genetic syndrome. As noted throughout this article, etiologyrelated behaviors are probabilistic, not deterministic, in nature. Not every person with Down syndrome shows relatively high visual short-term memory and not every person shows problems in articulation, grammar, or expressive language. For this reason, one should consider etiology-related intervention techniques as general guidelines that will apply to some, but not all, children. As general guidelines, these ideas highlight where one might look for cognitivelinguistic strengths-weaknesses, potential maladaptive behaviors, and possible trajectories of development. As a practical matter, many children with a speciﬁc disorder will show the strength, weakness, maladaptive behavior, or slowed trajectory that characterizes that child’s etiological group. Such etiology-related intervention guidelines should thus be the ﬁrst place —but not the last place—to look concerning how best to intervene with children with diVerent genetic disorders.

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Theme 2: Follow the symptom or proﬁle. So far, most suggestions concerning etiology-based interventions are aimed at the behavioral symptom, not any underlying neurological or other mechanisms. Therefore, one might intervene in addressing the attentional-hyperactivity problems shown by boys with fragile X syndrome or the obsessions and compulsions of those with Prader-Willi syndrome (Dykens & Hodapp, 1997). Similarly, one might more often recommend that young adults with Williams syndrome perform various ‘‘people-oriented’’ jobs (e.g., receptionist), whereas such jobs might be more diYcult for many young adults with fragile X syndrome. Such suggestions follow the symptom or proﬁle that is characteristic of a particular etiology. Such thinking is also evident in the many diVerent types of intervention. Consider the case of Williams syndrome, in which most individuals are highly social, show relative strengths in language and weaknesses in visuospatial skills, and show a propensity to many fears and anxieties (Dykens, 2003). In recommending interventions for such individuals, the educator might try verbal (as opposed to visually based) approaches to introducing educational material, while at the same time trying harder to calm the child’s anxieties and to encourage group projects. The psychotherapist might use verbal and group counseling, and possibly consider anxiety-reducing medications if necessary. The adult worker might suggest ‘‘people-oriented’’ jobs, while generally recommending against employment choices that require high levels of visuospatial skills or eye-hand coordination (e.g., factory-line work). Following the symptom cuts across various disciplines, interventions, and life spheres. While the current suggestion is to follow the symptom, future work may go beyond symptoms per se. Speciﬁcally in the area of neurological functioning in a few genetic disorders, researchers are beginning to understand why—at a neurochemical level—certain behavioral symptoms occur. Using animal models of fragile X syndrome, for example, Miyashiro et al. (2003) have recently suggested that the social anxieties seen in many males with this syndrome may be due to particular, etiology-related changes in the expression of a speciﬁc protein (FRM1) in particular parts of the brain. If so, it may be possible to go beyond the symptom per se and instead use altered or deﬁcient brain functioning to guide psychopharmacological interventions. Such advances, although several years away, seem akin to ‘‘geneticopharmacology,’’ or the treatment of identical symptoms (e.g., high blood pressure, depression) with diVerent agents or classes of agents because of an individual’s particular underlying genetic predisposition(s). Theme 3: Play to strengths or ameliorate weaknesses? Particularly when discussing proﬁles of cognitive-linguistic strengths and weaknesses, one can either play to the strengths or ameliorate the weaknesses (Hodapp et al.,

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2003). For example, if the child with Williams syndrome has relative strengths in language and relative weaknesses in visuospatial skills, one can choose to use language to circumvent the relatively weaker visual domain. Similarly in Prader-Willi syndrome, one might use relative strengths on tasks that are more visual, Gestalt-like, and simultaneous, as opposed to tasks that are more oriented toward serial, step-by-step, sequential learning (Kaufman et al., 1984). From the opposite perspective, precisely because such skills are so weak, one might instead choose to intervene by targeting visual skills in Williams syndrome, or by targeting sequential, step-by-step learning in Prader-Willi syndrome. No answer currently exists as to whether it is better to play to the etiologyrelated strengths or to ameliorate the etiology-related weaknesses. It is also important to note that this question pervades special education interventions, with no clear answer currently available. Like many others, our general sense has been to play to the strengths, to use to one’s advantage those areas that are relatively strong in a particular syndrome. But others question this approach. They note that ﬁndings of etiology-related proﬁles or of changing proﬁles with age do not necessarily lead one to recommend working on strong as opposed to weak areas (Abbeduto & Keller-Bell, 2002). The resolution of this issue awaits more rigorous studies. Theme 4: Disperse knowledge about etiology-related behaviors. Despite the many unanswered issues concerning intervention, a more general theme relates to the need for etiology-related information to be more widely dispersed. From our own studies (e.g., Fidler et al., 2002), we ﬁnd that parents of children with disorders such as Williams and Prader-Willi syndromes have little knowledge of their child’s etiology-related strengths and weaknesses. But even in the absence of much etiology-related knowledge, parents of children with Williams and with Prader-Willi syndromes are often the sole providers of information about their child’s etiology to teachers, speech pathologists, school psychologists, and other education professionals. We suspect that parents of children with many of these conditions are also the sole information providers to medical and other professionals. Even with many unanswered questions, an enlarged sphere of communication about diVerent etiologies will help many persons with these syndromes and their parents. For example, if the wide variety of educational personnel—from the school bus driver, to the general education teacher, school psychologist, adaptive physical education teacher, and others—all know that the student with Prader-Willi syndrome needs to be on a rigorous diet, fewer tragedies will occur. Over the past 10 years, a series of books, pamphlets, websites, and articles providing etiology-related behavioral tips have all proliferated, and the translation seems well underway of laboratory ﬁndings into useful, parent- and teacher-friendly practices and suggestions (Dorn &

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GoV, 2003; Finucane, 1995; Finucane et al., 2003). Future years should bring about even greater success in disseminating etiology-related behavioral ﬁndings to the larger, non-scientiﬁc community.

IV.

CONCLUSIONS

From Down, to Zigler’s two-group approach in the late 1960s, to more recent research across a variety of disciplines, advances concerning behavioral phenotypes have been remarkable. Partly as a result, behavioral research in mental retardation has increasingly often and enthusiastically examined behavior in persons with diVerent genetic mental retardation syndromes. In organizing this burgeoning area of research, it may be helpful to adopt the perspective of Werner (1957). A psychologist at Clark University, Werner and his colleagues and students (one of whom was Zigler) promulgated a grand view of the development of any living system. According to Werner (1957), anywhere development occurs it ‘‘proceeds from a state of relative globality and lack of diVerentiation to a state of diVerentiation, articulation, and hierarchic integration.’’ Simply stated, development proceeds from global and undiVerentiated, to diVerentiated but unintegrated, to diVerentiated and integrated. Seen in this light, behavioral research on genetic mental retardation syndromes might be considered in the middle stage along this developmental continuum. As Figure 3 shows, the 1970s (and before) could be characterized as a more global stage. Zigler may have formalized the twogroup approach, but knowledge was lacking about all genetic disorders, except Down syndrome (Gibson, 1978). More recently, during the 1980s and 1990s, the behavioral importance of genetic etiologies has become increasingly obvious. Even compared to 10 years ago, we now know much more than before about such disorders as fragile X, Prader-Willi, and Williams syndromes. In Werner’s (1957) terms, we have many speciﬁc-but-unintegrated pieces of information.

FIG. 3. Development of etiology-based research.

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The task for the future involves integration. Although we obviously need more behavioral information—particularly regarding many of the 1,000þ genetic mental retardation syndromes—we also need to tie together what we already know. Such ties seem necessary in almost every direction. We need more work on gene-brain-behavior connections; on how such connections change as proﬁles, maladaptive behaviors, and developmental trajectories evolve as the child gets older; and on how transactions between the child and the child’s environments relate to such age-related changes (and their neurological concomitants). We need more work tying the child’s behaviors (over time) to reactions from parents, siblings, families, teachers, and peers. Finally, we need better integration of all of this knowledge with intervention eVorts, which so far have generally eschewed etiology-based strategies. Research on behavioral phenotypes may be exploding, but much more work remains to be done. REFERENCES Abbeduto, L., & Keller-Bell, Y. (2002). Review of genetics and mental retardation syndromes: A new look at behavior and interventions. American Journal on Mental Retardation, 107, 412–414. Achenbach, T. M. (1991). Manual for the Child Behavior Checklist/4–18 and 1991 Proﬁle. Burlington, VT: University of Vermont, Department of Psychiatry. Anderson, L., & Ernst, M. (1994). Self-injury in Lesch-Nyhan disease. Journal of Autism and Developmental Disorders, 24, 67–81. Baumeister, A. A., Bacharach, V. R., & Baumeister, A. A. (1997). ‘‘Big’’ versus ‘‘little’’ science: Comparative analysis of program projects and individual research grants. American Journal of Mental Retardation, 102, 211–227. Baumgardner, T. L., Reiss, A. L., Freund, L. S., & Abrams, M. T. (1995). Speciﬁcation of the neurobehavioral phenotype in males with fragile X syndrome. Pediatrics, 95, 744–752. Bell, R. Q. (1968). A reinterpretation of direction of eVects in studies of socialization. Psychological Review, 75, 81–95. Bell, R. Q. (1979). Parent, child, and reciprocal inﬂuences. American Psychologist, 34, 821–826. Bellugi, U., Marks, S., Bihrle, A., & Sabo, H. (1988). Dissociation between language and cognitive functions in Williams syndrome. In D. Bishop & K. Mogford (Eds.), Language development in exceptional circumstances (pp. 177–189). Edinburg: Churchill Livingson. Bellugi, U., Mills, D., Jernigan, T., Hickok, G., & Galaburda, A. (1999). Linking cognition, brain structure, and brain function in Williams syndrome. In H. Tager-Flusberg (Ed.), Neurodevelopmental disorders (pp. 111–136). Cambridge, MA: MIT Press. Bihrle, A. M., Bellugi, U., Delis, D., & Marks, S. (1989). Seeing either the forest or the trees: Dissociation in visuospatial processing. Brain Cognition, 11, 37–49. Bishop, D. V. M. (1999). An innate basis for language? Science, 286, 2283–2284. Blackhurst, A. E., & Berdine, W. H. (1993). An introduction to special education. New York: Harper Collins. Burack, J. A. (1990). DiVerentiating mental retardation: The two-group approach and beyond. In R. M. Hodapp, J. A. Burack, & E. Zigler (Eds.), Issues in the developmental approach to mental retardation (pp. 27–48). Cambridge: Cambridge University Press.

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Burack, J. A., Hodapp, R. M., & Zigler, E. (1988). Issues in the classiﬁcation of mental retardation: DiVerentiating among organic etiologies. Journal of Child Psychology and Psychiatry, 29, 765–779. Butler, J. V., Whittington, J. E., Holland, A. J., Boerr, H., Clarke, D., & Webb, T. (2002). Prevalence of, and risk factors for, physical ill health in people with Prader-Willi syndrome: A population-based study. Developmental Medicine and Child Neurology, 44, 248–255. Cahill, B. M., & Glidden, L. M. (1996). Inﬂuence of child diagnosis on family and parent functioning: Down syndrome versus other disabilities. American Journal on Mental Retardation, 101, 149–160. Chapman, R. J., & Hesketh, L. J. (2000). Behavioral phenotype of individuals with Down syndrome. Mental Retardation and Developmental Disorders Research Reviews, 6, 84–95. Dingman, H. F., & Tarjan, G. (1960). Mental retardation and the normal distribution curve. American Journal of Mental Deﬁciency, 64, 991–994. Dorn, B., & GoV, B. J. (2003). The student with Prader-Willi syndrome: Information for educators. Sarasota, FL: Prader-Willi Syndrome Association (PWSA; www.pwsausa.org). Down, H. L. (1866). Observations of an ethnic classiﬁcation of idiots. London Hospital Clinical Lecture and Report, 3, 259–262. Dunn, P. M. (1991). Dr. Langdon Down (1828–1896) and ‘‘mongolism.’’ Archives of Disease in Childhood, 66, 827–828. Dykens, E. M. (1995). Measuring behavioral phenotypes: Provocations from the ‘‘new genetics.’’ American Journal on Mental Retardation, 99, 522–532. Dykens, E. M. (1999). Prader-Willi syndrome. In H. Tager-Flusberg (Ed.), Neurodevelopmental disorders (pp. 137–154). Cambridge, MA: MIT Press. Dykens, E. M. (2002). Are jigsaw puzzles ‘‘spared’’ in persons with Prader-Willi syndrome? Journal of Child Psychology and Psychiatry, 43, 343–352. Dykens, E. M. (2003). Anxiety, fears, and phobias in Williams syndrome. Developmental Neuropsychology, 23, 291–316. Dykens, E. M., Cassidy, S. B., & King, B. H. (1999). Maladaptive behavior diVerences in Prader-Willi syndrome due to paternal deletion versus maternal uniparental disomy. American Journal on Mental Retardation, 104, 67–77. Dykens, E. M., & Clarke, D. J. (1997). Correlates of maladaptive behavior in individuals with 5p- (cri du chat) syndrome. Developmental Medicine and Child Neurology, 39, 752–756. Dykens, E. M., & Hodapp, R. M. (1997). Treatment issues in genetic mental retardation syndromes. Professional Psychology: Research and Practice, 28, 263–270. Dykens, E. M., & Hodapp, R. M. (2001). Research in mental retardation: Toward an etiologic approach. Journal of Child Psychology and Psychiatry, 42, 49–71. Dykens, E. M., Hodapp, R. M., & Finucane, B. (2000). Genetics and mental retardation syndromes: A new look at behavior and treatments. Baltimore, MD: Paul H. Brookes Publishing Company. Dykens, E. M., Hodapp, R. M., & Leckman, J. F. (1987). Strengths and weaknesses in intellectual functioning of males with fragile X syndrome. American Journal of Mental Deﬁciency, 92, 234–236. Dykens, E. M., Hodapp, R. M., Walsh, K. K., & Nash, L. (1992). Proﬁles, correlates, and trajectories of intelligence in Prader-Willi syndrome. Journal of the American Academy of Child and Adolescent Psychiatry, 31, 1125–1130. Dykens, E. M., Rosner, B. A., & Ly, T. M. (2001). Drawings by individuals with Williams syndrome: Are people diVerent from shapes? American Journal on Mental Retardation, 106, 94–107.

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Elliott, C. D. (1990). DiVerential abilities scales. San Diego, CA: Harcourt, Brace, Jovanich. Ellis, N. R. (1969). A behavioral research strategy in mental retardation: Defense and critique. American Journal of Mental Deﬁciency, 73, 557–566. Fidler, D. J., Hodapp, R. M., & Dykens, E. M. (2002). Educational experiences of children with Down syndrome, Prader-Willi syndrome, and Williams syndrome. Journal of Special Education, 36, 80–88. Finucane, B. M. (1995). What’s so special about genetics? A guide for special educators. Elwyn, PA: Elwyn, Inc. Finucane, B. M., Haas-Givler, B., & Simon, E. W. (2003). Genetics, mental retardation, and the forging of new alliances. American Journal of Medical Genetics, 117C, 66–72. Finucane, B. M., Konar, D., Haas-Givler, B., Kurtz, M. D., & Scott, C. I. (1994). The spasmodic upper-body squeeze: A characteristic behavior in Smith-Magenis syndrome. Developmental Medicine and Child Neurology, 36, 78–83. Flynt, J., & Yule, W. (1994). Behavioural phenotypes. In M. Rutter, E. Taylor, & L. Hersov (Eds.), Child and adolescent psychiatry: Modern approaches (3rd ed., pp. 666–687). London: Blackwell Scientiﬁc. Fowler, A. (1990). The development of language structure in children with Down syndrome. In D. Cicchetti & M. Beeghly (Eds.), Children with Down Syndrome: A developmental approach (pp. 302–328). Cambridge: Cambridge University Press. Gersh, M., Goodart, S. A., Pasztor, L. M., Harris, D. J., Weiss, L., & Overhauser, J. (1995). Evidence for a distinct region causing a cat-like cry in patients with 5p- deletions. American Journal of Human Genetics, 56, 1404–1410. Gibson, D. (1978). Down’s syndrome: The psychology of mongolism. Cambridge: Cambridge University Press. Greenberg, F., Lewis, R. A., Potocki, L., Glaze, D., Parke, J., Killian, J., Murpha, M. A., Williamson, D., Brown, F., Dutton, R., McCluggage, C., Friedman, S., Sulek, M., & Lupski, J. R. (1996). Multidisciplinary clinical study of Smith-Magenis syndrome (deletion 17p11.2). American Journal of Medical Genetics, 62, 247–254. Hallahan, D. P., & KauVman, J. M. (2000). Exceptional children: Introduction to special education (8th ed.). Needham Heights, MA: Allyn & Bacon. Hodapp, R. M. (1994). Cultural-familial mental retardation. In R. Sternberg (Ed.), Encyclopedia of intelligence (pp. 711–717). New York: Macmillan. Hodapp, R. M. (1997). Direct and indirect behavioral eVects of diVerent genetic disorders of mental retardation. American Journal on Mental Retardation, 102, 67–79. Hodapp, R. M. (1999). Indirect eVects of genetic mental retardation disorders: Theoretical and methodological issues. International Review of Research in Mental Retardation, 22, 27–50. Hodapp, R. M., DesJardin, J. L., & Ricci, L. A. (2003). Genetic syndromes of mental retardation: Should they matter for the early interventionist? Infants and Young Children, 16, 152–160. Hodapp, R. M., & Dykens, E. M. (1994). Mental retardation’s two cultures of behavioral research. American Journal on Mental Retardation, 98, 675–687. Hodapp, R. M., & Dykens, E. M. (2001). Strengthening behavioral research on genetic mental retardation syndromes. American Journal on Mental Retardation, 106, 4–15. Hodapp, R. M., Dykens, E. M., Ort, S. I., Zelinsky, D. G., & Leckman, J. F. (1991). Changing patterns of intellectual strengths and weaknesses in males with fragile X syndromes. Journal of Autism and Developmental Disorders, 21, 503–516. Hodapp, R. M., Evans, D. W., & Gray, F. L. (1999). Intellectual development in children with Down syndrome. In J. A. Rondal, J. Perera, & L. Nadel (Eds.), Down’s syndrome: A review of current knowledge (pp. 124–132). London: Whurr Publishers.

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Hodapp, R. M., & Fidler, D. J. (1999). Special education and genetics: Connections for the 21st century. Journal of Special Education, 33, 130–137. Hodapp, R. M., Ly, T. M., Fidler, D. J., & Ricci, L. A. (2001). Less stress, more rewarding: Parenting children with Down syndrome. Parenting: Science and Practice, 1, 317–337. Hodapp, R. M., & Ricci, L. A. (2002). Behavioural phenotypes and educational practice: The unrealized connection. In G. O’Brien (Ed.), Behavioural phenotypes in clinical practice (pp. 137–151). London: Mac Keith Press. Hodapp, R. M., Ricci, L. A., Ly, T. M., & Fidler, D. J. (2003). The eVects of the child with Down syndrome on maternal stress. British Journal of Developmental Psychology, 21, 137–151. Holm, V. A., Cassidy, S. B., Butler, M. G., Hanchett, J. M., Greenswag, L. R., Whitman, B. Y., & Greenberg, F. (1993). Prader-Willi syndrome: Consensus diagnostic criteria. Pediatrics, 91, 398–402. Hornby, G. (1995). Fathers’ views of the eVects on their families of children with Down syndrome. Journal of Child and Family Studies, 4, 103–117. Jarrold, C., Baddeley, A. D., Hewes, A. K., & Phillips, C. (2001). A longitudinal assessment of diverging verbal and non-verbal abilities in the Williams syndrome phenotype. Cortex, 37, 423–431. Kahn, J. V. (1988). Review of the book Special education: A sourcebook. American Journal on Mental Retardation, 92, 550–551. Kasari, C., & Freeman, S. F. N. (2001). Task related social behavior in children with Down syndrome. American Journal on Mental Retardation, 106, 253–264. Kasari, C., Mundy, P., Yirmiya, N., & Sigman, M. (1990). AVect and attention in children with Down syndrome. American Journal on Mental Retardation, 95, 55–67. Kaufman, A. S., Kaufman, N. L., & Goldsmith, B. Z. (1984). K-SOS: Kaufman sequential or simultaneous? Circle Pines, MN: American Guidance Service. Kemper, M. B., Hagerman, R. J., & Altshul-Stark, D. (1988). Cognitive proﬁles of boys with fragile X syndrome. American Journal of Medical Genetics, 30, 191–200. Kumin, L. (1994). Intelligibility of speech in children with Down syndrome in natural settings: Parents’ perspectives. Perceptual and Motor Skills, 78, 307–313. Lejeune, J., Gautier, M., & Turpin, R. (1959). Etudes des chromosomes somatique de neuf enfants mongoliens. Comptes Rendus de l’Academie les Sciences, 48, 1721–1722. Lewis, E. O. (1933). Types of mental deﬁciency and their social signiﬁcance. Journal of Mental Science, 79, 298–304. Loeber, R., Stouthamer-Loeber, M., & Green, S. M. (1991). Age of onset of problem behavior in boys, and later disruptive and delinquent behaviors. Criminal Behaviour and Mental Health, 1, 229–246. Ly, T. M., & Hodapp, R. M. (2002). Maternal attribution of child noncompliance in children with mental retardation: Down syndrome versus other etiologies. Journal of Developmental and Behavioral Pediatrics, 23, 1–8. Ly, T. M., & Hodapp, R. M. (2004). Children with Prader-Willi syndrome vs. Williams syndrome: Parents’ attributional cues on a jigsaw puzzle task. Submitted for publication. Lytton, H. (1990). Child and parent eVects in boys’ conduct disorder: A reinterpretation. Developmental Psychology, 26, 683–697. MacMillan, D. (1982). Mental retardation in school and society (2nd ed.). Boston, MA: Little, Brown, and Company. McElwee, C., & Bernard, S. (2002). Genetic syndromes and mental retardation. Current Opinion in Psychiatry, 15, 469–475. Mervis, C. B., Morris, C. A., Bertrand, J., & Robinson, B. F. (1999). Williams syndrome: Findings from an integrated program of research. In H. Tager-Flusberg (Ed.), Neurodevelopmental disorders (pp. 65–110). Cambridge, MA: MIT Press.

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Miller, J. (1999). Proﬁles of language development in children with Down syndrome. In J. F. Miller, M. Leddy, & L. A. Leavitt (Eds.), Improving the communication of people with Down syndrome (pp. 11–39). Baltimore, MD: Paul H. Brookes Publishing Company. Miyashiro, K. Y., Beckel-Mitchener, A., Purk, T. P., Becker, K. G., Barret, T., Liu, L., Carbonetto, S., Weiler, I. J., Greenough, W. T., & Eberwine, J. (2003). RNA cargoes associating with FMRP reveal deﬁcits in cellular functioning in FMR1 mice. Neuron, 37, 417–431. Mundy, P., & Kasari, C. (1990). The similar structure hypothesis and diVerential rate of development in mental retardation. In R. M. Hodapp, J. A. Burack, & E. Zigler (Eds.), Issues in the developmental approach to mental retardation (pp. 71–92). New York: Cambridge University Press. Nadel, L. (1996). Learning, memory, and neural functioning in Down’s syndrome. In J. A. Rondal, J. Perera, L. Nadel, & A. Comblain (Eds.), Down’s syndrome: Psychological, pyschobiological, and soci-educational perspectives (pp. 21–42). London: Whurr Publishers. Nadel, L. (1999). Learning and memory in Down syndrome. In J. A. Rondal, J. Perera, & L. Nadel (Eds.), Down syndrome: A review of current knowledge (pp. 133–142). London: Whurr Publishers. Nyhan, W. (1972). Behavioral phenotypes of organic genetic disease. Presidential address to the Society of Pediatric Research, May 1, 1971. Pediatric Research, 6, 1–9. Nyhan, W. (1995). Foreward. In G. O’Brien & W. Yule (Eds.), Behavioural phenotypes (pp. ix–x). London: Mac Keith Press. O’Brien, G. (Ed.) (2002). Behavioural phenotypes in clinical practice. Clinics in Developmental Medicine, No. 157. London: Mac Keith Press. O’Brien, G., & Yule, W. (Eds.) (1995). Behavioural phenotypes. Clinics in Developmental Medicine, No. 138. London, England: Mac Keith Press. Olweus, D. (1980). Familial and temperamental determinants of aggressive behavior in adolescent boys: A causal analysis. Developmental Psychology, 16, 644–660. Opitz, J. M. (1985). Editorial comment: The developmental ﬁeld concept. American Journal of Medical Genetics, 21, 1–11. Patterson, G. R. (1976). The aggressive child: Victim and architect of a coercive system. In E. J. Mash, L. Hamerlynck, & L. Handy (Eds.), Behavior modiﬁcation and families (pp. 267–316). New York: Brunnner/Mazel. Pearson, K., & Jaederholm, G. A. (1914). On the continuity of mental defect. London: Delau & Company. Pennington, B. F., Moon, J., Edgin, J., Stedron, J., & Nadel, L. (2003). The neuropsychology of DS: Evidence for hippocampal dysfunction. Child Development, 74, 75–93. Penrose, L. S. (1949). The biology of mental defect. New York: Grune & Stratton. Pitcairn, T. K., & Wishart, J. G. (1994). Reactions of young children with Down’s syndrome to an impossible task. British Journal of Developmental Psychology, 12, 485–489. Pueschel, S. R., Gallagher, P. L., Zartler, A. S., & Pezzullo, J. C. (1986). Cognitive and learning proﬁles in children with Down syndrome. Research in Developmental Disabilities, 8, 21–37. Reisbaum T., Hodapp R. M., Dykens E. M. (in preparation). Leisure activity choices among individuals with Prader-Willi syndrome, Williams syndrome, and Down syndrome. Rondal, J. (1995). Exceptional language development in Down syndrome. New York: Cambridge University Press. Roof, E., MacLean, W., Feuer, I. D., Thompson, T., & Butler, M. G. (2000). Intellectual characteristics of Prader-Willi syndrome: Comparison of genetic subtypes. Journal of Intellectual Disability Research, 44, 25–30.

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Prenatal Drug Exposure and Mental Retardation ROBERT E. ARENDT THE BUCKEYE RANCH GROVE CITY, OHIO

JULIA S. NOLAND, ELIZABETH J. SHORT, AND LYNN T. SINGER SCHOOL OF MEDICINE CASE WESTERN RESERVE UNIVERSITY CLEVELAND, OHIO

I.

INTRODUCTION

When Stephen Schroeder (1987) edited an American Association on Mental Retardation monograph on neurobehavioral toxicology and teratology, the dominant, and for all practical purposes the only empirically studied, models of toxic substances related to mental retardation involved either alcohol or lead. Current statistics regarding drug use and abuse in the prenatal period, however, portray a diVerent picture. Alcohol abuse and its consequence, fetal alcohol syndrome (FAS), is still considered the most common, preventable form of mental retardation (Sampson et al., 1997) and aVects 0.5 to 2.0 children per 1,000 births in the U.S. (May & Gossage, 2001). However, 17% of pregnant women smoke cigarettes (Substance Abuse and Mental Health Services Administration, 2000), with tar and nicotine shown to negatively aVect birth weight and increase risk of abruptio placentae, anencephaly, and sudden infant death syndrome (Martin, 1992). Three in 100 babies are born in this country to mothers who report using illicit drugs (March of Dimes, 2001), and new illicit drugs, such as the ‘‘club’’ drugs methylenedioxymethamphetamine (MDMA), ketamine, and rohypnol, are rising in popularity (National Institute on Drug Abuse, 2002). Given that these are but a few of the proven or potential teratogenic substances to which a fetus may be exposed through maternal lifestyle, it is imperative to INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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update the knowledge base of both professional and lay people surrounding the issues related to behavioral teratology, developmental neurotoxicology, and mental retardation. A.

Brief Review of the Principles of Behavioral Teratology

The ﬁeld of behavioral teratology is relatively new, beginning in the 1960s with a series of articles by WerboV and Gottlieb (1963). The term ‘‘behavioral teratology’’ was coined to refer to the eVect of prenatal exposure to drugs and postnatal behavior. In 1986, Vorhees enumerated 12 principles of behavioral teratology, elaborating on Wilson’s general principles and mechanisms of teratogenic response (1977). These 12 principles included, with some minor behavioral modiﬁcations, Wilson’s 6 principles of teratology: (1) genetic determinism, (2) critical periods, (3) speciﬁc mechanisms, (4) teratogenic response, (5) target access, and (6) dose-response relationships. Principle 1 (Wilson, 1977) states that susceptibility to teratogenesis depends, in varying degrees, on heredity, environment, and the interaction between the two. The similarity between this principle and the traditional concept of cognitive development is clear. Principle 2, that susceptibility to teratogenic agents varies with developmental period, is central to teratology because it is the only one that explicitly incorporates a developmental perspective, (e.g., developing organisms are diVerent from adults). Principle 3, that teratogenic agents act in speciﬁc ways at the cellular level to initiate pathogenesis, emphasizes the biological nature of behavioral teratology. Principle 4, that the ﬁnal outcomes of a teratogenic process are death, malformation, growth retardation, and functional disorder, may be thought of as the basic deﬁnition of teratology. Principle 5, that access depends on the nature of the agent, points out the diVerence between agents, such as radiation or extreme temperatures, that reach the fetus directly versus agents, such as drugs, that are routed through maternal factors, either altering maternal function or crossing the placenta. And ﬁnally, Principle 6 states that as exposure increases the negative manifestations increase, from no eVect to lethality. This dose-response relationship has become a hallmark of the behavioral teratology ﬁeld. Although the original intent of ‘‘functional disorder’’ in Principle 4 may have referred to speciﬁc physiological impairments, this principle has been extended to refer to cognitive, sensorimotor, aVective, and/or social dysfunctions as well. It is also important to note that, except for some biological aspects of pathology (Volpe, 2000), the principles of behavioral teratology apply equally well to exposure in both the prenatal and postnatal periods. Most notably, although Principle 2 (critical periods) has long been accepted in developmental biology, ‘‘continued histogenesis, functional organization, and growth occur long after birth for many organ systems, most notably the

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brain (up to at least two years after birth in human beings), and for some systems even later. . .’’ (Vorhees, 1986, p. 25). In addition to the familiar example of FAS, other examples of prenatal teratogenic exposure eVects are radiation, methylmercury (MeHg), Lead (Pb), and organochlorines (PCBs). Although data on postnatal exposure eVects are still being collected, most clinicians and scientists have reached the conclusion that limiting the exposure of infants and toddlers to moderate-to-high doses of radiation, MeHg, Pb, or PCBs is equally important (Dietrich, 2000). One potential ramiﬁcation of this long developmental period in humans is that the eVects of prenatal exposure, in particular behavioral dysfunction, may not be evident until later in development. Another point to recognize in this regard is that, regardless of the ‘window of opportunity’ for access to treatment provided by prenatal and perinatal medical care, a woman will not routinely stop using drugs simply by virtue of giving birth. Children prenatally exposed to drugs may thus be at an increased risk of developmental delay or mental retardation through the inﬂuence of both an impoverished environment and postnatal drug exposure. It is also worthwhile to note that Principle 6 (dose-response) has often been interpreted to mean an invariant order or sequence of eVects as dosage decreases, from fetal death, to malformation, growth, and functional deviations and ﬁnally to no eVect, that holds for all drugs. However, there is not a prior reason to assume this sequence is valid for all agents. In theory, some drugs may produce malformations without behavioral dysfunction. In cases where an agent has been shown to aVect all four endpoints (i.e. death, malformation, growth, and function), however, behavioral outcomes should be a more sensitive index of a teratogenic eVect. To Wilson’s six principles, Vorhees (1986) oVered the six additional principles: environmental determination, types of teratogens, response relationships, maximum susceptibility, limits of susceptibility, and preconceptual/ transgenerational eVects as potential additions. In Principle 7, environmental determination, it was noted that a behavioral teratogenic eVect depends on both prenatal and postnatal environmental factors. This was meant to be more than just a restatement of Principle 1, and is the basis for the crossfostering studies done with animal models. ‘‘The fundamental purpose of fostering oVspring to a parent other than the biological parent is to sort out the direct eVect of the independent variable on the oVspring from the indirect eVect that could occur if the independent variable aVects the dam.’’ (Vorhees, 1986, pg. 36–37, italics added for emphasis). Principle 8 (types of behavioral teratogens) suggested that behavioral teratogenic eVects are produced by agents that are central nervous system (CNS) teratogens or are psychoactive. Although this formulation of behavior as solely a product of the CNS appears to take a restricted view of

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development, as opposed to a dynamic systems approach (Thelen, 1995), it is in line with mainstream clinical syndrome identiﬁcation, such as the Institute of Medicine’s diagnostic criteria of alcohol-related neurodevelopmental disorder (ARND) (Stratton et al., 1996). Principle 9 (response relationships) reinforced the point that research has repeatedly demonstrated that behavioral teratogenic eVects occur at doses lower than those causing malformations. This principle again contains the stipulation that this relationship likely holds true for all agents capable of producing both types of eVects but is not universally true of all agents. Although accompanied with several caveats, Principle 10 (maximum susceptibility) proposed that maximum susceptibility to behavioral teratogenic eVects corresponds to the period of CNS neurogenesis. This principle further provided that the CNS is vulnerable at all stages of development, a sometimes overlooked elaboration. Finding evidence to refute this principle will be diYcult in quasi-experimental studies of human drug exposure. It does, however, raise interesting questions in populations taking prescribed medications for long periods of time. Principle 11 (limits of susceptibility) was included to clarify the relationship between behavioral and malformation teratogens. Although for most agents there is a considerable overlap in dosages at which behavioral and other teratogenic eVects (growth retardation, malformation, embryo mortality) occur, there are dose levels at which three, two, or only one outcome is possible. It is also worth noting that neither this principle nor any of the others imply that a behavioral eVect, such as mental retardation in cases of FAS, is less important than a physical defect when they co-occur. Finally, Principle 12 (preconceptual and transgenerational eVects) was tentatively proposed to consider the possibility that some agents can induce eVects through exposure of the germ cells to the toxin. Naturally, this malemediated teratogenesis would occur before conception. A similar line of reasoning was made concerning unfertilized ova. B.

New Assessment Instruments

At the same time as behavioral teratology was changing how the eVects of prenatal exposure to drugs and other potential teratogens were conceptualized, methodological advances in the ﬁeld of pediatric neuropsychology were changing how relationships between nervous system structures and their corresponding behavioral functions were measured. In studies of infant outcomes, the traditional macro level measures, such the Bayley Scales of Infant Development or the Brazelton Neonatal Behavioral Assessment Scale, have been factor-analyzed, reﬁned, or augmented by more domainspeciﬁc measures. New assessment tools are often a hybrid of physiological

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parameters and behavior, focusing on sensory development, arousal and attention regulation, attachment, learning, or information processing, and are often adapted to speciﬁc populations, such as the fetus or infants born premature (Singer & Zeskind, 2001). In older pediatric populations, methodological advances in noninvasive electrophysiological and neuroimaging techniques (Stern & Silbersweig, 2001) are being integrated with neuropsychological assessments (Bernstein, 2000) to produce converging evidence on brain-behavior relationships in a variety of special populations. These neuropsychological measures have led to new approaches in the related ﬁeld of developmental neurotoxicology (Dietrich, 2000). These approaches are based on the inference that a toxin might disrupt CNS maturation without causing gross structural damage. Despite the lack of gross physical changes, subtle structural disruptions may be responsible for behavioral deviance of exposed individuals when compared to unexposed controls. It is relatively easy to see a parallel between this neurobehavioral model of toxicology and the challenges of understanding mental disorders, including some cases of mental retardation, in the absence of objective biological evidence. That is, even in the absence of a clear pathogenic etiology for mental retardation, subtle structural anomalies due to drug exposure could be responsible for behavioral deviance at a global level.

II.

FINDINGS FROM EARLY PRENATAL COCAINE EXPOSURE STUDIES

Two recent factors have brought prenatal drug exposure to the interest of researchers in the ﬁeld of mental retardation. The ﬁrst was the clear empirical evidence, by French (Lemoine et al., 1968) and American (Jones & Smith, 1973) scientists that prenatal exposure to alcohol produces a recognizable neurodevelopmental syndrome with attendant mental retardation. Following these ﬁndings regarding alcohol was the epidemic of cocaine use, primarily in the free-base form called ‘‘crack,’’ in the 1980s and early 1990s by women of child-bearing age (Musto, 1992). Combining these elements together with the evidence for the strong eVect cocaine has on the nervous system of adult users, it was hypothesized that cocaine was a potentially strong teratogen. It was expected that it would produce a wide variety of negative outcomes, including the possibility of increased rates of mental retardation, similar to or greater than those produced by alcohol. Most early studies of prenatal exposure to cocaine, however, were ﬂawed (Neuspiel, 1995). Singer et al. (2001) enumerated many of these studies and attendant problems in their review. Many previous studies used retrospective case identiﬁcation, or had small sample sizes, high attrition rates, and/or

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lacked information on children lost to follow-up, introducing the possibility of sample bias. Another problem of early studies was a diYculty in accurately identifying and quantifying cocaine use (Arendt et al., 1999b). Further, early studies often failed to report and/or account for the frequency and distribution of confounding and mediating variables, particularly exposure to other drugs and medical and environmental variables known to be associated with drug use and correlated with child outcomes. Additionally, as pointed out by Bendersky et al. (1995), many early studies used inadequate/subjective outcome measures and tested children at various ages. The methodological diYculties of most early cocaine exposure studies, therefore, make their internal and external validity questionable and interpretation of results problematic. It is also evident, in hindsight, that the search for congenital abnormalities (Bingol et al., 1987; ChasnoV et al., 1988) and frank neurological disorders such as seizures, sudden infant death syndrome, or profound mental retardation (see Hutchings, 1993 for review) was unlikely to be fruitful (Singer, 1997). For example, one of the early publications involving prenatal drug exposure (ChasnoV et al., 1988) involved a case of prune belly syndrome, a speciﬁc constellation of anomalies consisting of an abdominal wall deﬁcient in muscular tissue that produces a wrinkled external appearance of a prune. The syndrome also includes a dilated urinary tract, bilateral cryptorchidism, and in the majority of cases, multiple malformations of the cardiopulmonary, gastrointestinal, and orthopedic systems (Jennings, 2000). Instead of gross abnormalities such as prune belly syndrome (ChasnoV et al., 1988), our clinical experience and recent empirical evidence points to subtle neurological impairments in cocaine-exposed infants (Chiriboga, 1998) and perhaps subclinical cardiac dysfunction (Mehta et al., 2001). This shift to investigating subtle eVects of cocaine (Jacobson & Jacobson, 1996; Lester et al., 1998) may have prompted some to question the presumed detrimental relationship between prenatal cocaine exposure and cognitive deﬁcits (Frank et al., 2001). Further, a lack of consistent ﬁndings demonstrating a signiﬁcant adverse eVect of prenatal cocaine exposure on mental and behavioral development produced a backlash against labeling children ‘‘crack babies’’ (Mayes et al., 1992). In some ways, this phenomenon regarding labeling was similar to how the term mental retardation has taken on a pejorative meaning (Taylor, 2002). Although there are problems with the overgeneralization of negative ﬁndings based on case studies and retrospective data, such as stigmatization of cocaine-exposed children as ‘‘crack kids’’ and the punitive stance evidenced toward women who use cocaine during pregnancy (Zuckerman et al., 2002), there may be a parallel danger in assuming that cocaine exposure has no detrimental eVect on the fetus or, implicitly, that cocaine use by pregnant women is not harmful. A recent review of the cocaine literature by Frank and colleagues strenuously argued

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that: ‘‘there is no convincing evidence that prenatal cocaine exposure is associated with developmental toxic eVects that are diVerent in severity, scope, or kind from the sequelae of multiple other risk factors’’ (Frank et al., 2001, p. 1613). However, there is disagreement about aspects of the Frank et al. (2001) review, including their selection criteria and misinterpretation of ﬁndings. Stanwood and Levitt (2001) question the review’s omission of recent prospective studies by Leech et al. (1999) and Mayes et al. (1998) that demonstrate subtle but clinically important deﬁcits in cognitive and attentional process in 6- and 7-year-old children that are consistent with a prenatal cocaine exposure eVect on limbic system development. Stanwood and Levitt further question the failure of the review to adequately consider evidence collected from animal models that are less vulnerable to methodological limitations. Delaney-Black et al. (2001) voice their concern that Frank et al. misinterpreted the ﬁndings from the studies of the former authors (Delaney-Black et al., 1998, 2000). Delaney-Black et al. (2001) further caution that the review should not be construed as supporting the conclusion that there are no long-term eVects of prenatal cocaine exposure. Singer and Arendt (2001) raise two additional concerns. They argue that, by taking a conservative approach, attempting to isolate prenatal cocaine exposure from all other developmental inﬂuences, Frank et al. ignore other possible relationships between cocaine exposure and confounding, mediating, and moderating factors. Singer and Arendt also reinforce the point that, as can be the case when reviewers subjectively pick and choose the inclusion criteria, some important ﬁndings may have been overlooked and less compelling ﬁndings given inordinate weight.

III. A.

DIRECT AND INDIRECT PATHWAYS

Mechanisms of Effect

As with most drugs consumed by pregnant women, a case can be made for multiple pathways of eVect on child developmental outcomes. Some negative outcomes may occur as the result of a direct teratogenic eVect on the fetus or maternal physiology (e.g., FAS). Other outcomes may be due to an indirect eVect through behavioral or environmental factors related to the caregiver’s drug-using lifestyle (e.g., HIV). In the case of cocaine, both direct and indirect eVects have been posited (Singer et al., 1994). Cocaine may produce a direct eVect through the explicit transfer of the drug across the placenta and into the developing monaminergic neurotransmitter system of the fetal brain (Chiriboga, 1998). Another mechanism that could produce a direct eVect would be cocaine-induced maternal vasoconstriction reducing the

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supply of nutrients and oxygen to the fetus (Dow-Edwards, 1995). In addition to the potential direct eVects of cocaine, there are several indirect pathways by which cocaine might aVect development (Mayes & Bornstein, 1995). A partial list of indirect pathways includes: mental health problems concurrent or subsequent to drug abuse, impaired parenting skills, lack of ﬁnancial resources, and increased exposure to poverty and violence. The realization that exposure to a neurotoxicant, such as cocaine, could produce eVects through diVerent mechanisms led to a major shift in how research in this area was conducted. Attention shifted to numerous prenatal and perinatal confounding factors that might blur the picture of drug eVects (Richardson, 1998), including: exposure to other drugs, amount of prenatal care, or accuracy of drug exposure quantiﬁcation. Further, the understanding that drug eVects might be produced through indirect mechanisms meant that other variables known to impact infant development, such as gestational age, intrauterine growth, or maternal psychological status and IQ, had to be taken into account. Finally, the ﬁeld also recognized that developmental outcomes were likely either ameliorated or exacerbated by the postnatal environment. Variables highly related to drug use, such as family income, maternal age, number of siblings, out-of-home placements, and the nurturing level of the home, began to be considered in a second wave of more rigorous studies (Jacobson & Jacobson, 2001). Figure 1 illustrates the model we have developed to study prenatal cocaine exposure. However, it could be adapted to the study of exposure to other substances. A current list of confounding, mediating, or moderating factors that we take account of in our studies include: maternal demographics, such as age at delivery, parity, number of prenatal visits, years of education, marital status, socioeconomic status, income, employment, cognitive abilities, psychological distress, and use of alcohol, cigarettes, and other drugs at the time of assessment; current caregiver (if other than biological mother), such as cognitive and psychological functioning and use of alcohol, cigarettes, and other drugs; infant characteristics, such as race and gender; birth parameters, including gestational age, length, weight, and head circumference; infant medical condition, such as APGAR and Hobel Neonatal Risk scores; caregiving environment, such as number of placements, exposure to violence, and Home observation for the measurement of the Environment (HOME) score; and severity (amount and frequency) of prenatal exposure to drugs including alcohol, nicotine, marijuana, and cocaine. Many of these factors are time-dependent and are assessed at multiple points. Outcomes of interest include both medical such as health, growth, and neurophysiology, and developmental, such as cognitive, sensorimotor, language, aVective, social, behavioral, and neuropsychological domains. As we learn more

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

39

FIG. 1. Model of prenatal drug exposure.

about how prenatal cocaine exposure is involved in infant, child, and adolescent development, we continue to modify and reﬁne the variables that are included. B.

The Relationship of Prenatal Cocaine Exposure to Other Developmental Influences

The current research into prenatal cocaine exposure recognizes that both teratogenic and environmental inﬂuences are at work simultaneously, but the full nature of the relationship remains uncertain. Whether they act independently, adaptively, or synergistically is still unclear. Regardless, there is no doubt that environmental factors may exacerbate, ameliorate, or simply coexist with the prenatal drug eVect. Because the study of the complex relationships between prenatal exposure to illicit drugs and other factors that inﬂuence child development necessitates quasi-experimental designs, statistical procedures are used to assess relationships between variables. To account for confounding variables, the data analyses in our studies involve several steps. Confounding variables are deﬁned as factors, such as maternal education, that have been established to aVect child developmental outcomes in the general population independent of drug exposure. A potential confounding variable is entered into the

40

Robert E. Arendt et al.

analyses if it correlates with both an independent (e.g., cocaine exposure) and a dependent variable of interest, such as ﬁne motor development, at the p < 0.10 level (Jacobson & Jacobson, 1995). This methodology accounts for the possibility that a negative rearing environment would add to the teratogenic eVect and, thereby, magnify group diVerences. Similarly, it is possible that a positive rearing environment could mask a teratogenic eVect. Confounding variables, therefore, are entered into regression analyses before the drug exposure variables to establish the independent eVect of exposure after accounting for other eVects. An early ﬁnding of several studies was that children prenatally exposed to cocaine are also simultaneously exposed to other drugs, primarily alcohol and cigarettes (Woods et al., 1995). Because there are numerous studies demonstrating the negative eVects of these drugs on development, measures of polydrug exposure also must be included in the analyses. In our studies, drug exposure variables are entered into the regression equations in the following order: nicotine, alcohol, marijuana, and cocaine. Analyses involving cocaine exposure are generally performed using two strategies. In the ﬁrst, the drug exposure variable is coded as a bivariate, either present or absent. In the second set of analyses, drug exposure is coded as a continuous variable combining both amount and frequency into a single severity variable. In order to avoid underestimation of drug exposure eVects, mediating and moderating variables are distinguished from confounding variables. Mediating variables are considered to be part of a causal chain between the prenatal drug eVect and the outcome of interest. Physical outcomes at birth, such as gestational age, birth weight, height, and head circumference are considered mediating variables, since they could be aVected by the drug exposure and also have an eVect on outcomes. Potentially mediating variables are entered into the regression equation after a signiﬁcant eVect of exposure is found for any of the drugs. In this way, results of analyses excluding mediators can be understood in comparison to analyses including them (Jacobson & Jacobson, 1995). Finally, moderating variables are empirically deﬁned as characteristics of the participants that change the eVect of the drug exposure. An example of a moderating variable is gender. Again, these variables are entered into the regression analyses after a signiﬁcant drug exposure eVect is found. Moderating variables are tested by entering them in as an interaction term (example: cocaine exposure gender) if both independent eVects are signiﬁcant. It is also possible that prenatal exposure to cocaine alters the neurodevelopmental process so that an exposed child is more susceptible to environmental factors. As children mature, plasticity in the CNS enables the typical child to develop the appropriate skills. Therefore, it is important to adopt a

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

41

longitudinal approach repeatedly measuring outcomes. Alternatively, when the child matures and is challenged by the environment to function at a higher level, hidden problems may emerge due to the subtle changes in the brain caused by drug exposure. As is readily apparent from the description of factors that must be accounted for over time when studying prenatal cocaine exposure, studies require initial recruitment of an appropriately large cohort of participants and intensive eVorts to maintain the sample. IV. A.

CURRENT FINDINGS

Newborns and Infants

In a rigorous, methodologically advanced, longitudinal prospective study of prenatal cocaine exposure, Singer and colleagues (Singer et al., 2000, 2001, 2002a,c) have reported developmental outcomes from a group of 415 newborns (218 cocaine-exposed and 197 unexposed) through two years of age. A research nurse recruited all of the participants from the same at-risk sample shortly before or after delivery at a large, urban hospital. Reasons for exclusion included: maternal psychiatric history, no meconium (controls), heroin use, HIV-positive, FAS, genetic or congenital abnormality, maternal mental retardation, signiﬁcant maternal or newborn medical illness, and maternal age <19 years. The majority of both the cocaine-using and the non-using mothers were African American and had low income or were unemployed. Drug-exposure status was conﬁrmed using a combination of maternal report and biological assay. To explore the dose-response relationships of cocaine exposure, we have employed three strategies. Initially, when the primary aim was to investigate group diVerences, analyses entailed dividing the participants into three groups: unexposed, light exposure, and heavy exposure. In order to be classiﬁed as unexposed, infants had to have negative results on all available indicators: meconium testing, infant urine screens, maternal urine screens, maternal self-report, and hospital records review. Infants who tested positive for cocaine on any one or more of the measures were identiﬁed as cocaine-exposed. Cocaine-exposed infants were then further subdivided into heavier and lighter categories based on a combination of maternal self-report or meconium results. If data from either of these two measures indicated maternal cocaine use greater that the 70th percentile for the user group, the infant was identiﬁed as heavier-exposed. In a more recent analyses (Singer et al., 2000, 2002a,c), Spearman correlations between severity of prenatal drug exposure based on maternal

42

Robert E. Arendt et al.

self-report by trimester and infant outcomes were used to establish doseresponse relationships. This second method allows each drug of interest (i.e., alcohol, nicotine, marijuana, and cocaine) to be considered as a continuous variable. Because users are likely to have diYculty in accurately remembering how much and when they used each drug and because there are legal incentives and social pressures to underreport use, the accuracy of maternal selfreported drug use has been questioned. We have demonstrated in prior studies that metabolite concentrations from meconium analysis have reasonable concordance with maternal self-report (Arendt et al., 1999b). When a woman denied cocaine use but her infant’s meconium screens were positive (n ¼ 10 in our sample), exposure data was estimated by assigning the median score for the group (heavy/light) to which the pair was assigned based on the meconium results as described previously. Although estimation of fetal drug exposure through meconium analysis has limitations (Koren et al., 2002), it may also be possible that quantitative biological markers, such as the amount of a drug or its metabolite in meconium, may detect higher levels of exposure more reliably. The ﬁnal method used to establish dose-response relationships, therefore, was to calculate Spearman correlations between concentrations of meconium metabolites of cocaine, particularly benzoylecgonine, and outcomes (Singer et al., 2000, 2002a). Cocaine-using mothers were older and had more children then non-using mothers. The cocaine-using mothers also had achieved lower educational levels, lower vocabulary scores, were less likely to be married, more likely to use other drugs, had higher psychological distress scores, and received less prenatal care than non-using mothers. Cocaine-exposed newborns had a signiﬁcantly shorter gestational age than the unexposed group and, after adjusting for the diVerence in gestational age, were smaller on all birth parameters (Singer et al., 2000). Of particular concern were ﬁndings that cocaine-exposed infants were more likely to be small for gestational age and microcephalic (head circumference less than the 10th percentile for gestational age) (Singer et al., 2002c). At 43 weeks post-conception, after controlling for other factors, the more heavily cocaine-exposed infants were four times as likely to be jittery and nearly twice as likely to demonstrate a neurobehavioral abnormality. At one year of age, the more heavily cocaine-exposed infants had lower auditory comprehension scores than unexposed infants and lower total language scores than lighter and unexposed infants, again independent of confounding factors. At 24 months, cocaine exposure accounted for a six-point deﬁcit in Bayley Mental Development Index (MDI) scores. Further, cocaine-exposed children were twice as likely to have signiﬁcant delays (MDI <80). Speciﬁc

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

43

ﬁndings of this ongoing study that relate to mental retardation will be highlighted later in this chapter. Why should anyone working in the ﬁeld of mental retardation worry about a six-point reduction in MDI points (Lester et al., 1998)? Weiss (1995) notes that such questions should be regarded from an epidemiological perspective. For example, consider the fact that there are approximately 4 million children born in the U. S. every year (http://factﬁnder.census.gov/ servlet/BasicFactsServlet; Oct 17, 2002). Also consider that prenatal drug exposure is a long-term problem and that prevalence is a major concern. In a large population (Weiss used a sample of 100 million, i.e., 4 million times 25 years), 2.3% or 2.3 million would be expected to score above 2 standard deviations, i.e. gifted, on a standardized test of intelligence with a mean of 100 and a standard deviation of 15. If that same normal distribution of scores is shifted lower, conservatively estimated from our cocaine study ﬁndings, by 5 points, yielding a mean of 95, only 990,000 will score above 130. By the same token and more to the point of the current discussion, instead of 2.3 million people scoring below 70 IQ, after the 5% downward shift more than twice as many, 4.8 million, people would fall below 70. Now consider the case if 10% of the population is aVected, a reasonably conservative percentage to use in an example of prenatal drug exposure based on the number of children exposed to cocaine in the late 1980s and early 1990s. In this situation, instead of 230,000 children falling below 70 IQ, 478,000 will be below 70. Although ‘‘. . .most initial predictions of catastrophic eVects of prenatal cocaine exposure upon newborns were exaggerated,’’ (Frank et al., 2001, p. 1614), the addition or prevention of 248,000 diagnosable cases of mental retardation, roughly 10,000 a year over this 25-year span example, is a strong reason why a six-point reduction in IQ attributable to prenatal cocaine exposure is important and should concern child advocates and mental retardation researchers alike. B.

Long-Term Consequences of Prenatal Cocaine Exposure

Our assessment of 376 children (190 cocaine-exposed, 186 non–cocaineexposed, retention rate ¼ 90.6%) at 4 years of age included the Weschler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R), which allowed us to investigate diVerences in verbal and performance intelligence between cocaine-exposed and non–cocaine-exposed children. We statistically controlled for the degree to which intellectual performance of cocaineexposed and non–cocaine-exposed children might diVer due to prenatal exposure to other substances (tobacco, alcohol, and marijuana) as well as diVerences in the environments in which they were or are currently being raised. We assessed several aspects of caregiver functioning (cognitive,

44

Robert E. Arendt et al.

mental, behavioral, substance use) in an attempt to establish the degree to which any observed diVerences between cocaine-exposed and non–cocaineexposed children were due to diVerences in the postnatal environment (Singer et al., 2001). Regression analyses were performed to control for any potentially confounding environmental variables, as well as the eVects of prenatal exposure to other drugs. Fetal cocaine exposure was a signiﬁcant predictor of lower Arithmetic and Object Assembly performance on the WPPSI-R, and heavier exposure predicted lower Vocabulary and Information scores (all p values < 0.05), independent of potential environmental and polysubstance confounds (Singer et al., 2001). In addition, independent eVects of cocaine were obtained for children’s anxiety and aggression as reported by the caregivers on the Child Behavior Checklist (CBCL) (Singer et al., 2002b). Finally, in a very recent analyses we have detected an eVect of prenatal cocaine exposure on expressive language at 4 years of age on the clinical evaluation of language fundamentals (preschool), with this cocaine eVect independent of potential confounding variables (Lewis et al., in press). In addition to the results reported in the preceding text, we have analyzed long-term outcomes collected from a similar, but completely independent, cohort of mothers and children recruited before meconium analysis procedures were available at our site. This cohort was recruited either at birth or from a high-risk clinic at 1- and 2-year-old well-baby visits in a large urban teaching hospital. The children were assessed at ages 4 months and 1, 2, 3, 4, 7, and 9 years. For the purpose of the current review, results from the 7-year visit and preliminary ﬁndings from the 9-year visit will be described. Interested readers can refer to Arendt et al. (1998) and Arendt et al. (1999a) for details of earlier ﬁndings. At the 7-year-old visit, 50% of the cocaine group and 54% of the non-cocaine group were males (p ¼ 0.53); 99% and 95% of the cocaine and non-cocaine groups, respectively, were African American (p ¼ 0.14). The groups were not diVerent on mean age. The cocaine and non-cocaine groups had signiﬁcantly diVerent distributions of primary caregivers (7 years: p < 0.001). The exposed group had a higher percentage of children residing outside maternal care (56% vs. 13%). At the 7-year-old visits, maternal education means were not diVerent between the exposure groups. Family income, however, was diVerent between the groups, with the monthly income of families with unexposed children signiﬁcantly higher ($1,025 vs. $1,528, p < 0.001). Data were available on 231 children (101 cocaine-exposed and 130 unexposed) at 7 years of age (86% of the enrollment sample). Findings from the developmental test of Visual Motor Integration-4th edition (VMI), the Bruininks-Oseretsky Test of Motor Proﬁciency (BOTMP), and an abbreviated form of the Wechsler Intelligence Scale for Children-3rd edition

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

45

(WISC-III) were analyzed. Initially, diVerences between group means were evaluated using t tests. There was a signiﬁcant diVerence on the VMI motor supplemental test scores (84.3 vs. 87.4, p < 0.05), with the cocaineexposed children not doing as well. There was also a non-signiﬁcant trend diVerence in the same direction on the BOTMP ﬁne motor subscale and total scores. On the abbreviated WISC-III, there were signiﬁcant diVerences on the Verbal subscale (84.5 vs. 88.5) and the prorated Full Scale (81.1 vs. 84.9) intelligence quotient scores (p < 0.05 for both). Again, the cocaine-exposed children did worse than the unexposed children. Further analyses controlling for environmental factors, as well as severity of alcohol, marijuana, and tobacco exposure, revealed independent negative eVects of cocaine exposure on visual-motor skills (p < 0.05) and a trend on overall motor functioning (p < 0.10). The most useful predictors of outcomes were the signiﬁcant positive eVects of a better maternal vocabulary (PPVT) and a more positive home environment. Initial studies from birth to 4 years with this cohort found delays in sensory motor development in infants and young children prenatally exposed to cocaine and other drugs. Our follow-up hypothesis was that children exposed to cocaine in-utero would show abnormalities in sensory processes and motor abilities at 7 years of age. To test that hypothesis, occupational therapists with specialized training administered 13 Sensory Integration and Praxis Test (SIPT) subtests to 96 cocaine-exposed and 113 unexposed children (Arendt et al., 2001). A multivariate analysis of variance revealed no overall exposure group eVect on SIPT performance. Additionally, there were no signiﬁcant group diVerences on univariate tests of the individual subtests. However, 78% of the exposed and 66% of the unexposed children displayed some form of low average/problematic functioning on the SIPT. Although these results were not as predicted, the poor performance by both groups on the SIPT suggest that environmental factors may mask diVerences due to prenatal drug exposure. It has been suggested that there are gender-speciﬁc behavioral eVects related to prenatal cocaine exposure (ChasnoV et al., 1998; Delaney-Black et al., 2000). A preliminary analysis was conducted on data from the CBCL completed by the primary caregivers at the 7-year visit in the sample recruited from both the high-risk clinic and the normal nursery. At the time of these analyses, complete data were available on 164 7-year-olds. Although there were no signiﬁcant diVerences between groups on the total score, there were trends (p < 0.10) for diVerences on the internalizing and the externalizing scales, with the exposed group exhibiting more problematic behavior on both scales. There was one diVerence in the subscale scores, with the cocaineexposed group exhibiting more aggressive behavior, consistent with Singer’s ﬁndings on a separate cohort at 4 years. There were also interesting gender

46

Robert E. Arendt et al.

diVerences. Although the cocaine-exposed males were not rated as signiﬁcantly diVerent from the unexposed males, the cocaine-exposed females were rated signiﬁcantly more problematic than the unexposed females on total, aggression, and attention scales. There were trends for diVerences on the internalizing, externalizing, socialization, and thought problems scales. Because these data were collected from the older sample that did not have meconium collected and because some of the participants were recruited 1 to 2 years after birth, these ﬁndings, however, should be interpreted with extra caution. Further analyses controlling for other drug exposure, postnatal environmental factors, and intelligence are planned. Based on our previous ﬁndings and the ﬁndings of other investigators, it was hypothesized that children exposed prenatally to cocaine may be at risk for neuropsychological problems at school age. To date, preliminary data on 173 9-year-old children (80 cocaine exposed, 93 unexposed) (66% of the total) have been analyzed (Arendt et al., 2002). The test battery included the Developmental Neuropsychological Assessment (NEPSY) and a repeated administration, this time in its entirety, of the WISC-III. The NEPSY is a relatively new, standardized, comprehensive test for children designed to assess basic and complex aspects of cognitive capacities critical to learning and adaptive functioning. The NEPSY includes a broad range of subtests, which, for the goal of this portion of the project, assessed four core domains: attention/executive functions, language, sensorimotor functions, and visuospatial processing. Analysis of exposure group by WISC-III IQ scores revealed a signiﬁcant group diVerence. Univariate tests revealed that the cocaine-exposed group scored signiﬁcantly below the unexposed group on the Verbal and Full Scale scores and there was a higher percentage of cocaine-exposed children who were mildly delayed (IQ < 80). Multivariate analyses of the NEPSY showed a trend (p < 0.10). Univariate tests revealed that there was a signiﬁcant group diVerence in the language domain, again with the exposed children performing worse (81.6 12.3 vs. 89.5 14.7). Further analyses of the language subtests revealed signiﬁcant exposure group diVerences on the Arrows subtest (p < 0.02), Phonological Processing (PP) and Comprehension of Instruction (CI) tests (p < 0.005), and a non-signiﬁcant trend for the Speeded Naming (SN) test. There was also a non-signiﬁcant trend eVect on the sensorimotor domain (p < 0.10). Although there are limitations to the later time-point data, taken as a whole, results from this long-term follow-up suggest that prenatal exposure to cocaine is associated with poorer developmental outcomes as late as 9 years of age, particularly in the language domain on a measure of phonological processing. These data are preliminary and resolution of mechanisms by which cocaine exposure may have an eVect requires further analyses to include numerous environmental factors. In addition, gender may play a

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

47

role, particularly on behavioral ratings. These results indicate that children with a history of prenatal exposure to cocaine may have speciﬁc sensorimotor delays early in childhood and language, particularly phonological processing, and other cognitive diYculties later. C.

Parenting by Women With a History of Cocaine Abuse

Even when in treatment programs, many families headed by women with a history of substance abuse live in negative economic and social conditions (Mayes et al., 1997). Cocaine abuse is also associated with a relatively high rate of illegal activity (Boyd & Mieczkowski, 1990) that may increase the stress and social isolation of these families. For children reared by women struggling with drug dependency, the health of the parent-child relationship is of particular concern. 1. PARENTING BEHAVIOR

Children reared by cocaine-abusing women have been found to be at-risk for increased physical abuse and neglect. Wasserman and Leventhal (1993) tracked children from birth to 2 years of age and recorded the number of injuries consistent with maltreatment in 47 cocaine-exposed children and 47 non–cocaine-exposed children matched on race, family income, and parents marital status. Signiﬁcantly more of the cocaine-exposed children (23%) experienced episodes of maltreatment than controls (4%). Parents with a history of drug and alcohol abuse demonstrate less understanding of child development (Kaltenbach & Finnegan, 1998), endorse harsher forms of discipline (Wellisch & Steinberg, 1980), and describe their own experience of parenting in a manner associated with poorer child outcomes (Bernardi et al., 1989). Similarly, Bauman and Dougherty (1983) found that women who use drugs were more likely to threaten physical punishment and less likely to use positive reinforcement than socio-economic status (SES)-matched controls. 2. PARENT-CHILD INTERACTIONS

Observational studies that compare the interaction behaviors of mothers with and mothers without a history of substance abuse have been the focus of recent attention (Hogan, 1998). Several studies have reported no motherchild interaction diVerences associated with cocaine use (Black et al., 1993; Johnson & Rosen, 1990). Neuspiel et al. (1991) found no diVerences in newborn feeding behavior between cocaine-abusing women and controls. Another study also found no diVerence between cocaine-using and cocaine-naive women in their responsivity to their 4-month-old infants (Bendersky & Lewis, 1998).

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However, several other studies have reported disturbed maternal-child social interactions in cocaine-using women when compared to SES-matched controls. Drug-abusing women demonstrate less positive aVect in playing with their infants (Burns et al., 1997; Minnes et al., 2001b). In addition, cocaine-abusing women were found to be less sensitive in interactions with their infants (Mayes et al., 1997). Bernstein, Jeremy, and Marcus (1986) found reduced levels of responsiveness in drug-using women in their interactions with their infants, a ﬁnding recently replicated by Suchman and Luthar (2000). Not only are disturbances noted on the parental side of the relationship, but also on the infant/child side. Children reared by cocaine polydrugabusing women are less likely to be securely attached than children of low SES controls or depressed mothers (Espinosa et al., 2001), a possible consequence of less responsive parenting. Indeed, the eVect of prenatal substance exposure on child behavior may exacerbate these disruptions of parent-child interactions. The behavior of an alcohol exposed infant inﬂuences the quality of the mother-child interaction (O’Connor et al., 1992, 1993). One interpretation, by Johnson et al. (2002), of this inconsistency (the ﬁndings of disrupted parenting behavior by drug users in some studies but not others) is as follows: substance use in the absence of other mental health issues, cognitive disabilities, or life stressors does not disrupt parenting to the extent that it does in combination with these other risk factors. If this interpretation is correct, inconsistencies in reported ﬁndings may result from diVerences in study samples, with less disruptions presenting in less at-risk groups. 3. MATERNAL MENTAL HEALTH

The reported rate of psychopathology in drug-abusing mothers is high (Luthar et al., 1998) and women who used cocaine during pregnancy have been found to be at risk for depression, paranoia, anxiety, and personality disturbances (Howard et al., 1995; Singer et al., 1995, 2002c). In a study of cocaine-using mothers, paranoia alone or accompanied by depression predicted less sensitive caregiving and less secure infant attachment (Espinosa et al., 2001). Does substance abuse uniquely account for any of the disruptions in parenting seen in addicts independent from other mental health issues? In some studies, after considering diVerences in the psychological state of the mothers, there has been no unique variance in parenting behavior attributable to substance use. Minnes et al. (2001b) found that both maternal psychological distress and impaired executive functioning

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

49

mediated the relationship between cocaine use and maternal aVective behavior. Another study found that SES and maternal psychosocial functioning were better predictors than drug addiction itself of the interaction style of methadone-treated women and their controls (Bernstein et al., 1984). However, we have presented preliminary evidence that prenatal cocaine use was associated with less maternal sensitivity to infant cues during the ﬁrst postnatal year and that this eVect was independent of maternal education, employment, SES, IQ, or psychiatric health (Minnes et al., 2001a). Two other studies have found disruptions in parenting behavior that could not be attributed to diVerences in parent mental health. In the ﬁrst, drug addiction was related to child neglect even after controlling for SES and maternal psychosocial functioning (Egami et al., 1996). More recently, Johnson et al. (2002) investigated, in a sample of over 300 women, the interactions between mothers with and without a history of cocaine use and their preschool-aged children. The two groups were not diVerent in socio-economic variables, psychiatric symptoms, cognitive functioning, or the amount of stress they reported having experienced recently. The mother-child interactions were rated, blind to drug status, with an instrument reliable in low SES and high-risk samples. The behaviors of the mothers with a history of cocaine use were rated higher on negative characteristics (hostility and intrusiveness) and lower on positive characteristics (quality of instructions and conﬁdence). The interaction styles of the children were not diVerent by group so the parenting diVerences did not result in behavioral diVerences in the children. Rather, the results indicate that a history of maternal cocaine use may be interpreted as a risk to the maternal-child regulatory relationship that is not attributable to other maternal factors or child behaviors. D.

Foster/Adoptive Care as Intervention

The placement of children into foster/adoptive homes, as frequently mandated by child welfare agencies in cases of maternal drug use, can be characterized as a naturalistic intervention. The enormous implications of this policy for society are beyond the scope of this chapter. Our longitudinal study, however, allows us to tentatively address questions concerning the eVectiveness of foster/adoptive care as a cognitive intervention for cocaineexposed children. More speciﬁcally, does growing up in a foster/adoptive care environment improve the cognitive functioning of prenatally cocaineexposed children and, if so, does this change in the postnatal environment completely compensate for prenatal cocaine exposure? In our longitudinal cohort of children at 4 years of age, almost all (95%) of the non–cocaine-exposed children were in the care of their biological

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parents, whereas only 55% of the cocaine-exposed group were in the care of their biological parents (Singer et al., 2004). Of the 45% of children in the cocaine-exposed group who were not in the care of a biological parent, 22% were in non-relative placements, roughly equally distributed into foster or adoptive care, and 23% were cared for primarily by relatives other than their parents. For the children in foster/adoptive care at 4 years of age, their ﬁrst placement out of their biological mothers’ care had occurred early, before 6 months of age for the majority. Our contention that foster care is a naturalistic intervention rests on the fact that child welfare agents have requirements for potential foster and adoptive parents that are stricter than the requirements relative caregivers or biological parents must meet. As such, these diVerences are reﬂected in the higher educational attainment of the foster/adoptive caregivers as compared with the combined group of biological parents and relative caregivers (Singer et al., in preparation). The foster/adoptive caregivers had higher levels of verbal IQ as assessed by the PPVT-Revised and provided a more stimulating home environment as assessed by the preschool HOME-interview version (Table I). Both maternal PPVT-R and HOME scores have demonstrated relationships with child IQ (Bornstein & Hayes, 1998; Bradley & Caldwell, 1976).

TABLE I ENVIRONMENTAL DIFFERENCES BY CAREGIVER GROUP Cocaine

Home Current caregiver PPVT-R score GSI Heavy exposure Average number rocks

Non-Cocaine

I

II

III

BIO/REL (n ¼ 148) M SD

Adopt/FC (n ¼ 42) M SD

(n ¼ 186) M SD

F/X2

p

41 7 76 17

45 7 89 18

41 7 78 15

5.77 8.55

0.003* 0.0002*

0.35 0.4 75 (51%) 21 35

0.24 0.2 27 (64%) 42 71

0.39 0.4 — —

1.79 2.4 2.6

0.7 0.12 0.01

*II > I and III. BIO/REL ¼ biological/relative care; FC ¼ foster care; GSI ¼ General Severity Index score from Brief Symptom Inventory; HOME ¼ Home Observation for the Measurement of the Environment; m ¼ mean; PPVT-R ¼ Peabody Picture Vocabulary Test-Revised; SD ¼ Standard deviation.

51

PRENATAL DRUG EXPOSURE AND MENTAL RETARDATION

It should be noted that the children placed in this foster/adoptive care environment were, at birth, the most vulnerable ones, as measured by the degree of cocaine exposure (Table I), and were born earlier and smaller than the cocaine-exposed children in biological parent/relative care (Singer et al., in preparation). Despite their greater initial vulnerability, the cocaineexposed children in foster/adoptive care had higher verbal IQs than the cocaine-exposed children in the combined biological parent/relative caregiver group (Singer et al., 2001). On the Full Scale WPPSI-R assessment, signiﬁcantly more of the cocaine-exposed children in biological parent/relative care scored in the ‘‘intellectual deﬁciency’’ range than either cocaine-exposed children in foster/adoptive care or non–cocaine-exposed children (Table II). So, in answer to the ﬁrst question: comprehensive environmental changes appear to reduce the prevalence of mental retardation in cocaine-exposed children. However, there are limitations to the ameliorating eVects of even this intensive intervention. Regardless of whether they have been placed out of home or not, cocaine-exposed children were less likely than unexposed children to have full-scale IQ scores above the normative mean (Singer et al., 2004) (Table II). At this point we can only speculate about why foster/adoptive care was associated with reducing the eVect of cocaine on the low functioning end, but not with raising the number of above average IQ scores. One possibility open to empirical investigation is the attentional diYculties that have previously been associated with prenatal cocaine exposure (Leech et al., 1999; Mayes et al., 1998) may interfere with the success of the more demanding items. If attentional demands of the testing situation increase as the diYculty of the test questions increase then any persistent

TABLE II GROUP DIFFERENCES BY COCAINE AND CAREGIVER STATUS Cocaine

IQ > 100 IQ < 70

Non-Cocaine

I

II

III

BIO/REL (n ¼ 148) (n) %

Adopt/FC (n ¼ 42) (n) %

(n ¼ 186) (n) %

X2

p

(6) 4% (36) 26%

(1) 2% (3) 7%

(21) 12% (29) 16%

6.2 4.5

0.01* 0.03{

*III > I and II. { I > II and III. BIO/REL ¼ biological/relative care; FC ¼ foster care.

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attention problems could aVect the rate at which above average scores were attained. Two other studies, Koren et al. (1998), and Van Beveren et al. (2000) have reported impaired cognitive functioning of cocaine-exposed infants raised in adoptive homes as compared to unexposed controls. Both found that despite a higher SES postnatal environment cocaine-exposed children were not functioning as high as unexposed children born (Koren et al., 1998) or adopted (Van Beveren et al., 2000) into higher SES environments.

V.

PRENATAL DRUG EXPOSURE AND THE ETIOLOGY OF MENTAL RETARDATION

Establishing how prenatal exposure to drugs adds to the prevalence rate of mental retardation is diYcult, but nonetheless important for several reasons, including treatment, prevention, and administrative purposes (American Association on Mental Retardation, 1992). Leaving out the ‘‘unknown’’ as a category, the etiology of mental retardation was traditionally divided into two broad categories: biological and psychosocial. Under the biological category, the Diagnostic and Statistical Manual of Mental Disorders-4th edition (American Psychiatric Association, 1994) reports that the etiology of mental retardation cases is as follows: 5% of cases are due to heredity, 30% of cases are due to early alterations of embryonic development, 10% of cases are due to prenatal and perinatal problems, and ﬁnally, 5% of cases are due to general medical conditions acquired in infancy and childhood. The reported prevalence of environmental inﬂuences and other mental disorders is 15% to 20%; 30% to 40% of cases have no clear etiology. By way of comparison, in a recent study of 2,106 residents with severe mental retardation (IQ <50) living in a state-operated facility, Stevenson et al. (1996) reported etiology as: genetic 19.6%, environmental 26.9%, and unknown 53.6%. The etiology rates cited above illustrate two issues. First, the distinction between biological and psychosocial is often blurred (Rowitz, 1986). For example, mental retardation associated with anoxia due to premature placental separation appears on the surface to be biological, but in some cases may also stem from poverty, poor prenatal care, and/or prenatal cocaine or other drug exposure. Researchers accounting for the amount of variance, public policy-makers setting political priorities, and therapists making distinctions between primary and secondary axis may all ﬁnd it important to distinguish between the various contributing factors. On the other hand, except for the possibility of treatment and prevention in the future, such partitions probably make little diVerence to either the child or those who

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care for them. Telling caregivers that their child lost a certain number of IQ points due to prenatal drug exposure, a certain number more because of an additional factor, such as poor prenatal care, and so on for each identiﬁed unfavorable factor would obviously be misleading. In the same sense, it is arbitrary to assign the etiology of mental retardation to prenatal exposure to cocaine, alcohol, or cigarettes in the usual case where the child is exposed to all three. A second issue raised by questions of etiology but which are beyond the scope of this paper is the relationship between prenatal and postnatal environments and genetic factors. Some researchers have suggested that sensitivity to alcohol (Crabbe, 2002; Nestler, 2000) and vulnerability to cocaine (Kendler & Prescott, 1998) abuse and addiction in women are inﬂuenced by genetic factors. How these genetic factors interact with the in utero environment may relate to the diVerences in birth outcomes among children exposed to drugs. It has long been recognized that some children born to mothers who consumed high levels of alcohol while pregnant appear relatively unharmed whereas others exposed to relatively lower amounts of alcohol seem greatly aVected (Abel, 1995). Similar diVerences in outcomes with regard to cocaine exposure are, as of now, largely unexplored.

VI.

CONCLUSIONS

A reasonable conclusion, based on the evidence available from our ongoing, methodologically sound study, is that prenatal exposure to cocaine is a behavioral teratogen. The early ‘‘rush to judgement’’ (Mayes et al., 1992) that occurred with crack cocaine can be replaced by sound research. As is also now evident from studies of cocaine exposure, even in cases where no birth defects are obvious, long-term follow-up may be needed to detect and ameliorate neurobehavioral eVects. At both the individual and the societal levels, even in situations where etiology and pathogenesis are well known, developmental disorders such as mental retardation do not emerge as a result of a single factor or at a single point in development. Neither a prenatal teratogenic environment nor a postnatal rearing environment model of development following prenatal cocaine exposure has total explanatory power. Additionally, they are not diametrically opposed. In fact, we argue that a melding of the two approaches is not only possible but also desirable and even necessary. At each stage in development the human brain is uniquely susceptible to exposure of teratogenic compounds. It is also readily apparent that prevention and treatment of conditions arising from exposure to teratogenic

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substances will be largely dictated by the stage or stages in which the exposure occurs. There is extensive, elegant evidence that the period from conception to birth is critical for CNS development and that the fetal CNS is exquisitely sensitive to neurotoxic agents. From the perspective of a typically lifelong developmental outcome such as mental retardation, however, arguing whether the prenatal environment is more or less important than the postnatal environment is pointless. Rather, because one of the deﬁning criteria of mental retardation is that it manifests itself, not only at birth, but up to the age of 18 years (American Association on Mental Retardation, 1992), it is essential to consider that ﬁndings on myelination, dendritic arborization, synaptic pruning, and lifelong neurogenesis support the plasticity of the human brain throughout life. Although postnatal risk and intervention factors occur later in a causal developmental model, these postnatal factors will continue to have an inﬂuence over a longer time frame than the prenatal factors. The traditional etiological classiﬁcation of mental retardation—prenatal, perinatal, or postnatal—has several drawbacks. It creates ambiguous classiﬁcation situations. For example, when does an inborn error of metabolism, such as phenylketonuria, or a neurodegenerative disorder, such as Retts syndrome, cause mental retardation? It also leads to the false impression that developmental outcomes (eVects) are caused at a single point or in a short period in time. What our current model of drug exposure emphasizes is that a better distinction to make is between direct eVects, such as organogenesis, versus indirect eVects, such as maternal psychological status, the drug can have on development. This is not to suggest that the timing of a life event is unimportant. From the standpoint of intervention, the prenatal period presents unique opportunities and challenges in comparison to the postnatal period. This is, however, a suggestion to consider timing of the insult as only one factor in a host of factors to consider when preventing, diagnosing, and treating mental retardation. In this way the focus is not on a particular event in time (i.e., birth), which for many drug-exposed infants was uneventful, but on the nature of the eVect and the mechanism by which it operates. Given those admittedly debatable points, two further implications arise. First, neither prenatal drug exposure nor the avoidance of prenatal drug exposure ensures that the newborn or young child is protected from postnatal exposure, either with the same or diVerent neurotoxin. In terms of investigating cocaine exposure, this translates into accounting for the fact that living in an environment where drugs are used, particularly those like ‘‘crack’’ that can enter the child’s respiratory system through secondhand smoke, can play a role in a child’s development, both through direct postnatal neurotoxic eVect and through an indirect eVect mediated

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through the caregiving environment. This also highlights ﬁndings from cocaine exposure studies that other risk factors, such as exposure to nicotine, marijuana, and environmental toxicants such as lead, correlate with cocaine exposure. Second, concentration on prenatal exposure may create a false impression that, should a newborn or infant show no immediate unfavorable eVect of prenatal drug exposure or outgrow an early acute eVect, the danger is over. Because behavioral outcomes change in adolescence, there is the possibility of ‘‘sleeper’’ eVects that do not show up until later in development when the aVected function typically appears. It is also possible for an infant to test average or above average, for example on the motor items where high muscle tone possibly related to drug exposure leads to advanced performance, and then gradually decline in childhood. Although it is estimated that 70,000 chemicals are in commercial use, only a few, such as methylmercury and polychlorinated biphenyls, are documented to be human teratogens (Shephard, 1994). Most environmental chemicals have not been subjected to developmental neurotoxicity testing. Pregnancy outcomes following maternal use of newer pharmaceutical agents have been tested for rates of major congenital malformations and other birth outcomes. On the other hand, longitudinal data have not been collected on the neurodevelopment of children exposed in utero to medications a woman might take for seizures, cancer, HIV, depression, or any of the host of other medical conditions. Current multivariate investigations of prenatal cocaine exposure can serve as models for what will undoubtedly be a growing area of behavioral research into prenatal substance exposure. In designing intervention strategies for infants and young children with mental retardation, it is important to note that services are primarily based on behavioral, not biological, criteria. Development in children is diYcult to predict, both because current assessment instruments lack precision and because behavior changes dramatically from birth to school age as part of the natural process of maturation. From the intervention perspective, therefore, prenatal exposure to drugs may be best thought of as a risk factor for mental retardation, rather than the cause of the exposed child’s intellectual problems, potentially interacting with other risk factors to produce detrimental outcomes for children and society as a whole.

ACKNOWLEDGMENTS Portions of this paper were presented at the 34th Annual Gatlinburg Conference on Research and Theory in Intellectual and Developmental Disabilities, in March 2001. Partial support for Drs. Arendt, Noland, Short, and Singer came from NIDA grants number DA F3205904, DA07358, and DA07957.

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Spina Bifida: Genes, Brain, and Development JACK M. FLETCHER, HOPE NORTHRUP, SUSAN H. LANDRY, LARRY A. KRAMER, AND MICHAEL E. BRANDT DEPARTMENT OF PEDIATRICS UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT HOUSTON HOUSTON, TEXAS

MAUREEN DENNIS, MARCIA A. BARNES, AND SUSAN E. BLASER DEPARTMENT OF PSYCHOLOGY THE HOSPITAL FOR SICK CHILDREN TORONTO, ONTARIO, CANADA

H. JULIA HANNAY, KIM COPELAND, AND DAVID J. FRANCIS DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF HOUSTON HOUSTON, TEXAS

Spina biﬁda meningomyelocele (SBM) is the most common severely disabling birth defect in North America; nevertheless, our knowledge of this condition is fragmented, incomplete, restricted, and unidimensional. Knowledge is fragmented because research has been largely disciplinespeciﬁc, with studies of genetics, development, brain imaging, and cognitive outcomes conducted in parallel rather than in integration. Knowledge is incomplete because little research has exploited recent developments in genetic analysis, structural and functional brain imaging, and decomposition of cognitive functions. Knowledge is generally restricted to a relatively narrow range of the lifespan, typically the school-age years. Knowledge is unidimensional, because the conﬂuence of multiple factors relevant to outcomes has not been studied in a multidimensional framework. INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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In this Chapter, we discuss SBM from the viewpoint of an integrated, multidisciplinary research program directed towards characterizing SBM and the biological and environmental factors that account for variability in outcomes. The central idea, shown in Figure 1, is that a complex pattern of gene/environment interactions produce a neural tube defect that is associated at birth with distinctive physical, neural, and behavioral phenotypes. These phenotypes themselves have both a modal group expression and variations in key components that account for individual diVerences. The physical phenotype of SBM follows directly from the spinal compromise. Children with SBM are born with a spinal lesion that produces long-term impairment of lower and upper extremity coordination, often with signiﬁcant paraplegia and limited ambulation. Yet importantly, SBM is a developmental disorder of both spinal cord and brain. While the public perception of SBM highlights the spinal cord defects and their life-long orthopedic sequelae, the less-studied neural phenotype, also a consequence of early gestational disruptions in neuroembryogenesis, includes signiﬁcant perturbations of brain development. These include congenital abnormalities of several brain regions—cerebellum, midbrain, and corpus callosum— as well as alterations of brain structure and growth as a result of hydrocephalus and the need for shunting. The cognitive phenotype is associated with the diverse brain compromises in SBM. Cognitive problems and learning disorders appear early in the development of infants and preschoolers, persist throughout the years of formal schooling, and continue into adulthood, limiting employment options and quality of life. For a quarter of a century, our group of researchers has studied SBM and other early brain disorders that lead to hydrocephalus. Beginning from a series of discipline-speciﬁc projects, we assembled as a group in 1998 with

FIG. 1. Central organizing framework for the research program. Complex gene-environment interactions produce variability in physical, neural, and cognitive phenotypes.

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funding from the National Institute of Child Health and Human Development for a program project entitled ‘‘Spina Biﬁda: Neurobiological and Cognitive Variability.’’ The goals of this project have included systematic interdisciplinary research addressing the genetic, neural, and cognitive components of SBM in infants, preschoolers, and school-aged children. During the course of the studies, we have adopted a life span approach to the SBM condition, recognizing the importance of studying adult outcomes and their developmental origins. This history of discipline-speciﬁc and multidisciplinary, collaborative research has shaped our view of SBM (Fig. 1). We believe that the eVects of SBM are evident throughout the life span, and modeled at key points in development by a cascade of events involving gene, brain, and experience. The neural phenotype of SBM, itself the product of genetic and environmental factors, leads to early core deﬁcits in cognitive functions: timing and motor control, and attention orientation. We have hypothesized that early deﬁcits limit active exploration and other interactions with the environment reﬂecting similar hypotheses developed for other neurologically impaired populations, such as cerebral palsy (Abercrombie, 1964; Rourke, 1989). The environment is altered by caregivers to compensate for these diYculties (Holmbeck et al., 2002). As the individual with SBM moves into the school-age years, the neural and cognitive resources available for learning are reduced (Fletcher et al., 2000). The adult with SBM has often failed to master the important academic and independent living skills, limiting higher education and vocational options (Bowman et al., 2001; Hetherington et al., in press). In this Chapter, we will explore the modal outcomes of SBM at a group level, and identify the sources of variability in outcomes for the physical, neural, and cognitive phenotypes, at an individual level.

I.

NATURE OF SPINA BIFIDA

Spina biﬁda is a generic term for a class of neural tube defects that represent the most frequent cause of congenital brain and spine malformations in children. Spina biﬁda meningomyelocele is the most common condition in children who survive neural tube defects. The deﬁning spinal lesion, meningomyelocele, is a ﬂuid-ﬁlled sac that herniates and protrudes through the spinal cord and meninges. It can occur at any level of the spine, secondary to a failure of the more caudal end of the neural tube to close. Depending on the level of the spinal lesion, children born with a meningomyelocele have problems with ambulation (including complete paraplegia), neurogenic bladder and bowel (often leading to incontinence), and upper limb control.

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Most children with SBM have a malformation of the cerebellum and hindbrain, the Chiari II malformation, that blocks cerebrospinal ﬂuid ﬂow and leads to hydrocephalus and shunt treatment in 80% to 90% of individuals (Reigel & Rotenstein, 1994). Thus, SBM aVects the development of the brain in two ways. First, the failure of neuroembryogenesis is associated with anomalies in regional development, especially the corpus callosum, midbrain/tectum, and cerebellum. Second, additional injury to the brain occurs due to hydrocephalus and its treatment, which disrupts not only the development of white matter tracts and myelination, but also cortical neuronal development (del Bigio, 1993). Despite progress in antenatal diagnosis, and apparent reductions in prevalence in North America, SBM remains a signiﬁcant developmental disability. The child with SBM faces a lifetime of motor disability as well as orthopedic and neurosurgical monitoring. Correction of congenital spinal disorders (scoliosis, kyphosis) is often necessary, and other problems in the spine (tethered cord, syringomyelia) may require intervention. Additional surgery is related to shunt malfunctions or infections. The Chiari II malformation may press down on the brain stem, causing life-threatening problems with respiratory function and sometimes death without upper cervical surgery. These multiple medical challenges produce long-term needs for psychosocial adaptation to the medical needs and cognitive and motor consequences by caregivers, children, and young adults with SBM (Holmbeck et al., 2002). Learning compromises form an important part of the constellation of disabilities in SBM. Cognitive outcomes will vary, but children with SBM commonly experience diYculty in ﬂexible problem-solving, attention, contextual language, and mastery of the complement of educational skills necessary for full academic success. The magnitude of these learning diYculties varies, and is undoubtedly inﬂuenced by instructional factors, and by the expectations and approaches that parents and other caregivers develop in addressing the orthopedic and cognitive consequences of SBM (Holmbeck et al., 2002). The pioneers of the shunt treatment that became widely available in the 1960s are now reaching adulthood, constituting the ﬁrst generation of survivors. Little is known about these young adults, although many have signiﬁcant functional disabilities, despite average intelligence and proﬁciency with several aspects of language and academic skills. A.

Epidemiology and Relation to Other Congenital Disorders

Neural tube defects occur in approximately 1 to 2 per 1000 live births in North America, with SBM representing a subset that occurs in 0.5 to 0.7 per 1000 births. Other neural tube defects include encephalocele, anencephaly,

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holoprosencephaly, and craniorachischisis; the latter three are typically lethal. Anencephaly, essentially absence of the cerebral hemispheres with a hypoplastic brain stem, has about the same incidence as SBM. The others are more rare: encephalocele (also called cranium biﬁdum to represent the dysraphism in the skull from which the meninges and brain protrude); holoprosencephaly, essentially absence of the cerebral hemispheres; and craniorachischisis, in which the entire central nervous system is exposed with an absent or split spinal cord. Meningomyelocele is not the only type of spina biﬁda. Some children are born with a less severe spinal defect in which the lesion is a closed defect with no herniation, called a meningocele, or with a fatty tumor, termed a lipoma. These defects result in ambulation, and bladder and bowel diYculties, although they rarely entail a complete loss of ambulation or severe brain problems, such as the Arnold Chiari II malformation, dysgenesis of the corpus callosum, or hydrocephalus. Spina biﬁda occulta is a milder spinal defect that is relatively common. It is a failure of vertebral column formation after neural tube closure that results in opening of the vertebral arch. Spina biﬁda meningomyelocele (ﬁve times more frequent than other major spinal dysraphisms) is responsible for most cases of congenital hydrocephalus. The two other primary congenital conditions associated with hydrocephalus, Dandy-Walker syndrome and aqueductal stenosis, may represent neural tube defects (Menkes, 1995), although their etiology is not wellestablished. Dandy-Walker syndrome occurs in about 1 per 25,000 live births. Its deﬁning characteristic is a cystic malformation of the fourth ventricle with partial dysgenesis of the vermis of the cerebellum, often with partial dysgenesis of the corpus callosum (Chuang, 1986). About 70% to 80% of children with Dandy-Walker syndrome develop hydrocephalus. Aqueductal stenosis occurs in approximately 1 per 17,000 live births and is generally observed only in the presence of hydrocephalus, which is due to the narrowing of the cerebral aqueduct that gives it its name (Barkovich, 1995). The cerebellum is often normal in aqueductal stenosis (in contrast to SBM and Dandy-Walker syndrome); the exceptions reﬂect a downward extension of the cerebellum due to hydrocephalus, which may be identiﬁed as an Chiari I malformation. B.

The Cognitive Phenotype

Children with SBM are characterized by a number of cognitive strengths and weaknesses that are often expressed as group averages in diVerent studies (Dennis, 1996; Fletcher et al., 2000; Wills, 1993). In the course of our studies, we have adopted two concepts to characterize outcome in SBM: the modal proﬁle, and sources of variability around the modal proﬁle.

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Although it is common in the literature to describe group averages for children with SBM in multiple outcome domains, SBM is more accurately characterized by considering not only a modal proﬁle, but also variability in the overall level of functioning and the characteristic pattern of strengths and weaknesses. A two-fold goal of our research program has been to delineate the modal proﬁle more exactly, and to account for the variability responsible for the range of outcomes. The sources of this variability include genetic factors and variations in the neural phenotype (including hydrocephalus) as well as environmental factors, especially early in development. The delineation of the modal proﬁle has a long research history, and involves studies of school-age children with SBM in speciﬁc cognitive and academic domains. Research studies have diVerentiated preserved and impaired functions within a number of cognitive and academic domains. As a group, children with SBM are stronger in language and weaker in perceptual and motor skills, demonstrated through many comparisons of verbal and performance IQ scores (Dennis et al., 1981; Fletcher et al., 1992; Raimondi & Soare, 1974). Within the language domain, children with SBM use and understand single words with some skill; however, many of these children have signiﬁcant problems with language at the level of text and discourse that involves an inability to use and understand language in a ﬂexible and adaptive manner (Barnes & Dennis, 1992, 1998; Dennis et al., 1994). The discourse deﬁcits also interfere with reading comprehension (Barnes & Dennis, 1998). In terms of academic competencies, math is commonly impaired relative to word recognition skills, and writing problems are common (Barnes et al., 2002; Dennis & Barnes, 2002). Studies involving memory and learning functions show signiﬁcant problems on diVerent indices of short-term memory, especially list learning, in groups with SBM (Scott et al., 1998; Yeates et al., 1995). Some attention and executive regulation skills may also be impaired (Brewer et al., 2001; Fletcher et al., 1996), but as with memory, skills within this domain are not uniformly impaired. Behavioral studies generally show higher rates of adjustment diYculties, but speciﬁc types of adjustment diYculties have not been identiﬁed (Donders et al., 1992; Fletcher et al., 1995; Greenley et al., in press). Domain-speciﬁc group studies have provided information about outcomes in children with SBM, showing a characteristic pattern of strengths and weaknesses. These studies have established that children with SBM are not compromised in all aspects of cognitive development, and that strengths and weaknesses exist within most domains. Domain-speciﬁc group studies, however, are limited in three important aspects (Fletcher et al., 2000). First, they have generally been conducted on school-aged children, so that the origins of cognitive diYculties (in infants and preschoolers) and the long-term outcomes of compromised cognition (in young adults) are not understood. Second,

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discipline-speciﬁc studies have not analyzed the range of cognitive outcomes in the same individuals, so the interrelations among domains are not known. Third, the considerable variability in cognitive proﬁles associated with variations in the neural phenotype, hydrocephalus and its treatment, and environmental factors have not been studied (Fletcher et al., 2000). To understand outcomes in a condition like SBM with multiple determinants from genotype to neural and cognitive phenotypes, a multidisciplinary approach with large samples is required. A modal cognitive phenotype may be described for children with SBM in which some components (e.g., motor deﬁcits) may be fairly uniform. However, individual children with SBM will vary around this phenotype, reﬂecting the multiple factors that inﬂuence their development. To understand how these factors inﬂuence outcomes, the variability underlying the modal phenotype must be addressed. Outcomes vary in SBM, even though this condition has deﬁning and distinct dysmorphologies and modal cognitive characteristics. The primary objectives of our research programs are to continue discipline-speciﬁc research to characterize the modal phenotype, but also to integrate ﬁndings across domains and disciplines in order to elucidate mechanisms underlying this variability. II.

A MULTI-DISCIPLINARY RESEARCH PROGRAM

To accomplish these goals, we initiated genetic, neuroimaging, and cognitive studies of several samples of infants, school-aged children, and adults with SBM through our program project. Any willing participant with SBM and his/her parents were asked to provide a blood sample for genetic analysis. The school-aged children received magnetic resonance imaging (MRI) of the brain, which was coded for qualitative components of the neural phenotype and analyzed quantitatively for regional variations in brain tissue composition. A separate longitudinal study of infants with SBM was initiated, along with pilot studies of adults with SBM. Medical records were reviewed and coded for all participants. To enhance ethnic and geographic diversity, the studies took place in two geographically disparate sites: Houston, Texas, and Toronto, Ontario. In the following Sections, we will describe the samples to date and some overall ﬁndings, then turn to the ﬁrst set of results of the discipline-speciﬁc studies involving genetics, and ﬁnally to a series of cognitive neuroscience and developmental studies. A.

Samples

There were four primary samples for this research program: 1) a genetic study sample, 2) a sample of infants followed longitudinally, 3) a school-age sample, and 4) a subset of the school-age children who participated in more

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speciﬁc cognitive studies involving cerebellum and corpus callosum functions, and math, reading, and discourse outcomes. In addition to MRI, school-aged children were administered a set of core measures of intelligence, cognitive and academic functions, adaptive behavior, and behavioral adjustment. The infants were identiﬁed at the time of birth and to date have been followed to 36 months of age. There was also a ﬁfth pilot sample of adults in Toronto. The genetics study collected blood samples from probands with SBM of any age from the Houston and Toronto sites as well as from sites in Lexington and Los Angeles. There are over 320 Hispanic probands and 260 Caucasian probands. An additional 102 Hispanic controls were recruited (54 females, 48 males). Total blood samples exceed 1800. For the infant development study, 165 infants were recruited, including 91 with SBM and 74 normal controls. The school age sample (n ¼ 457) included 298 children with SBM, 40 with aqueductal stenosis, 29 with Dandy-Walker syndrome, and 64 normal controls, along with 26 children initially thought to have SBM, but who later proved to have other etiologies of spina biﬁda (meningocele, lipoma). From this sample, approximately 130 children with SBM, 25 with aqueductal stenosis, 15 with Dandy-Walker Syndrome, and 40 controls participated in one or more of three cognitive neuroscience studies involving the cerebellum, corpus callosum, and math, reading, and discourse functions. The samples for these three studies varied slightly depending on selection criteria speciﬁc for each study. These restrictions precluded many from the larger sample from participation due to mental retardation, because of diYculties understanding directions, uncorrected sensory disorders, and other factors. In the genetic, school age, and infant samples, there were few exclusions because the goal was to recruit broadly representative samples. B.

Recruitment

Children and families for all but the infant study were recruited from three primary sites, with additional sites available if needed. Two sites were in Houston, the Spina Biﬁda Clinic at Texas Children’s Hospital, and the Shriners Hospital for Children–Houston. Both provide long-term medical care for most children with spina biﬁda in the area. In Toronto, participants were recruited from The Hospital for Sick Children. To recruit from these sites, research nurses in Houston and Toronto attended the clinics, working with primary care personnel to explain the studies to families and obtain permission for blood samples and other parts of the study. As not all individuals with spina biﬁda attend these clinics, additional potential participants were identiﬁed from the patient registries maintained by pediatric neurosurgeons at these hospitals. Many patients in Toronto live in outlying areas and came to The Hospital for Sick Children for initial neurosurgical care,

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but receive long-term care closer to home. Therefore, we expanded recruitment eVorts to clinics outside of Toronto. Finally, we worked closely with local parent groups for children with spina biﬁda, from whom participants were also recruited. Although the sample is not epidemiological, it is geographically, ethnically, and economically diverse. Recruitment of infants was based on ascertainment of new births in Houston and Toronto. The physicians who are responsible for neurosurgical and follow up care at the clinics are also responsible for new births. When a new birth occurred, the research nurses were introduced to the families and explained the study. The infants were seen initially at 6 months of age. In all studies, there were beneﬁts to participation, including the MRI scan and the assessments. Reports were written for schools and infant programs. Parents received consultation about the child’s development and assistance with procuring services. These beneﬁts were critical for ensuring support of the families and of the primary care personnel. In the remainder of the chapter, we will summarize pertinent research ﬁndings from our research program on SBM, beginning with the ﬁndings from the genetics study. C.

Genetic Factors in SBM

1. HERITABILITY OF NEURAL TUBE DEFECTS

It is diYcult to discuss the heritability of SBM independently of other neural tube defects. The rates of these defects vary across ethnic groups around the world. The risk of the occurrence of neural tube defects in oVspring is higher, not only for parents with a previous aVected pregnancy, but also in their ﬁrst- and second-degree relatives. Genetic alterations in folate metabolism are associated with an increased risk for neural tube defects, especially in animal models. Other genetic syndromes and chromosomal abnormalities are associated with neural tube defects. Environmental factors are also critical (Kirkpatrick & Northrup, 2003; Northrup & Volcik, 2000). 2. VARIATIONS IN GEOGRAPHIC SITES AND ETHNIC GROUPS

Around the world, the prevalence of neural tube defects ranges from approximately 1 to 10 per 1000 births (Botto et al., 1999). The prevalence is higher in Mexico, Northern China, and South America, and lower in the northern European and Southeast Asian countries (Botto et al., 1999). Hispanics and Caucasians are generally at higher risk than blacks and Asians. The ethnic variations clearly reﬂect in part the impact of environmental factors. For example, the rates appear higher in families in Mexico than in second and third generation immigrants who move to the U.S. and in Caucasians who move from Northern Europe to Canada (Kirkpatrick

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& Northrup, 2003). However, these relations reﬂect a complex interplay of genetic and environmental factors. 3. FAMILY RECURRENCE

Within families, risk of recurrence rises with increases in the number of aVected family members, roughly doubling with the birth of each additional aVected child. For children with an aVected sibling, the risk is 2% to 5%, about 25 to 50 times the risk of the general population. Because strict Mendelian autosomal recessive inheritance would predict a sibling risk of 25%, a simple autosomal recessive mode of inheritance with complete penetrance is unlikely. For third-degree relatives, the risk is approximately equal to that of the general population (Elwood et al., 1992). Parent-child pairs in which both are aVected are rare, with most aVected relative pairs either ﬁrst- or second-degree relatives. 4. FOLATE METABOLISM

Women with a child aVected with a neural tube defect have elevated blood homocysteine levels that have been related to problems with the metabolism of folic acid. Genes related to folate metabolism have been studied, including 5,10-methylene-tetrahydrofolate reductase (MTHFR). Initial studies concluded that a speciﬁc mutation (C677T), in either homozygous or heterozygous form, resulted in increased enzyme sensitivity to temperature, with homozygous mutants showing elevated plasma homocysteine and decreased plasma folate levels (Rozen, 1997). Another speciﬁc mutation (A1298C) in the same gene resulted in decreased activity of MTHFR (Rozen, 1997). The frequency of the C677T mutation in certain ethnic groups roughly corresponds to the incidence of neural tube defects: common among Hispanics, less frequent among whites, and rare in blacks (Botto & Yang, 2000). The Relation with ethnicity are not exact as the mutation is common in certain populations in which neural tube defects occur less frequently. This MTHFR variant could interact with other mutations in the folate metabolic pathway, producing a range of occurrence rates. 5. OTHER GENETIC SYNDROMES

Many known genetic syndromes co-occur with neural tube defects, including Meckel-Gruber syndrome, autosomal dominant Waardenburg syndrome types I and II, acrocallosal syndrome, cerebro-costmandibular syndrome, congenital hemidysplasia with ichthyosiform and limb defects (CHILD) syndrome, Fraser syndrome, Jarcho-Levin syndrome, and trisomies 13 and 18 (Melvin et al., 2000). In addition, chromosome abnormalities have been identiﬁed in neural tube defects at a rate of 5% to 17% (Melvin et al., 2000). These data are limited by ascertainment factors. It is too expensive to obtain cytogenetic assays on every stillborn birth.

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Environmental Factors

A broad range of environmental factors has been studied, including demographic variables (ethnicity, socioeconomic status, and parental age), maternal diet and multivitamin use, maternal obesity and diabetes, maternal hyperthermia and illness, and maternal drug and medication usage. Despite this research, the role of environmental factors is poorly understood, with many conﬂicting research ﬁndings that partly reﬂect relatively small samples. 1. DEMOGRAPHIC VARIABLES

Studies of paternal and maternal age have not yielded consistent results. Whereas ethnic diVerences are well documented (Northrup & Volcik, 2000), no deﬁnitive conclusions emerge when socioeconomic status is examined, or even when parental education and occupation are separately analyzed. Thus, while one research group reports that parental age or socioeconomic status is associated with a particular neural tube defect (Brender & Suarez, 1990; Farley et al., 2002), another group of researchers reports a lack of association with the same defect (Strassburg & Greenland, 1983; Vrijheid et al., 2000). Small samples contribute to this pattern of ﬁndings. 2. METABOLIC FACTORS

The impact of dietary factors typically invokes metabolic pathways involving folate or glucose, hence, the associations with insuYcient intake of folate and vitamin B or with maternal obesity and diabetes. The most signiﬁcant ﬁnding involves folic acid deﬁciency, especially the ﬁnding that folate supplementation through the intake of multivitamins signiﬁcantly reduces neural tube defect risk (Northrup & Volcik, 2000). The Centers for Disease Control and Prevention recently reported that the incidence of neural tube defects has decreased by roughly 20% for spina biﬁda and anencephaly since food fortiﬁcation began in the U.S. (Honein et al., 2001). Folic acid seems important as a cofactor for enzymes in deoxyribonucleic acid (DNA) and ribonucleic acid synthesis and in the supply of methyl groups in the methylation cycle. A diet with low or absent folate could cause premature apoptosis (programmed cell death) due to inhibition of DNA synthesis. In addition, inadequate amounts of folate could lead to methionine shortage, preventing cells from methylating proteins, lipids, and myelin. However, although folic acid is important in preventing neural tube defects, it does not prevent every single occurrence. The mechanism whereby folate exerts a preventative eVect on neural tube defects is not established. Women who are diabetic or obese are more likely to have a child with a neural tube defect, thus implicating glucose pathways. Women who were obese before conception have an increased risk for an aVected pregnancy

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independent of folate intake and familial history of neural tube defects (Northrup & Volcik, 2000). The risk for a neural tube defect in the oVspring of maternal diabetics is 2 to 3 times greater than the normal population (Northrup & Volcik, 2000). The underlying mechanisms are not well-established. The predominant hypothesis involves alterations of glucose metabolism due to genetic mutations in the responsible metabolic pathway, which parallels hypotheses of the role of genetic aberrations in folic acid metabolism in causing neural tube defects. A major diVerence is that folic acid supplementation reduces the risk of neural tube defects. 3. MATERNAL ILLNESS AND MATERNAL MEDICATION USE

Maternal illness and hyperthermia early in fetal development have been associated with increased occurrence of neural tube defects (Botto et al., 1999). Hot baths, saunas, electric blankets, and fevers from the ﬂu in the ﬁrst month after conception somehow interfere with the process of neurulation. Use of some anticonvulsants by pregnant women with epilepsy is associated with an increased risk of neural tube defects, speciﬁcally SBM (Northrup & Volcik, 2000). Again, the mechanisms are not well understood. E.

Our Approach to Genetic Factors and Some Initial Results

As this review makes clear, neural tube defects are multifactorial, and heritable factors occur in the context of complicated gene/environment interactions. Closure of the neural tube is an intricate process requiring many diVerent genes, suggesting genetic heterogeneity in a complex disorder. The mode of inheritance is not clear and few families have more than one aVected person. By the way of overview, our studies follow standard genetic methods. We attempt to obtain DNA (blood) samples from children with SBM and their families. We then proceed to search for genes related to SBM in two ways. First, we apply statistical models to the DNA collected from the children and their parents. These models are used to detect genetic markers that occur with greater frequency in children with SBM and their families than in controls, thus indicating a possible role in SBM. Second, candidate genes are identiﬁed based on hypotheses about the causes of SBM. Thus, for example, knowledge about genes involved in folate metabolism would be used to identify potential genetic markers. Other potential genes might be identiﬁed from animal models involving neuroembryogenesis and the development of the central nervous system. In both approaches, genetic heterogeneity would be evaluated by examining relations with clinical

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markers that vary in children with SBM, such as lesion level and ethnicity. Thus, the goals of our studies have been to accrue a large, heterogeneous sample of families with SBM to: evaluate genetic factors in the etiology of SBM determine sources of genetic variability related to clinical markers, such as the lesion level, ethnicity, and other sociodemographic factors conduct candidate gene searches based on various models of neural tube defects. 1. STATISTICAL METHODS

For disorders such as SBM, it is necessary to use methods that do not require families with multiple aVected individuals. Many epidemiological studies of complex disorders, especially birth defects, employ case-control methodology. The diYculties with this study design involve the deﬁnition of appropriate controls. To avoid the pitfalls of the usual case-control study, statistical methods, such as the Transmission Disequilibrium Test (TDT), have been developed. The TDT was developed to allow a joint test for linkage and disequilibrium in candidate genes, using aVected individuals and their non-aVected parents as the primary source of data (parent-child trios) (Spielman & Ewens, 1996). Morrison et al. (1996) successfully used the TDT to detect linkage disequilibrium between neural tube defects and the human homologue (T) of the mouse T (Brachyury) gene. In addition to the extension to multiple loci, the TDT has also been modiﬁed to incorporate data from multiplex families. It is likely that interaction among several genes plays a signiﬁcant role in the development of SBM. Several studies have consistently implicated altered folate metabolism as a risk factor. There may be an interaction involving several of the genes in the folate pathway that yields an increased susceptibility to SBM. One of the quandaries in the statistical analysis of gene-gene interactions is that small samples produce many empty cells in contingency tables. Combining typical TDT analyses with methods that allow for epistasis, the situation in which an allele of one gene can block the expression of all alleles of another gene, should increase the likelihood of successfully identifying the genes underlying SBM. 2. ETHNICITY

These methods necessitate large samples, which we have assembled. To increase the sample size, we have recruited children at any age from across the country, concentrating on clinics where large numbers of children with SBM receive clinical care. We have focused on Hispanics because they represent the ethnic group in the U.S. most likely to have a child aVected

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with neural tube defect and are the fastest growing segment of the U.S. population (Green, 2002). 3. LESION LEVEL

In addition to ethnicity, lesion level is another clinical marker that may be especially important in accounting for the genetic heterogeneity of SBM. How the malformations of the neural tube occur during embryogenesis has been a source of heated debate, mostly involving the spine. For many years it was generally accepted that the neural tube closed by ‘‘zipping’’ up, starting in the cervical region and proceeding rostrally and caudally (Fig. 2). The one exception to the complete closure following this pattern was the caudal end in the region of the future sacrum, so that the sacral region was hypothesized to close by a diVerent mechanism (canalization) that involved a hollowing out of structures after formation. van Allen et al. (1993) challenged this theory, hypothesizing that the neural tube had sites of closure starting at multiple points rather than the single initiation point in the cervical region. They based their new theory, the ‘‘multisite closure model,’’ on mouse embryology, as the mouse has four well-recognized separate closure initiation sites, and on human fetuses displaying more than one neural tube defect. Along the back, van Allen et al. (1993) stated there were two initiation

FIG. 2. Zipper versus multi-site models of neural tube closure.

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points, one in the previously recognized site near the juncture of the rhombencephalon and the cervical spinal cord (closure site 1) and another lower site (closure site 5) with a proposed meeting point at L1–L2. Whether there are multiple closure sites in the head remains hotly debated (Nakatsu et al., 2000; O’Rahilly & Muller, 2002); however, there is now a general consensus based on studies of human embryos that the original site in the cervical region is correct and that canalization is responsible for the area of the lower sacrum (Nakatsu et al., 2000). For our studies, the multi-site closure theory was important in yielding a theoretically motivated subdivision of the spinal cord to guide explorations of genetic heterogeneity. The spine is divided into thoracic, lumbar, and sacral regions and each vertebra is numbered within the region. We initially followed van Allen et al. (1993) and divided the lesion level at L1/L2. We subsequently decided to change our subdivision to T12/L1, reasoning that vertebrae with ribs (T1/T12) are likely to require diVerent genetic programming than vertebrae without ribs (L1 to sacrum). In working with others in the research program, we found that this subdivision seemed more robust, so it was adopted throughout diVerent parts of the research program. 4. GENES INVOLVED IN FOLATE METABOLISM

Folate metabolism has been intensively studied because of the compelling evidence that a pregnant woman’s folate status is a risk factor for neural tube defects. We were one of the ﬁrst groups to propose that the maternal environment as indicated by the mother’s genotype for folate status was important in the susceptibility for SBM. First, when comparing frequencies of the C677T homozygous mutant genotype in the overall Hispanic SBM study population to their respective Hispanic controls, Hispanic patients and their mothers were homozygous for the C677T variant at a signiﬁcantly higher rate. Second, signiﬁcant ﬁndings were observed only when the SBM population was analyzed according to level of spinal defect (T12 and above ¼ upper; L1 and below ¼ lower). Hispanic mothers of patients with upper level spinal defects showed the homozygous mutant genotype for C677T variant at a statistically signiﬁcant higher rate than controls. In addition, Hispanic mothers of patients with upper level defects have the highest frequency of the C677T variant observed in any SBM population reported to date. On the basis of our data, we estimate the fraction of upper level SBM defects due to maternal homozygous C677T genotype in Hispanics to be 22% (Volcik et al., 2000). One explanation for our ﬁnding that folate status is more important for upper than lower level defects is that upper level defects are a result of failure to close in sites where growth is required to produce neural folds large enough to elevate, overarch, oppose, and fuse (Seller, 1995). During critical

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stages of organogenesis, cell growth is primarily established by cell division and any severe deﬁciencies of essential nutrients, such as folate, can result in fetal death or malformations (Mooij et al., 1993). Thus, a lack of available folate, could lead to a reduction in proﬁcient cell division and growth needed for competent neural tube closure. The area of folate metabolism and its relationship to neural tube defect susceptibility has continued to be fraught with controversy. One group (Isotalo et al., 2000) postulated that a combination of three or four mutant alleles (677CT/1298CC and 677TT/1298CC) decreased in utero viability. They studied DNA extracted from neonatal cord blood and fetal tissue for the polymorphic variants. While all combinations were observed in the fetal group, the combinations with three or four mutant alleles were not observed in the neonatal group, leading them to this conclusion. Our hypothesis is that there is a threshold eVect of variants in the MTHFR gene that leads to susceptibility for neural tube defect formation (Volcik et al., 2001). We had studied the polymorphic variants in our aVected populations (Hispanic individuals of Mexican descent, U.S. and Canadian individuals of European descent), their parents, and control subjects. We observed combinations of three mutant alleles in the expected frequencies (including patients, healthy parents, and normal controls), but not combinations with all four of the mutant genotypes. 5. GENES DETERMINED IN MICE AND RATS TO CAUSE NEURAL TUBE DEFECTS

In addition to folate metabolism, other hypotheses about genes involved in SBM can be derived from animal models. There are over 100 known mouse models with a neural tube defect phenotype (JuriloV & Harris, 2000); 21 display SBM as part of the phenotype, with 14 of these showing SBM in combination with exencephaly and only 2 appear to represent a true model for non-syndromic SBM. We have tested markers relating to nine mouse models (Volcik et al., 2002a,b). Of the nine mouse models, seven have a phenotype speciﬁcally relating to SBM, rather than anencephaly. Unfortunately, only three of our nine mouse models had a known causative gene. The three mouse models with known causative genes were all genes that we had included as candidate genes in other categories (splotch mouse-Pax3 gene; undulated mouse-Pax1; patch mouse-a deletion of one copy of the growth factor receptor gene pdgfra in combination with a mutation in an additional locus). While neither undulated nor patch mice alone exhibit SBM, double-mutant mice with both copies of the Pax1 gene mutated and only one copy of pdgfra present had SBM. From our studies of mouse models, only Pax1 yielded a positive result (Volcik et al., 2002a,b).

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6. HOX AND PAX GENES

The HOX and PAX genes were selected as candidate genes based on their function in embryological development. The HOX genes are a family of genes in four complexes (HOX A, B, C, and D). Members of all four HOX clusters are implicated in neural tube closure. We screened for the HOX genes by testing one or two markers from within each cluster (Volcik et al., 2002a). All of our results for the HOX genes were negative (Volcik et al., 2002a). We have not adequately screened for all possible candidate genes within the four HOX clusters, so further research is needed. The PAX genes also play a role in embryonic development. Six of the nine PAX genes that have been discovered are expressed during the formation and/or organization of the neural tube along its entire axis (Tremblay & Gruss, 1994). Analysis of mouse models and human syndromes has revealed that PAX genes serve a role as regulators of normal development (Mansouri et al., 1999). Mutations in the murine Pax1 gene are responsible for the undulated phenotype that exhibits various vertebral abnormalities. Further, when undulated and Patch mutant mice are crossed, a high incidence of mice with lumbar level SBM are observed, indicating that Pax1 may be involved in speciﬁc types of human neural tube defects (Balling et al., 1988; Helwig et al., 1995; Hol et al., 1996). Mutations within the murine Pax3 gene result in the splotch mouse mutant with homozygotes dying during gestation with spina biﬁda and/or exencephaly (Auerbach, 1954; Vogan et al., 1993). We tested seven of the nine PAX genes, six because of their expression in neural tube development (PAX 2, 3, 5, 6, 7, and 8) and Pax1 because it is causative in the undulated/Patch double mutant mice as well as other studies implicating involvement in human neural tube defects (Balling et al., 1988; Helwig et al., 1995; Hol et al., 1996; Tremblay & Gruss, 1994). We found signiﬁcant evidence for linkage disequilibrium with SBM for the following markers: D20S101 ﬂanking the Pax1 gene, D1S228 within the Pax7 gene, and D2S110 within the Pax8 gene (Volcik & Northrup, 2002b). These results were obtained after overall analysis of our entire subject population. Analysis was also performed according to ethnic group (Hispanic versus Caucasians) and level of spinal defect (upper versus lower level), with either non-signiﬁcant results or less robust results than obtained from the overall analysis. We then tested the genes directly for mutations, detecting novel variations in Pax1, Pax7, and Pax8, which in turn suggests that these variations contribute to disease susceptibility (Volcik & Northrup, 2002b). However, other analyses showed that the variations were not passed from parent to aVected child along with the positively transmitted alleles. Therefore, the variations we detected are not disease-causing.

80 F.

Jack M. Fletcher et al. Conclusions: Genetic Factors

It is clear that neural tube defects have heritable factors. A major goal of our research program is to link the genetic ﬁndings with studies of the neural and behavioral phenotypes. The present sample size is not adequate as the sample with MRI and behavioral data is much smaller than the overall sample for genetic studies. But as we will see in the next section, markers that help explain genetic variation also seem to explain variations in the neural and behavioral phenotypes, highlighting the value of interdisciplinary studies, which help with the task of linking gene, brain, and behavior for individuals with SBM. III.

OVERALL OUTCOMES IN SCHOOL-AGE CHILDREN

In the genetic studies, lesion level and ethnicity helped account for the genetic heterogeneity of SBM. We evaluated data from our core school-age sample to determine whether clinical markers, such as ethnicity and lesion level, account for neurobehavioral variability. The goals have been to: characterize the sample of children with SBM as a whole; evaluate major disorders of development (mental retardation, learning disabilities, and attention deﬁcit/hyperactivity disorder [ADHD]) and more general cognitive outcomes; relate these outcomes to clinical markers involving ethnicity and lesion level in an attempt to explain variability in outcomes. A.

Sample

The school-age sample of 298 children with SBM averages about 11 years of age and is almost evenly divided by gender (150 females, 148 males). It is 7% African-American, 3% Asian, 31% Hispanic, 58% Caucasian, and 2% other. For socio-economic status (SES), 51% are below the midpoint of the Hollingshead scales (M ¼ 37), a composite of parental education and income (Hollingshead, 1975). In terms of the language of evaluation, 92% of the children were tested in English and 8% in Spanish. Most (n ¼ 277) were shunted, with 6% (n ¼ 17) showing arrested hydrocephalus that was not deemed of suYcient severity for shunting, and 2% (n ¼ 4) with no evidence of hydrocephalus. As there are few with SBM who were not shunted, we restrict this discussion to those with shunted hydrocephalus. There are several clinical markers associated with SBM. For lesion level, 69% of the sample has spinal defects below T12, while 31% has defects above L1. As expected, most of the group (92%) has the Arnold Chiari II

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malformation, with 2% having Arnold Chiari I malformations, 3% having a normal cerebellum, and 3% not classiﬁed with a Chiari malformation, but having other cerebellar abnormalities (e.g., low lying tonsils). Over one-half (52%) of the children are missing one or more corpus callosum structures, with 44% showing only hypoplasia (thinning) and only 4% with a normal corpus callosum. In terms of clinical markers related to hydrocephalus and the spinal dysraphism, few children had experienced more than 10 shunt revisions (3%), reﬂecting continued improvements in shunt technology. Most children have experienced two to four revisions (33%), with relatively few with ﬁve to nine revisions (8%). Almost one-quarter of the sample (24%) had never experienced a shunt revision. Ambulatory status and neurogenic bladder categories show the expected patterns, with 50% of those with SBM nonambulatory and 96% having a neurogenic bladder. Less than 1% had normal ambulation; 19% could walk independently with no support and 30% required a walker or other means of support. The overall rate of seizures is higher than the population rate, with 10% actively treated with anticonvulsants and 15% with a history of seizures but not presently treated with anti-convulsants. Four individuals have poorly controlled seizures, all with severe mental retardation. B.

Major Developmental Disorders Of Cognition, Behavior, and Learning

Although this sample is not epidemiologically derived, it was suYciently large enough to allow for the examination of the incidence of intellectual, behavioral, and achievement patterns that may be associated with common developmental disorders. To date, it has been unclear how frequently children with SBM experience mental retardation and common problems, such as learning disabilities and ADHD, especially in relation to ethnicity and lesion level (Fletcher et al., 2003). Mental retardation was deﬁned using the composite score from the Stanford-Binet Intelligence Tests-IV (Thorndike et al., 1986) and the Scales of Independent Behavior-Revised (SIB-R) (Bruinicks et al., 1984). There is controversy over deﬁnitions of mental retardation, such as the weighting of IQ and adaptive behavior quotients and where to place the cut point on both. Since we are not making clinical judgments, we deﬁned mental retardation as those participants who had a Stanford-Binet-IV composite IQ and SIB-Revised composite scores two standard deviations below the mean of 100 (i.e., <70). For the Stanford-Binet-IV, we explored diVerent patterns, such as requiring that all four administered subtests be <70, but the particular rules made little diVerence to the classiﬁcation. For the SIB-R, we excluded the motor domain and recalculated the composite score because

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inclusion of the motor scale provided extremely low scores for many nonambulatory children who had stronger development in other areas. Applying these criteria revealed that 21% of the group with SBM met research criteria for mental retardation, a rate that is generally much higher than expected from the literature, highlighting the variability in cognitive outcomes. This rate was highest for children of Hispanic origin with thoracic level lesions—about 59% (20 of 34) of this subgroup (Fletcher et al., 2003). Interestingly, the means for the Stanford-Binet and SIB-R composites do not vary signiﬁcantly in the four ethnicity (Hispanic, non-Hispanic) and lesion level (upper, lower) subgroups, with an IQ range of 52 to 59 (standard deviation range of 7 to 12) and an adaptive behavior range of 33 to 47 (standard deviation range 17 to 25). Children with SBM were divided into putative ADHD subtypes using statistical cutoV scores based on estimates of population parameters for the average response per item for the parent-based Inattention and Hyperactivity/Impulsivity Scales of the Swanson Nolan Achenbach Pelham-IV (SNAPIV) scales (Swanson, 1992). CutoV scores were equivalent to the population mean þ 1.65 standard deviations, which have been proposed to identify 5% of the population (Swanson, 1992). Children in the combined group had scores on the Hyperactivity/Impulsivity Scale 1.44 and Inattention Scale scores 1.78. The hyperactive-impulsive type was deﬁned with a score on the Hyperactivity/Impulsivity Scale 1.44 and Inattention Scale score <1.78. Children with scores 1.78 on the Inattention Scale but <1.44 on the Hyperactivity/Impulsivity Scale were classiﬁed as the predominantly inattentive type. Although we recognize that criteria based solely on rating scales are not adequate for clinical diagnoses, we propose the resultant subgroups as a useful heuristic to identify the rate of attention problems in SBM. About 27% of the children who met criteria for mental retardation also met criteria for attention problems. Most were in the group who met criteria for inattention (14%), but not hyperactivity-impulsivity, with 6% in the hyperactive-impulsive group, and 8% in the combined group. For those not classiﬁed as having mental retardation (also see Burmeister et al., in press), 34% showed elevated parent ratings on the SNAP-IV, the largest group (26%) representing children who met criteria for the predominantly inattentive group. There were 2% in the hyperactive-impulsive group and 6% in the combined group. In the latter group, elevations typically reﬂected excessive or disorganized verbal behavior that may reﬂect their diYculties with contextual language as opposed to true hyperactivity-impulsivity. These ﬁndings may reﬂect the diYculties with altertness and arousal commonly seen in children with SBM. Achievement diYculties were deﬁned using low achievement cut points, which have shown to be reliable markers for learning disabilities in children

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without general mental retardation (Stuebing et al., 2002). What is important here is not only the incidence, but also the patterns in reading and math. Fletcher et al. (2003) used a cut-oV point at the 25th percentile to deﬁne diYculties in reading (Woodcock-Johnson Psycho-Educational Test Battery-Revised (WJR) Word Identiﬁcation) and math (WJR Calculation). In our sample, 55% met criteria for reading and/or math diYculties. Speciﬁc problems involving word recognition occurred in only 3%. Reading comprehension deﬁcits are more common in children with SBM who have average word recognition skills, as discussed in the following text in a separate section on math and reading in school-aged children with SBM. Speciﬁc math problems were much more frequent (27%) than speciﬁc word recognition problems. When overlap was examined, 26% of the children performed below the 25th percentile in both reading and math. Altogether, over 50% of children with SBM had math diYculties. The overlap of achievement and attention problems was about 35% across all achievement subgroups, so the presence of ADHD does not explain the high number with math diYculties. The incidence of math diYculties in children with SBM highlights the need for further investigation of this domain. C.

Relationships with Clinical Markers

Altogether, 22% of the sample showed no evidence for problems with intellectual functions, attention, or academic skills using the preceding criteria. The average composite on the Stanford-Binet-IV was 80, with a verbal reasoning average of 86 and visual reasoning average score of 85. On the WJR, averages were obtained from 91 in word identiﬁcation, 88 in passage comprehension, 77 in calculations, and 80 in quantitative concepts, showing the stronger development of reading than math skills. The composite score on the SIB-R of 55 children illustrate the pervasive impairments in adaptive behavior in the group with SBM. However, average scores were much higher in social communication (87) than in motor (50), personal living (53), and community living (67) domains, reﬂecting the modal behavioral phenotype of stronger social than daily living skills. These data have been presented combining across sites in Houston and Toronto, which have diVerent sociodemographic characteristics. In Houston, the groups are ethnically diverse, with a large Hispanic contingent. In Toronto, the cohort is predominantly Caucasian and higher in socioeconomic status. We thought that these diVerences would be seen as a higher rate of participants meeting mental retardation criteria in the Houston Hispanic cohort, reﬂecting the eVects of economic disadvantage and linguistic diversity. In Toronto, the overall rate of mental retardation across ethnicities is 9%, representing 10% of their Caucasian cohort. In Houston,

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the overall rate is 19%, but varies by ethnicity: 12% Caucasian and 27% Hispanic. It should be noted that the criteria are also based on parent reports of adaptive behavior from interviews conducted in Spanish. There is no signiﬁcant diVerence in the socioeconomic levels of Caucasians in Houston (M ¼ 42) and Toronto (M ¼ 40). Examining data separately by sites shows that on virtually all cognitive variables, the overall Toronto cohort is consistently higher performing than the Houston cohort. In addition, as Table I shows, whereas the expected higher scores on verbal IQ relative to non-verbal IQ scores were apparent in the Toronto cohort (94 verbal; 88 visual), it was not apparent in the Houston cohort (81 verbal; 86 visual). But this is actually due to the inclusion of the Hispanics in Houston, showing that the cognitive phenotype is diVerent by ethnicity (Fletcher et al., 2003). The Houston Caucasian cohort also has higher Verbal (90) than Visual (86) scores. Table I shows that scores of TABLE I STANFORD-BINET INTELLIGENCE TEST-IV VERBAL REASONING AND VISUAL/ABSTRACT REASONING SCORES BY SITE, ETHNICITY, AND LESION LEVEL FOR CHILDREN WITH SPINA BIFIDA MENINGOMYELOCELE AND HYDROCEPHALUS Verbal reasoning

Visual/Abstract reasoning

N

M

SD

M

SD

146 90

81 94

21 15

86 88

17 19

153 83

92 74

16 21

87 84

19 16

Lesion level score (Caucasian and Hispanic) L1/Below 162 89 T12/Above 74 79

19 20

88 81

18 16

Lesion level ethnicity (Caucasian) L1/Below 110 T12/Above 43

94 88

17 13

88 85

19 17

(Hispanic) L1/Below T12/Above

79 67

18 22

89 75

15 13

Site (Caucasian and Hispanic) Houston Toronto Ethnicity Caucasian Hispanic

52 31

M ¼ mean; SD ¼ standard deviation.

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Caucasians across sites are higher on the verbal scale, but not the visual scale, and show a diVerent pattern than those of Hispanics. These diVerences reﬂect more than the greater economic disadvantage of the Houston Hispanic cohort, which has an average Hollingshead score of 26. To illustrate, consider Stanford-Binet verbal and visual reasoning scores by ethnicity and lesion level. There is no site diVerence in the proportion of upper and lower lesions in Caucasians. But the patterns in the Houston Hispanic cohort are diVerent, with proportionally more Hispanics than Caucasians with upper level lesions. Obviously sociolinguistic diversity contributes to these diVerences. But lesion level—as in the genetic studies in the following text—also accounts for variability in cognitive outcomes, using IQ just as a marker for these variations. Collapsing across ethnicity, Table I shows that children with SBM and lower level lesions have higher verbal (89) and visual (88) scores than those with (upper) level lesions, verbal (79), visual (81). But hidden in these comparisons are complex interactions of ethnicity, lesion level, and type of test. Averaging across scores, Hispanics with upper level lesions are proportionally the poorest performers (verbal, 67; visual, 75). Caucasians with lower level lesions, who predominate in older outcome studies, show the characteristic higher verbal (94) than non-verbal (88) IQ scores, but this is not observed in other ethnicity/lesion level subgroups, including Caucasians with upper level lesions (verbal, 88; visual, 85) and Hispanics with lower level lesions (verbal, 79; visual, 89). The interpretation of these ﬁndings is enhanced by the genetic studies, where both ethnicity and lesion level are phenotypic variables that account for variability in the genetic expression of SBM. Indeed, these comparisons were motivated by ﬁndings from genetic studies and show that these clinical markers account for genetic variability. These ﬁndings take on more signiﬁcance when it is recognized that the distribution of upper and lower lesions varies with ethnicity in the group with SBM, with lesions above L1 more characteristic of the Hispanic neural phenotype (Caucasian: 28% upper; Hispanics: 41% upper; African-American: 17% upper; Asian/Other: 27% upper). Moreover, those with SBM who have upper level lesions are about twice as likely to be missing the end structure of the corpus callosum (dysgenesis of the splenium: 47%) than those with lower lesions (26%). In contrast, those with lower level lesions are much more likely to have thinning of the corpus callosum (64%) versus those with lower level lesions (47%). The multidisciplinary, multi-institutional data help clarify the elusive relation of spinal lesion level to cognitive outcome. While relationships of lesion level and outcome have been described in the past, they have not been consistently replicated across centers (Fletcher et al., 2003; Wills, 1993). Moreover, they have not been based on a theoretically motivated model of

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lesion level, which was derived from the genetic studies. These clinical markers are also important for studies in the next section, which will examine the role of the corpus callosum and cerebellum.

IV.

NEURAL PHENOTYPE OF SBM: RELATIONSHIPS WITH COGNITIVE AND MOTOR FUNCTIONS

This section will focus on major dysmorphologies of the SBM brain: the cerebellum, midbrain, and corpus callosum. These are the most common forms of congenital dysmorphology associated with SBM, and represent major developmental brain dysmorphologies. Figure 3 illustrates some of the major features of this dysmorphology. In the left panel, the midsagital slice from a child with SBM is shown, illustrating severe dysgenesis of the corpus callosum (upper arrow), and a severe Arnold Chiari II malformation (lower arrow). The center panel shows a child with SBM, predominant hypoplasia (thinning) of the corpus callosum, with some dysgenesis of the splenium, a mild Arnold Chiari II malformation, and no tectal beaking (upper arrow). The right panel shows a child with SBM who is missing the rostrum of the corpus callosum, the end structure (splenium), a severe Arnold Chiari II malformation, and tectal beaking (upper arrow). These examples illustrate the heterogeneity of SBM at the level of the brain. In each section, we will review the pattern of dysmorphologies associated with SBM, separately by lesion level, and then we will describe the studies of cognitive and motor functions related to these brain regions. The goals of this component of the research program are to: characterize the brain anomalies associated with SBM, evaluate core functions mediated by the cerebellum, midbrain, and posterior cortex, determine relations of cognitive and motor functions with brain anomalies and clinical markers to help explain variations in these outcome domains.

A.

Midbrain and Cerebellum

1. ANOMALIES

Table II summarizes the frequency of abnormalities involving midbrain and cerebellum. It shows that midbrain abnormalities are common in SBM, and are more common in association with upper than lower level spinal

FIG. 3. Mid-sagital slices from MRIs of three children with spina biﬁda meningomyelocele and hydrocephalus. The ﬁrst image shows a child with signiﬁcant dysgenesis involving the posterior part of the corpus callosum (upper arrow). This child also has a severe Arnold Chiari II malformation that is downwardly extending into the brain stem (lower arrow). The second image shows a child with a normal tectum (upper arrow), signiﬁcant thinning of the corpus callosum, mild posterior dysgenesis, and a mild Arnold Chiari II malformation (lower arrow). In the third image, there is tectal beaking (upper arrow), thinning of the corpus callosum with dysgenesis of the rostrum and splenium, and a severe Arnold Chiari II malformation (lower arrow). Note the variation in the size of the cerebellums.

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Jack M. Fletcher et al. TABLE II FREQUENCY OF MRI ABNORMALITIES BY LESION LEVEL (UPPER, T12 ABOVE; LOWER, L1 AND BELOW) MRI variable

Upper level

Lower level

Midbrain Tectum Axial Beaking Sagittal Beaking Posterior fossa

0.65 0.95 0.85 0.75 0.95

0.55 0.78 0.75 0.43 0.88

Small Pons Medulla

0.80 0.95

0.65 0.89

Cerebellum Small Dysplastic Upward herniation Vermis Hemispheres Tonsils Arnold Chiari II

1.0 0.55 0.95 0.70 0.90 1.0 0.65 0.96

0.92 0.42 0.85 0.57 0.82 0.71 0.64 0.90

A frequency of 1.0 indicates that the abnormality is always present. MRI ¼ magnetic resonance imaging.

lesions. The typical tectal dysmorphology involving the upper part of the midbrain involves beaking in both the axial and sagittal planes in upper spinal lesions, but primarily axial beaking in lower lesions. The posterior fossa (ﬂoor of the skull that holds the cerebrum, pons, and medulla), pons, and medulla are abnormal in SBM, and more so in association with upper level spinal lesions. Although posterior fossa dysmorphologies are not unexpected, the pons and medulla abnormalities have not previously been identiﬁed in a large sample. The rate of these anomalies, especially in individuals with upper lesions, is high. As expected, the cerebellum is abnormal in 100% of upper lesions and 92% of lower lesions, with 96% of upper level lesions and 90% of lower level lesions showing the Arnold Chiari II malformation of the hindbrain and cerebellum. Although not unexpected, we found that the cerebellum is more often dysplastic (maldeveloped) than simply small; and when examining speciﬁc cerebellar structures, that while both vermis and hemispheres are abnormal, the vermis (i.e., showing evidence of abnormal growth structure) but not the hemispheres (lateral structures) is displaced. Patterns of cerebellar dysmorphology are similar in upper and lower lesions. Altogether, children with

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upper spinal lesions tend to demonstrate more extensive dysmorphology of the midbrain and tectum, and pons, which may help explain their greater cognitive diYculties. 2. COGNITIVE AND MOTOR FUNCTIONS

The modal proﬁle for children with SBM involves deﬁcits that reﬂect fundamental modes of processing information over a number of cognitive domains. We have attempted to relate these processes to the relevant brain regions, including cerebellum, midbrain, and posterior cerebral cortex. Recent work in this area has concerned:

timing, motor speech, and motor learning (cerebellar functions), covert attention shifting (midbrain function), voluntary attention shifting (posterior parietal function), object (ventral processing) and action (dorsal processing) perception.

3. TIMING

Perceptual timing includes the ability to make judgments for the duration of events, such as the interval between two brief tones. Children with SBM and controls heard a series of pairs of two intervals deﬁned by 50-ms 1000Hz boundary tones at the beginning and end of each interval, and separated by an empty interval of 1000 ms. The target duration was 400 ms, and the foil duration was always longer. They made judgments about which interval was longer, the ﬁrst or the second. They also made judgments on the duration of an interval between two tones that varied around an interval of 400 ms, and judgments of frequency, around 3000 Hz. Children with SBM and controls were equally able to discriminate frequency, but the SBM groups were less able than controls to discriminate duration (Fig. 4A). Motor timing includes the ability to perform isochronous tapping. Children with SBM and controls could both tap along with a computergenerated cue, but the children with SBM, especially those with upper spinal lesions, could not maintain isochronous tapping without an external cue (Dennis et al., 2004). Children with SBM thus have deﬁcits in both perceptual and motor timing that varies with lesion level. They also have problems in complex skills, such as motor speech, that require precise temporal regulation of motor mechanisms. 4. MOTOR LEARNING

The cerebellum contributes to adaptive learning (Grafman et al., 1992; Laforce & Doyon, 2002; Saint-Cyr et al., 1988). We studied adaptive motor learning in children with SBM and typically developing controls, using a

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FIG. 4. Frequency and duration timing for children with spina biﬁda meningomyelocele (upper and lower lesions) and controls (A). Adaptive motor learning in children with spina biﬁda meningomyelocele (upper and lower lesions) and controls (B).

mirror-drawing task that required them to trace the outline of a star visible only in a mirror (Edelstein et al., in press). Although all children learned the task, those with SBM required more time to trace the star, made more errors, and retained less information (Fig. 4B). These diYculties did not vary by lesion level. 5. COVERT AND VOLUNTARY ATTENTION SHIFTING

Dennis et al. (2003) assessed visual attention using a variation of the Posner cued orienting and detection paradigm (Posner et al., 1987). Children were required to press a button when diVerent targets appeared in one of four peripheral boxes, located to the right, left, above or below the central ﬁxation point on a computer screen. We investigated the plane of attention, whether horizontal or vertical, and whether performance with diVerent attention cues was related to diVerent brain anomalies. Exogenous cues (e.g., brightening of a box in the visual periphery) involve covert shifts of attention because the visual marker cues location of the upcoming target (Akhtar & Enns, 1989) and likely involve midbrain processing (Jonides, 1981). Endogenous cues (e.g., a central arrow pointing to a peripheral

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location) prompt a voluntary shift in attention (Jonides, 1981) that tap the posterior parietal attention system (Posner et al., 1987). Children with SBM showed deﬁcits in the orienting of attention in the vertical but not horizontal plane. They were less able to shift attention from the incorrectly cued location to the position where the target appeared. Like typically developing younger children they were slow to detect targets on invalid trials. Children with SBM and upper spinal lesions had particular diYculty with attention control. Children with SBM had diYculty in both covert and overt shifting of attention, and these diYculties were related to features of their anomalous brain development. Speciﬁcally, tectal dysmorphology impaired the exogenous control of attention, whereas reductions in white matter volume impaired the endogenous control of attention (Dennis et al., 2003). 6. OBJECT VERSUS ACTION PERCEPTION

Children with SBM have poor visual perception skills that appear to be related to brain dysmorphologies. For example, children with selective posterior cortical compromise have greater visual perception and non-verbal cognitive impairments than those with more anterior-posterior symmetry (Dennis et al., 1981; Fletcher et al., 1996; Ito et al., 1977). Because they aVect the development of the midbrain and posterior cortex, the brain anomalies of SBM may disrupt action-based visual perception more than object identiﬁcation. We studied visual perception in intellectually normal (IQ over 70) children with SBM (Dennis et al., 2002), using three sets of tasks: 1) objectbased visual perception (e.g., visual constancy illusions, face recognition, recognition of fragmented objects, line orientation); 2) action-based visual perception requiring the representation of visual space in egocentric coordinates (e.g., stereopsis, visual ﬁgure-ground identiﬁcation, perception of multistable ﬁgures, egocentric mental rotation); and 3) action-based visual perception requiring the coupling of visual space to overt movement (e.g., visual pursuit, ﬁgure drawing, visually guided route ﬁnding, visually guided route planning). EVect sizes, measuring the magnitude of the diVerence between children with SBM and controls, were consistently larger for action-based than object-based visual perception tasks. Children with SBM were more impaired on tasks requiring multistable representations of visual space or visually guided action, with better development of visual perception for objects. This pattern of visual perception is consistent with the reported compromise of their posterior cortex. Altogether, these results show that children with SBM have diYculties on several measures mediated by the cerebellum, midbrain, and posterior cortex. These diYculties are associated with variations in brain anomalies and lesion level.

92 B.

Jack M. Fletcher et al. Corpus Callosum and Other Cerebral Commissures

The corpus callosum, the great cerebral commissure that connects the brain’s two hemispheres, is a major white matter tract. It not only connects the commissure with the anterior commissure, hippocampal commissure, and other pathways, it also provides additional means of connectivity between the two hemispheres. Any eVects of diminished connectivity as a result of corpus callosum anomalies are important, because this commissure contributes to the development of cerebral specialization of language and other cognitive skills, as well as facilitating communication across diVerent parts of the brain. A relatively recent observation is that the corpus callosum is missing, at least in part, in a large number of individuals with SBM, and hypoplastic in another signiﬁcant proportion (Barkovich, 1995; Hannay, 2000). The eVects of diminished connectivity are important as the corpus callosum is essential for the development of cerebral specialization of language and other cognitive skills as well as facilitating communication across diVerent parts of the brain. 1. ANOMALIES

Qualitative coding of MRI scans in our large sample of children with SBM revealed that only 4% had a normal corpus callosum, while none had complete agenesis. Practically all of the children had some hypoplasia, while 52% had partial dysgenesis and 44% had hypoplasia and no dysgenesis. Upper level lesions are more commonly associated with dysgenesis of the splenium. Almost every child who had partial dysgenesis also had some hypoplasia (96%). However, simply observing the presence of dysgenesis and hypoplasia is misleading. There are 24 patterns of corpus callosum dysmorphology that involve variations in dysgenesis and hypoplasia of the rostrum, genu, body, and splenium. The most common pattern is a completely hypoplastic corpus callosum (22%). A pattern of absent rostrum and splenium with hypoplastic genu and body occurs in 16% of the children, with an absent rostrum and a hypoplastic genu, body, and splenium occurring in 11% of the cases. Both of these patterns likely represent the eVects of abnormalities in neuroembryogenesis and secondary destructive hydrocephalus as do many of the other patterns that have <10% rate of occurrence. The reason that many of the patterns are believed to reﬂect a congenital defect as opposed to simply the destructive eVects of hydrocephalus is that the ends of the corpus callosum, rostrum, and splenium, are frequently missing. Defects in neuroembryogenesis are most likely to aVect the ends and the destructive eVects of hydrocephalus tend to aVect the middle structures (Barkovich, 1995).

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Compensatory mechanisms have been suggested for partial agenesis of the corpus callosum (Jeeves, 1994). These include enhanced transmission by other commissures, or by ipsilateral and/or subcortical pathways. These mechanisms may be critical in supporting interhemispheric transfer and the integration of information that is so diYcult for many with SBM. Little is known about the anterior, hippocampal, and posterior commissures and Probst bundles that may help compensate for callosal defects. The anterior commissure conveys axons from visual, auditory, or olfactory regions such that some degree of interhemispheric transfer of information involving these regions is apparent in patients with a callosotomy (Risse et al., 1978). Another potential compensatory mechanism is the hippocampal commissure, which Barkovich (1995) reported as enlarged in some cases of dysgenesis. Probst bundles may be present if the hippocampal commissure is enlarged. The axons of some of the callosal neurons that normally would run interhemispherically may turn and run parallel to the interhemispheric ﬁssure forming the longitudinal bundles of Probst and producing crescent-shaped lateral ventricles (Barkovich, 1995). Not much is known about Probst bundles in humans. It has been suggested that Probst bundles do not contain commissural ﬁbers (Chiarello, 1980). However, research with mice having congenital agenesis of the corpus callosum indicates that some of the ﬁbers leave the bundles and traverse the midline by growing across the dorsal surface of the hippocampal commissure when it is large enough (Ozaki & Wahlsten, 1993). Whether Probst bundles are present in children with SBM and the possible role for the hippocampal commissure, has not been considered in the literature on plasticity. With MRI data, the frequency of enlargement of the anterior, hippocampal, and posterior commissures and the frequency of Probst bundles can be determined. Of the 52% of children with SBM who show dysgenesis, 61% are only missing the splenium; only two are missing both the splenium and the body, and one is only missing the body. The other 38% are missing the rostrum with or without the splenium. Only six children with MRI data on the corpus callosum and the other commissures have an enlarged anterior commissure, so it is unlikely that this is a compensatory mechanism for callosal anomalies. It might be a compensatory mechanism in these six individual cases, two of whom are missing the splenium, four of whom have a hypoplastic splenium, and all of whom have a hypoplastic body. More of the children (24) have an enlarged hippocampal commissure, but none of them or any of the other children so far show evidence of Probst bundles. It is interesting to note that 15 of these 24 children (63%) are missing the splenium as opposed to the 32% in the total sample.

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2. INTERHEMISPHERIC TRANSFER

Previous research on interhemispheric transfer of information in individuals with partial or complete agenesis of the corpus callosum suVers from several limitations (Hannay, 2000; Hannay et al., 1999), with the most common being sample sizes of fewer than 10 participants. Small sample sizes magnify the eVects of variables such as gender, age, and handedness. Relatively few researchers have documented the nature of the callosal dysmorphologies with MRI, determined the status of the other cerebral commissures, or determined the relationships between structural anomalies and behavior (Fischer et al., 1992; GeVen et al., 1994). As is the case with many areas of psychological research, there is no single set of accepted callosal tasks making it diYcult to compare and interpret ﬁndings. Generalizations are often made from data collected on a few, possibly atypical cases; it is, of course, important not to overlook such cases. We planned a research project designed to avoid most of these problems by focusing on children with SBM, where callosal anomalies are common, but variable. A variety of interhemispheric transfer tasks were implemented in a systematic study of auditory, visual, and tactile transfer. These tasks were selected as they could be diVerentially sensitive to the variations in the integrity of the corpus callosum described in the preceding text. To illustrate, many children with SBM are missing the posterior body and the splenium, important for interhemispheric transfer of auditory information. In the dichotic listening task, sounds are presented simultaneously to both ears and the listener must report what was heard. Those who are left hemispheredominant for language correctly report more linguistic sounds, such as consonant-vowel syllables, presented to the right rather than the left ear. This right ear advantage occurs because linguistic sounds presented to the right ear go primarily to the left hemisphere to be processed. On the other hand, linguistic sounds presented to the left ear go primarily to the right hemisphere initially and then must cross over in the corpus callosum to be processed in the left hemisphere. When there is disruption of the route for interhemispheric transfer of auditory information, relatively few of the syllables presented to the left ear will be heard (left ear extinction). The posterior body carries auditory ﬁbers linking the superior temporal lobe regions (de Lacoste et al., 1985). Left ear extinction is apparent on dichotic listening tasks in adults with discrete lesions in the posterior body (Alexander & Warren, 1988). More recently, Pollman et al. (2002) and Sugishita et al. (1995) reported that lesions of the posterior 20% of the corpus callosum, a region that comprises the splenium and sometimes the posterior body of the corpus callosum, resulted in left ear suppression.

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Although research involving patients with destructive lesions of the corpus callosum are important for specifying the likely regions of the corpus callosum involved in auditory transfer in the normally developing brain, they do not address the basis of auditory transfer in individuals such as those with SBM who have congenital dysmorphologies of the corpus callosum. None of these studies can address the eVects of thinning of the corpus callosum. We analyzed data on a sample of children with SBM who completed a consonant-vowel dichotic listening task and MRI. The largest groups within this sample were children with a missing splenium and a hypoplastic body (n ¼ 25) and hypoplasia of the splenium and body (n ¼ 35). The ﬁndings for these two groups and the entire sample did not diVer signiﬁcantly. However, children with lower level spinal lesions showed a signiﬁcant right ear advantage, while children with upper level lesions did not show an ear advantage, implying anomalous cerebral representation of language. Similarly, right-handers showed a signiﬁcant right ear advantage, but not left-handers. None of the children showed complete extinction of either ear. These data generally support the idea that hypoplastic regions of the corpus callosum have the ability to transfer much of the auditory information necessary to recognize consonant-vowel syllables presented to the left ear in right-handers and to the right ear in lefthanders. Subcortical pathways may be involved, but this has not yet been established. The data presented here are helping to answer some of the questions posed about interhemispheric transfer of information and the status of the corpus callosum and the other cerebral commissures. As with other projects, clinical markers help explain variations in at least one outcome measure. Analysis of the data from the other interhemispheric transfer tasks will help determine whether the mechanisms used vary with the type of information transferred and the remaining regions of the corpus callosum. In the next few years, we expect to continue addressing the role that abnormalities in interhemispheric transfer play in various aspects of life, not only when individuals with SBM are children, but also in adult life.

V.

DEVELOPMENTAL FACTORS: A LIFE SPAN APPROACH

We now turn to studies addressing critical aspects of the development of children with SBM as infants and preschoolers, in school-age children, and as adults. The common threads across these studies and the previous studies are the focus on core process, major outcome domains, and relationships with clinical markers that help explain variations in outcomes.

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Jack M. Fletcher et al. Early Development

The studies reviewed in the previous sections suggest that children with SBM show core neurocognitive diYculties involving motor timing control, and learning; visual perception; attention regulation; and interhemispheric integration. These diYculties likely produce problems with rule-based problem solving, contextual language, and behavior regulation that, in turn, have a negative impact on the development of intelligence, academic functions, and adaptive behavior in school-age children. Therefore, the core diYculties cut across domains of function and are related to the brain dysmorphologies associated with SBM, and to the environment in which the children develop. The developmental origins of these core diYculties have not yet been studied, and there are few studies of the early development of children with SBM. In the present component of the research program, we studied these core processes from 6 to 36 months of age, including; (1) motor skills, including motor timing, control, and learning; (2) visual perception; and (3) attention regulation. The goals were to: evaluate the development of basic cognitive and motor skills; determine how early in development, diYculties with core processes can be identiﬁed; evaluate the relationship of early diYculties with core processes to later diYculties in basic cognitive and motor skills and more complex behaviors referred to as integration of information and contingency learning (II/CL) skills; identify caregiver and family background characteristics that may moderate the impact of these early learning deﬁcits on long-term outcomes. These research questions were addressed in a longitudinal study of 91 infants with SBM and 74 controls assessed up to ﬁve times over the ﬁrst three years of life (6, 12, 18, 26, and 36 months); the attrition rate was 7%. Within the group with SBM, 79 had shunted hydrocephalus and 12 had arrested hydrocephalus; 75 had lower level spinal lesions and 16 had upper level spinal lesions. In terms of sociodemographic characteristics, 48% were male; ethnicities were: 56% Caucasian, 30% Hispanic, 8% African American, and 6% other (Native American, Asian). The babies were mostly identiﬁed at birth in Houston and Toronto, with some supplementation from outlying areas in south Texas and southern Ontario. The demographics are similar to those for the school-aged sample, with the slightly increased number of Hispanics and reduced number of Caucasians likely reﬂecting the changing demographics of spina biﬁda.

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FIG. 5. Model for relations of core deﬁcits in infancy, emerging information integration, and contingency learning/II/CC, skills in toddlerhood, and long-term competencies.

Figure 5 presents a model guiding the development of this study that has inﬂuenced the research program as a whole. In this model, core deﬁcits involving motor timing, control, and learning, visual perception, and attention regulation emerge early in infancy. These cross-domain deﬁcits aVect emerging skills in the toddler with SBM, which result in weaknesses in II/CL skills: rule-based and social problem-solving, contextual language, and behavioral regulation. They also have an impact on the development of cognitive, language, and motor skills that also inﬂuence the development of the integration of II/CL skills. The emergence of these competencies is moderated by parenting and family background factors. The competencies that are the end products of the model in Figure 5 emerge as long-term diYculties experienced by many children with SBM. Rule-based problem-solving involves the ability to follow an unseen but predictable pattern based on the discovery and utilization of a set of rules and procedures. Contextual language tasks involve re-telling a story the child has immediately ﬁnished hearing, coaching an examiner through a social situation that had been familiar to the child, and oVering socially appropriate responses in a conversation with the examiner. Finally, we assessed behavior regulation through an unstructured, goal-directed play task and the Daily Living skills domain of the Vineland. Adaptive Behavior Scales (Sparrow, Balla, Cicchetti, 1984). This domain involves the ability to organize and execute complex chains of behavior. In the next section, we will

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report preliminary results involving the development of basic cognitive and motor skills and core processes; the relations of core processes to II/CL at 36 months of age; and the impact of the environment on these relations in the context of this model. B.

Basic Cognitive and Motor Skills

Performance on the Bayley scales of infant development was evaluated over the ﬁve time points from 6 to 36 months of age in a comparison of infants with SBM (shunted and arrested hydrocephalus) and controls on growth on the Bayley mental and motor scales (Lomax-Bream et al., 2003). There was an SES by group interaction for overall level of performance, indicating that the eVects of lower levels of SES on mental development were greater for children with SBM than for controls. Additionally, lower levels of SES resulted in slower rates of linear growth in mental development. Figure 6A shows that growth was linear in all groups, with lower scores for the group with SBM and shunted hydrocephalus. The group with arrested hydrocephalus had higher Bayley mental scores at each time point, although this group also showed lower levels of performance than the controls. For the Bayley motor scale, Figure 6B shows that performance was lower in both groups with SBM, with little diVerence in growth or level of performance. There was also an SES by group interaction, demonstrating the greater eVects of low SES on motor development for children with SBM, relative to typically developing children. However, growth was not linear, with Figure 6B revealing that typically developing children were beginning to show a leveling in their rate of growth on the motor scale by the ﬁnal time point, 36 months. However, even at this ﬁnal evaluation period, the typically developing children showed a higher level of performance than children with SBM, who did not show ﬂattening of the growth patterns. C.

Core Processes

At 6 months, assessments of motor timing and control discriminated children with SBM from typically developing controls. In particular, children with SBM scored higher on a measure of the quality of motor responses, where higher scores are associated with poorer motor quality. Their problems on this scale were evident on items examining quality of upper and lower limb movement and organization of motor actions. As we found little diVerence in the groups with SBM and shunted versus arrested hydrocephalus, we did not separately report results for these groups in these analyses. Motor contingency learning was evaluated by studying the ability of infants to learn that the movements they made with their arms, when one arm

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FIG. 6. Growth curves for the Bayley mental scale (A) and motor scale (B) for children with spina biﬁda meningomyelocele (SBMM) (shunted and unshunted) from 6 to 36 months and normal controls (NC).

was attached by a string to a brightly colored mobile, caused the motion and rate of motion of the mobile. Children with SBM were much less successful than controls during the acquisition phase of the motor contingency learning paradigm. Assessment of attention regulation showed diVerences between children with and without SBM. Attention shifting was measured using the Cohen visual habituation paradigm (Cohen, 1972), with the attention shift measured as time to shift gaze from a ﬂashing and beeping red light to a presentation of a human face on a television screen that was controlled by a computer. Up to 24 months of age, children with SBM took signiﬁcantly longer to shift from one compelling stimulus to another. While shifting attention was

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expected to be an early problem for children with SBM that normalized after the ﬁrst year of life, this result demonstrates that children with SBM have attention regulation diYculties into the second year of life. The pattern across time showed that the diVerences between the groups were not present at 6 months as both groups showed relatively long latencies to turn to the stimulus. However, by 12 months of age, typically developing children had established the contingency between the light going oV and the stimulus appearing, because their latency to shift decreased dramatically and remained at this level through 26 months. This developmental transition was not manifested for children with SBM. Studies of older children using the Posner paradigm (Posner et al., 1987) document deﬁcits in the cued control of attention (Dennis et al., 2003). Cumulatively, these ﬁndings suggested that infants with SBM experience problems with motor timing, control, and learning, and attention regulation. These skills were hypothesized to constitute early core deﬁcits. Correlations among these core deﬁcits demonstrated that the motor timing/control skills were moderately interrelated but were not related to attention shifting and exhibited only small correlations with motor learning. Motor learning and attention shifting were not related. The early core abilities appeared to represent separate or distinct skills that are expected to compose early foundation skills for a range of later abilities. D.

36-Month Outcomes: Relations With Core Processes

We examined the 36-month outcomes and the relation of growth in the core processes to the 36-month outcomes. At 36 months, we evaluated rule-based problem-solving via a complex search task in which the child must learn eYcient strategies to organize a search, problem-solving in social context via the number of prompts needed to teach a naı¨ve experimenter a simple board game, and contextual language via re-telling of a story with toy prompts. Behavior regulation was assessed with the daily living skills domain of the Vineland. Children with SBM performed more poorly on the search task, using less eYcient search strategies than typically developing children and requiring more trials to ﬁnd all of the hidden treats. In addition, children with SBM required more prompts to explain the tea party game adequately to a naı¨ve experimenter, suggesting that they are less able than controls to infer the perspective and situation of another person. On the contextual language task, the typically developing children were more successful than children with SBM at remembering and re-telling elements of a story with familiar characters from Winnie the Pooh. The Vineland daily living results paralleled those reported for the Bayley scales, but with considerable ﬂattening in the rate of growth by 36 months.

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In turning to 36-month outcomes, contextual language development at 18 and 26 months was associated with subsequent performance in social problem-solving, contextual language, and rule-based problem-solving at 36 months. Thus, earlier language ability and social responsiveness may be related to later skills in social problem-solving and contextual language. We also found relations between early language abilities and non-verbal procedural tasks. Because the search task, an assessment of rule-based problemsolving, requires use of eYcient search strategies, it may be that the children with stronger language skills used language through mental representation processes to formulate more eVective strategies. Children’s general cognitive and motor skills at early ages play an important role in their eventual ability to attend, plan, and execute eVective spatial search strategies. Scores on independent goal-directed play and on the Bayley mental and motor scales of infant development predicted the 36month outcome of rule-based problem-solving, as assessed by the box search task. The children’s performance on independent play tasks across 6 to 36 months also showed relations with competence on the box search task. This pattern may suggest that early motor, basic cognitive, and independent exploration skills are related to subsequent development of rule-based learning and problem-solving skills. Thus, measures more speciﬁc to motor timing and organization were related to better performance on measures of rule-based and social problem-solving, contextual language tasks, and behavior regulation. Children who demonstrated better motor timing and control in early infancy required fewer trials to ﬁnd hidden rewards in the box search, required fewer prompts during the tea party game to solicit socially appropriate responses, correctly narrated more elements of a story they had just heard during the story re-tell task, and had higher daily living scores. Another revealing pattern of relations was found using measures obtained from the administration of the Cohen habituation paradigm, which uses the computer-timed presentation of a series of familiar and novel human faces as the child shifts attention between the faces and a ﬂashing light with tone. This measure evaluated one of our core deﬁcits, visual perception. First, the length of time required for children to shift attention between the compelling stimuli in this paradigm at 18 months was related to the number of trials required for their searching during the simplest level of the box search series at 36 months. In addition, the children’s eYcient shifting of attention at 12 and 18 months was related to their rate of growth on the Bayley mental scale, and this ﬁnding was stronger for the children with SBM. Second, the percentage of time the children spent looking at familiar (versus novel) faces at 26 months was signiﬁcantly related to the number of trials they required during the total box search. That is, children who were more successful at

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habituating to familiar faces at 26 months then demonstrated more accurate and eYcient search strategies (fewer searches) in a spatial reasoning task at 36 months. Cumulatively, the preceding ﬁndings support the model in Figure 5. Although not conclusive, the ﬁndings suggest that the early abilities of children with SBM in such areas as motor timing, control, and learning, visual perception, and attention regulation, all of which we have identiﬁed as core deﬁcits, may form an important foundation for the II/CL skills required to exhibit later mature problem-solving and physical exploration of ageappropriate stimuli. As our study of preschool development continues, we expect to expand the number of domains assessed and to more closely link core processes and II/CL skills. We will also begin to evaluate the impact of caregiver and family background factors that likely moderate the impact of these core processes on long-term outcomes. Ultimately, we will link this study with the studies involving school-age children reported throughout this chapter. E.

Academic Functions in SBM: The School-age Child

Spina biﬁda meningomyelocele is associated with an atypical pattern of academic skill development: Reading decoding is often well developed, but reading comprehension, writing, and math are acquired less well (Barnes & Dennis, 1992, 1998; Barnes et al., 2001, 2002; Halliwell et al., 1980; Wills, 1993). Our research approach has been to describe the pattern of academic function associated with SBM using the models and tools of cognitive and developmental science to understand how literacy and numeracy skills develop or fail to develop in individuals with SBM. 1. READING

Studies of reading in children with SBM have revealed a pattern of good decoding accuracy, reading ﬂuency, and phonological processing skills accompanied by poorer than expected reading comprehension, even in those individuals with average verbal intelligence (Barnes & Dennis, 1992; Barnes et al., 2001). The rate of reading comprehension disability is also greater than the rate of disability in reading decoding, provided that a more complex assessment of comprehension is employed. A subset of our children with SBM participated in a speciﬁc study of reading and math skills. These children (n ¼ 111) met more stringent selection criteria, including an absence of mental deﬁciency and reading decoding levels of at least grade 3. In this subsample of school-age children, 26% had scores below the 25th percentile on a text reading comprehension task compared to 18% (ignoring math diYculties) in this subsample with scores below the 25th percentile on the

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WJR word identiﬁcation task. Whereas average scores on the WJR word identiﬁcation subtest (M ¼ 106) and cloze-based passage comprehension (M ¼ 103) subtests are age-appropriate, the average comprehension score on the text passage task was 88. Here the child has to read paragraphs and answer questions related to literal, inferential, and thematic aspects of the passages. Our previous studies of the sources of comprehension deﬁcits in children with SBM revealed particular diYculties in inferential comprehension and construction of meaning from context (Barnes & Dennis, 1998; Barnes et al., 2003). Particularly robust is the ﬁnding from our current project that children with SBM have diYculties making inferences in oral language, with 43% of the group with SBM performing below the 25th percentile on a test of inference making. These deﬁcits in inferencing and text-level skills have also been observed in non–brain-injured children with a reading comprehension disability, but no neurological disorder (Cain et al., 2001). Of importance is the ﬁnding that inference-making skills contributed unique variance to the prediction of reading comprehension after having accounted for word-level reading and semantic processes (e.g., vocabulary knowledge). 2. MATHEMATICS

Studies of math achievement in SBM have consistently revealed deﬁcits in mental and written arithmetic and functional numeracy (Dennis & Barnes, 2002; Halliwell et al., 1980; Wills, 1993). The prevailing hypothesis about the origins of calculation disabilities in SBM has been that their characteristic visuo-spatial impairments underlie the deﬁcits in math computations (Fletcher et al., 2000; Wills, 1993). Visual-spatial skills are related to geometry, estimation, and problem-solving in children with SBM (Barnes et al., 2002). These are areas of math associated with visual-spatial skill in normal development, and are also areas of signiﬁcant disability in children with SBM. However, our recent math studies reported in the following text suggest that the calculation diYculties of individuals with SBM are not related to deﬁcits in visual-spatial processing. To investigate the cognitive sources of the math diYculties, we have used a math disability model (Geary, 1993) that proposes three subtypes of math disability, each of which has diVerent underlying cognitive characteristics as well as diVerent patterns of relation with reading. This model stems from earlier work examining the subtypes of reading and math disability (Rourke, 1989). According to Geary’s model, deﬁcits in math computation may arise from three sources, each of which may lead to a subtype of math disability: 1) problems in learning, representing, and retrieving math facts from semantic memory, leading to a subtype related to reading disability through a common proposed deﬁcit in verbal working memory; 2) diYculties in the

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acquisition and use of developmentally mature problem-solving strategies or procedures to perform mental or written calculations, leading to a subtype with procedural diYculties in which the relation to reading is not speciﬁed; or 3) diYculties in the spatial representation and manipulation of number information, leading to a less common subtype that may characterize individuals who have speciﬁc math impairment, with no reading disability. Based on this model, we hypothesized that a small set of core cognitive deﬁcits might underlie some of the cognitive and academic diYculties of children with SBM. In the case of math, we were interested to see whether the known visuo-spatial deﬁcits associated with SBM might also be related to their math disability, and whether diYculties related to the learning and transfer of procedures might be related to their impairments in mathematical processing. Barnes et al. (2002) investigated the types of errors that children with SBM and their typically developing controls make in written calculations. We used a multi-digit written subtraction task in which errors were coded as reﬂecting problems related to the three math disability subtypes. Three types of errors were coded: 1) math fact retrieval errors reﬂecting an error on single-digit subtraction within the multi-digit problem even when borrowing procedures might have been accomplished correctly (e.g., 32936 ¼ 292); 2) errors reﬂecting the misapplication of arithmetic procedures, which could take several forms, including always subtracting the smaller from the larger number (e.g., 32936 ¼ 313) and problems in borrowing across multiple zeros; and 3) errors due to problems in visuo-spatial processing, manipulation of numbers such as misreading or miswriting numbers, neglecting one side of the problem, or misalignment of numbers in columns. We compared a large group of good word decoders with SBM, and a smaller group of poor word decoders with SBM to controls. Based on the math disability model presented in the preceding text, we predicted that the poor readers with SBM would have more math fact retrieval and visuo-spatial errors than controls, while the good readers with SBM would have more visuo-spatial errors. Children with SBM who had diYculties in both reading and math demonstrated more math fact, procedural, and visuo-spatial errors than controls. Good readers with SBM scored lower on the written subtraction task than controls, and diVered from controls only in the rate of procedural errors. Children with SBM who have diYculties in both reading and math have more pervasive math problems than their SBM peers who are good readers. Their calculation performance is poorer and they have a higher incidence of all type of errors, including math fact errors, which are purported to characterize children with co-morbid reading and math disability. The results for the poor reader group are similar to those for children with both reading and math disabilities without SBM who also have problems in multiple domains

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of math (Jordan & Hanich, 2000). Good readers with SBM have problems with the learning and application of arithmetic procedures. There is no evidence that a core deﬁcit in visuo-spatial processing underlies calculation skills in SBM. Although these error analyses suggested no diVerences between good readers with SBM and controls in terms of math fact retrieval processes, accurate performance is not the same as skilled performance. Skilled performance is both fast or ﬂuent and accurate. To test whether good readers with SBM were both accurate and fast in math fact retrieval, we used a cognitive addition task. Children saw single-digit addition problems on a computer screen (e.g., 4 þ 3 ¼?) and had to say the answer as quickly, but as accurately as possible. The experimenter recorded the apparent strategy used, which was veriﬁed by asking the participant to say what strategy he/she used after each trial. Strategy use was coded in sequence from most to least developmentally mature as follows: 1) direct retrieval: the child just knew the answer for 3 þ 4 was 7; 2) counting up: the child counted up from the highest number: 4, 5, 6, 7; and 3) counting all: the child counted verbally or on ﬁngers: 1, 2, 3, 4, 5, 6, 7. We found that good readers with SBM were as accurate as controls in solving the single-digit arithmetic problems, and both groups used the same proportion of computation strategies. Most children from both groups used direct retrieval, the most developmentally mature strategy, while the next most frequently used strategy was counting up. Although equally accurate and similar to controls in strategy use, the group with SBM was slower than controls on both the counting up trials and also on memory retrieval trials. These results are not consistent with models of math disability that propose that math fact retrieval is intact in good readers (Geary, 1993). In this group of good readers with SBM, math fact retrieval is accurate, but slow. Slow math fact retrieval may lead to processing bottlenecks, reducing cognitive resources needed for learning, and the application of more complex arithmetic procedures. Thus, the math disability of children with SBM may be related to processing deﬁcits in very basic aspects of arithmetic. Developmental studies show that individual diVerences in math fact retrieval are associated with diVerences between children in early development (Siegler, 1988). Thus, the cognitive origins of deﬁcits in basic computation are likely to be found in problems in the development of informal math skills in preschoolers with SBM. Preliminary data from our longitudinal study of infants suggest that the emergence of early number skills is delayed. Preschoolers with SBM have diYculty compared to age peers on a variety of early math tasks including matching on the basis of number and understanding counting concepts. Our current studies investigate how ﬁne motor function and visuo-spatial processing are related to the emergence of diVerent

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aspects of emerging number skills. We will also begin to evaluate relationships with lesion level, brain anomalies, and other factors. F.

Cognitive Outcomes of Adults with SBM

Infants with SBM grow into children, who, in turn, mature into young adults. A signiﬁcant body of information is now available about cognitive function in children with SBM (Fletcher et al., 2000), although little is known about neurocognitive function in young adults with SBM. We have considered the issue of adult outcome in relation to ﬁve questions: Is the proﬁle of cognitive strengths and weaknesses developmentally stable? Are there neurocognitive deﬁcits that abate or attenuate with increasing age? Are there neurocognitive deﬁcits that emerge only in adult life? What are some of the sources of variability within groups of young adults with SBM? What are the consequences of neurocognitive deﬁcits for quality of life and employment? 1. DEVELOPMENTALLY STABLE NEUROCOGNITIVE DEFICITS

The proﬁle of cognitive strengths and weaknesses is developmentally stable from childhood into adult life. The overall level of intelligence does not change from childhood to adulthood (e.g., McLone, 1992). Preschoolers and school-aged children with SBM (predominantly Caucasian with lower level lesion) are often reported to show a characteristic pattern of IQ test performance, with higher verbal IQ than performance IQ scores (Dennis et al., 1981). This pattern does continue into adulthood in this subsample, with larger sample studies showing statistical diVerences (e.g., Dennis & Barnes, 2002), and smaller sample studies showing non-statistical diVerences but the same IQ pattern (e.g., Hommet et al., 1999). Motor function is impaired in children with SBM. Aside from the obvious lower limb motor impairments, children and adults have signiﬁcant upper motor limb dysfunction involving both unimanual and bimanual function (Dennis et al., 2002; Hetherington & Dennis, 1999). Children and adults with SBM also have motor speech deﬁcits that include dysﬂuency, ataxic dysarthria, and slowed speech rate (Huber-Okrainec et al., 2002). Neurocognitive proﬁle is generally stable from childhood to young adulthood. Vocabulary skills are generally well developed in children (Dennis & Barnes, 1993) and young adults with SBM (Barnes et al., 2003). The visual

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perception deﬁcits of childhood in SBM (Dennis et al., 2002) continue to be evident in young adult life (Hetherington & Dennis, 2001). Literacy patterns are stable from childhood into young adulthood. Children with SBM have preserved reading decoding relative to their own reading comprehension (e.g., Barnes & Dennis, 1992), as do young adults with SBM (Barnes et al., 2003). Writing is poor in both children (Anderson & Spain, 1977) and adults (Barnes, Dennis et al., 2003) with SBM. The stability of mathematics deﬁcits, a signiﬁcant source of disability in children with SBM, has been demonstrated in both longitudinal and cross-sectional investigations of adults with SBM. Of interest are measures of adult functional numeracy, the ability to perform number operations such as making price comparisons, performing banking operations, dealing with coins, and budgeting. Longitudinally, individuals with SBM who have poor mathematical problem-solving as children grow into adults with poor mathematics problem-solving skills and limited functional numeracy; young adults as a group have poor computation accuracy, poor computation speed, diYculties with mathematical problem-solving, and poor functional numeracy (Dennis & Barnes, 2002). 2. NEUROCOGNITIVE DEFICITS THAT ABATE OR EMERGE BY YOUNG ADULTHOOD

To date, there have been no studies reporting abatement or attenuation of the broad domains of cognitive impairment characteristic of children with SBM. On the contrary, it appears that new cognitive challenges emerge. For example, young adults with SBM show neurocognitive problems in the domain of memory. Rote memory is a cognitive strength for younger children with SBM, although some forms of memory are poorer in older adolescents than in younger children with SBM. Although children with SBM have been reported to show some selected memory diYculties (e.g., Yeates et al., 1995) the memory problems in adults are more severe and, in some instances, constitute clinical memory deﬁcits. Adolescents and young adults with SBM have memory deﬁcits relative to published norms on several tasks (Hommet et al., 1999). SBM involves late-emerging, selective deﬁcits in immediate and delayed retrospective memory and functional, everyday memory, in young adults with SBM, and these deﬁcits are disproportionate to problems in either verbal IQ or attention (Dennis et al., 2001). 3. SOURCES OF WITHIN-GROUP VARIABILITY IN YOUNG ADULTS WITH SBM

We have shown that spinal lesion level is a source of variability within the group of children with SBM, with children with upper spinal lesions typically exhibiting more cognitive diYculties that those with lower spinal

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lesions (e.g., Dennis et al. 1981). In young adult life, upper rather than lower spinal lesion level has been related to greater upper limb motor dysfunction (Dennis et al., 2002), less motor independence (Hetherington et al., in press), and poorer occupational status (Hetherington et al., in press). Shunt revision history, a proxy for medical instability, is a source of variability within the group of children with SBM. For the most part, shunt revision history has proved unrelated to cognitive outcomes in children with SBM (e.g., Raimondi & Soare, 1974; Tromp et al., 1979). To be sure, frequent shunt revisions may signal good shunt maintenance (McLone et al., 1982). In adults with SBM, the number of shunt revisions has been related to retrospective and functional memory problems (Dennis et al., 2000) and poor functional numeracy (Dennis & Barnes, 2002), although not to literacy (Barnes et al., 2003). 4. CONSEQUENCES OF ADULT NEUROCOGNITIVE FUNCTION FOR QUALITY OF LIFE

We have recently studied quality of life in young adults with SBM (Hetherington et al., in press). Instruments measured physical and occupation function, cognitive/psychological function, somatic sensation, and social interaction, in the context of the ability to live independently. Basic quality of life was not impaired, in the sense that, except for motor independence scores were within one standard deviation of the population mean. Not unexpectedly, motor independence is compromised in adult life for individuals with SBM. It may be that deterioration in motor status in adults with SBM contributes to poorer quality of life in the motor domain; for example, mobility decreases from childhood to the teen years and is sustained into young adulthood (McLone, 1992). Childhood academic deﬁcits that persist into adult life compromise quality of life. Both writing deﬁcits and poor functional numeracy are related to lower levels of adult independence in domains such as social language, personal living, and community independence (Barnes et al., 2003; Dennis & Barnes, 2002). Research on adult outcomes has implications for whether the cognitive problems of children with SBM should be addressed with the passage of time or with active educational intervention. The data on young adults with SBM do not support the view that the neurocognitive deﬁcits of SBM abate with time. Rather, an untreated math disability in childhood evolves, 20 years later, into adult innumeracy involving an inability to use numbers in everyday life, and that signiﬁcantly limits functional independence and quality of adult life. Some, but not all of the cognitive proﬁle of adults with SBM, are predictable from knowledge of their childhood neurocognitive function. Memory problems that appear to be related to an unstable shunt history are currently

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unpredictable. Some 75% of individuals born with SBM will reach early adulthood (Bowman et al., 2001). A signiﬁcant proportion of these individuals may exhibit emergent problems in functional memory that were not evident in childhood. Awareness of these emergent cognitive diYculties will help ensure that adults with SBM have access to eVective cognitive treatments, if required. More broadly, the emergence of new cognitive problems in the adult life of individuals with SBM is consistent with the idea that individuals with neurodevelopmental disorders reach adulthood with limited cognitive and brain reserve, which makes them vulnerable to new neurocognitive problems as they move through adult life (Dennis, 2000; Dennis et al., 2000).

VI.

CONCLUSIONS AND FUTURE DIRECTIONS

The approach we have adopted in our attempts to understand SBM has involved four major goals: (1) the delineation of a modal proﬁle; (2) a search for core processes that cut across domain-speciﬁc modal deﬁcits; (3) identiﬁcation of the sources of genetic, neural, and cognitive variability; and (4) an attempt to study outcomes from infancy to young adult life. The neurocognitive impairments of SBM appear to be reliable over populations and stable over the life span. Cognitive strengths shown in childhood continue to be demonstrated in adulthood, and deﬁcits that are evident in childhood do not abate in adult life. If we consider isolated pieces of information about cognitive function, the neurocognitive proﬁle of children with SBM may appear to be domain speciﬁc; however, if we explore the core deﬁcits underlying problems in diVerent domains, as we have done in recent studies, the deﬁcits are process speciﬁc, with preserved and impaired neurocognitive function varying within each domain according to task domains. There is an important implication of this ﬁnding, which is that particular brain regions are likely to be involved in neurocognitive deﬁcits across domains. To illustrate, the motor domain has long been observed to be impaired in children with SBM across the life span. The lower limb gross motor deﬁcits of these children are predictable and related to spinal function. Deﬁcits in the upper extremities involve control, organization, and quality of gross and ﬁne motor movements, many of which are modulated by the cerebellum and depend on motor cortex, visual cortex, and parietal areas for guidance. A major ﬁnding by our group is that some of the ﬁne motor deﬁcits of children and adults with SBM represent, not only movement disorders, but also timing impairments, and that some functions mediated by the cerebellum, such as speech articulation, and precise motor movements appear to be

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impaired across the life span, regardless whether the response requires a motor response, with no identiﬁed strengths in these areas. The visual perception domain has also been a source of consistently reported impairment in children with SBM. In our studies of infants, we have shown that impairments in a variety of non-verbal skills are apparent early in development. Motor, perceptual-motor, and visual-perceptual skills are commonly impaired in studies of infants, school-age children, and adults, although there is variation within these domains depending on task and cognitive demands. The attention regulation domain is also impaired in individuals with SBM. Our studies of early development have shown that attention impairments can be detected as early as 6 months with habituation tasks that require focusing and manipulation of perceptual stimuli. In school-aged children, these diYculties are evident on attention regulation tasks that are ageappropriate, suggesting a relation with infant habituation tasks that assess attention regulation and visual perception (Colombo, 1995). Attention problems are tightly linked to visual perceptual deﬁcits early in development. Later in childhood, exogenous and endogenous attentional control are impaired, and are related to the midbrain, white matter, and posterior cortex brain anomalies of SBM. The investigation of neurocognitive outcomes of SBM in the context of process speciﬁcity has been productive. There are other areas that we and others are evaluating. The ﬁndings generated so far suggest that brain dysfunction in SBM may be quite speciﬁc. Consistently, we have observed impairments in individuals with SBM for core processes that are mediated by the cerebellum and more posterior regions of the brain, such as timing and endogenous control of attention. We have also reported impairments in core processes that are mediated by the corpus callosum, angular gyrus, and heteromodal cortex, and that require complex, interhemispheric integration of knowledge and currently activated information, such as inferencing, and the understanding of idiomatic language. In contrast, functions mediated by the anterior temporal and frontal regions appear relatively better developed. We also know that basic motor, perceptual, and language functions are organized diVerently in individuals with congenital brain injury, but large groups of children with early congenital injuries have rarely been studied. The critical question is whether there are variations within SBM that explain these anomalies and their organization in the brain. We plan to continue to address variations in the modal cognitive proﬁle of children with SBM, and, at the same time, explicitly study the functional organization within brain regions of basic motor, perceptual, and cognitive functions. In order to complete these studies, new technologies for functional neuroimaging will be critical. In addition, the life span approach that is emerging

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from our research program is critical. Studies of young children must continue and we hope to follow the infants in our longitudinal studies to school age so that we can fully integrate the early development and school-age components of the study. Studies of adults are also critical. The consequences of the physical, medical, and cognitive eVects of SBM extend into young adulthood and have an impact on quality of life. But investigation of many of the core cognitive deﬁcits of SBM has not yet been conducted in young adults. It is important to study core processes and clinical markers in young adult populations as these variables seem to be related, not only to motor and cognitive function, but also to adult occupational status and quality of life (Hetherington et al., in press). Studies of the neural phenotype and genetic factors must continue. The cognitive studies are most meaningful when accompanied by a full characterization of the genes and brains of each individual with SBM. If we can increase the sample size, we hope to link the genetic, neural, and behavioral studies even more closely. For example, it will be informative to analyze the genetic data according to the nature of the corpus callosum anomaly, and also to relate variations in reading and math skills, both with established heritable components (Grigorenko, 2001), to the genetic data. Finally, the genetic studies are critical for elucidating causes of SBM and ultimately methods for prevention. Studies of multi-aVected families and trios will be especially important. The goal of unlocking the mysteries of a complex neurodevelopmental disorder like SBM will be best achieved by studying large, well-characterized samples within a multi-disciplinary perspective at key points throughout the lifespan. ACKNOWLEDGMENTS Supported in part by National Institute of Child Health and Human Development Grant P01 HD35946 ‘‘Spina Biﬁda: Cognitive and Neurobiological Variability.’’

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The Role of the Basal Ganglia in the Expression of Stereotyped, Self-Injurious Behaviors in Developmental Disorders HOWARD C. CROMWELL DEPARTMENT OF PSYCHOLOGY BOWLING GREEN STATE UNIVERSITY BOWLING GREEN, OHIO

BRYAN H. KING DARTMOUTH MEDICAL SCHOOL LEBANON, NEW HAMPSHIRE

Self-injurious behavior (SIB) in the context of various developmental disorders has been the focus of increased research and clinical attention in recent years (e.g., Schroeder et al., 2002). Self-biting is a particularly devastating form of this behavior and the majority of animal models of SIB involve stereotyped biting. In humans, self-injurious acts, such as biting and hitting, are common in the broad spectrum of developmental disorders, particularly in cases with more severe degrees of cognitive and emotional disability (Bodﬁsh et al., 1996; GriYn et al., 1987; Murphy et al., 1999; Newell et al., 1999; Oliver et al., 1987; Schroeder et al., 1978), and can result in signiﬁcant morbidity (Oliver et al., 1987). A recent analysis of impact forces in children with mental retardation equated the force of self-hitting to that associated with boxing blows and karate hits (Newell et al., 2002). Thus, injuries from head-banging, injuries to the eyes and face from self-hitting, self-biting of the lips or ﬁngers, and even death may result from SIB associated with developmental disorders (King, 1993; Nissen & Haveman, 1997). SIB is also a risk factor for out-of-home or institutional placements, and can signiﬁcantly adversely aVect the quality of life of the individual and the people involved in their life (Burack, 1994; Oliver et al., 1998; Symons et al., 1999). INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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Most of the clinical discussion of SIB focuses on cognitive or emotional factors that contribute to its expression (Ball et al, 1985; Baumeister, 1978; Kahng et al., 2002). Without diminishing the signiﬁcance of the relationship between these behaviors and higher-level psychological processes, it is also important to highlight the observation that repetitive, stereotyped SIB shares features with or frankly co-exists with disorders of movement as well as motor control (Bodﬁsh & Lewis, 2002; Bodﬁsh et al., 2000; McKay & Halperin, 2001). Indeed, in a study of the early emergence of SIB, Murphy and colleagues (1999) observed that within a population of children with severe intellectual disabilities, children with general motor deﬁcits were more likely to exhibit SIB than were controls. In their recent review, Bodﬁsh and Lewis (2002) have noted that, as a potential neuroanatomic home for disorders of movement and emotion, the basal ganglia (BG) is particularly appealing. Recently, we have used manipulations of the BG to learn more about the neural basis of stereotyped movements including self-injury (Cromwell & Berridge, 1996; Cromwell et al., 1996, 1997, 1998; King et al., 1995, 1998). Like Bodﬁsh and Lewis (2002), our experience and review of the literature have led us to believe that this neural system in conjunction with its cortical pathways is important in the production of SIB in some developmental disorders. Thus, our aim in the present review is to discuss the potential roles for the BG in the production of SIB. First, we will describe the BG system and the movement impairments that occur when the system is damaged. Second, we will review studies using animal models of stereotyped movements, locomotion, and SIB. We will conclude with ideas for future directions of study and treatment.

I.

THE BG SYSTEM: FUNCTION AND DYSFUNCTION

The BG system includes the subcortical structures of the striatum, globus pallidus (GP), and the substantia nigra (SN). Other structures intimately connected with the BG system include the subthalamic nucleus, amygdala, and the pedunculopontine nucleus (Kelley et al., 1982; Lee et al., 2000). Each of these brain regions has well demarcated subregions and each subregion has a set of distinct connections that make it unique from adjacent subregions. The striatum is comprised of three well-recognized major subregions: the caudate nucleus, the putamen, and the ventral striatum or nucleus accumbens. The globus pallidus has medial (i.e., internal segment), lateral (i.e., external segment), and ventral subregions; and the substantia nigra contains two main subregions: the pars compacta and the pars reticulata. This set of BG structures comprises the largest subcortical system in the brain, and its complex connectivity and internal structure have made it

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extremely diYcult to address questions about its functional nature. A relatively recent, but well-documented observation is that the system participates in numerous non-motor functions that include perceptual, cognitive and emotional aspects (Berridge & Cromwell, 1990; Ravizza & Ivry, 2001; Ring & Serra-Mestres, 2002; Schneider & Lidsky, 1981; Setlow et al., 2003). This idea of functional heterogeneity has not been associated with the BG system throughout the history of neuroscience research. Traditionally, it was thought that the system had a uniform motor function, mainly involved in movement generation, initiation, or in postural control (Carpenter, 1966; Martin, 1977; Wilson, 1914). Wilson (1914, p. 478) stressed this point in writing: ‘‘When we remember the histological simplicity and comparative structural homogeneity of the corpus striatum, in contrast with the greater dimensions, much more intricate cytoarchitectural complexity, and far wider connections of the rolandic motor cortex, the idea of attributing all of the disturbances to striatal disease and of crowding corresponding centers into that ganglion becomes nothing short of ludicrous.’’ In the past 20 years or so, researchers have been increasingly crowding diVerent functional centers inside the BG system. The initial impetus for the attribution of functional heterogeneity came from the realization that the anatomy of these structures was not simply homogeneous (Kemp & Powell, 1970; Mensah, 1977). Novel methods for tract-tracing (Heimer & Wilson, 1975; Nauta & Gygax, 1954) and histochemical identiﬁcation (Falck et al., 1962; Lindvall et al., 1978) revealed that the BG system contains many diVerent inputs and outputs and neurochemical patterns distributed in a topographic fashion. As ideas about the functional nature of the BG system have depended upon the evolution of anatomical ﬁndings, it is essential to address some of the most prevalent and inﬂuential anatomical-based theories that involve this system. We brieﬂy review some details of this functional heterogeneity by presenting the main parts of the BG story and its connectivity, and the most recent ideas about how information is integrated within the internal networks and associated external circuitries of this fascinating system. A.

The Corticostriatal Connection

One critical feature of the BG network is the size and scope of the cortical input (Kemp & Powell, 1971; Webster, 1965). The cortical to striatal projection is massive with an estimation of some 380,000 cortical axons innervating the volume of a dendritic tree of a single neuron located within the striatum (Kincaid et al., 1998). This immense projection is coupled by a great diversity of incoming projections. At a systems level, neuroanatomists have found corticostriatal connections emanating from every cortical region,

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including the more ancient allocortex characterized with only three layers (McGeorge & Faull, 1989). A topographic map of the projections arising from cytoarchitectonically distinct areas of cortex has been uncovered using anatomical tracing (Selemon & Goldman-Rakic, 1985) as well as physiological mapping (Brown, 1992; Brown et al., 1996, 1998). Brown and colleagues (1992, 1996, 1998) used somatosensory stimulation of the forelimbs, hindlimbs, and trunk to demonstrate that a map existed for these body parts in the lateral striatum. Similar to the overlying sensory and motor cortex, the map had the facial body parts of a mouth and a snout in the more ventral areas and the forelimbs and hindlimbs are represented in the more dorsal areas. Carrelli and West (1991) also found similar topographical inverse mapping for both motor and sensory information using in vivo neurophysiology of single neuron activity. A body homunculus representation has also been found in the cat (Malach & Graybiel, 1986) and both human and non-human primates (Alexander & Delong, 1985; Gerardin et al., 2003). Selemon and Goldman-Rakic (1985) elegantly showed that the conﬁguration of the cortical topography from association areas in the frontal, temporal, and parietal lobe could be described as a longitudinal arrangement with a series of interdigitating strips running along the anterior-posterior extent of the caudate, putamen and ventral striatum. The input from cortex to striatum utilizes glutamate and acts on numerous receptors located on the most prevalent striatal cell-type, the medium-sized spiny projection neuron (Bolam et al., 2000; McGeer et al., 1977). These glutamate receptors are varied and include n-methyl-d-aspactate (NMDA) and non-NMDA subtypes (Cepeda et al., 1991a,b), and the activity of these glutamate receptor subtypes is modulated by the incoming dopaminergic inputs from the substantia nigra (Cepeda et al., 1993; Levine et al., 1996). Extensive study of the neuromodulatory actions of dopamine (DA) at the level of the striatum has revealed their complexity (Hu et al., 1990; Levine et al., 1996; Weick & Walters, 1987). Recent studies support the idea that activation of diVerent receptor subtypes has a diVerential eVect upon the temporally related glutamate receptor activation (Cepeda et al., 1991a; Levine et al., 1996). In particular, D1 receptor activation enhances subsequent activation of the NMDA glutamate receptor, and D2 activation decreases the subsequent activation on the non-NMDA receptor located on the medium spiny projection neuron of the striatum. Dopaminergic inﬂuences appear also to be critical with respect to the function of striatal interneuron activity. Striatal interneurons comprise just 2% to 4% of the neuronal population of this structure, and can be divided into cholinergic and GABAergic cells based upon the main neurotransmitter they release. The important role for these aspiny neurons in regulating BG

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circuitry is increasingly being appreciated, and Centonze and colleagues (2003) have recently shown that D5 receptors may be particularly important in some of the regulatory eVects of striatal interneurons on BG output. Having such a large excitatory input arriving to the BG makes the system susceptible to excitotoxic damage caused by dysregulation of glutamate receptor function at the level of the striatum. The BG pathology is consistently linked to a large set of developmental and neurodegenerative disorders thought to be partially caused by developmental or chronic excitotoxic reactions in the brain (Selemon, 2001). Within the second week of life in the rat (Nansen et al., 2000), glutamate receptors appear early in the development of the brain with populations of striatal neurons expressing diVerent types of glutamate receptors. These glutamate receptors are functional early in the developing brains of rats and cats (Cepeda et al., 1991a; Colwell et al., 1998). Interestingly, compared to glutamate responses in the adult animal, the developing animal has enhanced evoked potentials following local stimulation (Siviy et al., 1991). Thus, overstimulation of the glutamate receptors can produce excitotoxic damage including cell loss and altered connectivity (Brunsen et al., 2001). This early development of the massive corticostriatal glutamate input as well as the enhanced responsivity to glutamate during development could leave the striatum as well as other BG structures particularly vulnerable to damage early in life. Several studies have found a high susceptibility of BG structures to hypoxia and ischemia, complications that may be seen during birth and that have been thought to be related to the etiology of some developmental disabilities (Mallard et al., 1995; Pastuszko et al., 1993; Schmidt et al., 1988; Toft, 1999). Neurotoxicity associated with hyperbilirubinemia, another cause of developmental disability, also appears to be mediated by glutamatergic mechanisms (Grojean et al., 2000; McDonald et al., 1998). Similar neurotoxic mechanisms have been postulated to play a role in the progressive cell death seen in neurodegenerative BG disorders, such as Huntington’s and Parkinson’s disease (Graybiel et al 1990; Lancelot & Beal, 1998). B.

Parallel Circuits of the BG System

Early work on BG functional neuroanatomy stressed the segregated nature of the looping circuits (Fig. 1) that seemed to be the elemental processing units of the system (Alexander et al., 1985; Alexander & Crutcher, 1990; Albin et al., 1989; Delong et al., 1984; Penney & Young, 1986). This idea of segregated closed loops utilized a set of generalized characteristics that included: 1) a set of discrete non-overlapping portions of the BG system structures involved in each loop; 2) a reception of multiple but highly related cortical inputs to each circuit; 3) a gradual funneling of these

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FIG. 1. Generalized corticostriatal loop. The BG system is characterized by connections arriving from the cortex to the BG input nuclei of the caudate nucleus and putamen (striatum). This structure (striatum) then sends outputs to the BG output centers of the globus pallidus and substantia nigra. These output structures then send projections to regions in the thalamus. The thalamus, in turn, has a major output to the cortex. This cortico-BG-thalamo-cortical loop has been the standard circuit in which to characterize information ﬂow through the BG system. Most accounts of this circuitry have proposed that functionally related sets of striatal cells receive information from a related set of cortical areas. In this way, the striatum would consist of micro-zones of inter-related functional clusters that received inputs and funneled outputs to the next circuit location. DA ¼ dopamine; GABA ¼ gamma amino butyric acid; M1 ¼ primary motor cortex; PM ¼ premotor cortex; SMA ¼ supplementary motor area; Thal ¼ thalamus.

projections as they course from the striatum to the pallidal/nigral output structures of the BG; and 4) this funneling ending with a return to a single cortical region located in the frontal motor area of the cortex (Alexander et al., 1990). The set of inputs that arrive into discrete basal ganglia subareas have been proposed to be a functionally related set (Alexander & Delong, 1985) or at least arrive from regions of cortex that themselves are co-connected (Yeterian & Van Hoesen, 1978). The loops were never posited as rigid or selfenclosed but they were emphasized to be mainly segregated in terms of their functional role and driven by a functionally constrained set of cortical centers. Five major loops were proposed including: (1) a motor loop with inputs from frontal motor cortical regions including the supplementary motor area and primary motor cortex to the lateral putamen; (2) an oculomotor loop with inputs from the frontal eye ﬁelds to the caudate nucleus; (3) a dorsolateral prefrontal circuit with inputs from the prefrontal cortex to the head of the caudate nucleus; (4) a lateral orbitofrontal loop with inputs from prefrontal

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and temporal cortices to the ventromedial caudate; and (5) an anterior cingulate loop with inputs from the medial prefrontal cortex, hippocampal formation, and temporal lobe to the ventral striatum. In this schema, the cortical inputs are the clear deﬁning source and these models emphasized not only that the BG system was highly diverse in function but also that the cortex guided this diversity and controlled how the striatum received information. At the same time new models arose attempting to better deﬁne the output principles of BG function. Segregated pathways from the striatum were proposed based upon neurochemical and neuropharmacological composition of the striatal neurons themselves (Chang & Kitai, 1982; Gerfen, 1984; Wilson & Phelan, 1982). This segregation consisted of dual projections from the striatum to subdivisions of the pallidal and nigral output centers of the BG system. One of the main diVerences between these output circuits was the DA receptor subtype located on the striatal projection cell. The two main output pathways were characterized as direct and indirect. The direct pathway consisted of neurons that projected directly to the output centers of the medial globus pallidus and the substantia nigra (Gerfen et al., 1990). These output regions project out of the BG system to the thalamus, and the neurons that project to them were shown to contain substance P and have D1-type dopamine receptors. The indirect pathway consisted of striatal neurons that projected to the lateral segment of the globus pallidus and had D2-type dopamine receptors. Since this GP sub-area projects to the subthalamic nucleus instead of the typical output centers, it is an indirect circuit. The neurons within the indirect circuit co-localize the peptide enkephalin, which makes them easily discriminable from the cells in the direct loop. Evidence for these direct/indirect striatal output systems arrives from multiple sources including peptide immunocytochemical work (Beckstead & Kersey, 1985; Gerfen et al., 1995), DA receptor localization (Gerfen et al., 1990), and functional data showing that DA oppositely regulates these two pathways (Cenci et al., 1992; LeMoine et al., 1991). Behavioral data have also supported the idea that D1 and D2 receptor activation involves diVerent neural ensembles and can involve diVerent functions. Selective eVects of D1 or D2 receptor function on movement control (Cromwell et al., 1998; Onla-or & Winstein, 2001), emotional responses (White & Viaud, 1991) and cognition (Williams & Goldman-Rakic, 1995) support the idea that these pathways are distinct in function. These parallel circuit models for cortical inputs and striatal outputs dramatically increased the understanding of the functional heterogeneity of the BG system. More recent work has taken these ﬁndings to a new level by re-incorporating the importance of divergence and convergence within and between these looping circuits.

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The description of the BG system as a set of parallel inputs or outputs led to many commentaries on the extent of the closed nature of these loops and recent proposals have debated the issue with evidence that the BG loops are more open and interconnected than previously thought (Haber & Fudge, 1997; Joel & Weiner, 1994; Levy et al., 1997; Smith et al., 1998; Thompson et al., 1988). One of the main issues was the degree of overlap of cortical inputs from diVerent cortical locations. Was the topography arranged as a set of related cortical structures that sent their projections to a common BG location? Yeterian and Van Hoesen (1978) found that very disparate regions of cortex including the parietal and prefrontal cortices sent overlapping inputs to the striatum. Yet, they proposed that the cortical regions that did overlap were interconnected at the cortical level. Others have found the same relationship between interconnected cortical areas and their degree of overlap at the level of the striatum (Andersen et al., 1990; Cavada & Goldman-Rakic, 1991). There are, however, exceptions to this relationship. Graybiel and colleagues completed a series of studies that showed the cortical-striatal relationship to be more complicated but to retain some of the properties of the older model. They used sophisticated coupling of neurophysiological recording with tract-tracing of the anatomical connections to map the functional connections between sensory and motor areas of cortex and striatum (Flaherty & Graybiel, 1991). They asked the question: ‘‘Would functionally related but spatially distinct areas of cortex converge onto overlapping sites within the striatum?’’ They found a high degree of convergence from diVerent cortical areas that mapped the same body part onto overlapping striatal zones but also found divergence in that diVerent body part representations from primary sensory cortex provided diVerent inputs to diverse non-overlapping striatal areas. A set of studies by this research group (Flaherty & Graybiel, 1991, 1993a,b, 1994) laid the foundation for a primary re-assessment of the parallel nature of BG connections. The input-output organization was described as ‘‘a set of divergence and a re-convergence’’ that may enable local associative networks within the striatum that could allow for integration between distinct areas of the cortex. Output signals may carry an even greater degree of divergent information but our understanding of these pathways is just now being more clearly examined and elucidated (Hoover & Strick, 1993).

D.

Information Integration

The latest property used to describe the BG system has been integration. An integrative systems model for intrinsic BG processing and for processing functions between the BG system and other neural systems and structures

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has overtaken the previous notions of segregated circuitry (Fig. 2). Will this approach better describe the normal functions of this complex system or the complex symptoms observed following BG system dysfunction? Haber and colleagues (1997, 2000, 2001) have completed numerous tract-tracing studies to reveal several interactive points along the BG system circuit. These interactive points include areas such as the DA cell-rich areas of the midbrain. Here it seems that subgroups of DA cells located with the dorsal tier of the region, substantia nigra pars compacta (SNpc), receive input from the ventral striatum and amygdala and send their outputs to regions within the frontal cortex (mesocortical tract). Another DA cell group located in the ventral tier of the SNpc receives inputs mainly from the medial and ventral striatum but sends outputs to the lateral ‘sensorimotor’ striatal regions (Francois et al., 1984; Parent & Lavoie, 1993). This type of criss-crossing connectivity between purportedly functionally diverse BG subareas is also seen in thalamic projections. The thalamus sends direct inputs to the striatum as the second largest source of excitatory

FIG. 2. Parallel loops with some proposed sites of interaction. More recent models of BG system connectivity emphasize both the loop system and a high level of integration. These two characteristics are evident from the basic circuitry of the striato-thalamo-cortical structure of the system and from the newly found evidence of interactions between BG structures at diVerent levels of the system. These open-ended traits of the loops reduce the parallel nature of information ﬂow and allow for much more intercommunication between the sensory, motor, cognitive, and aVective circuits that comprise the BG system. Accepting this fact, we now may return our eVorts to attempting to understand a common function for the BG that includes these diverse properties. dm Thal ¼ dorsomedial thalamus; GABA ¼ gamma amino butyric acid; SNpc ¼ substantia nigra pars compacta; vlThal ¼ ventrolateral thalamus; vmThal ¼ ventromedial thalamus; VTA ¼ventral tegmental area.

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input to the center (second to that of the cortex). The majority of the ﬁbers come from the midline and intralaminar nuclei (Beckstead, 1984; GimenezAmaya et al., 1995), but there is also a direct connection from the reticular nuclei of the thalamus (Groenewegen & Berendse, 1994). Direct connections from the ventral tier nuclei of the thalamus exist (McFarland & Haber, 2002; Smith et al., 1987); these are the same nuclei that receive inputs from the BG output structures of the globus pallidus and the substantia nigra. This connection could provide more direct feedback to the striatal structures as an oVshoot of the information ﬂowing onto the cortex. Finally, a recent study by Kolomiets and colleagues (Kolomiets et al., 2003) demonstrated that the output lines of the direct and indirect pathways seem to send convergent information to single cells in the substantic nigra pais reticulate (SNpr). Their data revealed a link of trans-subthalamic and direct striato-nigral pathways within and between channels of communication. This level of cross-talk has been proposed to function as a higher level gating mechanism for motor and sensory control between diVerent motor and sensory channels that course through the BG. In addition to these sites of convergence and divergence between BG structures, a number of other inputs also arrive to the BG from outside sources. These inputs include ﬁbers arriving from the amygdaloid complex that includes connections to the basolateral nucleus of the amygdala and to the central and medial nuclei of the amygdala (Fass et al., 1984). These diVerent amygdaloid centers send outputs mainly to the dorsal and ventral striatal region, respectively. Additionally, smaller ﬁber bundles arrive from the hippocampus, bed nucleus of the stria terminalis, and the midline nuclei of the septum (Nauta, 1989). These subcortical structures have been proposed to be involved in aVective processing (amygdala) and in cognitive/ spatial mapping (hippocampus) in addition to other roles in emotion and learning. Each of these inputs must be recognized and accounted for to fully understand the complex role of the BG in behavior. Clues as to the magnitude of the diversity of inputs onto single striatal neurons were found during a recent analysis of the connectivity of single corticostriatal axons (Kincaid et al., 1998). These researchers examined whether cell clusters within the striatum were composed mainly of sets of neurons that received either: (1) a common set of inputs; (2) mostly overlapping inputs; or (3) mostly non-overlapping inputs. If the inputs are similar between the diVerent neurons within a cluster, then the individual cells are interchangeable and the cell cluster (200 to 500 um in diameter) would be functionally homogenous. If the cell clusters contained units that received dramatically diVerent inputs, then neighboring cells would be computing unique input combinations involved in functionally diverse operations leading to functional heterogeneity. Results of their microtopographic mapping

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showed that the individual cells receive dramatically diVerent inputs. It was estimated that a low proportion of the thousands of cortical axons synapse onto to the neighboring neurons in the striatum (1.4% at the most conservative level). Similar ﬁndings for partially overlapping inputs onto striatal interneurons has recently been shown (Ramanathan et al., 2003). This uniqueness of the connectivity of neighboring striatal cells strongly supports the idea that the individual cells within these tight clusters process diVerent information. Functional studies using in vivo electrophysiology have found exactly this type of delineation of cell responsiveness when measuring more complex integrative aspects of the cell response (Cromwell & Schultz, 2003). By better understanding the complex nature of the integrations of the BG system, we can better appreciate how damage to this system could lead to complex problems in motor performance. E.

Neurodegenerative Disease and the BG System

As noted at the outset, the importance of the BG in motor control has long been observed in clinical practice. Marsden (1982) was among the ﬁrst clinicians to propose that the ‘mysterious function of the basal ganglia’ was to integrate various processes; he developed this idea mainly from viewing the motor impairments seen in patients with Parkinson’s disease (PD). The prominent motor symptoms of patients with PD, including akinesia, rigidity, and postural imbalance, can be modulated by their emotions. In addition, emotional disorders, for example, depression, are often seen in persons with PD either co-existing with the motor problems or even preceding them. Thus, some clinicians have suggested that these aVective disturbances are related to the earliest stages of the neurodegeneration involved in PD. Huntington’s disease (HD) is also characterized by motor, emotional, and cognitive changes (Folstein et al., 1983). The choreiform movements of HD are often exacerbated or ameliorated by the emotional state of the aVected individual. Similar to PD, persons with HD also frequently experience emotional disorders, and several studies suggest that these aVective disorders are not due simply to the recognition of the onset of a neurodegenerative disease but are caused by the neuropathological changes of the disease process itself. Other emotional-motor disorders are thought to involve alterations in BG processing. These include Tourette syndrome, obsessive-compulsive disorder, and even schizophrenia (Arnsten, 2001; Mega & Cummings, 1994; Mink, 2001). Dysregulation of the BG has been found in the midbrain DA-rich ﬁelds in each of these disorders and major deﬁcits in motor and cognitive function seem to arise when the DA pathways to the striatum and cortex become imbalanced (Busatto & Kerwin, 1997; Carlsson, 2001; Swerdlow, 2001). In Tourette syndrome, intrusive tics may include recurrent,

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rapid movements such as head-shaking, wrist-ﬂicking, ﬁnger-twiddling, grimacing, or mouth-opening (Messiha & Carlson, 1983; Richardson, 1982). Interestingly, as many as 30% of persons with Tourette syndrome may exhibit SIB (Robertson et al., 1989). This wealth of data provides support for the BG involvement in emotional modulation of action and in the production of action sequences that rely on integration of information from multiple brain regions. Developmental disorders are clearly heterogeneous, and caused by alterations in several body and brain systems (Mann & Iwatsubo, 1996; Martineau et al., 1992). On the other hand, might alterations in the BG system play a fundamental role in particular motor symptoms seen in some of these disorders? Using work from the clinic as well as work completed using various animal models, we will now review more direct evidence that support a link between this system and the dramatic motor impairments seen in some developmental disorders.

II.

BG PATHOLOGY AND DEVELOPMENTAL DISORDERS

Dysfunction within the BG system has been noted in several developmental disorders and in the majority of cases, motor sequencing functions are impaired in conjunction with emotional and cognitive problems (Arena et al., 1992; Aylard et al., 1997; Harris et al., 1995; Kostrzewa et al., 1994; Okano et al., 1992; Russell et al., 1995; Tan et al., 1997; Sonuga-Barke, 2002). Many of the motor symptoms seen in developmental disorders mimic the hyperkinetic movements seen in BG disease. These types of correspondences will be reviewed in the following section and, using neuroimaging techniques, we will highlight the growing evidence that the BG system is altered in several types of developmental syndromes (Santosh, 2000). These relationships have not been well appreciated in the past and the awareness of how the BG might be involved will allow us to approach the cases with more treatment strategies and a better comprehensive therapy approach. Lesch-Nyhan syndrome is a neurodevelopmental disorder associated with alteration in purine metabolism through the functional loss of the X-linked HPRT protein (Jankovic et al., 1988; Nyhan, 1973). Children with this disorder exhibit choreiform movements, and invariably present with severe SIBs (Hall et al., 2001). Neuroanatomic and recent neuroimaging studies have demonstrated signiﬁcant alteration in striatal dopamine measures in this disorder (Nyhan, 2000; Saito et al., 1999; Wong et al., 1996). Wong and colleagues found the levels of DA transporters signiﬁcantly reduced in patients with Lesch-Nyan syndrome (n ¼ 6) using the WIN-35,428 ligand and positron emission tomography (PET) imaging (1996). The range of reduction within the caudate nucleus and putamen regions was 50% to 75% against

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a comparison of control subjects (n ¼ 10). Decreased dopa decarboxylase and DA storage activity has also been described in the Lesch-Nyhan syndrome using ﬂuorodopa F-18 tracers (Ernst et al., 1996). Areas of decrease include the caudate nucleus (39% lower), putamen (31% lower), and frontal cortex (44% lower) in comparison to controls. Ernst and colleagues (1996) concluded that patients with this rare disorder have signiﬁcantly fewer dopaminergic nerve terminals and cell bodies, and the developmental insult aVects the BG system directly as well as indirectly by involving regions of the brain that send inputs into the BG system (frontal cortical regions). Similarly, Visser and colleagues (2000) have suggested that Lesch-Nyhan disease is a BG disorder. Sears and colleagues (1999) have called attention to the involvement of BG structures in autism. In their study, high-resolution scans were obtained in high-functioning adolescents and autistic young adults (ages 12 to 29 years). In comparison to matched controls, caudate volumes were found to be larger in the subjects with autism, and this change in caudate size signiﬁcantly correlated with ritualistic-repetitive behaviors. In particular, the neural change was signiﬁcantly and positively correlated with complex mannerisms that were scored in the ritualistic-repetitive domain of the Autism Diagnostic Interview (ADI), but the BG change was not correlated with other symptoms of autism captured on the communication or social domains of the ADI (Sears et al., 1999). Other research teams here also found links between autism and BG function (Robinson et al., 2001; Rumsey & Ernst, 2000; Sahley & Panksepp, 1987). Muller and colleagues (2001) imaged subjects with autism during the performance of a ﬁnger movement Go/ No-Go task. Areas of lesser activation during the task included the caudate nucleus and the frontal motor cortical regions. Surprisingly, the group with autism showed less deactivation in non-motor regions such as the parietal and occipital cortex and more deactivation in prefrontal regions. The authors suggested that attentional focus could be reduced due to the loss of attentional-induced down-regulation of the posterior and prefrontal cortices relative to forebrain motor systems. Accumulation of heavy metals, which target BG structures, has been found in autism as well (Latif et al., 2002). Rett syndrome is one of the pervasive developmental disorders and is remarkable for the development of hand stereotypies at the expense of functional movements. BG involvement has been demonstrated in Rett syndrome by various groups (Casanova et al., 1991; Jellinger & Seitelberger, 1986; Leontovich et al., 1999; Wenk, 1995). Signiﬁcant alterations in the size of the caudate have been found in this syndrome (Casanova et al., 1991) and a growing number of studies have found alterations in the BG dopaminergic system in patients with Rett syndrome. The number of DA receptors (D2)

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and re-uptake sites have been shown to be decreased in the putamen as well as in the cortex (Wenk, 1995). Overall levels of DA and its metabolites have been shown to be decreased (Wenk, 1995). Marsden (1984) postulated that deﬁcits in action sequencing seen in PD and other BG disorders reﬂect the ‘‘true’’ function of the BG system. Dysfunction of the striatum leads to abnormal execution of learned motor programs dependent upon sensory, emotional, and cognitive sets (Buchwald et al., 1975; Marsden, 1984). The response set biased the group of motor programs available within a speciﬁc context and removed the chances that other distracting information (sensory or motor) would disrupt the completion of the pattern of movement. Such deﬁcits have been extensively revealed using a variety of reaction time tasks (Evarts et al., 1981; Harrington & Haaland, 1991; Heilman et al., 1976). Relevant to the present review, these similar reaction time and anticipation tasks have been found to be impaired in children with developmental disorders (Brewer & Smith, 1984; Mottron et al., 1999; Rubia et al., 1999). In some persons with SIB, could dysregulation of BG systems result in the over-expression of certain action sequences and the intrusion of unwanted motor and sensory information? If so, the expression of repetitive or in some cases apparently compulsive acts like SIB would be expected to be modulated by the emotional state of the individual, similar to the motor impairments of BG disease (Kemperman et al., 1997; King, 1993; Powell et al., 1996; Ross & Oliver 2002). III.

ANIMAL MODELS OF STEREOTYPED SELF-INJURY

Considerable information regarding the relationship of BG function to the expression of stereotypy and even self-injury is available from work with animals. Indeed, new animal models are still being elaborated. For example, the study of spontaneously emergent stereotypy in the deer mouse, Peromyscus, (Powell et al., 1999; Turner et al., 2001), and the study of L-type calcium channel agonist-induced self-biting (Jinnah et al., 1999), hold particular promise. A.

Dopaminergic Models of Stereotypy and Self-Injury

Great progress in the use of animal models to study the neural basis of motor dysfunction in developmental disorders has come from manipulating the function of the DA pathway from the midbrain to forebrain areas of the BG system and cortex (Breese et al., 1994; Delfs & Kelley, 1990; Eichler et al., 1980; Hartgraves & Randall, 1986; King, 2002; Randrup & Munkvad, 1968; Sivam, 1996).

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6-hydroxy-dopamine (6-OHDA), a neurotoxin that can be selective to DA cells in the midbrain or be placed in other regions to selectively remove dopaminergic input, has been used extensively to study the neural mechanisms of locomotion, stereotypy, and SIB. Ungerstedt (1968) injected 6-OHDA bilaterally into the substantia nigra of young adult rats. Thereafter, administration of a single dose of the mixed DA agonist, apomorphine (5 mg/kg), produced a sequence of behaviors beginning with ‘‘increased motility and sniYng that changed into licking and biting. (They) soon developed a furious compulsive gnawing which was far more violent than after the same dose of apomorphine administered to a normal animal. The operated animals even ‘chewed up’ their front paws, bit oV their ﬁngers, or ate themselves into their abdomen’’ (p. 108). Several important attributes of this DA depletion model have since been investigated. One aspect is the timing of the lesion. Does the DA damage have to occur at a speciﬁc timepoint during development to produce abnormal behaviors? Bruno and colleagues (1998) have shown that early lesions of the DA system have dramatically diVerent eVects on behavior and somatosensory function compared to lesions later in life. Rats depleted of DA as neonates are usually spared the signiﬁcant spontaneous behavioral alterations seen in adult animals with DA lesions (Bruno et al., 1998). The seemingly normal appearance of the animals masks many neurophysiological and neurochemical alterations that occur in these animals (Moy et al., 1997). Alterations occur in other neurotransmitter systems such as serotonin and acetylcholine (Descarries et al., 1992; Sandstrom et al., 1996). Hyperinnervation of serotonin input to the striatum has been shown to occur after early DA depletion in rats (Descarries et al., 1992). Moreover, the behavioral eVects of D1 or D2 receptor manipulations are altered in rats with early DA depletion. The eYcacy of DA receptor compounds to induce catalepsy or immobility varies depending upon the lesion and the time of drug administration (Byrnes et al., 1996). The importance of the developmental timing can be seen by noting the time of onset for the diVerent types of behavioral symptoms. In the early animal modeling work of Ungerstedt (1971), the experiments were completed with young adult animals, but in man, SIB typically starts in childhood (Murphy et al., 1999). Moreover, neurodegenerative disorders of BG function appearing late in life like PD and HD are not generally associated with stereotyped self-injury. Breese and colleagues (1984, 1994) examined the issue of timing and found that rats treated with intracisternal 6-OHDA as neonates and challenged as adults with DA agonists (L-dopa, apomorphine) will self-bite, but animals given intracisternal 6-OHDA as adults will not self-injure when similarly challenged. The likelihood of self-biting increases with repeated exposure to

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the DA agonist, a reverse-tolerance phenomenon that the investigators call ‘‘priming’’ (Breese et al., 1984, 1994). On the other hand, when the nigrostriatal dopaminergic system is lesioned in adult animals by direct infusion of 6-OHDA into the nigra (Price & Fibiger, 1974; Ungerstedt, 1971) or striata (Hartgraves & Randall, 1986), an apomorphine challenge also produces self-biting. Are there critical sites or thresholds for DA depletion in the BG system for stereotyped self-biting to be expressed? Other studies have found the placement and extent of DA loss is indeed critical for the production of Parkinsonian symptoms in humans and in animal models of BG disease (Hudson et al., 1993; Jellinger, 1987). Could it be that the timing of the 6-OHDA lesion depends less upon developmental consequences than upon the extent of the lesion produced? ErinoV and colleagues (1984), for example, suggested that intracerebral ventricular (ICV) 6-OHDA in neonates resulted in a more complete depletion of DA than for adult animals. Whishaw and colleagues (1987) found a positive correlation between impairments on spatial navigation, forelimb use, tongue protrusion, limb posture, and sensorimotor tests and the extent of DA depleted from the striatum (caudate/putamen). These lesions were made in 3-day old rats and support the idea that early loss of DA has diVuse eVects upon behavioral and cognitive functions and that these eVects depend upon the amount of DA absent from the BG system. Moody and Spear (1992) found the degree of acute DA depletion to be positively correlated with the likelihood of selfbiting behavior (Moody & Spear, 1992), they also found an interesting third factor that correlated with the others—the degree of increase in DA receptor numbers following the DA depleting lesion. A critical relationship between degree of 6-OHDA–induced DA loss and the degree of DA receptor supersensitivity has been identiﬁed by several groups and the onset of supersensitivity at the pre- or post-synaptic levels could be crucial in the later production of stereotyped movements and SIB (Breese et al., 1987; Casas-Bruge et al., 1985; Marshall & Ungerstedt, 1977; Saito & Takashima, 2000). In supersensitivity paradigms, considerable time must elapse before biting behavior is elicited with a DA challenge. Interestingly, following intracisternal administration of 6-OHDA to neonates, D1 receptor number (Bmax) is increased in the substantia nigra in animals that exhibit L-dopa–induced self-biting (Yokoyama & Okamura, 1997). This leads to the question as to whether one type of DA receptor or another is more important in the elicitation of SIB or in stereotyped movements. Moody and Spear (1992) found that treatment with reserpine and alpha-methyl-p-tyrosine (AMPT) could result in intense self-biting with subsequent administration of the combination of SKF38393 (a D1 agonist) and quinpirole (a D2 agonist) after just 5 hours. When these same drugs were

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administered separately, however, self-biting was much less likely to occur. This response was evident in animals studied as weanlings (postnatal day 21), but not at postnatal day 10. Neal-Beliveau and Joyce (1999) similarly reported a critical period with respect to intrastriatal 6-OHDA lesions. Such lesions at post-natal day 7, but not post-natal day 1, will lead to self-biting with a DA challenge in adulthood. Lesions associated with self-biting had a more signiﬁcant eVect on D1mediated behaviors such as grooming, gnawing, and explosive jumping. The investigators interpreted their ﬁndings in light of the diVerent critical periods for the expression of D1 and D2 receptor subtypes during ontogeny, with attendant diVerential windows of vulnerability. Others have similarly found that self-biting behavior seems to be preferentially produced from D1 receptor activation in animals lesioned as neonates (Breese et al., 1985, 1994; Criswell et al., 1992; Moy et al., 2001). More work needs to be done to determine how this possible uncoupling or selective alteration of receptor function might occur in the early lesioned animal and how this functional change may lead to the motor responses seen in the animal at diVerent developmental stages. Interestingly, self-biting associated with activation of L-type calcium channels (Jinnah et al., 1999)—which is also relatively enhanced in younger animals—could be mediated through D1 receptor subtype activation (Cepeda et al., 1998; Hernandez-Lopez et al., 1997). B.

Pemoline Model of Self-Biting Behavior

Genovese and colleagues (1969) reported the phenomenon of SIB occurring in mice and rats after administration of high doses of pemoline (5-phenyl-2-imino-4-oxo-oxazolidine). These investigators noted that the self-biting ‘‘(had not) been described for any other drug in such an evident form and high incidence’’ (p. 513). Interestingly, in humans, pemoline has also been associated with motoric hyperactivity and athetoid and choreiform movements including prominent orofacial movements and tongue protrusion (Abbott Laboratories, 1975; Bonthala & West, 1983; Dren & Janicki, 1970; Everett, 1975; McNeil, 1979; Nausieda et al., 1981; Singh et al., 1983). Because of its reliability, Mueller and Hsiao (1980) selected pemoline over other agents like caVeine and clonidine that had also been linked to selfbiting behavior in rodents (Boyd et al., 1965; Jones & Barraclough, 1978; Peters, 1967; Razzak et al., 1975; Sallee et al., 1989). These investigators detailed the behavioral response to pemoline noting that the rats became hyperactive, and later exhibited stereotypy, abnormal social and sensorimotor behavior, and seemed unresponsive to moderate levels of sensory stimuli. Increases in locomotor activity occurred within the ﬁrst two hours after

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pemoline receipt. Subsequently, animals displayed increasing degrees of stereotypy culminating in the emergence of self-biting, primarily of the medial foreleg. Once it had commenced, the animals generally persisted in self-biting despite a number of signiﬁcant environmental stressors. For example, poking the rats with a Q-tip, adding a new cagemate, soaking the rats with water, or even banging on the cage with a metal coVee can did not appreciably deter the animals from self-biting (Mueller & Hsiao, 1980). Because of topographical similarities between elements of a normal grooming sequence and self-biting, and because the locations most likely to be injured are typically the ﬁrst to be attended in the context of a typical grooming sequence, Mueller and Hsiao (1980) proposed that pemolineinduced self-biting represented a fragmented grooming response. This is an interesting speculation given the fact that grooming in rats is speciﬁcally triggered by D1 receptor activation (Berridge & Aldridge, 2000), is impaired in mutant mice lacking D1 receptors (Cromwell et al., 1998), and the speciﬁc sequences of grooming behavior are disrupted by striatal lesions (Cromwell & Berridge, 1996). Similarities between this constellation of behaviors and those of some persons with Cornelia de Lange syndrome—speciﬁcally hyperactivity, stereotypy, abnormal social behavior, avoidance of physical contact, and self-mutilation in a manner suggestive of grooming—prompted Mueller and colleagues (1980, 1982) to propose that pemoline might provide a useful animal model for Cornelia de Lange or perhaps the Lesch-Nyhan syndrome. Today, similarities to obsessive-compulsive disorder or Tourette syndrome might also be drawn. Does the pemoline model of SIB share with the 6-OHDA models a dependence upon dopaminergic alterations within the BG system? Accumulating evidence suggests that it does. The dopamine antagonists, pimozide or haloperidol, eVectively prevent or reduce pemoline-induced behaviors (King et al., 1994; Mueller & Nyhan, 1982). Pretreatment with compounds that alter other systems, such as the serotonin neurotoxin, p-chloroamphetamine (PCA), or the serotonin synthesis inhibitor, p-chlorophenylalanine (PCPA), have little or no eVect on pemoline-induced self-biting behavior. The serotonin reuptake inhibitor, paroxetine, may even make the behavior worse (Turner et al., 1999). The GABAergic agonists, such as benzodiazepine and diazepam, are also without consistent eVect on self-biting (Mueller & Nyhan, 1982). Thus, despite the high doses of pemoline utilized in this model, and the possibility of direct eVects on non-dopaminergic receptors, self-biting appears to be mediated primarily by dopaminergic mechanisms. More recent studies have found a link between DA alterations in the BG system and self-biting in the pemoline model. We performed unilateral 6-OHDA lesions of the medial forebrain bundle (MFB) and subsequently challenged rats to a single, high dose of pemoline (250 mg/kg) (Cromwell

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et al., 1996). This paradigm is useful in distinguishing direct from indirect DA agonists, as animals rotate away from the side of greater dopaminergic activation. Thus, a direct DA agonist (acting on post-synaptic receptors), such as apomorphine, would cause rotational behavior toward the unlesioned side by stimulating supersensitive DA receptors on the side of the lesion. Using this paradigm, Cromwell et al. (1996) observed that the lesioned animals rotated away from the unlesioned side, indicating that the pemoline eVect is indirect, thus mediated either by the release of endogenous DA or by preventing the reuptake of this neurotransmitter into the cellular vesicles. Subsequent studies measured intrastriatal pemoline levels following a single subcutaneous injection (250 mg/kg) (King et al., 1998). Interestingly, peak levels of pemoline in the striatum are reached at approximately 4 hours, and remain relatively constant for the next 24 hours. The investigators concluded that the large dose of pemoline, a relatively insoluble drug, probably serves as a reservoir for continuous infusion similar to the amphetamine pellet used by Mueller and colleagues (1982). Our preliminary attempts to directly infuse pemoline into the striatum have resulted in the production of stereotypy, but self-biting has not been observed. Nonetheless, it appears that the eVects of pemoline are likely to be signiﬁcant within the BG system at the level of the striatum. For example, striatal DA depletion after pemoline administration has been observed in self-biting animals. Zaczek et al. (1989) observed self-biting in rats after repeated injection of pemoline over the course of three days. These investigators found that in self-biting animals (in contrast to animals treated with lower pemoline doses that did not self-bite), striatal DA levels were signiﬁcantly reduced (to 60% of control values). Midbrain and hypothalamic norepinephrine levels were also reduced, but levels of the serotonin metabolite, 5-HIAA, were increased. If pemoline is a DA-reuptake inhibitor, one might predict that chronic GBR-12909 administration in the rat would also lead to self-biting behavior over a similar time course, as GBR-12909 is a potent and selective DA reuptake inhibitor (Andersen, 1989). In fact, Sivam (1995), observed that a full 100% of the rats treated with daily doses of GBR-12909 (20 mg/kg) exhibit self-biting after four days. Sivam’s analysis of striatal DA content in these animals reveals signiﬁcant reductions in both DA and its metabolite, DOPAC. In the case of DA, values were reduced to 67% of control values. This degree of depletion is remarkably consistent with that for pemoline, and as with pemoline (King et al., 1995) and the 6-OHDA models, GBRinduced self-biting can be prevented by the DA antagonists, SCH23390 (D1), and spiperone (D2) (Sivam, 1995). Mueller and colleagues (1982) found a dissociation in the production of SIB from other stereotyped movements. When pimozide was administered

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to rats prior to an injection of pemoline, it inhibited SIB but had a relatively small eVect on pemoline-induced stereotypy or hyperactivity. Interestingly, pimozide diVers from other DA antagonists in that it is also a calcium channel antagonist (King et al., 1989; Santi et al., 2002). One wonders, in light of Jinnah and colleagues (1999) highlighting the potential importance of calcium channels in the expression of self-biting, whether pimozide functions as a relatively D1 selective agent at the doses utilized by Mueller and colleagues (1982). Pimozide has been shown to inhibit both L- and T-type calcium channels (Bertolesi et al., 2002), and the aYnity of pimozide for the T-type calcium channel has recently been shown to be from 12- to 20-fold greater than that for haloperidol (Santi et al., 2002). Mueller and colleagues (1982) explored two additional models—chronic caVeine and chronic amphetamine—in an attempt to characterize the relationship between stereotypy and self-biting behavior in the rat. After three days of daily caVeine injections some animals began to self-bite. Haloperidol co-administration delayed the onset and decreased the incidence of self-biting. In animals treated with continuous-release amphetamine pellets, selfbiting was seen within the ﬁrst 48 hours of receipt. Interestingly, with chronic low-dose amphetamine, ‘‘such obvious examples of stereotypy, as headweaving, continuous sniYng, or repetitive licking of the cage, were virtually never observed’’ (p. 616). The authors postulated that continuous administration of lower doses of pemoline may also likely produce selfbiting in the absence of intense stereotypy, and this prediction was subsequently conﬁrmed in their laboratory with weanling rats (Mueller et al., 1986). This is an interesting ﬁnding and one that may provide an explanation for clinical experience that would suggest that while SIB often occurs in the context of other stereotyped movements, it does not necessarily occur as the ﬁnal punctuation of a bout of unrelated stereotypies. The self-biting behavior seen in the pemoline and other dopaminergic models clearly depends upon functional alterations in the DA system, but such alteration is most likely interactive with other neurotransmitter systems (King et al., 1993, 1998; Turner et al., 1999). Additional work toward understanding the pathophysiological consequences of chronic low-dose or acute high-dose exposure to DA transport inhibitors associated with selfbiting would be valuable. We believe such mechanisms involve the BG system and in particular the DA pathways to the striatum and frontal cortical areas. C.

Striatal Manipulations

The question of whether SIB or stereotyped movements involve striatopallidal processing has been studied more directly by altering neural activity in these areas and examining the behavioral consequences. Lesions of the

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striatopallidal complex in the rat lead to alterations in action sequences involved in general locomotion (Pisa et al., 1980; Sanberg et al., 1979), forepaw use (Pisa, 1988; Whishaw et al., 1986), taste reactions (Cromwell & Berridge, 1994), and grooming (Cromwell & Berridge, 1996). Hyperactivity occurs following lesions to the pallidal regions with a concomitant decrease in other speciﬁc actions such as scratching, sniYng, rearing, and grooming (Norton, 1976). The ventral striatum has been shown to be very important in the elicitation of DA-sensitive behaviors like stereotypy and locomotion (Mason et al., 1978; Meyer et al., 1993; Mogenson and Yang, 1991; Winn & Robbins, 1985). These studies have shown that the striatum is intimately involved in the production of stereotyped movements including locomotion. More recent work has shown that the striatum could be involved in the SIB that is seen in the context of certain developmental disorders. Delfs and Kelley (1990) localized orofacial stereotypy in the rat to the ventrolateral striatum (VLS) (Kelley et al., 1988), and wanted to reveal the relative contributions of D1 and D2 stimulation in this region. These receptors are located on the medium-sized striatal neurons that project to the pallidum and substantia nigra. Microinjection of the D1 agonist, SKF 38393, did not produce any changes in behavior during the 30-minute testing period. However, some three hours later, intense self-biting occurred. The same response could also be seen with infusion of DA or amphetamine directly to the VLS, and the self-biting was signiﬁcantly reduced by haloperidol, as well as by the relatively D1-selective antagonist SCH23390 and the D2-selective antagonist raclopride. These results support the idea that SIB involves striatal circuitry and may rely upon DA dysregulation of striatal information processing (Kelley et al., 1989; Kelley & Delfs, 1994). More recently, Canales et al. (2000), have initiated studies to map the neural pathways that mediate behaviors associated with amphetamineinduced stimulation of the VLS. When lidocaine is used to selectively inactivate the substantia nigra pars reticulata (SNpr), oral stereotypy induced by amphetamine microinfusion into the VLS is abolished. Interestingly, the converse is also true. Thus, activation of the SNpr by direct injection of the GABA agonist, muscimol, produces self-biting behavior in the rat (Baumeister & Frye, 1984). The self-biting response in this paradigm also requires an intact midbrain reticular formation, as bilateral electrolytic lesions of the latter area ventrolateral to the periaqueductal gray matter, including the pedunculopontine nucleus, selectively block self-biting but not other stereotypies (Baumeister & Frye, 1986). The BG system sends direct output to this nucleus and this pathway has been thought to provide more direct access to the BG system for inﬂuencing motor programs. Interestingly, Mathur et al. (1997), have also observed stereotypy, including self-biting

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and grooming, in rats treated with bilateral microinjections of scopolamine into the pedunculopontine tegmental nucleus. Self-biting in this model is reduced with parenteral haloperidol administration. Reciprocal interactions between cholinergic and dopaminergic systems have long been appreciated. Thus, Mathur and colleagues (1997) concluded that scopolamine likely acts by blocking muscarinic receptors on mesopontine cholinergic neurons, releasing their inhibition and thereby activating DA neurons. The glutamatergic input from cortex to striatum may be another important locus in the pathogenesis of SIB (Fig. 3). Our basic research supports the idea that one of the main factors that underlies BG dysregulation may be the loss of, or alteration in, the cortical inputs that arrive to the striatum (Cromwell et al., 1995, 1996b, 1999; King et al., 1998). We have observed that bilateral frontal cortical lesions decreased self-biting latency and increased the incidence of pemoline-induced self-biting behavior (Cromwell

FIG. 3. Model of BG involvement in SIB. Early damage or other abnormalities associated with certain developmental disorders may inﬂuence the DA system that projects from the midbrain DA ﬁelds of the substantia nigra pars compacta to the striatum. Evidence now supports the idea that diVerential eVects upon the DA receptors could occur. Thus, supersensitivity of D1 receptors would lead to hyperactivity of the striatal inhibition of BG output nuclei. This would come about because of the enhanced interactive D1 modulation of the glutamatergic cortical inputs arriving to the striatal medium spiny projection neurons. Recent ﬁndings suggest that these supersensitive D1 receptor eVects are mediated by activation of L-type calcium channels. This increase in striatal inhibitory projections subsequently leads to a disinhibition of the thalamic glutamatergic projections to the frontal motor cortex. The overstimulation of this thalamo-cortical projection could lead to hyperkinesia, stereotyped movements, and SIB. Small arrows denote normal or reduced activity between structures and larger arrows denote over-activity following BG dysregulation. DA ¼ dopamine; GP ¼ globus pallidus; PpnT ¼ pedunculopontine nucleus; SN ¼ substantia nigra; SNpc ¼ substantia nigra pars compacta; Thal ¼ thalamus.

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et al., 1999). These ﬁndings are in keeping with others who have shown that cortical lesions enhance amphetamine-induced behavior (Braun et al., 1993; Iversen, 1971), and are of particular interest given that individuals with cortical pathology, such as in severe and profound mental retardation, are more likely to exhibit SIB (King, 1993). Additional ﬁndings of interest concerning the importance of glutamatergic inﬂuences on self-injury derives from electrophysiological studies in pemoline-treated animals as well as treatment with the NMDA antagonist, MK 801. We have (1997) observed that pemoline treatment alters the direction of the modulatory action of DA on synaptic responses recorded in striatal neurons only in rats that display selfbiting. In control animals, DA causes attenuation in synaptic response size, but in animals that show biting behavior after receipt of pemoline, the same DA treatment potentiates the amplitude of the response. This enhancement is blocked by the NMDA receptor antagonist, 2-amino-5-phosponopentanoic acid (Cromwell et al., 1997). Pre-treatment of animals with a glutamate receptor antagonist, MK-801, also reduces or prevents self-biting seen after pemoline injection (King et al., 1993). The same is true for self-biting in the 6-OHDA model (Criswell et al., 1993). These ﬁndings support the idea that cortical glutamatergic inﬂuences are critical in the mediation of SIB and the massive corticostriatal projection could be one of the pathways involved in this inﬂuence. IV. A.

FUTURE DIRECTIONS AND CONCLUSIONS

Summary

Developmental disorders that lead to SIB arise from multiple, interactive points of origin in the brain and body. The motor impairments are produced from a dysregulation of multiple systems including the cerebellum, brainstem, and motor cortical regions. We have presented the latest evidence from animal and human studies that shows that the BG system is also critically involved in the production of motor problems in a broad spectrum of these disorders. Damage to BG structures in humans leads to alterations in motor patterns and the elicitation of involuntary and repetitive actions. Animal models that have focused upon these alterations in the BG system (DA cell groups, striatum, or pallidal regions) have provided much information concerning the neural basis of motor problems in some persons with developmental disabilities. In particular, alterations of DA activity to striatum or prefrontal cortex can lead to stereotyped actions and SIB. Drugs such as pemoline that seem to inﬂuence the DA system within the BG lead to SIB in both young and mature animals. How these drugs produce such actions is unknown but as

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more evidence accumulates we are closer to understanding the physiological mechanisms involved. In concert with the animal studies, a growing number of human studies links BG dysfunction to some developmental disorders. Such studies have identiﬁed structural abnormalities at the striatal level including alterations in DA receptor number in several neural regions. Our understanding of the potential signiﬁcance and functional expression of such alterations in humans will only be achieved through the combination of detailed basic and clinical studies. B.

Future Directions in Animal Models

Considerable work remains to be done with respect to: (1) determining the importance of the timing of neural alterations; (2) examining the diVerential eVects of damage to speciﬁc locations within neural systems and especially within the BG system; and (3) attempting to understand how neural systems become altered during development as a function of genetic or environmental insult. The ﬁrst issue is critical for our ability to comprehend the importance of development in the production of stereotyped self-injury. Timing of the neural damage seems to be a critical aspect in the development of these motor changes. We have reviewed a wide array of behavioral and pharmacological studies that suggest early brain damage leads to a greater severity of symptoms. The long-lasting eVects of the early damage include supersensitivity of receptor populations, a functional division between normally interactive receptor groups (Bruno et al., 1998), an alteration in connectivity that changes the fashion of information transfer within and between structures, and neuron loss that leads to changes in basic functional roles. The timing aspect needs to be examined more thoroughly by analyzing the eVects of damage at a greater number of timepoints and determining the inﬂuence of damage in a larger set of structures. This ‘‘damage’’ may also include the absence of environmental stimuli during critical stages of development— thus, models of spontaneous production of stereotypy, as recently described by Lewis and his colleagues (Powell et al., 1999; Turner et al., 2002), or genetic factors that predispose to the expression of stereotypy in these models, hold particular promise (Turner et al., 2001). The study of factors that facilitate or interfere with the palliative eVects of environmental enrichment in this model may have tremendous payoV. A second aspect that includes investigating where in the brain the damage occurs is no less vital. It will be important to focus on a set of structures and to understand the eVects of early damage on these structures at multiple levels. This includes a detailed investigation of neuroanatomical,

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neurochemical, and behavioral eVects. We have endorsed the BG system as a critical brain region that becomes dysregulated in certain developmental disorders and that this dysregulation is related to the production of aberrant motor sequences. Much research has already been done to pinpoint certain structures involved, such as the substantia nigra and the striatum, but additional work needs to be completed to determine the networks involved in the production of these motor changes. Each BG structure has been found to be functionally heterogeneous and it is likely that the critical damage which leads to self-injury may be located within a smaller subregion of the striatum and its associated regions within the cortico-basal ganglia circuitry. Lastly, it will be important that we begin to incorporate more general, but clinically relevant, means to produce the pathological changes in the animal models. These might include environmental, genetic, or other mechanisms. For example, studies of animal models of the fragile X, Down, and Lesch-Nyhan syndromes are already yielding important insights with respect to factors that may inﬂuence the development and expression of stereotyped behaviors (Gruss & Braun, 2001; Turner et al., 2001; Visser et al., 2002). To make these and other models complete, these new paradigms should be elaborated and combined with detailed physiological and behavioral methods and replicated and extended in diVerent laboratories. C.

Future Directions in Treatments

BG dysregulation is involved in the production of stereotyped actions and self-injury. This idea allows for a more solid theoretical framework to guide treatment options for motor disabilities in certain developmental disorders (Baumeister & Sevin, 1990). New approaches in treatment need to take this idea into account so that the debilitating motor symptoms can be reduced. New therapies for BG disease are progressing, for example, using new technologies like deep brain stimulation of the globus pallidus, subthalamic nucleus, and other forebrain sites (Berk & Honey, 2002; Krauss et al., 2002; Vitek, 2002). Persons with PD, HD, multiple sclerosis, or dystonia have had beneﬁcial eVects from the deep brain stimulator technique (DBS) (Hooper et al., 2002; Krack & Vercueil, 2001; Thompson et al., 2000). More recently, empirical ﬁndings have shown that DBS may be beneﬁcial to patients with other neuropsychiatric disorders (Roth et al., 2001). In February 2001 the ﬁrst patient in the U.S. underwent DBS treatment for OCD. Prior to the surgery, the subject performed hand-washing rituals up to 70 times per day, and afterwards his lifestyle was signiﬁcantly improved with an absence of the debilitating repetitive hand-washing rituals and a return to work. It may be that with SIB or debilitating stereotypy, DBS may some day oVer potential. Within the BG system, targets that would inhibit movement

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would most likely be the internal segment of the pallidum or select regions of the thalamus that receive throughput from the BG system (Vitek, 2002). Other treatments may arise from emerging genetic technologies, the use of drug or polydrug therapies, or combinations of the above with behavioral treatment. Our recent ﬁndings that the neurochemical systems within the BG are involved in motor problems seen in certain developmental disorders have led us to hypothesize that the interaction between DA and glutamate becomes dysfunctional in some persons with SIB (King et al., 1998). The recent elaboration of a model of self-injury involving L-type calcium channels may suggest new opportunities for pharmacological intervention (Jinnah et al., 1999). Newer pharmacological treatments that target particular receptor complexes in these systems may thus hold particular promise in reducing SIB in some persons with developmental disorders.

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Risk Factors for Alzheimer’s Disease in Down Syndrome LYNN WARD DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF ADELAIDE ADELAIDE, AUSTRALIA

Medical and social advances during the 20th century have resulted in dramatic increases in the longevity of people with an intellectual disability (ID) (Patja et al., 2000). In 1929, the average life expectancy of a person with Down syndrome (DS), the most common genetic cause of ID, was 9 years of age whereas now it is 45 years of age (Carr, 1994; Holland, 2000). Currently, 44% of individuals with DS reach 60 years of age with an increase of 200% in the number of individuals age 50 years expected between 1990 and 2010 (SteVelaar & Evenhuis, 1989). With increasing longevity, age-related health problems in adults with ID are becoming increasingly apparent. In particular, DS is linked to premature aging and an increased risk of developing dementia of the Alzheimer disease (AD) type relatively early in life. Compared to the non-disabled population, higher prevalence rates of dementia have been reported for people with DS (Zigman et al., 1993) and for people with ID with etiology other than DS (Cooper, 1997). Furthermore, higher prevalence rates have been reported for people with DS >50 years of age compared to those with other types of ID in the same age bracket (Zigman et al., 1995). Age-related decrements in cognitive performance and adaptive behavior that occur as a result of both normal aging and the onset of dementia place an increasingly heavy burden on individuals with DS, their care-givers, and social and health care services (McCarron et al., 2002; Oliver et al., 2000). Etiological links between DS and AD have been well established by histopathological studies. Most individuals with DS >40 years of age develop the same neuropathological changes observed in the brains of individuals with AD (Mann, 1988). Furthermore, a cholinergic deﬁcit is observed in both INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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disorders (Mufson et al., 1995). Distinctive neuropathological characteristics of AD include neuroﬁbrillary tangles and neuritic plaques. Neuroﬁbrillary tangles are ﬁbre-like strands composed of a hyperphosphorylated form of the tau protein within the cell cytoplasm; neuritic plaques are spherical deposits with a central amyloid protein core found throughout the association areas of the cerebral cortex and the hippocampus. Amyloid beta protein (A), the main constituent of neuritic plaques, is derived from the cleavage of a set of amino acids collectively referred to as the amyloid precursor protein (APP), in a process regulated by estrogen, cholinergic stimulation, and interleukins (Folstein & Folstein, 1997). Overproduction of amyloid causes cell death, with cholinergic cell death linked to increased amyloid production in a positive feedback loop (Buxbaum et al., 1992). Progressive cognitive decline is associated with cell death, with pathological changes occurring ﬁrst in the limbic system followed by the parietal cortex. Disease progression thus entails anosmia and amnesia, followed by aphasia, apraxia, agnosia and, ﬁnally, gait disorder and incontinence (Folstein & Folstein, 1997). The locus of APP has been mapped to chromosome 21, and in DS there is an increased gene dosage for APP as a result of triplication of chromosome 21. Despite the ﬁndings of neuropathological studies, not all individuals with DS develop clinical symptoms of AD. Age-speciﬁc rates of dementia in DS range from 1% to 2% for individuals in their 30s to 40% for individuals in their 50s (Holland et al., 1998). Furthermore, age of onset of AD varies widely reﬂecting large individual diVerences in vulnerability to pathology. There is a pressing need then for research to account for the disparity in neuropathological and clinical ﬁndings and, in particular, to identify biological and environmental factors that impact on the development of the clinical syndrome of AD in DS. The identiﬁcation of risk factors is important because, in addition to extending our understanding of AD in general, it will inform the development of treatment and prevention strategies for people with DS. Recent attempts to identify risk factors have implicated factors associated with beta-amyloid deposition (Schupf, 2002) and oxidative damage (Lott & Head, 2001). Various risk factors for AD have been identiﬁed for the general population, the most robust being age, family history of dementia, and DS. Mortimer (1997) identiﬁes three sets of risk factors: (1) those related to etiology of the pathogenic process, (2) those related to clinical expression of the process, and (3) those that reﬂect preclinical indicators of the disease. The ﬁrst category includes the main genetic risk factors of family history of dementia, DS, and apolipoprotein E genotype. The second category incorporates factors that impact on clinical presentation among individuals who have pathological lesions. These include risk factors associated with brain reserve capacity (including brain size, premorbid ability/education,

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and head trauma), as well as factors that may protect against AD, including non-steroidal anti-inﬂammatory drugs, cholinergic stimulation, estrogen, and nicotine. The third category incorporates factors that reﬂect prodromal symptoms of AD, including depression and physical and social inactivity. This chapter examines the risk factors for AD in DS. Relevant research is reviewed with comment on the theoretical basis for each putative risk factor. The following risk factors identiﬁed by electronic literature search are considered: age, apolipoprotein E (ApoE) genotype, brain size, ability level and head trauma, and gender and estrogen. In addition, a future direction for research is suggested. It is argued that faulty folate metabolism and B-group vitamin deﬁciency confer increased risk for developing AD in DS. This putative risk factor has yet to be empirically examined in DS.

I.

AGE

Age has been consistently identiﬁed as a risk factor for AD in epidemiological studies of the general population with prevalence and incidence rates rising with increasing age (Jorm et al., 1987). Since the 1980s, a substantial number of studies have examined the prevalence rates of dementia in DS with somewhat fewer focusing on prevalence rates in ID (mixed etiology). Studies of prevalence rates in DS have diVered with respect to study design, and have assessed dementia according to various criteria, in samples that diVer with respect to inclusion criteria, including age and institutionalization. Prevalence estimates vary from 15% to 45% (Prasher, 1994). In addition to providing overall estimates, a subset of studies have also tried to determine age-speciﬁc prevalence (e.g., Holland et al., 1998; Lai & Williams, 1989; Tyrrell et al., 2001; Visser et al., 1997) and incidence rates (Holland et al., 2000; Prasher & Krishnan, 1993) across successive age-bands. A thorough review of prevalence studies conducted prior to 1993 was presented in Zigman et al. (1993). They reviewed retrospective, cross-sectional, and prospective studies, and concluded that prevalence rates of the clinical syndrome are well below the prevalence rates of the neuropathological indicators. Moreover, prevalence rates do increase with age with the increase in risk occurring between 50 and 60 years of age. Discrepancies in estimates across studies were most plausibly attributed to methodological diVerences including selection and diagnostic criteria. The following section highlights selected studies that have examined age as a risk factor for AD in DS that have been published since the Zigman and colleagues (1993) review. The four studies presented in Table I have found very similar age-speciﬁc prevalence estimates for AD in non-institutionalized individuals with DS. A prospective study of prevalence in an institutionalized sample (Visser et al.,

TABLE I PREVALENCE ESTIMATES OF AD

IN

DS Age Brackets

Study

Methodological Considerations

30–39 years

40–49 years

50–59 years

60–69 years

Holland et al. (1998)*

Population-based sample. CAMDEX informant interview of personality, memory, and general cognitive functioning. N ¼ 106, 15.1% with dementia. Medical staV observations of memory, speech and comprehension, self-help skills, personality, and social/vocational skills. N ¼ 201, 13.4% with dementia. Participant and carer interviews assessing personality, memory, confusion, self-care, speech output, incontinence, seizures, and behavioral problems. N ¼ 285, 13.3% with dementia. DSM-IV criteria.

3.4%

10.3%

40%

—

0%

16%

41%

—

2%

9.4%

36.1%

54.5%

1.4%

5.7%

30%

41.7%

Sekijima et al. (1998)

Prasher (1995)

Tyrrell et al. (2001){

CAMDEX ¼ Cambridge Examination for Mental Disorders of the Elderly. * Only two participants in this study were aged over 60 years and neither had AD. { Estimate for 60–69 years group includes all people over 60 years. Prevalence in people over 70 years was 50%.

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1997) produced a similar estimate for individuals in the 40 to 49 years age bracket (11%) and somewhat higher estimates for those age 50 to 59 (66%) and 60 to 69 years (77%). Diagnosis was based on clinical signs, cognitive functioning, and electroencephalographs. During the course of the study, 18% developed dementia, with a mean age of onset of 56 years. Clearly the nature of the sample (institutional vs. community-based) impacts on absolute prevalence estimates. Two studies have examined the incidence rates. Prasher and Krishnan (1993) reviewed case reports of clinical dementia in DS published over a 50-year period from 1940. They report a mean age of onset of 51.7 years with a mean duration of 6 years. When data from two extreme scorers with dementia were excluded, mean onset age became 51.9 years with a mean duration 4.8 years. Most importantly, the incidence of dementia was unimodal, increasing after 40 years of age with a peak in the 51 to 55 years age band. They did not ﬁnd evidence for a linear relationship, arguing instead that incidence rates increase with age but not later than the sixth decade of life. Furthermore, in contrast to ﬁndings for the general population, they found no evidence to suggest that there are two distinct types of dementia (early or late onset) in DS. Holland and colleagues (2000) conducted an 18-month follow-up of the original prevalence study sample described in the preceding text (Holland et al., 1998). Clinical change over time was assessed using a modiﬁed version of the informant interview of the Cambridge Examination for Mental Disorders of the Elderly (CAMDEX) (Roth et al., 1986). AD was assessed using Cambridge Examination for Mental Disorders of the Elderly (CAMDEX) criteria and ICD-10 (WHO, 1992) and DSM-IV (APA, 1994) criteria. Using the former criteria, incidence rates were highest in the 40- to 49-year-old age group whereas using the latter they were highest in the 50- to 59-year-old group. The aim of this Chapter is to highlight risk factors for AD and to this end it is the pattern of relative rather than absolute rates that is telling the story. Clearly prevalence and incidence rates of AD in DS increase with age, as in the general population. No attempt is made here to reconcile the diVerences in actual estimates across studies because they all reveal the same basic agebased pattern. Attention should be drawn, however, to methodological considerations that do impact on the actual estimates. These have been previously highlighted by Zigman and colleagues (1993) and include the type of design utilized, sampling and selection eVects, and diagnostic criteria employed. Indeed, Zigman and colleagues (1995) highlighted the impact that more or less stringent diagnostic criteria have on prevalence estimates. Their calculated age-based prevalence estimates of dementia derived using strictest criteria were 2.3%, 2.7%, 7.3%, and 15.5% for age-bands 31 to 40, 41 to 50, 51 to 60, and 61 to 70 years, respectively. The corresponding estimates using the most lenient criteria were 23.5%, 21.1%, 31.6% and 52.6%, respectively.

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Regardless of the criteria used, the patterns across the studies consistently show an age-related risk of AD with a marked rise in prevalence and incidence occurring during the early 50s. Riedell-Heller and colleagues (2001) report prevalence estimates for dementia of 5%, 16%, 28.5%, 47.9%, and 57.1% for non-disabled adults in age brackets 75 to 79, 80 to 84, 85 to 89, 90 to 94, and >95 years, respectively. Prevalence estimates of dementia in DS appear to show a similar trajectory to that found in the non-disabled population although clearly the age of onset is much younger. Furthermore, incidence rate patterns suggest that there are not two distinct types of dementia (early or late onset) in DS.

II.

APOLIPOPROTEIN E GENOTYPE

There is consensus that genetic factors play a role in the onset of AD. Three chromosomes have been implicated: chromosomes 21 and 14 in early onset, and chromosome 19 in late onset AD. Massart and colleagues (2001) identiﬁed 68 gene polymorphisms that have been implicated in the pathogenisis of AD, the most robust association being with the "4 allele of ApoE located on chromosome 19. ApoE is a lipid transport molecule involved in the regulation of plasma lipoprotein metabolism. It has an aYnity for, and thus binds with, A in neuritic plaques (Strittmatter et al., 1993). The three isoforms of ApoE—E2, E3, and E4—are encoded for by the "2, "3, and "4 alleles, respectively. Although the mechanism by which ApoE genotype inﬂuences risk of AD has not been elucidated, it is thought to modulate the disease process because the alleles have diVerent binding aYnity for betaamyloid, and thereby impact on the rate of amyloid depositon (Polvikoski et al., 1995). Moreover, Mazur-Kolecka and colleagues (2002) found that oxidative stress caused by treatment with Fe2þ ions produced more protein carbonyls in "4/"4 than in "3/"3 carriers, suggesting that reduced antioxidant defense in "4 carriers contributes to beta-amyloidosis. In the general population, possession of one "4 allele or more has been associated with increased rate of cognitive decline in non-demented older adults (Anstey & Christensen, 2000; Small et al., 1998), increased deposition of beta-amyloid (Hyman et al., 1995; Polvikovski et al., 1995), and increased risk and earlier onset of AD (Corder et al., 1993; Katzman et al., 1997; Mayeux et al., 1993). A higher frequency of ApoE "4 has been noted for early onset (van Duijn et al., 1994), late onset (Corder et al., 1993), and familial cases of AD (Hardy et al., 1993). The "2 allele, in contrast, is associated with increased longevity and reduced risk of AD (Corder et al., 1994; Schachter et al., 1994). In the general population, "3 is the most common allele and "2 the least common allele.

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The ﬁnding that the ApoE gene impacts risk, age of onset, and disease progression in the general population has prompted researchers to examine whether it is also an important factor in AD in people with DS, given the increased amyloid burden associated with DS. It is certainly true that AD is not universal in people with DS and that the average age of onset in those who do develop the disease varies widely. Studies to date have included participants across the spectrum of genotypes and have typically not included genotype as a predictor variable. Since the early 1990s, however, a number of studies have been conducted in which the diVerential impact of the ApoE genotype on AD in DS has been explicitly examined. The conclusions reached by these studies are at best tentative because many have insuYcient power due to small sample size to detect an association. Moreover, they diVer with respect to criteria for diagnosis of dementia, and some, but not all, studies control for age. Studies have examined: (1) genotype and allele frequency in DS compared to the general population; (2) genotype and allele frequency in DS with dementia compared to DS without dementia; (3) the impact of genotype on onset age of AD and age of death for individuals with DS; and (4) the relationship of genotype to speciﬁc aspects of cognitive functioning in individuals with DS. A.

Genotype and Allele Frequency in DS

Studies comparing the DS and non-disabled populations typically report no diVerence between groups in genotype distribution or allele frequency; however, there is some evidence showing lower "4 allele frequencies in older adults with DS, consistent with the diVerential mortality risk associated with "4 in the general population (Schachter et al., 1994). Hardy and colleagues (1994) conducted postmortem analyses on 22 individuals with DS. The distribution of allele frequencies for the general and DS populations, respectively, were; "2: 5% and 10%; "3: 85% and 68%; and "4: 10% and 22%. Other studies also report no diVerence in genotype distributions for groups with DS and the general population (Annoni et al., 1997; Del-Bo et al., 1997; Lai et al., 1999; Martins et al., 1995; Prasher et al., 1997; Rubinsztein et al., 1999; van Gool et al., 1995). In contrast, Cosgrave and colleagues (1996) compared genotypes and allele frequencies in 77 women with DS (age over 35 years; 12 of whom had AD, and 182 controls). The frequency of the "4 allele in women with DS was one-half that of the controls. This was subsequently conﬁrmed by Tyrrell and colleagues (1998) who compared control participants to those with DS, including children and adults with and without dementia. There was a lower frequency of the "4 allele in the DS group compared to controls (12.7% and 20.6%, respectively), and in DS

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participants with AD compared to age-matched DS controls (0% and 8.3%, respectively). The "4 allele frequency in newborns with DS is the same as that in the general population, suggesting that results for older adults are the result of selective survival (Holder et al., 1996). Edland and colleagues (1997), however, found little evidence for reduced survival to adulthood of "4 homozygotes with DS suggesting that the impact of "4 occurs predominantly for age-related conditions. Indeed, the "4 allele predisposes to various forms of premature death. This confounding of age and ApoE-related survival may be particularly salient when more severely disabled or institutionalized samples are examined (Wisniewski et al., 1995). The ﬁndings of Cosgrave and colleagues (1996) and Tyrrell and colleagues (1998) are certainly consistent with reports of the relatively lower "4 allele frequency in centenarians in the general population (Schachter et al., 1994). Presumably, the increased mortality risk associated with the "4 allele is manifest at an earlier age in DS. Indeed, Tyrrell and colleagues (1998) suggest that an agerelated reduction in the frequency of the "4 allele in the DS population makes it diYcult to detect an association between ApoE and AD. Clearly, as a result of diVerential survival eVects, age should be controlled in analyses that examine the impact of ApoE genotype on dementia status. That this has not always been the case may account in some part for the discrepant ﬁndings reviewed in the following text. Furthermore, Prasher and colleagues (1997) have warned that discrepant conclusions on the relationship between AD and genotype may occur when prevalence and incidence report studies for AD are compared. They suggest the possibility that "2 carriers may develop a more aggressive form of AD and are thus underrepresented in prevalence studies. B.

Genotype, Allele Frequency, and Dementia in DS

A number of studies have compared ApoE genotype and allele frequencies in demented and non-demented adults with DS. The aim of such comparisons has been to determine whether "4 is associated with increased risk and whether "2 is associated with reduced risk of AD. The relationship has also been the subject of three recent meta-analyses (Deb et al., 2000; Prasher et al., 1997; Rubinsztein et al., 1999). A number of studies report higher "4 frequencies in DS participants with AD (DS-AD). Martins and colleagues (1995) found that in six DS-AD participants, three had at least one "4 allele, whereas only one had an "2 allele. In 17 non-demented participants, 5 were "2 heterozygotes. Sekijima and colleagues (1998) found "4 allele frequencies in 18.8% of DS-AD participants compared to only 4.5% of non-demented adults with DS and 6.7% of control participants. Furthermore, this eVect was more marked when those who developed AD under 50 years of age were

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examined (28.4%). Two studies by Schupf and her coworkers (1996, 1998) have examined genotype and cumulative incidence rates of AD in individuals with DS. Compared to "3 homozygotes, possession of one "4 allele led to either a ﬁve-fold (Schupf et al., 1996) or a four-fold (Schupf et al., 1998) age-adjusted risk of AD Cumulative incidence rates of dementia to age 65 years were 0.74 and 0.45 in those with any "4 genotype compared to the ApoE 3/3 genotype, respectively, in the earlier study, and 0.79 and 0.50, respectively, in the later study. No interaction was found between the ApoE genotype and gender (Schupf et al., 1998). In contrast, Lai and colleagues (1999) found a trend for higher frequency of "4 in demented (18%) versus non-demented adults (13%), although this was not statistically signiﬁcant. However, they did ﬁnd a signiﬁcantly lower frequency of "2 in DS-AD compared to non-demented DS adults (4% and 13%, respectively). The risk ratios, using "3/3 as reference group, were 0.34 for "2/3 (p ¼ 0.04) and 1.44 (not signiﬁcant) for "3/4 and 4/4 combined. Lai and colleagues suggest that the diVerence between their results and those of Schupf and her coworkers may be due to the higher mean age of participants in their study. Although of comparable size, the studies of Schupf and her coworkers assessed younger individuals and consequently had smaller subgroups of demented individuals. Indeed, they suggest that the eVect of the "4 allele in DS may be attenuated by the very high rates of AD in the older age groups. Other studies that also report low rates of AD in individuals with an "2 allele include: Lambert et al. (1996), Roysten et al. (1994), Schupf et al. (1998), and Tyrrell et al. (1998). Not all studies, however, have found diVerences in genotype or allele frequency. van Gool and colleagues (1995) found no diVerence in either "4 or "2 allele frequency in 26 DS participants with AD and 26 DS participants without AD where participants were matched for age, gender, and premorbid ability. Farrer and colleagues (1997) dichotomized adults with DS according to whether they showed no decline or some decline (mild impairment to severe dementia) in cognitive performance measures over ﬁve years. They found no association between "4 allele dosage and onset or progression of cognitive decline. Prasher et al. (1997) report similar ﬁndings for their sample in which gender distribution and level of mental retardation but not age were equivalent. The DS-AD participants (n ¼ 17) were older than non-demented adults with DS (n ¼ 83). Moreover, this result was conﬁrmed by their meta-analysis. Deb and colleagues (2000) also found a nonsigniﬁcant excess of "4 carriers in 24 DS-AD participants compared to 33 non-demented DS adults over 35 years of age. Although they also found a lower frequency of "2 allele in the demented DS participants, the meta-analysis that was subsequently conducted by these researchers showed a higher frequency of "4 but no signiﬁcant reduction in "2. In the third study

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that incorporated a meta-analysis, Rubinsztein and colleagues (1999) found no diVerence in allele or genotype frequency for 20 demented and 25 nondemented individuals with DS. In contrast, their meta-analysis did show an increased risk for AD for "4 carriers compared to "3/3 (odds ratio 2.74) and a reduced risk for "2 carriers (odds ratio 0.37). Table II displays a summary of these meta-analyses. The three metaanalyses report: no eVect of ApoE on AD (Prasher et al., 1997); an increased risk for "4 only (Deb et al., 2000); and an increased risk for "4 as well as a reduced risk for "2 (Rubinsztein et al., 1999). These ﬁndings are clearly the result of the diVerent data sets analysed. Unfortunately, the study by Lai and colleagues (1999) containing the largest sample of DS-AD adults in a single study (n ¼ 57), was not incorporated into any of the meta-analyses. This study found a lower risk associated with "2. The combined meta-analyses and the ﬁndings of Lai and colleagues (1999) suggest that in this population there is a trend for an increased risk associated with "4 and a reduced risk associated with "2. Given the limited number of studies that have examined the impact of the ApoE genotype and the small samples and consequent low power of the studies, there is clearly a need for further research and for future meta-analyses to incorporate all existing datasets.

TABLE II SUMMARY OF META-ANALYSES EXAMINING THE IMPACT OF GENOTYPE ON AD IN DS Meta-Analyses

Studies Included in Analyses Wisniewski et al. (1995) Martins et al. (1995) Royston et al. (1994) van Gool et al. (1995) Schupf et al. (1996) Lambert et al. (1996) Sekijima et al. (1998) Tyrrell et al. (1998) Prasher et al. (1997) Deb et al. (2000) Rubinsztein et al. (1999) Conclusion reached

Prasher et al. (1997)

Deb et al. (2000)

Rubinsztein et al. (1999)

Included Included Included Included Included Included X X Included X X No eVect of ApoE

X Included Included Included Included Included Included Included Included Included X Increased risk for "4 carriers

Included Included Included Included Included X X X X X Included Increased risk for "4, reduced risk for "2

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Genotype, Age of Onset of AD, and Age of Death

Despite suggestive trends, there are insuYcient data available to assess the impact of the ApoE genotype on age of onset of AD and age at death in DS. Typically, studies comparing those who do and do not possess "4 alleles report no diVerence in mean age of onset AD. Mean ages of onset "4 carriers and noncarriers, respectively, are 51 and 53 years (Deb et al., 2000), 44.3 and 47 years (Martins et al., 1995), 45.2 and 47.8 years (Sekijima et al., 1998), and 54.1 and 54.6 years (van Gool et al., 1995). The meta-analysis by Prasher and colleagues (1997) found a nonsigniﬁcant trend for younger onset in those with an "4 allele. Mean age of onset was 52.4, 51.2, and 45.7 years for "2, "3, and "4 carriers, respectively. Two studies have examined cumulative incidence rates for AD by the ApoE genotype (Lai et al., 1999; Schupf et al., 1998). Lai and colleagues (1999) report no diVerence in mean onset age by genotype whereas Schupf and colleagues (1998) found that the presence of an "4 allele was associated with earlier onset. Despite the suggestion that "4 carriers are underrepresented among older groups with DS (Cosgrave et al., 1996; Tyrrell et al., 1998), very little empirical data is available on the impact of the ApoE genotype on age at death. Although Lai and colleagues (1999) found no impact of genotype on age at death, earlier studies were consistent with the view that the "2 allele is associated with increased longevity. Hardy and colleagues (1994) conducted postmortem analyses of 22 individuals with DS. The longest surviving participant was an "2 homozygote (age 76 years), followed by one of two "2 heterozygotes (age 69 years). Possession of an "4 allele did not appear to be associated with earlier death; the mean age at death was 55 years and 54 years for "3 homozygotes and "3/4 heterozygotes, respectively. This trend was also found by Roysten and colleagues (1994) in their retrospective study of case records. They found that "4 heterozygotes were youngest at death (mean age of 57 years), followed by "3 homozygotes (mean age 60 years) and those with at least one "2 allele (mean age 66 years). The longest lived person was an "2 homozygote (age 68 years). The impact of "2 was statistically signiﬁcant; mean age at death of "2 carriers was 66 years compared to 58 years for those without an "2 allele.

D.

Genotype and Aspects of Cognitive Functioning

A number of studies have examined eVects of the ApoE genotype for speciﬁc aspects of cognitive functioning. Schupf and colleagues (1996) found a greater decline in adaptive functioning across four annual assessments for individuals possessing one or more "4 allele regardless of dementia status. Del-Bo and colleagues (1997) examined 106 young people with DS (mean

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age 13.1 years). They obtained full-scale IQ (FSIQ), verbal IQ, (VIQ) and performance IQ (PIQ) scores using Wechsler scales (WPPSI, WISC-R, and WAIS). There was no diVerence between groups with and without an "4 allele on FSIQ, VIQ, or PIQ. They did, however, ﬁnd an inverse correlation between age and FSIQ and PIQ for the subgroup of "4 carriers. Furthermore, two estimates of FSIQ with a test-retest interval of at least four years were compared for 38 participants age over 10 years. Presence of an "4 allele was associated with a faster rate of decline. Alexander and colleagues (1997) examined the impact of the ApoE genotype on 41 non-demented DS adults (age 22 to 61 years). The group was subdivided with those 40 years of age (n ¼ 17) classiﬁed as old and those <40 years (n ¼ 24) as young. Participants were compared on general intellectual function, memory, visuospatial skills, attention, and language ability. Older participants had poorer longterm memory and orientation scores. In contrast, language, attention, and praxis (the ability to perform skilled movements) were relatively preserved with age. High language scores were associated with "2 allele and lower language scores with "3 and "4 alleles. In other words, possession of an "2 allele was associated with higher scores on cognitive skills that are relatively preserved in aging with DS. Overall then, ApoE genotype is a risk factor for the development of AD in DS, as in the general population. Evidence suggests that possession of an "4 allele is associated with an increased risk of AD whereas the "2 allele is associated with a reduced risk of AD. It is interesting to note that the distribution of genotypes in DS is similar to that of the general population. In other words, the increased risk of developing AD pathology in DS is not reﬂected in the genotype distribution. This may mean that the development of clinical features of AD in DS is more sensitive to other risk factors. Alternatively, other risk factors may exacerbate the eVects of genotype in people with DS.

III.

BRAIN RESERVE CAPACITY HYPOTHESIS

In the general population some risk factors are assumed to impact on the clinical presentation of AD because they are related to individual diVerences in brain reserve capacity. This argument is essentially based on a threshold model whereby a person who has high reserve capacity can compensate for changes early in the disease process. The disease must thus progress further before symptoms are noted. Individuals whose reserve capacity is lower as a result of pre-existing neuropathological and functional impairment are more vulnerable to a lesser degree of pathological change (Schoﬁeld,

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1999). Factors assumed to inﬂuence (or reﬂect) brain reserve that have been identiﬁed in the general population include brain size, education, and head trauma (Mortimer, 1997).

A.

Brain Size

There is some evidence that brain size is related to cognitive ability in nondisabled aging adults without dementia (Jorm et al., 1997), although the magnitude of the relationship is not large. More importantly, there is some support for the notion that brain size has an impact on the development of AD in the general population. An autopsy study by Katzman and colleagues (1988), for example, examined a subgroup of nursing home residents (n ¼ 10) who had pathological changes consistent with AD but no cognitive impairment. These individuals had larger brains than control participants and residents with dementia. Furthermore, Schoﬁeld et al. (1995) found larger premorbid brain size, assessed by computerized tomography (CT) of the intracranial area, was associated with a later onset age for AD. Graves and colleagues (1996) found an association between head circumference (a proxy of premorbid brain size) and severity of cognitive impairment in AD after controlling for age and level of education. More recently, Mortimer et al. (2003) examined the relationship between head circumference, educational attainment, and risk of dementia in the Nun Study. Participants with low education and small head circumference had a four-fold increase in risk of dementia after controlling for age and ApoE status. Structural magnetic resonance imaging (MRI) investigations have demonstrated smaller whole brain volumes in DS compared to non-disabled controls (Haier et al., 1995; see Strydom et al., 2002, for review). Furthermore, brain weight has been found to be 30% below normal in DS adults over 30 years of age (Wisniewski et al., 1985). Haier and Colleagues (1995) reported a correlation of 0.65 between FSIQ and brain size assessed using MRI in a sample that included individuals with mild mental retardation and DS (without dementia). No studies could be identiﬁed, however, that examine the relationship between premorbid brain size and either risk of AD or severity of symptoms in adults with DS. To the extent that brain size is a correlate of premorbid ability, it may provide a means of testing the impact of individual diVerences in reserve capacity on development of AD in DS that avoids some of the problems associated with the use of cognitive testing to determine premorbid levels in this group. These include ﬂoor eVects in the tests and the higher prevalence of comorbid psychiatric disorders at more severe levels of ID (Cooper & Prasher, 1998). Although it is acknowledged that both education and brain size are highly correlated with premorbid

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ability level, the association with education level is likely to be more problematic in people with ID than in the general population. Research on the relationship between brain size and AD in DS is warranted and may inform future treatment approaches. Speciﬁcally, optimizing brain growth and development during infancy and childhood could ultimately reduce the risk of AD in adulthood for people with DS.

B.

Ability Level and Education

In the general population there is mounting evidence to suggest that low educational attainment is associated with a higher risk of AD (Katzman, 1993; Stern et al., 1994; Zhang et al., 1990) although this is not unequivocal (Fratiglioni et al., 1991). Educational opportunity and premorbid ability level are clearly correlated variables and determining their relative contributions to AD risk may be complex. Indeed, Fioravanti and Carlone (2001) suggest that the impact of education on the cognitive tests that are used to establish the presence of dementia may lead to a measurement bias whereby undereducated people are overrepresented in dementia groups. Snowden and colleagues (1996) did ﬁnd that estimates of premorbid ability measured by linguistic complexity in early life predicted cognitive functioning in aged nuns such that higher linguistic functioning protected against clinical symptoms of AD in the presence of neuropathological changes. Most of the studies of people with DS have focused on premorbid ability level operationalized as degree of mental retardation according to ICD-10/ DSM-IV criteria. Higher estimates of AD in ID compared to the general population (Cooper, 1997) are consistent with the idea that premorbid ability impacts upon risk of AD. Moreover, prevalence studies typically report higher rates of AD in older adults with DS in institutionalized, compared to communitybased, settings. Attempts to reconcile these ﬁndings have argued that the former contain more adults with lower premorbid ability levels whereas the latter are more likely to contain higher functioning individuals. This argument is certainly consistent with the reserve capacity hypothesis. Attempts to demonstrate that low ability level constitutes a risk factor for AD in DS have not, however, produced conclusive ﬁndings. Two studies have found evidence that premorbid ability is related to cognitive decline and dementia status. Temple and colleagues (2001) assessed 35 adults with DS between 29 and 67 years of age over periods ranging from six months to three years to determine factors associated with AD. Dementia status was assessed using a caregiver report scale in combination with a battery of neuropsychological tests to yield six diagnostic rating categories. Recreational activity, educational level, years of institutionalization, and

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employment information were recorded. Premorbid level of cognitive functioning was determined from clinical records using ordinal scaling with ﬁve functional levels according to ICD-10 criteria. Multiple regression revealed that age and premorbid level of cognitive functioning predicted diagnostic rating score, suggesting that higher functioning individuals were less likely to show decline. Level of education, institutionalization, and employment were not directly associated with decline. However, post-hoc analyses revealed that these variables were all related to premorbid level of cognitive functioning. Oliver and colleagues (1998) examined cognitive proﬁles on a neuropsychological battery over 50 months in a DS sample that excluded those with severe, pre-existing cognitive decline or dementia. Rate of decline was faster in older adults with DS and in those with a greater degree of pre-exisiting decline. Pre-existing decline was assessed using an adaptive behavior measure. Both Temple and colleagues (2001) and Oliver and colleagues (1998) have used a severity rating of cognitive change or dementia rather than a simple dichotomy between presence/absence of dementia. The ﬁndings of Oliver and colleagues (1998) rest on the validity of using an adaptive behavior measure as an index of premorbid ability. Indeed, their results could be interpreted parsimoniously as showing that adaptive behavior and cognitive decline are correlated. In contrast, ﬁve studies ﬁnd no evidence for an association between level of ID and AD. Visser and colleagues (1997) conducted a prospective study (over 5 to 10 years) of institutionalized adults with DS. Dementia was assessed using a symptoms checklist, an adaptive behavior measure, and EEG recordings. Participants were at the more severe end of the cognitive functioning scale according to DSM-IV criteria: 27% had profound, 43% severe, and 30% moderate mental retardation. Level of retardation had no impact on the age at which deterioration occurred. Although restricted range could account in part for the ﬁndings of Visser (1997), some studies employing both institutionalized and community-based samples have also found no eVect of ability level on prevalence of AD (Lai et al., 1999; Schupf et al., 1998; Tyrrell et al., 2001). In the cross-sectional study by Tyrrell and colleagues (2001) ID, deﬁned by IQ or mental age on entry to various ID services in Ireland, was stratiﬁed according to ICD-10 criteria with mild/moderate and severe/profound groups combined. No relationship between ability and prevalence was found. Lai and colleagues (1999) conducted a large-scale, prospective study that included community-based and institutionalized adults. Level of retardation (mild, moderate, severe, profound) was not related to development of dementia after the eVects of gender and ApoE genotype were controlled. Similarly, Schupf and colleagues (1998) showed that level of retardation was

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not an independent risk factor for AD in a reconstructed cohort design. Prasher and colleagues (1997) reviewed case reports and studies on clinical dementia conducted up to 1995 that included suYcient information on severity of ID and dementia status. A total of 86 cases were examined. There was no signiﬁcant diVerence in age of onset of dementia for individuals with moderate (mean 46.9 years) or severe (mean 50.3 years) ID, nor was there an eVect on duration of dementia with mean durations of ﬁve and four years for moderate and severe ID, respectively. Holland and colleagues (1998) conducted a population-based study assessing prevalence of AD, frontal lobe dementia, and Lewy body dementia. Level of premorbid ability (mild/moderate or severe/profound) was not related to prevalence of dementia (combined across all types) or to age of onset of symptoms. There was, however, some evidence that frontal lobe dementia was more common in the more severe group. The authors argued that preexisting abnormalities of brain development inﬂuence the presentation of dementia in DS. The studies reviewed diVer with respect to whether they consider severity ratings of dementia or simply the presence or absence of AD as the dependent variable. Those that consider severity ratings are more likely to show an eVect of premorbid ability. Furthermore, some studies use a restricted range of premorbid ability levels or combine data across ability level categories. In most but not all cases, premorbid levels have been derived from case ﬁles. Furthermore, there are a number of issues to consider when comparing across levels of ability. First, prevalence studies confound diVerential mortality rates across premorbid levels; that is, there is a healthy survivor eVect particularly for less severely disabled individuals. Second, assessment may be problematic when verbal or cognitive measures are used, particularly for people with more severe premorbid impairment. Third, comorbid psychiatric conditions are more common in persons with more severe premorbid ID. Thus, at this stage, the ﬁnding that ability level appears to have little relationship to symptoms of AD should only be tentatively considered. There is clearly a need for large-scale, prospective, incidence studies in which clear diagnostic criteria and a range of valid premorbid measures are used. Moreover, there is a need for increased speciﬁcity in the reserve capacity hypothesis. Although gross measure of brain reserve, such as brain size and premorbid ability level, are informative, attempts to understand the development of AD in DS may be helped by consideration of the relationship between individual diVerences in reserve capacity in speciﬁc brain areas that are known to be compromised in both disorders. For example, early clinical change is more likely in areas of the brain where reserve is already compromised in DS. Holland and colleagues (1998, 2000) argued that pre-existing hypoplasia of the frontal lobes in DS increases vulnerability to neuropathological changes

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so that functions mediated by this area will show early clinical changes. A study of the relation between individual diVerences in premorbid frontal lobe integrity and symptoms of AD would identify whether this aspect of brain reserve constitutes a risk factor for people with DS. It may be possible to increase brain reserve capacity in people with DS by modifying educational practices or utilizing cognitive training. There is some evidence that adults with DS show improved cognitive performance after an Instrumental Enrichment Program (Lifshitz & Rand, 1999). Furthermore, the eVect is found across age groups (20 to 29, 30 to 39, 40 to 49 and over 50 years), and improvement is greater for people with moderate rather than mild retardation. Research that examines the impact of intellectual stimulation on age of onset or severity of symptoms of AD in people with DS is sparse. To the extent that such activity impacts on brain reserve capacity, it may represent a modiﬁable lifestyle factor that can delay or reduce the impact of AD in DS. C.

Head Injury

Studies in the general population indicate that sustaining a head injury earlier in life exacerbates age-related cognitive decline (Corkin et al., 1989) and increases the risk of AD (Plassman et al., 2000; Schoﬁeld et al., 1997), although this is not unequivocal (Nemetz et al., 1999). The EURODEM Risk Factors Research Group provide a pooled relative risk estimate of 1.82 for AD following head trauma (Mortimer et al., 1991). There is some emerging evidence for an association between head trauma and an increased risk of AD for people with ID who do not have DS. Popovitch et al. (1990) found that prevalence of AD was higher in individuals whose mental retardation was due to head trauma. This risk factor has not been systematically studied in people with DS, which is somewhat surprising given that trauma is thought to impact on processes that are already compromised in DS. Speciﬁcally, the increased risk of AD following head injury may be the result of the impact of trauma on redundancy in brain tissue, the increased deposition of beta-amyloid, or the metabolism of oxygen-derived free radicals. The ﬁrst of these implies that the neuronal damage caused by head trauma reduces brain reserve so that less brain pathology can be tolerated before clinical symptoms of dementia are evident (Satz, 1993). With respect to the second factor, there is evidence from the non-disabled population that beta-amyloid deposition occurs in response to head trauma (Roberts et al., 1991). Furthermore, there is an increased risk of this occurring in people carrying one or more "4 allele for apolipoprotein E (Nicoll et al., 1995). Mayeux and colleagues (1995), for example, found a 10-fold increase in risk of AD in people without disabilities carrying an "4 allele following head

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trauma. Clearly, the increased amyloid burden carried by people with DS makes them even more vulnerable to this additional insult. With respect to the third factor, oxygen-derived free radicals, speciﬁcally the superoxide and hydroxyl species, are linked to AD and DS. Oxygenderived free radicals damage cell lipids and proteins, and result in the production of endogenous neurotoxins (Volicer & Crino, 1990). Head trauma increases the formation of oxygen free radicals. Moreover, there is evidence for increased oxygen free radical formation in DS (Ani, 2000; Iannello et al., 1999) with the genetic locus for one of the key enzymes in free radical metabolism (Cu,Zn-superoxide dismutase (SOD-1) (located on chromosome 21. Evidence to suggest that DS is associated with chronic oxidative stress is found in reduced plasma glutathione levels (Pogribna et al., 2001), elevated levels of reactive carbonyls in the brain (Balcz et al., 2001), premature aging, and premature onset of degenerative pathologies including cataracts and autoimmune diseases (Jovanovic et al., 1998). Increased SOD-1 activity is associated with increased glutathione peroxidase activity, and Brugge et al. (1999) found that this activity was signiﬁcantly correlated with memory function in adults with DS between 22 and 51 years of age Furthermore, these authors argue that between-individual variability in SOD-1 activity in DS leads to diVerences in vulnerability to oxidative damage and that this is associated with diVerential risk for AD. Moreover, there is an interaction between processes of oxidative damage and amyloid deposition (Lott & Head, 2001) with oxidative damage leading to increased amyloid deposition. Evidence is emerging that long-term antioxidant supplementation ameliorates complications in AD (Sano et al., 1997) with evidence from in vitro studies suggesting that a similar eVect occurs in DS (Ani et al., 2000; Busciglio & Yankner, 1995). Despite the theoretical argument that people with DS may be more vulnerable to the impact of head injury because of premorbid compromising of brain reserve, increased beta-amyloid deposition, and pre-existing oxidative stress, only one study that included head injury as a predictor of dementia in people with DS could be identiﬁed. Tyrrell and Colleagues (2001) established a prevalence rate of 13% for dementia in an Irish sample with DS, age 35 to 74 years. When demented (n ¼ 38) and non-demented (n ¼ 245) groups were compared, the former were found to be older and more likely to have epilepsy or myoclonus or to have sustained a head injury, deﬁned as loss of consciousness requiring hospitalization. The actual number of people with AD who had sustained a head injury was small (n ¼ 2) and both were ApoE "3 homozygotes. Therefore, no ﬁrm conclusions can be drawn concerning the association between AD and head trauma in DS or the interaction between head trauma and relative risk associated with possession of one or more ApoE "4 alleles in

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DS. There is an urgent need for research on this topic. Given the importance of oxidative damage in DS, head trauma, and AD, research on individual diVerences in susceptibility to oxidative damage in DS is required. Furthermore, there is a need for research on the impact of antioxidants such as vitamin E on cognitive performance in adults with DS both with and without dementia. Antioxidant supplementation is a modiﬁable lifestyle factor that has the potential to reduce or delay the impact of AD in the population with DS.

IV.

GENDER AND ESTROGEN

Women are at increased risk following menopause for a range of chronic conditions including osteoporosis, osteoarthritis, coronary artery disease, breast cancer, AD, and depression (Harlow & Ephross, 1995; Massart et al., 2001). In the general population, prevalence rates of AD are higher in women than in men (Fratiglioni et al., 1991), and there is some evidence for higher incidence rates in women (Fratiglioni et al., 2000; Ott et al., 1998), although this is not unequivocal (Edland et al., 2002). Thus, the increase in risk is found after correcting for greater longevity of women, and the disease, once established, progresses more rapidly in women than in men (GarciaSegura et al., 2001). Menopause is said to have occurred when a women has experienced 12 consecutive months of amenorrhea resulting from reduced ovarian follicular activity in which estrogen levels are insuYcient to stimulate endometrial growth (Greendale et al., 1999). Hormonal markers for menopause include raised levels of follicle stimulating and lutenizing hormones and a marked reduction in estrogen levels. There is mounting clinical evidence to suggest that the chronic health conditions of postmenopausal women are related to changing levels of gonadal hormones, and in particular, to the reduction in estrogen levels (Palacios, 1999). The neuroprotective eVects of estrogen suggest that it may be an important determinant of general cognitive functioning in older women, and reduction in estrogen levels may result in increased risk of AD. Furthermore, estrogen replacement may have therapeutic value in reducing the severity of dementia symptoms. Various neurophysiological and biochemical mechanisms proposed to explain the role of estrogen in maintaining integrity of cognitive functioning have been the subject of recent reviews (Taber et al., 2001; YaVe et al., 1998). Models of the eVect of estrogen have included its impact on the modulation of neurotransmitters, reorganization of synapses, alteration in lipoproteins including modulating the expression of the ApoE gene, and the prevention of cerebral ischemia via enhancement of cerebral blood ﬂow (YaVe et al., 1998). Estrogen maintains cholinergic neurons

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projecting to the hippocampus and cortex (Gibbs & Aggarwal, 1998), it increases cholinergic activity (Goodman et al., 1996), and it interacts with neurotransmitters including dopamine, serotonin, norepinephrine, and acetylcholine (Taber et al., 2001). In addition, estrogen modulates neuronal placticity by acting on the formation of synapses and dendritic spines (Simpkins et al., 1997). It has antioxidant eVects (Niki & Nakano, 1990), and it protects against the formation of beta-amyloid via its role in regulating the metabolism of amyloid precursor protein (JaVe et al., 1994; Petanceska et al, 2000). Variants of the estrogen receptor alpha (ER) gene interact with the ApoE "4 genotype to impact on the risk of AD in women (Brandi et al., 1999; Mattila et al., 2000). Bretsky and Colleagues (1999), for example, used regression and proportional hazard models to show that non´ disabled women with an ApoE "4 allele were more likely to develop AD whereas it did not confer increased risk for men. Payami and Colleagues ´ (1994) report that risk of AD in women with one "4 allele was equal to that ´ of men with two "4 alleles. Similarly, YaVe and colleagues (2000) examined the eVect of estrogen replacement therapy (ERT) on cognitive performance ´ in women with or without the ApoE "4 allele. Women with the allele had a greater adjusted hazard ratio of cognitive impairment and ´ estrogen replacement reduced the risk of cognitive impairment in ApoE " 4 negative women, ´ whereas it had no impact on ApoE "4 positive women. There has been a proliferation of studies on the non-disabled population examining the role of ERT in reducing the risk of dementia, in ameliorating symptoms of dementia, and in reducing cognitive decline in non-demented women (for recent reviews see Le Blanc et al., 2001; Taber et al., 2001; YaVe et al., 1998). There are plausible physiological mechanims via which estrogen may exert an inﬂuence on cognitive processing and there is mounting evidence to suggest that ERT does reduce the risk of developing AD. Furthermore, ERT is associated with less subclinical cortical and central atrophy (Resnick et al., 1998) and with improved functioning in speciﬁc cognitive domains in non-demented, postmenopausal women (Carlson et al., 2001; Le Blanc et al., 2001), although this is not unequivocal (Barrett-Connor & Kritz-Silverstein, 1999; Binder et al., 2001). Evidence for the eYcacy of ERT on disease progression after onset is more equivocal (Taber et al., 2001) with some randomized control trials in women with mild to moderate AD showing no eVect on progression after onset (Henderson et al., 2000; Mulnard et al., 2000) and others showing positive eVects on memory and attention (Asthana et al., 1999, 2001). There has been no systematic examination of the impact of gender and menopausal status on cognitive functioning in DS, although there are a number of reasons to suspect that a reduced level of estrogen might play a role in the development of AD in adults with DS. First, compared to the

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non-disabled population, the rate of ERT is lower in women with ID, and, some hormonal and metabolic functions may be compromised in adults with DS through the use of psychotropic and antiepileptic medication (Walsh, et al., 2001). Second, estrogen impacts on cholinergic functioning (Gibbs & Aggarwal, 1998; Granholm et al., 2002), and a cholinergic deﬁcit is observed in both AD and DS (Mufson et al., 1995). Third, recent studies have suggested that women with DS have lower endogenous estrogen levels because they are younger at onset of menopause. Granholm and colleagues (2002) investigated the impact of ERT on cholinergic cell loss and cognitive decline using a mouse model of DS (mice with segmental trisomy of chromosome 16 represent DS patients). Estrogen supplementation improved learning of a T-maze and increased NGF protein levels in the basal forebrain. The extent to which ERT is eYcacious for women with DS remains an empirical question. The average age at menopause in the non-disabled population is 51 years (Greendale et al., 1999). There is a paucity of research on menopause in women with ID. In the 1990s, researchers became interested in whether early menopause occurred as a symptom of premature aging in DS. Carr and Hollins (1995) examined age distribution and menstrual status of 45 women with DS and 126 women with ID of unspeciﬁed etiology. General trends were found for earlier menopause in women with ID compared to the normal population, and for earlier menopause in DS compared to women with unspeciﬁed ID. Although it was not possible to determine the average age of menopause, no one over 51 years of age in the DS group, and no one over 54 years of age in the ID group, was still menstruating: 69% of women with ID and 87% of those with DS had stopped menstruating by 46 years of age. This trend has been conﬁrmed and extended in recent studies. Schupf et al. (1997) found the age adjusted likelihood of menopause was twice as high in a population-based sample of women with DS compared to those with non-DS ID. They reported median ages at onset of menopause of 47.1 and 49.3 years for DS and ID (non-DS), respectively. Cosgrave and colleagues (1999) reported a mean age of onset of 44.7 years for a sample of Irish women with DS. Consistent with this, a prospective study by Seltzer, Schupf and Wu (2001) used three techniques to determine the distribution at age of menopause. They reported a mean age at menopause of 44.6 years, and median ages of 46.1, 47.1, and 45.8 years, estimated using reconstructed cohort, prospective cohort, and logistic regression methods, respectively. Thus, women with DS experience menopause between four and six years earlier than their non-disabled counterparts, and they are thus exposed to lower levels of endogenous estrogen. Although there is a substantial body of research implicating gender as a risk factor for AD in the general population, the relationship has received

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scant attention in adults with DS. Cooper (1997) conducted a populationbased survey of people with ID over the age of 65 and found higher prevalence rates for dementia in women compared to men, consistent with ﬁndings for the general population. Findings with respect to gender eVects in DS have been more equivocal. A.

Impact of Gender on Cognitive Functioning

Despite a proliferation in research on age-related cognitive changes in DS, very few studies provide a breakdown for gender eVects. Studies examining gender and age-related cognitive functioning in non-demented individuals with DS tend to ﬁnd either that women are at increased risk of decline or that there is no eVect of gender. Burt et al. (1995) found no eVect of gender on change in cognitive, adaptive, and physical indices over a 3 to 4 year period. Similarly, Oliver and colleagues (1998) found that although 80% of those showing cognitive deterioration over time were female as compared to 52.4% of those in the no deterioration group, this diVerence was not statistically signiﬁcant. Hon and colleagues (1998, 1999) have examined general cognitive functioning and memory functioning in a population-based sample of 74 adults with DS (including 10 adults with AD). No gender or gender-byage interactions eVects were found in either domain. In contrast, Patel and colleagues (2001) compared non-demented, premenopausal and postmenopausal women with DS with age-matched men with DS. Cognitive functioning was assessed at baseline and two years later using ﬁve subtests of the Woodcock-Johnson Tests of Cognitive Ability-Revised (long-term memory, short-term memory, auditory processing, visual processing, and comprehension). Compared to age-matched male peers, premenopausal women performed better, and postmenopausal women performed worse, in all cognitive domains. Signiﬁcant age-related declines in cognitive functioning were found for postmenopausal women only. This study provided crosssectional and longitudinal analyses of the eVects of menopause after controlling for confounds of age, level of obesity, and depression. B.

Impact of Gender on AD in DS

Studies on the association between gender and AD in DS have also produced conﬂicting results. Four studies showed no eVect of gender on AD although two of these (Lai & Williams, 1989; Visser et al., 1997) reported nonsigniﬁcant trends for earlier age at onset in women. Visser in colleagues (1997) found symptoms of dementia were equally prevalent in men and women in a prospective study of AD in 307 institutionalized adults with DS over a 5- to 10-year period. Women were only six months younger

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than men at onset of distinctive dementia, and no gender diVerence was found for age of complete dependency. Similarly, Lai and Williams (1989) reported no signiﬁcant diVerence in mean age at onset (55.6 years and 52.6 years for males and females, respectively), and no diVerences in duration of dementia in those who died during the course of their prospective longitudinal study (4.1 and 5.6 years for men and women, respectively). Tyrrell and colleagues (2001) reported no gender diVerence in prevalence rates of dementia in an Irish sample (n ¼ 38 from a sample of 285). Krinsky-McHale and colleagues (2002) prospectively examined changes in explicit memory in early dementia in 85 people with DS. They reported a trend for higher prevalence rates in women, although this was not statistically signiﬁcant and the sample size (n ¼ 14) was small. In contrast, Farrer and colleagues (1997) grouped 41 DS adults age 35 to 62 years according to whether they showed no deterioration (group 1) or some deterioration, ranging from mild impairment to severe demential (group 2), over 50 months of psychometric testing. There was no signiﬁcant diVerence in gender distribution between the two groups although cognitive deterioration over time was greater in males than females. This interpretation is limited by grouping together participants with symptoms ranging from mild cognitive decline to severe dementia. Schupf and colleagues (1998) conducted a cohort analytic study involving 174 adults with DS between 30 and 70 years of age (21 of whom had AD). They reported cumulative incidence rates of AD to age 65 years of 0.79 and 0.28 for men and women, respectively. Men had a three-fold risk of developing AD after controlling for premorbid levels of mental retardation as well as age. Furthermore, they found no interaction between gender and ApoE genotype; in both men and women the "4 allele was associated with higher risk and the "2 allele was associated with lower risk. Schupf and colleagues (1998) argued that the relative protection aVorded to non-disabled men by preservation of estrogen is not available to men with DS. They reported that men and women with DS have elevated levels of follicle stimulating hormone and luteinizing hormone at puberty, that this progresses with age, and that it is more frequent in men. In contrast, ﬁve studies have reported higher rate and/or earlier onset in women compared to men. Prasher and Krishnan (1993) reviewed case reports of clinical dementia published over a 50-year period from 1940. Women had an earlier onset (mean age of 53.6 and 49.8 years for men and women, respectively), whereas duration of dementia did not diVer between the genders (4.5 years and 5.6 years for men and women, respectively). Furthermore, they found that the later the age at onset of dementia, the poorer the prognosis; this was particularly so for women. Raghavan and colleagues (1994) conducted postmortem neuropathological analyses on

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brain tissue from 25 individuals with DS over 40 years of age, 21 of whom had undergone prospective neuropsychiatric assessment. Senile plaques and neuroﬁbrillary tangles were counted in the four neocortical lobes of the right hemisphere. Consistent with the notion that women experience a more severe form of AD, the density of neuroﬁbrillary tangles was higher in women than men, although there was no gender diVerence with respect to the density of senile plaques. Furthermore, all of the women in the sample had clinical evidence of dementia whereas only 54% of the men did. Consistent with Prasher and Krishnan (1993), Raghavan and colleagues (1994) reported earlier onset of dementia in women compared to men (48.8 and 53.6 years, respectively) and no diVerence in duration of dementia. Prasher and Filer (1995) compared behavioral disturbances in people with DS who had (n ¼ 15) or did not have AD (n ¼ 25). They reported a preponderance of females in the group with dementia (males:females ratio ¼ 1:2.8). Similarly, Prasher and Corbett (1993) retrospectively assessed 19 people with DS after death. Eleven met criteria for AD, with a female:male ratio of 7:4. Women had a signiﬁcantly younger age of onset (47.9 and 57.2 years for women and men, respectively). In a prospective study of incidence rates controlling for age and level of disability, Lai and colleagues (1999) found that 46% of the men and 72% of the women in their sample of adults age 35 to 79 years had AD. Women were 1.77 times more likely to develop dementia than men. Risk of AD was thus higher for women prior to age 65 years. By age 65 years, however, cumulative incidence rates were similar. This result is considered reliable because the sample contains the largest number of people with dementia in a single study to date (n ¼ 57). Only one study to date has examined the impact of age at menopause on onset of AD in women with DS (Cosgrave et al., 1999). Despite ﬁnding no signiﬁcant diVerence between age of menopause for women with and without dementia, they found a relationship between age at menopause and age at onset of dementia in the subgroup who had dementia. It is diYcult to draw ﬁrm conclusions from the preceding summary of studies. There appears to be some consensus that there is no gender diVerence in the average duration of dementia (Lai & Williams, 1989; Prasher & Filer, 1995; Raghavan et al., 1994), although Raghavan and colleagues (1994) argued that women experience a more severe form of the disorder. One study (Schupf et al., 1998) reports higher rates of AD in men whereas four studies report higher rates in women (Lai et al., 1999; Prasher & Corbett, 1993; Prasher & Filer, 1995; Raghavan et al., 1994). Similarly, one study reports younger age at onset in men (Schupf et al., 1998); two report nonsigniﬁcant trends for younger onset in women (Lai & Williams, 1989; Visser et al., 1997); and four report signiﬁcantly younger age of onset in women (Lai et al., 1999; Prasher & Corbett, 1993; Prasher & Krishnan,

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1993; Raghavan et al., 1994). In most of the studies, relatively small numbers of people with dementia have been examined, so the power to detect gender diVerences is weak. Moreover, the interpretation of gender diVerences in relative risk is constrained by methodological concerns and by factors that confound prevalence and incidence estimates. Gender diVerences in survival inﬂuence prevalence estimates and retrospective analyses. Higher prevalence estimates for women may reﬂect their increased longevity. Alternately, retrospective studies in which postmortem analyses are conducted (such as Prasher & Corbett (1993) and Raghavan et al. (1994)) may overestimate prevalence rates for women. If women develop a more severe form of the disease, they are more likely to have died at a younger age and thus are more likely to be included in the sample. Incidence rates give a more accurate picture of gender eVects. Unfortunately, the two studies that estimated incidence rates (Lai et al., 1999; Schupf et al., 1998) have reported ﬁndings discrepant with each other Schupf (2002) has argued that in both studies the gender eVect occurs mainly at younger ´ ages and it may be masked by the strong eVect of the ApoE "4 allele. Indeed, the Study by Lai and colleagues (1999) found very little diVerence between men and women until age 45 years, after which women had a greater risk than men until age 65 years. In the paper by Schupf and colleagues (1998), however, the gender diVerence (favoring men) is apparent after age 55 years. Lai and colleagues consider two possible explanations to account for the discrepancy between their ﬁndings and those of Schupf and colleagues. First, the studies used diVerent designs. Lai and colleagues used a prospective design involving the inclusion of incidence cases. Schupf and colleagues used a reconstructed cohort design with prevalence cases, which Lai and colleagues argued may have singled out women who developed AD early and who had died. Second, they suggested that the behavioral manifestations of early dementia in men with DS may be more disturbed than in women leading to underreporting of incidences of AD in women. Schupf and colleagues however, argued against diVerential referral on the basis of similar rates of behavioral disturbance in men and women (3.3% and 3.1%, respectively). Although the results of studies on the whole tend to suggest that women are at greater risk and have earlier onset of AD, ﬁndings are equivocal. It is interesting to note that the interval of time between menopause and onset of AD is much shorter in DS than in the non-disabled population. This might suggest that reduced estrogen has a greater impact in DS or that it exacerbates other risk factors. Clearly, there is a great deal of work to be done on gender and menopause eVect on cognition and AD in DS. First, large-scale, longitudinal, population-based studies are needed to clarify gender diVerences in incidence rates. Studies need to take menopausal status into account. Second, interactions between gender and apolipoprotein genotype for

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risk and severity of AD need to be explicated. Third, gender diVerences in patterns of cognitive functioning in demented and non-demented, aging adults with DS need to be examined. Fourth, there is a pressing need for randomized, placebo-controlled studies of ERT in DS women.

V.

FOLATE METABOLISM, B-GROUP VITAMINS, AND RISK OF AD IN DS: A HYPOTHESIS IN SEARCH OF DATA

There is a growing body of work linking nutritional factors, including vitamin status, to age-related changes in cognitive functioning (Bryan, 2003). The B-group vitamins—folate (folic acid or folacin), B-6 (pyridoxine), and B-12 (cobalamin)—have an impact on central nervous system (CNS) integrity because of the role they play in cellular one-carbon metabolism pathways. The two main functions of the cellular one-carbon metabolism pathways are deoxyribonucleic acid (DNA) synthesis and repair and normal cellular methylation reactions. These pathways can be compromised either as a direct result of inadequate folate or B-12 intake or the overexpression of genes coding for speciﬁc enzymes. The integrity of the cellular one-carbon metabolism pathway can compromise neurological functioning via two mechanisms. First, there can be an acute eVect via the inhibition of methylation reactions. The methionine synthase reaction regenerates methionine from homocysteine and generates tetrahydrofolate (THF) for DNA/ribonucleic acid (RNA) nucleotide synthesis. Methionine, in turn, is the precursor for the synthesis of S-adenosylmethionine (SAM), the main intracellular methyl donor for a range of CNS reactions (Calvaresi & Bryan, 2001). Second, there can be an indirect eVect whereby low folate, B-6, and B-12 status is associated with increased risk of vascular disease (Hankey & Eikelboom, 1999). Alterations in folate metabolism have been linked to a range of health conditions including neural tube defects, cardiovascular disease, cancer, aVective disorders, and dementia (Lucock, 2000). The relationship between B-group vitamins and neurological functioning has been examined in nondemented older adults, in older adults with mild cognitive decline and in adults with AD (Bryan, 2003; Calvaresi & Bryan, 2001; Selhub et al., 2000). There is some evidence that the incidence of AD is associated with reduced levels of serum folate and B-12 (Karnaze & Carmel, 1987; Selhub et al., 2000; Sommer & Wolkowitz, 1988), with folate status associated with severity of the atrophy (Snowdon et al., 2000), and B-12 levels related to cognitive status (Levitt & Karlinsky, 1992). Furthermore, there is some evidence that supplementation with B-group vitamins results in improved cognitive performance scores for individuals in the early (Martin et al., 1992) but not more severe stages of cognitive decline (Teunisse et al., 1996).

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There are compelling reasons to believe that deﬁciencies in B-group vitamins and alterations in folate-dependent pathways are linked to increased risk of AD in DS. It is argued that triplication in DS leads to altered folatedependent pathways. Furthermore, in the presence of altered pathways, individual diVerences in B vitamin status due to nutritional intake and absorption result in increased vulnerability to cognitive decline and risk of AD. Recent research has linked both genetic and nutritional deﬁciencies that aVect folate metabolism, and thus the cellular one-carbon pathways, to maternal risk of DS (Hobbs et al., 2000; James et al., 1999; O’Leary et al., 2002; Rosenblatt, 1999). Polymorphisms in both the methylenetetrahydrofolate reductase gene (MTHFR) and the methionine synthase reductase gene (MTRR) are associated with abnormal folate metabolism and DNA hypomethylation, and these are signiﬁcant maternal risk factors for DS. Importantly, in the current context, altered folate metabolism also occurs in the oVspring with DS (Al-Gazali et al., 2001). In DS, functional folate deﬁciency is secondary to overexpression of the gene coding for the enzyme cystathionine -synthase (CBS), located on chromosome 21 (Pogribna et al., 2001). Triplication in DS leads to increased CBS activity resulting in the removal of homocysteine from the homocysteine-methionine cycle and a slowing of DNA and SAM synthesis. A decrease in SAM also impacts on the endogenous formation of choline. Individuals with DS thus have a susceptibility to DNA damage via folate-dependent pathways that increases the risk of AD. Indeed, Regland and Gottfries (1992) have argued that slowed synthesis of DNA and methionine is a common pathogenic mechanism in DS, AD, and dementia in acquired immunodeﬁciency syndrome (AIDS). In addition, various complications of DS including congenital heart disease, thyroid disorders, and celiac disease interfere with adequate nutrition and cause malabsorption of vitamins (Pueschel, 1999). Hestnes and colleagues (1991) found lower levels of B-12 in institutionalized individuals with DS compared to controls with ID. Moreover, individuals with DS may have a functional folate deﬁciency even if they have normal plasma levels of folate and B-12. Pogribna and colleagues (2001) compared lymphocyte DNA methylation status in children with DS (n ¼ 42) and their siblings (n ¼ 36). Plasma levels of homocysteine, methionine, S-adenosylhomecysteine, and SAM were lower in the children with DS. In DS then, individual diVerences in B-group vitamin status are likely to compound the level of risk associated with altered folate-dependent pathways. That there is a link between folate metabolism, B-group vitamin status, and cognitive decline and risk of AD in DS is a theoretically intriguing but, as yet, empirically untested proposition. Research on this topic could inform the use of B-group vitamin supplements to prevent and treat symptoms of cognitive decline and AD in aging adults with DS.

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CONCLUSIONS

This review has considered various risk factors for AD in DS. Consideration was given to age, ApoE genotype, brain reserve capacity, premorbid ability level, head trauma, gender, estrogen, folate metabolism, and B-group vitamins. Other factors that have not been considered here include family history of AD, the protective eVects of non-steroidal anti-inﬂammatory medication and nicotine, and the risk associated with depression. The interpretation of studies is constrained by a number of limitations. First, studies have diVered with respect to diagnostic and inclusion criteria. Age has been controlled in some but not all studies, and some studies excluded participants with AD. Second, many studies have small sample size and thus insuYcient power to detect eVects. There is a need for large scale collaborative studies using prospective designs to assess risk factors, including randomized control trials to test the eYcacy of treatments that are assumed to reduce risk of AD, including ERT, antioxidants, and B-group vitamins. Third, various confounding factors need to be considered. For example, diVerential mortality rates occur across ApoE genotype and there is a diVerential prevalence of comorbid psychiatric illness across premorbid ability levels. With respect to the risk factors considered, ﬁndings were generally consistent with those for the general population in that strongest support was found for the impact of age and ApoE genotype. Prevalence and incidence rates of AD increase with age in DS with the increase in risk occurring during the early 50s. The "4 allele was associated with increased risk of AD and early mortality, whereas the "2 allele was associated with decreased risk and increased longevity. There was moderate support for gender as a risk factor. There was an increased risk in women in general and for menopausal women, more speciﬁcally. Although estrogen was found to impact on cholinergic function and cognitive performance in a mouse model of DS, there are no studies that have examined the eYcacy of ERT in women with DS. The reserve capacity hypothesis, although theoretically sound, did not receive strong support. In part, this reﬂects a paucity of studies on factors such as head injury and brain size. It also reﬂects the relatively low eVect size of some of these factors and the lack of speciﬁcity of the hypothesis. It was suggested that individual diVerences in reserve capacity should be formulated in terms of the speciﬁc brain regions compromised in DS. It was also suggested that there may be individual diVerences in vulnerability to oxidative damage in DS. Finally, it was argued that altered folate metabolism and B-group vitamin status constitute a risk factor for AD. Although intriguing, this proposition has yet to be tested. Some of the research considered suggests that there may be risk factors for AD that are potentially modiﬁable.

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Cognitive reserve capacity and the role of supplements and nutritional factors have not been systematically examined in DS. If it is the case that they can be shown to both have an impact and be modiﬁable, then there is the potential that research can inform treatment approaches that may delay or reduce the risk of onset of AD in individuals with DS.

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Precursors of Mild Mental Retardation in Children with Adolescent Mothers JOHN G. BORKOWSKI, CHRISTINE WILLARD NORIA, JENNIFER BURKE LEFEVER, DEBORAH A. KEOGH, AND THOMAS L. WHITMAN DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF NOTRE DAME NOTRE DAME, INDIANA

JULIE L. LOUNDS WAISMAN CENTER UNIVERSITY OF WISCONSIN-MADISON MADISON, WISCONSIN

KERI WEED DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF SOUTH CAROLINA, AIKEN AIKEN, SOUTH CAROLINA

The Notre Dame Adolescent Parenting Project, begun in the late 1980s, was one of the ﬁrst National Institute of Health-supported research projects to prospectively study the onset and development of mild mental retardation and learning disabilities across time. The project followed high-risk teenage mothers and their children through age 10, assessing them prenatally, at birth, at 6 months, and at 1, 3, 5, 8, and 10 years of age. Our theoretical model and initial ﬁndings were reported in an earlier volume of this book (Borkowski et al., 1992), and comprehensive data through the ﬁrst ﬁve years of childrens’ lives were recently published (Whitman et al., 2001). INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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At the project’s outset, we chose to study a high-risk sample—teenage mothers—because the data sets of Broman (1981) and Furstenburg et al. (1987) had identiﬁed an elevated risk for mild mental retardation and/or children’s adjustment problems in this population, even though the majority of mothers moved satisfactorily into adulthood. The rates of developmental delay in these longitudinal projects, three to four times higher than for children born to adult mothers, were not surprising given the characteristics of most of the adolescent mothers: low educational attainment, depression, low IQ, poor social supports, histories of abuse and/or neglect, and a general lack of readiness to parent (Whitman et al., 2001). The long-term social consequences of parenthood for adolescent mothers with limited education often include problems of underemployment, restricted lifetime earnings, and harsh parenting (Russell, 1980)—factors that typically have negative consequences for a child’s development, especially as they enter their ﬁrst formal schooling, often in Head Start programs. In addition, adolescence, as a unique stage of development, often brings its own problems including: a view of the self as egocentric and unstable; inexperience in handling life experiences and crises; poor decision-making and social problem-solving skills; and stressful relationships with partner, family, and friends (Borkowski & Rellinger, 2001). In this chapter, we will present additional data that focuses on development during middle childhood for children born to adolescent mothers in the late 1980s and early 1990s. A prospective analysis of children’s development enabled us to understand the eVects of early parenting, in combination with other maternal personal, social, and emotional factors, on the emergence of mental retardation and other developmental delays. We were particularly interested in the processes through which parenting aVects child development and the impact of parenting styles (e.g., insensitive or punitive practices), children’s attachment, and self-regulation on socioemotional development and early academic success and failure. This chapter is organized as follows: (1) We brieﬂy describe the Notre Dame Adolescent Parenting Project and then summarize major developmental patterns through age 5. (2) Next, we present maternal and child data related to the emergence of ‘‘early signs’’ of mild mental retardation and learning disabilities, tracing children’s developmental trajectories for intelligence, language, adaptive behaviors, and adjustment for the entire sample as well as for children who at age 10 showed delays in intelligence and adaptation. (3) We present data on the role of parenting in helping to explain developmental delays, emphasizing new ﬁndings on the interrelationships between maternal and child developmental trajectories. (4) Finally, we oVer three interrelated explanations regarding factors that might inﬂuence children’s developmental delays: disorganized attachment, failures to teach and model self-regulation skills, and neglectful-abusive parenting.

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The Notre Dame Adolescent Parenting Project: Sample and Measurement Scheme

The characteristics of the sample of adolescent mothers in our project permit meaningful generalizations to most teen mothers in the U.S., since, in many respects, they mirror the demographic characteristics of the population. For instance, the average age of the mothers at the time of childbirth was 17.1 years, 9% were married, and about 20% were from small towns or rural areas. The mothers had completed, on the average, 10.5 years of school at the time of the prenatal assessment. Their average IQ was 87, with 8.9% having IQs <70, and few having IQs >100. The sample was 62.5% African American, 33.2% European American, and 4.3% Hispanic American. At birth, most infants (91%) had weights <2500 g; APGAR scores were within normal limits, and the average six-month Bayley IQ (mental scale) was 102. However, comparative analyses revealed diVerences at six months of age in observed responsivity, activity, and mood between the infants of adolescent and low-risk adult mothers (Whitman et al., 2001). The low-risk adult mothers had an average age of 25 at childbirth. Their years of education averaged 13.29 and the sample had an estimated IQ of 91. Ethnic composition was 76% European American and 21% African American. What is interesting here is that much like the Milwaukee (Garber, 1988) and Abcederian (Ramey et al., 2002) projects, infants in the Notre Dame Adolescent Parenting Project appeared developmentally normal and indistinguishable from infants of adult mothers, whereas the teen mothers themselves were reliably diVerent from adult mothers on almost all of the dimensions we assessed such as cognitive readiness to parent, IQ, socioemotional adjustment, and social support (Borkowski et al., 2002). Despite the generally positive proﬁle of early infant development, developmental problems began to emerge by the end of the ﬁrst year of life. Our attempts to understand a variety of developmental delays in children with teenage mothers has been guided by a conceptual model that suggests how at-risk, young mothers inﬂuence their children’s social, emotional, and cognitive development. Before discussing speciﬁc childhood delays, this model will be described in detail. The model serves as a conceptual framework for assessing the numerous personal, social, and contextual factors that often combine to inﬂuence the development of infants and children in poverty. Many of the projects presented in the chapter have their origins in our model of adolescent parenting.

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Our model of adolescent parenting emphasizes variables that inﬂuence parenting beliefs and practices (Borkowski et al., 1992). The current version of our model is presented in Figure 1 and represents a revision of the Whitman et al. (2001) original model. Six major constructs are central to understanding parenting and childrearing in at-risk mothers. These constructs include maternal adjustment, child characteristics, and social support—all proposed in the Belsky (1984) model of adult parenting—along with four constructs unique to at-risk mothers: cognitive readiness to parent, learning ability, substance abuse, and past history of domestic violence, abuse, and/or neglect. For simplicity, we have embedded substance abuse and past history of abuse-neglect and violence in a single construct; in fact, they are often causally related with childhood abuse/neglect leading to adolescent substance abuse. It should be noted that the addition of substance abuse and history of maltreatment to our model is consistent with Belsky’s (1984) earlier model of parenting which contained a ‘‘developmental history’’ construct. Although the model in Figure 1 describes numerous direct and indirect inﬂuences on early parenting behaviors, the most important relationships

FIG. 1. A revised conceptual model of teenage parenting.

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can be summarized as follows: to parent eVectively, an at-risk teen mother must be cognitively and emotionally prepared. Her cognitive readiness is related to her socioemotional status (e.g., personal adjustment, history of abuse or neglect, dependency on drugs or alcohol) as well as her social supports and learning ability. These maternal characteristics inﬂuence cognitive readiness to parent and determine, directly or indirectly, the nature and quality of parenting practices, including insensitive parenting and child maltreatment. In addition, a mother’s capacity to deal emotionally with the stresses associated with the parenting role depends on whether her child displays challenging characteristics (e.g., a diYcult temperament or insecure attachment) that can further complicate her parenting and coping resources. By the end of the ﬁrst year of life and during subsequent years, the model postulates that the quality of children’s cognitive (e.g., attention, intelligence, and language) and socioemotional (e.g., attachment, adjustment, and adaptive behavior) development are related to the combined inﬂuence of the factors represented in Figure 1; with cognitive readiness to parent (i.e., a mother’s knowledge of child development, attitudes about parenting, and ‘‘endorsed’’ style of parenting) serving an important mediational role in explaining variability in the quality of parenting, including inconsistent and neglectful parenting. In turn, parenting practices inﬂuence subsequent child development in multiple domains, such as language development, personal adjustment, preschool success, and achievement during the early elementary school years. In the remainder of this Chapter, we will use the model as a conceptual framework from which to understand the emergence of various developmental delays in children with teenage mothers. In the next Section, we will summarize children’s delays in intelligence, adjustment, adaptation, and achievement that we have observed during infancy and early childhood. C.

Early Onset of Developmental Delays

During the ﬁrst 5 years of life, we observed a cascading set of developmental delays that began with insecure attachment and culminated in a general lack of school readiness. The most notable delays we observed were in the domains of attachment, intelligence, language, adjustment, and adaptation. 1. ATTACHMENT

The ﬁrst problematic developmental outcome involved a disruption in the relationship between mothers and their children: a majority of infants showed disorganized (41%) or other patterns of insecure attachment (22%) at one year of age; only 37% of children were classiﬁed as securely attached in contrast to the expected 70% level. The proportion of securely attached

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infants was even lower than that typically observed in low socio-economic status (SES) samples (Vaughn et al., 1979); moreover, the frequency of disorganized attachments was approximately 10% higher than in other studies with children of adolescent parents (Spieker & Bensley, 1994; Ward & Carlson, 1995). We believe that over the past 40 years social environments have changed radically, with each passing decade placing children entrenched in poverty at greater risk for insecure attachment, in part because of the increased incidence of neglectful parenting. 2. INTELLIGENCE, LANGUAGE, AND ACHIEVEMENT

When children reached three and ﬁve years of age, there was additional evidence of emerging developmental problems in four important domains: (1) intellectual-linguistic, (2) socioemotional, (3) adaptive behavior, and (4) pre-academic skills. A large percentage performed in the borderline and mentally retarded ranges of intellectual functioning: 45% at 3 years and 26% at 5 years, with only a small percentage scoring in the above-average category. Even more troublesome, many children showed serious signs of delayed language development and visual motor integration problems; approximately 80% were at or below the 10th percentile on the Peabody Picture Vocabulary Test-Revised (PPVT-R) at both 3 and 5 years of age, while 57% were in this same range at 5 years of age on the Developmental Test of Visual Motor Integration. Academically, 50% and 34% of 5-year-old children were at or below the 10th percentile on the pre-math and pre-reading portions of the Peabody Individual Achievement Test (PIAT), respectively. 3. ADJUSTMENT AND ADAPTATION

With respect to personal adjustment, a high percentage of children showed either internalizing problems (37% at 3 years and 24% at ﬁve years) and/or externalizing problems (35% at 3 years and 14% at 5 years). Children also displayed adaptive behavior deﬁciencies: By age 5, average scores on the Vineland Adaptive Behavior Scales—which assessed communication, daily living, socialization, and motor skills—had fallen to one standard deviation below the population mean. Most importantly, children of adolescent mothers generally did not meet age-appropriate expectations for communication or daily living skills (Whitman et al., 2001), behaviors which were expected to improve as a result of participation in Head Start programs. In fact, however, 30% of the eligible children in our sample (almost all children were eligible) never enrolled in Head Start, and 80% of those who did enroll attended infrequently or irregularly. In short, it seems likely that participation in Head Start had no appreciable eVects on children’s development because high-risk teenage mothers in our sample either failed or were unable

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to utilize available preschool programs on a consistent basis. It is not surprising to ﬁnd that school-related problems emerged by the 2nd grade.

II.

A.

THE EMERGENCE OF MILD MENTAL RETARDATION AND LEARNING DISABILITIES

Undiagnosed Mild Mental Retardation and Learning Disabilities

In this section, we will describe data that suggest the presence of a variety of major achievement-related delays among the children in the Notre Dame Adolescent Parenting Project once they entered elementary school. At 8 years when most of the children were in the 2nd grade, 12.6% had repeated a grade. The majority were in regular education classrooms (93.5%); 4.3% attended special education classes and the remaining 2.2% had been placed in alternative educational arrangements, such as resource rooms for a few hours per week or regular education classrooms with more one-on-one instruction. Although these data indicated that the vast majority of children were in regular education classrooms, it should be noted that 39% had been referred by a teacher for special services. Based on data for intelligence, standardized achievement, and adaptive behavior, we grouped children into one of four diagnostic categories: (1) those performing at least at an average level in school; (2) those with low achievement; (3) those with learning disabilities; and (4) those with mild mental retardation. Children were considered average in their school performance if their scaled scores for the PPVT-R, PIAT-R total reading, and PIAT-R total math were all 85; conversely, low achievement was deﬁned as having a score <85 on one or more of these achievement measures. Students with learning disabilities were identiﬁed by calculating an achievementaptitude discrepancy of 18 or more points (using math or total reading scores from the PIAT-R, as an index of achievement), after accounting for regression towards the mean. Finally, mild mental retardation was deﬁned as having an IQ <75 and adaptive behavior deﬁcits in two or more subscales of the Vineland Adaptive Behavior Scales. Figure 2 contains the percentages of children in the various achievementor IQ-related categories: 26.6% had average school performance in the 2nd grade; 34.0% exhibited low achievement; 24.5% of children showed evidence of learning disabilities; and 14.9% were classiﬁed as mildly mentally retarded. Thus, nearly 75% of the children in this study exhibited school-related problems as early as the 2nd grade; however, of these children with academic problems only 51.5% had been referred for special services. In the

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FIG. 2. Incidence of achievement-related problems in the 2nd grade.

district where the majority of these children were attending school, the reported overall incidences of learning disabilities and mild mental retardation were 4.0% and 2.6%, respectively (Fig. 2). Our data suggest that a disproportionate percentage of children who will eventually be identiﬁed as learning disabled or mentally retarded will be the children of adolescent mothers. B.

Developmental Trajectories for Intelligence and Adaptive Behavior

We turn now to the issue of how children vary in their development of intelligence and adaptive behaviors—the dual criteria for diagnosing mental retardation—over the ﬁrst 10 years of life. We noted that at age 3, 31% of children had IQs 75 and 6% had adaptive behavior scores 75; in contrast, at 10 years, 19% had IQ scores 75 and 40% had adaptive behavior scores 75. As can be seen in Figures 3 and 4, IQ signiﬁcantly increased over time (0.9 points per year) and adaptive behavior decreased (2.2 points per year). Despite the overall increase in IQ scores for the full sample, children who had low IQs at age 3 also tended to have low IQs at age 10 (Fig. 3). In contrast, adaptive behavior composite scores declined for the full sample; however, those children with the lowest adaptive behavior scores at age 10 showed the most rapid declines between ages 3 and 10 (Fig. 4). What is interesting are the diVerential directions of change for IQ and adaptive

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FIG. 3. Intelligence trajectories from 3 to 10 years of age.

FIG. 4. Adaptive behavior trajectories from 3 to 10 years of age.

behavior and the contrasting developmental trajectories for the lowest scoring children when compared with children in the full sample. Hierarchical Linear Modeling (Bryk & Raudenbush, 1992) was used to examine the intercepts and trajectories of IQ and adaptive behavior over the

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7-year period (ages 3 to 10) as a function of a variety of predictor variables. Maternal depression at age 3 predicted children’s IQ scores at age 10, with higher levels of maternal depression associated with lower levels of children’s intelligence. When changes in children’s intelligence were considered, prenatal maternal IQ and the quality of maternal interactions predicted the slopes of these trajectories: children who had intelligence trajectories that declined the most were parented by mothers with lower prenatal intelligence and had the least optimal interactions with their children as observed in a laboratory setting. Relatedly, prenatal maternal IQ, the quality of maternal interactions, and child abuse potential predicted adaptive behavior at age 10, with more intelligent, less abusive, and more responsive mothers having children with higher adaptive behavior skills. None of these variables, however, predicted the trajectories of change in adaptive behaviors. Interestingly, maternal child abuse potential, at ages 3 and 5, mediated the eVects of prenatal maternal IQ on children’s adaptive behavior scores at age 10: mothers who had lower IQs were more likely to be rigid and unhappy— the major components of child abuse potential—and their children were more likely to have lower levels of adaptive behavior. These relationships represent an example of how a biologically based characteristic (maternal IQ) may be linked to a behavioral outcome (children’s adaptive behavior) through environmentally based mediators, such as maternal adjustment or parenting style.

III. A.

THE IMPORTANCE OF EARLY PARENTING

The Timing of Verbal Encouragement and Responsivity

In the Notre Dame Adolescent Parenting Project, we hypothesized that problematic parenting among teenage mothers would adversely aVect the cognitive, adaptive, and socioemotional development of their children. In order to better understand the relationships between parenting and early child development, we observed and recorded adolescent mothers interacting with their children in toy play situations when the children were 6 months, 1, 3, and 5 years of age. When infants were 6 months old, mothers were instructed to try to get their infants to reach for, hold and squeeze, or shake each of three toys (a squeeze toy, a rattle, and an infant’s key ring). The 1-year interactive episode was less structured: mother and child played on the ﬂoor, surrounded by a variety of age-appropriate toys; they were given 5 minutes to play ‘‘like they normally do at home.’’ Play periods at 3 and 5 years were similar: mothers and children sat at a small table, and were given a simple puzzle, nesting toy, and shape-sorter to play with for 5

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minutes. All episodes were videotaped through a one-way mirror for later coding of parenting (Borkowski et al., 2002; Whitman et al., 2001). At each age, observers rated items reﬂective of verbal encouragement (general talkativeness, contingent praise, and positiveness) and responsiveness (ﬂexibility, over/understimulation, and aVectional match). Since verbal encouragement and responsiveness were moderately correlated, the six items comprising the two factors were summed to form an overall measure of parenting quality. CoeYcient alphas, based on the intercorrelations of the six items, ranged from 0.87 to 0.90 across the four assessment periods. Parenting skills were found to undergo signiﬁcant changes during the early years. For adolescent mothers, these changes may have been due to growth in their cognitive and emotional maturity, changes in their child, or their parenting experiences. Four patterns of parental changes were observed:

1. High levels of verbal encouragement and responsiveness, which were sustained as infants became toddlers. 2. Initially high levels of verbal encouragement and responsiveness, which declined over time; mothers in this category were seemingly unable to cope with the growing demands of an active, mobile toddler. 3. Low early levels of verbal encouragement and responsiveness, but improvements over time; perhaps these teens were cognitively or emotionally unprepared for parenting but gradually acquired useful parenting skills. 4. Consistently low levels of verbal encouragement or responsiveness across time. More positive developmental outcomes, such as higher intelligence and better receptive vocabulary, occurred when mothers demonstrated high levels of verbal encouragement and responsiveness at some point during the 5-year period. It did not matter whether positive parenting practices occurred early, late, or consistently across time. Moreover, children whose mothers used verbal encouragement or responsiveness, either in infancy or early childhood, scored signiﬁcantly higher on premath skills at age 5. Internalizing, but not externalizing, problems were also related to parenting: children who received high levels of verbal encouragement and responsiveness across time had signiﬁcantly fewer internalizing problems than other children. Next, regression analyses were used to evaluate the relationship between early parenting practices at 6 months of age and later development. For each of the child outcomes that showed a relationship with parenting, 6-month measures of maternal interactions were included in the regression equations

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after controlling for the eVects of 3-year parenting behaviors and maternal intelligence: parenting early in life accounted for signiﬁcant variations in 5-year intelligence scores, with better parenting associated with higher scores. Similarly, the quality of maternal interactions at 6 months of age explained signiﬁcant variations in children’s communication skills as well as internalizing problems (i.e., depression) at age 5, with higher quality associated with better communication skills and fewer internalizing problems. In contrast, early parenting behaviors failed to account for additional variance, above and beyond that explained by 3-year parenting behaviors, in children’s premath and receptive vocabulary scores. In summary, the timing and quality of interactions between adolescent mothers and their children were associated with positive outcomes in three domains: (1) intellectual, (2) adaptive, and (3) socioemotional. This set of ﬁndings suggest the unique importance of the quality of early childrearing behavior. Mothers who were responsive to their infants at 6 months and who exhibited consistent verbal encouragement, had children who were more intelligent, were better communicators, and had fewer internalizing symptoms. These results remained even after controlling for maternal intelligence, and even when responsiveness and verbal encouragement decreased over time. B.

Interrelating Developmental Trajectories for Mothers and Children

Another approach to understanding the role of parenting is to examine linkages between maternal and child development over time. In traditional developmental research, a single measure is often used to predict the variability in a measure of development obtained at a later point in time or changes in development. For example, Ramey and Ramey (1992) found that maternal IQ predicted changes in children’s IQ during early childhood. Similarly, maternal adjustment has been used to predict behavioral outcomes as well as changes in the children’s socioemotional development (Burke et al., 2000; Spieker et al., 1999). Few studies, however, have observed how changes in a mother’s personal adjustment are related to changes in their children’s development using developmental trajectories to provide information about the nature of change and its correlates. Because of the longitudinal, repeated-measures design of the Notre Dame Adolescent Parenting Project, we are in the unique position to observe interrelationships between developmental trajectories for both teenage mothers and their children during early and middle childhood. For the purposes of this analysis, 160 mother-child dyads were selected from the larger project because they participated in at least three of the

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assessments that occurred when the children were 3, 5, 8, and 10 years of age. At each time point, mothers completed questionnaires concerning their own self-esteem and anxiety as well as their children’s behavioral problems and adaptive behaviors. Both maternal and child IQs were also assessed during each measurement period. Group trajectories were plotted for mothers and children on each socioemotional and intellectual measure using hierarchical linear modeling (HLM) (Bryk & Raudenbush, 1992). Examination of the group trajectories revealed that mothers improved over time in their socioemotional adjustment, with mothers reporting lower levels of anxiety and higher levels of selfesteem over time. The rate of change in both trajectories was signiﬁcantly diVerent from 0, with a rate of approximately one-half point per year. Although the rate of change in maternal intelligence was also signiﬁcantly diVerent from 0, a rate change of 1/5 of 1 point per year indicates a very stable construct. Children’s intelligence improved with an average change of approximately 1/2 point per year. Although children displayed decreasing levels of behavioral problems (as measured by the Child Behavior Checklist), this was accompanied by increasing adaptive behavior problems (Vineland) between 3 to 10 years. In order to establish an association between the developmental trajectories of mothers and children, we used multiple regression analyses to predict changes in children’s behavior based on changes in maternal self-esteem, anxiety, and intelligence. These three predictors explained 6% of the variance in changes in children’s behavior problems, F(3, 155) ¼ 3.16, p ¼ 0.03, with changes in self-esteem playing a signiﬁcant role, ¼ 0.20, p ¼ 0.03: as maternal self-esteem increased over time, reports of behavior problems decreased. Although the association between maternal adjustment and children’s behavior problems has widespread support in the research literature using static measures to predict change (Spieker et al., 1999), our results suggest that changes in maternal adjustment also predict changes in children’s adjustment. Next, multiple regression analyses were used to predict the rate of change in children’s adaptive behavior scores, with changes in maternal anxiety, self-esteem, and intelligence again explaining a signiﬁcant portion of the variance, R2 ¼ 0.07, F(3, 156) ¼ 3.79, p ¼ 0.01. Finally, changes in children’s intelligence were entered into a multiple regression analysis with the same three maternal predictors—anxiety, esteem, and intelligence. Of the variation in the children’s changes in intellectual functioning, 6% was predicted by changes in maternal socioemotional status and intelligence F(3, 155) ¼ 3.22; p ¼ 0.03. Maternal anxiety played a signiﬁcant role, with growth in the children’s intelligence related to decreases in maternal anxiety ( ¼ 0.25, p < 0.01).

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This pattern of results suggests the value of evaluating the eVects of changes in maternal adjustment and anxiety over time on children’s cognitive and socioemotional development. Such an approach could be useful in understanding the emergence of mental retardation and psychopathology in high-risk populations as well as providing insights into possible prevention strategies. For example, the early treatment of maternal adjustment problems, over a period of years, may prevent the emergence of both behavioral and socioemotional problems in children. IV.

PATHWAYS TO DEVELOPMENTAL DELAYS

We believe that an interrelated set of complex developmental pathways lead to the high incidence of mild mental retardation and learning disabilities in children with adolescent mothers. These paths often begin with poverty and its correlates—particularly, immature, inconsistent, and inadequate parenting—and adversely aVect children’s attachment security and the development of socioemotional and cognitive self-regulation. In turn, diminished regulation capabilities lead to low levels of intelligence, poor adaptive behavior skills, and early school achievement and adjustment problems. We believe that children’s developmental delays may be especially aVected by their experience of neglectful and/or abusive parenting during early childhood. In the next section, a model of attachment and self-regulation will be presented that helps to explain the emergence of mild retardation and low achievement in children with teen mothers. We will conclude the section with a consideration of how neglect and abuse may negatively inﬂuence the development of attachment and regulation, leading to additional problems in both depression and aggression. A.

A Model of Attachment and Self-Regulation: Relationships to Responsive Parenting, Attachment, Language, and Achievement

1. A MODEL OF SELF-REGULATION

Figure 5 presents a general model describing factors that inﬂuence attachment, as well as its cognitive-social consequences, and how self-regulation mediates the eVects of attachment on children’s cognitive and behavioral adjustment skills. On the left side of the ﬁgure are the general contextual and caregiver inﬂuences on infant attachment. Most prominent is the parenting role played by the child’s primary caregivers who are often, but not exclusively, the mother and grandmother. Other qualities of the infant’s

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FIG. 5. A model of the causes and consequences of attachment: direct and indirect inﬂuence on self-regulation, intelligence, and adaptation.

immediate caregiving environment are also assumed to be pivotal in the development of attachment security, particularly maternal characteristics such as attachment history and psychological stability (Colin, 1991). In general, caretaker characteristics are likely associated with contextual factors, such as the availability of instrumental and emotional social supports from family and friends as well as the quality of neighborhoods (Borkowski et al., 1992; Nath et al., 1991). The interaction of these antecedent macro- and micro-level variables is known to have important causative eVects on infant attachment (Colin, 1991). In contrast, the consequences of attachment on intelligence is not as obvious. Although there is little solid evidence pointing to a deﬁnitive, direct relationship between attachment security and the emergence of intelligence (Lamb et al., 1985), we believe that self-regulation is the missing link in the chain of events that ﬂow from infant attachment to childhood intelligence and social-emotional maturity to academic achievement. Self-regulation is a complex construct involving metacognitive, motivational, and behavioral processes used by children to promote educational attainment (Zimmerman, 1996). This perspective assumes that academic success depends on constructive eVorts by students to understand their own experiences—a cognitive process—in order to optimize their academic performance through eVort—a motivational process. The latter involves goal setting, self-eYcacy, and attributional beliefs whereas the former involves strategic-based learning necessary for problem solving. Self-regulated

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students are motivated to learn, set realistic academic goals, choose eVective strategies, and monitor their progress (Martinez-Pons, 1996), which allows them to activate and sustain cognitive processes and motivational dispositions that help them achieve their educational goals. Self-regulated learners have higher levels of strategy use, greater awareness of the eVectiveness of their strategies, and higher levels of self-eYcacy (Borkowski et al., 2000; Schunk & Zimmerman, 1997; Zimmerman, 1996). For these aspects of cognitive control to be utilized with regularity in classroom settings, children must develop more rudimentary regulation skills (e.g., inhibition and eVortful control) during early childhood. Parents foster the development of self-regulation in their children through modeling, encouragement, facilitation, and rewarding of self-regulated behaviors (Martinez-Pons, 1996). Grolnik and Ryan (1989) investigated how parents inﬂuence children’s school performance and adjustment, particularly in the domains of self-regulation and school competence. They found that high levels of parental support for autonomy were related to eVective selfregulation and low levels of acting out: children of parents who provided environments that facilitated learning and encouraged autonomy had higher academic achievement, with children’s self-regulatory abilities serving as the mediator between parenting and achievement (Grolnick & Ryan, 1989; Martinez-Pons, 1996). Thus, early in children’s cognitive development, modeling and imitation serve as important social inﬂuences (Zimmerman, 1996), with children acquiring new skills through: (1) observing learning strategies, (2) imitating the performance associated with those strategies, (3) self-controlled practice of the newly acquired strategies, and (4) adapting and self-regulating strategies to ﬁt immediate goals. These processes begin socially, that is, through interactions with competent adults (Zimmerman, 1998), and later become self-directed (Schunk & Zimmerman, 1997). Inspired by the insightful ideas of Main (1991), we have begun to consider whether, and how, insecure attachment might delay the emergence of selfregulation, eventually producing deﬁcits in intelligence and academic achievement. We do not believe that attachment is a suYcient construct that, in isolation, accounts for higher-levels of cognition, and other complex components of intelligence. Rather, it may be one of several salient organismic variables (including attentional ﬂexibility) that inﬂuence the formation of self-regulation and, interestingly, indirectly determine the quality of environments in which control and monitoring skills are modeled and taught by parents, caregivers, and teachers. Simply put, the emergence of selfregulation is inﬂuenced by attachment, both directly and indirectly (Moss & St.-Laurent, 2001), with resulting consequences for intelligence, adaptive behavior, and, ultimately, academic achievement (Borkowski & Dukewich, 1996).

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Attachment security is directly associated with both attentional ﬂexibility and early emotional regulation: the securely attached child who explores the environment and who controls emotions in the face of stress has the basic prerequisites for learning how to perform tasks, how to be organized, and how to respond with deliberation to obstacles and frustration encountered during more complex learning challenges. Indirectly, securely attached children help create their own enriched environments that foster the growth of self-regulation. These stimulating environments encourage exploration, innovation, and the emergence of creativity (Moss & St.-Laurent, 2001). Prompted in part by the skills and dispositions of the securely attached child, an enriched environment will likely be characterized by more stimulating learning activities and by more challenging interactions and expectations from others, which help to facilitate self-regulation and intellectual development. In the next section, we will present data on the potential relationship between several constructs in the model (Fig. 5), such as attachment, intelligence, adaptation, and regulation, with the aim of showing how insecure attachment is associated with mild mental retardation. B.

Disorganized Attachment in Children of Adolescent Mothers

Infant attachment to a primary caregiver is believed to be related to the prior quality of caretaker-child interactions, with securely attached infants using the parent as a base from which to explore and learn from their environments. When distressed, these infants are able to seek comfort and be calmed by their attachment ﬁgure (Ainsworth et al., 1978). Most importantly, secure attachment is associated with not only earlier but later quality parenting as well as child outcomes. For example, securely attached children elicit responses from both parents and educators that often result in successful academic and cognitive development (van IJzendoorn et al., 1995). In contrast, infants who display disorganized attachment appear to possess no coherent mechanism for coping with stress and communicating their needs to the mothers. For example, in the ‘strange situation’ assessment these infants blend contradictory features of several strategies (such as strong proximity-seeking followed by strong avoidance) or appear dazed and disoriented upon reunion with the caretaker (Carlson et al., 1989). A disorganized style of attachment appears to place children at risk for developmental problems in multiple domains (Vondra & Barnett, 1999). For example, Speltz et al. (1990) have shown that disorganized attachment is predictive of the development of behavior problems in the early school years. Moreover, disorganized attachment has been associated with

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problems in academic self-esteem and school performance (Moss & St-Laurent, 1999). van IJzendoorn and van Vleit-Visser (1988) found a relationship between IQ and attachment, with securely attached children possessing higher IQs. It may be that the decreased activity and enthusiasm found in children with disorganized attachment results in less exploration, less interaction with parents, and eventually lower overall cognitive performance as compared with securely attached children. Borkowski and Dukewich (1996) have suggested that insecurely attached children—especially those classiﬁed as disorganized—may evoke less stimulation and metacognitive instruction from their caregivers, resulting in lower levels of self-regulation. From this perspective, disorganized attachment can lead to behavior problems in school and substandard academic performance because of failures in social, emotional, and cognitive self-regulation. We recently used our dataset to examine the role of disorganized attachment as a risk factor leading to mild mental retardation in the children with adolescent mothers (Lounds et al., 2001). First, the occurrence of disorganized attachment and its stability were examined to determine if disorganized attachment among infants and children was as prevalent as suggested by the extant literature. Subsequently, children were divided into stable-secure and stable-insecure disorganized subgroups (at ages 1 and 5) in order to evaluate relationships between attachment status and children’s development at age 8, by comparing self-regulation, adaptation, and intelligence in disorganized versus secure children. Three hypotheses were examined: (1) children of adolescent mothers will have elevated rates of disorganized attachment at 1 and 5 years of age, as well as lower stability in their attachment status; (2) stable-disorganized attachment will be associated with deﬁcits in cognitive self-regulation, intelligence, and adaptive behaviors in the children at 8 years of age relative to the children who were securely attached during both infancy and early childhood; and (3) attachment status will be associated with a variety of maternal characteristics (e.g., punitive parenting styles) and developmental outcomes associated with mild mental retardation, with children’s cognitive self-regulation serving as a mediating variable between attachment and intelligence and adaptive behavior. 1. ATTACHMENT CLASSIFICATIONS AND THEIR STABILITY BETWEEN AGES 1 AND 5

In order to determine attachment status and its stability across time, attachment was measured at 1 and 5 years of age. At age 1, the majority of children were classiﬁed as disorganized (43%), whereas 24% were insecure; only 32% were securely attached. When these children reached 5 years of

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age, the incidence of secure attachment increased to 49% and insecure attachment to 39%; only 12% of the sample remained disorganized. Consistent with the literature on attachment stability, 44% of the children exhibited stable attachment between 1 and 5 years; most who were secure at 1 year remained so (77%), whereas almost one-half of the children (47%) who were insecure at 1 year became secure. The majority of the children who were disorganized at 1 year became insecure at 5 years (52%), 14% remained disorganized, and approximately 33% became securely attached. 2. DEVELOPMENTAL DIFFERENCES BETWEEN SECURE AND DISORGANIZED CHILDREN

We were able to classify 36 children as secure; they showed secure attachment to their mothers at two separate time points (ages 1 and 5 years). Children whom we classiﬁed as disorganized-insecure (N ¼ 29) expressed disorganized attachment to the mother at one of the two time points, and avoidant, withdrawn, or disorganized insecure attachment at the other. These children had not formed a secure attachment bond at either time, as measured by the ‘strange situation’ paradigm. We refer to this subgroup as disorganized-insecure. Analysis of variance was used to test for diVerences in the characteristics of the secure and disorganized-insecure subgroups when the children were 8 years old, speciﬁcally the two behavioral components needed for a diagnosis of mild mental retardation (IQ and adaptation) and a potential mediating variable (cognitive self-regulation) that might help explain the attachmentmild mental retardation relationship. Means and standard deviations for each of these variables as a function of group membership are presented in Table I.

TABLE I MEANS AND STANDARD DEVIATIONS FOR IQ, REGULATION, AND ADAPTATION AT AGE 8 AS A FUNCTION OF DISORGANIZED AND SECURE ATTACHMENT SUBGROUPS Secure Attachment n ¼ 36

Disorganized Attachment n ¼ 29

Child Outcomes

M

SD

M

SD

IQ Cognitive regulation Adaptive behavior

90.1 32.7 80.3

17.0 8.5 8.4

82.9 28.4 76.7

12.2 6.8 7.4

M ¼ mean; SD ¼ standard deviation.

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Disorganized-insecure children had lower IQs and lower levels of cognitive regulation than securely attached children, F(1, 63) ¼ 4.18 and 4.69, respectively, p < 0.05. In order to assess whether the IQ deﬁcit at 8 years was a function of disorganized attachment or simply a continuation of pre-existing sample diVerences, group-related IQ diVerences were contrasted at 6 months (D ¼ 6.75), 3 years (D ¼ 4.70), and 5 years (D ¼ 1.66). No signiﬁcant diVerences in IQ emerged prior to 8 years of age. Finally, disorganized-insecure children had a marginally signiﬁcant deﬁcit in adaptive behaviors at age 8 when compared with securely attached children, F(1, 63) ¼ 3.28, p ¼ 0.08. 3. MATERNAL CHARACTERISTICS, PARENTING, AND ATTACHMENT: PREDICTING CHILD OUTCOMES

Maternal and parenting factors were entered into a series of regression equations in order to reveal the portion of variance in attachment classiﬁcations accounted for by each variable. Together, maternal IQ, parenting style, behavior problems, mother-child interactions, and child abuse potential accounted for 23% of the variance in attachment. Individually, maternal behavior problems and punitive parenting styles were associated with signiﬁcant amounts of variance in attachment status, F(1, 63) ¼ 5.55 and 5.13, respectively, p < 0.05. It should be noted that maternal intelligence, when entered into this regression equation, did not account for a signiﬁcant amount of the variance in attachment classiﬁcation, suggesting the importance of social-environmental factors as antecedents of attachment. 4. COGNITIVE REGULATION AS A MEDIATING MECHANISM

Next, we tested whether a mediational model could account for how cognitive regulation inﬂuenced children’s intelligence and adaptive behaviors. This hypothesis was originally suggested by Borkowski and Dukewich (1996) to explain how attachment might lead to delays in intelligence and adaptive behavior via self-regulation; the model was discussed earlier in this chapter and is presented in Figure 5. The three criteria for a mediational relationship, as proposed by Baron and Kenny (1986) were met for the dependent variable of children’s intelligence: Relationships between attachment and cognitive regulation, attachment and child IQ, and cognitive regulation and child IQ were all signiﬁcant. The results of the mediational analysis can be found in Figure 6. The most important relationships centered on change in the attachment-IQ relationship. Before cognitive regulation was entered into the model, the relationship between attachment and children’s intelligence had a beta-weight of 0.23 (p < 0.05). After cognitive regulation was entered into the model as a

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FIG. 6. Cognitive regulation as a mediator of the attachment-intelligence relationship. The initial path between attachment status and children’s intelligence is indicated by the betaweight on top of the line connecting these variables, whereas the beta-weight after cognitive regulation was entered as a mediator is indicated by the value directly under this path. *p < 0.05; z p < 0.001.

mediator, the relationship between attachment and children’s intelligence became nonsigniﬁcant, with a beta-weight of 0.12. Furthermore, adding cognitive regulation into the model as a mediating variable increased the variance of children’s intelligence accounted for by the model from 8%, F(1, 63) ¼ 4.18, p < 0.05, to 25%, F(1, 63) ¼ 10.55, p < 0.001. In contrast to its role in explaining the attachment-IQ relationship, cognitive regulation did not mediate the relationship between attachment and adaptive behavior. Moss and St.-Laurent (1999) and Borkowski and Dukewich (1996) have suggested that attachment inﬂuences self-regulation which, in turn, aVects the development of intelligence, cognition, and adaptive behaviors. Attachment may indirectly aVect the emergence of self-regulation by restricting the kinds of cognitive instruction that children receive at home and in preschool settings. From this perspective, diVerences in the quality of cognitive instruction lead to diVerences in self-regulation and determine both adaptive behaviors and intelligence and later academic achievement. The results of this study are, in general, consistent with this model. However, since we failed to ﬁnd a cognitive self-regulation–adaptive behavior relationship, it may be that a diVerent kind of regulation—namely, socioemotional regulation—is the underlying causal mechanism though which attachment aVects the social side of children’s adaptation.

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5. IDIOGRAPHIC ANALYSES

Disorganized-insecure children were at greater risk for a possible diagnosis of mild mental retardation than those who were securely attached: 35% of disorganized-insecure children had IQ scores <75 in contrast to 19% of securely attached children. Furthermore, 48% of disorganized-insecure children (as opposed to 33% of secure children) had adaptive behavior scores <75. In combination, 18% of disorganized-insecure children (versus 8% of securely attached children) had both IQ and adaptive behavior scores <75. Thus, children with adolescent mothers who were disorganized were more than two times as likely to have intellectual and adaptive behavior scores suYcient for a diagnosis of mild mental retardation by age 8 than children who were securely attached. Obviously, the percentage of children who met these criteria in both the disorganized and secure subgroups was considerably above the expected level of mild mental retardation in the general population (around 3.5%). We now turn to the important issue of self-regulation, which we hypothesize is a major problem for children with teenage mothers. C.

Self-Regulation, Achievement, and Adolescent Parenting

Self-regulatory skills can be seen in thoughtful task analysis, wise choices about tactical and strategic approaches, active processing of performance feedback, appropriate strategic revision, problem reformulation, and/or the recognition of a correct solution—all hallmarks of intelligence. In this way, what we know and how we learn are associated with the quality of our selfregulatory processes. In addition, self-regulation is necessary for achieving emotional and social maturity. In fact, emotional regulation likely precedes, and is a prerequisite for, the emergence of cognitive self-regulation. 1. SELF-REGULATION IN CHILDREN WITH TEEN AND LOW EDUCATION ADULT MOTHERS

A major factor that may not only explain intellectual development but also many school-related problems in at-risk children is their mothers’ failure to model and teach self-regulation early in life. In order for parents to assist their children in learning self-regulatory skills, the parents themselves need to know how to regulate their own behaviors (i.e., to possess selfcontrol). Because mothers are, in large part, responsible for teaching their children self-regulatory skills, success will be more likely if they have personal histories of successful self-regulated learning. Unfortunately, many teenage and low education adult mothers have not developed mature forms of cognitive and emotional self-regulation themselves. From an academic perspective, they are often not self-motivated; their study skills are

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frequently unplanned and disorganized; their time management skills are not well developed; their self-monitoring is not systematic; and they often fail to seek help when needed (Whitman et al., 2001); that is, they lack the cognitive and motivational processes necessary to be successful self-regulators. Because at-risk teenage mothers are unaware of the importance and nature of eVective self-regulation, it is diYcult, if not impossible, for them to teach similar skills to their children. For these reasons, their children often enter preschool and Head Start lacking the self-regulatory processes necessary for success. We suspect that future research will reveal that a major characteristic of teenage and adult parents with low educational attainment is their inability to promote cognitive, emotional, and social self-regulation in their children. This assumption underlies our recommendation, presented at the conclusion of this Chapter, for the development of highly speciﬁc child-oriented parent training intervention programs. That is, the inability to model self-regulation is a major problem with most at-risk parents and should be a key focus of future intervention eVorts. We believe that appropriate instruction and modeling by parents and caregivers become the crucial ‘‘ﬁrst steps’’ in the emergence of eVective and consistent forms of children’s self-regulation. In the next section, we will present data showing the importance of self-regulation for academic achievement and the likely failure of teen mothers to teach their children regulation skills early in life. 2. SELF-REGULATION, PARENTING, AND DEVELOPMENTAL DELAYS

Willard Noria et al. (under review) have analyzed the importance of early maternal and child characteristics thought to be important in school success—including adolescent parenting practices, maternal depression, anxiety, self-esteem, child temperament, and early child adjustment—on a range of subjective (grades) and objective (standardized tests) educational outcomes. In addition, a potential cognitive mechanism that could mediate between early maternal and child characteristics and school success, achievement, and classroom adjustment—self-regulation—was explored. Maternal and child characteristics were measured at four time points: prenatally, 6 months, 3 years, and 5 years after the birth of the child. Measures of self-regulation, academic performance, and classroom behavior were gathered at age 8. Wherever possible, aggregation across multiple measurement points were used to obtain the most stable estimates of each construct (Rushton et al., 1983). For instance, maternal reports 3 and 5 years after each child’s birth were averaged to create a stable measurement of early maternal depression. In addition, composite scores were created from the aggregated scores, including a maternal adjustment composite—consisting of depression, trait anxiety, and self-esteem—and a parenting composite—indexed by child

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abuse potential, the quality of mother-child interactional patterns, and cognitive readiness for parenting (knowledge, attitudes, and style). Early child characteristics included measures of temperament and behavioral adjustment. Self-regulation was assessed through teacher reports about cognitive self-regulation using the Teacher-Child Rating Scale (Hightower et al., 1989). Landy et al. (1998) have used this scale to measure self-regulation in children, and several studies have demonstrated convergent validity with measures of cognitive self-control (Cowen et al., 1993, 1994; Magnus et al., 1999; Pianta et al., 1999). Finally, children’s academic performance was evaluated through grades, teacher reports about classroom behavior, and standardized test scores in reading and math. We hypothesized that early maternal and child characteristics would signiﬁcantly predict school functioning at 8 years of age, speciﬁcally reading and math achievement, grades, and teacher perceptions of classroom adjustment. Satisfactory maternal and child adaptive behaviors were expected to relate to better school functioning. In addition, we hypothesized that students’ ability to self-regulate their own behaviors would be associated with school success in reading and math achievement, grades, and teacher-perceived behavioral adjustment, with self-regulation serving as a mediator between early mother-child characteristics and later school functioning. When early parenting, maternal and child adjustment, and self-regulation were used to simultaneously predict academic achievement, 30.4% of the variance was accounted for; self-regulation explained a signiﬁcant portion of unique variance in achievement, 21% ( ¼ 0.48, p < 0.01), suggesting that children who were more skilled in cognitive self-regulation had higher levels of achievement. Parenting approached signiﬁcance when race and mothers’ prenatal SES were controlled, uniquely accounting for only 3% of the variance in achievement ( ¼ 0.25, p ¼ 0.067). When race and SES were not controlled, parenting accounted for 4% of unique variance ( ¼ 0.21, p < 0.05); mothers who exhibited more optimal parenting practices had children with higher levels of achievement (Willard Noria et al., under review). When classroom adjustment was examined as the dependent variable using the same predictors from the previous model, 47.8% of the total variance was accounted for by the model; self-regulation and early child adjustment both contributed a unique proportion of variance, accounting for 40.2% and 3.3%, respectively ( ¼ 0.66, p < 0.01, and ¼ 0.23, p < 0.05). Children more skilled in regulation and children with better early adjustment experienced fewer behavioral problems in school. Contrary to our hypotheses, there were no signiﬁcant relationships among three early potential antecedents (parenting, maternal adjustment, and child adjustment) of children’s later self-regulation. Thus, a model testing self-regulation

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as a mediator between early characteristics and school outcomes could not be evaluated (Baron & Kenny, 1986). Although self-regulation did not mediate the eVects of parenting characteristics on school outcomes, the results indicated direct relationships between maternal as well as child characteristics and school functioning. Parenting was shown to be an important inﬂuence on children’s achievement in the 2nd grade. It appears that teen mothers with children who were successful in school were more likely to have helped them prepare for school entry. Previous research has found a similar pattern of results: parents who are supportive of their children’s development tend to have children who achieve in school (Brody & Flor, 1997; Brody et al., 1994; Dubow & Ippolito, 1994; Martinez-Pons, 1996; Zellman & Waterman, 1998). Relatedly, children’s early adjustment was the only early personal characteristic related to later classroom adjustment; children with lower levels of externalization at ages 3 and 5 were more likely to be appropriate in their classroom behaviors (Willard Noria et al., under review). Given the lack of a relationship between important maternal characteristics (including parenting) and children’s self-regulation, it may be the case that adolescent mothers generally do not teach and model self-regulatory skills in the same way as adult mothers (and fathers). If adolescent mothers are themselves poor regulators, they are in a poor position to teach regulation to their children. The research by Brody and Flor (1997) on single-parent families has found that mothers who are less ﬁnancially secure have lower self-esteem and provide less predictable and structured learning environments, resulting in lower self-regulatory abilities in their children. The additional demands on adolescent mothers—due to their oV-time transition to parenthood, in conjunction with the absence of a stable partner—often leave them with limited psychological resources to advance their children’s development of self-regulation. We suggest that home environments created by teen mothers do not provide adequate structure and stimulation for their children to practice or improve upon the regulatory skills they hopefully acquire at school. The teaching of regulation is likely a missing or ‘‘neglected’’ component of adolescent parenting. In the ﬁnal section of the chapter, we will address the issues of child neglect and abuse among teenage mothers in greater depth. D.

Neglect, Abuse, and Regulation

Our data revealed that children raised by adolescent mothers are at risk for a variety of developmental problems including deﬁcits in intellectual ability, delays in receptive language, immature adaptive behaviors, socioemotional maladjustment, and academic achievement problems. Abused children

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show many of these same developmental diYculties (Lynch & Roberts, 1982). For instance, HoVman-Plotkin and Twentyman (1984) found that the average IQ of abused children was approximately 20 points lower than for non-abused children. Other researchers have found that by age 9, the reading skills of abused children were severely delayed (Oates et al., 1984). Abused children frequently lack the skills necessary for school success; often, they are impulsive, unable to organize their behavior, and have lower cognitive functioning (Barth, 1998). Neglected children—who typically have low cognitive abilities, attentional problems, diYculties in understanding their assigned work, and high levels of anxiety, depression, and aggression—sometimes fare even worse in school (Barth, 1998). Although cognitive and language deﬁcits have been noted in abused and neglected children, problems in behavioral and emotional regulation are generally the critical indicators of maltreatment. Frequently, behavioral problems include an impaired ability to inhibit aggressive impulses and an outpouring of physical aggression with peers and adults (Wolfe, 1987). Egeland and Sroufe (1981) found that maltreated children, as young as 2 years of age, showed more anger, aggression, frustration, and non-compliance when interacting with their mothers than children who were not maltreated. In clinical contexts, abused children—especially boys—have more conduct disorders than is typically observed in the general population (National Research Council, 1993). Abused children are also more likely than non-abused children to be socially withdrawn, depressed, and display feelings of helplessness (Wolfe, 1987). Based on data from our adolescent parent sample, we found that children whose mothers reported more neglectful behaviors were more likely to have externalizing problems (Lounds et al., in preparation). One explanation for the similarities between the children of adolescent parents and abuse-neglected children is that teenage parents are at greater risk for engaging in abusive or neglectful parenting practices than adult parents. Bolton (1990) reported that although 20% of all children are born to adolescent mothers, the proportion of abused children raised by adolescent mothers is estimated to be between 35% and 50%. In a study of adolescent parenting practices, de Lissovoy (1973) found that adolescent parents were more likely than older parents to use physically punitive techniques for gaining child compliance. Furthermore, Connelly and Strauss (1992) showed that the age of the mother at the birth of her ﬁrst child signiﬁcantly predicted the occurrence of child maltreatment—even when income, race, education, number of children, and age of the child were controlled. Finally, Dukewich and Borkowski (1996) have suggested that teen mothers who were less cognitively prepared for parenting and who showed an early preference for using punishment as a childrearing technique were at greater risk for abusing their children.

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Dukewich et al. (1999) found that maternal potential for abuse was signiﬁcantly related to developmental delays in children of adolescent mothers: higher abuse potential predicted lower Stanford Binet IQ scores, poor receptive language skills, lower levels of adaptive behaviors (e.g., social skills, communication, living skills, and motor coordination), and higher internalizing and externalizing problems. In addition, a unidirectional inﬂuence was identiﬁed for some of these relationships, suggesting that abuse potential impacted children’s intelligence and adaptive behavior, but that the reverse did not hold. We hypothesize that abuse and neglect negatively impact children’s development by hindering the emergence of cognitive and emotional self-regulation, thus providing an additional, often interactive, pathway for explaining developmental delays in children with teen mothers. The source of maternal abuse and neglect is often rooted in the teen’s own history of experiencing abuse, neglect, and harsh parenting; these relationships are an integral part of our revised model of adolescent parenting as presented in Figure 1.

V.

SUMMARY AND RECOMMENDATIONS

The Notre Dame Adolescent Parenting Project has revealed major developmental delays in most ﬁrst-born children of adolescent mothers. The delays began with insecure attachment and ended with immature selfregulation and poor academic achievement, with language, adjustment, and adaptation problems often developing between 3 and 8 years of age. The children typically experienced poor parenting early in their lives and encountered intermittent or prolonged maternal neglect and/or abuse. A major reason for this sequence of inconsistent, inadequate, or inappropriate parenting by adolescent mothers is that they were not cognitively prepared for the complex parenting task as they began that journey. They held misguided, often negative, attitudes about the role of parents in advancing child development, displayed limited knowledge of child development, and endorsed harsh styles of parenting. Our data also revealed that the complex and multifaceted socioemotional needs of teen mothers inﬂuenced their children’s development. The ﬁnding that positive changes in maternal adjustment (e.g., improving self-esteem and reducing anxiety) were related to positive changes in the children’s development suggests that maternal socioemotional adjustment should be a main focus in intervention/prevention programs. By providing a mother with a sense of personal stability and competence in order for her to develop the parenting skills, a more secure relationship with her child will be enhanced. From this base, she will be more likely to stimulate cognitive and

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emotional development and teach self-regulation skills through modeling as well as direct instruction. EVective intervention programs for teen mothers and other at-risk parents should be made available during pregnancy or shortly after delivery in order to counter the devastating eVects of inadequate parenting on children’s development that we have repeatedly observed in the Notre Dame Adolescent Parenting Project. Some of the important characteristics associated with individualized, innovative, child-centered parenting programs should include: The availability of specialized services for mothers who are low-functioning, depressed, substance abusers, or have been exposed to acts of violence and abuse. The explicit formation of a clear positive model of parenting that is practical, evidence-based and culturally-sensitive; speciﬁc parenting strategies and behaviors should be taught at a level that is developmentally appropriate for each at-risk mother. An early focus on building parenting skills prior to the emergence of major problems in ﬁrst-born children, with follow-up training to address the parenting skills needed as children develop; there should be an explicit concern with linking the intensity of the intervention at any given time with the parenting skills of the mother. The systematic involvement of a friend or relative of the mother in the intervention in an eVort to ensure appropriate support and mentoring from an individual with whom she already has a meaningful relationship. It should be noted that based on our analyses, we do not know how second- and third-born children of teenage mothers fare, but we suspect that their developmental trajectories may be even more compromised than those of ﬁrst-born children since at-risk mothers are likely even more stressed and their personal resources more taxed by additional children, problems in relationships, and ﬁnancial diYculties. Hence, the need for intervention may be even greater for teen mothers with two or more children born within a 2-year time span. The exception would be the teen mother who acquires good parenting skills, succeeds in obtaining adequate education and job training, and moves swiftly and surely into adulthood; developmental outcomes for their later-born children will likely be more favorable. Intervention programs built around the principles listed in the preceding text are likely to oVset many of the developmental delays associated with teenage parenting. In many cases, parent training programs may need to be

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supplemented by high quality childcare, either in home or daycare settings. Without highly focused, intense, early, and prolonged child-focused interventions, mothers, children, and society will continue to suVer. Because of changes in the welfare system and the ‘‘viciousness’’ of poverty, the need for high quality prevention programs may be even greater today than in previous generations.

ACKNOWLEDGMENTS This Chapter is based on research supported by NIH grant HD-26456. Authors Lounds, Willard Noria and Burke Lefever were also supported by an NIH training grant (HD-07184).

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The Ecological Context of Challenging Behavior in Young Children with Developmental Disabilities ANITA A. SCARBOROUGH AND KENNETH K. POON CHILD DEVELOPMENT INSTITUTE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL CHAPEL HILL, NORTH CAROLINA

The U. S. Individuals with Disabilities Act (IDEA) and the EURLYAID manifesto, based on the United Nations Convention of the Rights of the Child and IDEA (De Moor et al., 1993), recognizes the centrality of the family to the child’s healthy development and thus seeks to increase the dimensions in which families are positively supported. Reﬂecting the spirit of these initiatives, this chapter examines how challenging behavior impacts the child with developmental disabilities and their family, the larger ecological context within which these challenging behaviors occur, and how interventions for these children may be planned recognizing the ecological context of the child and family. I.

CHALLENGING BEHAVIOR AND CHILDREN WITH DEVELOPMENTAL DISABILITIES

The higher frequency of challenging behaviors associated with developmental disabilities has been described in numerous studies (Berg & Gosse, 1990; King et al., 1994; Moss et al., 2000; O’Brien, 1992; Reber, 1992). Einfeld and Tonge (1996) found that over 40% of the children between 4 and 18 years of age with mild intellectual disability could be classiﬁed as having serious behavioral problems. Gillberg et al. (1986) and Rutter et al. (1970) found similar proportions. Three-year-olds with cognitive delays are 3 to 4 times more likely to have challenging behavioral patterns compared to their typically developing peers (Baker et al., 2002). INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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Challenging behaviors and developmental disabilities are linked by a combination of neurological, social, psychological, and personality risk factors, coupled with the behavioral characteristics of speciﬁc chromosomal abnormalities (Dosˇen & Day, 2001). Examples of challenging behaviors include: hyperactivity; repetitive, aimless motor activity; stereotyped play; unusual seeking of sensory experience; inﬂexibility; passivity; and restlessness (Kaminer & Cohen, 1995). Self-injurious behavior (SIB) is also reportedly present in 3% to 17% of children with mental retardation (MacLean et al., 1994) and is more common among the most cognitively delayed. Other challenging behaviors manifested in young children with developmental disabilities are related to aggression, modulation of emotional response, and diYculties in relatedness (Kaminer & Cohen, 1995). Growing recognition of the importance of the development of behavioral patterns is apparent in the National Institute of Child Health and Human Development (2000) identiﬁcation of the examination of interactive factors associated with behavioral development in children with developmental disabilities as a priority research agenda.

A.

Defining Challenging Behavior

Deﬁning challenging behavior is complicated by the fact that while behavior is typically judged by a conventionally and culturally understood standard, children with developmental disabilities have predictable limitations in competence (Masten & Curtis, 2000). For instance, young children with cognitive delays frequently exhibit behavioral patterns similar to that of chronologically younger children (Siegel, 1996). The discrepancy between chronologically expected and developmentally appropriate behavior is a contributor to parental insecurity about how to respond to or gauge reasonable expectations for behavior (Chinitz, 1995; Cullen et al., 1991; Fombonne et al., 2001). Moreover, this asynchrony increases the likelihood of the development of challenging behaviors due to the diminished quality of parent-child interactions. Unrealistic expectations for child behavior have been shown to be related to child control problems (Rickard et al., 1984). Inappropriate parental expectations are likely to exacerbate challenging behaviors for children with developmental disabilities (Chinitz, 1995). Discriminating between very problematic behavior and psychopathology in young children is diYcult, as it is for adults (Moss, 2001). However, extremely severe behavioral disturbances in young children with cognitive delays are thought to be related to caregiving interactions characterized as neglectful, abusive, or isolating (Gaedt, 2001).

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B.

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Understanding the Outcomes of Challenging Behavior

Given the prevalence of challenging behavior among young children with developmental disabilities, it is important to appreciate the potential negative consequences of those behaviors if left unchecked. Three important outcome areas have been identiﬁed: the impact on the child’s developmental trajectory and likelihood of social inclusion; contribution to family stress; and the avoidance of the development of more serious behavioral problems. 1. IMPACT ON CHILD DEVELOPMENT

Acknowledging that challenging behavior has the potential to interfere with optimal development obliges early intervention professionals to address problematic behaviors (Kaminer & Cohen, 1995). There is recognition that fostering positive emotional and social development in young children with developmental disabilities is equally, if not more, important than maximizing language and cognitive abilities. Behaviors that negatively aVect interaction with peers have the capacity to impact the child’s ability to successfully socially integrate (Gaedt, 2001; Wood et al., 2002). In this manner achieving meaningful social inclusion for children with developmental disabilities is heavily reliant on appropriate social behavior (Berney & Corbett, 2001). 2. CONTRIBUTION TO FAMILY STRESS

The natural environment of very young children is the home, the environment where challenging behaviors are ﬁrst noted. Speciﬁcally, it is diYcult behavior that is most responsible for additional family stress (Floyd & Gallagher, 1997; Honjo et al., 1998). The demonstrated relationship between challenging behaviors and the degree of stress reported by families (Baker et al., 2002; Donenberg & Baker, 1993) provides added exigency for professionals to understand factors that contribute to the development of challenging behaviors in order to provide appropriate intervention services. Moreover, research ﬁndings from studies of young children with chronic health conditions suggests that alleviating parenting stress is an intervention strategy that has the potential to reduce the development of challenging behavior (Carey, 1998; Goldberg et al., 1997). 3. ESCALATION OF CHALLENGING BEHAVIORS

Another factor driving attention to the identiﬁcation of the source of challenging behaviors is related to educational mandates regarding permissible disciplinary action for school-age special education students. These mandates have generated eVorts to isolate indicators of the earliest signs of behavioral diYculty, which would allow the provision of intervention to prevent the escalation of problem behaviors that could aVect the child’s learning potential and social inclusion during the school-age years (Sandall & Ostrosky, 1999).

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The quest to understand the origin of challenging behaviors of young children with developmental disabilities is driven by the need to provide appropriate intervention, with the goal of enhancing optimal long-term outcomes for children and families. Knowledge of the source of behavioral patterns is requisite in devising interventions to reduce the negative eVects of challenging behaviors on learning and to avoid the escalation of more serious behavioral problems. Understanding the development of challenging behavior is an important component to support the social inclusion of young children with developmental disabilities. Along with families, practitioners of all disciplines and researchers hold a vested interest in comprehending the ecological contributors to behavioral diYculties. Isolating modiﬁable components of the caregiving environment is essential to devising interventions that positively inﬂuence child outcomes (Forness et al., 1996, 1999).

II.

THE ECOLOGICAL CONTEXT OF CHALLENGING BEHAVIORS

Behavioral characteristics of young children with developmental disabilities can be broadly attributed to three primary sources: (1) inherent behaviors; (2) behaviors that are learned, reﬂecting the child’s interactive experience and the characteristics of the developing child’s caregiving environment; and (3) behavioral patterns that reﬂect the dynamic transaction between inherent and learned behaviors. A.

Genotype: Inherent Behaviors

The genotype represents the genetic constitution of an individual. Genotype behaviors may be conceived of as being derived from three identiﬁed sources. First, inherent dispositional characteristics, such as temperament, may be thought of as familial traits in the sense that they are behavioral patterns resulting from genetic characteristics that shape the neurological functioning of the child. Second, behavioral traits called behavioral phenotypes are also inherent in that they are characteristic of a speciﬁc genetic disorder that aVects the neurological functioning of all children with the disorder in a somewhat similar fashion. Conditions such as depression and speciﬁc psychopathologies such as schizophrenia (McClellan & Werry, 1997) and obsessive-compulsive disorder (Leonard et al., 1997) have been examined from the perspective of being genetically determined aspects of behavior. And third, other inherent behavioral characteristics are the result of biological factors that physiologically impact the child’s neurological

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functioning in a manner that inﬂuences behavioral patterns. In this manner inherited temperament, behavioral phenotype associated with a genetic disorder, and biological factors physiologically impacting the child’s neurological system may all contribute to behavioral genotype. 1. TEMPERAMENT

The observation of individually consistent behavioral patterns in the reaction of newborns to stimulation supports the assumption that inherent components of temperament are discernable in neonates (Korner, 1996; Lewis, 1992). Consistency has been observed within neonates regarding their availability to sensory stimulation, excitability, irritability, and activation, as well as sensory threshold levels to auditory and visual stimulation (Korner, 1996). Since these behaviors are apparent almost immediately after birth, individual diVerences cannot be attributed to the caregiving experience. Instead these traits reﬂect innate diVerences in central nervous system functioning that form the foundation of how an infant will interact with the caregiving environment (Akhtar & Samuel, 1996; Korner, 1996). Thomas and Chess (1977) conceptualized temperament as the style of behavior, rather than the motivation or the intention. It is heavily inﬂuenced by inherited traits and remains basically stable throughout life. In this sense, temperament is considered the foundation of infant behavior based solely on inherent genetic components and/or neural structure. Thomas and Chess (1977) speculated that challenging behaviors were the consequence of negative interactions between a child’s temperament and parental expectation. Although temperamental characteristics may be tempered by environmental interactions (Bates et al., 1994), they nevertheless tend to remain recognizable traits throughout childhood (Pedlow et al., 1993). 2. BEHAVIORAL PHENOTYPES

Nyhan (1972) introduced the term behavioral phenotype, which is a repertoire of behaviors more likely to be associated with a speciﬁc genetic disorder. Research focused on the identiﬁcation of behavioral phenotypes is a relatively new endeavor, evolved from the recently expanded scientiﬁc capacity to genetically identify disorders associated with developmental disabilities. Acknowledging individual variations and other ecologically inﬂuenced behavioral variations, behavioral proﬁles or phenotypes have been described for certain genetic disorders (Dosˇen & Day, 2001), for example, Lesch-Nyhan syndrome, Down syndrome, or Williams syndrome. The formation of alternative neurological pathways provides a plausible explanation for unique and sometimes seemingly contradictory skill patterns (Moss et al., 1999) that may be encompassed within a single behavioral phenotype, and may contribute to the explanation of disorder-speciﬁc

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behaviors. The behavioral phenotype associated with a disorder such as the over-friendly nature of children with Williams syndrome (Dykens et al., 2000) may be considered a more negative or positive behavioral characteristic, depending on familial and cultural expectation. The isolation of behavioral characteristics associated with speciﬁc disorders is of importance because it can be utilized to augment the earliest possible identiﬁcation of children, thus permitting the delivery of eVective intervention services (Neisworth et al., 1999). Neuroscience researchers utilizing state-of-the-art technology have just begun to explore the derivation of behaviors in relation to the biophysical perspective of brain structure (Wang et al., 1992a,b) biochemical processes (Ernst et al., 1999), and the identiﬁcation of the hemispheric location of emotional control. Because the developing structure of the brain in young children and the associated neurochemical function associated with brain function provide the physiological basis for early observable behavior, theories on how faulty neurological structure or function is responsible for observable behavior have been postulated (Rourke et al., 2002). There is increasing understanding of how behavioral patterns are linked to developmental status using anatomical or biochemical terms; autism is a prime example of a disorder with behavioral components as mandatory features for identiﬁcation, although a single physiological or genetic cause has yet to be identiﬁed (Piven & O’Leary, 1997). 3. BIOLOGICAL FACTORS WITH THE POTENTIAL TO AFFECT BEHAVIOR

Infants born prematurely or with certain diagnosed medical conditions (e.g., metabolic, genetic, and seizure disorders) are at varying degrees of risk of subsequent developmental disabilities. Inherent temperamental characteristics of these neonates are tempered by compromised neurological systems that present a biological risk to the child. This compromised physiological status has the potential to aVect temperament, behavior, and cognition. DiYculties with certain aspects of physiological regulatory characteristics that correspond with the ability to self-regulate or related dimensions of inherent temperamental traits are described as regulatory disorders. Infants considered regulatory disordered (i.e., disturbances in sleep, feeding, state control, and self-calming) (Degangi et al., 1993) or with reduced capacity to regulate their cardiac vagal tone in response to events related to feeding or during painful situations (Porges et al., 1996), have been found to be at higher risk for the development of challenging behaviors at preschool age. Studies have found that children born the most premature are more likely to develop challenging behaviors (Sommerfelt et al., 1993), be described as hyperactive, or diagnosed with attention deﬁcit hyperactivity disorder

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(Chapieski & Evankovich, 1997; McCormick, Gortmaker, & Sobol, 1990; Robson & Pederson, 1997; Whitaker et al., 1997). Premature infants with diYcult temperaments, albeit a small group, were found most likely to have challenging preschool behaviors. (Goldberg et al., 1990). The fragile physiological status of preterm infants has the capacity to alter caregiver-child interaction (Case-Smith et al., 1998), which complicates the process of isolating the source of subsequent behavioral diYculties. A relational pathway between characteristics of parenting practice, language development, and hyperactivity, with neonatal health rating and hyperactive behavior in preterm infants at 5 years of age has been described (Girouard et al., 1998). Providing support for the interactional and transactional nature of these factors, a Japanese study found that very low-birth-weight infants and their families that participated in early intervention programs were less hyperkinetic and had better language skills at 24 months of age than the controls (Matsuishi et al., 1998). Overall, researchers have found that attentional diYculties in low-birth-weight infants appear to be positively associated with birth weight (Chapieski & Evankovich, 1997) and related to dimensions of infant-caregiver interaction (Robson & Pedersen, 1997). The twin studies comparing temperamental characteristics with neonatal reactivity by Korner (1996) revealed that neonatal reactivity for infants born appropriate for gestational age (AGA) was more predictably related to temperamental characteristics, than those born small for gestational age (SGA). This variability in temperament is related to diVerent neurological developmental patterns for infants subject to the stress associated with intrauterine growth retardation (Riese, 1998). Although birth weight and gestational age are correlated, SGA infants are speciﬁcally at higher risk for developmental disabilities (Lagercrantz, 1997). The underlying reasons for this increased risk may also be the same phenomenon that impacts the development of temperamental characteristics of SGA children. The development of challenging behavior is associated with events that injure the neurological system and alter developmental patterns. Other factors known to present risk to the developing neurological system are systemic infections, extremely poor nutrition, or exposure to toxins in the environment such as lead (Wasserman et al., 1998), and prenatal exposure to drugs, alcohol, or tobacco.

III.

ENVIRONTYPE: THE ECOLOGICAL CONTEXT OF BEHAVIOR

Besides inﬂuences from the genotype on behavior, researchers have long studied the impact that society as a whole has on the developing child. Thus, the development of challenging behavior from an ecological perspective

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examines the contribution of environmental factors to child social-emotional well-being and to the development of behavioral patterns. The social ecology theory of Bronfenbrenner (1977, 1979) oVers a means for understanding the impact of ecology on the child. He posited that each individual was embedded within multiple systems that impact daily functioning. Bronfenbrenner described four nested ecological layers: (1) the mircosystem consists of relationships between individuals within the family (e.g., father-mother and siblingchild relationship); (2) the mesosystem comprises the relationships between the individual and other systems in which it actively participates (e.g., relationships between family and the hospital, early intervention, and extended family); (3) the exosystem comprises settings in which the individual is not actively involved but which can aVect the family (e.g., welfare systems, and mass media); and (4) the macrosystem which includes the general societal values that inﬂuence not just the individual but all of the nested systems (e.g., ethnic, socioeconomic, and religious backgrounds). Bronfenbrenner’s ecological model and SameroV’s (1998) cumulative risk theory both have relevance in describing challenging behavior of children with developmental disabilities. A.

Microsystem: The Impact of Family Experience

Aspects of the broad scope of the family’s experience, such as the stress the family is experiencing, the quality of the marital relationship, parental wellbeing (i.e., having a caregiver with a psychopathology, mental retardation, or a substance abuse problem), and the emotional warmth expressed within parent-child interactions have all been examined as contributors to the development of challenging behaviors. Negative outcomes do not necessarily apply to all children described as having one of the aforementioned risk factors (Brinker et al., 1994), but many of these factors are more frequently associated with poverty. B.

Mesosystem and Exosystem: The Impact of Poverty on Challenging Behavior

Studies have substantiated that poverty is the largest single predictor of abnormal developmental screening for preschoolers (Miller, 1998; Msall et al., 1998). Dodge et al. (1994) found that low socio-economic status predicted the development of challenging behaviors in preschool-age children, and that poverty was correlated with harsh discipline, lack of maternal warmth, exposure to aggressive adult models, maternal aggressive values, extreme family stressors, lack of maternal support, peer group instability, and lack of cognitive stimulation. The 1988 National Health Interview Survey found that poor children between 3 and 17 years of age were more likely to have a parent report the child as having a behavioral or emotional

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problem than their non-poor peers (Brooks-Gunn & Duncan, 1997). The National Early Intervention Longitudinal Study found that among toddlers 12 to 33 months of age participating in early intervention services, caregivers described 20% of toddlers living in households with $15,000 or less annual income as often aggressive, compared to 3% of children from households with annual incomes over $75,000 (Spiker et al., 2004). Since poverty is correlated with many factors that contribute to the child’s caregiving environment, children living in poverty are at increased risk for both developmental disabilities and challenging behaviors (Halfon & Newacheck, 1999). Numerous studies found challenging behaviors to be more prevalent among children from families in lower socio-economic groups (Briggs-Gowan et al., 2001; Keenan et al., 1997; McMunn et al., 2001; SameroV, 1998). Complicating the derivation of challenging behaviors in low-birth-weight infants is the ﬁnding that these children from poor families more frequently have challenging behaviors (Laucht et al., 2001) compared to children who have never been poor, even after controlling for maternal education and the family constellation (Duncan et al., 1994). A recent survey of mental health in Great Britain found one-ﬁfth of children living in a home without an employed parent to have a mental disorder such as a conduct disorder, hyperactivity, or autism, twice the proportion of families with a working parent (Meltzer et al., 2000). Thus, from an ecological perspective, poverty is a condition whose eVects may permeate all aspects of the exosystem (e.g., dangerous neighborhood and poorly funded schools), as well as the mesosystem (e.g., poor parentalschool relationship due to the lack of time and early intervention agency not understanding the neighborhood). Due to the constraints poverty places on the parents, even the microsystem of the child is impacted (e.g., authoritarian parenting practices and childcare arrangement). Many environmental risk factors related to poverty have been identiﬁed as potential contributors to poorer developmental outcomes: such as parental substance abuse; teen mothers; low levels of maternal education; poor infant health status; lead exposure (Wasserman et al., 1998); and increased exposure to an array of environmental hazards such as air pollution and toxins associated with poor housing conditions. Because of complex interrelations, the exact manner in which poverty aVects child development is unclear, but various mechanisms have been posited such as lack of food and necessary goods, lack of access to health services, and an unstimulating, chaotic home environment (Bradley et al., 1994). In general, there is reason to believe that poverty with its accompanying economic stress elevates the rate of challenging behaviors because of the tendency for parents to interact with children in a harsh and inconsistent manner and to ignore the child’s dependency needs (McLoyd, 1998).

238 C.

Anita A. Scarborough and Kenneth K. Poon Macrosystem: Cultural Influence on Child Behavior

DiVering cultural expectations for socialization, developmental expectations, and home environments impact development through culturally unique parental practices as evidenced in parent-child interactions. The socialization of children within a culture is a function of the parent-child interactions, general living conditions (e.g., home and physical environments), and symbolic systems (i.e., the shared cognitive schema among a population). Cultural parenting diVerences have been found in parents from non-Western cultures relying less on the vocal-verbal mode of communication and having a shorter duration of eye contact when interacting with their child (Scho¨lmerich et al., 1995). The speciﬁc mechanism that accounts for diVerences in interactions is rooted in the cultural beliefs that parents have regarding behavioral expectations. For example, American parents are more likely to have earlier expectations for certain behaviors than Italian parents (Edwards et al., 1996). Culturally derived aspects of the physical home environment have the capacity to inﬂuence parent-child interactions. For example, a study of Malaysian Chinese, Malay, and TamilIndian infants found that because of the common small living space Malay infants were more likely to initiate contact with their mothers than Chinese or Tamil-Indian infants (Woodson & da Costa, 1989). Culture plays an integral role in shaping behavior and hence the development of the child. Culture impacts upon socialization practices and these socialization practices are mediated by parental beliefs. Furthermore, parentchild interactions are constrained by the physical environment. Because challenging behaviors have their origins in the interaction of the child and family (Patterson, 1982; Rothbart, 1989; Thomas & Chess, 1977), it follows that culturally based parent-child interactions can contribute to the development of challenging behavior for young children with development disabilities. Accompanying the research on ecological factors, in the Rochester Longitudinal Study SameroV (1998) reported another salient ﬁnding—the cumulative risk of living in a family environment with multiple problems increased the likelihood of the development of challenging behaviors. The evaluated risk variables were: history of maternal mental illness; high maternal anxiety; parental perspectives that reﬂected rigidity in attitudes, beliefs, and values in regard to their child’s development; few positive mother-child interactions; head of household with an unskilled occupation; minimal maternal education; disadvantaged minority status; single parenthood; stressful life events; and large family size. Thus, the number of co-occurring risk factors appears to be more predictive of negative developmental outcomes than any individual risk factor (Laucht et al., 1997; SameroV, 1998; Sedlak & Broadhurst, 1996; Zeanah et al., 1997).

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In summary, interactive experiences of children with their caregivers are inﬂuenced by the cultural norms for behavioral expectation (Graziano et al., 1998; Olson et al., 2001), caregiver characteristics, and endless inﬂuential factors in the ecosystem of the developing child (SameroV & Fiese, 2000). Beyond that, behavioral patterns are the result of a complex continuous and dynamic interaction of traits inherent to the child, inﬂuencing and being inﬂuenced by dimensions of the caregiving experience, that develop over time. As children age, environmental inﬂuences on behavior become more unique, but the inherited portion of behavioral traits remain as the foundation for behavioral propensities (Rutter et al., 1997). This dynamic interplay between the genotype and the environtype is best captured by the transactional model.

IV.

INTERACTION: TRANSACTIONAL MODELS

Despite research eVorts that have contributed signiﬁcantly to understanding how nature and nurture inﬂuence development in an interactive manner, the quest to isolate the contribution of each to observable behavior patterns has evaded quantiﬁcation (National Research Council and Institute of Medicine, 2000; Rutter et al., 1997). Extracting empirical evidence of the proportional contribution of genotype to observable behavior is challenged by the inextricable eVect of life experience on children and on their caregivers, in concert with cultural expectations for behavioral norms (Graziano et al., 1998; Olson et al., 2001). In explaining the contribution of the environment to the development of challenging behaviors, the ubiquitous genetic contribution cannot be underestimated, but the synergistic eVects of the genetic constitution of the child (genotype) and the exhibited characteristics (phenotype) on the development of behavior must be kept in mind. Inherent behavioral traits have the capacity both to aVect characteristics of the caregivers and inﬂuence the caregiving environment (Kendler, 1996; Rutter et al., 1997). Behaviors inherent to the child are the means that enable children to modify their own caregiving environment. As children grow physically more independent, personal preferences contribute to how they shape their own developmental experiences (Scarr & McCartney, 1983). The capacity of inherent child characteristics to elicit complementary responses from caregivers, and thus inﬂuence the family environment is an example of a mutual inﬂuence model (Ge et al., 1996). What constitutes the development of challenging behavior in young children with developmental disabilities is the result of a unique and complex interplay of inherited traits, both being inﬂuenced and inﬂuencing personal and family environmental experience.

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Challenging behavior, whether an inherent characteristic or the result of dynamic interactions with environmental factors, is not a phenomenon relegated to children with developmental disabilities and, therefore, models regarding how aspects of the interaction between these two domains operate to shape behavior are equally applicable to other populations. Models that detail speciﬁc dimensions of the interactive relationship between the child and the caregiving environment contribute to understanding the nature of the interaction and how the quality or content of these interactions has the potential to mold the child’s behavioral characteristics. Four models that speciﬁcally address interaction in terms of behavioral outcomes will be examined. They are models relating to goodness of ﬁt (temperament), attachment theory, adaptive theory, and transactional theory. A.

Goodness of Fit

Temperamental diYculties can be reﬂective of a chronic state of stress in the child-caregiver relationship. The evaluation of temperament in infants is typically based on maternal report (Bates, 1987; Thomas & Chess, 1977) which may contribute to the stability of temperamental characteristics over time in that maternal expectations for behavior expectations are reﬂected in temperament measures. The relationship between a child’s ability to selfregulate, the essential behavioral trait captured within the construct of temperament, and caregiver interaction with the child, are considered the foundation of behavioral characteristics in the temperament model. In the paradigm of temperament, challenging behaviors are manifestations of interactive diYculties. In this manner, challenging behavior in a young child with a developmental disability can be a mechanism for garnering attention from an unresponsive parent. Indeed, diYcult temperament in toddlers has been linked to maternal emotional neglect (Harrington et al., 1998). Temperament traits also contribute to various conditions, such as accidents, abuse, failure to thrive, obesity, and recurrent abdominal pains and headache, making the occurrence of such conditions more likely for certain kinds of children (Carey, 1998). Thomas and Chess (1977) proposed the concept of ‘goodness of ﬁt’ to describe how temperamental characteristics of the child meet the expectations of the caregiving environment. A young child with a developmental disability and with diYcult temperamental traits may present more of a problem to caregivers with certain behavioral expectations. This lack of ﬁt can contribute to caregiver inaccurate attribution of challenging behavior as being intentional, revengeful, or simply due to lack of motivation on the part of the child and may serve to exacerbate challenging behaviors over time.

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A related theory proposed by Rothbart and Derryberry (1981) conceives essential components of temperament as the child’s reaction to the caregiving environment or the ability to self-regulate. Transactional adaptations are continuously at work between the child’s temperament and the caregiving environment. Components of temperament evolve in the developing infant in a normally predictable sequence (Rothbart, 1989) with variation related to changes in the child’s increased ability to self-regulate. As such, there is a typically expected age range for the emergence of developing behaviors and similarly for self-regulatory skills. Variation in the organization within the subsystems of temperament is in turn dependent on the maturation of speciﬁc neurological structures (Derryberry & Rothbart, 1997). The changing capabilities and requirements of toddlers demand continual parental adjustment, particularly in children with atypical developmental patterns. Two dimensions of adaptation are particularly essential to maintain harmonious child-caregiver interaction. Parental expectation for the child’s self-control at each level must be realistic and the caregiver’s tolerance or threshold for excitement must match the level generated by the child. A discrepancy between parental expectation for child behavior and the child’s ability to self-regulate or parental intolerance of the excitement caused by the child’s behavior can cause long-lasting problems in the interactive pattern between parent and child (Rothbart, 1989). Thus, for toddlers with developmental disabilities, the interaction between child and caregiver becomes more intricate because of the complex interrelationships among self-regulation, temperament, behavior, and neural development (Rothbart et al., 1994). For example, although most children progress through a typical developmental sequence, there are infants who may show signs of speciﬁc developmental delay, such as not walking by 18 months, but who otherwise appear to be developmentally and behaviorally typical. Conversely, infants who demonstrate precocious motor skills, such as walking at an early age, may be demonstrating variation in developmental rate due to experience, rather than an inherent characteristic. This same pattern of variability pertains to the development of neural pathways responsible for the reactivity of neural systems or the ability to self-regulate. The child’s capacity to control these behavior-generating subsystems is related overall to the developmental status of the child (Derryberry & Rothbart, 1997) and to experiential opportunities. B.

Attachment Theory

Bowlby (1971) introduced the general notion of attachment in order to understand close relationships in a young child’s life. The inherent characteristics of infants require that they have nurturing and protective care, and

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adults have inherent characteristics to provide that care. Attachment is the term used to describe the emotional bond formed by a young child for the primary caregiver or mother ﬁgure (Ainsworth et al., 1978). The quality of infant attachment is a dimension of the caregiver relationship that has been associated with challenging behaviors in preschool age children and in adolescents (Greenberg et al., 1997). Typically developing children with insecure attachment have been described as socially withdrawn, aggressive, and with reduced reciprocity in social interactions (Lyons-Ruth, 1996). The quality of the attachment that a child forms with the primary caregiver has been suggested as a potential mediating variable for the later development of psychopathology (Carlson, 1998). The inherent dispositional characteristics of infants that comprise temperament bring unique demands to the relationship between the child and the caregiver. Both temperament and attachment theorists alike agree on this relationship, but diVer in their interpretation of infant behavior in the strange situation. The strange situation (Ainsworth et al., 1978) is used to assess an infant’s orientation to the primary caregiver. The range of the expected behavioral repertoire, such as crying, clinging, and seeking of the caregiver, are used to determine the pattern of the infant’s attachment. Temperament theorists interpret such behavior as a demonstration of the child’s inherent behavioral characteristics, while attachment theorists describe this behavior as the result of the caregiving relationship and identify the nature of this response as an indicator of attachment quality. As with other nature versus nurture quandaries, twin studies have been utilized to attempt to delineate child and caregiver contribution to patterns of attachment. This research has supported the notion that the inherited behavioral characteristics of infants, particularly those associated with irritability, contribute to the development of attachment patterns (Goldberg, 2000). Physiologically, infants born prematurely or with diagnosed medical conditions are subject to an increased occurrence of developmental delay and frequently demonstrate temperamental characteristics that have the potential to aVect the child-caregiver relationship. Parents of these infants are required to provide additional and more demanding care. These infants may not only appear physically diVerent from typical infants, but they may have a reduced capacity to initiate interactive signals that are easily interpretable. Despite this general reduction in frequency and intensity of initiations, research regarding the attachment status of infants born prematurely or with high-risk medical conditions has not shown that attachment patterns diVer signiﬁcantly from the attachment patterns of typical infants (van IJzendoorn et al., 1992). Overall, what has been demonstrated to aVect attachment and subsequent behavioral patterns is more related to characteristics associated with the child’s environment, such

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as the quality of the child-caregiver relationship, and not with measures of the child’s temperament or inherent behavioral traits (Carlson, 1998). Speciﬁcally, characteristics of the mother appear to mold the attachment relationship. Maternal problems such as mental illness contribute more to diVerences in the quality of attachment, than do characteristics associated with the child, such as deafness (van IJzendoorn et al., 1992). Overall, it appears that children form attachment relationships with caregivers, except under extreme adverse conditions, and that attachment and child temperament patterns are related (Wachs & Desai, 1993). Twin studies have demonstrated that there is a signiﬁcant genetic contribution to attachment patterns, and the mechanism for this is mediated through the heritable aspect of temperament (Goldberg, 2000). C.

Adaptive Theory

The adaptive theory (Sackett et al., 1999) is based on an animal model for relating early experience to behavioral characteristics. The theory proposes that young children exposed to a caregiving environment rich in varied experience produces an individual that is likewise more psychologically complex. Such children are more likely to approach and enjoy novel learning situations, which exponentially increases the opportunities to learn. On the contrary, children raised in an unstimulating environment avoid novel and complex situations, and thereby further reduce learning opportunities. High psychological complexity is produced when children are exposed to caregiving environments that contain many stimulus changes, multi-modal stimulation, predictable and unpredictable feedback, and control of some external events (Sackett et al., 1999). However, inherent temperamental diVerences alter the amount and number of simultaneous stimuli that can be tolerated before evoking an avoidance response in a young child. A rich and complex interaction with the caregiver forms the child’s social cognition in knowing how to interact with other individuals. The caregiving environment for children with mental retardation or severe sensory limitations may be conceived as being deprived due to their inability to perceive or interpret the stimuli being provided. This manifests itself in a form of privation rearing with the resulting loss of interpretable interaction apparent in the child’s behavioral patterns. Uninterpretable behavior could be considered challenging behavior from the caregiving perspective. These reviewed interactional frameworks demonstrate that an interactional account is essential for understanding challenging behavior among children with developmental disabilities. Although the transaction between genotype and environtype is explained, the account is largely static and does

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not take into consideration how behaviors develop over time and does not account adequately for the complexity of the total ecological environment. D.

The Transactional Model

A model with adequate complexity to encompass multiple simultaneous interactions is the transactional model of development. The transactional model (SameroV, 1993; SameroV & Chandler, 1975) illustrates how the interaction between the child’s inherent characteristics (genotype) and the caregiving environment (environtype), results in both being mutually aVected. Thus, developmental outcomes are the product of the interaction between the biological composition of the child and environmental inﬂuences. Developmental outcomes at any particular point in time (i.e., the phenotype) are the result of the child’s impact on the environment and vice versa; this process is continual and dynamic. In outlining the framework, SameroV (1993) described the genotype as the product of the genetic organization and biological regulation of the individual. He deﬁned the environtype as the larger environment of the individual that encompasses the family and all other systems within the Bronfenbrenner (1979) social ecology model. Although the transactional model (SameroV & Fiese, 2000) stresses the importance of the interaction of the child’s inherent genotype with the environment, no greater importance is placed on any single factor; consequently, the search for predictive factors associated with developmental outcomes continues (Zeanah et al., 1997). The SameroV (1993) transactional model highlights the inﬂuence of the child’s cultural ecology within the context of child development. This model recognizes that it is important to divide environtype into two portions if the roles of culture and parenting practices within the family are to be detailed. Culture indirectly impacts the development of children through the socialization practices of the parents. More importantly, family practices develop in a manner corresponding to the development of the child, in response to how the inherent characteristics of the child inﬂuence the caretaking environment. The transactional model includes the Bronfenbrenner (1979) four ecological layers and speciﬁes the interaction between cultural systems and parental practices. The genotype and the phenotype correspond to areas described by SameroV (1993). However, the environtype may also be elaborated revealing familial and cultural systems, corresponding to the family and cultural eVects on development considered by SameroV and Fiese (2000). The model also includes longitudinal eVects of the processes across the lifespan of the developing child. Across time, the directionality of interaction is unchanged, but the changing magnitude of dimensions of the interactive process is recognized. Thus, in infancy, the child’s phenotype

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is determined largely by the genotype and contributes in a limited but continually increasing extent to his or her biological composition. Similarly, the family exerts inﬂuence on the infant’s development but is reciprocally inﬂuenced by the infant’s inherent behavioral characteristics. Development progresses during infancy largely according to a maturational schedule. Culture has a signiﬁcant role on family practices and while family mediates the culture in the child’s environtype, the model recognizes that the family’s impact on culture is marginal. Child characteristics, parenting practices, phenotype, and genotype impact on each sequential phase of development, however, each component has a varying impact on child development over time. Whereas the impact of the genotype and cultural systems remain fairly consistent, the phenotype and family systems gain momentum in their impact on development with their relative contribution to the interactive process over time. An important implication of this model is the recognition of the increasing inﬂuence of culture over development, albeit mediated by the family system (e.g., parent-child interaction) as the child matures.

V.

AN ECOLOGICAL MODEL OF INTERVENTION

Progressively more complex intervention models have developed to accommodate the expanding sphere of recognized behavioral inﬂuences, paralleling complex ecological models that recognize varied contributors to the development of challenging behaviors. Isolating modiﬁable components that inﬂuence the development or reinforce challenging behaviors is a necessary component in creating interventions to positively inﬂuence child outcomes (Forness et al., 1996, 1999). Intervention refers to a program or therapy aimed at increasing appropriate behaviors and/or reducing inappropriate behaviors in children with developmental disabilities. Used widely, intervention refers to programs aimed at helping a child maximize his or her learning potential in home or center-based educational programs or therapy designed to help the child develop social competence. Beginning with the Skinner (1953) A-B-C model of operant learning, the role of ecology in intervention will be elaborated and applied. The S-O-R-K-C framework (Kanfer & Phillips, 1970; Kanfer & Saslow, 1969) represents an expanded model that includes not just the immediate environment but also organismic variables, although the importance of the ecology of the child is understated. Mirroring the SameroV (1993) transactional model, the E[S-O-R-K-C] model is an elaboration of the previous models to portray the multiple inﬂuences of learning.

246 A.

Anita A. Scarborough and Kenneth K. Poon The A-B-C Paradigm

In Skinner’s (1953) seminal publication he advocated the imperative to study behavior scientiﬁcally. Acknowledging that some behaviors are reﬂexes or acquired through classical/Pavlovian conditioning processes, he posited that the bulk of human behavior was acquired via operant learning. In operant learning, behavior is deﬁned as being a function of its consequences, which provide some form of feedback to the child. This model has been developed for application within various ﬁelds, most notably developmental disabilities. The functional analysis of behavior, the A-B-C paradigm (Bihm et al., 1996), describes the contingency between Antecedents, Behaviors, and Consequences. Skinner (1953) posits that once these dimensions are identiﬁed, behavior may be predicted and controlled. Antecedents refer to the stimuli that have set the occasion for a reinforced response (i.e., discriminative stimulus). Behaviors are actions and must be observable. Consequences follow behavior and may either be rewarding or punishing. Rewarding consequences increase the chance of a reoccurring behavior. They may be positive via the presentation of something rewarding or negative via the removal of something aversive. Punishing consequences decrease the chance of a reoccurring behavior and involve either the application of a noxious stimulus or the removal of something positive. Functional analysis of behavior has been applied in the area of intervention to teach new skills and to manage behavioral diYculties in children with developmental disabilities. Lovaas et al. (1966) published a landmark paper on intervention with children with autism. An intensive operant learning program for speech development was implemented using rewards for appropriate responses and punishment for disruptive behaviors. Within 26 days most of the formerly mute children acquired at least some form of verbal imitation. This operant learning was developed into a program based in behaviorism termed ‘discrete trial training’ (Lovaas, 1981). Lovaas (1987) reported that close to one-half the children with autism participating in the program were indistinguishable from their typically developing peers within 2 years. Functional analysis of behavior has also been applied successfully to children with SIB. Iwata and colleagues (1994) examined 152 functional analyses of SIB and reported that they were able to understand the etiology of about 95% of the cases and to develop corresponding intervention programs. Although the A-B-C paradigm has signiﬁcantly contributed to the ﬁeld of developmental disabilities in terms of establishing intervention programs to educate, train, and treat children, it is limited by its narrow focus of observable behaviors. Notably, the contribution of the individual’s appraisal of the event and the role of the ecology of the child has been ignored. To account for this limitation, theorists have included organismic variables into the behavioral analysis equation.

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The S-O-R-K-C Behavioral Equation

Kanfer and colleagues (Kanfer & Phillips, 1970; Kanfer & Saslow, 1969) expanded the Linsley (1964) behavioral equation, a reﬁnement of the functional analysis of behavior by Skinner (1953). Linsley (1964) re-termed Antecedent, Behavior, and Consequence as Stimulus, Response and Consequence, respectively, and added Contingency (K) to the equation arguing that it was important to understand the nature of the stimulus-consequence relationship. In light of cognitive, social, and emotional research, Kanfer and colleagues (1970, 1969) also argued for the inclusion of Organism to the behavioral equation. With intervention in mind, they developed the S-O-R-K-C as a functional (or behavioral) analytic approach which attempts to determine not just the immediate environmental but also other historical variables that control the present behaviors. Unlike the A-B-C paradigm that focused on immediate antecedents, this model includes the relationship between the environment and individual behavior. 1. STIMULUS (S)

Stimulus refers to stimuli within the environment, but only those that aVect behavior are considered relevant. A discriminative stimulus consists of stimuli produced by others or by the response of the individual (e.g., behavior chains formed when one response serves as a discriminative stimulus for the following response). Stimuli may be divided into: historical—those that precede a behavior indirectly increasing the probability of its occurrence such as a sleepless night; contextual—stimuli that occur concurrently with a speciﬁc behavior increasing its likelihood of occurrence but not directly, such as soft music’s properties in inducing sleep; and immediate—stimuli that occur directly prior to the response. Kanfer and Phillips (1970) acknowledge the role of society that ‘‘guides and directs the individual toward some learning experiences and excludes him [or her] from others’’ (p. 63). Societal inﬂuence is mediated by parents who serve to selectively reinforce or not reinforce speciﬁc behaviors leading to culturally inﬂuenced discriminative stimuli. The model is explicit in recognizing the signiﬁcant impact society has on the individual and that it is responsible for diVerences between subgroups. Despite recognizing the contribution that society makes to shaping behavior, the impact of ecology is not very developed. 2. ORGANISM (O)

The chief contribution of the S-O-R-K-C framework is the inclusion of Organism as a variable within the behavior equation. Organism refers to mediating variables in the relationships between the stimulus and response. Although it is clear that operant learning plays a fundamental role in behavior, biological factors also play an important role. Social and cultural attitudes must also be taken into consideration as they impact upon the

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individual’s ability to function in a speciﬁc setting. Moreover, there is interdependence and inseparability of social, behavioral, and biological functions. The importance of expectancies and other variables aVecting the organism, such as illness, cognition, aVect, and medication/drugs are stressed in the model. 3. RESPONSE (R)

Response comprises the overt or covert actions of the individual. Following Skinner (1953), Kanfer and Saslow (1969) divided response into respondents or involuntary acts acquired via Pavlovian learning, and operants or instrumental responses. They also argued that not all responses (or behaviors) may be modiﬁed by changing the reinforcing contingencies alone. Thus, there is a need to understand the organismic variables and the reinforcement history since most speciﬁc behavior patterns are learned or can be taught from a very early age. 4. CONTINGENCY (K)

Contingency refers to the relationship between behavior and its consequences. Of importance are schedules of reinforcement, which are arrangements of response-reinforcement contingencies (Ferster & Skinner, 1957). Examples of such schedules include ﬁxed-ratio and variable-ratio reinforcement schedules. Shaping is a process wherein the response-reinforcement relationship shifts from the reinforcing of events from one class of behavior to another, overlapping but slightly diVerent, response class. Kanfer and Phillips (1970) suggest that these behavior-consequence contingencies are inﬂuenced by ‘‘social inﬂuences [that] not only determine the skills and knowledge of the developing person; they also aVect his reactions toward himself. . .and the way in which the individual’s hierarchy of reinforcing stimuli is arranged’’ (p. 63). Again, there is an allusion, albeit brief, to the wider ecology. 5. CONSEQUENCES (C)

Consequence refers to feedback that represents a response to the stimulus. Although important, consequence does not hold the central place in the S-O-R-K-C framework that Skinner (1953) accorded it, as the behavioral response is inﬂuenced not only by the consequence, but also by other previous factors, such as the stimulus, organism, and contingencies. An implication that follows from this approach is that since the individual operates in many systems (psychological, biological, economic, and social), these systems must be considered as potential variables in behavioral analysis. Many of these social interaction patterns are operant responses with the behavioral repertoire being limited by the individuals’ biological, social, and

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intellectual competence, history of reinforcement, and the current norms of membership groups that indicate the need for behavioral assessment that is unique to the child’s environmental and behavioral characteristics. Intervention designed within this framework may consist of not only the manipulation of reinforcements but also of antecedents (Kanfer & Saslow, 1969). This framework is commonly utilized in behavioral and cognitive-behavioral interventions due to its acknowledgement of the expectancies of the individual. Despite the acknowledgement of the importance of the environment and genetic and cognitive factors, the role of the wider ecology inﬂuencing behavioral patterns is still relatively understated. C.

Ecology and the Behavior Equation: E[S-O-R-K-C]

The Bronfenbrenner (1977, 1979) social ecology theory posits that each individual is nested within multiple subsystems within the ecological context. Transactional theory proposes that the development of an individual is due to the transactional interaction between the child’s genotype, environtype, and the cumulative result of previous interactions. An attempt will be made to integrate these dimensions with the S-O-R-K-C framework. Due to the S-O-R-K-C framework’s underacknowledgement of ecology’s contribution, the E[S-O-R-K-C] model is an expansion of the S-O-R-K-C framework. Here, the ecological environment’s role, denoted by ‘E’ in the equation, is emphasized in all elements of the S-O-R-K-C framework. Hence, it is placed outside parentheses signifying its encompassing presence and inﬂuence. Its impact on each of the elements of the S-O-R-K-C framework will be expounded. 1. STIMULUS

The ecological environment determines the availability and frequency of the historical, contextual, and immediate stimuli that a child with a developmental disability encounters. This variability in experience results in children responding to the same immediate stimulus diVerently. For example, the presentation of a book may serve as a discriminative stimulus to a child who has positive experiences with print and knows to gather around the teacher to listen, whereas another child who has experienced being placed in a restraining chair during reading sessions may react with aversion. Similarly, the historical stimuli preceding an intervention session will inﬂuence an individual’s behavior. For example, a parent’s state of alcohol intoxication leading to domestic violence the night prior to an intervention session will signiﬁcantly inﬂuence the child’s behavior during the session. In this manner, children from diVerent home environments may react diVerently due to diVerential acquisition of discriminative stimuli.

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2. ORGANISM

Organismic variables, which include mediating biological, social, cultural, and cognitive variables are likewise inﬂuenced by the ecological environment. Transactional theory proposes that the ecological environment impacts child behavior indirectly through parent-child interactions. There is ample evidence suggesting that cultural factors impact upon cognitive factors, such as expectations. As mentioned, Italian parents appear to have later chronological behavioral expectations than American parents (Edwards et al., 1996). These ﬁndings provide further evidence of how the cultural background of parents inﬂuences socialization goals that, in turn, inﬂuence parenting practices and hence child outcomes. DiVerences in organismic variables will thus be manifested in diVerences in cognition, health status, and activity level, among other outcomes. 3. RESPONSE

Any behavioral response within the behavioral equation is a function of stimulus, organism, contingency, and consequence. Because ecology impacts upon each of them, it follows that ecology too will have an impact on response. These ecological inﬂuences constitute the diVerences in behavior observed between individuals of various cultures. 4. CONTINGENCY

The ecological environment shapes the response-consequence or contingency. Reinforcement schedules diVer between cultural environments. The traditional Chinese socialization strategy has been characterized as lenient and indulgent for the ﬁrst 6 years of life, but changes to strict and seemingly harsh/authoritarian parenting thereafter (Ho, 1986; Kim, 1997). Chinese disciplinary strategies traditionally involve scolding or spanking. Positive strategies, such as persuasion or praise, are rare. In this manner, there are diVerences in reinforcement contingencies and the application of punishment instead of positive reinforcement across ecological environments. 5. CONSEQUENCES

Consequences are also shaped by the ecological climate. Individuals from diVerent cultures employ diVerent methods of disciplinary control. For instance, parents from American and European cultures are more likely to apply strategies such as time-out as opposed to those from Asian cultures that may be more likely to employ physical punishment (Ho, 1986; Saraswathi & Pai, 1997). Kanfer and Phillips (1970) suggest that the environment shapes the hierarchy of reinforcers. A child with a disability who has frequent and positive exposure to a computer is likely to regard it as a reinforcing

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consequence compared to a child with a disability from a non-technological society who might ﬁnd sitting in front of a computer screen a learning rather than a reinforcing consequence. D.

Implications for Intervention

The goal of understanding the origin of challenging behaviors of individuals with developmental disabilities is driven by the need to provide appropriate intervention, with the goal of enhancing optimal long-term outcomes for children and families. Given the universal role of ecology on all aspects that inﬂuence behavior, a number of implications for intervention may be derived. 1. ECOLOGY-CENTERED INTERVENTION

An important implication that logically follows is that intervention needs to move beyond the traditional individual-focused framework to a more inclusive one that takes into account the larger ecological context. Intervention requires more than family-centered practice (Dunst & Trivette, 1996). In the case of children with developmental disabilities, there is a need to include even more than the home and family environment, corresponding to the Bronfenbrenner (1979) microsystem. The relationship between family members needs to be understood. The environment is not restricted to the home but includes the mesosystem from the Bronfenbrenner (1979) model which refers to the range of settings a family may participate within in the larger environment and includes the extended family, neighborhood, church groups, early intervention, and mental health programs. In this sense, managing challenging behaviors when they occur may not lie with ‘changing’ the child as the ideal course of action but rather the environment (i.e., stimuli) as it may be due to a lack of child-environment ‘ﬁt’ (Thomas & Chess, 1977). 2. ASSESSMENT AS INTERVENTION

Another implication of this ecological framework is the recognition of assessment as being part of the intervention process. As events from the wider ecological environment (such as home, school, and work) impact upon the individual, devising intervention entails ﬁrst developing a clear understanding of the complexities that underlie the transactions between systems. Assessment in this sense is inseparable from intervention. A useful framework that may be adopted is the dynamic assessment framework whereby the process of assessment involves an active evaluation to understand and to discover ways to overcome sources of diYculty between systems during the assessment process (Feuerstein et al., 1979).

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3. INDIVIDUALIZED INTERVENTION

The complexity of the learning process, given the ecological dimension of transactional theory, logically implies that broadly designed intervention programs cannot be implemented across groups of young children with developmental disabilities, unless these intervention programs were designed for a population largely similar in not just behavioral phenotype but also in ecological circumstances. Even so, there needs to be accommodation for individualization of such intervention programs. Philosophies such as full inclusion for children with developmental disabilities within settings for typically developing children need to recognize both inherent and ecological diVerences in children. Intervention programs need to be matched to the unique needs of children and families, and designs that adequately account for the complexity of the individual child need to be employed. VI.

CONCLUSIONS

The eYcacy of early intervention is founded on the notion that changing the child’s interactive experience with the environment alters developmental progression. With regards to the development of challenging behaviors, clearly preventing problems is preferable to the eVort required to alter established behavior problems. Understanding the source of challenging behaviors has practical implications for the design of interventions to reduce the development of avoidable secondary behavior problems that may have detrimental eVects on learning, family stress, and opportunities for social inclusion. Challenging behavior in young children with developmental disabilities is an exemplar of the perpetual quandary of the contribution of nature versus nurture to developmental outcomes. Challenging behavior is not a characteristic within a child, but is rather a transactional phenomenon with the capacity to shape the individual child’s environtype, as well as aVect that of the child’s family members (SameroV & Fiese, 2000). Although experience clearly aVects behavior, inherent characteristics provide the foundation for that interactive development. Since little or nothing can be done to alter the genotype of children with developmental disabilities, the responsibility, therefore, falls on caregivers and professionals to adapt the caregiving environment to best meet the needs of the child in order to optimize the development of positive behavioral characteristics. The interactive models described all stress the importance of early childcaregiver interaction on the development of later behavioral characteristics. Undoubtedly, child-caregiver interaction and the caregiving environment are modiﬁable aspects of the transactional relationship. Carey (1998) recommends that inherent temperamental diVerences in children are best managed

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by accommodation to reduce unnecessary stress, rather than by working against temperamental characteristics by trying to change the child. In that regard, interventions must focus on recognizing the positive potential of all children with developmental disabilities, and strive to promote longterm positive outcomes by best meeting their needs and the needs of their families. Models for reducing or avoiding diYcult behaviors must recognize the broad range of contributors. The ubiquitous eVect of poverty on children with developmental disabilities is a serious issue that cannot be overlooked. The increased frequency of mental health problems including behavior problems and mental retardation among children living in poverty has been documented (Halfon & Newacheck, 1999). The cumulative risk notion proposed by SameroV (1998) regarding long-term outcomes for children with developmental delays, underscores the importance of providing intervention programs to foster appropriate child-caregiver relationships, but also recognizes the broader ecology of the child and family as contributing to the nature of those relationships. Intervention for behavioral concerns should utilize all potential resources and recognize the importance of ecological contexts in the design of individualized intervention programs.

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Employment and Intellectual Disability: Achieving Successful Employment Outcomes KAYE SMITH, LYNNE WEBBER, AND JOSEPH GRAFFAM SCHOOL OF HEALTH SCIENCES DEAKIN UNIVERSITY BURWOOD, VICTORIA, AUSTRALIA

CARLENE WILSON DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF ADELAIDE ADELAIDE, AUSTRALIA

In this Chapter, we will review the research that has explored variables that can shape employment outcomes for people with an intellectual disability. Deﬁning ‘‘success’’ in employment outcome is diYcult—with success largely dependent on both the opportunities available, the aspirations of the potential employee in terms of hours and conditions, and the perspective of the person making the judgment. Thus, in some industries, casual and temporary employment predominate and achievement of either is deemed as ‘‘success.’’ Furthermore, individuals diVer in the extent to which they seek full-time employment; many employers and employees now prefer part-time or ﬂexible hours. Lastly, success can be judged from a variety of perspectives: the employee who asks whether he or she is content with their current employment situation, and the employer who asks whether the employee is performing in a number of areas including, but not limited to, productivity and culture ‘‘ﬁt.’’ In the current review, we will focus on determining employee success as measured by employer satisfaction and will attempt to anchor this against satisfaction with employees without disabilities. Although this is obviously only one possible way of operationalizing success, it provides the advantage of helping us understand barriers to employment outcomes for INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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people with a disability. When attempting to understand inﬂuences that aVect employment outcomes it is important to realize that inﬂuences extend beyond the workplace and those who operate within the workplace, to the broader environment (i.e., ecological system). For this reason, Bronfenbrenner’s (1989) ecological systems theory has provided the framework for reviewing research in this area. Using this framework has allowed us to conceptualize successful employment outcomes as dynamic and complex phenomena, resulting from interplay between individual, social, and environmental factors. In its most recent classiﬁcation manual, the American Association on Mental Retardation (AAMR) has spent considerable space elaborating on the contextual nature of mental retardation (AAMR, 2002). Thus, an individual’s ability to function to the full extent of his/her capabilities can be determined by ﬁve dimensions: (1) intellectual abilities; (2) adaptive behavior; (3) participation, interactions, and social roles; (4) health; and (5) context. The latter has been deﬁned to include environments and culture. The role of the service provider is to provide support that optimizes individual outcomes. In this review, we will reiterate the importance of a focus at the level of context in order to identify barriers to desired employment outcomes for people with an intellectual disability. We will argue that it is important to understand the environment in which employment of people with an intellectual disability occurs, and to recognize that barriers need to be overcome by appropriate levels of support in the immediate environment (microsystem); the neighborhood, community, or organization (mesosystem); and the overarching patterns of culture, society, country, and sociopolitical system (macrosystem or megasystem). In other words, we will endorse the contention of the AAMR that the context can and must ‘‘provide opportunities and foster well-being’’ (AAMR, 2002, p. 47). Furthermore, we will argue that it must do this consistently across contexts because opposition, particularly at a more micro-level, can eVectively interfere with support within any other contextual level. Bronfenbrenner’s (1989) ecological systems theory emphasized that a person’s development is inﬂuenced by various contexts within which the person operates, and that the person in turn inﬂuences these contexts. This theory described an ecological hierarchy of four levels: (1) microsystem, (2) mesosystem, (3) exosystem, and (4) macrosystem. The microsystem comprised interrelationships between an individual and a speciﬁc environment in which the person operates, including interrelationships with others within that environment. The mesosystem comprised interrelationships that occur between the diVerent microsystems in which the person operates, while the exosystem was described as an extension of the mesosystem and included at least one additional environment in which the person does not usually operate, but which nonetheless impacts the person. For an employee with an intellectual

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disability, a microsystem would be the workplace, including relationships that occur therein; a mesosystem would include other microsystems in which the person operates, such as their home environment; and a exosystem could be the environment of the disability support service that assists the person in their employment. The fourth level, the macrosystem, comprised the prevailing belief system and culture within which the microsystem, and exosystem are embedded. Aspects, such as attitudes of the wider community toward people with an intellectual disability and anti-discrimination legislation, would be part of the macrosystem. Therefore, this theory extends the focus of development beyond the individual to other factors that aVect performance. Recognition of the importance of ecological factors on a person’s participation is also consistent with a social model of disability (Barnes, 1998). An appreciation that a complex interaction of contextual factors can aVect the achievement of successful employment outcomes, has guided the review of research undertaken in this Chapter. This Chapter will begin with an overview of the literature and research of immediate relevance at the macrosystem level, including changes in how ‘‘disability’’ has been understood in relation to the broader ecological context, and the prevailing belief system and culture in which employment, intellectual disability, and other forms of disability are embedded. The second Section of the Chapter will focus on research more directly predictive of successful employment outcomes of people with an intellectual disability, multiple disabilities, and other forms of disability. The third section will discuss the future directions for maximizing successful employment outcomes of people with an intellectual disability.

I. PERCEPTIONS OF DISABILITY INCLUDING INTELLECTUAL DISABILITY AT THE MACRO LEVEL AND IMPLICATIONS FOR EMPLOYMENT How intellectual disability and other forms of disabilities are perceived in relation to the broader ecological context has been the subject of debate in recent years. ‘‘Disability’’ is a complex multidimensional and dynamic concept, and one that has been subject to various interpretations. Altman (2001) argued that concepts of disability for research purposes reﬂect a growing awareness of the multiple factors that impact on disability. He reported that disability has been described from various perspectives, including economic, administrative, medical, and socio-political. An important and well documented conceptual shift in recent years has been from a medical to a social understanding of disability, in which disability is no longer understood solely in terms of personal attributes but also as a concept that involves the physical, social, and cultural

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aspects of those environments in which a person operates (Bickenbach et al., 1999; Shakespeare, 1998; Shakespeare & Watson, 2000; World Health Organization, 1997). Under the medical model, strategies aimed at rectifying the ‘‘problem’’ are geared toward the individual. The social model of disability, on the other hand, understands disability as a socially constructed issue (Oliver, 1990). The social model considers the physical and social environments as the cause of disadvantage, and subsequently these become the foci of attention and intervention. Whereas the medical model has focused interventions on the individual and tended to ignore the impact of the environment on the individual, the social model has concentrated on the environment and tended to ignore the impact of the individual’s condition on the individual’s experiences. However, Albrecht and Bury (2001) cautioned against the oversimpliﬁcation and categorization of disability into discrete frameworks, such as medical or social. They argued that disability is a complex phenomenon and more recent conceptual understandings of disability recognize the importance of the interrelationship between the individual and their environment. Recognizing the importance of this interrelationship is consistent with Bronfenbrenner’s (1989) ecological systems theory. The World Health Organizations (WHO) (2001) International Classiﬁcation of Functioning, Disability, and Health (ICF) uses a biopsychosocial approach to their classiﬁcation of disability and functioning. The multiperspective approach advocated by the WHO is a blending of both the medical and social models. The ICF is a revision of the 1980 International Classiﬁcation of Impairments, Disabilities, and Handicaps (ICIDH). Whereas the ICIDH had a focus on the ‘‘consequences of disease,’’ the focus of the ICF is on the ‘‘components of health.’’ The ICF understands ‘disability’ as an umbrella term that not only covers ‘impairment,’ but also ‘activity limitations’ or ‘participation restrictions.’ In considering activity and participation, the focus is on contextual factors. The ICF also diVers from the ICIDH in recognizing the importance of the interrelationship between the individual, and environmental and personal factors. Although personal factors are not classiﬁed in the ICF, they are nonetheless recognized as important. That is, the WHO now recognizes disability as a complex phenomenon that both inﬂuences and is inﬂuenced by a range of contextual variables. Although the importance of understanding disability, including intellectual disability, within a broader ecological context has been well documented, in countries such as Australia (Carney, 2000), the U.S., and many Western European countries (O’Day & Berkowitz, 2001; Thornton & Project Team of Experts, 1998) eligibility for a disability support pension is still based on criteria of functional incapacity. Thus, these criteria deﬁne disability as a biomedical construct (Meijers, 1997). Furthermore, eligibility for a support

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pension determines eligibility for other services, including disability employment services. This form of assessment, based on the medical model, places the source of disability and hence, eligibility, within the body, rather than within the broader environment. Thus, people are categorized and become eligible for government support solely on the basis of a biomedical understanding of disability. Employment, however, is contextually based; achieving successful employment outcomes for all employees is dependent on a range of contextual variables, such as employer attitudes, workplace culture, physical accommodations, and government policies. Hence, basing eligibility for employment support exclusively on a medical assessment has questionable validity. A.

The Context of Employment and Intellectual Disability

Historically, employment has inﬂuenced society’s perception of people with an intellectual disability as well as other forms of disability. Industrialization, with a need to work at a set rate in spaces that were often cramped and diYcult to access, contributed to the exclusion of people with a disability, including intellectual disability, from economic participation in their communities (Marks, 1999; Oliver, 1990). People with a disability were seen as ‘‘unable’’ to work, rather than ‘‘unwilling’’ to work; a distinction that deemed them worthy of assistance from society. Disability was commonly understood as ‘‘work disability’’ (Bickenbach, 1996). However, for people with an intellectual disability, being labeled as ‘‘employable’’ or ‘‘unemployable’’ has been a transient rather than ﬁxed concept, and one that can be linked to the broader environment in which employment occurs. Bickenbach (1996) has pointed out, for example, that during times of acute labor shortage, such as war-time, many people with a disability, who had previously been institutionalized and viewed as ‘‘unemployable,’’ were successfully employed in the community or conscripted into the armed services, only to be returned to their institutions as available labor increased at the end of the war. This illustrates that complex relationships between political, economic, and social factors can contribute to the designation of people with a disability as ‘‘employable’’ or ‘‘unemployable.’’ People with a disability have experienced many forms of exclusion. Ravaud and Stiker (2001) distinguished between early forms of exclusion, which focused on exclusion from society (for instance, killing or abandoning those with a disability), to more recent forms, which focus on exclusion within society (for instance, discrimination or segregation in areas such as employment). Albrecht et al. (2001) suggested that people with mental conditions were more likely to be separated within their communities than those with physical disabilities. The history of people with a disability in society is one that recounts various forms of oppression including stigma,

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segregation, sterilization, and physical and emotional abuse. It is also one that describes recent collective struggles for human rights and dignity (Braddock & Parish, 2001). How disability is understood is subject to the speciﬁc cultural, social, and economic contexts; disability as a concept is dynamic. Russell (1998) argued that limited and ﬂawed information has contributed to negative attitudes held by employers. There is a long history of people with a disability experiencing economic and cultural disadvantage in western societies. Economically, people with a disability have been considered one of the most disadvantaged groups in society (Schriner, 2001). Whereas, economic independence and empowerment can promote inclusion in the social, political, and cultural domains of society, economic dependence can result in social exclusion. Alston (1995) highlighted a link between economic independence and the exercise of various rights and freedoms: ‘‘Unless the economic and social rights dimension is also addressed, the enjoyment of civil and political rights can easily become largely illusory’’ (p. 96). The Australian Institute of Health and Welfare (1999) has reported a much lower rate of employment participation (53.2%) for people with a disability than for people without a disability (80.1%). Schriner (2001) gave a similar account of the employment situation for people with a disability in both Canada and the U.S. Furthermore, the International Labour Organisation (ILO) has highlighted an interrelationship between disability and poverty, with disability contributing to poverty and poverty contributing to disability (Vocational Rehabilitation Branch–ILO, 1999). This interrelationship is important, given that poverty has been linked to a restriction in the exercise of social and economic rights (Beresford, 1996; Marks, 1999). On the other hand, employment, with its resultant economic beneﬁts, is an important route to the exercise of social, political, and economic rights. As evidence of this, recent Australian research has shown that people with an intellectual disability who are employed in the community experience a higher quality of life than those with an intellectual disability who are either unemployed or in sheltered employment (Eggleton et al., 1999). From an ecological perspective, interest in achieving successful employment outcomes for people with a disability, including those with an intellectual disability, extends beyond those at the microsystem (employers, employees with a disability, disability employment professionals), mesosystem (families, advocates), and exosystem (government funding departments, and so forth) levels. This interest is also driven by broader political, social, and economic imperatives at the macrosystem level. The ILO (Vocational Rehabilitation Branch–ILO, 1999) presented examples of three macro-level imperatives for urgent attention in order to improve employment outcomes of people with a disability. One was the increasing worldwide political pressure for both social and economic inclusion of people with a disability,

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including those with an intellectual disability. Pressure from various civil rights groups in addition to international treaties, documents, and local legislation have provided an increasing demand for supporting equality of opportunity and non-discriminatory practices in employment. A second imperative was the large and increasing numbers of people with a disability— estimated by the ILO to be approximately 10% of the population. The ILO noted that whatever the ‘‘head count’’ for the proportion of people with a disability, the social and economic outcomes have much wider impact. A third imperative was the considerable cost implications that result from excluding people with a disability from employment. The ILO argued that, rather than investing resources in the form of beneﬁts, resources should be invested in assisting access to employment (Vocational Rehabilitation Branch–ILO, 1999). Thus, not only does society impact on people with an intellectual disability, but also excluding such people from employment impacts the social, economic, and political fabric of society. The macrosystem in which employment and disability occur reﬂects concerns with social justice. These concerns have been evident in the rhetoric adopted by employment-related organizations surrounding the employment of people with a disability. Organizations, such as the European Trade Union Committee, International Labour Organisation, and United Nations Economic and Social Council, have all supported the equalization of opportunities for people with a disability, including an intellectual disability, in relation to employment (European Trade Union Committee, 1995; International Labour OYce, United Nations Educational Scientiﬁc and Cultural Organization, & World Health Organization, 1996; United Nations Economic and Social Council, 1995). The ILO Convention No. 159 (1983a) and ILO Convention 168 (1983b) both support workplace inclusion for people with a disability. Many of the initiatives important to the ecological system in which employment and disability are embedded derive from human rights’ initiatives at the macrosystem level. Anti-discrimination legislation is an example of such initiatives. For example, the Australian Disability Discrimination Act (1992) has been enacted to enforce many of the human rights obligations endorsed by Australia, and the Americans with Disabilities Act (1990) has been used in a similar way in the U.S. These legislations require employers, at the microsystem level of the workplace, to introduce practices that allow equality in terms of opportunities for people with a disability. Although anti-discrimination legislation operates at the macrosystem level and impacts on the lives of people with a disability at the microsystem, its implementation was largely due to eVorts by grass-roots activists operating at the microsystem level. This process demonstrates the important interrelationship between diVerent levels of the ecological system.

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Another inﬂuence at the macrosystem level, which also has an important impact at the microsystem level of the workplace, is the increase in the diversity of the population and subsequently the workforce. The increase in the ratio of women, immigrants, older workers, and minority groups in the workplace has resulted in an increased interest in workplace diversity (Bond & Pyle, 1998; Stoner & Russell-Chapin, 1997). Several authors (Gilbert & Ones, 1998; Richard, 2000; Williams & Bauer, 1994) have outlined beneﬁts associated with workplaces in which diversity is well managed. Hicks-Clarke and Iles (2000) showed that a workplace culture in which diversity was valued beneﬁted work satisfaction and commitment of the employees. Nonetheless, Stoner and Russell-Chapin (1997) argued that, despite greater diversity in the workplace, many employers have not adopted practices to beneﬁt from this change. Employees with intellectual and other disabilities are part of a diverse workforce and their work performance has tended to be well regarded by employers (Hill & Wehman, 1979; Kregel & Unger, 1993; Ravaud et al., 1992; Reisman & Reisman, 1993). However, for many employees with a disability the major barrier to successful job performance is a lack of workplace accommodations that will help them prosper in their job (Hendricks, 1995; Lunt & Thornton, 1994). In part, this has been recognized in countries such as Canada, Australia, and the U.S., where the role of the workplace environment in promoting or impeding successful employment outcomes has been acknowledged both by the adoption of workplace practices to accommodate diversity (Bond & Pyle, 1998; Brady, 1996; Iannuzzi, 1997; LiV & Wajcman, 1996; Lynch, 1997; Stoner & Russell-Chapin, 1997) and by anti-discrimination legislation (e.g., ‘reasonable accommodation’ requirements). These policies and practices at the cultural and political level, together with research conﬁrming the satisfactory work performance of employees with a disability, should have a direct bearing on practices adopted in employment settings; yet high levels of unemployment for people with a disability suggest that this outcome has not been achieved. Changes at the macro level that do not translate to the workplace have been found in relation to anti-discrimination legislation. For example, a study by Trupin et al. (1997) used data from the U.S. National Health Interview survey to show that implementation of the Americans with Disabilities Act (1990) had not been successful in increasing the employment rate of people with a disability. Similarly, Sidoti (1998), then Acting Disability Discrimination Commissioner in Australia, commented on a similar lack of improvement in employment rates following the promulgation of the Disability Discrimination Act (1992). Nonetheless, those operating in the workplace have recognized the importance of macrosystem inﬂuences for achieving successful employment outcomes for people with a disability. In a recent Australian study, Smith (2002)

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interviewed 50 managers and supervisors who had employed someone with a disability (approximately 40% of whom had mental retardation or a learning disability), and 40 disability employment service providers. The majority from both respondent groups identiﬁed the Disability Discrimination Act (>70%), had attitudes favoring social justice (>80%), and reﬂected disability awareness (>80%) as important for achieving successful employment outcomes. Thus, even though human rights measures at the macro level may not have the desired inﬂuence on workplace practices, those directly concerned with achieving successful employment outcomes in the workplace nonetheless recognized their relevance. The context in which employment and disability operate is complex, and it would be naive to expect a direct path from legislation to workplace change. As Bronfenbrenner (1989) has emphasized, it is the interaction between and among various ecological factors, rather than a single factor, that inﬂuences behavior. Hence, in addition to an array of changes, which occur at broader ecological levels, research more directly related to the workplace, including research that seeks the views of those who operate within the employment context, would be expected to aVect employment outcomes directly.

II. PRACTICES THAT PROMOTE SUCCESSFUL EMPLOYMENT OUTCOMES FOR PEOPLE WITH INTELLECTUAL DISABILITY A.

History of Disability Employment Support

Eligibility for disability employment services in many countries is commonly established by way of an economic administrative category. Typically, such systems have in the past ignored the powerful inﬂuence of contextual variables on employment outcomes. However, the development of disability employment service provision since the 1980s has reﬂected a more enlightened view, consistent with an emerging understanding of disability and employment as complex phenomena, the inﬂuences on which are diverse. In Australia, government funding for competitive employment services has been available since the introduction of the Disability Services Act (1986). This funding closely followed mounting international evidence, principally from the U.S., supporting positive employment outcomes for people with a disability (Brolin & Brolin, 1982; Kregel et al., 1990; Rusch & Hughes, 1990; Wehman, 1988). Employment service provision has emerged from an early focus on simply matching the individual’s skills to the requirements of the job (Brolin & Brolin, 1982; Callahan & Garner, 1997), to more recent approaches that have increasingly recognized the important interplay

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between the individual and the complex network of contextual factors in which disability and employment are embedded. Initially, if a person had the skills for the job, they were deemed suitable for the position. Employment strategies were geared toward training the individual to perform assigned tasks at an acceptable rate and quality (Callahan & Garner, 1997). These strategies were closely aligned to an understanding of disability consistent with the medical model. The focus was on the initial placement of an individual in a speciﬁc job, with an emphasis on ﬁtting the person to the job, not on changing the workplace environment to accommodate the person. Training was the domain of the disability employment professional and was focused on bridging the gap between the skills of the employee and the demands of the job (Callahan & Garner, 1997; Moon & GriYn, 1988; Renzaglia & Hutchins, 1988; Rogan et al., 1993). B.

Current Trends in Disability Employment Practices

Subsequent redirection of policies has recognized the relevance of the workplace environment to achieving successful employment outcomes. The culture within the workplace has increasingly been viewed as critical (Callahan & Garner, 1997; Hagner, 1992) and placement practices have increasingly embraced work-related ancillary skills, such as the ability to form friendships, to conform to the required rules in the work place, to interact positively with supervisors and coworkers, and to be able to access the wider work environment. Such practices have been referred to as achieving a ‘‘person-environment ﬁt’’ (Calkins & Walker, 1989; Schalock, 1989). According to this view, not only is it important to be able to perform the job, it is also important for the employee to feel accepted in the work environment and to be accepted as a valued staV member (Hagner, 1992). Person-environment ﬁt places both job skills and social behaviors under the spotlight; both need to be compatible with the work environment. Social behaviors of people with an intellectual disability have been considered an important aspect of successful employment outcomes (Butterworth & Strauch, 1994; Ferguson et al., 1993; Holmes & Fillary, 2000; Martella et al., 1993; Salzberg et al., 1986). Butterworth and Strauch (1994) showed that both task and non-task related social skills contributed to supervisor and co-worker ratings of the quality of work performance. Nonetheless, although the social skills and social competence measured were shown as important to the development of social relationships, the contribution was small. Physical integration, not social integration, in the workplace was considered successful for the 98 subjects in the Butterworth and Strauch (1994) study. Salzberg et al. (1986) identiﬁed task-related social skills as important to entry-level employment. Martella et al. (1993) showed that

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individuals with an intellectual disability could be taught certain task-related social skills (such as asking for assistance) using verbal problem-solving strategies. Holmes and Fillary (2000) have pointed out that, although casual workplace interactions are important for social integration, such interactions require complex social skills that typically take years to acquire through exposure to diVerent social contexts. Therefore, Holmes and Fillary (2000) advocate that strategies need to be devised to provide this exposure. Although the importance of social skills places the focus on the individual, it is, nonetheless, recognition of the need to attend to the interrelationship between the individual and their environment. In other words, the speciﬁc social skills required to operate within a speciﬁc context (e.g., the speciﬁc employment site and speciﬁc coterie of coworkers and customers) must be the focus of any targeted training or support. Recognizing the importance of the social environment to satisfactory employment outcomes is consistent with the social model of disability (Bickenbach et al., 1999; Lunt & Thornton, 1994). Rather than expecting a person with a disability to ﬁt into a static work environment, there is a realization that environments can also change to accommodate individual needs. Employers have become important stakeholders in the development of placement strategies and, therefore, have become increasingly viewed as part of the ‘solution’ rather than as ‘barriers’ to eVective employment outcomes (Flexer et al., 1994). In addition, collaboration with people with a disability has gained momentum in being considered an important aspect of employment service provision (European Trade Union Committee, 1995; Parent et al., 1996). Flannery, Slovic, Treasure, Ackley and Lucas (2002) argued for the importance of ensuring that people with a disability have the necessary skills and knowledge to be active partners in identifying their employment goals and the necessary resources to achieve these goals. Thus, the importance of sharing responsibility for eVective employment outcomes between service providers, employers, and employees with a disability has become evident (Albin, 1992; Fabian et al., 1994). In addition, past reviews of employment for people with an intellectual disability (Gold, 1973; Kirby, 1997) concluded that more research was needed that involved the employer and placement agency because both recognized that these people played an important role in the future employment of people with intellectual disabilities. It has also been argued that these partnerships assist integration and job tenure (Fabian et al., 1995). The value of a partnership approach for successful employment outcomes appears to have gained recognition and widespread acceptance among academics and policy specialists during the past decade (Albin, 1992; Brooke et al., 1998; European Trade Union Committee, 1995; Fabian et al., 1995; Flexer et al., 1994; Kenny, 1995; Mank et al., 1998; Nietupski et al., 1996;

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Peterson, 1995; Petty & Fussell, 1997; Rhodes et al., 1991; Stansfeld et al., 1995; Thornton & Project Team of Experts, 1998; Vocational Rehabilitation Branch–ILO, 1996). However, despite the changing paradigm within which academics have viewed employment, changes in employment practices have been slower. Thus, although collaboration with people with a disability is now a requirement for services funded under the Australian Disability Services Act (1986), collaboration with employers has not been a requirement for funding under this legislation. This is despite the fact that directing responsibility for successful employment outcomes from disability employment professionals to employers has been shown to improve job-retention (Fabian et al., 1993). Involving employers in service provision shifts the role of disability employment professionals from being the sole provider of services, to one that facilitates supports in the workplace; disability employment professionals become consultants to the organization (Trach & Sheldon, 1999). In addition to concerns about the compatibility of individuals and the workplace environment (person-environment ﬁt), attention has also been directed at ensuring that intervention programs are compatible with workplace environments (Callahan, 1992). This concern with designing program implementation to be compatible with a range of aspects in the work environment has been termed ‘‘program-environment’’ ﬁt in the literature (Calkins & Walker, 1989; Schalock, 1989). Program-environment ﬁt is consistent with the view that no single model of service provision works best. Rather, intervention programs need to be tailored to speciﬁc individuals and speciﬁc work environments (Buckley et al., 1990). Importantly, the recent literature provides support for positive relations between program-environment ﬁt and job retention (Calkins & Walker, 1989; Schalock, 1989). Beneﬁts from approaches that actively involve those other than disability employment professionals (employers and co-workers) in the delivery of workplace training have been recognized (Callahan, 1992; Fabian et al., 1995; Hagner et al., 1992; Mank et al., 1998). For example, Mank, O’Neil, and Jensen (1998) examined the main features of a demonstration project in the U.S. that resulted in the employment of 55 people with a developmental disability (95% of whom had an intellectual disability). These 55 employees had worked an average of 3 years and received 3 times the wage and beneﬁt outcomes of other nationally supported employees. Mank et al. (1998) stressed the importance of developing strong relationships between employers and service providers, in particular the importance of a commitment from managers and coworkers and the active involvement of co-workers in training and supporting employees with a disability. Fabian et al. (1995) also stressed the importance of a close collaboration between employers and service providers; they argued that, rather than simply focusing on an employee’s ability to perform the job, service providers need to also

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include the performance of their own service to an employer when assessing employer satisfaction. Furthermore, Fabian et al. (1995) reasoned that engaging employers in training their employee with a disability promoted workplace integration. Anti-discrimination laws in countries such as Australia, Canada, and the U.S. place requirements on businesses to make reasonable accommodations to workplaces, in order to promote equal access to employment opportunities for people with an intellectual and other form of disability. Identifying and implementing accommodations, in collaboration with employers (an aspect of program-environment ﬁt), are considered important strategies for service providers when promoting job retention (Roessler & Rumrill, 1995; Rumrill et al., 1998; Thornton & Project Team of Experts, 1998). Recent approaches to employment have focused on identifying variables important to job retention. For example, job retention and return to work were the focus of an international research project by Thornton and Project Team of Experts (1998). This project was a joint initiative of the ILO and the Global Applied Disability Research and Information Network on Employment and Training, and involved participants from several countries. These researchers noted that internationally, largely due to legal and economic imperatives, the business sector has shown an increased interest in retaining employees with a disability, including those with a deteriorating mental condition. This has resulted in businesses developing policies and practices to minimize turnover of employees with a disability. Thornton and Project Team of Experts (1998) considered that this level of interest in job retention was not as strongly embraced by disabled people’s organizations, where entry to work, rather than job retention, was the overriding concern. The importance to job retention of involving key players, including employees with a disability, in the development and implementation of policies and practices was highlighted by these authors, as was the importance of changing physical aspects of the workplace and workplace practices to accommodate the needs of people with a disability. The ILO has also reinforced adopting a partnership approach between those operating in the employment context (the employee with a disability, employers, co-workers, and service providers) to ensure ongoing support. That is, the environment in which employment is embedded impacts on employment outcomes. Because of the dynamic nature of the work environment, including those operating within the workplace, interactions among variables inﬂuencing employment outcomes will also operate dynamically. It is this changing nature in the composition of variables operating in the ecological system, which impacts on employment outcomes for a worker with a disability, and which highlights the importance of a ﬂexible and long-term approach to support strategies. Yet little or no research has focused on the dynamic

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interplay between variables that aVect employment outcomes of people with a disability. The literature reviewed thus far suggests that successful employment outcomes for workers with an intellectual disability are inﬂuenced by both the interaction of the person with the work environment (person-environment ﬁt) and the strategies adopted (program-environment ﬁt). In addition to service provision strategies, which reﬂect a growing appreciation of the importance of the environment for achieving successful employment outcomes, research has also been concerned with the views of employers. Because of the central decision-making role held by employers, their opinions, attitudes, and behavior toward the employment of someone with a disability contribute an important inﬂuence on the ecological system in which disability and employment are embedded; an ecological system that inﬂuences whether employment outcomes are successful or not. C.

The Perceptions and Attitudes of Employers

In this section, we shall ﬁrst overview the literature that has examined the attitudes and the importance of strategies that promote the job retention of people with a disability (Vocational Rehabilitation Branch–ILO, 1999). A recent trend in the disability employment literature has involved a focus on ‘natural supports’ (Butterworth et al. 1996; Callahan, 1992; Fabian et al., 1995; GriYn, 1994; Hagner et al., 1995; Mank et al., 1997; Sandow et al., 1993). Cimera (2001) has argued that deﬁnitions of natural supports are varied and numerous. Butterworth et al. (1996) provided the following deﬁnition of ‘natural supports’: ‘‘Assistance provided by people, procedures, or equipment in a given workplace that (a) leads to desired personal and work outcomes, (b) is typically available or culturally appropriate in the work place, and (c) is supported by resources from within the work place, facilitated to the degree necessary by human service consultation’’ (p. 106). Although supports may be considered ‘natural’ to the workplace, their successful implementation often requires extensive planning (Trach & Mayhall, 1997; Trach & Sheldon, 1999). Providing ‘natural supports’ for disability employment can involve: tapping into training that is available to other employees; training co-workers to train employees with a disability; partnership development; and the execution of training programs that incorporate, as near as practicable, training strategies used in that particular work environment. By identifying factors and processes that promote successful employment outcomes, employment programs that encompass the use of ‘natural supports’ take an approach that considers a range of factors in the context of the workplace. Taking a contextual approach provides a social

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perspective to disability employment policy, one that extends the focus of intervention beyond the individual to the environment in which they work (Lunt & Thornton, 1994). A recent study by McHugh et al. (2002) indicated that the use of natural supports by three job coaches increased workplace integration for each of three targeted employees with a developmental disability (one per job coach). This study comprised: training the job coaches to implement a range of natural support strategies; recording the use of natural support strategies; using the Vocational Integration Index to record indicators of vocational integration; and using a social validation assessment instrument to record the views of the employer on four questions related to social integration in the workplace. Although the social validation assessment returned mixed results, the Vocational Integration Index showed a general increase in all four areas of vocational integration, with all three employees showing an increase in the area of employee beneﬁts. The notion that ‘natural supports’ can facilitate employment outcomes for people with a disability is consistent with research by Mank et al. (1998), which has demonstrated the important relationship between workplace practices and employment outcomes. As mentioned previously, employment outcomes in this program showed 3-year average job tenure and three times the wage levels of the average competitive employment placement. Characteristics of their employment program included: co-worker involvement in the design and delivery of supports; partnership development; a workplace culture that valued and managed diversity; and long-term support. Of the 55 participants in this program, 34 with a developmental disability continued to receive long-term support. Post-placement support has been considered an important component of service delivery for promoting job retention (Brooke et al., 1998; Rumrill et al., 1998) and career advancement (Brooke et al., 1998). These authors (Brooke et al., 1998; Rumrill et al., 1998) also recognized the importance of within the general population of employers, some of whom have employed people with a disability, before proceeding to the literature that has speciﬁcally targeted attitudes of employers who have used a disability employment service. Overall, this literature suggests that many factors interact in aVecting employers’ attitudes. Russell (International Labour Organisation Report, 1998) has argued that inappropriate information has contributed to prejudicial attitudes among employers about people with a disability. Both disability employment professionals and employers have identiﬁed disability awareness training as an important strategy in improving the employment outcomes of people with a disability (Smith, 2002).

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Tse (1994) sought the views of 38 employers in Hong Kong who had employed someone with a mild intellectual disability. Tse reported that the majority of these employees had received some training since commencing work, but had been given no additional support. The employers’ expectations for employees with an intellectual disability had been met or exceeded in all but 5 of the 25 performance areas rated. Although performance by workers with mental retardation was signiﬁcantly higher in seven areas, including speed, reliability, and willingness to work hard, the wage earned by these employees was 30% less than co-workers without a disability performing similar work. Tse suggested that although lower wages in some circumstances could result from lower productivity rates, the lower wages reported here reﬂected discrimination against employees with an intellectual disability, given that employers indicated that the productivity of mentally retarded workers was adequate. A range of variables has been found to inﬂuence employers’ attitudes toward employing someone with a disability. For example, the existence of policies on employing someone with a disability (Jones et al., 1991); higher levels of education among managers, having a female manager, and/or being a public sector employer (Levy et al., 1992); previous contact with a person with a disability, and level of disability (mild, not moderate intellectual disability) (Rimmerman, 1998) have all been associated with more favorable attitudes toward the employment of people with a disability. However, the inﬂuence of some variables has not been consistent across studies. Thus, whereas Levy et al. (1993) and Rimmerman (1998) found that larger organizations held more positive attitudes, this was not the case in a study by Kregel and Tomiyasu (1994). Furthermore, previous contact with people with a disability was found to be a predictor of favorable attitudes by Rimmerman (1998) but not by Florey and Harrison (2000) or by Levy et al. (1992). This inconsistency between studies suggests the importance of the interplay between contextual variables. That is, ‘predictors of favorable attitudes’ do not operate in isolation; rather, they are in turn subject to inﬂuences from other variables operating within the employment context. Nonetheless, one variable appears more reliable when predicting employers’ favorability in attitude toward employees with an intellectual or other disability, namely, previous positive experience with a person with a disability that is work-related (Levy et al., 1992, 1993; Rimmerman, 1998; Smith, 2002). This suggests that experience with just one employee with an intellectual disability can impact the future employment opportunities of others with an intellectual disability, and highlights the importance of working with employers to ensure their satisfaction with an employment outcome.

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Employer Satisfaction With Work Performance

Although positive experience in employing someone with a disability appears to be an important determinant of positive employer attitudes toward other people with a disability, little research has examined the eVect of diVerent aspects of the employees’ work behaviors on employer satisfaction. Furthermore, much of the research related to employment outcomes for people with a disability has tended to focus on practices at just one speciﬁc level of the ecological system—such as the workplace environment— rather than take a broader ecological approach. Recently, Smith (2002) used Bronfenbrenner’s (1989) ecological systems theory as a framework for articulating how variables internal and external to the workplace environment might inﬂuence employment outcomes. Smith’s work comprised two major studies: one that explored variables within the workplace (e.g., speed/rate or work) important to employer satisfaction (Smith et al., in press), and one that identiﬁed contextual factors (e.g., community attitudes) important to successful employment outcomes (Smith, 2002). Smith et al. (in press) examined questionnaire responses from 656 employers, each of whom had employed a person with a disability, using the services of a disability employment agency. Approximately 47% of these employers employed a person with an intellectual or learning disability. Comparing the employer ratings on employer satisfaction and work performance between employees with and without a disability yielded three interesting ﬁndings. First, employers rated employees with a disability signiﬁcantly lower than other employees on employer satisfaction and on each of three work performance variables tested. The variables represented were: work performance; speed/rate and accuracy/quality of work, and workplace climate (an amalgam variable that included work group eYciency, supervisor eYciency, impact on workplace morale, behavior of co-workers, inclusion in team, consistency of work behavior, and stability of social behavior). Second, although all three work performance variables inﬂuenced employer satisfaction with employees with a disability, only workplace climate inﬂuenced employer satisfaction with other employees. Third, employers were more satisﬁed with employees with a disability than other employees in relation to the three variables representing work performance. Taken together, these ﬁndings suggest that employers have diVerent expectations for their employees with a disability than for other employees. This highlights the complex interplay between variables at the microsystem level of the workplace in determining employer satisfaction. Although reasons for diVerences in the relative eVect of the work performance variables could not be identiﬁed, Smith et al. (in press) and colleagues speculated that the employers’ expectations and concerns could be responsible.

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This would be consistent with work by Nietupski et al. (1996), who identiﬁed a lack of necessary work skills among people with a disability as an important concern to potential employers. Finding that the same determinants of employer satisfaction are not common to all employees has important practical implications for service provision, and supports the view that employer satisfaction is sensitive to a complex interplay between factors that occur within the microsystem of the workplace. The study by Smith and colleagues (in press) compared two groups of employees: those with and those without a disability. An earlier study by Salzberg et al. (1986) was concerned with the diVerences in determinants of successful employment outcomes for employees with an intellectual disability in diVerent kinds of jobs. These researchers reported diVerences in the relative importance of certain work behaviors between diVerent job types. They suggested that such diVerences were related to the perceived importance of these behaviors to employee productivity. Smith (2002) also investigated whether the employers’ perceptions of jobmatch aVected employer satisfaction. Path analysis showed that job-match had both a direct eVect and an indirect eVect on employer satisfaction (through the three work performance variables previously described for Smith et al. (in press)). Second, almost all employers who rated their satisfaction with their employee with a disability as equal to or higher than their satisfaction with other employees, identiﬁed their employee with a disability as well matched to the job. The ﬁnding that the employers’ perceptions of job-match were related to their satisfaction has important implications for service provision. If the goal is to achieve positive employment outcomes, then involving employers in decisions relating to the job-match process, so that a positive perception of job-match is developed and maintained, should help to support this goal. Results from the Smith (2002) analysis were consistent with the literature previously described that has recognized the importance of employer participation in achieving successful employment outcomes (Albin, 1992; Brooke et al., 1998; European Trade Union Committee, 1995; Fabian et al., 1995; Kenny, 1995; Mank et al., 1998; Nietupski et al., 1996; Peterson, 1995; Petty & Fussell, 1997; Rhodes et al., 1991; Stansfeld et al., 1995; Thornton & Project Team of Experts, 1998; Vocational Rehabilitation Branch–ILO 1996). In response to the question as to whether employer satisfaction with employees with a disability aVected future hiring intentions toward other people with a disability, Smith (2002) found that, when employers rated their employee with a disability higher or at the same level as other employees on employer satisfaction, they were much more likely to report an intention to employ a person with a disability in the future than employers who rated

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employees with a disability lower on employer satisfaction. This ﬁnding is consistent with previous research linking a positive work-related experience when employing someone with a disability with the employers’ favorable attitudes (Diksa & Rogers, 1996; Florey & Harrison, 2000; Levy, 1992, 1993; Rimmerman, 1998). This suggests that the employers’ positive experiences with one employee with a disability can aVect the future employment intentions for other people with a disability. This generalization from past experience to future intention to employ someone implies that many employers are treating people with a disability as an homogenous group. This has serious implications for service provision, suggesting that when employers are less satisﬁed with their employee with a disability than with their other employees, the employment opportunities for other people with a disability are aVected. Thus, unfair discrimination against other people with a disability in their employment endeavor is a possible outcome. Millington et al. (2000) have warned against this possibility, emphasizing, that ‘‘unfair discrimination is the logical interpretation of biased values attached to the job candidate’’ (p. 42). A second study by Smith (2002) sought the views of employers and service providers on aspects important to employment outcomes for people with a disability. An ecological framework was used to interpret data from the following three sources: (1) interviews with 50 disability employers (employers who had employed a person with a disability through a disability employment service, 40% of whom had employed someone with an intellectual disability or a learning disability); (2) interviews with 40 disability employment service professionals; and (3) survey responses from 36 nondisability employers (employers who had not employed someone with a disability) to open-ended questions. Two thematic analyses were undertaken to identify the importance of factors at the levels of the micro-, meso-, exo-, and macro-systems. The ﬁrst was based on interviews with disability employers and service providers. Interviewees identiﬁed characteristics at the micro, meso, exo, and macro levels that they considered important for successful employment outcomes. Smith (2002) found support for the impact of context on concern. Service providers, whose involvement with employees with a disability extends beyond the workplace, were more attuned than employers to aspects external to the workplace that can aVect successful employment outcomes, such as access to support services and education. Nonetheless, both employer and union organizations have emphasized these broader concerns. For example, an International Labour OYce report by Russell (1998) argued that a lack of appropriate skills (academic and practical), rather than ‘‘inherent capacity,’’ prevented people with a disability, including those with an intellectual disability, from achieving successful employment outcomes. The European

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Trade Union Committee (1995) advocated the importance of broader ecological factors in promoting successful employment outcomes for people with a disability. In addition to aYrming the importance of relevant experience and qualiﬁcations in achieving economic and social integration, the European Trade Union Committee also identiﬁed other factors, such as adequate housing and transport. Using an ecological framework provided Smith (2002) with a model for understanding the similarities and diVerences in the responses of service providers and disability employers. Nonetheless, the model could not explain why the majority of disability employers, but not service providers, identiﬁed ‘relationships between employers and service providers’ as important. This relationship occurs in the work environment—the microsystem common to both respondents. Smith (2002) suggested that this unexplained discrepancy could indicate that service providers were underestimating the importance of their services to employers. Consistent with this interpretation, a study by Fabian et al. (1995) also found that employers placed greater emphasis on the importance of service provision than service providers themselves. Because service providers support work performance, a behavior shown as important to employer satisfaction (Smith et al., in press), service providers, in undervaluing the importance of their services to employers, might be missing worthwhile opportunities for promoting successful employment outcomes. The second thematic analysis used the views of three groups of respondents—two groups of employers (disability employers and non-disability employers) and one group of disability employment service providers—to analyze the barriers to successful employment outcomes and detail possible strategies for achieving successful employment outcomes for people with a disability. Considerably more employers (both employer groups) than service providers identiﬁed ‘resources/costs’ as a barrier, and the importance of service provider strategies, in particular job-match, to successful employment outcomes. This diVerence in the importance of service provider strategies further supported the view that service providers can underestimate the importance of services that they can oVer employers. Using an ecological framework highlights the importance of attending to the perspectives of others in the ecological system. Although somewhat broader than the partnership approach between employers, service providers, and employees with a disability as advocated by Fabian et al. (1994), an ecological approach is nonetheless consistent with a partnership approach because it highlights the contribution that interrelationships between those operating at diVerent levels of the ecological system can make to employment outcomes. Importantly, an ecological framework allows complex information to be interpreted and subsequently used for augmenting

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successful employment outcomes. Furthermore, using an ecological framework draws attention to the dynamic nature of the interplay that occurs between the many factors, internal and external to the workplace, which inﬂuence employment outcomes. Thus, the Smith studies (2002, in press) have highlighted the importance of attending to aspects in the workplace and in the broader environment for achieving successful employment outcomes.

III.

MAXIMIZING THE ACHIEVEMENT OF SUCCESSFUL EMPLOYMENT OUTCOMES: FUTURE DIRECTIONS

Examining employment outcomes within an ecological framework has drawn attention to the complexities involved when considering the variables, both internal and external to the work environment, that impact employment for people with an intellectual disability. An understanding of this complexity is necessary in order to maximize the eVectiveness of strategies and policies aimed at promoting successful employment outcomes. Furthermore, in highlighting the dynamic nature of the interplay between individuals and environments in which they operate, the literature reviewed here suggests that achieving successful employment outcomes requires ongoing monitoring of service delivery and its inﬂuence on outcomes, and an appreciation of the interplay of variables in the ecological system that contribute directly and indirectly to this outcome. Not only are the diVerent contexts in which employment occurs dynamic, employment aspirations of employees are also inclined to be dynamic. That is, what constitutes a successful employment outcome for an individual can diVer across time. The ILO argued that merely concentrating on job acquisition does not meet the employment needs of those who have a disability. Job security and career advancement need to be on the agenda (Vocational Rehabilitation Branch–ILO, 1996). The ILO has argued that ensuring that workers who have a disability have the same opportunities for career advancement as other workers has received little attention from policy makers. Yet the issue of equal career prospects is a requirement under the ILO Convention 159 (Vocational Rehabilitation Branch–ILO, 1996). The major focus of policymakers concerned with employment prospects for people with an intellectual disability has been placement in employment, with little attention beyond job acquisition. For many people who have a disability, employment access and career advancement are elusive goals without the appropriate support mechanisms in place; yet such mechanisms require funding. Ensuring equal opportunity in employment is a social justice commitment, but the realization of the commitment is an economic issue.

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The literature reviewed herein underscores the importance of coordinated and multi-pronged approaches to service provision that target diVerent levels of the ecological system, including those who operate within them. Yet research in this area is of little more than academic interest without the practical application of this knowledge. However, much of the practical application is dependent on adequate resourcing. In many Western countries a large proportion of the funding related to successful employment outcomes, such as funding for disability employment service provision, education, and disability awareness, is government funding. Governments, however, have both economic and social responsibilities towards the community (Saltmarsh, 1994). These responsibilities can be inﬂuenced by conﬂicting ideologies that need to be recognized. Although most governments are committed to human rights values, tensions exist between these values and economic rationalist policies (Saltmarsh, 1994). Ling (1999) has recently suggested that tensions between the overt and covert goals of government create diYculties for practitioners in the disability sector. Tensions between social justice and economic rationalist paradigms are just part of the wider environment in which employment and disability operate (Smith et al., in press). The existence of these tensions highlights the importance of recognizing interrelationships between the levels of the ecological system. Merely identifying factors of relevance to employment outcomes without considering the often-complex nature of the interplay between factors, can reﬂect a simplistic and distorted picture of the environment in which disability and employment operate. Maximizing successful employment outcomes is fraught with many challenges. Not only is attention required to all levels of the ecological system in creating an environment that supports positive employment outcomes, but also service providers must be cognizant of factors important to this goal and negotiate a path relevant to the employment aspirations of speciﬁc individuals with a disability, including persons with an intellectual disability. Not only will factors important to this goal diVer between individuals, settings, and prevailing cultures, but these factors will ﬂuctuate across time. For example, the literature reviewed herein has highlighted the importance of ﬂexible and long-term planning approaches that account for changing goals and circumstances. IV.

CONCLUSIONS

The literature reviewed herein attests to the wide acceptance of the importance of achieving successful employment outcomes, and identiﬁes a range of factors that can inﬂuence this goal. Nonetheless, literature on the low rates of employment for people with an intellectual disability also conﬁrms the inadequacy of current measures employed toward this goal. Bronfenbrenner

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(1989) has argued for the importance of considering not just the impact of speciﬁc variables on development, but also the eVect of the interplay between these variables. Although Bronfenbrenner’s focus was on child development, Smith (2002) showed Bronfenbrenner’s theory to be applicable when interpreting the inﬂuence of an array of factors across the ecological system on employer satisfaction with employees with a disability, including a high proportion with an intellectual disability. The importance of measures, both internal and external to the workplace, in improving employment outcomes has been recognized (European Trade Union Committee, 1995; Russell, 1998; Smith, 2002). Yet research on employment and disability and subsequent recommendations for improving employment outcomes, have tended to target speciﬁc levels of the ecological system, usually, the employment setting, or disability service provision, rather than taking a multi-level approach. The literature reviewed herein has depicted disability and employment as dynamic and complex phenomena with diverse inﬂuences. The future challenge for the disability employment sector is to consider ways in which these complex phenomena intersect, and how to work with this complexity to achieve successful employment outcomes, not only for speciﬁc individuals, but also for people with a disability in general. Scrutinizing disability and employment within an ecological framework provides a means for clarifying and interpreting complex information, and highlights the importance of interrelationships both within and between the diVerent ecological levels, including those who operate within these levels. Both this framework and the literature reviewed uphold the importance of ensuring interrelationships between all stakeholders involved in the employment area. These interrelationships are important for the development of negotiated strategies based on shared goals and commitments. In achieving successful employment outcomes for people with an intellectual disability, service providers are faced with challenges that are both exciting and considerable. Strategies and information that can assist service providers to understand the many layers of complexity that can impact on employment outcomes are important in surmounting this challenge. REFERENCES Albin, J. (1992). Quality improvement in employment and other human services: Managing for quality through change. Baltimore, MD: Paul H. Brookes. Albrecht, G., & Bury, M. (2001). The political economy of the disability marketplace. In G. Albrecht, K. Seelman, & M. Bury (Eds.), Handbook of disability studies (pp. 585–609). Thousand Oakes, CA: Sage. Albrecht, G., Seelman, K., & Bury, M. (2001). Introduction: The formation of disability studies. In G. Albrecht, K. Seelman, & M. Bury (Eds.), Handbook of disability studies (pp. 1–8). Thousand Oakes, CA: Sage.

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Technology Use and People with Mental Retardation MICHAEL L. WEHMEYER, SEAN J. SMITH, AND SUSAN B. PALMER DEPARTMENT OF SPECIAL EDUCATION UNIVERSITY OF KANSAS LAWRENCE, KANSAS

DANIEL K. DAVIES AND STEVEN E. STOCK ABLELINK TECHNOLOGIES COLORADO SPRINGS, COLORADO

Technology has become a pervasive aspect of life in the 21st century, impacting every aspect of daily living: cash registers at fast food restaurants are sophisticated computers; grocery checkout lanes use data scanned from universal product codes on packaging; computers in automobiles use global positioning satellite data to provide directions to the nearest restaurant; medical diagnoses and treatment are available to rural areas by telemedicine; personal digital assistants have replaced personal planners and calendars; consumers are purchasing everything from clothing to movie tickets online; digital and cellular phones are steadily replacing traditional telephones, whose demise began with the sweeping adoption of electronic mail; universities and colleges are oVering more content and course credit online—this litany of the impact of technology on our lives could, quite literally, continue almost indeﬁnitely. The ubiquity of technology suggests that if one is to achieve a better quality of life, one must, in most countries, have both access to and be able to use technology. The potential for technology to contribute to ‘the good life’ was a primary impetus for Public Law 100–407, the Technology-Related Assistance for Individuals with Disabilities Act of 1988 (Tech Act). This Act noted that the provision of assistive technology (AT) devices and services to INTERNATIONAL REVIEW OF RESEARCH IN MENTAL RETARDATION, Vol. 29 0074-7750/04 $35.00

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individuals with disabilities enables ‘‘individuals to: (A) have greater control over their own lives, (B) participate in and contribute more fully to activities in their home, school and work environments, and in their communities, (C) interact to a greater extent with non-disabled individuals, and (D) otherwise beneﬁt from opportunities that are taken for granted by individuals who do not have disabilities’’ (p. 1044). People with and without disabilities universally value these goals of self-determination, inclusion and participation in one’s school or community, and enhanced social inclusion. This value for greater control and inclusion and the potential for technology to lead to these outcomes are, presumably, no less true for people with mental retardation than anyone else. Technology can facilitate education and therapy and enhance physical functioning: ultimately, it allows fuller participation in the world of persons without disabilities (Parette, 1991). The position statement for the Council for Exceptional Children’s (CEC) Division on Developmental Disabilities noted that assistive technology devices could ‘‘enable persons with mental retardation and developmental disabilities to acquire important skills that may enhance their quality of life and result in greater independence in family and community settings’’ (Parette, 1997). However, along with the infusion of technology into every aspect of life has come the problem of the ‘digital divide,’ a term coined generally to refer to the gap between the ‘‘haves’’ and the ‘‘have nots’’ with regard to access to technology and, more speciﬁcally, access to information through computer and Internet technology. In the 2001 report A Nation Online: How Americans Are Expanding Their Use of the Internet, the U.S. Department of Commerce documented that while Internet access is increasing among all populations, people who are poor or who have lower education rates are, generally, not beneﬁting from this technology compared with other Americans. While the existence of the digital divide and the contribution of technology to either exacerbate the negative or improve the positive life conditions of people who are marginalized remains a point of controversy, it does not seem controversial to suggest that whether we are comparing people with mental retardation with other people with disabilities or with the general population, there is a digital or technology divide. As this gap widens, the potential that technology will promote valued outcomes like enhanced self-determination, social inclusion, and community integration for people with mental retardation diminishes exponentially. This chapter will provide a comprehensive examination of the use of technology by people with mental retardation with the intent to provide a framework within which to consider the beneﬁts of technology use by this population. We will begin by examining the potential beneﬁt of technology use for people with mental retardation.

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A.

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IMPORTANCE OF TECHNOLOGY USE TO PEOPLE WITH MENTAL RETARDATION

Types of Technology

Traditionally, when one thinks of issues pertaining to technology and disability, it is within the context of a class of high- and low-tech devices that fall under the category of assistive technology. The Tech Act deﬁned AT as ‘‘any device, piece of equipment, or product system, whether acquired commercially or oV-the-shelf, modiﬁed, or customized, that is used to increase, maintain, or improve functional capabilities of individuals with disabilities’’ [29 U.S.C. 2202, Sect. 3(1)]. Examples include mobility devices (wheelchairs, scooters, cane), augmentative and alternative communication devices, devices to assist people with sensory impairments (alerting systems, high-contrast clocks, hearing aids), daily living aids (dressing devices, eating devices), and environmental control devices (sound or motion detectors to control lighting). One can make the case that any number of technology devices qualify as ‘improving functional capabilities,’ and one might include common kitchen appliances (microwave, blender, coVee maker) or other daily living supports (washing machine, dryer, electric razor) as qualifying as AT devices. Indeed, items that seem not to be technological devices at all, such as rubber grips for holding a pencil or tactile enhancements such as raised lines, often fall under the category of AT. The key to the classiﬁcation as being ‘AT,’ then, must rely less on the technology aspect and more on the capacity of the device, equipment, or adaptation to improve functional capacity by, in essence, accommodating for or providing an adaptation that is directly related to the functional limitation(s) imposed on the person by the disabling condition. While common technology can and has been used as ‘AT’, such devices are in essence linked deﬁnitionally to functional limitations. A second class or type of technology—electronic and information technologies (E&IT)—is becoming more prevalent and, in many cases, beginning to replace traditional AT. In 1998, the Rehabilitation Act deﬁned electronic and information technology as any equipment or interconnected system or subsystem of equipment that is used in the creation, conversion, or duplication of data or information. The Architectural and Transportation Barriers Compliance Board, charged in the 1998 reauthorization of the Rehabilitation Act with deﬁning the term ‘‘electronic and information technology,’’ was statutorily required to be consistent with the deﬁnition of information technology (IT) in the federal Information Technology Management Reform Act, which was passed to streamline government IT acquisitions and management. This act deﬁned IT as including computers, ancillary equipment, software, ﬁrmware, and similar procedures, services (including

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support services), and related resources. The E&IT, as such, were deﬁned to include IT products, such as those listed as IT as well as telecommunications products (such as telephones), information kiosks, and transaction machines, World Wide Web sites, multimedia, and oYce equipment such as copiers and fax machines. While E&IT products and devices can, indeed, serve the same purpose of addressing functional limitations as AT devices, such devices are not developed with that narrow intent, but instead are aimed at addressing broader goals for technology to enhance productivity, automating routine tasks, improving the ﬂow of information, streamlining and improving communication, and so forth. It is, in many ways, the explosion of activity in this second category of technology that has created both the opportunity for technology to signiﬁcantly improve the quality of life for people with and without disabilities and, as such, created the aforementioned digital divide. A third type of technology sometimes mentioned involves ‘‘universallydesigned technology,’’ which refers to technology devices incorporating the principles of universal design (discussed subsequently) ensuring that the design of products and environments be usable by all people, to the greatest extent possible, without the need for adaptation or specialized design. It is the goal of most eVorts to improve access to technology, both assistive and electronic, and information, to ensure that devices are ‘‘universally designed.’’ Most of the literature pertaining to technology use in special education, rehabilitation, and disability services has focused on AT. This chapter will examine the use of both types of technology by people with mental retardation. However, even the comparatively limited literature concerning mental retardation and AT (that is, limited in comparison to the literature on other disabilities and AT) is voluminous. This chapter is intended to be thorough in its examination of both classes of technology. However, we have attempted to be complete only in our review of E&IT as they apply to mental retardation, partly because this is a smaller and more manageable literature base and partly because we believe that many of the beneﬁts of technology in the future for people with mental retardation will be hinged not on new AT, but on the degree to which E&IT are universally designed. B.

Technology as Support Under New Definition

The relevance of technology as a support for people with mental retardation took on additional importance as the ﬁeld began to reconceptualize mental retardation. The 9th Edition of the American Association on Mental Retardation (AAMR) Handbook on deﬁnition and classiﬁcation of mental retardation (Luckasson et al., 1992) introduced a functional deﬁnition and classiﬁcation system intended to link the classiﬁcation of mental retardation

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to a system of supports. In this edition of the AAMR classiﬁcation manual, mental retardation is deﬁned not as something that a person has or something that is a characteristic of the person, but instead as a state of functioning in which limitations in functional capacity and adaptive skills must be considered within the context of environments and supports. Luckasson et al. (1992) noted ‘‘mental retardation is a disability only as a result of this interaction’’ (p. 10); that is, only as a result of the interaction between the functional limitation and the social context, in this case the environments and communities in which people with mental retardation live, learn, work, and play. The AAMR’s functional deﬁnition of mental retardation emphasizes the interaction between the person with the disability and the context in which he or she lives, learns, works, or plays. By deﬁning disability as a function of the interaction between the environment and a person’s functional limitations, the focus of the ‘problem’ shifts from being a deﬁcit within a person to the identiﬁcation and design of supports to address that person’s functioning within that context, with an enhanced focus on accommodations and modiﬁcations to the context. Technology, thus, becomes a critical support to enhance performance across multiple environments. C.

Functional Use Areas

Technology has the promise not only of making life better or easier for people with mental retardation, but of providing low-cost, powerful supports that accommodate and compensate for limitations inherent in cognitive impairments in ways that traditional AT cannot. For example, many people now use inexpensive and widely available software programs to balance their checkbooks, build a budget, or pay taxes. These programs take inputted data and conduct calculations that are beyond the capacity of many people with mental retardation, thus automating the bill-paying or budgeting process. These software programs then communicate electronically with banks and ﬁnancial institutions, providing the opportunity to conduct one’s personal ﬁnancial business online and virtually paper-free. The requirements for independent ﬁnancial management in this scenario move from being able to do tasks requiring mathematic skills pertaining to addition, subtraction, multiplication, and division to being able to input data on income and expenses into the software program, to go online to check balances, and to navigate automated teller machines (ATMs) to withdraw cash and make deposits. In fact, as more companies move toward automatic payment options and as debit cards replace cash, many of these second-generation ﬁnancial management tasks are becoming less critical for independent money management. Such beneﬁts could be seen in virtually any sphere of life, across multiple domains. In this chapter, we will examine the use of technology by people

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with mental retardation within a two-tiered framework classifying technology devices into seven ‘‘functional use’’ areas—communication, mobility, environmental control, activities of daily living and community inclusion, education, employment, and sports and recreation—and examine the barriers of using these areas as a function of the ‘‘user characteristics’’ associated with mental retardation. With the latter, we were interested in moving beyond a deﬁcits’ approach and preferred to look at user characteristics within an ‘abilities’ focus. As such, we have examined barriers to use and user characteristics within the human cognitive abilities taxonomy proposed by Carroll (1993). In a subsequent section, we will brieﬂy overview these cognitive ability domains and discuss how limitations in abilities within each domain impact technology use. We will then provide a comprehensive review of the literature pertaining to technology use by people with mental retardation within each of the functional use areas. First, however, it is important to examine what we currently know about technology use by people with mental retardation. D.

Technology Use and People With Mental Retardation

A focus on technology use by people with mental retardation is a fairly recent phenomenon. In 1982, the national headquarters of the Association for Retarded Citizens (now The Arc of the United States) launched a programmatic initiative called the Bioengineering Program, intended to address the lack of focus in technology development for people with mental retardation. For more than one decade, this program developed technology for and advocated on behalf of people with mental retardation (Brown & Cavalier, 1992; Cavalier & Brown, 1998; Mineo, 1985; Mineo & Cavalier, 1985). By the mid to late 1990s, there was a shift in focus at The Arc from development activities to advocacy and, in 1995, The Arc conducted a national survey to examine the use of technology by people with mental retardation and to identify barriers to that use (Wehmeyer, 1998, 1999). Respondents reporting on behalf of an adult family member (1,218) with mental retardation indicated that in two use areas, the percentage of people with mental retardation who needed but did not use AT exceeded the percentage actually using such technology (Table I). Satisfaction with training provided was generally low. The two primary barriers to device use identiﬁed by respondents whose family member did not have a device but might beneﬁt from one, were information about the availability of the device and the cost of devices. The third most common barrier was the unavailability of assessment information, while limited training on device use was identiﬁed as the fourth, and device complexity as the ﬁfth. With regard to computer use, 33% of respondents (n ¼ 399) indicated there was a computer in their home. A smaller percentage (23%; n ¼ 284)

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TABLE I FREQUENCY AND PERCENT OF ADULTS WITH MENTAL RETARDATION WHO USED OR NEEDED BUT DID NOT USE TECHNOLOGY Device Use and Need Device Purpose

Frequency Use

% Use

Frequency Need

% Need

Mobility Hearing and vision Communication Home adaptation Environmental control

155 107 59 117 66

12.7 8.9 4.9 9.7 5.5

30 57 104 95 87

2.5 5.0 9.3 8.4 7.6

indicated their family member used a computer, either at home or in another setting, such as work or in a recreation or leisure program. When asked to identify what the person with mental retardation did with the computer, 30 respondents indicated it was for communication, 130 for educational activities, 10 for household ﬁnances or budgeting, 183 for leisure activities, 29 for work-related activities, and 26 for other activities (respondents checked all that applied). Of respondents whose family member did not use computers (n ¼ 872), 330 (38%) indicated they believed their family member could beneﬁt from a computer. The most frequently cited barrier to computer use was cost or lack of funds (n ¼ 223), followed by lack of available training (n ¼ 169), complexity of the device (n ¼ 124), lack of assessment (n ¼ 88), and a lack of information about what the computer could do to beneﬁt the family member (n ¼ 84). The ﬁndings for the youth sample (n ¼ 516) of the survey were similar (Wehmeyer, 1999). As depicted in Table II, the percentage of students who could potentially beneﬁt from assistive devices but did not currently have access to such devices was greater than the percentage of students who currently used such devices in most use areas. Satisfaction with training was low and, indeed most respondents reported that they received little or no training. Of the respondents, 60% (n ¼ 349) indicated there was a computer in their home. However, younger people did have greater access to computers. Of the respondents, 83% (n ¼ 421) indicated that the student in their family had access to or used a computer either at home or in another environment. Of these 421 computer users, 382 indicated they used it in a school program, 4 in a work setting, 242 at home, 8 in a living situation other than home, 36 in a recreation or leisure program, and 9 in other situations (respondents checked all that applied). When asked to identify what the student with mental retardation did with the computer, 70 respondents indicated it was used for communication, 362 for educational activities, 1 for

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MENTAL

TABLE II FREQUENCY AND PERCENT OF STUDENTS WITH RETARDATION WHO USED OR NEEDED BUT DID NOT USE TECHNOLOGY BY AGE GROUP

Device Purpose Mobility Ages 1–5 Ages 6–15 Ages 16–21 Total Sample Hearing and vision Ages 1–5 Ages 6–15 Ages 16–21 Total sample Communication Ages 1–5 Ages 6–15 Ages 16–21 Total sample Home adaptation Ages 1–5 Ages 6–15 Ages 16–21 Total sample Environmental control Ages 1–5 Ages 6–15 Ages 16–21 Total sample

Frequency Use

% Use

Frequency Need

% Need

16/67 65/303 27/146 108/516

24 8 18 21

1/67 12/303 3/146 16/516

1 4 2 3

8/67 34/303 14/146 56/516

12 11 10 11

7/67 47/303 12/146 66/516

10 16 10 13

14/67 62/303 27/146 103/516

21 20 18 20

25/67 75/303 28/146 128/516

37 25 19 25

8/67 46/303 32/146 86/516

12 15 22 17

16/67 56/303 22/146 94/516

24 18 15 18

14/67 46/303 18/146 78/516

21 15 12 15

21/67 65/303 30/146 116/516

31 21 20 22

household ﬁnances or budgeting, 270 for leisure activities, 6 for work-related activities, and 19 for other activities. For respondents whose family member did not use computers either at home or elsewhere (n ¼ 183), 142 (78%) indicated they believed their family member could beneﬁt from a computer. The most frequently cited barrier to computer use was the cost or lack of funds (n ¼ 111), followed by the lack of training available (n ¼ 38), a lack of information about what the computer could do to beneﬁt the family member (n ¼ 38), the complexity of the device (n ¼ 31), and the lack of assessment (n ¼ 24). The Arc’s survey results were consistent with another survey of technology use and needs by 680 people with mental retardation in Arkansas (Parette & VanBiervliet, 1992). Table III displays their data regarding technology use and unmet needs for respondents across 16 use areas. As with The Arc’s survey

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TABLE III FREQUENCY AND PERCENT USE AND UNMET NEED ACROSS MULTIPLE USE AREAS (ADAPTED FROM PARETTE & VANBIERVLIET, 1992) Device Use and Need Device Purpose

Frequency Use

% Use

Frequency Need

% Need

Getting around Self-help Work/work training Recreation School training Taking care of home Things that aid vision Specialized seating Specialized transportation Artiﬁcial limbs, braces, and prostheses Using a telephone Talking with others Building accessibility Reading, writing, and typing Hearing aides and other hearing devices Using a computer

179 234 150 185 146 151 101 78 108 67

73 69 62 59 59 59 59 53 52 50

67 105 91 130 102 106 71 68 98 68

27 31 38 41 41 41 41 47 48 50

99 122 99 96 53

49 48 48 42 41

102 132 109 135 76

51 52 52 58 59

44

21

161

79

results, unmet needs often matched the actual use of devices, and in seven of the use areas, need exceeded use. The Parette and VanBiervliet (1992) survey found similar issues with regard to evaluation and training as well. E.

Summary

Technology, both AT and E&IT, has the potential to dramatically improve the quality of life for people with mental retardation and their families. Indeed, a functional deﬁnition of mental retardation provides a compelling role for technology to mitigate the adverse impact of a person’s cognitive impairments on school, work, and community functioning. Yet, despite a growing literature base indicating that people with mental retardation can both use and beneﬁt from technology and increased recognition of the importance to ensure cognitive access for technology, at the present time it is evident that the promise of technology is largely unfulﬁlled for many people with mental retardation and their families. The following sections are intended to identify what we know about technology use by people with mental retardation within a framework that emphasizes cognitive abilities that

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are important to all people and that must be considered when designing technology. II.

USER CHARACTERISTICS ASSOCIATED WITH MENTAL RETARDATION THAT IMPACT TECHNOLOGY USE

As previously, discussed the AAMR’s functional model deﬁnes mental retardation only in the context of a person’s functioning in community environments typical of the individual’s age peers and culture, and emphasizes that such limitations can coexist with strengths. In many ways, the promise of technology lies not in compensating for deﬁcits, but in enhancing human capacity and ability so that people with mental retardation can function competently across a wide array of environmental contexts. As such, we have turned to research pertaining to human cognitive abilities as a means to provide a taxonomy of cognitive skills that might be supported by technology use. To establish a ‘strength-based’ framework within which to examine technology use by functional domains, we have drawn from Carroll’s (1993) factor-analytic work regarding human cognitive abilities. A.

Human Cognitive Abilities and People With Mental Retardation

Carroll (1993) conducted a comprehensive survey and analysis of correlational and factor-analytic research on cognitive abilities, resulting in the identiﬁcation of eight primary or ﬁrst-order factors of cognitive ability: (1) language; (2) reasoning; (3) memory and learning; (4) visual perception; (5) auditory reception; (6) idea production; (7) cognitive speed; and (8) knowledge and achievement. Each domain is discussed brieﬂy in the next section (readers are referred to Carroll (1993) for more detail), with a subsequent discussion of how impairments in that domain impact technology use. In a later section, we will examine the literature by functional use with reference to these cognitive ability domains. Within each of these primary human cognitive ability domains there is a voluminous literature, even within the narrower scope of those studies that pertain primarily to people with mental retardation. As such, our intent is not to provide a comprehensive literature review within each domain, but instead to capture some sense of the characteristics of people with mental retardation as ‘users of technology’ with regard to each domain. Within each cognitive ability area, we brieﬂy discuss how and why limitations to such abilities serve as barriers for technology use for people with mental retardation. A subsequent section will identify how universal design features can address these barriers.

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1. LANGUAGE ABILITY AND AUDITORY RECEPTION

Perhaps the broadest ﬁrst-order domain presented by Carroll is that of language ability. Factors identiﬁed within this domain included language development, verbal or printed language comprehension, lexical knowledge, reading comprehension, decoding and speed, cloze ability, spelling ability, phonetic coding, grammatical sensitivity, foreign language aptitude and proﬁciency, communication ability, listening ability, oral production, oral language style, and writing ability. By and large, this domain references the cognitive processes and tasks that pertain to the use of language that result in outcomes such as reading, writing, and verbal comprehension. Such skills include verbal and gestural imitation skills, interactive communication skills, and the more straightforward issues of speech and language production. Auditory reception factors identiﬁed by Carroll refer to abilities that include hearing and speech threshold, speech sound discrimination, music and musical sound perception, absolute pitch ability, and sound localization. a. Impact on Technology Use by People With Mental Retardation. The limitations in the intellectual functioning characteristic of people with mental retardation introduce obvious restrictions to the full expression of language ability for this population. Abbeduto (1991) noted that skills in this domain are primary factors measured in traditional intelligence tests, performance on which has essentially deﬁned the condition of mental retardation. There is extensive literature documenting impairments in language ability as a characteristic of people with mental retardation (see Abbeduto, 1991, 2003 for recent IRRMR chapters on language development, comprehension, and interventions, including reading skills). Impairments in language and communication ability impact technology use in several ways. Impairments in receptive and expressive communication skills limit the degree to which some people with mental retardation will be able to utilize technology, particularly the expanding class of telecommunication technologies. Additionally, a growing means of inputting information used by technology (e.g., computer programs) involves speech input devices. Problems of speech articulation certainly pose barriers in both cases, but other factors pose problems with these and other technologies. For example, the speed at which verbal information to operate technology is provided and by which people with mental retardation process such information can create barriers. Similarly, more complex verbal instructions, such as those often found in voice mail systems, may limit use for people with cognitive impairments. Similarly, impairments in reading and writing skills introduce barriers to eVective device use. The most obvious is often that the primary input mode to access a wide array of computer technology involves typing or, with newer

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handwriting transcription technologies, writing abilities. Even when input is not required, most software programs require rather high levels of reading ability to navigate. Many instructions to technology use and maintenance are often written in overly complex formats that people with mental retardation cannot read or understand. Technology devices often emit tones and other sounds intended to convey meaning. However, it is often diYcult to discern their meaning even for experienced technology users. With computers, in many cases the audio signal is accompanied by a text message in a message box or somewhere else on the computer screen. Technology developers generally assume the ability for users to read the accompanying text message. The need to read to understand the meaning of the audio signal thus greatly limits the number of users with mental retardation who can understand the computer-generated message. 2. REASONING AND IDEA PRODUCTION

The second domain identiﬁed by Carroll was labeled as reasoning abilities, which include ﬁrst-order factors such as sequential reasoning (deductive, logical, and verbal reasoning, symbol manipulation, match problems), inductive ability (requiring a person to inspect a class of stimulus materials to infer a common characteristic), and quantitative reasoning (e.g., those requiring reasoning based on mathematical properties and relations, including critical evaluation, arithmetic reasoning and problem solving, math aptitude, and number series, classiﬁcation, and operations). Carroll also proposed a fourth factor, called Piagetian reasoning factors, because they contained reasoning tasks devised and studied by Piaget and his collaborators, including operativity, conservation, and representational, meta-representational, and meta-cognitive skills. An additional ﬁrst-order factor—idea production—is similar in the impact on technology use to the reasoning factor. Carroll’s idea production cognitive ability domain refers, quite simply, to abilities for individuals to produce ideas and communicate them in linguistic or other means. These refer in general, to ﬂuency and creativity factors. First-order factors in this area include ideational ﬂuency, naming facility (naming common concepts), associational ﬂuency (producing words/concepts that are associated), expressional ﬂuency, word ﬂuency, sensitivity to problems, originality/creativity, ﬁgural ﬂuency (producing original drawings or sketches), and ﬁgural ﬂexibility (solving ﬁgurative problems). a. Impact on Technology Use by People With Mental Retardation. In that these domains encompass abilities that are considered to be at or near the core of what is ordinarily meant by intelligence, it follows that they signiﬁcantly

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inﬂuence whether and to what degree ability of individuals with lower intelligence scores can access and use technologies. For example, virtually all appliances, devices, and software systems require some level of sequential reasoning, even if it is as simple as having the ability to assess whether the system is turned on or not. This may be true for a wide range of simple to complex technologies, from knowing whether the iron is on, to activating an augmentative communication system. To the more complex side of things, most computer programs are complex and interactive, requiring the user to constantly take actions and draw conclusions from the system’s reaction as to what is the most likely next move. Another example can be seen in the design and use of common augmentative communication systems. These systems, which usually involve a grid of some kind that allows the user to activate individual squares on the grid to elicit speciﬁc words or phrases, provide a feature for increased functionality that allows the user to change ‘‘levels’’ on the grid, so that multiple phrases can be programmed into a single square on the grid. The interface for switching between levels on these devices is a purposeful multi-step process that avoids accidental level-switching, but precludes individuals with signiﬁcant limitations in inductive reasoning from independently using this feature. The impact of limitations in the numeracy area on technology use can also be seen in the many systems that involve numerical comprehension and manipulation. From setting a stove temperature and dialing a telephone to using calculators and entering data, situations abound where limitations in qualitative reasoning skills impact technology use. Limitations in this area can be compensated for by providing non-numerical interventions to improve independent access, such as in picture-based speed dial telephones or special markings on dials or switches to cue the user to a speciﬁc setting or switch when many choices are available. Technology accommodations for other reasoning limitation factors can take advantage of common methodologies used previously in other life areas to improve access, such as providing limited choice options to decrease the need for advanced reasoning skills. For example, mainstream computer programs invariably oVer a myriad of interface choices at any given time, many of them providing multiple input options for the same output (e.g., text menu, key board shortcuts, button toolbars). Specialized computer programs can be created that utilize a limited number of repetitive processes that are largely ‘‘linear’’ in nature. This means that at any given time while interacting with the software either a single choice is available for the next step, or system-generated cues (such as audio prompts) guide the user to the next-most-likely action. Other examples of limiting choice options to make technologies more accessible include special desktop software that provides access to a limited set of computer

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features or augmentative communication device and keyboard overlays that reduce or reprogram available keys. Often, people with mental retardation have some level of diYculty understanding the abstract concepts and metaphors used in technology devices, not only at the language ability level, but in areas more closely related to reasoning. For example, beyond the need to understand that the words ‘‘ﬁle’’ or ‘‘folder’’ refer to something diVerent when in the context of a computer system, computer users must also conceptualize the virtual location of these ﬁles within a computer directory. Indeed, many mainstream novice computer users have diYculty retrieving computer ﬁles due to their lack of understanding of ‘‘locations’’ and of ‘‘electronic’’ data storage. Other technologies present their own challenges to the capacity of students with cognitive impairments and their ability to reason abstractly. Communication devices often include customizable pictures or text buttons that, when pressed, ‘‘speak’’ the indicated word or phrase. To provide added functionality, most of these devices include a feature that allows the user to create diVerent overlays, or layers, so that more words or phrases can be accessed. For example, a typical device may have 16 buttons that can be programmed to speak a designated phrase. But an additional switch allows the user to activate another layer of programming so that the same 16 buttons can speak entirely diVerent phrases. However, many of these devices are not usable by students with mental retardation, due in part to the inability to conceive of these diVerent ‘‘layers.’’ Other examples may be as simple as failure to recognize or understand the meaning of when the computer cursor arrow turns into a hand icon when it is placed over a click-able element of a web site, or in understanding the diVerence between a single click, a double click, or a right-click. Even the most basic of software features—such as in the practice of disabling or ‘‘graying out’’ buttons when they have no practical use—often are too subtle to be recognized by users with cognitive disabilities. Using technology on a regular basis often entails problem identiﬁcation and problem solving by the technology user which would serve as a barrier to people with mental retardation. Many technology users rely on their ability to generalize previous learning to problem-solve unexpected occurrences. However, many individuals with mental retardation have limited ability to generalize learning from one situation to another and, therefore, do not develop the ‘‘workaround’’ strategies that users of technology develop to overcome problems. 3. MEMORY AND LEARNING

Carroll’s third cognitive ability domain involves memory and learning factors. The ﬁrst-order factors in this taxonomy include memory span,

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associative memory, free recall memory, meaningful memory, visual memory, and learning abilities. In addition, Carroll’s factor analyses yielded some factors which fell under a ﬁrst-order factor titled simply ‘other,’ including factors of memory for events, verbal discrimination memory, and clustering ability. a. Impact on Technology Use by People With Mental Retardation. The complexity of most technologies inherently provides barriers to use for people with limitations in memory and learning. It is typical of people to react to the complexity of technologies by mastering a small piece of the system’s capability, and then using that part of the interface exclusively. Our common reaction to seek simplicity when faced with system complexity similarly provides alternatives to improving access to technology for people with memory and learning limitations. These techniques, not surprisingly, involve a reduced dependency on memory and learning by once again implementing strategies previously demonstrated as eVective in teaching and training, such as the concept of consistency and repetition. These techniques are closely associated with the concept of providing limited choices to address limitations in reasoning. Limiting choices may involve limiting the number of features or processes that are available in a given technology, while consistency and repetition require that these limited features are accessed via interfaces which provide a consistent set of steps and allow opportunities to repeatedly engage in the process. 4. VISUAL PERCEPTION

The fourth cognitive ability domain is visual perception, including factors in visualization, spatial relations, closure speed (e.g., the ability to combine disparate visual stimuli into a meaningful whole), closure ﬂexibility (ability to manipulate, visually, multiple objects or conﬁgurations, such as hidden ﬁgure tasks), serial perceptual integration (integrating sequential images), spatial scanning (speed in exploring a visual ﬁeld), perceptual speed (speed of ﬁnding desired images or stimuli), imagery (ability to image or visualize performance or action sequence), length estimation, perception of illusion, and perceptual alternations. These factors relate to the abilities in ‘‘searching the visual ﬁeld, apprehending the forms, shapes, and positions of objects as visually perceived, [and] forming mental representations’’ (p. 304). a. Impact on Technology Use by People With Mental Retardation. Limitations in visual perceptual ability can have a signiﬁcant impact on one’s capacity to operate software programs and, in particular, software operating systems. As graphical user interfaces using pointing devices such as a mouse or touchpad have evolved and become the dominant mode of interacting with computers, the ability to scan, locate, and act upon key information on

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the display screen has become of paramount importance. Attending to relevant environmental cues can often be diYcult for individuals with mental retardation and this diYculty also exists when viewing complex displays, with potentially many windows, buttons, and other screen elements. Larger computer monitors combined with increasing display resolutions provide the capability to populate the computer display with many windows and graphical elements including icons, menus, and other images. Without careful attention, screen clutter can be very distracting and can make managing a computer session very diYcult or impossible for users with visual spatial limitations. In addition, subtle changes to controls to indicate changing states, such as graying out the labels of buttons not available, often are not detected by users with cognitive limitations and can result in frustration when the individual attempts to click a button that has been used before, but now does not seem to work. Another signiﬁcant limitation can result from diYculty mastering the skill of moving the mouse or other pointing device and associating that with moving the arrow or pointer on screen. With most computers, the predominant input control device is a mouse, trackball, or touchpad. The ability to successfully correlate hand movements with the movement of the arrow on screen is necessary to use these standard input devices. Touch screens are often a good alternative given their direct cause eVect function, but they are still somewhat expensive and are not standard equipment with oV-the-shelf commercial systems. In addition, touch screens are only useful if the software applications have a user interface designed with larger buttons and controls to allow them to be selected with a ﬁnger on the display. Additionally, visual perceptual impairments can impact a person’s interactions with virtually any type of technology device, including diYculty in following instructions for the device use, diYculty with operating device controls, and so forth. 5. COGNITIVE SPEED

Carroll’s seventh ﬁrst-order factor—cognitive speed—includes ﬁrst-order factors that also loaded in the domains of reasoning, language ability, and idea production, as well as unique factors such as rate-of-test-taking, reaction time, and number ability or numerical facility (although numeracy issues were primarily addressed within the reasoning domain). a. Impact on Technology Use by People With Mental Retardation. Limitations in these abilities may impact technology use, although it is often not as obvious as in the related areas of reasoning and memory or learning. Current technology devices generally have ample processing power that does not require users to wait for very long for actions to be accomplished.

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One exception, however, is the area of utilizing dynamic content and applications delivered over the Internet. While access speeds are increasing rapidly, there still can be delays when using web applications due to the type of connection as well as the type of media being delivered (e.g., streaming audio and video). The inability to detect when to wait for the program or web page to ‘‘catch up’’ after making user inputs can lead to errors as users may click buttons multiple times waiting for the program to do what it is supposed to do, without realizing that the ﬁrst button press was suYcient and the program is just waiting for the web to respond. The ability to respond quickly to operate technology devices can also be an important factor in technology operations. For example, some ATMs require users to make inputs within very short time spans. If a user is slow at making an input, the ATM will either display a text message such as ‘‘Do you want to continue?’’ (which many people with mental retardation would not be able to read) or may simply end the activity. Some ATMs, when expelling the ATM card for the user to take, sound an audio tone for a short time and, if the card is not taken quickly, the card may be taken back into the machine and kept. Cognitive speed limitations that impair an individual’s ability to use technology ‘‘fast enough’’ can introduce barriers to technology use. 6. KNOWLEDGE AND ACHIEVEMENT

The ﬁnal cognitive ability domain identiﬁed by Carroll is that of knowledge and achievement. This ability domain includes ﬁrst-order factors identiﬁed as general school achievement, verbal information and knowledge, information and knowledge in mathematics and science, technical and mechanical knowledge, and knowledge of behavioral content (personal-social interaction knowledge). a. Impact on Technology Use by People With Mental Retardation. Computers are common tools for acquiring new knowledge and generating new works of achievement, and are used to learn nearly any topic as well as to produce, such as in writing, composing music, or generating artistic works. The majority of software applications that have been used for people with mental retardation to acquire new knowledge or abilities have been developed for other groups of individuals and primarily for children. Thus, ageappropriateness has often been absent when it comes to learning software for individuals with mental retardation, as few applications have been designed with the appropriate user interfaces and with ranges of content level appropriate. Early reading or basic math programs may be beneﬁcial for some persons, but generally the programs that are available are not ageappropriate for older students and adults with mental retardation and, although simpler to operate, again are often too complex overall.

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Programs for writing, such as word processors and other simple writing programs, may be useful for a minority of users with mental retardation who have attained some level of literacy skills. There are writing programs that have been developed for individuals with various other disabilities, such as learning disability, which oVer features such as word prediction, or sentence completion, but the cognitive abilities’ requirements for operating these programs often make them inaccessible to users with mental retardation. Better success may be achieved in using painting and graphics programs, although these vary greatly in complexity of operation. Simpler-to-use drawing programs allow users with mental retardation a vehicle for artistic expression, but there are also barriers to independent use, Mouse skills are usually required which can often present a barrier. Alternative input devices can be used eVectively, however, including graphics tablets or touch screens. Saving ﬁles and printing the ﬁnished product may also be diYcult as menus and print options may be diYcult to navigate. There appears to be a great opportunity for innovation in the area of designing software applications to generate creative content that can be used independently by individuals with various levels of cognitive ability.

B.

Features of Technology That Address User Characteristics

1. UNIVERSAL DESIGN

The principles of universal design emerged from the ﬁeld of architecture. The concept of universal design as applied to buildings and a built-environment suggests that all such buildings/environments should be accessible to all people (Moon et al., 1995). These principles were subsequently applied with the same intent to the design and development of consumer products and assistive devices. In essence, the principle of universal design was introduced to ensure that members of certain groups have access to the environment or products that could enhance their quality of life. Buildings are designed with adequate ramps, wider doors, or accessible restrooms, and products are designed with simple controls and clear understandable uses. These principles, as applied to technology design and development, provide many of the keys to addressing the underutilization of AT by people with mental retardation by focusing on the features of technology regarding user characteristics. The Trace Center, a rehabilitation, engineering, and research Center on telecommunications and information technology at the University of Wisconsin, and the Center for Universal Design identiﬁed seven principles of universal design to consider when creating technology.

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1. Equitable use: a design is useful and marketable to any group of users; 2. Flexibility in use: a design accommodates a wide range of individual preferences and abilities; 3. Simple and intuitive use: use of the design is easy to understand, regardless of the user’s experience, knowledge, language, or cognitive skills; 4. Perceptible information: the design communicates the information needed by the user, be it through diVerent modes or by providing adequate contrast; 5. Tolerance for error: the design minimizes adverse consequences or accidental or unintended actions; 6. Low physical eVort: the design can be used comfortably with minimum fatigue; and 7. Size and space for approach and use appropriate: design allows for approach, reach, manipulation, and device use independent of user’s body size, posture, or mobility (Center for Universal Design, 1997). If all technology devices took into account all of these principles, it is quite likely that many more devices would be useable by people with mental retardation. However, several might be particularly important in light of the previous discussion on cognitive abilities and the impact of limitations in these areas on technology use. First, devices that abide by the ﬂexibility in use principle inherently accommodate for use by a wider range of individual preferences and abilities. This includes providing options that accommodate for users’ accuracy and precision, and adapt to a user’s pace. For example, computer programs providing multiple input and output options (auditory, visual, icon, and so forth) ﬁt this category, as do telephones that have larger buttons with more space between numbers (The Center for Universal Design, 1997). Issues of simplicity and intuitiveness of use, another principle, are obviously important for people with mental retardation. Many devices are overly complex and operate counter to users’ expectations, including common appliances such as VCRs and alarm clocks. Universally designed devices also typically provide some supports (prompting, graphic, visual, or audio directions) for use. The principle of perceptible information requires not only that information needed to operate the device be easily seen, but also that such information be provided in multiple modes, with redundant presentation of information. Finally, an important and often overlooked feature for people with mental retardation is the principle of tolerance for error. People with mental retardation frequently make mistakes in using technology and if that error

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results in a failed use, the device becomes essentially impossible for people with mental retardation to access. For example, irons that shut oV automatically minimize the risk associated with using an iron (The Center for Universal Design, 1997). Developing technology that never encounters unexpected errors is, essentially, impossible. However, given the diYculty many persons with mental retardation have responding to unexpected errors, it is imperative that priority be placed on identifying highly reliable technology supports for students with mental retardation. Device failure is often a function of device complexity. The more complex a device is and the more features it has, the more likely it is to have unexpected errors. At times it may be more important to identify less complex devices with fewer features if they provide the beneﬁt of greater reliability. Moreover, many devices have, in essence, a one-strike-and-you’re-out policy where one error (wrong key stroke, wrong button, and so forth) results in the failure of the user’s session. For example, the value of a dialogue box that prompts you to conﬁrm a selection (deletion, exit) becomes evident when you inadvertently hit the exit icon without having saved work on an ongoing activity. The dialogue box allows you to select ‘Cancel’ and does not immediately delete unsaved work. People with mental retardation need devices that minimize the potential for error, but also which allow errors to occur without dire consequences. Another example of how features of technology address the characteristics of users with mental retardation involves recommendations from the Telecommunications Access Committee (TAAC, 1999), which was commissioned to examine engineering and design features that would ensure access to telecommunications technology for people with cognitive disabilities. This committee identiﬁed four classes of strategies that achieve this: 1. 2. 3. 4.

Redundant, user-controlled modality of information Streamlined, user-controlled amount and rate of information Procedural support Content organization

Strategies to ensure that the device design contains redundant, user-controlled information include the use of visual examples (diagrams, graphic icons, line drawings), in addition to or instead of text, providing information both in visual and auditory formats, providing descriptions of pictures, captions, and so forth, and allow multiple methods that enable users to locate and use controls (shape, size, texture, color, labels, voice output, and so forth) (TAAC, 1999). Allowing users to control the amount and rate of information and streamlining the information provided is the second strategy identiﬁed. Such strategies support people with attention and memory

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limitations by allowing a user to control aspects (size, placement, appearance) of display elements, by providing simple, standardized layouts for devices and controls, presenting information in a step-by-step fashion, keeping needed information available until the user dismisses it instead of timing display changes (such as information on the screen of a digital phone), eliminating functions that require simultaneous action, providing mechanisms to speed up, slow down, or repeat information, and using ‘‘select and conﬁrm’’ strategies that involve users conﬁrming they have completed a step in the process (TAAC, 1999). Procedural support strategies address executive function, planning, and sequencing issues, reducing memory load and limiting distraction. Such strategies include providing step-by-step instructions, cue sequences and feedback cues in multiple formats, the use of ‘wizards’ to oVer help and support operation, and automating more complex aspects of the technology use (e.g., storing phone numbers in memory). Finally, content strategies include keeping language simple, highlighting key information or providing summaries of information, and so forth. C.

Summary

This section provided a limited exploration of user characteristics of people with mental retardation that impacts technology use, and technology design features that can address those user characteristics. The ﬁnal section of this chapter will provide a comprehensive review of the literature pertaining to technology use by people with mental retardation.

III.

TECHNOLOGY USE BY PEOPLE WITH MENTAL RETARDATION

The following review is structured within the context of the functional use areas identiﬁed earlier. While much of the literature has not presented research outcomes in light of cognitive ability domains and does not adequately detail universal design features, when such information was provided, we have included it in this review. The review is based on a comprehensive search of databases for any and all articles that involved the use of technology by people with mental retardation. This search yielded 428 articles. Those that directly involved individuals with mental retardation and were databased are reviewed. In many cases, the study participant was identiﬁed primarily as having severe or multiple disabilities or developmental disabilities, not exclusively mental retardation, and in quite a few of these studies people with mental retardation were included in a sample that included people with

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disabilities other than mental retardation. We opted to retain those articles in which it was evident that at least one person with mental retardation was part of the sample and to diVerentiate, if possible, those aspects of the study relevant to this population. In addition, because of the paucity of research with people with mental retardation in the environmental control functional area, these studies have been combined with the activities of daily living and community integration functional area. A.

Review of Literature

1. COMMUNICATION

The largest body of literature pertaining to technology use by people with mental retardation involves communication-related technology, primarily assistive and augmentative communication devices. Being able to communicate is, of course, a critical skill that facilitates interactions with others and enables us to meet our most basic needs. Romski and Sevick (1988) noted that the ﬁeld of mental retardation has adopted a broad deﬁnition of communication, including vocalizations, gestures, and other modes of expression, from among which technology plays a central role. A number of research studies have identiﬁed the potential importance of using technology to provide alternative means of communication for individuals with severe impairments (Blischak, 1999; McGregor et al., 1992; Meyers, 1994; Osguthorpe & Chang, 1988; Schepis et al., 1998). Augmentative and alternative communication (AAC) involves the use of technology in the form of voice output communication aids (VOCA) and synthesized speech, but may also include a wide array of options for communication from low-tech message boards, signing, symbols, pictures, and visual prompts to very complex technology (Blamires, 1999; Blischak & Lloyd, 1996; Hooper & Hasselbring, 1985; Sigafoos & Iacono, 1993). The AAC approaches may be divided into conversational or written formats (Washington AT Alliance, 2003). Due to the multidisciplinary nature of the ﬁeld, the literature related to AAC is diverse, using a number of applications and conditions, illustrating devices that range from very rudimentary to particularly complex technological equipment. The development of speech synthesis techniques in the early 1970s led to the design and use of speech output systems (Baker et al., 1991; Lancioni et al., 2001). As noted, some people with mental retardation are not able to communicate verbally and could beneﬁt from a form of AAC that could involve voice output technology (Detheridge, 1997). Sigafoos and Ianoco (1993) suggested that, in selecting such a device, a person and his or her family, in conjunction with a wider team of professionals, should look at such factors as symbol options (real objects, photographs, or line drawings); the representation of

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the message and how that message is accessed (direct selection, eye gaze, scanning); the options for output such as visual or speech output; and the expandability/portability of the device, related to storage capacity for communication units and the size/weight of the device. The user characteristics that may limit technology use for communication by people with mental retardation include limited attention capacity (Nugent & Mosley, 1987; Odom-Brooks & Arnold, 1976); selective listening (Snyder & McLean, 1977); and limited joint attention to a referent (Snyder & McLean, 1977; Yoder & Farran, 1986). Turner (1986) mentioned that the main reason people with cognitive disabilities may be less likely to use an AAC speech output system is related to a cost/beneﬁt economic decision, in that people with severe disabilities may be perceived (by others) to be so limited, cognitively, so as to not be able to use the device and, as it were, justify the expense, an assumption that might account for why people with mental retardation are not always considered to be candidates for the use of the full range of AAC (Romski & Sevick, 1988; Turner, 1986). However, a growing number of research studies have illustrated the successful use of voice output devices for individuals who have mental retardation and other severe cognitive impairments and who do not use verbal communication (Datillo & Camarata, 1991; Schepis et al., 1996). Research concerning AAC and individuals with mental retardation and severe cognitive disabilities has focused on diverse, but related aspects of the communication process, including communicative intent (Dicarlo & Banajee, 2000), social interaction (Abrahamson et al., 1989), functional communication (Dyches, 1998), symbol recognition (Abrahamson et al., 1989), and communication to encourage positive behavior support (Danquah et al., 1996). A study by Dicarlo and Banajee (2000) used a multiple baseline design to evaluate the eVects of voice output devices for young children with signiﬁcant developmental delays who were not verbal. The Alpha Talker (Prentke-Romich) and a Dual Rocking Lever Switch (Enabling Devices) using Picture Communication Symbols (Mayer-Johnson) were used with two children who were approximately two years old. Increased communication initiations were found for these children following baseline observation and training on the use of one of these devices for each child. At any age, VOCA devices: (1) lessen the burden on the listener, (2) serve as a means of getting attention, rather than having to gain attention ﬁrst before communication starts, (3) and facilitate typical communication by storing messages in advance (Dicarlo & Banajee, 2000; Mustonen et al., 1991). Abrahamson et al. (1989) showed that AAC technology improved the social interaction skills of individuals with mental retardation to establish naturally occurring peer-directed communicative interactions. Use of AAC

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technology has been shown to improve speech comprehension, speech production, attention span, visual attention in a visual-motor task, and social interaction in a study conducted with children with mental retardation in a residential setting (Abrahamson et al., 1989). Studies have demonstrated that people with severe cognitive and multiple disabilities can beneﬁt from using a simple switch to produce functional communication using a tape-recorded message (Dyches, 1998) or to signal the need to continue an activity (Gee et al., 1991). Technology can also be eVective in supporting a person in demonstrating a preference or making a request for an activity (Wacker et al., 1988). Computers can be useful as AAC devices for individuals with mental retardation. Hetzroni et al. (2002) showed that a classroom computer was used eVectively as AAC by incorporating eye gaze technology for young girls with Rett syndrome. Similarly, the System for Augmenting Language (SALI) (Romski & Sevcik, 1996) instructional approach uses computerbased speech output devices to pair symbols with English words. Partners in communicative interactions learn to use the device to augment their speech input to the participant’s symbol input, and ongoing resources and feedback to support both communication partners are put into place. Technology applications have also been used to support communication to decrease agression and self-injurious behavior. One study investigated the use of the Dan Communication System (Dan CS) symbol boards designed with a computerized voice interface to decrease the use of self-injurious behaviors and to support interactions between individuals with mental retardation and their caregivers using audio and visual signs (Danquah et al., 1996). A group of 30 participants with severe mental retardation showed signiﬁcant improvements in control of aggression and increased social interactions with caregivers using Dan CS boards. In a study by Durand (1993), three children ages 3 to 15 years old used the Introtalker (Prentke-Romich) and the Wolf Communication Board (Adamalab) to decrease challenging behavior by using their devices to request items and maintain interaction during activities. Finally, research illustrates that providing communication support for people with cognitive disabilities is often complicated. For example, a case study of a 35-year-old woman with cognitive, physical, and hearing impairments illustrated the multiple means used to support communication (Blischak & Lloyd, 1996), including visual (manual signs and graphic symbols) and auditory (natural speech, VOCA) supports. For quick unaided communication, this woman used gestures or manual signs. Then, both augmented input (traditional orthography, print-based, Blissymbols, communication boards) for cognitive, linguistic, and literacy development and augmented output (VOCA) for quick, audible communication for pragmatic/conversational skills supported further

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development of her communication skills. Messages were included on the VOCA (Digital Augmentative Communicator [DAC], Adaptive Communication Systems) to communicate emergencies, urgent needs, and social routines to interact with individuals who do not sign. 2. MOBILITY

Limitations in mobility have implications for most functional life areas, such as employment, recreation, and community inclusion. Despite the pervasiveness of limitations related to mobility among people with mental retardation, there is little research evaluating the use of technology applications and these limitations. Research that has been published on this issue describes the use of automated systems that guide the user to a destination, and the use of robotic assistance for ambulation (Lancioni et al., 1996, 1998, 1988, 1997). In one study, Lancioni et al. (1996) taught two adults with severe mental retardation and visual impairments to use a radio/light system to assist in indoor travel in familiar and unfamiliar environments. The technology system used involved a portable device that sensed the proximity of designated light sources. The device was capable of turning the lights on as the user approached, and subsequently turning them oV as the user passed a light source. Researchers programmed both the device and light sources for the appropriate route during test sessions. Results demonstrated that not only were the two subjects able to use the system to orient and move independently in the familiar environment, they were also able to successfully generalize the use of the light-guiding system to an unfamiliar environment. Another approach to guiding people with mental retardation in a familiar environment involved the use of ‘‘corridors’’ made of string that could be opened or closed by computer-controlled gates (Lancioni et al., 1988). This research demonstrated that three people with cognitive, vision, and hearing disabilities were able to perform more activities independently when using the system. A similar study published the following year demonstrated that computer cueing systems could help people with mental retardation navigate to desired work activities and increased time-on-task without requiring the constant need of a human supervisor (Lancioni et al., 1989). Lancioni and colleagues also evaluated the use of a robot to provide mobility assistance in guiding users with mental retardation to designated activities within a familiar environment (Lancioni et al., 1997). Two participants with severe mental retardation who were blind and had signiﬁcant to profound hearing loss held the robot’s guiding arm to activate it, and then used the pre-programmed robot to navigate to an appropriate destination

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and complete a simple activity (e.g., depositing containers in a pouch). Results showed that without the robot’s assistance during baseline, subjects were unable to complete any tasks. However, with the robotic intervention, the two participants successfully completed nearly all tasks. Other studies have dealt with more common mobility technologies or addressed gross motor movement for people with mental retardation, as opposed to destination-based movement issues. For example, Mendelson et al. (1995) assessed the technology needs of 268 nursing home residents with developmental disabilities and determined that the equipment they most needed were wheelchairs and seating systems. May (1983) demonstrated that a wheelchair user with severe cognitive and physical disabilities could beneﬁt from a switch-activated system that played music when she lifted her head into a desired position. Similarly, Horn and Warren (1987) used a computer system that activated toy reinforcers to substantially increase motor skills (e.g., pulling, kneeling, sitting up) in two young children with severe, multiple disabilities. Nochajski et al. (1996) took a diVerent approach in examining use and satisfaction of assistive devices for older people with cognitive impairments—several of which involved mobility and motor functioning. Findings from this study indicated that this population typically used physical devices (e.g., walkers or shower chairs) more often than cognitive assistance systems (e.g., labeling systems, cue cards, electronic medication reminders) despite having a stronger dislike of the physical devices. This was apparently due to safety or security needs surrounding physical devices that made their use mandatory (e.g., ambulation must continue, and use of a walker makes ambulation safer and easier even if the subject is dissatisﬁed with the device itself). In contrast, individuals were largely able to discontinue use of cognitive systems (e.g., labels on kitchen cabinets) when dissatisﬁed without compromising safety. Research in this area consistently speaks of the need to provide technology that is adequate for the job it is intended to do (Desch, 1986; Lancioni et al., 1988, 1989; May, 1983). For example, if a technology system is designed to measure and provide reinforcement for head positioning, it must be able to accurately and consistently detect the desired head position. Technological adequacy also may include automation processes to reduce oversight needs and features that prohibit or limit the opportunities for users to make errors. Technologies that have potential for saving caregiver time and organizational expense are also desirable, such as in systems that monitor or prompt performance (Horn & Warren, 1987; Lancioni et al., 1997; May, 1983). Other features described as desirable include: the ability to customize systems to meet the needs of diVerent users or diVerent environments; sturdiness; ﬂexibility; use of color, graphics, and sound

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(Hannaford, 1983); portability (Lancioni et al., 1996, 1998); and safe operation (Nochajski et al., 1996). Researchers have also identiﬁed barriers to the successful use of technological aids for mobility for people with mental retardation. Overwhelmingly, there is a need identiﬁed to provide proper, suYcient, eVective, and timely training to both end users and caregivers on the use of speciﬁc systems (Lancioni et al., 1989; May, 1983; Nochajski et al., 1996). Similarly, technologies that work inconsistently (e.g., software ‘‘bugs’’) or require excessively complex set-up routines can also create barriers and reduce a user’s willingness to try new tools (Hannaford, 1983; Lancioni et al., 1998; May, 1983; Nochajski et al., 1996). Finally, access to the potential beneﬁts of technology-aided mobility is limited by both a lack of information and awareness as to approaches and systems, and by societal attitudes that equate a requirement for technology use with high levels of cognitive functioning (Desch, 1986). 3. ACTIVITIES OF DAILY LIVING, ENVIRONMENTAL CONTROL, AND COMMUNITY INTEGRATION

Technology use can support greater independence in activities of daily living, control over one’s environment, and enhanced community integration (Anderson et al., 1997; Felce & Emerson, 2001; Johnson & Miltenberger, 1996; Lancioni, 1994; Mann et al., 1992; Mendelson et al., 1995). In general, the impact of technology use on community inclusion has not been tested directly and is inferred from the capacity of technology to support greater independence in daily living activities and in environmental control, as well as the potential for technology to support greater mobility around the community, as discussed in that functional area. Studies have examined the use of audio prompts to increase independence. Lancioni et al. (2000) documented the eYcacy of a computer-controlled audio prompt device to enhance completion of table setting and cleaning tasks for two adults with mental retardation. A case study by Lancioni et al. (2002) and supported the eYcacy of audio prompts delivered via a portable tape player in reducing the time needed for a young adult with multiple disabilities to complete dressing and washing activities. Similarly, Browning and White (1986) demonstrated the eYcacy of interactive video-based instructional materials to promote greater community participation and functional life skills for students with mental retardation, and Langone and colleagues have shown the eYcacy of video-based instructional materials to promote community integration skills, such as grocery shopping (Langone et al., 1999; Mechling et al., 2002). Riley et al. (2001) showed that use of The Tickle Box (Adaptive Learning Company), a reminder system that includes a modiﬁed pager to help people

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manage their own activities, by a young woman with fragile X syndrome enabled her to independently complete more daily living tasks than when she was not using the device. Control over one’s environment is also an important component of increased independence to which technology can contribute (Hammel, 2000), although there are few studies that have examined this with regard to individuals with mental retardation. Lancioni et al. (2001c, d) showed that two boys with multiple disabilities could use microswitches to control aspects of their environment, providing a greater range of response options and opportunities for environmental input than without such switches. Hammel et al. (2002) conducted a longitudinal study of people with developmental disabilities who are aging, and found that a majority of persons had better function with regard to community living outcomes with the use of AT. 4. EDUCATION

Technology is widely used in education for a variety of purposes, including communication and supporting activities of daily living (such as eating, recreation, and leisure), as well as to enhance learning. Studies that addressed other functional areas performed in a school context are addressed in those functional areas. This section will present as overview of the technology used to promote learning, largely via computer-assisted instruction (CAI) and multimedia technologies. In addition, educators and policy makers have suggested that technology may be an eVective tool to promote inclusion in the general education classroom and access to the general curriculum (Hasselbring, 1989; Holzberg, 1994; Wehmeyer, Smith, & Davies, in press). However, application of technology to promote the inclusion of students with mental retardation has been limited. Instead, there have been a few studies focusing on CAI for academic and social enhancement that have application to inclusive practices. Research in special education during the 1980s and 1990s examined whether CAI was a complete or stand-alone instructional delivery system, or if some form of teacher guidance was also needed for it to be eVective (e.g., Stevens & Slavin, 1991). The majority of these studies examined commercial CAI math and spelling programs and focused on students with learning disabilities (Higgins & Boone, 1990; Hofmeister, 1984; Horton et al., 1988). For students with mental retardation, studies focused on basic skills and the related practice and automation of these skills. Because CAI can be individualized, repetitive, and systematic in its presentation of material, it has been found to be particularly promising for providing extended practice needed to promote the automaticity of basic skills (e.g., mathematics, word recognition) of students with mental retardation (Kinney et al., 1988).

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The study by Lin et al. (1991) on word recognition improvement typiﬁes a series of comparisons between CAI and traditional instruction. In their study, 45 students with mild mental retardation used a word attack program to strengthen word recognition skills. On the computer screen, the word was ﬁrst introduced, followed by a phrase, and then a series of complete sentences. The outcome of the drill and practice CAI was an increase in the response rate for students, but no signiﬁcant change in the number of correct words identiﬁed. The increased response rate was attributed to improvement in students’ ability to monitor their performance as well as the immediacy of the feedback and reinforcement in the CAI condition. Similarly, Podell et al. (1992) found a decrease on average from 22 seconds to 7 seconds for 71 individuals with a mild mental retardation in the practice of mathematical addition. This exempliﬁes ﬁndings from a series of CAI studies (e.g., Margalit & Roth, 1989; Podell et al., 1992) that found an increase in response rate but not a signiﬁcant improvement in correct responses. Results are consistent across an array of academic content areas, including, addition and subtraction, word recognition, and spelling (Farmer et al., 1992). Subsequent studies comparing CAI and traditional instruction have been extended to include instructional content beyond core academic areas (e.g., social skills) and have thoroughly examined speciﬁc instructional design variables used in software programs as well as face-to-face instruction (Margalit, 1991, 1995). Schery and O’Connor (1992), for example, questioned the beneﬁt of CAI with this population because of the level of supervision required to sustain the interest and the eVectiveness of the CAI intervention. It should be noted that the issue of more intense external support needs appears to be an issue primarily concerning instructional supports for students with more extensive support needs rather than students with mild levels of mental retardation (Jaspers & Van Lieshout, 1994). Lin et al. (1994) examined CAI and mathematic skills in students with and without mental retardation. In the addition portion of their study they found minimal diVerence, but in the subtraction portion diVerences between the CAI and pencil-and-paper conditions were found. Faster response time was reported and attributed to the inherent features of the computer-based program. These ﬁndings extend earlier ﬁndings (Podell et al., 1992) on automaticity and mathematical skill instruction. Similarly, Leung (1994) found that teaching simple addition to children with mental retardation using a computer could improve sustainable performance and generalize to paper-and-pencil applications and related tests. The application of CAI to students with mental retardation has also been shown to beneﬁt skill generalization. For instance, Stevens et al. (1991) delivered instruction on word recognition and spelling via CAI. Student spelling and word recognition performance improved signiﬁcantly and

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outcomes indicated that immediate generalization from computer training to teacher-directed handwritten format can occur without the need of continuous computer-assisted feedback. Likewise, Jaspers and Van Lieshout (1994) showed that students who received technology-based external modeling instruction outperformed other children. Students exposed to this intervention also learned to construct problems internally which transferred to paper-and-pencil situations. Distinct from CAI but equally important in education is research conducted to examine the use of computers or related technologies to assist in the continued engagement of students in the learning experience or a functional task (LeGrice & Blampied, 1994). Lancioni and his colleagues conducted a series of studies to explore the eVectiveness of technology and the role it can play in promoting task performance (Lancioni et al., 1999, 2000, 2001b). In these studies, an electronic device, similar to a PDA, emitted auditory and tactile (vibrations) prompts and oVered step-by-step instructions in the task to be completed. Lancioni and his colleagues found that the computer-based strategy improved performance across tasks for individuals with moderate-to-severe mental retardation. Briggs and colleagues (1990) examined prompt systems for adolescents with moderate-to-severe mental retardation focusing on a self-operated auditory prompting system. Like Lancioni and colleagues, Briggs and colleagues observed generalization of the use of the self-prompting device across settings as well as maintenance of the skill and the problem-solving behavior. LeGrice and Blampied (1994) integrated video prompts to support successful completion of a task. Unlike Lancioni and his colleagues, the video prompting involved preparing the individual to correctly perform the steps. The focus here is to transfer the video prompts to the personal operation of a computer. Studies of the use of video prompting that emerged in special education technology literature during the late 1980s have examined the impact of this technology across disability categories, including students with mental retardation (Woodward & Rieth, 1997). Whether frustrated with the limited nature of traditional CAI technologies or the growth of multimedia-based applications, researchers began to turn to graphic-based multimedia tools as ways to integrate technology into instruction. Spencer (1981) oVered an early example of the eVectiveness of interactive media presentations in his comparison of tape-slide and ﬁlm presentation and their eVectiveness when used as automated teaching aids. Cuvo and Klatt (1992) conducted a more recent examination in the use of videodisc technology with a computer to assist individuals to tell time. Similarly, Wissick et al. (1992) used an interactive videodisc to assist learners with mental retardation to tell time, understand directions, discriminate the worth of coins, and develop

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appropriate social skills. These forms of multimedia instruction build upon previous CAI research (e.g., simple and strategic feedback, practice, explicit strategies) as well as related direct instruction and behavioral components. From early examinations, researchers have expanded multimedia applications reﬂecting a constructivist approach to learning. Rather than teacherdirected instruction, multimedia-based eVorts have fostered learning through media tools. According to Langone and colleagues (1999) a simple multimedia computer-based instruction program can be used to establish match-to-sample skills, as well as subsequent generalization of those skills to the natural setting for students with moderate-to-severe mental retardation. Using photographs of cereal boxes as part of an interactive HyperStudio tutorial, Langone and his colleagues increased the likelihood that selection of speciﬁed cereal boxes would generalize to the grocery store in the community. Other studies have employed media, including video illustrations, to serve as training illustrations for understanding, application, and subsequent use in the classroom or community setting (Mechling et al., 2002; Morgan & Salzberg, 1992; Wissick et al., 1992). By using real-world examples via video illustrations, researchers like Branham and colleagues (1999) have attempted to connect functional exercises in a more contextualized setting, with the expectation that skills will generalize to the real-world setting. The outcome reported by Haring and colleagues (1995) is that individuals with mental retardation can learn skills via rich media-based illustrations in one setting that will generalize to another setting (e.g., community, home). Finally, although not a direct examination of the use of technology on inclusion, Lieber and Semmel (1989) conducted a study to examine whether grouping students impacted social and instructional interaction between children with disabilities and their typically developing peers. The purpose of the study was to compare social and instructional interaction, by way of microcomputers, based on group conﬁguration and alterations to task diYculty. Although the primary focus was not on inclusive practices, per se, the ﬁndings from this study have implications with regard to the potential role that technology can play in promoting inclusive practices for students with mental retardation. Lieber and Semmel found that when paired with typically developing peers with the use of computer technology as the focal point, children with mental retardation were more likely to interact with peers, make positive self-evaluation statements, and make negative peer-evaluation statements. In short, then, there is evidence that technology use, particularly CAI strategies and multimedia technology programs, can inﬂuence the education and inclusion of students with mental retardation by: enhancing motivation, interest, and attention to task in the provision of needed repetition; providing learning opportunities in ecologically valid areas that have

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the potential to generalize to real-world settings; and promoting acquisition in core academic content areas. Technology also has the potential to promote social interaction among students with and without mental retardation. Almost without exception, however, this literature base must be seen as an emerging knowledge base; there is considerable work that remains to be done in this important functional area. 5. EMPLOYMENT

Employment is an area of both importance and dependency for people with mental retardation, and technology use has become an increasingly important way to support individuals with mental retardation in gaining and maintaining employment. The advent of supported employment models that stress the integration of workers with mental retardation into mainstream work environments has provided a more visible role for technology as a valuable support. In 1987, Gaylord-Ross identiﬁed the use of instructional technology as an important element in successful supported employment eVorts. While the use of technology for job training and job skill development, as emphasized by Gaylord-Ross, is still important for people with mental retardation, the emphasis on technology use in this functional area has grown to include the use of technology to provide on-the-job supports and real-time assistance to workers with mental retardation. In addition, technology is being used to teach complex job-related skills that do not pertain to a speciﬁc task or activity, but rather the acquisition of positive behavioral and social skills necessary for successful employment (Morgan & Salzberg, 1992; Storey & O’Neil, 1996). More recent examinations of technology use to improve vocational outcomes for individuals with mental retardation have generally addressed two areas: (1) improvement of speciﬁc job task performance while minimizing human supports from others (i.e., job coaches, supervisors) and (2) improvement of social and behavioral skills related to work settings. Such applications of technology have generally yielded positive vocational outcomes (Davies et al., 2002a; Mitchell et al., 2000; Moccia, 2002; Taber et al., 1998). Teaching appropriate job-related social skills is an area where technology has been applied to support workers with mental retardation. Morgan and Salzberg (1992) investigated the use of video-assisted training on acquisition of employment-related social skills by adults with severe mental retardation. In video-assisted training, participants discriminated a model’s behavior on videotape and received feedback from the trainer for responses to questions about video scenes. Two related studies were conducted. In the ﬁrst, three adults in an employment program participated in video-assisted training to learn the proper method for requesting assistance when encountering work

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problems. The targeted social skill was that of asking for assistance politely and quickly after a problem was identiﬁed. Results indicated that participants discriminated the behavior of soliciting help when viewing the video but eVects did not generalize to the work setting for two participants until they had practiced the behavior. In the second study, two participants were taught to ﬁx and report four work problems using video-assisted procedures. Results indicated that after subjects rehearsed how to ﬁx and report one or two work problems, they began to ﬁx and report the remaining problems with video-assisted training alone. Exploration of the beneﬁts of general purpose audio recording devices, such as tape recorders, have shown that some such readily-available devices can be applied for uses not originally intended. Audio cassette recorders have been used as a self-operated audio prompting device to teach independent living and vocational tasks to students with severe disabilities (Alberto et al., 1986; Briggs et al., 1990). Mitchell and colleagues (2000) taught three students with mild mental retardation to use a cassette recorder as an auditory prompting system to assist with a variety of vocational skills in a middle school. The ability of the students to learn to operate the recorder and follow the instructions was assessed, as well as the ability to generalize the acquired skills to another setting. In addition, eVects on skill maintenance were assessed. Students were taught how to turn on the cassette recorder, listen to the auditory instructions while wearing headphones, and to turn oV the cassette recorder after listening to the instruction and hearing a ‘‘beep.’’ Students were instructed to verbalize the step and then perform it. A multiple probe across behavior design was used and the results demonstrated that students were able to acquire the targeted skills and that the skills did transfer to another setting. In another study, a portable cassette recorder with step-by-step recorded prompts was used to evaluate the utility of a self-operated auditory prompting system with ﬁve school-age workers with moderate mental retardation using prompts delivered in one-word or multiple word instruction segments (Taber et al., 1998). Instructions were presented in a ‘‘to-do’’ list format. Subjects were taught to press the play button to listen to the task, and then stop the recorder between tasks. The number of successful transitions from one task to another measured task performance, as subjects had demonstrated great diYculty moving from one task to the next independently in baseline sessions. Results showed signiﬁcant improvement in the ability to change from one task to the next when using either the single or multiple word auditory prompting system. There were no signiﬁcant diVerences found when comparing the single and multiple word auditory prompting approaches. Computer-based prompting devices with specialized interfaces have been applied to support vocational tasks. Moccia (2002) described a system used

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to provide vocational supports that was designed speciﬁcally for individuals with mental retardation to provide self-directed audio prompts as well as a system using both audio and picture prompts to support independent task performance in vocational settings. This system was evaluated in an employment setting to assess its utility for improving task accuracy and independence in accomplishing two diVerent vocational assembly tasks, folding pizza boxes and packaging a commercial software product (Davies et al., 2002b). Ten individuals with mental retardation performed each task with and without the presence of the technology system. The self-directed visual and auditory prompting system was implemented on a Windows CE portable computer that allowed custom picture prompts and audio instructions to be delivered with a simple interface designed speciﬁcally for individuals with mental retardation. The system is self-contained and uses a Windows CE handheld computer to allow caregivers to create personalized task instructions. The portable computer served both as the digital camera (using a compact ﬂash camera that was inserted into the portable computer) for taking pictures of each step in the task as well as a digital recorder for recording verbal instructions. After initial training on both the task and use of the computer system, subjects used the specialized software to follow step-by-step picture and audio prompts at their own pace. Results indicated that the computerized prompting system signiﬁcantly improved task performance. In addition, these gains were achieved with signiﬁcantly greater independence, as measured by the amount of assistance required from a job coach to complete each task. In addition, subjects expressed positive reactions as well as preference for using the specialized prompting system. A series of six single case experiments were reported in which a portable, computerized prompting system was evaluated in real-work settings (Furniss et al., 1999). A portable computer system was used to present pictorial instructions and audio prompts of each step in a number of work tasks, which included a radio communication system for alerting job coaches when help was needed. While researchers reported that results were somewhat mixed, overall they suggested that the portable computer-aided prompting system was eVective in enabling subjects to achieve higher task accuracy scores following a brief period of intensive training, particularly for more complex tasks that were new to the individuals. However, they also reported that the nature of the task may have been more important than the persons’ ability in determining the utility of the portable computer system. These data suggested that matching the technology intervention to the task is an important selection factor that should be considered, as well as matching the technology intervention to the speciﬁc individual’s needs and abilities. Furniss and colleagues (2001) summarized ﬁve studies, including Furniss et al. (1999), in which evolving versions of this same portable computerized

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prompting system were used to improve performance accuracy for individuals with severe disabilities. These studies collectively demonstrated that a computerized prompting system was more eVective than using pictorial instructions presented in booklets, that users repeatedly preferred use of the computerized system to picture booklets, and that the computerized system was usable in real-work settings. The authors also noted that eVective use of the system required job coaches to acquire competence in systematic instruction as well as basic computer skills. For example, set-up of the prompts and timing information is performed on a desktop personal computer and then downloaded to a ‘‘player’’ application on the portable computer; job coaches need basic computer skills to manage these activities. In addition to end users with severe disabilities preferring the technology supports, Furniss and colleagues (2001) reported that caregivers and coworkers viewed the use of the technology by their co-workers with disabilities very positively. Positive impacts of note included social interaction and conversation regarding use of the technology. In addition to technology applications for providing self-directed prompting to facilitate task performance, research has also addressed use of technology to promote time management in vocational settings. Davies et al. (2002a) described a software program running on a portable computer that can be used by supervisors, job coaches, or other caregivers to create a picture and audio-based scheduler that can be programmed to prompt users on speciﬁc vocational activities at a particular time or according to a predeﬁned schedule of activities. At the prescribed time, the handheld computer turns itself on and alerts the individual to the activity using a combination of audio and visual alarms, a picture cue representing the event, and personalized audio messages describing what the individual needs to do at the particular time. Study participants were required to initiate a number of tasks at speciﬁc times. An error was recorded if the individual failed to initiate the activity at all, if he or she did not initiate the activity within one minute of the scheduled time, or if the activity was initiated too early. Results showed signiﬁcant improvement in the ability to initiate tasks on schedule in response to the prompting system as compared to baseline data. Although studies on the application of technology in supported employment have been sparse, extant evidence suggests that technology systems, particularly those designed to address support and user-interface needs of individuals with mental retardation, can improve vocational outcomes for many individuals. These outcomes can also be sustained over time, as demonstrated by Mann and Svorai (1994). Their project demonstrated successful placement of 17 of 27 persons during a 3-year demonstration project of individuals who had utilized a computer training system to learn skills necessary to retain basic computer jobs.

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6. SPORTS AND RECREATION

Applications of technology to the area of sports, recreation, and leisure has considerable promise to improve the quality of life of people with disabilities (Cain, 1984). Being able to ﬁll spare time in purposeful ways is important to one’s quality of life. Recreational programming of age-appropriate skills helps to bridge the gap between individuals with and without disabilities for inclusion in community settings (Sedlak et al., 1982). Toy use by children with mental retardation has been studied extensively. Particularly for young children with multiple cognitive and sensory disabilities, toys using switches and other technologies encourage play, motivate movement, and support cause-eVect learning. Switches are simple and intuitive, and can be mastered with low physical eVort (Bailey, 1993). Behrmann et al. (1989) suggested that technology can beneﬁt young children to encourage learning, recreation, and life skills. In fact, various sensory modalities can be encouraged by technology use: visual sensory input can be supported by ﬂashing and blinking light toys; auditory input by tape recordings, music, and sounds; and tactile input through the use of vibrating toys. There has been some discussion of the motor skills (range of motion, press and release), visual perceptual skills (visual tracking, ﬁgure ground), cognitive or language skills (cause and eVect, attention span that is sustained and selective, object permanence, making choices), and social skills (turn-taking, following one-step directions) needed for initial switch or technology use (Behrmann et al., 1989). However, these skills can be supported in young or less capable individuals to encourage participation for technology use. Research also shows that older students with mental retardation can beneﬁt from the use of microswitch technologies. In a multi-component study by Kennedy and Haring (1993), recreational stimuli were used to provide a contingency for choice. Participants used microswitches to request a change related to recreation, and the use of this technology increased the level of alertness and response to interactions by children and adolescents with mental retardation in school settings. A study by Realon et al. (1988) assessed the use of adapted leisure materials on the engagement of people with multiple disabilities, including people with mental retardation. They determined that adapting electrically operated leisure activities was a cost-eVective way of increasing the independent leisure activity engagement of adults who had severe, multiple disabilities. Realon et al. (1989) compared the use of adapted leisure materials with standard, unadapted materials. Adapted leisure materials were found to beneﬁt visual tracking, motor control, communication, and independence of participants. According to Bailey (1993): ‘‘Learning to operate a simple

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switch opened up the world of choice for people with severe multiple impairments’’ (p. 343). Computer or video games provide age-appropriate, socially acceptable opportunities to both participate in preferred leisure and recreation activities and learn a number of cognitive and eye-hand coordination skills. Cain (1984) suggested that computer-gaming devices are the only recreational media that are interactive, in contrast to radio, television, and movies in which the observer is passive. A study by Sedlak et al. (1982) investigated the ability of three adolescents with severe cognitive impairments to learn to play a popular video game and generalize this skill to a community setting. Two of the three students were able to accomplish these objectives with a minimum of instruction and follow-up. In another study, leisure skills, including playing cards, selecting a television program, playing a sports videotape, and playing a computer game, were taught to four secondary students with moderate intellectual and motor disabilities using a system of least prompts (Collins et al., 1997). During generalization, these students were able to perform the tasks with little prompting as monitored by peers without disabilities. Increased interaction with non-disabled peers was also supported through the students’ mutual interest in the technology applications. The World Wide Web has become a source of recreation and leisure for many people. Barriers for people with mental retardation to use the Web include limited opportunities to use computers, lack of appropriate and cognitively accessible Internet-access software, and the complexity of computer operating systems and amount of reading required. Davies et al. (2001) examined a prototype Web browser, Web Trek (AbleLink Technologies), which was designed to provide access to the Internet for individuals with mental retardation. The performance of 12 participants with mental retardation was compared on two browsers—the Web Trek and Microsoft’s Internet Explorer. Measuring independence, accuracy, and task completion, participants showed signiﬁcantly more success using the Web Trek browser. The Web Trek was able to reduce screen clutter to minimize confusing symbols, could be personalized to support user’s preferences, used pictures and audio prompts rather than text-based directions, and supported error minimization to support universal design for access. According to Nielson (1996), online information provides many beneﬁts compared with printed text, including ease for people with poor eyesight to increase font size and text-to-speech conversion for people who are blind or do not read. Recreational pursuits such as exercise and physical ﬁtness have also been supported with the use of technology. A study by Stanish et al. (2001) measured the eVects of leader support to facilitate engagement in moderate-to-vigorous physical activity related to aerobic dance with

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17 adults with mental retardation. The program was video-based and lasted 10 weeks. Participants were divided into two groups; one group had an exercise leader. Through the video-based exercise activities, people with mental retardation were able to engage in recreational activities that also would lead to improved health. Douglas et al. (1989) used technology to provide reinforcment for a 14-year-old student with moderate levels of mental retardation to ride a stationary bike so that a minimum amount of teacher supervision was required for exercise to occur. Of the three conditions (television, ﬂashing lights, or vibrator sound), the most eVective reinforcing consequence for the student’s exercise behavior was vibrator sound. Another instance of exercise management was a study completed by Ellis et al. (1992) that used a digital kitchen timer and an adapted lap counter to facilitate selfmanagement of exercise for ﬁve students with moderate and severe mental retardation. Time-management related to exercise and physical ﬁtness is a need for many people, including people with mental retardation. 7. SUMMARY

The above literature base provides, in our opinion, ample evidence of the potential for technology to inﬂuence the lives of people with mental retardation across multiple functional domain areas. In general, however, there are too few studies (and too few studies that go beyond a pilot examination) on the impact of technology with this population, especially in certain domains. For example, there has been limited demonstration in the research literature of the potential beneﬁts that technology can provide to increase mobility opportunities for persons with mental retardation. It would appear that this is more accurately attributable to a lack of scientiﬁc evaluation in this area, as opposed to limitations in available technologies, devices, or methodologies of implementation. Indeed, what literature there is indicates that AT appear to be most used when driven by fundamental needs, a person may or may not have to execute mathematic equations, but will always have to perform certain activities (e.g., eating, showering, positioning) in which some type of mobility is inherent (Horn & Warren, 1987; Nochajski et al., 1996). The potential for technology-assisted mobility can be seen in the remarks of Lancioni and colleagues (1998) noting that mobility is ‘‘(a) essential for participating in diVerent functional activities, (b) overturns the stigma of sedentariness, and (c) may have beneﬁcial eVects on behavior.’’ In other functional areas, such as communication, education, and employment, there is more relevant research. With regard to the last, for example, there is quite a bit of evidence suggesting that technology can be used to teach job skills and knowledge to individuals with mental retardation and to provide support to them in job situations, thereby overcoming impairments

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that limit productivity. There is particular promise on the impact of new and emerging technologies, such as providing support through handheld personal computers. It is also evident, even in these more prevalent areas, that there is little research that examines in any speciﬁcity the factors that support or hinder technology use or factors that combine with technology use to enhance success. These issues, among others, comprise critical issues for future directions. B.

Future Directions

Does technology hold the same promise for a better life for people with mental retardation that the Tech Act holds to be true for all people with disabilities? The answer would seem to be an unqualiﬁed ‘‘yes.’’ The challenge is to turn that promise into reality. Such an outcome will require the combined eVorts of policy makers, people with disabilities who use technology, technology developers, professional, and other advocates to address barriers to that outcome, many of which have been documented in this chapter. In considering the role of research, several issues seem particularly important. First, an examination of the literature suggests that in too many cases, issues pertaining to the characteristics of people with mental retardation were of secondary or no real concern in the evaluation of the use and impact of technology. With only a few exceptions, technology devices have not been designed or evaluated with the access needs of people with mental retardation in mind. Only a handful of studies addressed issues of technology use pertaining to cognitive impairments, and none, to our knowledge, have actually evaluated the relative importance of the various principles of universal design on technology use by this population. Future studies need to go beyond the basic ‘‘can this work with this person or these people’’ design and examine not only the impact of technology on particular functional areas, but also examine the multiple factors that inﬂuence that technology use, including environmental factors, factors related to the individual user, and factors pertaining to the device’s design. The issue of research design and the general quality of the research in this area is a second area that needs attention. There are too few studies that use rigorous research designs or conduct longitudinal research that can provide causal linkages between technology use and positive outcomes. A recent report examining areas of research need with regard to technology and mental retardation, Rizzolo et al. (2003) noted that large-scale, longitudinal studies are needed to examine some of these issues. Finally, the movement from a deﬁcit focus to a functional deﬁnition of mental retardation places much more importance on technology to improve

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the functioning of individuals with mental retardation, and the research base needs to move from documenting how individual deﬁcits impact technology use to how technology can enhance cognitive abilities and enable people to succeed. We are to a point where our knowledge of cognitive abilities and our capacity to design technology to impact those abilities are both advanced enough that yesterday’s science ﬁction scenario can become today’s technology support. Digital wireless telephone and Internet technologies; global positioning data and devices capable of utilizing these data; portable, powerful computers with accessible input/output capacities; nanotechnology; personal digital assistants—the potential to beneﬁt the lives of people with mental retardation is signiﬁcant. These technologies can augment cognitive abilities ranging from memory and attention, to computation and decision-making skills. There is a hopeful start to achieve the promise of technology for people with mental retardation, but much remains to be done to make it a reality. REFERENCES Abbeduto, L. (1991). Development of verbal communication in persons with moderate to mild mental retardation. In N. Bray (Ed.), International Review of Research in Mental Retardation (Vol. 17, pp. 91–115). New York: Academic Press. Abbeduto, L. (2003). Language and Communication in Mental Retardation (International Review of Research in Mental Retardation, Vol. 27). New York: Academic Press. Abrahamson, A. A., Romski, M. A., & Sevcik, R. A. (1989). Concomitants of success in acquiring an augmentative communication system: Changes in attention, communication, and sociability. American Journal on Mental Retardation, 93, 475–496. Alberto, P. A., Sharpton, W. R., Briggs, A., & Stright, M. H. (1996). Facilitating task acquisition through the use of a self-operated audio prompt system. Journal of the Association for Persons with Severe handicaps, 11, 85–91. Anderson, M. D., Sherman, J. A., Sheldon, J. B., & McAdam, D. (1997). Picture activity schedule and engagement of adults with mental retardation in a group home. Research in Developmental Disabilities, 18, 231–250. Bailey, D. M. (1993). Technology for adults with multiple impairments: A trilogy of case reports. American Journal of Occupational Therapy, 48, 341–345. Baker, B. R., Stump, R. T., Nyberg, E. H., & Cocnti, R. B. (1991). Augmentative communication and vocational rehabilitation. Journal of Vocational Rehabilitation, 12, 71–83. Behrmann, M. M., Jones, J. K., & Wilds, M. L. (1989). Technology interventions for very young children with disabilities. Infants and Young Children, 1, 66–77. Blamires, M. (1999). Enabling technology for inclusion. Thousand Oaks, CA: Sage. Blischak, D. M. (1999). Increases in natural speech production following experience with synthetic speech. Journal of Special Education Technology, 14, 44–53. Blischak, D. M., & Lloyd, L. L. (1996). Multimodal augmentative and alternative communication: Case study. Augmentative and Alternative Communication, 12, 37–46. Branham, R. S., Collins, B. C, Schuster, J. W, & Kleinert, H. (1999). Teching community skills to students with moderate disabilities: Comparing combined techniques of classroom

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Index

intelligence/behavior trajectories for children of, 204–206 interactions between children and, 206–208 interrelating developmental trajectories for children and, 208–209 intervention programs for, 223–224 maternal depression of, 205 maternal/child characteristics of children and, 219–220 mild mental retardation risk factor in children of, 213–216 model of, 199–201 pathways to developmental delays of children with, 209–223 self-regulation of children of, 218–219 social consequences of, 197–198 Adoptive care, as intervention in maternal drug abuse cases, 49–52 Age AD onset, 160 of AD onset/DS death, 169 as AD risk factor in DS, 161–164 cocaine-exposed newborns’ gestational, 42 Cognitive-linguistic profiles and, 14 gestational, 235 health problems of people with ID related to, 159 of menopause, 179 mental/chronological, 15 AIDS. See Acquired immunodeficiency syndrome Alcohol, 35. See also Fetal alcohol syndrome Alcohol-related neurodevelopmental disorder (ARND), 34 Alpha-methyl-p-tyrosine (AMPT), self-biting and, 134

A AAC. See Augmentative and alternative communication A-B-C paradigm, 246 Abuse cocaine use and physical, 47 developmental difficulties of children with history of, 221–223 Achievement of adolescent mothers’ children, 201–202 impact on technology, 307–308 parenting predicting child’s academic, 220 of successful outcomes of employment, 281–282 Acquired immunodeficiency syndrome (AIDS), 185 AD. See Alzheimer disease ADI. See Autism Diagnostic Interview Adolescent mothers. See also Notre Dame Adolescent Parenting Project abused children vs. children of, 221–223 achievement of, children, 201–202 adjustment/adaptation of children with, 202 attachment of children of, 201 characteristics of, 197–198 cognitive readiness of, 200 constructs central to understanding, 199–200 developmental delays’ early onset of children of, 201–202 disorganized attachment in children of, 213–218 early parenting’s importance by, 206–209 influence on children’s development, 199–202 339

340 Alzheimer disease (AD) age as risk factor in DS of, 161–164 age of onset of, 160 ApoE genotype influences risk of, 164, 170 ApoE genotype on onset age of, 169 brain reserve capacity’s individual differences and, 170–177 brain size impact on development of, 171 CAMDEX assessment of, 163 cholergenic functioning in, 179 in DS and folate metabolism/B-group vitamins, 181–185 DS etiological links to, 159–160 in DS impacted by gender, 180–184 education level achieved associated with risk of, 172 ER impacted women’s increase in risk of, 178 ERT reducing risk of, 178 estrogen reduction increasing risk of, 177 family history of, 186 gender as risk factor for, 179–180 genetic factors’ role in onset of, 164–170 head injury increasing risk of, 175–177 ID level/level of, 173–174 institutionalized settings and, 172 meta-analysis, 168 neuropathological characteristics of, 159–160 oxygen-derived free radicals linked to, 176 risk factors in DS of, 160–164 women as experiencing more severe form of, 182 AMPT. See Alpha-methyl-p-tyrosine Amyloid precursor protein (APP), 160 ApoE genotype. See Apolipoprotein E genotype Apolipoprotein E (ApoE) genotype on AD meta-analysis, 168 AD risk influenced by, 164 cognitive functioning aspects and, 169–170 on death age in DS, 169 DS frequencies of allele and, 166–168 estrogen and, 177 gender and, 181 on onset age of AD, 169 in plasma lipoprotein metabolism, 164

index APP. See Amyloid precursor protein ARND. See Alcohol-related neurodevelopmental disorder Assessment instruments development, 34–35 as intervention, 251 Assistive technology as defined, 292–293 functional limitations of, 293–294 At-risk mothers. See Adolescent mothers Attachment adolescent mothers’ children having disorganized, 213–218 caregiver-child relationships formed with, 243 of children with adolescent mothers, 201 classifications/stability of, 214 cognitive regulation as mediator of relationship of intelligence and, 216–217 developing children with insecure, 242–243 development differences of children’s secure/disorganized, 214–215 environment variables on infant, 211 intelligence consequences of, 211 IQ relationship to, 213 mild mental retardation risk factor as disorganized, 213–216 model of self-regulation and, 210–213 parenting and variance of children’s, 215–216 security, 212–213 self-regulation development delayed by insecure, 212 theory of, 241–243 Attention shifting, of children with SBM, 90–91 Augmentative and alternative communication (AAC) computers as, 314 for people with mental retardation, 312–313 research on, 313 social interaction improved by, 313–314 Autism BG structures involvement in, 131 intervention with children with, 246 Autism Diagnostic Interview (ADI), 131

341

index B Basal ganglia (BG) action sequencing in disorders of, 131–132 autism involvement of, 131 corticostriatal connection in, 121–123 DA depletion in system of, 133 damage to structures of, 141 dysregulation, 139, 143 emotional-motor disorders involving alterations in processing of, 129–130 excitotoxic damage and, 122–123 functional diversity of, 124 functional nature of system of, 121 hypoxia/ischemia susceptibility of structures of, 123 information integration in system of, 126–129 inputs’ convergence/divergence in system of, 125–126 inputs from outside sources to, 128–129 intrinsic processing of, 126, 127 Lesch-Nyhan diseases disorder of, 130 motor problems role of, 141 motor programs influenced by, 139 motor/sensory control between channels through, 128 neurodegenerative disease and, 129–130 non-motor functions of system of, 120–121 output principles of function of, 124–125 parallel circuits of system of, 123–125 pathology and developmental disorders, 130–132 pemoline effects as significant in system of, 137 Rett syndrome involvement of, 131 self-biting in pemoline model/DA alterations in, 136 in SIB production, 120 stereotyped self-injury relationship to function of, 132–141 system of, 120–130 Bayley Scales of Infant Development, 34 Behavior. See also Challenging behavior adaptive theory of, 243–244 adolescent mothers’ children’s developmental trajectories for, 204–206

biological factors with potential to affect, 234–235 characteristics of young children with developmental disorders, 232–235 cultural influence on child, 238–239 DS characteristics of, 2 ecological context of, 235–239 elicitation by children of adult, 17–19 etiology-based research issues on, 11–24 etiology-related distinctive, 8–9 etiology-related high vs. low abilities and maternal, 20–21 etiology’s importance for people with mental retardation, 5 functional analysis of, 246 genes-brain connection to, 12–14 genetic disorders on outcomes of, 6–7 genotype, 232–235 inherent, 232–233, 239–240 knowledge dispersed about etiologyrelated, 23–24 maladaptive, 10 nervous system functions of, 34–35 partially specific effects of, 9 regulation of children with SBM, 97–98, 100 reinforcement, 20–21 SBM/developmental disorders with, 81–83 Behavioral phenotypes. See also Genetic mental retardation areas of interest concerning, 11–24 definitions/findings of, 6–11 deterministic definition vs. probabilistic definition of, 7–9 development disorders and, 233–234 differences of people with MR and, 2–6 domains of, 9 research on, 1 Behavioral teratology, 31. See also Teratogenic agents biological nature of, 32 dose-response relationship of, 32–33, 42 environmental determination of, 33 prenatal exposure to cocaine as, 53 principles of, 32–34 response relationships of, 34 susceptibility to agents of, 32–34 types of teratogens in, 33–34 BG. See Basal ganglia

342

index

B-group vitamins AD in DS risk and, 184–185 deficiencies in, 185 Bioengineering Program, 296 Brain. See also Basal ganglia; Spina bifida meningomyelocele behavior/genes connection with, 12–14 behaviors’ derivation in relation to biophysical perspective of structure of, 234 corpus callosum/cerebral commissures of, 92–95 corticostriatal connection in, 121–123 DA cell-rich areas of, 126–127 Down syndrome link to functioning of, 13 dysmorphologies of SBM, 86, 88–96 head injury and, 175 reserve capacity hypothesis, 170–177 size, 171–172 SMB and midbrain/cerebellum of, 86, 88–91 Brazelton Neonatal Behavioral Assessment Scale, 34 Breast cancer, risk increased after menopause, 177

C Caffeine, self-biting and, 137–138 CAI. See Computer-assisted instruction Cambridge Examination for Mental Disorders of Elderly (CAMDEX), 163 CAMDEX. See Cambridge Examination for Mental Disorders of Elderly Central nervous system (CNS) behavioral functions measured of structures of, 34–35 development of, 54 neurogenesis, 34 plasticity of, 40–41 teratogens, 33–34 Cerebral palsy, 5, 65 Challenging behavior. See also Self-injurious behavior children with developmental disabilities and, 229–232 defining, 230 development of, 252 ecological context of, 232–239

ecological model of intervention for, 245–252 environment’s contribution to development of, 239 examples of, 230 family experience impact on developing, 236 implications for intervention for, 251–252 inherent behaviors of children and, 239–240 interactive difficulties relation to, 240–241 multiple problem family environment on developing, 238 origin of, 229 outcomes of, 231–232 poverty’s impact on, 236–237 stress in family environment contribution of, 231 temperament traits contribution to, 240 CNS. See Central nervous system Cocaine cognitive deficits and, 36 developmental/influence’s relationship to prenatal exposure of, 39–41 direct/indirect effects of child development of, 37–39 gender-specific behavioral effects related to prenatal exposure to, 45–46 long-term consequences of prenatal exposure to, 43–47 maternal health of users of, 48–49 neurodevelopment process altered by prenatal exposure to, 40–41 newborns/infants with prenatal exposure to, 41–43 parent-child interactions affected by abuse of, 47–48 parenting by women with history of abuse of, 47–49 physical abuse and use of, 47 prenatal exposure as behavioral teratogen of, 53 prenatal exposure studies on, 35–37 stigmatization of children affected by prenatal use of, 36–37 subtle effects of, 36–37 Cognition SBM/developmental disorders with, 81–83 SBM’s neural phenotype’s relationship with functions of, 86–95

343

index Cognitive-linguistic profiles, age-related course of, 14 Computer-assisted instruction (CAI), 318–321 Cornelia de Lange syndrome, 136 Coronary artery disease, risk increased after menopause, 177 Corpus callosum, SBM and, 92–95 Corticostriatal loop, 121–124 Crack. See Cocaine Culture child development role of, 238–239, 245

D DBS. See Deep brain stimulator technique Deep brain stimulator technique (DBS), 143 Dementia age-specific rates in DS of, 160 DS and genotype/allele frequency and, 166–168 DS’s prevalence rates of, 161 ERT and reduction of, 178 frontal love/Lewy body, 174 gender effect on, 180–182 types in DS, 163 Depression, 186 maternal, 205 risk increased after menopause, 177 Development adaptive theory of, 243–244 adolescent mothers’ influence on children’s, 199 bidirectional effects and, 17–18 challenging behavior’s impact on child, 231 of children with SBM, 95–109 delays during infancy/early childhood, 198–202 early onset of adolescent mothers’ children’s delays in, 201–202 etiology-related profiles’ changes from, 14–15 interrelating mothers’/children’s trajectories of, 208–209 pathways to delays in, 209–223 prenatal drug exposure’s multiple pathways of effect on children’s, 37–41 secure/disorganized attachment of children causing differences in, 214–215

of self-regulation, 211–212 teratogenic compounds and brain, 53–54 transactional model of, 244–245 Development Neuropsychological Assessment (NEPSY), 46 Developmental disorders A-B-C paradigm contribution to field of, 246 animal model use for studying neural basis of motor dysfunction in, 132 attachment theory of, 241–243 behavioral characteristics’ sources of young children with, 232–235 behavioral phenotypes and, 233–234 BG dysfunction and, 141 BG pathology and, 130–132 challenging behavior of children with, 229–232 child/caregiver interactions of children with, 241 inherent behaviors of children with, 232–233 leading to SIB, 141 motor symptoms in, 130 neurotoxicity as cause of, 123 premature infants developing, 234–235 regulatory disordered infants and, 234 SBM and, 81–83 temperament of children with, 233 Developmental neurotoxicology, 31 approaches in field of, 35 Diet neural tube defects and, 73–74 for Prader-Willi syndrome, 23 Disability. See also Developmental disorders; Intellectual disability concept of, 263 current trends in employment practices and, 270–274 economic disadvantages of people with, 266 employer satisfaction with work performance of person with, 277–281 employment implications from perceptions at macro level of, 263–269 exclusion experiences of people with, 265–266 job retention of people with, 273–276 macro system of, 267–269

344 Disability (cont. ) quality of life of people with, 266 social model vs. medical model of, 264 sports/recreation applications of technology for people with, 326–328 understanding in ecological context of, 264–265 variables affecting employment outcomes of people with, 274 Down syndrome (DS) activities of people with, 16–17 AD’s etiological links to, 159–160 advantage, 19–21 age as AD risk factor in, 161–164 age-specific rates of dementia in, 160 animal models of, 142–143 ApoE as factor for AD in people with, 165–166, 170 ApoE on death age in, 169 behavioral characteristics of people with, 2 brain functioning link to, 13 brain reserve capacity increased in people with, 175 brain size impact on, 171 causes of, 5 cholergenic functioning in, 179 complications of, 185 dementia types in, 163 dementia’s prevalence rates in, 161 folate metabolism/B-group vitamins and AD risk in, 184–185 gender effects on, 180 gender impact on AD in, 180–184 gender/menopausal status on cognitive functioning in, 178–179 as genetic cause of ID, 159 genotype/allele frequency in, 165–166 genotype/allele frequency/dementia in, 166–168 hypoplasia of frontal lobes in, 174–175 institutionalized settings on rates of AD in, 172 language deficits and, 12 life expectancy of people with, 159 linguistic grammar deficits and, 7–8 oxygen-derived free radicals linked to, 176 premorbid ability level and, 172–173 research on, 6 risk factors of AD in, 160–164

index visual-over-auditory short-term memory of people with, 14 Drugs. See also Cocaine; Prenatal drug exposure adolescent mothers and abuse of, 199–200 foster/adoptive care as intervention for maternal abuse of, 49–52 maternal mental health and use of, 48–49 prenatal/perinatal medical care and use of, 33 DS. See Down syndrome

E Ecology children impacted by, 235–239 S-O-R-K-C behavioral equation and, 249–251 Education. See also Learning; Learning disorders AD risk associated with low attainment in, 172 mothers with low, 218–219 self-regulation promoting attainment of, 211 technology use in, 318–322 Employment barriers to successful outcomes of, 262 context of ID and, 265–269 current trends in practices of disability, 270–274 disability perceptions’ implications for, 263–269 diversity in, 268 ecological systems theory and, 262–263 employer satisfaction with work performance of person with disability in, 277–281 employers’ perceptions/attitudes in, 274–276 employers’/service providers’ relationship and, 280 influences affecting outcomes of, 261–262 job retention of people with disability in, 273–276 low rates of people with ID, 282–283 macro system of, 267–269 maximizing achievement of successful outcomes of, 281–282

345

index natural supports for outcomes in, 275 partnership approach in, 271–272 post-placement support for, 275–276 practices promoting success of people with ID in outcomes of, 269–281 programs, 274–275 quality of life of people with disability and, 266 social environment’s importance in outcomes of, 270–271 social skills and, 322–323 success in outcomes of, 261–262 support of disability history, 269–270 technology application in supported, 325 technology used by people with mental retardation in, 322–325 variables affecting employers’ attitude about disability in, 276 Environment adaptive theory of children’s relationship to, 243–244 adolescent mothers’ children’s immediate caregiving, 211 challenging behavior development contribution of, 239 challenging behavior’s contribution to stress in family, 231 choosing one’s, 16 eliciting behavior and, 17–18 of employment of people with ID, 262 employment outcomes/workplace, 270–271 etiology-related profiles affected by, 15–17 individuals’ compatibility with workplace, 272–273 inherent behaviors as means to modify children’s caregiving, 239–240 inherent characteristics of child interaction with caregiving, 244 mentally retarded children’s caregiving, 243 multiple problem family, 238 poverty/caregiving, 237 prenatal cocaine exposure and influences of, 39–40 SBM and factors of, 73 stimuli in, 247 technology enabling people with mental retardation control over, 318 transactions between child and, 17

Epilepsy, 176 ER gene. See Estrogen receptor alpha gene ERT. See Estrogen replacement therapy Estrogen. See also Estrogen receptor alpha gene; Estrogen replacement therapy AD risk increased by reduction of, 177 menopause marked by reduction of, 177 models of effect of, 177–178 neuronal plasticity modulated by, 178 neuroprotective effects of, 177 Estrogen receptor alpha (ER) gene, AD risk in women impacted by, 178 Estrogen replacement therapy (ERT) on cognitive performance of women, 178 dementia reduction and, 178 in women with ID, 179 Etiology-related profiles development caused changes in, 14–15 environment as affecting, 15–17 Exclusion, experiences of people with disability, 265–266

F FAS. See Fetal alcohol syndrome Fetal alcohol syndrome (FAS). See also Prenatal drug exposure as MR cause, 3 as preventable form of mental retardation, 31 Folate metabolism, 72 AD in DS risk and, 184–185 genes involved in, 77–78 MTHFR/MTRR and, 185 Foster care. See Adoptive care Fragile X syndrome, 5, 14 animal models of, 142–143 attention-hyperactivity of people with, 22 research on, 6 Free radicals, 176

G Gender AD in DS impact by, 180–184 as AD risk factor, 179–180 ApoE genotype and, 181

346

index

Gender (cont. ) cocaine, prenatal exposure, behavior and, 45–46 cognitive functioning’s impact by, 180 dementia effected by, 180–182 Genes to behavior to brain connections, 12–14 in folate metabolism, 77–78 HOX/PAX, 79 neural tube defects caused by, 78 Genetic disorders. See also Genetic mental retardation on behavioral outcomes, 6–7 Down syndrome advantage effect of, 19–20 etiology-related strategies of intervention for, 21–24 indirect effects of, 19–21 neurological functioning in, 22 specifying indirect effects of, 17–21 Genetic mental retardation behavioral effects of, 8–9 behavioral research on, 6, 24–25

H HD. See Huntington’s disease Hierarchical Linear Modeling, 205, 208 Huntington’s disease (HD), 129 Hyperactivity, 9 Hyperphagia, 10

I ID. See Intellectual disability Information technology, 293 Instruments, development assessment, 34–35 Intellectual disability (ID). See also Employment AD level/level of, 173–174 age-related health problems of people with, 159 comorbid psychiatric disorders at severe levels of, 171 dementia’s prevalence rates in, 161 employer experience with employees with, 276

employment and low rates for people with, 282–283 employment context and, 265–269 employment environment of people with, 262 employment implications from macro level perceptions of, 263–269 employment outcomes’ barriers to success of people with, 262 employment outcomes for people with, 261 employment outcomes success maximized for people with, 281–282 employment practices for successful outcomes and, 269–281 ERT rate in women with, 179 head injury/AD risk without DS with, 175 menopause in women with, 179 task-related social skills taught to people with, 270–271 Intelligence of adolescent mothers’ children, 201–202 adolescent mothers’ children’s developmental trajectories for, 204–206 attachment’s consequences on, 211 cognitive regulation influence on children’s, 216–217 K-ABC and, 10 prenatal cocaine exposure and verbal/ performance, 43–44 verbal encouragement/responsiveness effect on children’s, 207 Intervention A-B-C paradigm, 246 adolescent mothers’ programs of, 223–224 assessment as, 251 autism, 246 ecological model for challenging behavior, 245–252 ecology-centered, 251 efficacy of early, 252 etiology-related strategies of, 21–24 foster/adoptive care as maternal drug abuse, 49–52 implications for challenging behavior, 251–252 individualized, 252 S-O-R-K-C behavioral equation for, 247–251 IQ, 213

347

index K K-ABC. See Kaufman Assessment Battery for Children Kaufman Assessment Battery for Children (K-ABC), 10 Ketamine, 31

L Language ability/auditory reception and technology, 301–302 of adolescent mothers’ children, 201–202 contextual, 100 Down syndrome and deficits in, 12 SBM and, 68 Williams syndrome and abilities with, 11 Learning motor contingency, 98–99 multimedia approach to, 321 SBM and motor, 89–90 Learning disorders emergence in children with adolescent mothers, 202–206 SBM and, 64, 81–83 undiagnosed mild mental retardation and, 202–204 Lesch-Nyhan syndrome, 130 animal models of, 143 pemoline and, 136 Lipoprotein metabolism, ApoE genotype in, 164

M Mathematics cognitive sources of disability in, 103–104 SBM and skills in, 103–106 MDMA. See Methylenedioxymethamphetamine Memory Down syndrome and visual-over-auditory short-term, 14 SBM and deficits with, 107 technology and, 305

Menopause chronic condition risk increased after, 177 hormonal markers for, 177 in women with ID, 179 Mental retardation. See also Cerebral palsy; Down syndrome; Fragile X syndrome; Genetic mental retardation; Mild mental retardation; Technology AAC for people with, 312–313 behavioral research on, 5–6 CAI for people with, 318–321 caregiving environment for children with, 243 causes of, 3 child-environment transactions and, 17 cognitive speed impact on technology use by people with, 306–307 communication-related technology use by people with, 312–315 computer use of people with, 296–298 contextual nature of, 262 cultural-familial, 3 daily living activities supported by technology of people with, 317–318 defining, 81 differences between people with, 2–6 employment technology used by people with, 322–325 etiology-based approach to grouping people with, 2–6 familial vs. organic, 4 FAS as preventable form of, 31 future directions for applications of technology for people with, 329–330 history of etiology-based approaches to, 2–3 human cognitive abilities and people with, 300–308 intellectual impairment grouping of people with, 2 knowledge/achievement impact on technology use of people with, 307–308 language ability/auditory reception impact on technology use and, 301–302 literature review on technology use by people with, 312–329 memory/learning impact for people using technology with, 305

348 Mental retardation (cont. ) mobility technology for people with, 315–317 negative reaction to etiology-based classifications of, 5–6 organic vs. non-organic forms of, 2–3 prenatal drug exposure and etiology of, 52–53 prenatal exposure to cocaine as cause of, 35–36 quality of life improved by technology for people with, 299 SBM and, 81–82 SIB and, 140 social interaction of people with, 313–314 technology compensating for limitations in, 295 technology enabling environmental control for people with, 318 technology use and people with, 296–299, 311–330 technology use impacted by user characteristics associated with, 300–311 technology use importance to people with, 292–299 tolerance for error in technology and, 309–310 traditional etiological classification of, 54 two-group approach criticisms of, 4–5 two-group approach to, 3–5 universal design in technology and, 308–309 user characteristics limiting technology use for communication and, 313 visual perception impact for people using technology with, 305–306 World Wide Web and, 327 Methionine synthase reductase gene (MTRR), 185 Methylenedioxymethamphetamine (MDMA), 31 Methylenetetrahydrofolate reductase gene (MTHFR), 185 Mild mental retardation adolescent mothers as risk for, 197 adolescent mothers’ children’s emergence of, 202–206 developmental pathways leading to, 209–223

index disorganized attachment as risk factor for, 213–216 learning disabilities/undiagnosed, 202–204 Mothers. See Adolescent mothers Motor functions BG and, 120–121, 129 SBM and responses/skill of, 96–99, 106 SBM’s neural phenotype’s relationship with functions of, 86–95 MTHFR. See Methylenetetrahydrofolate reductase gene MTRR. See Methionine synthase reductase gene

N NEPSY. See Development Neuropsychological Assessment Nervous system. See also Central nervous system cocaine’s effect on, 35 Neural tube defects. See also Spina bifida meningomyelocele diet and, 73–74 folate metabolism and, 72, 77–78 genes causing, 78 genetic syndromes associated with, 72 heritability of, 71 types of, 66–67 Neurodegenerative disease, 129–130 Neurofibrillary tangles, 160 Neurotoxicity, as developmental disability cause, 123 Neurotoxicology. See Developmental neurotoxicology Neutritic plaques, 160 Notre Dame Adolescent Parenting Project, 197 achievement-related delays among children in, 202–204 developmental delays revealed by, 223 problematic parenting in, 206 sample/measurements scheme of, 198–199

O Obsessive-compulsive disorder, 136 Osteoarthritis, risk increased after menopause, 177

349

index Osteoporosis, 177 Oxygen free radicals, head injury increases formation of, 176

P Parenting. See also Adolescent mothers; Notre Dame Adolescent Parenting Project academic achievement predicted by, 220 factors and attachment variance of children, 215–216 importance of early, 206–209 later effects of early, 207 maternal mental health and, 48–49 maternal/child development link over time for, 208–209 self-regulation taught through, 218 verbal encouragement/responsiveness in, 207 by women with cocaine abuse history, 47–49 Parkinson’s disease (PD) action sequencing deficits in, 131–132 motor impairments of people with, 129 PD. See Parkinson’s disease Peabody Picture Vocabulary Test-Revised (PPVT-R), 11 Pediatric neuropsychology, 46 methodological advances in, 34–35 Pemoline infused into striatum, 136–137 model of self-biting behavior, 135–138 motoric hyperactivity associated with, 135 striatal DA depletion after administration of, 137 PET imaging. See Positron emission tomography imaging Positron emission tomography (PET) imaging, 130 Poverty caregiving environment correlated with, 237 challenging behavior impacted by, 236–237 disability relationship with, 266 PPVT-R. See Peabody Picture Vocabulary Test-Revised

Prader-Willi syndrome activities of people with, 16–17 diet for, 23 processing in children with, 9 UPD as form of, 12 visual-spatial skills in, 10, 20 Prenatal drug exposure. See also Behavioral teratology to alcohol, 35 current findings of, 41–52 current statistics on, 31 developmental influences relationship with, 39–41 direct/indirect pathways of effect on child development outcomes of, 37–41 etiology of mental retardation and, 52–53 examples of, 32–33 late evidence of effect of, 33 long-term consequences of, 43–47 Problem solving, rule-based, 97, 100 Profiles. See Cognitive-linguistic profiles; Etiology-related profiles Psychopathology, in drug-abusing mothers, 48

Q Quality of life of adults with SBM, 108–109 of people with disability and employment, 266 technology and, 291 technology improving people with mental retardation, 299 universal design and, 308

R Reading math difficulties related to difficulties in, 104–105 SBM and, 102–103 Recreation, 326–328 Rett syndrome, BG involvement in, 131 Rohyphol, 31 Rubella, as MR cause, 3

350

index S

SBM. See Spina bifida meningomyelocele Self-biting, 119 bilateral frontal cortical lesions decrease latency of, 139–140 caffeine/chronic amphetamine and, 137–138 DA depletion in BG system for expression of stereotyped, 133–134 fragmented grooming response/ pemoline-induced, 135–136 L-dopa-induced, 134 pemoline model of behavior of, 135–138 Self-injurious behavior (SIB), 119. See also Self-biting animal models of stereotyped, 132–141 BG in production of, 120 DBS and, 143 developmental disorders leading to, 141 dopaminergic models of, 132–135 early emergence of, 120 future directions in animal models of, 141–143 glutamatergic input from cortex to striatum in, 139–141 mental retardation and, 230 in pemoline model/DA alterations in BG system, 136 striatal manipulations for, 138–141 timing and, 132–133 Self-mutilation, 6, 8 Self-regulation academic success and, 211 of adolescent/low education mothers’ children, 218–219 insecure attachment delaying development of, 212 model of attachment and, 210–213 parents as fostering development of, 211–212 Sensory Integration and Praxis Test (SIPT), 45 SIB. See Self-injurious behavior Similar-sequence hypothesis, 4 Similar-structure hypothesis, 4 SIPT. See Sensory Integration and Praxis Test S-O-R-K-C behavioral equation, 247–248 ecology and, 249–251

Spina bifida meningomyelocele (SBM) academic functions in, 102–106 ADHD and, 82 attention regulation of children with, 99–100, 110 attention shifting of children with, 90–91 behavior regulation of children with, 97–98, 100 brain development affected by, 66 cognition/development/learning development disorders and, 81–83 cognition/motor functions of children with, 89 cognitive outcomes of adults with, 106–109 cognitive phenotype of, 64, 67–69 contextual language of children with, 97, 100–101 corpus callosum of children with, 92–95 delineation of modal profile, 68 development of children with, 95–109 domain-specific group studies on outcomes in children of, 68–69 early development of children with, 96–98 environmental factors and, 73 epidemiology/relation to other congenital disorders of, 66–67 family recurrence of, 72 genetic factors in, 71–72, 74–79, 111 HOX/PAX genes and, 79 interhemispheric transfer in brain of children with, 94–95 knowledge of, 63–64 lesion level in accounting for genetic hetergeneity of, 76–77, 80, 107–108 life span approach to, 65 literacy patterns of people with, 107 maternal illness/medication use associated with, 74 mathematical skills of children with, 103–106 memory deficits of people with, 107 midbrain/cerebellum of brain with, 86, 88–91 modal profile/variability around modal profile of, 67–68 motor functions of children with, 98–99, 106, 109–110 nature of, 65–69

351

index neural phenotype of, 64–65, 80, 86–95, 111 neurocognitive deficits of adults with, 106–107 outcomes in school-age children with, 80–86 perceptual skills of children with, 91 perceptual timing of people with, 89 physical phenotype of, 64 quality of life/neurocognitive function of adults with, 108–109 reading of children with, 102–103 reading/math difficulties’ relation for children with, 104–105 recruitment for research of, 70–71 research program of, 64, 69–80 rule-based problem solving of children with, 97 samples used in research of, 69–70 shunt treatment for, 66, 99, 108 statistical methods used for research on, 75 visual perception and, 101–102, 110 within-group variability in young adults with, 107–108 Sports, 326–328 Stress, 231 Success academic, 211 in employment outcomes of people with ID, 261, 269–282

T TDT. See Transmission Disequilibrium Test Tech Act. See Technology-Related Assistance for Individuals with Disabilities Act of 1988 Technology. See also Assistive technology; Information technology application in supported employment, 325 cognitive speed and, 306–307 communication related use of, 312–315 daily living activities of people with mental retardation supported by, 317–318 digital divide of, 292 education use of, 318–325 electronic/information, 293 functional use areas of, 295–296

future directions for applications for people with mental retardation of, 329–330 greater control/inclusion from, 292 impact of, 291 knowledge/achievement impact on, 307–308 language/communication ability impairments impact on use of, 301–302 limitations in mental retardation compensation in, 295 literature review on use by people with mental retardation of, 312–329 memory/learning impact for people with mental retardation using, 305 mobility, 315–317 numeracy area limitations in, 303 quality of life improved for people with mental retardation by, 299 reasoning/idea production impact on, 302–304 self-directed prompting facilitating task performance applications of, 325 sports/recreation application of, 326–328 as support under new definition, 294–295 tolerance for error in, 309–310 types of, 292–294 universally designed, 294, 308–311 use and people with mental retardation, 296–299, 311–330 use impacted by user characteristics associated with mental retardation, 300–311 use importance to people with mental retardation, 292–299 user characteristics addressed by features of, 308–311 visual perception impact for people with mental retardation using, 305–306 Technology-Related Assistance for Individuals with Disabilities Act of 1988 (Tech Act), 291–293 Temperament child-caregiver relationship and, 240 of developmentally disabled children, 233 Teratogenic agents prenatal effect of, 33 susceptibility to, 32 Tetrahydrofolate (THF), 184

352

index

THF. See Tetrahydrofolate Tourette syndrome, 136 Transmission Disequilibrium Test (TDT), 75 U Uniparental disomy (UPD), as form of Prader-Willi syndrome, 12 V Ventrolateral striatum (VLS), 138 DA/amphetamine infusion to, 139 neural pathways/amphetamine-induced stimulation of, 139

Vitamins. See B-group vitamins VLS. See Ventrolateral striatum Vocal output communication aids, 312

W Williams syndrome activities of people with, 17 verbal-over-visuospatial profile of children with, 14 visual-spatial skills in, 11, 20

Contents of Previous Volumes

Volume 1

Volume 2

A Functional Analysis of Retarded Development SIDNEY W. BIJOU

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

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

The Role of Input Organization in the Learning and Memory of Mental Retardates HERMAN H. SPITZ Autonomic Nervous System Functions and Behavior: A Review of Experimental Studies with Mental Defectives RATHE KARPER

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

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

Experience and the Development of Adaptive Behavior H. CARL HAYWOOD AND JACK T. TAPP

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

A Research Program on the Psychological Effects of Brain Lesions in Human Beings RALPH M. REITAN

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

Long-Term Memory in Mental Retardation JOHN M. BELMONT

Programming Instruction Techniques for the Mentally Retarded FRANCES M. GREENE

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

Some Aspects of the Research on Mental Retardation in Norway IVAR ARNIJOT BJORGEN

Author Index-Subject Index

353

354

contents of previous volumes

Research on Mental Deficiency During the Last Decade in France R. LAFON AND J. CHABANIER

A Theory of Primary and Secondary Familial Mental Retardation ARTHUR R. JENSEN

Psychotherapeutic Procedures with the Retarded MANNY STERNLIGHT

Inhibition Deficits in Retardate Learning and Attention LAIRD W. HEAL AND JOHN T. JOHNSON, JR.

Author Index-Subject Index

Volume 3 Incentive Motivation in the Mental Retardate PAUL S. SIEGEL Development of Lateral and Choice-Sequence Preferences 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

Growth and Decline of Retardate Intelligence MARY ANN FISHER AND DAVID ZEAMAN The Measurements of Intelligence A. B. SILVERSTEIN Social Psychology and Mental Retardation 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

Reaction Time and Mental Retardation ALFRED A. BAUMEISTER AND GEORGE KELLAS

Operant Procedures with the Retardate: An Overview of Laboratory Research PAUL WEISBERG

Mental Retardation in India: A Review of Care, Training, Research, and Rehabilitation Programs J. P. DAS

Methodology of Psychopharmacological Studies with the Retarded ROBERT L. SPRAGUE AND JOHN S. WERRY

Educational Research in Mental Retardation SAMUEL L. GUSKIN AND HOWARD H. SPICKER

Process Variables in the Paired-Associate Learning of Retardates ALFRED A. BAUMEISTER AND GEORGE KELLAS

Author Index-Subject Index

Volume 4

Sequential Dot Presentation Measures of Stimulus Trace in Retardates and Normals EDWARD A. HOLDEN, JR.

Memory Processes in Retardates and Normals NORMAN R. ELLIS

Cultural-Familial Retardation FREDERIC L. GIRARDEAU

355

contents of previous volumes German Theory and Research on Mental Retardation: Emphasis on Structure LOTHAR R. SCHMIDT AND PAUL B. BALTES

Placement of the Retarded in the Community: Prognosis and Outcome RONALD B. MCCARVER AND ELLIS M. CRAIG

Author Index-Subject Index

Physical and Motor Development of Retarded Persons ROBERT H. BRUININKS

Volume 6 Cultural Deprivation and Cognitive Competence J. P. DAS Stereotyped Acts 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

Subject Index

Volume 8 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

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

contents of previous volumes 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 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

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

Public Residential Services for the Mentally Retarded R. C. SCHEERENBERGER

Inhibition and Individual Differences in Inhibitory Processes in Retarded Children PETER L. C. EVANS

Research on Community Residential Alternatives for the Mentally Retarded LAIRD W. HEAL, CAROL K. SIGELMAN, AND HARVEY N. SWITZKY

Stereotyped Mannerisms in Mentally Retarded Persons: Animal Models and Theoretical Analyses MARK H. LEWIS AND ALFRED A. BAUMEISTER

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

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

357

contents of previous volumes Volume 12

Volume 13

An Overview of the Social Policy of Deinstitutionalization BARRY WILLER AND JAMES INTAGLIATA

Sustained Attention in the Mentally Retarded: The Vigilance Paradigm JOEL B. WARM AND DANIEL B. BERCH

Community Attitudes toward Community Placement of Mentally Retarded Persons CYNTHIA OKOLO AND SAMUEL GUSKIN

Communication and Cues in the Functional Cognition of the Mentally Retarded JAMES E. TURNURE

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. FUJIURRA 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

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

358 Molar Variability and the Mentally Retarded 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 ERNESTO POLLITT

contents of previous volumes 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 JANE L. MATHIAS

359

contents of previous volumes 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 OROSSIII Stimulus Organization and Relational Learning SAL A. SORACI, JR. AND MICHAEL T. CARLIN

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 TREAVOR 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 SILERMAN Characteristics of Older People with Intellectual Disabilities in England JAMES HOGG AND STEVE MOSS

360 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

contents of previous volumes 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

Index

A Review of Self-Injurious Behavior and Pain in Persons with Developmental Disabilities FRANK J. SYMONS AND TRAVIS THOMPSON

Volume 20

Recent Studies in Psychopharmacology in Mental Retardation MICHAEL G. AMAN

Parenting Children with Mental Retardation BRUCE L. BAKER, JAN BLACHER, CLAIRE B. KOPP, AND BONNIE KRAEMER Family Interactions and Family Adaptation FRANK J. FLOYD AND CATHERINE L. COSTIGAN 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 CLAUSSEN, AND LOIS-LYNN STOYKO DEUEL

Methodological Issues in the Study of Drug Effects on Cognitive Skills in Mental Retardation DEAN C. WILLIAMS AND KATHRYN J. SAUNDERS 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 Direct Effects of Genetic Mental Retardation Syndromes: Maladaptive Behavior and Psychopathology ELISABETH M. DYKENS

361

contents of previous volumes 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 KAROLY HORVATH AND J. TYSON TILDON 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 International Quality of Life: Current Conceptual, Measurement, and Implementation Issues KENNETH D. KEITH

362 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

contents of previous volumes 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

The Parent with Mental Retardation STEVE HOLBURN, TIFFANY PERKINS, AND PETER VIETZE

Social Cognition: A Key to Understanding Adaptive Behavior in Individuals with Mild Mental Retardation JAMES S. LEFFERT AND GARY N. SIPERSTEIN

Psychiatric Disorders in Adults with Mental Retardation STEVE MOSS

Proxy Responding for Subjective Well-Being: A Review ROBERT A. CUMMINS

Development and Evaluation of Innovative Residential Services for People with Severe Intellectual Disability and Serious Challenging Behavior JIM MANSELL, PETER MCGILL, AND ERIC EMERSON

People with Intellectual Disabilities from Ethnic Minority Communities in the United States and the United Kingdom CHRIS HATTON

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 Volume 25 Characterizations of the Competence of Parents of Young Children with Disabilities CARL J. DUNST, TRACY HUMPHRIES, AND CAROL M. TRIVETTE

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 Psychopathology in Children and Adolescents with Intellectual Disability: Measurement, Prevalence, Course, and Risk JAN L. WALLANDER, MARIELLE C. DEKKER, AND HANS KOOT

363

contents of previous volumes Resilience, Family Care, and People with Intellectual Disabilities GORDONGRANT, PAULRAMCHARAN, AND PETER GOWARD

Reading Skills and Cognitive Abilities of Individuals with Mental Retardation FRANCES A. CONNERS

Prevalence and Correlates of Psychotropic Medication Use among Adults with Developmental Disabilities: 1970–2000 MARIA G. VALDOVINOS, STEPHEN R. SCHROEDER, AND GEUNYOUNG KIM

Language Interventions for Children with Mental Retardation NANCY C. BRADY AND STEVEN F. WARREN

Integration as Acculturation: Developmental Disability, Deinstitutionalization, and Service Delivery Implications M. KATHERINE BUELL

Augmentative and Alternative Communication for Persons with Mental Retardation MARYANN ROMSKI, ROSE A. SEVCIK, AND AMY HYATT FONSECA

Cognitive Aging and Down Syndrome: An Interpretation J. P. DAS

Atypical Language Development in Individuals with Mental Retardation: Theoretical Implications JEAN A. RONDAL

Index

Index

Volume 27 Language and Communication in Individuals with Down Syndrome ROBIN S. CHAPMAN 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 CARMICHAEL OLSON, AND GERALYN R. TIMLER Memory, Language Comprehension, and Mental Retardation EDWARD C. MERRILL, REGAN LOOKADOO, AND STACY RILEA

Volume 28 Promoting Intrinsic Motivation and Self-Determination in People with Mental Retardation EDWARD L. DECI 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 Understanding the Development of Subnormal Performance in Children from a Motivational-Interactionist Perspective JANNE LEPOLA, PEKKA SALONEN, MARJA VAURAS, AND ELISA POSKIPARTA

364 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

contents of previous volumes 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