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Social Networks and Participation of Youth with Learning Disability, Attention Deficit Disorder or Autism Spectrum Disorder

Permanent Link: http://ufdc.ufl.edu/UFE0045245/00001

Material Information

Title: Social Networks and Participation of Youth with Learning Disability, Attention Deficit Disorder or Autism Spectrum Disorder a Mixed-Method Study Using Personal Network Analysis and Qualitative Interview
Physical Description: 1 online resource (147 p.)
Language: english
Creator: Kreider, Consuelo Maun
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2013

Subjects

Subjects / Keywords: disability -- social-networks -- youth
Rehabilitation Science -- Dissertations, Academic -- UF
Genre: Rehabilitation Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Youth growing up with cognitive disabilities face barriers tothe development and maintenance of optimal social networks. Social networksserve as arenas for participation, a developmentally critical concept inrehabilitation. The purpose of this study was to explore social network linksto participation and experiences for 19 youth with diagnoses of learningdisability, attention deficit disorder or autism spectrum disorder. Socialnetworks and participation were compared to those of 17 typically developingyouth. Methods of personal network analysis were used to ascertain thestructure of the youth’s social network. The Children’s Assessment ofParticipation and Enjoyment (CAPE) was used to assess participation. Socialnetwork links to participation were analyzed using correlation and linearregression statistics. Cognitive interview was used to gain understanding ofsocial network perceptions and experiences for the youth with disabilities. Differences were found in the composition of networkmembers. The youth with disabilities had more adults and fewer peers in theirnetwork. Differences were also found in participation of physical activities,as well as differences in where and with whom activities occur. Multiple socialnetwork variables had significant correlations to participation. Networkcomposition and structure predicted where and with whom participation occurred.Qualitative interviews provided insight into how the youth with disabilitiesbuilt and experienced their social networks. Youth with disabilities describedexplicit, and at times scripted, strategies for participating in the socialgoings-on within their social network. Visually explicit understanding of theyouth’s social network, as gained through use of personal network analysis, wasuseful to parents and youth with disabilities in shaping plans and socialstrategies. The personal network analysis and resulting network map has thepotential to serve as a therapeutic framework for context-specific detaileddiscussion regarding social situations. Greater understanding of socialnetwork’s links to participation has the potential to inform strategies used tofacilitate social participation for youth growing up with impairments ininformation processing inherent to cognitive disabilities related todevelopment.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Consuelo Maun Kreider.
Thesis: Thesis (Ph.D.)--University of Florida, 2013.
Local: Adviser: Mann, William C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2013
System ID: UFE0045245:00001

Permanent Link: http://ufdc.ufl.edu/UFE0045245/00001

Material Information

Title: Social Networks and Participation of Youth with Learning Disability, Attention Deficit Disorder or Autism Spectrum Disorder a Mixed-Method Study Using Personal Network Analysis and Qualitative Interview
Physical Description: 1 online resource (147 p.)
Language: english
Creator: Kreider, Consuelo Maun
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2013

Subjects

Subjects / Keywords: disability -- social-networks -- youth
Rehabilitation Science -- Dissertations, Academic -- UF
Genre: Rehabilitation Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Youth growing up with cognitive disabilities face barriers tothe development and maintenance of optimal social networks. Social networksserve as arenas for participation, a developmentally critical concept inrehabilitation. The purpose of this study was to explore social network linksto participation and experiences for 19 youth with diagnoses of learningdisability, attention deficit disorder or autism spectrum disorder. Socialnetworks and participation were compared to those of 17 typically developingyouth. Methods of personal network analysis were used to ascertain thestructure of the youth’s social network. The Children’s Assessment ofParticipation and Enjoyment (CAPE) was used to assess participation. Socialnetwork links to participation were analyzed using correlation and linearregression statistics. Cognitive interview was used to gain understanding ofsocial network perceptions and experiences for the youth with disabilities. Differences were found in the composition of networkmembers. The youth with disabilities had more adults and fewer peers in theirnetwork. Differences were also found in participation of physical activities,as well as differences in where and with whom activities occur. Multiple socialnetwork variables had significant correlations to participation. Networkcomposition and structure predicted where and with whom participation occurred.Qualitative interviews provided insight into how the youth with disabilitiesbuilt and experienced their social networks. Youth with disabilities describedexplicit, and at times scripted, strategies for participating in the socialgoings-on within their social network. Visually explicit understanding of theyouth’s social network, as gained through use of personal network analysis, wasuseful to parents and youth with disabilities in shaping plans and socialstrategies. The personal network analysis and resulting network map has thepotential to serve as a therapeutic framework for context-specific detaileddiscussion regarding social situations. Greater understanding of socialnetwork’s links to participation has the potential to inform strategies used tofacilitate social participation for youth growing up with impairments ininformation processing inherent to cognitive disabilities related todevelopment.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Consuelo Maun Kreider.
Thesis: Thesis (Ph.D.)--University of Florida, 2013.
Local: Adviser: Mann, William C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2013
System ID: UFE0045245:00001


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1 SOCIAL NETWORKS AND PARTICIPATION OF YOUTH WITH LEARNING DISABILITY, ATTENTION DEFICIT DISORDER OR AUTISM SPECTRUM DISORDER: A MIXED METHOD STUDY USING PERSONAL NETWORK ANALYSIS AND QUALITATIVE INTERVIEW By CONSUELO M. KREIDER A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2013

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2 2013 Consuelo M. Kreider

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3 To my amazing husband and beautiful children

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4 ACKNOWLEDGMENTS It is with deepest gratitude and admiration that I thank my husband, David Kreider, for his unwavering support and devotion. He makes me believe I can accomplish it all; and the n he makes so. I also thank my children, Dominick, Jocelyn and Natalie, for the years of encouragement, prayers, and understanding sacrifices they and their father have made so that I could accomplish this milestone. I thank my mother, Alicia Maun, and my mother in law, Emily Pugh, for their steadfast support. Their belief in this endeavor and continuous assistance with all things mother and grandmother has been instrumental to my success. I extend my sincere appreciation to my doctoral committee, Dr. Will iam Mann, Dr. Roxanna Bendixen, Dr. Mary Ellen Young, and Dr. Christopher McCarty. Their encouragement, guidance and wise counsel kept me focused, engaged, and enthusiastic. I especially thank, Dr. Bendixen for her friendship and generous mentorship. I rem ain grateful for her guidance throughout every step of this professional journey. I am indebted to Ms. Renee Hobbs, Ms. Margaret Odom and all of my colleagues at the University of Florida Department of Occupational Therapy. Each member of the faculty and s taff has been an invaluable source of camaraderie and encouragement. In particular, I thank Dr. Joanne Foss for her guidance and support in helping me manage my many competing demands, and for her unrelenting expectation that I would finish. I also thank m y Sensei, Dr. Sherrilene Cl assen, who was instrumental in my development of the mental and physical strength needed to sustain in this endeavor with a semblance of balance.

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5 I would also like to acknowledge Ms. Christen Fechtel, who assisted in this researc h study as part of her undergraduate honors research. Her keen intellect and innate curiosity was invaluable in the development of conceptual understanding of the qualitative data. My gratitude is also extended to Dr. Jose Silva Lugo for his patient statis tical guidance. And lastly, I thank all the families who have shared their journeys with me. Their stories continue to inspire.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 LIST OF FIGURES ................................ ................................ ................................ ........ 11 LIST OF ABBREVIATIONS ................................ ................................ ........................... 12 ABSTRACT ................................ ................................ ................................ ................... 14 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 16 Background and Significance ................................ ................................ ................. 16 Conceptual Framework for Investigating Social Networks and Participation .......... 16 Introduction to Participation ................................ ................................ .................... 19 Introduction to the Social Network Perspective ................................ ....................... 23 Introduction to Social Network Analysis ................................ ................................ .. 25 Social Networks of Youth Growing Up with Disabilities ................................ .......... 27 Summary ................................ ................................ ................................ ................ 30 Specific Aims, Hypotheses and Research Questions ................................ ............. 31 2 STUDY DESIGN AND DESCRIPTION OF STUDY SAMPLE ................................ 32 Study Design ................................ ................................ ................................ .......... 32 Two Group, Cross Sectional, Mixed Method Study ................................ ......... 32 Overview of Study Protocol ................................ ................................ .............. 33 General Analytic Approach ................................ ................................ ............... 33 Participants ................................ ................................ ................................ ............. 34 Inclusion and Exclusion Criteria ................................ ................................ ....... 34 Secondary Participants ................................ ................................ ..................... 35 Recruitment ................................ ................................ ................................ ............ 35 Setting ................................ ................................ ................................ ..................... 36 Overview of Data Collection Used to Quantifiably Describe Study Participants ...... 37 Study Procedures for All Study Participants ................................ ..................... 37 Additional Data Collection for Youth in the Clinical Group ................................ 37 Demographic Description of the Study Sample ................................ ...................... 38 Demographic Variables ................................ ................................ .................... 38 Analysis of Demographic Variables ................................ ................................ .. 39

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7 Clinical Descriptions of Stu dy Sample ................................ ................................ .... 42 Instruments Used to Clinically Describe the Study Sample .............................. 42 Analysis of Clinical Variables ................................ ................................ ............ 44 Motor characteristics ................................ ................................ .................. 45 Functional characteristics ................................ ................................ ........... 45 Additional Clinical Description of the Youth in the Clinical Group ..................... 48 Description of additional clinical assessments ................................ ........... 49 Results of additional clinical assessment ................................ ................... 50 Description of Participation for the Study Sample ................................ ................... 51 Instrument Used to Measure Participation ................................ ........................ 51 Analysis of Participation ................................ ................................ ................... 53 Results ................................ ................................ ................................ ............. 54 Summary ................................ ................................ ................................ ................ 55 3 SOCIAL NETWORK ANALYSIS AND LINKS TO PARTICIPATION ....................... 57 Introduction to Methods of Personal Network Analysis ................................ ........... 57 Coll ection of Social Network Data ................................ ................................ ........... 60 Social Network Visualizations ................................ ................................ ................. 63 Social Network Variables ................................ ................................ ........................ 64 Network Variables Related to Composition ................................ ...................... 65 Network Variables Related to Structure ................................ ............................ 65 Density ................................ ................................ ................................ ....... 66 Centrality ................................ ................................ ................................ .... 66 Operating definitions of structural variables ................................ ............... 66 Network Va riables Related to Support ................................ ............................. 67 Developmental support ................................ ................................ .............. 67 Social support ................................ ................................ ............................ 68 Multiplexity ................................ ................................ ................................ 68 Operating definitions of network variables related to support .................... 69 Experiment 1: Describing Networks and Testi ng Compositional and Structural Differences ................................ ................................ ................................ .......... 70 Analysis of Compositional Network Variables ................................ .................. 70 Analysis of Structural Network Varia bles ................................ .......................... 72 Analysis of Network Support Variables ................................ ............................ 73 Summary of Experiment 1: Differences in Network Composition, Structure and Suppor t ................................ ................................ ................................ ... 74 Experiment 2: Relationship of Social Network to Participation ................................ 74 Statistical Procedures Used for Testing Correlations ................................ ....... 74 Results of Correlation Analyses of Network Variables and Participation Dimensions ................................ ................................ ................................ ... 75 Correlation and Regression Analyses of Network Va riables and Participation Dimensions by Activity Type ................................ ................................ ................ 77 Network Composition and Participation ................................ ................................ .. 78 Correlations for Compositional N etwork Variables and Participation ................ 78 Linear Regressions for Compositional Network Variables ................................ 79 Network Structure and Participatio n: Correlations and Linear Regression ............. 82

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8 Network Support and Participation: Correlations and Linear Regressions .............. 83 Summary of Expe riment 2: Relationship of Social Network to Participation ........... 84 4 EXPERIENCES AND PERCEPTIONS OF SOCIAL NETWORKS ......................... 86 Introduction to Q ualitative Inquiry ................................ ................................ ........... 86 Qualitative Methods ................................ ................................ ................................ 88 ................................ ................................ ........................ 88 Qualitative Data Collection ................................ ................................ ............... 88 Analysis of Qualitative Interview Data ................................ .............................. 90 Strategies for Enhancing Trustworthiness of Findings ................................ ..... 91 Overview of Qualitative Findings ................................ ................................ ............ 92 Forming Networks Theme ................................ ................................ ....................... 92 Strat egies for Increasing Social Connections ................................ ................... 92 Social Dismissal ................................ ................................ ............................... 93 Others Reaching Out ................................ ................................ ........................ 94 Finding Similarities ................................ ................................ ........................... 94 Understanding Social Self ................................ ................................ ................ 95 Applying Social Rules ................................ ................................ ....................... 97 Weighing Social Rules ................................ ................................ ..................... 98 Parental Building of the Social Network ................................ ............................ 99 Group Engagement Theme ................................ ................................ .................. 100 Egalitarian Peer Groups ................................ ................................ ................. 100 Avoiding Social Negotiations ................................ ................................ .......... 101 Verbal Stra tegies ................................ ................................ ............................ 102 Language Communication Issues ................................ ................................ .. 104 Summary ................................ ................................ ................................ .............. 105 Limitation s in Qualitative Inquiry ................................ ................................ ........... 106 5 DISCUSSION ................................ ................................ ................................ ....... 108 Differences in Participation ................................ ................................ ................... 109 Differences in Social Networks ................................ ................................ ............. 111 Discussion of Social Network Links to Participation ................................ .............. 113 Compositional Network Links to Participation ................................ ................. 114 Structural Network Links to Participation ................................ ........................ 115 Network Support Links to Participation ................................ ........................... 115 Discussion of Qualitative Findings ................................ ................................ ........ 117 Expanded Understanding of Quantitative Data From Qualitative Data ................. 1 19 Potential Clinical Utility of Methods of Social Network Analysis ............................ 122 ................................ ................................ ............. 122 Youth Re sponses to SNA ................................ ................................ ............... 123 Conclusions Regarding Clinical Use of Methods of Social Network Analysis 124 Limitations ................................ ................................ ................................ ............. 126 Conclusion ................................ ................................ ................................ ............ 127

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9 APPENDIX: NETWORK VISUALIZATIONS ................................ ............................... 129 LIST OF REFERENCES ................................ ................................ ............................. 138 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 147

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10 LIST OF TABLES Table page 2 1 Demographic characteristics of clinical and comparison groups ........................ 40 2 2 Diagnostic and clinical history of clinical and comparison groups ....................... 42 2 3 Motor characteristics of cli nical and comparison groups ................................ .... 46 2 4 Functional characteristics of clinical and comparison groups ............................. 47 2 5 Performance of clinical g roup on occupational therapy clinical assessments ..... 51 2 6 CAPE scores and comparisons between clinical and comparison groups ......... 54 3 1 Social network questions ................................ ................................ .................... 62 3 2 Compositional network variables for youth in clinical and comparison groups ... 71 3 3 Structural network variables for youth in clinical and comparison groups ........... 72 3 4 Network support variables for youth in clinical and comparison groups ............. 73 3 5 Overview of group differences for network variables ................................ .......... 74 3 6 Overview of relationships of social network variables to participation dimensions of Diversity, Intensity, With Wh om and Where ................................ 76 3 7 Regression calculations based on network composition variables ..................... 80 3 8 Correlations for compositional network variables and participation ( p < 01) ....... 81 3 9 Correlations for structural network variables and participation ( p < .01) ............. 82 3 10 C orrelations for network support variables and participation ( p < .01) ................ 85 4 1 Guiding questions and probes for cognitive interview ................................ ......... 89

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11 LIST OF FIGURES Figure page 1 1 Research as situated within the International Classification of Functioning, Disability and Health ................................ ................................ ........................... 19 2 1 Visua l diagram of study design ................................ ................................ ........... 32 2 2 Visual diagram of general analytic approach ................................ ...................... 33 4 1 qualitative analysis ................. 87

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12 LIST OF ABBREVIATIONS AASP Adolescent/Adult Sensory Profile ADD Attention deficit disorder AS Asperger syndrome ASD Autism spectrum disorder ATNR Asymmetric tonic neck reflex B EERY VMI Beery Bukteni ca Developmental Test of Visual Motor Integration, Sixth Edition BOT 2 Brunicks Oseretsky Test of Motor Proficiency, Second Edition CAPE CDC Centers for Disease Control and Prevention DCD Developmental coordination disorder Developmental Coordination Disorder Questionnaire 2007 ICF International Classification of Functioning, Disability and Health ICF CY International Classification of Functioning, Disability and Health for Children and Youth LD Learning disability OT Occupational therapy PDD NOS Pervasive developmental disorder, not otherwise specified P EDS QL TM Pediatric Quality of Life Inventory TM PI Principal investigator PNA Personal network analysis PT Physical therapy QNST 3 Quick Neurologi cal Screening Test 3 rd Edition SDQ Strengths and Difficulties Questionnaire SNA Social network analysis

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13 SRS Social Responsiveness Scale ST Speech therapy STNR Symmetric tonic neck reflex WHO World Health Organization

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14 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy SOCIAL NETWORKS AND PARTICIPATION OF YOUTH WITH LEARNING DISABILITY, ATTENTION DEFICIT DISORDER OR AUTISM SPECTRUM DISORDER: A MIXED METHOD STUDY USING PERSONAL NETWORK ANALYSIS AND QUALITATIVE INTERVIEW By Consuelo M. Kreider May 2013 Chair: William C. Mann Major: Rehabilitation Science Youth growing up with cognitive disabilities face barriers to the de velopment and maintenance of optimal social networks. Social networks serve as arenas for participation, a developmentally critical concept in rehabilitation. The purpose of this study was to explore social network links to participation and experiences fo r 19 youth with diagnoses of learning disability, attention deficit disorder or autism spectrum disorder. Social networks and participation were compared to those of 17 typically developing youth. Methods of personal network analysis were used to ascertain the Enjoyment (CAPE) was used to assess participation. Social network links to participation were analyzed using correlation and linear regression statistics. Cognitiv e interview was used to gain understanding of social network perceptions and experiences for the youth with disabilities. Differences were found in the composition of network members. The youth with disabilit ies had more adults and fewer peers in their ne twork. Differences were also found in participation of physical activities, as well as differences in where and with

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15 whom activities occur. Multiple social network variables had significant correlations to participation. Ne twork composition and structure p redicted where and with who m participation occurred Qualitative i nterviews provided insight into how the youth with disabilities built and experienced their social networks. Youth with disabilities described explicit, and at times scripted, strategies for participating in the social goings on within their social network. Visually explicit understanding of the yout as gained through use of personal network analysis, was useful to parents and youth with disabilities in shaping plans and so cial strategies. The personal network analysis and resulting network map has the potential to serve as a therapeutic framework for context specific detailed discussion regarding social situations. Greater understanding of social network s links to particip ation has the potential to inform strategies used to facilitate social participation for youth growing up with impairments in information processing inherent to cognitive disabilities related to development.

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16 CHAPTER 1 INTRODUCTION Background and Signific ance Yo uth growing up with disabilities face challenges to the creation of social networks that facilitate developmentally important social ly based participation in everyday activities. This study was designed to provide greater understanding of social env ironmental factors believed to influence participation, and thus health, for you th growing up with impairments in information processing inherent to cognitive disabilities related to development. This study explore s social networks and participation utiliz ing methodology from the social sciences, with the ultimate goal of application to rehabilitation practice. Social networks refer to the people within the social structures surrounding an individual, such as a family or a classroom. Participation, as defin ed by social involvement in e veryday activities such as eating, playing or engaging in classroom activities (Cole & Donohue, 2011). For children and youth, participation is a heath related construct whereby social involvement ( i.e. participation) in the outside world is needed for healthy development (Forsyth & Jarvis, 2002) Conceptual Fra mework for Investigating Social Networks and Participation; Introduction to the International Classification of Functioning, Disability and Health may therefore be called th e enabling process (p 3; Institute of Medicine For youth growing up with disabilities, rehabilitation entails the science and process whereby individual capacities are enabled th rough development, support, and or

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17 restoration For children and you th, rehabilitation works to facil itate performance and maximum participation within the current and future roles. The development or restoration s of individual capacities are achievable through rehabilitation efforts aimed at functional change to b oth the person and the surrounding environment (I nstitute of Medicine 1997 ). of health, disability functioning and participation. Ecological paradigms of health and disability provide structure for viewing behaviors that impact health and function Within these ecological models of health, disability is understood to be a function of the e.g. psychologi cal, social and built environments). Contemporary functional models of disability reflect this biopsychosocial paradigm and recognize disability to be the result of a lack of fit between the person who is experiencing a biopathology and the environment in which the individual is functioning (Smart, 2009: WHO, 2002). In the case of youth growing up with cognitive impairments functional effects of the deficiencies can be curtailed by the provision of appropriate academic accommodations, acce ss to appropriate supports, and or the presence of supportive and inc lusive attitudes and policies (Orr & Hamming, 2009; Garrison Wade & Lehmann 2010). The International Classification of Functioning, Disability and Health for Children and Youth (ICF CY) is a biopsychosoc ial framework of health and disability adopted by the WHO in 2007. It was derived from, and parallels, the International Classification of Functioning, Disability and Health (ICF), which was adopted by the WHO in 2001. Both the ICF and the ICF CY provide a framework and standard language for describing

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18 health and associated health related states. The Children and Youth version of the ICF provides additional language and details allowing for characterization of health and functioning while remaining sensitiv e to changes associated with growth and development (WHO, 2007). Like the ICF, the ICF CY models disability, and thus health and functioning, as a complex process that is both interactive and evolutionary. In the ICF frameworks, individuals function withi n the domains of (a) Body Functions and Structures, (b) Activities, and (c) Participation. Furthermore, an often ealth condition and his or her unique contextual factors. Environmental Factors and Personal Factors comprise these contextual factors (WHO, 2007). Within the ICF Environmental Factors include the domains of (a) Support and Relationships and (b) Attitude s B oth domains are function s of the social network. The Support and Relationships domain encompasses individuals surrounding the youth who serve as sources for relationships and who can provide practical support, nurturing, protection, and assistance ( WH O, 2007) The ICF domain of Attitudes encompasses attitudes that are the observable consequences of customs, practices, ideologies, values, norms, factual beliefs and religious beliefs. These attitudes influence individual behavior and social life at all levels 207; WHO, 2007). This research was conceptually guided by the ICF CY (Figure 1 1) It investigates social networks and potential links to participation for youth with cognitive disabilities related to development Social networks serve as the settings in which actions and attitudes of inclusion are created, disseminated, and nurtured into culture.

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19 For youth with disabilities, social supports are functions of the social net work that can interact with participation to influence funct ioning, healt h and development. Figure 1 1. Research as situated within the International Classification of Functioning, Disability and Health (adapted from World Health Organization. 2007 International classification of functioning, disability and health: Child ren & youth version Geneva, Switzerland: WHO Press. Page 17, Figure 1 .) Introduction to Participation Children and youth with disabilities encounter social and physical challenges to participation. For youth with disabilities, participation is shaped by the interplay of needed and available, and personal and familial choi ces and values (Forsyth et al. 2002). For youth with disab ilities, participation is not as simple as an autonomous

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20 individual making choices to engage in activities because the activities matter. The reality remains that many youth with disabilities engage in participatory choices made in consideration of disabil ity related constraints and are influenced by those around them The concept of participation is often an integral part of societal discourse, yet it remains a newly centralized co nstruct in rehabilitation and disability science (Whiteneck & Dijkers, 2009). With the 2001 adoption of the ICF, the WHO contributed to the multifaceted construct of participation Within the ICF, participation is defined as an life situations and everyday activities (WHO, 2001). Wh iteneck and Dijkers (2009) add to understanding of participation by differentiating it from activity. They conceptualize activities to occur at the individual level, while participation occurs at a soc ietal level. In explicating they adv ise, Activities are characteristics of people, and they can be assessed by examining the functional performance of an individual in isolation. In contrast, participation is a relational concept that can be assessed only by taking into consideration other factors beyond simply the capabilities and limitations of the individual. Role expectations held by subgroups or the overall society must be considered along with the social setting and environment in which the roles are to be performed (p S24 Whiteneck et al., 2009 ) The ICF CY further informs specific to childhood participation. In the Children and Youth derivative of the original ICF the WHO paralleled the processe s of development and enablement/ disablement. As with all children, including those growing up with disabilities, activity engagement and participation in everyday life situations provides a universal framework where youth can express themselves, develop skills, competencies, affiliations and friendships, an d establish a sense of belonging and life meaning (Tinsley & Eldredge 1995; WHO, 2007).

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21 In development, as children progress from early childhood through adolescence, participation moves along a continuum toward more socially based activities and behavio r (Parten, 1932). Within this continuum, children move from (a) unoccupied and onlooker behaviors, to (b) solitary play, then (c) parallel play where children play beside, but not with, each other. This is followed by engagement in associative activities w here Finally, children move into mature cooperative organized social activities where there is orms of behavior (Parten, 1932). However, for many youth with dis abilities, participation does not always move toward more advancing social activities. Rather, participation moves toward engagement in a narrower range of activities that are generally quie ter and less social. This occurs as the number of social engagements declines through adolescence (Blum, Resnick, Nelson, & St. Germaine, 1991; McAndrew, 1979; Skar, 2003; Stevenson, Pharoah, & Stevenson, 1997). As a result, children growing up with disabi lities are at risk of lower participation in everyday life activities (King et al 2004) putting them at greater risk of isolation and reduction of desirable health and developmental outcomes. Social participation in childhood requires not only physical proficiency in the activities, but navigation of the social demands encompassing developmental activities. Cognitive and regulatory processes are inherent to socially based participation. Such cognitive and regulatory processes allow humans to correctly in terpret the goings on around them form and execute an action plan, and simultaneously maintain appropriate levels of attention, vigilance, and emotionality to match both the task and social

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22 demands. Children with cognitive disabilities related to developm ent have difficulties with one or more of these processes required for childhood participation. Cognitive disabilities related to development are often characterized by difficulty or dysregulation in controlling attention, emoti on, sensorimotor responses, and or physiological states. The se difficulties can make it tricky for those with impairments to interpret and use environmental information necessary for generating responses tha t are functional or appropriate ( Zero to Three, 2005 ). Children with these t ypes of impairments often have difficulty attending in the classroom, managing playground equipment, and negotiating busy, unstructured social environments such as the lunchroom and recess. More specifically, dysfunctions can manifest as obsessiveness and rigidity, perseveration (difficulty making transitions), resistance to novel situations and changes in routine, passi ve aggression, self injury, and or inadequacy of social skills (Gu tman, McCreedy & Heisler, 2004); a ny of which can hinder social functioni ng and participation S ocially based participation is inextricably linked to cognitive functioning within the social environment. As a result, youth with cognitive disabilities can face social challenges. Their cognitive impairments can result in challeng es to appraising and traversing the social landscape. This is especially true in adolescence when the youth with cognitive disabilities must contend with already difficult social hierarchy and nuanced peer interactions. For these youth, social difficulties can serve as impediments to the formation of diverse social networks essential to developmentally necessary participation.

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23 Introduction to the Social Network Perspective This research applied social network models to investigation of the social environmen t. Social network theories posit the existence of patterns of dynamic reciprocal relationships between the individual and the social environment. The actions, attitudes, health, and developmental trajectories (Pescosolido & Levy, 2002). In turn, surrounding social relationships (also referred to as ties perspective, individua ls are viewed as existing within unique envelopes of social relationships nested within larger networks of relationships. The attitudes and values shared amongst network members serve as cultural norms influencing those within the network (Pescosolido et a l., 2002; Knoke & Yang 2008). Networks can have an effect on protective attitudes and behaviors that can work to optimize health, development, educational and youth trajectories ( Cohen & Lemay, 2007; Dumont & Provost, 1999). They can also serve to derail these trajectories, such as when a youth becomes involved with gangs or peers who engage in high risk behaviors. Social networks serve as both the context and vehicle for youth participation. Youth participation includes social behaviors, which have been inextricably linked to the development of social competence (Godde & Engfer, 1994). For youth with disabilities, simultaneously facilitating social development. The soci al network perspective incorporates explicit understanding of relationships between people (or entities) in the explanation of processes or phenomena. Theoretical and explanatory models utilizing social network perspectives

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24 incorporate into their framework s aspects of network structure (e.g. sub groups, weak ties) and composition (e.g. age, gender, role) of network members. Within the literature regarding analysis of social networks, common network level characteristics measured and found in health literatu re include: (1) r ange or size : refers to the number of network members; (2) h omogeneity : refers to the extent to which network members share similar characteristics; (3) m ultiplexity : refers to the number of types of transactions (e.g. supports) flowing th rough a network or set of ties; and (4) r eciprocity : refers to the extent to which exchanges between ties are reciprocal (Berkman, Glass, Brissette & Seeman, 2000). Within health literature, these network characteristics are referred to as structural chara composition al aspects of the network such as percentage kin (or other relationship), numbers of close ties, frequency of contact, and duration (referring to how long network members have known each other) are also commonly used in health research. Central to social network research is the assertion that greater understanding of the relationships between the parts of the system (i.e. network) enables richer comprehension of the individual parts of the network, as well as greater appreciation of the system as a whole. Social network researchers view social relationships in terms of the graphical representations of ties between individuals in the network that can impact the spread of informat ion, ideas, or attitudes across the network. Social networks are conceived of as whole networks and as personal networks Whole networks encompass the relationships between all individuals within a well defined group, such as a family, classroom or school The people known by, or tied to, one specific individual define a personal network. Whole network data is obtained via

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25 survey or observational methods. Personal network data is obtained by asking the target individual to respond to one or several cues de signed to elicit a list of people known to them (Knoke et al., 2008). Network data are then analyzed as to characteristics of the network as a whole and then investigated as to their relationships to characteristics or behaviors of the target individual. Appreciation of the interdependence of the network members and their actions is elemental to the social network perspective. Framed within this perspective is the conceptualization that network structures are created by the patterns of relationships (i.e. network linkages) that exist between network members. These patterns are understood to be dynamic in nature. As such, the ties between network members represent opportunities and or mechanisms for transfer of items. These items can include resources, info rmation, attitudes, and or ideas (Wasserman & Faust, 1994). It is through these mechanisms that social networks impact the behaviors, actions, perceptions, values, and or beliefs of individuals within the network (Knoke et al., 2008). These mechanisms of t he network can conceivably impact participation of the youth with disabilities. Introduction to Social Network Analysis Social network analysis (SNA) refers to research methods involving mathematical analysis of the ties between network members. SNA encomp asses a describing relationships among social actors embedded in networks of social su (Faber & Wasserman, 2002, p. 29). Methods of social network analysis have bee n applied in the study of several areas of family research. These include the areas of parenting, divorce, and adolescent peer networks. Social network analysis has also

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26 been used in the study of social behaviors occurring in classrooms and schools. Despit e methodological advances in statistical network models, the bulk of social network research in the social and health sciences are at the desc riptive level (Faber et al. 2002). social network is commonly used in referring to websites that enab le people to connect with their family, friends, and acquaintances. However, long before these websites were conceived, the soc ial sciences utilized the term social network to refer to a social structure that is made up of its members and their interconnec tions (Scott, 2000; Wellman & Berkowitz, 1988). Empiric investigation of social networks entails the systematic quantification and mapping of the relationships between network members. These interconnections are referred to as relational ties E xamples of relational ties include friendships, kinships, and ties bound by shared experiences such as beliefs, knowledge, prestige, or common goals. Soci al network researchers posit that both the network members, and the patterns of relationships among members impa ct behaviors and attitudes of those within the network (Knoke et al., 2008). In the social sciences, social network analysis (SNA) refers to specific techniques in studying social networks historically employed by scientists in psychology, sociology, and a nthropology (Liao, 2008). Social scientists have a well developed language and methods for describing and analyzing social networks that can be applied to rehabilitation and disability sciences SNA involves the mapping and measurement of connections betw een network members. In SNA, the characteristics of network members, as well as their relati ve locations within the network can be evaluated ( i.e. calculated) and then used as numeric

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27 metrics of the network. This allows for conventional (e.g. statistical) analysis of network attributes, such as the average strength of ties among network members, or the range of social support provided by network members. referred to as structural a ttributes, or structural metrics. A common structural metric used in SNA is network centrality Centrality refers to available social power, influence, (Hanneman & Riddle, 2005 ). For example, centrality has been measured in children with autism in the investigation of inclusion within mainstream classrooms (Chamberlain, Kassari, & Rotheram Fuller, 2007). Structural metrics are contrasted with compositional attributes of network members, such as gender, beliefs, and provider of social support. SNA can then be used to gain insights into the roles and groupings of network members, and tested for relationships to any number of social phenomena (e.g. community integration) and indivi dual behaviors (e.g. follow through with therapeutic recommendations). This study employed methods of SNA specifically personal network methods, to gain a better understanding of the social environments of youth with cognitive disabilities related to deve lopment. Social Networks of Youth Growing Up with Disabilities Children with disabilities experience both structural and compositional differences in their social networks The social networks of youth with disabilities are smaller than typically developin g peers (Kef, 1997). Moreover, the networks of the youth with disabilities are composed of a lower proportion of peers and have fewer peers classified as close relationships (Harty, Joseph, Wilder, & Rajaram, 20 07). These youth have

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28 fewer connections to ot hers within classroom and school networks as compared to their peers (Chamberl a in et al., 2007; Ochs, Kremer Sadlik, Solomon & Sirota, 2001). Empirical findings describe constrained social networks for youth growing up with disability. In summary, structur al differences in the networks of youth with disabilities include (a ) smaller networks (b) fewer connections within the network, (c ) proportional ly fewer peers in the network, (e) fewer close ties, and (f ) of these ties, fewer were reciprocated to be clas sified as close (Kef, 1997; Chamberl ain et al. 20 07; Harty et al., 2007). These findings empirically support commonly held perceptions of children and youth with disabilities as functioning on the periphery of peer and classroom groups ( Chamberl a in et al. 2007 ) Disability of a child also impacts the social network of the family. Families with a child with disabilities have distinct network structures, to include differences in network size. However, the size of the social network does not relate to its effectiveness in providing social support for the child (Kazak & Marvin, 1984). While network size does overall density of the network has the most impact on family adjustm ent. Families with more categories of people in their network, in conjunction with quality relationships, have the best adjustment to having a child with a disability (Harty et al., 2007). Unfortunately, Harty and colleagues (2007) also found that while a support network may be effective for the family, it remains very difficult to draw supportive members into the network of the child with disabilities. Paid professionals often fill the close supportive network positions for children with disabilities. In t his investigation they assessed network composition, density and size across categories of relationship type

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29 (e.g. close friends and relatives, paid workers ) for children with disabilities. The children had an average of 40 paid interventionists in their n etwork, with few network members in any other category. Resultantly, paid interventionists were also located in the close friends family. Additio nally, relatives, half sibling s and family friends were reported as close friends of the family, but not as close friends of the children with disability. These researchers concluded that while a support network may be effective for the family, it is less effective for the child with d isability because it is very difficult to draw supportive members in hey found that paid professionals often fill close supportive roles for children with disabilities. Chamberlin, Kassari and Rotheram Fuller (2007) utilized a mix ed method approach that included use of whole network analysis to investigate social network effects on classroom social involvement of children with autism enrolled in mainstream classrooms. The children with autism were less centrally located than peers on the classroom network map. Qualitative analysis revealed that positive peer support enhances the social inclusion and integration of the autistic children, even in the absence of peer friendship groups and strong peer ties. Use of a mixed methods approa ch allowed these researchers to quantitatively describe the social network while qualitatively elucidating salient features of the social environment. At present there are no benchmarks for childhood personal network size or compositions for either typica lly developing or disabled populations. While findi ngs reviewed provide empiric support for commonly held perceptions regarding youth with disabilities, the clinical utility of social network metrics such as density and centrality is

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30 not yet known. Even th ough social network structures and compositions have begun to be measured in disabled youth populations, no theories have been advanced regarding the interpretation or meaning of these network metrics in their everyday lives. The structures, attributes, an d circumstances by which social networks are linked to health related participation and social functioning require further study. The literature has only begun to inform as to the conditions and circumstances in which personal network configurations facili tate and constrain aspects of participation for children with disabilities. This research explores the structures, attributes and circumstances by which social networks are related to participation. Summary The environment al contexts of childhood have an i mpact on the functioning and health of the developing child Important environmental contexts include the physical, social and attitudinal environments in which the child lives and goes about daily life (WHO, 2007). Social networks contribute to the social environment (WHO, 2007) and act to affect the perceptions, beliefs and behaviors of those within the group (Knoke et al. 2008). For young people with disabilities, undesirable attitudes and the normative values held by members of the proximal social netw ork can negatively impact overall developmental trajectory. The you th with disabilities may be ill equipped to overcome such undesirable attitudes or normative values (Heyman, Swain, Gillman, Handyside, and Newman, 1997). Conversely, social networks can ac t to enhance development and health through the provision of support, emotional connection, autonomy, and organization (Be rkman et al. 2000; Cohen et al., 2007; Heaney & Israel, 2002; Litwin, 2006; Godde et al., 1994). Support from the social environment provides protective benefits that improve well being through pathways of belonging, approval and

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31 understanding; all of which are important for fostering self assurance and bolstering developmental trajectories (Bryant, 1994; Nestmann & Hurrelmann 1994). F or youth, social n etworks serve as contexts of participation necessary for healthy development This research is an exploratory investigation of childhood participation whereby understanding of the environment is integral to understanding of participation (WHO, 2007). Methods of social netwo rk analysis were used as the framework for examining the soci al environment, from which understandi ng of links to participation were sought. The primary purpose of this research was to describe social networks and partic ipation for youth with cognitive difficulties related to development ; specifically, youth with diagnoses of learning disability, attention deficit disorder or autism spectrum disorder Specific Aims, Hypotheses and Research Questions Specific Aim 1. Ident ification and description of aspects of the social network for youth growing up with cognitive disabilities related to development (clinical youth) and typically developing youth. Specific A im 1a : Personal network analysis of youth from the clinical and t ypically developing groups. Hypothesis. The social networks of the clinical youth will have both structural and compositional differences when compared to networks of youth from the typically developing group. Specific Aim 1b: Explore social network experi ences and understanding of youth from in the clinical group through cognitive interview. Research question: How do the youth with disability understand and experience their social networks? Specific Aim 2. Determine relationship of social network variable s to participation Hypothesis. Social network structures and compositions are significantly related to participation.

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32 CHAPTER 2 STUDY DESIGN AND DESCRIPTION OF STUDY SAMPLE Study Design Two Group, Cross Sectional, Mixed Method Study The overall goal of this research was to identify key social network variables to partici pation for youth with cognitive disabilities related to development A two group, cross sectional, mixed method approach was employed to address study aims Figure 2 1 graphically outline Figure 2 1 Visual diagram of study design The collection of both quantitative (i.e. social network metrics and participation data) and qualitative data (i.e. social network experiences and perceptions) takes advantage of the st rengths of both research approaches for the purpose of extending results (Cre swell & Plano Clark, 2007). The use of social network analysis within an

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33 investigation employing both statistical and qualitative analytic approaches enabled multiple vantages for Overview of Study Protocol participants ( N = 36 ) underwent measurement of participation and their social netw ork using methods of personal network analysis After this quantitative data collection, each participant A cognitive interview was then c onducted with youth in the clin ical group ( n = 19 ) where inquiry focused on perceptions and experiences related to their social network General Analytic A pproach Quantitative and qualitative data was collected simultaneously but analyzed separately. Quantitative data (social network m etrics and measurements of participation) were examined via descriptive statistical methods correlation analyses and simple linear regression Qualitative interview data underwent thematic analysis focusing on the discovery of patterns or recurring theme s. Following the separate quantitative and qualitative analyses, findings from both analyses were considered as a whole. This allowed for extension of interpretation of quantitative data through enhancement and elaboration of understandings gained from the cognitive interviews (Greene, Caracelli, & Grah am, 1989; Creswell et al. 2007). Figure 2 2 provides a visual model of the general analytic approach used in t his study Figure 2 2. Visual diagram of general analytic approach

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34 Participants A convenience sample of 36 youth was used in this two group study. The clinical group consisted of 19 youth with cognitive disabilities related to development. Clinical diagnoses included learning disability (LD), attention deficit disorder (ADD), and or autism spectrum disorder (ASD). The comparison group was comprised of 17 typically developing youth (no diagnosed physical, sensory or cognitive impairments). Groups were matched for similar age and gender distributions. Inclusion and Exclusion Criteria Inclusion criter ia : (1) Youth with self or parent reported diagnoses of learnin g disability, attention deficit disorder or high functioning autism or (2) typically developing youth who: are ages 11 16 years old at grade level ( 1 grade), reside at home with at least on e biological or adoptive parent or adult relative, and can engage in an English speaking verbal interview. Exclusion criteria: Youth who have: intellectual disability, sensory disability such as low vision or hearing, severe communication impairment an d/or use augmentative communication, chronic mobility or orthopedic impairment, cerebral palsy, a progressive neurological condition such as Muscular Dystrophy, a chromosomal or genetic condition such as Down Syndrome, or an acquired neurological conditi on such as traumatic brain injury. Youth with learning disability have difficulty in learning to read, do math, and or write. They can also have motor coordination, social, and emotional difficulties that can include problems expressing themselves, calmin g themselves down, and or reading

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35 social cues (American Psychiatric Association, 2000; McPhillips, Hepper, & Mulhern, 2000). Any of these difficulties can contribute to classroom and peer difficulties. Clinical symptoms of attention deficit disorders incl ude difficulty paying attention and difficulty controlling impulsive behaviors. Youth with attention deficit disorders can have high levels of impairment resulting in difficulties that interfere with friendships and classroom learning (Strine et al., 2006) They are three times more likely than typically developing youth to develop peer problems (Strine et al., 2006). Clinical symptoms of individuals on the autism spectrum include social and communication difficulties, as well as repetitive and stereotyped behaviors. They can also have difficulties with language and motor skills (National Institutes of Mental Health, 2011). All of which can contribute to participation difficulties in social groups. Secondary Participants (or adu lt relative assuming a parental role ) were also included as secondary participants. Secondary participants were queried as to demographic features of the household (e.g. income and education level) and, if agreed upon by the youth and parent, were present and conversant during the cognitive interview. While this study actually collected data from both the youth and parent, the term participant used throughout this dissertation refers to the youth. Recruitment Recruitment strategies included word of mouth, professional referral, recruitment flyers, and nomination. Recruitment flyers were posted in public areas and handed out at area schools and therapy clinics inviting potential participants to take part in the study. Recruitment flyers were also attached to informational (i.e. advertisement) e mails to professional and community contacts. Nomination (or chain) sampling was

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36 used to obtain additional participants by asking participants and potential participants to share an advertisement flyer, informational e information with other people they knew who meet the inclusion criteria and might be interested in participating (Bernard, 2006). Potential youth participants underwent phone screening to ensure study eligibility befor e obtaining informed consent. Eligible individuals were invited to participate, after which scheduling for review of the informed consent was arranged. Parent report was used to verify study eligibility. When meeting for the scheduled consent process, pare nts were asked to read and sign an informed consent form and written assent was requested of each youth prior to data collection. This study used only one Informed Consent Form so as to avoid stigmatizing youth in the clinical group. It was believed that youth with hidden disabilities might be only marginally aware of having a clinical diagnosis. Youth with hidden disabilities might not be aware that the difficulties experienced at home or school are due to their diagnostic condition. These youth might onl y conceptualize their supports as receiving Setting home or at the University of F lorida Department of Occ upatio lab The research lab, referred to as the Gator tech Smart House, afforded a convenient, private and comfortable home like setting for working with research participants. In order to minimize respondent burden, study researchers worked to complete data collection in one meeting. However, some participants from the clinical group required two meetings in order to complete data collection.

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37 Overview of Data Collection Used to Quantifiably Describe Study Par ticipants Study Procedures for All Study Participants For all participants ( N = 36), data collection included brief medical, developmental and educational history, as well as clinical observations of posture and reflex persistence. Data collection for all participants also included (a) questionnaires, social network visualization (visualizations were generated from the social network questions). This portion of data c ollection typically lasted between one to two hours amount of parental assistance provided in answering questions Parents of youth in both groups were invited to assist the youth with completing qu estionnaires and responding to social network questions as needed in order to reduce respondent burden. Also to minimize respondent burden, participants were given the opportunity to complete questionnaires at home over the course of a few days prior to me eting with researchers for the social network questionnaire and interview. Only two participants, one from each group, opted for this. All participating youth received at ten dollar gift card as thanks for their involvement in the research. No compensation was offered to the parents of participating youth. Additional Data Collection for Youth in the Clinical Group Youth in the clinical group ( n = 19) were asked to participate in an additional cognitive interview regarding their experiences with different pe ople and groups within their social network. In addition, youth in the clinical group underwent additional testing of motor skills, visual motor integration, and sensory processing. This was done to

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38 enable description of the target sample in more clinicall y meaningful ways. These additional procedures added approximately 1 to 1 hours to study involvement. Demographic Description of the Study Sample Demographic and clinical diagnosis, rehabilitation history, academic history, family composition, and parental education was collected using a paper and pencil questionnaire developed for this study. Parents, as secondary participants, completed the questionnaire while the researcher worked directly with the youth. Afterwa rds, responses were reviewed with the parents for validation purposes and to minimize missing information. Demographic variables were chosen, in part, due to their impact on participation (Law et al., 2004; Shikako Thomas, Majnemer, Law & Lach, 2008). Dem ographic Variables D emographic variables include d : to 15 days were rounded up to the next month. For example, a youth who was 12 years, 8 months and 20 days old was recorde d as 12 years 9 months olds and calculated to be 12.75 years old. Gender Grade: Since most data collection occurred in the summer, the last completed grade was recorded. School Setting: School setting of the last completed grade was recorded. School settin gs included public school, charter school, private school, and home school settings. Parental Education: Highest household parental educational attainment was recorded. Race Household Status: Number of households the youth is a member of (e.g. two househol ds in the case of divorced parents with shared custody)

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39 Number of Siblings: Total number of siblings; whole, half and/or step included Minors in Household(s): Total number of minors residing in each household Analysis of Demographic Variables Demographic v ariables were analyzed for differences between the clinical and typically developing group s with no statistically significant differences found ( p < 05 ). The groups were compared with regard to age using independent samples t test. The remaining continuou s demographic variables were analyzed for group differences using Mann normal distribution. Descriptive tests. Table 2 1 pre sents demographic characteristics of youth in the clinical and typically developing comparison groups. Clinical and comparison group participants were primarily Caucasian (78%) and male (83%). They had an average age of 13.9 years ( SD = 1.27). The average grade completed was the seventh grade. Half (50%) of the study sample attend public school, the other half were being educated in a charter, private or home school setting. Ninety four percent of youth in the sample were being raised in a household where a t least one parent had attended college, and 92% were being raised in a single household. Participants in this study resided with an average of 1. 4 additional minors ( SD = 1.1) and reported an average of 1.6 siblings ( SD = 1.6 ). Only 3 females were recrui ted who had qualifying clinical diagnoses. Diagnoses needed for inclusion in this study, LD, ADD and ASD, occur more frequently in boys than girls (Pastor & Reuben, 2008; Center s for Disease Control and Prevention, Autism and Developmental Disabilities Mon itoring Network Surveillance Year 2008 Principal Investigators [CDC], 2012 ). The 1:5 ratio of clinical participants obtained for this study is

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40 consistent with the Centers for Disease Control and Prevention reported prevalence of ASD; ASD is five times more common in boys than girls (CDC, 2012). Table 2 1. Demographic characteristics of clinical and comparison groups Demographic variable Youth with disability ( n = 19)* Typically developing youth* ( n = 17) Group differences ( p < .05 ) Age, mean, SD 13.9 1.3 13.9 1.2 p = .91 Gender Male Female 16 (84.2) 3 (15.8) 14 (82.4) 3 (17.6) p = 1.00 Grade, mean, SD 7.2 1.6 7.6 1.5 p = .55 School Setting Public Charter Private Home 9 (47.4) 2 (10.5) 6 (31.6) 2 (10.5) 9 (5 2.9) 0 (0.0) 8 (47.1) 0 (0.0) p = 1.00 Parental Education High School or below College or more 2 (10.5) 17 (89.5) 0 (0.0) 17 (100.0) p = .49 Race Caucasian Other Not reported 15 (78.9) 4 (21.1) 0 (0.0) 13 (76.5) 2 (11.8) 2 (11.8) p = 1.00 Single home Multiple homes (e.g. divorce) 17 (89.5) 2 (10.5) 16 (94.1) 1 (5.9) p = 1.00 Number of Siblings, mean, SD 1.4 0.8 1.8 1.0 p = .24 Minors in Household, mean, SD 1.3 0.9 1.5 1.1 p = .73 *Data are given as count (percentage within the group) unless otherwise indicated 2 sided assumed Comparing public school attendance versus attendance at all other school settings Comparing Caucasian versus other plus not reported From th e clinical group ( n = 19), 14 participants had a single diagnosis of LD, ADD or ASD. The remaining 5 participants had some combination of diagnoses that included ASD plus LD, ADD plus ASD, or ADD plus LD. Every combination of 2 of the 3 diagnoses was repre sented in the study sample. Co occurrence of the diagnoses of LD, ADD and ASD is not uncommon (National Institutes of Mental Health, 2011). In a United

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41 States population based cohort of 2,568 eight year olds identified with ASD, 83% had at least one other co occurring developmental diagnosis, which include diagnoses of ADD and LD (Levy et al., 2010). Data from the 2004 2006 National Health Interview Survey indicate that 4% of American yo uth, ages 6 to 17 years old, have both ADD and LD. This is compared t o 5% of children having ADD without LD, and 5% having LD without ADD (Pastor et al., 2008). Of the 14% of American youth with ADD and or LD, 28% had co clinical representat ion where 26% of the clinical group had co occurring diagnoses. Diagnostic and clinical histories of the study sample are reported in Table 2 2 The majority (74%) of youth in the clinical group had a medical history significant for rehabilitation services of occupational therapy (OT), speech therapy (ST), and or physical therapy (PT) services. This is compared to 4 (24%) youth from the comparison group, where 3 received PT due to sports injury or walking delay, and 1 received ST. Additionally, 12 clinical participants ( 63%) had a medical history significant for mental health counseling; only one (6%) youth from the comparison group has received mental health counseling. Eight youth from the clinical group (42%) had a history of receiving academic tutoring. Only 2 youth from the comparison group have received academic tutoring; notably, they are the same 2 youth who received early intervention PT for delayed walking. The range and extent of supportive services sought for the youth in the clinical group is con sistent with the range of difficulties associated with the diagnoses

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42 Table 2 2. Diagnostic and clinical history of clinical and comparison groups Clinical history Youth with disability ( n = 19) Typically deve loping youth ( n = 17) Single diagnosis of LD, ADD or ASD 2 of 3 co occurring diagnoses of LD, ADD, and/or ASD 14 (73.7) 5 (26.3) 0 (0.0) 0 (0.0) C urrently receiving OT 2 (10.5) 0 (0.0) Currently receiving ST 2 (10.5) 0 (0.0) Currently receiving PT 0 (0.0) 0 (0.0) Currently receiving counseling 5 (26.3) 0 (0.0) Currently receiving academic tutoring 4 (21.1) 0 (0.0) History of OT 13 (68.4) 0 (0.0) History of ST 8 (42.1) 1 (5.9) History of PT 9 (47.4) 3 (17.6) History of counseling 9 (47.4) 1 (5.9) History of academic tutoring 7 (36.8) 2 (11.8) Data are given as count (percentage within group) Clinical Descriptions of Study Sample In order to describe the study sample in more clinically meaningful ways, additional data was collected from all par ticipants re garding motor, social, academic and functional performance. Instruments used for clinical description of both groups include (a) the Developmental Coordination Disorder Questionnaire 2007, (b) the Pediatric Quality of Life Inventory TM (c) the Strengths and Difficulties Questionnaire, and (d) the Social Responsiveness Scale. In addition, primitive and postural reflexes were clinically observed for continued persistence or extent of maturation. Instruments Used to Clinically Describe the Study Sa mple The valid and reliable screen for childhood coordination disorder in youth ages 5 15 years old (Wilson et al., 2009) It is a brief 15 item parent report questionnaire with evidence for clinical cut scores using the total score. T he t otal score is a

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43 summative score from three factor scores of (a ) Control During M ovement, (b) Fine M otor/H andwriting, and (c) General C oordination. The Pediatric Quality of Life Inventory TM ( PedsQL TM ) w as used to measure P hysical Function, E motional Function, S ocial Function S chool Function and Cognitive F unction. Specifically, the PedsQL TM Generic Core Scales and the PedsQL TM Cognitive Functioning Scale (Varni, Seid, & Rode, 1998) were us ed. The PedsQL TM are brief parent or self report tools with evidence of validity and reliability in pediatric populations with ADD and related, co occurring psychiatric disorders (Limbers, Ripperger Suhler, Heffer, & Varni, 2011). It also distinguishes bet ween healthy children and those with health conditions as well as distinguishing severity (Varni, Seid & Kurtin, 2001). The Strengths and Difficulties Questionnaire is a valid and reliable brief measure of social and emotional behaviors in 3 16 year ol ds ( Goodman, 1997) Parents completed this 25 item questionnaire measuring ( a) E motional S ymptoms, (b) Conduct P roblems, (c) Hyperactivity I nattention, (d) Peer P roblems, and (e) Pro social B ehavior. Clinical cut scores indicative of performance in the B o rderline and C linical ranges have been established from representative youth samples in the United Kingdom and the United States. The Social Responsiveness Scale is valid and reliable parent questionnaire of interpers onal behaviors in the areas of Socia l Awareness, Social Cognition, Social Communication, Social Motivation, and Autistic M annerisms in children ages 4 18 years ( Constantino & Gruber, 2005). This instrument was standardized on a sample of >1600 school age children and yields norm referenced linear T scores that follow

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44 clinical conventions for interpretation ( T scores are derived standard scores with a mean of 50 and a standard deviation of 10) Clinical assessment of the persistence of primitive reflexes was also conducted on all study part icipants. The persistence of primitive reflexes in school age children are observed in children with learning and attention disorders (Blythe, 2006; Taylor, Houghton, & Chapman, 2004) and are used in the early detection of ASD (Teitelbaum et al., 2004). Ef fects of persistence of primitive reflexes and underdevelopment of postural reflexes include coordination and balance difficulties, visual perceptual difficulties, spatial disorientation, and poor posture (Goddard, 2005). Participants in this study were cl inically observed for the persistence of asymmetric tonic neck reflex (ATNR), symmetric to nic neck reflex (STNR), and development of the Landau postural reflex. Reflex testing involved asking participants to perform specific physical activities such as hol ding arms erect in front of the body while the examiner slowly turned the eyes were closed (Schilder test point scale whereby each reflex had specific descriptors for each rating. For example, indications for persistence of ATNR included ratings of 0 = no movement, able to sustain position; 1 = slight movement of the arms up to 20; 2 = movement of the arms up to 45; an d 3 = arm movement greater than 45 and/or swaying or loss of balance. Analysis of Clinical Variables Clinical variables were derived directly from clinical assessment tools and clinical observations previously described. Analyses of clinical variables wer e conducted to confirm that clinical differences existed between the clinical and typically developing groups. Statistically significant differences ( p < .05) were found for all clinical variables.

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45 Assumptions of normalcy were not met for the majority of the continuous clinical variables; therefore Mann Whitney U tests were used to test most group comparisons. When assumptions of normalcy were met, independent samples t tests were used. cal variables. Motor characteristics Analyses of clinically descriptive data related to the motor characteristics of the study sample are presented in Table 2 3 Youth in the clinical group demonstrated significantly different levels of neuromotor developm ent as indicated by scores on the otal scores 57 are clinically indicative of the presence of four coordination disorder. Only one youth in the typically developing group had an indication for developmental coordination disorder. Clinical observation of reflex persistence resulted in 84% of the clinical group demonstrating persistence or delay of >1 reflex. None from the comparison group demonstra ted the persistence or delay of >1 reflex. Functional characteristics Functional characteristics of the study sample were assessed using clinical history, the PedsQL TM the Strengths and Difficulties Questionnaire, and the Social Responsiveness Scale Stat istically significant group differences were found for all functional measures used. Table 2 4 presents characteristics. Significantly more youth in the clinical group had a history of academic retention (47% compared to 11% for youth in the comparison group).

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46 Table 2 3 Motor characteristics of clinical and comparison groups Motor clinical variables Youth with disability ( n = 19)* Typically developing youth ( n = 17)* Group differences ( p < .05 ) Indication of developm ental coordination disorder 16 (84.2) 1 (5.9) p < .001 median (Min Max) Movement control Fine motor control General coordination 39.0 (26.0 67.0) 19.0 (9.0 30.0) 9.0 (6.0 20.0) 12.0 (5.0 25.0) 74.0 (5 7.0 75.0) 30.0 (25.0 30) 20.0 (15.0 20.0 25.0 (12.0 25.0) p < .001 p < .001 p < .001 p < .001 Persistence or delay >1 reflex 16 (84.2) 0 (0.0) p < .001 Persistent ATNR 14 (68.4) 3 (23.5) p = .001 ATNR Mildly persistent Moderately persistent Strongly persistent 7 (36.8) 7 (36.8) 0 (0.0) 2 (11.8) 1 (5.9) 0 (0.0) Persistent STNR 15 (78.9) 5 (29.4) p = .006 STNR Mildly persistent Moderately persistent Strongly persistent 1 (5.3) 12 (63.2) 2 (10.) 5 (29.4) 0 (0.0) 0 (0.0) Poorly developed Landau 14 (73.7) 2 (11.8) p < .001 Landau Mild reflex lag Moderate reflex lag Severe reflex lag 8 (42.1) 6 (31.6) 1 (5.3) 2 (11.8) 0 (0.0) 0 (0.0) *Data are given as count (percentage with in the group) unless otherwise indicated. 2 sided assumed. On the PedQL TM higher scores indicate fewer problems in areas of health related quality of life. For the clinical group, the mean PedsQL TM total score was 55.2 out of 100 ( SD = 16.4). This is be low the established clinical cut point of 78 (Huang et al., 2009). Youth in the clinical sample were reported to have the most difficulty in cognitive and social functioning. All youth in the typically developing group scored above the clinical cut point o n the PedsQL TM

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47 Table 2 4 Functional characteristics of clinical and comparison groups Functional performance variables Youth with disability ( n = 19)* Typically developing youth* ( n = 17) Group differences ( p < .05 ) History of academic retention 9 (47.4) 2 (11.8) p = .03 1 Overall Function Mean, SD 55.2 16.4 92.5 6.8 p < .001 Physical Function Median ( Min Max ) 75.0 (33.0 100.0) 100.0 (65.6 100.0) p < .001 Emotional Function Median ( Min Max ) 60.0 (25.0 90.0) 95.0 (80 .0 100.0) p < .001 Social Function Median ( Min Max ) 45.0 (0.0 100.0) 100.0 (85.0 100.0) p < .001 School Function Median ( Min Max ) 50.0 (25.0 100.0) 85.0 (70.0 100.0) p < .001 Cognitive Function Median ( Min Max ) 4 1.7 (0.0 100.0) 95.8 (58.33 100.0) p < .001 Difficulties with conduct mean, SD 2.6 2.2 0.5 0.6 p < .001 Hyperactive behaviors mean, SD 6.0 3.0 2.2 1.3 p < .001 Peer problems mean, SD 4.2 2.6 0.5 0.7 p < .001 Social awareness dif ficulties Mild to moderate difficulties Severe difficulties 10 (52.6) 7 (36.8) 3 (15.8) 1 (5.9) 1 (5.9) 0 (0.0) p = .003 Social cognition difficulties Mild to moderate difficulties Severe difficulties 11 (57.9) 2 (10.5) 9 ( 47.4) 0 (0.0) 0 (0.0) 0 (0.0) p < .001 Social communication difficulties Mild to moderate difficulties Severe difficulties 13 (68.4) 9 (47.2) 4 (21.1) 0 (0.0) 0 (0.0) 0 (0.0) p < .001 Social motivation difficulties Mild to moderate difficulties Severe difficulties 12 (63.2) 6 (31.6) 5 (26.3) 0 (0.0) 0 (0.0) 0 (0.0) p < .001 *Data are given as count (percentage within the group) unless otherwise indicated 2 sided assumed Measured using the PedsQL TM Measured using the Strengths and Difficulties Questionnaire Measured using the Social Responsiveness Scale Using the Strengths and Difficulties Questionnaire (SDQ), parents reported youth in the clinical group to have significantly more difficulties with conduct, hyperact ive behaviors, and peer problems than compared to youth in the typically developing group.

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48 Higher scores on the SDQ indicate more problems. Clinical cut points for SDQ symptom scores are as follows: (a) Conduct P roblems H yperactive B ehavior and (c) P eer P roblems borderline or worse conduct problems. No youth in the comparison group were reported to have conduct problems. Borderline or worse hyperactive behavior problems were re ported in 10 (53%) clinical youth and no comparison youth. Borderline or worse peer problems were reported in 13 (68%) youth from the clinical group, and none reported for youth in the comparison group. Using the Social Responsiveness Scale (SRS), more tha n half of the youth in the clinical group had social impairments. On the SRS, lower scores indicate fewer problems. Scores reported throughout this dissertation refer to clinically meaningful T scores. Scores in the 60 75 range are identified to have M il d to M oderate S evere impairments. Mean total score on the SRS was 72.8 ( SD = 16.6) for the clinical group, and 41.6 ( SD = 5.3 ) for the comparison group. Fourteen youth f rom the clinical group ha d SRS Total S cores above the clinical cut point for clinically significant social impairments; no youth from the comparison group was abov e the clinical cut point for SRS Total S core s Additional Clinical Description of the Youth in the Clinical Group Add itional measures of individual differences were used to more fully describe the clinical group in ways familiar to practicing occupational therapists. Widely used occupational therapy evaluation instruments were used for the additional assessment. These cl inical assessments include d the Brunicks Oseretsky Test of Motor Proficiency, Second Edition (BOT 2), the Quick Neurological Screening Test 3 rd Edition (QNST 3), Beery Buktenica Developmental Test of Visual Motor Integration, Sixth Edition

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49 (Beery VMI), a nd the Adolescent/Adult Sensory Profile (AASP). Clinical measures chosen are sensitive to measurement of the varying levels of performance (e.g. motor coordination visual motor integration and sensory processing ) in i ndividuals with LD, ADD and ASD. Desc ription of additional clinical assessments The BOT 2 is a valid and reliable, widely used norm referenced comprehensive measure of motor proficiency for youth age 4 21 years. Youth engage in a variety of challenging game li k e tasks, many of which are tim ed. Examples of BOT 2 item activities include hopping on one foot, transferring pennies, and sit ups. The QNST 3 is a valid norm referenced measure of neurological soft signs in individuals 5 80 years old ( Mutti, Martin, Sterling & Spalding, 2011). The presence and severity of neurologic soft signs are indicative of the presence and severity of sensory motor regulation impairment ( Mutti et al. 2011). Administr ation of the QNST 3 involved structured observation of 13 tasks examples of which include palm form recognition, eye tracking, and reproduction of sound patterns Raw scores from individual items were interpreted in terms of three functional categories, which include d No D iscrepancy (performa iscrepancy (performance in 6 25th percentile), and Severe D percentile). The Beery VMI is a valid and reliable norm referenced measure of visual motor integration, visual perception, and motor coordination in individuals 2 100 years old Visual motor integration, visual perception, and fine motor coordination are common areas of impairment in youth with neurodevelopmental disabilities. This paper and pencil assessment asked the youth to copy geometric drawings, identify matching

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50 shapes from black and white models, and draw within the lines of black and white geometric shapes. The test of visual motor integrat ion (copy geometric drawings) was untimed, while the shape matching a nd drawi ng within the line sub tests w ere timed. The Beery VMI yields a standard score and percentile ranking for visual motor integration, visual perception, and motor coordination. The AASP is a valid and reliable measure of sensory processing in individuals ag es 11 years and older (Brown & Dunn, 2002) It is a 60 item self report questionnaire that yields information regarding individual differences in the categories of visual, auditory, touch, taste/smell, movement, and activity level sen sory processing. Respo ndents were asked to rank the frequency of response to everyday sensory experiences using a five point scale ranging from almost never to almost always. Cut scores and sensory processing classifications on the AASP are reflective of the ent along a continuum of normally distributed scores Results of additional clinical assessment Seventeen (89%) youth in the clinical group had difficulties that placed them in the lower quartile (to include at least one standard deviation from the mean of the normative sample) on at least 3 of the 5 additional clinical measures. Two youth had scores in the lower quartile on only 2 of the 5 measures. Of these two youth with the mildest difficulties, one was diagnosed with ADD and the other was diagnosed wit h ADD and AS. Table 2 5 assessments. The BOT 2 Short Form was used to test motor performance. On the BOT 2, 17 (89%) clinical youth scored in the lower quartile for their age and gender. The Q NST was used to test sensory motor maturation. On the QNST 3, 13 (69%) clinical youth

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51 scored in the lower quartile for their age. Beery VMI scores placed 8 of 17 (47%) in the lower quartile for visual motor integration. Eight (42%) clinical youth scored be low the 25 th percentile on the Beery Visual Perception subtest. Scores on the AASP indicated that 16 (84%) clinical youth have sensory processing 1 SD from the norm). Table 2 5 Performance of clinical group on occupational therapy clinical assessments Clinical assessment tool Count (Percentage) BOT 2 (motor coordination) 25 th percentile 6 th 24 th percentile 0 5 th percentile 2 (10.5) 13 (68.4) 4 (21.1) QNST 3 (neurologic soft signs) 25 th percentile 6 th 24 th percentile 0 5 th percentile 7 (36.8) 6 (31.6) 6 (3 1.6) Beery VMI (visual motor integration)* 25 th percentile 6 th 24 th percentile 0 5 th percentile 8 (47.1) 3 (17.6) 6 (35.3) Beery Visual Perception 25 th percentile 6 th 24 th percentile 0 5 th percentile 11 (58.0) 6 (31.6) 2 (10.5) AASP (sensory processing) 0 standard deviations from normative sample mean 1 standard deviation from normative sample mea n 2 standard deviations from normative sample mean 3 (17.6) 11 (58.0) 5 (26.3) n = 17 Description of Participation for the Study Sample Instrument Used to Measure Participation Participation is the dependent variable in this resea rch study. Assessment of Participation and Enjoyment (CAPE ; King et al., 2004) was used to measure participation. The CAPE is a 55 item questionnaire designed to assess the way in which youth ages 6 21 years with and without impairment, p articipate in

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52 everyday activities beyond those mandated by school The CAPE quantifies 5 dimensions of participation: Diversity the number of activities engaged in by the youth; Intensity the frequency of engagement in activities over the past 4 mont hs, reported on a 7 point scale (1 = once, 2 = twice, 3 = once per month, 4 = 2 3 times per month, 5 = once per week, 6 = 2 3 times a week, 7 = once daily or more); With Whom the breadth of with whom youth usually engages in activities, reported on a 5 p int scale (1 = alone, 2 = with family members, 3 = with other relatives, 4 = with friends, 5 = with others); Where where youth typically engages in activities, reported on a 6 point scale 4 = at school, 5 = in your community, 6 = beyond your community); and Enjoyment point scale (1 = not at all, 5 = love it). Additionally, the CAPE breaks participation dimension s down fur ther by activity type, to include (a) Recreational, (b) Physical, (c) Social, (d) Skill Based and (e) Self Improvem ent activities The CAPE also measures activity engagement within the domains of (a) Formal activities and (b ) Informal activities Infor mal activities refer to more spontaneous activities, which are contrasted with Formal activities that are scheduled and or structured (e.g. karate class, swim team ) Psychometric evidence has been reported as t o the construct validity of metrics used in th is instrument (King et al., 2007 ). Variables related to participation were drawn directly from the activity types, domains, and dimensions of participation measured by the CAPE. Study variables include d the dimensions of Diversity, Intensity, With Whom, and Where. Scores within each dimension were calculated for Overall, Informal, Recreational, Physical, and Social

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53 activities were also used as variables in this study. In this research, variables were categorized by activity type and activity dimension. Analys is of Participation All CAPE variables were assessed for violation of assumptions needed for application of i ndependent samples t tests to test for differences in CAPE scores between the two study groups Participation variables that were not normally dist ributed were tested for group differences using Mann Whitney U tests. The assumption of normality was satisfied for all group combinations of CAPE variables, with the exception of Overall Diversity and Social Diversity. Normalcy wa s assessed by Shapiro Wil with visual inspections of histograms and Normal Q Q Plots to confirm. There were no extreme outliers in the data. Outliers were determined by inspection of the box plot of all combinations of clinical/c omparison group and CAPE scores. O utliers we re considered extreme at >3 box lengths from the edge of the box Nine of 20 CAPE variables were identified to have ou tliers between 1.5 and 3 box lengths from the edge of the box Because these outliers were not extreme, they were included in the analyses For variables containing outliers, Mann Whitney U tests d was use to calculate e ffect sizes for normally distributed variables when assumptions for homogeneity of for equality of variances was used to test this assumption. When the assumption was violated, effect size was not calculated. Because both correlation coefficients and effect size are measures of association, the correlation coefficient, r, was used to ca lculate effect size for variables lacking normalcy. Effect size, or r was calculated by dividing the absolute value of the standardized test statistic, Z, by the square root of the number of observations (Corder & Foreman, 2009).

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54 Cohen (1988) suggestions that correlations and effect sizes of 0.5 ( r 2 = .25), 0.3 ( r 2 = .09), and 0.1 ( r 2 = .01) correspond to large, medium, and small relationships respectively were used in this study. Results Table 2 6 CAPE scores and comparisons between clinical and compa rison groups CAPE sub scale Clinical ( n = 19) Comparison ( n = 17) Group d ifferences ( p < .05) Effect size Diversity Overall Mdn = 33.0 Rng = 15.0 Mdn = 31.0 Rng = 15.0 U = 211.0 p = .47 r = .12 Informal 25.8 3.5 27.3 3.9 t = 1.214 p = .23 d = .4 1 Recreational 7.9 1.7 7.7 1.8 t (34) = .421 p = .68 d = .14 Physical 4.8 4.8 7.1 1.5 { t (34) = 4.093 p < .001 } d = 1.37 Social Mdn = 9.0 Rng = 6.0 Mdn = 8.5 Rng = 5.0 U = 158.0 p = .93 r = .0 2 Intensity Overall 2.5 0.3 2.6 0.4 t (34) = 1.163 p = .25 d = 39 Informal 2.9 0.3 3.1 0.5 t (34) = 1.244 p = .22 d = .42 Recreational 3.2 0.8 2.8 0.9 t (34) = 1.257 p = .22 d = .42 Physical 1.5 0.5 2.4 0.6 { t (34) = 3.950 p < .001} d = 1.43 Social 3.3 0.6 3.7 0.7 t (3 4) = 2.023 p = .051 d = .68 With Whom Overall 2.3 0.3 2.6 0.3 { t (34) = 2.700 p = .01} d = .90 Informal 2.2 0.3 2.5 0.3 { t (34) = 2.842 p = .01} d = .95 Recreational 2.0 0.5 2.2 0.5 t (34) = 1.190 p = .24 d = .40 Physical 2.7 .70 3. 1 2.7 { t(32.3) = 2.134 p = .04} nc** Social 2.5 0.5 2.9 0.4 { t (34) = 2.989 p = .005} d = .98 Where Overall 2.7 0.3 3.2 0.4 { t (34) = 3.890 p < .001 } d = 1.30 Informal 2.6 0.3 3.1 0.4 { t (34) = 4.046 p < .001} d = 1.35 Recreation al 1.9 0.5 2.1 0.6 t (34) = 1.119 p = .27 d = .37 Physical 3.3 0.9 4.1 0.5 { t (27.7) = 3.572 p = 001} nc** Social 3.1 0.5 3.4 0.7 t (34) = 1.470 p = .15 d = .49 *Data are Mean, SD unless otherwise reported **Not calculated due to lack of homogeneity in variance

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55 Table 2 6 provides detailed results of statistical analysis. Statistically significant differences were found in 9 of 20 participation variables measured by the CAPE Youth in the clinical group scored significantly lower on sever al CAPE scores regarding With Whom and Where. Lower With Whom scores correspond to proportionally more activities being done alone or with family. Lower Where scores correspond to proportionally more activities being engaged in at home or at a relative s h ome. As a group, youth in the clinical sample had significantly lower scores on 4 of 5 With Whom variables to include Overall, Informal, Physical and Social With Whom. They also had significantly lower scores on 3 of 5 measures of where activity occurred to include Overall, Informal and Physical Where. Youth in the clinical group had significantly lower Physical Diversity and Physical Intensity scores as compared to youth in the typically developing comparison group. Lower Physical Intensity scores indica te less frequent engagement in physical types of activities. Mean Social Intensity scores were lower for the clinical group, but only approached statistical significance ( p = .051). Lower Social Intensity scores are indicative of less frequent engagement i n social types of activities. N o differences were found in CAPE Recreation scores. Summary The two groups in this study were matched for age and gender distributions as well as demographic variables of race, parental education, and household and sibling st atus Beyond diagnostic differences, youth in the clinical group performed differently on measures of sensorimotor and functional performance. Youth in the clinical group had poorer performance on all sensorimotor and functional measures. The majority of c linical youth had difficulties with motor coordination (89%) and sensory processing

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56 (84%). Additionally, approximately half of the clinical youth had difficulties with visual motor integration and/or non motor visual perception. Because youth in the clini cal group had significantly different sensorimotor and functional performance abilities, it was not surprising that these youth would have different participation experiences than youth without disabilities. Several group differences were found on measures of With Whom and Where activity occurred. These effects were observed for both the Overall and Informal activity measures Youth in the clinical group had l ower CAPE With Whom and Where scores indicating that youth in the clinical group stay closer to hom e (Where) and doing more things alone or with family (With Whom).

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57 CHAPTER 3 SOCIAL NETWORK ANALYSIS AND LINKS TO PARTICIPATION This chapter describes the social network investigation conducted, and the statistical analyses of social network and particip ation variables. The chapter begins with methodo logical details regarding personal network analysis. The subsequent portion corresponds to Specific Aim 1a. In this portion of the chapter, visual and statistical network comparisons are presented for the 2 g roups used in this study. The final portion of the chapter corresponds to Specific Aim 2. In this final portion, correlation and regression statistics are presented for social network and participation variables. Details regarding specific aims and related hypotheses are provided again here for reference purposes. Specific Aim 1. Identification and description of aspects of the social network for youth growing up with cognitive disabilities related to development (clinical youth) and typically developing y outh. Specific A im 1a : Personal network analysis of youth from the clinical and typically developing groups. Hypothesis. The social networks of the clinical youth will have both structural and compositional differences when compared to networks of youth f rom the typically developing group. Specific Aim 2. Determine relationship of social network variables to participation Hypothesis. Social network structures and compositions are significantly related to participation. Introduction to Methods of Person al Network Analysis Key to this investigation is the assumption that the interactions between a youth growing up with disabilities and the individuals with whom they engage constitute key contextual factors that influence behavior. The assumption that thes e factors influence

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58 network analysis (PNA). While whole network studies focus investigation on the pattern of relations amongst individuals making up a defined group su ch as a classroom or church, studies utilizing methods of PNA focus on relationships surrounding one individual. The use of PNA allows for the quantification of relationships enveloping the This quantification enables t he application o f quantitative techniques to measurement of largely intangible facets of human interaction. Using PNA to measure the structures and compositions of these human interactions yield s quantitative contextual data not otherwise obtained with the employment of less structured or detailed methods of in quiry (McCarty, Molina, Aguilar & Rota, 2007). Use of PNA enabled detailed quantitative investigation of structural and compositional Because each network member can exert varying amounts of influence on the essential as the analysis of the characteristics ( i.e. composition) of the individuals making up the network. Consider this, while each member can exert varying levels of influence on the respondent, the same members contribute equally to the structure of contributions of network members in light of individual arrangement within the network. Graph based structural metrics such as network density and centrality derived from personal network data have been shown to be meaningful to respondents in assessment of their individ ual social environment (McCarty, 2002). PNA facilitates

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59 McCart y et al., 2007). of network membe rs obtained from a questionnaire designed to elicit a listing of the network members. The size and nature of the list varies with the nature of the research. For example, in inquiry regarding social support, respondents can be asked to name a handful of pe ople with whom they discuss matters of importance, while inquiry regarding acquaintances (referred to as weak ties ) might ask for up to 60 network members (McCarty, 2002). These techniques for name generation have been successfully used in personal network studies, to include use in the 1985 General Social Survey and later versions (Knoke et al., 2008). Once network members have been elicited, questions regarding characteristics of each network member are asked. Such compositional attributes of network memb ers can be summarized and used as independent or dependent variables (Knoke et al., 2008). Examples of potential compositional network variables include Proportion of the Network Made Up of K in or Average Age of Network M embers Beyond measuring the compo sition of social networks, researchers can also measure network structure. Following inquiry regarding compositional attributes of network members, systematic inquiry can be conducted as to the existence of relationships or ties between each pair of networ k members (McCarty, 2002; Knoke et al., 2008). Links between network pairs are used to construct the structure of nto network interconnections

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60 allows for the mapping of the social network. Network visualizations graphically reveal structural aspects of the network such as who are central ( i.e. well connected) and who make up social groups. The arrangement of network ties enables mathematical calculation of structural network metrics of interest. For instance, network density can be calculated from the number of existing ties proportional to the number of possible ties (or interconnections) within the network. In ass essing network structure in a personal network study, each pair of network relationship. At present, no convention exists for the number of network members elicited from either children or adult respondents; the numbers sought remain dependent on nature of the investigation. A random sampling of 20 25 network perso nal network (McCarty, Killworth & Rennell, 2007). In this study, participants were asked to generate a list of 25 network members. Because it is conceivable that acquaintances ( i.e. weak ties) can present additional opportunity for participation diversity, it was important to inquire a s to a network large en ough to include familial, close and weak ties. However, because of the exponential growth in respondent burden that results from each additional network member, the decision to inquire about 25 network members had to be balanced agai nst the age and projected cognitive capacities of the study sample being targeted. Collection of Social Network Data Network investigation bega n by asking each youth to list up to 15 people ( e.g. adults and children; kin or otherwise) who they do things w ith and or hang out with when not engaged in school mandated activities. The youth were cautioned to consider that

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61 they could only name 15 individuals (referred to as network alters ) who met the criteria and whom they felt were representative of their clos er network. This was done so as to reduce bias based on family size. Once the list of 15 network alters was generated the youth w as asked to generate the first names of people who they know and are known by both name and sight. These people were described to the youth as individuals a little further out in their circle of people. As we anticipated some youth with disabilities would have limited social networks, we ask ed those youth to list as comprehensive a group as possible We then incorporate d methods of weak tie name generation in order to bolster network size for youth with smaller or limited social networks. If the youth was unable to generate a total of 25 names from both methods of prompting ( i.e. people they do things with and people they know b y name and sight ), the social security listing of the most popular was used to prompt the youth and bolster weak tie name generation. Once 25 network members were successfully identified, data regarding m aracteristics and, (b) relationships, or ties with each other was collected ( Knoke et al., 2008). Table 3 1 summarizes questions asked during social network data collection. Questions were provided in writing as well as read aloud and then further explain ed or reiterated by the researcher when needed for the duration of social network data collection. Name generation and data collection regarding alter characteristics was conducted using researcher assisted paper and pencil modes. Often the youth in the cl inical sample, and younger youth in the typically developing group needed prompting and or redirection from the r esearcher in order to remain on task or

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62 provide clarification and re explanation of the name generation or alter characteristic criteria reques ted. Pilot network interviews conducted in preparation for this research revealed youth had notable difficulty with attention to data collection when alter characteristics and relational tie data were collected simultaneously via computer. Table 3 1. Soc ial network questions Category Questions Questions used to generate names of network members 1. Thinking about your family, relatives, friends, coaches or therapists, please give me up to 15 names of people you do thing with or hang out with outside of your required school activities. These people can be children, teens or adults, and they can be related to you or not. 2. Now give me t he names of some people who you know, and they names. 3. (If unab you of a person who you can include in your network, then just Inquiry as to each net work characteristics 1. relationships, age, sibling affiliations, & how well the youth knows each network member 2. type of supp or t; (a) do things or hang out, (b ) youth helps or takes care of, (c ) sometim es friend, sometimes nemesis, (d) share feelings & secrets, (e ) helps youth know when he/she has done something well or needs to b e done better or differently, (f ) gives informati on or advice regarding t hings that are difficult, and (g ) advocates for the youth. Alter tie questions Do __ & ___ have a connection (even when you are not around)? For example, do they talk, do things, or hang out when you are not with them? Are they connected in some way? Once name generation and alter characteristics were obtained via paper and pencil methods c ollection of information regarding network ties to others in the network was conducted on computer Egonet (version 2012 05 18), a java based

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63 shareware program, was used to collect alter tie data. Systematic alter tie questions were asked via computer with the researcher sitting alongside to answer questions and facilitate attention to task. Every combination of ties between each pers on in the network was asked about. This resulted in a total of 300 alter tie questions that are monotonous in nature. Via Egonet, a lter tie data was then used to generate a graphical network map and calculate structural network metrics based on the pattern of alter ties. Immediately upon completion of the 300 alter tie questions, the respondent, and network visualization onses to the visualization were audio recorded. Respondents were then asked to carefully review the visualization for accuracy and validation that the visualization indeed represented their network. Visualizations shared with the youth contained node label s (i.e. names) to facilitate orientation to the network graphic. No respondent noted errors at this point of the network validation interview. However, as the youth talked about specific nodes and structures of their network, relational tie errors were not ed if present. The researcher, under direction of the respondent, corrected errors after which network visualization and structural network metrics were re calculated. Social Network Visualizations Network visualizations, generated by Egonet, are presented for all participants in the Appendix. While these network visualizations only allow for visual analysis, graphical representation of the networks provided an additional layer of understanding ascending age order with clinical youth on the left and youth from the comparison group on the right.

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64 Because of the small sample size, diagnostic, age and gender information is not provided so as Information reg responsiveness) scores is provided in the captions for each network. Information scores are indicative of mo Higher SRS scores are indicative of more problems with social functioning. The point are clinically significant for social concerns. Youth with higher SRS scores may be more socially awkward. When reading the network visu alizations, mothers are denoted in pink, fathers in blue, and siblings in yellow. A circle, or node, denotes each network alter. The size and other words, the largest and darkest nodes belong to the network members with the greatest number of connections to others in the network (highest degree centrality ). The lines connecting the nodes represent a connection between the individuals. The strength of each connection is not depicted in the visualizations. Social Network Variables Several network variables were assessed in this study and are detailed in the following sections. Network composition refers to compositional attributes of the network members such as age and ki nship. This study had 6 compositional network variables.

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65 Network structure refers to the arrangement of the patterns of relationships or ties with in the network. This study had 5 structural network variables. Additionally, this study used 8 network variabl es related to social support. Basic c ompositional network variables are described first followed by description of structural variables Network variables regarding supportive attributes of the network are grouped together and presented last. Network Vari ables Related to Composition Compositional network vari ables afford easily understood descriptions of the who and what types of people make up a network. Compositional network variables used in this study included: Number of Same Gender: Number of alters who share the same gender as the youth Number of Kin: Number of alters related to the youth by blood or marriage Number of Grown ups: Number of alters considered by the youth to be a grown up Number o f Peers: Number of alters who are neither kin nor grown ups Number of Weak Ties: Number of alters reported by the youth to know a little or just know who he/she is Average Strength of Tie: Mean rating of how well the respondent knows each network member as rated on a four point scale Network Variables Related to Structure Variables related to the structure of the network are ones that could not be calculated without first determining the pattern of relational ties amongst members of the network. Structural variables are included in this study because it is believed that beyond whom and what types of people surround youth with disabilities, the patterns of relationships amongst those in the network are also important to consider.

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66 Density Network density prov ides a gross measure of the net measuring number of ties within a network relative to all possib le ties (Hanneman et al. 2005). N etwork s w ith higher overall number of ties are representative of more closely knit group s of per sonal network members We calculated network density by (the maximum number of ties possible in a network of 25 alters). Centrality Network centrality refers to social power that comes about as a result of the individual occupying an advantageous position in the network (Hanneman et al., 2005). Central network members are important targets of intervention when addressing (a) social issues s uch as bullying (Neal, 2010), (b) health issues such as interruption of contagion (Christakis & Fowler, 2010) and (c) adolescent tobacco cessation ( Valente Hoffman, Ritt Olson, Lichtman, & Johnson 2003) Degree centrality was assessed in this study Degree centrality refers to the number of direct connections a person has to others in the network (Freeman, 1979). from being high degree centrality have several connect ions within the network The degree centrality of sub groups of the network, to include siblings and supportive network sub groups, were also assessed. Operating definitions of structural variables Structural network variables used in this study include: D ensity: Number of existing network ties compared to number of total possible ties ; sum total of the raw degree centrality divided by 300

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67 Average Number of Ties: Average number of ties amongst all network members; mean raw degree centrality Number of Ties o f Most Central: The highest number of connections or ties for any one individual in the network; highest calculated raw degree centrality onnections to others in the network; mean degree centrality of all siblings Average Number of Ties in Support Network: For all network members providing at least one type of support, an average of the number of connections to others in the network; mean de gree centrality of all supportive alters Network Variables Related to Support Social support is a function of the social network. Compositional network variables also incorporated into this study include those related to developmental and social support pr network was also assessed. In this study, distinctions were made between developmental supports and social supports Conceptualizations regarding the type of supports are discussed next. This is followed by discussion regarding the range of supports, after which a listing of network variables related to support is provided. Developmental support Network members who serve various social roles are viewed to support the g part of the social arena in which the youth attains social skill and mastery. Participants were asked about developmentally supportive social roles of each network member. Specifically, youth were systematically asked which network members the youth (a ) hang/horse around with/do things with, (b) helps (is aided or taken care of by the youth), (c) is sometimes friend, sometimes nemesis/rival with, and (d) is able to confide in. Th e social roles asked about are believed to hav e positive effects on the youth s social cognitive development (Oswald, Krappmann,

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68 Uhlendorff, & Weiss, 1994). They are referred to as developmental supports throughout this dissertation. Social support Social support refers to support afforded by members of the network and used by th e youth to assist with coping or during times of difficulty. While social support is often primarily thought of as the type of emotional support used to help someone feel better, social support also includes the types of social assistance gained by individ uals w ho offer appraisal, information and instrumental assistance (Tardy, 1985). Appraisa l support refers to behaviors that communicate judgments that are useful for self evaluation, such as praise offered for a job well done. Information support involves the transmission of information or advice that is helpful in coping with difficulties. Instrumental support refers to tangible or practical kinds of assistance such as taking out the trash or providing a loan. Emotional support refers to the provision of p sychological needs such as love, trust, empathy, and belonging. Also important for individuals with disabilities are those who offer advocacy Advocacy support refers to supportive behaviors conducted on the behalf of the youth with disabilities. This can participate in activities. We inquired as to the provision of appraisal, information, instrumental, and advocacy support provided by each network member. Multiplexity M ultiplexity of support refers to the range of support offered. For instance, a support network consisting of only emotional support is likely to be lacking in ability or means ( e.g. time, know how) to actually get the youth out into the community and parti cipating in a wide variety of activities. This type of emotionally supportive network

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69 multiplexity of developmental and social support offered by (a) each network member ( b) key network members [ e. g. structurally central members] a nd (c) the network as a whole was assessed. Operating definitions of network variables related to support Network variables related to support include: Size of Support Network: Number of networ k members providing three or more types of support Multiplexity of Support From Top 3 Central: Number of types of support provided by the three alters with the highest number of connections to others in the network Developmental Support From Network: Total number of developmental supports provided by the network in relationship to (divided by) the total possible number of developmental supports Social Support From Network: Total number of social supports provided by the network in relationship to (divided b y) the total possible number of social supports Developmental Support From Most Central: Total number of developmental supports provided by network alter(s) with highest number of ties to others in the network (highest raw degree centrality) in relationshi p to (divided by) the total possible number of developmental supports Social Support From Most Central: Total number of social supports provided by network alter(s) with highest number of ties to others in the network (highest raw degree centrality) in rel ationship to (divided by) the total possible number of social supports Multiplexity of Support From Most Central: Total number of developmental and social supports provided by network alter(s) with highest number of ties to others in the network (highest r aw degree centrality) in relationship to (divided by) the total possible number of developmental and social supports

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70 Experiment 1: Describing Networks and Testing Compositional and Structural Differences Once network variables were calculated for all stud y participants, each variable was explored for distribution and the presence of outliers. Before testing with t tests, assumptions were tested for every combination of the network variable and the clinical/comparison group. Distributions were assessed by S hapiro p < .05) and confirmed with visual inspection of histograms and Normal Q Q plots. Boxplots were used to assess the presence of outliers. No outliers were observed for any normally distributed network variable. Independent samples t test s were used to compare groups for all normally distributed network variables; otherwise Mann Whitney U tests were used. All normally distributed variables met assumption requirements of equal variance d was calculated to measure effect size of normally distributed continuous network variables. Otherwise, correlation coefficients were calculated to measure effect sizes for group differences tested by non parametric statistics. Results of group comparisons are provided in the next sections; information is sorted by the 3 categories of network variables used in this study. Network variables were categorized as compositional structural, and network support variables Analysis of Composi tional Network Variables Five of 6 compositional network variables were compared using independent samples t tests. The 6 th compositional variable, Average Strength of Tie, was not normally distributed and therefore was tested for group differences using M ann Whitney U tests. Outliers were identified in the comparison group for the variables

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71 Number Same Gender and Number of Peers. However, since the outliers were not extreme outliers (greater than three box lengths from edge of box) no transformations were made and t tests were calculated with all recorded values. Table 3 2 presents results from analyses of compositional network variables. Table 3 2. Compositional network variables for youth in clinical and comparison groups Compositional network variables Youth with disability ( n = 19)* Typically developing youth ( n = 17)* Group differences ( p < .05) Effect size Number of Same Gender 14.3 3.1 Min = 6, Max = 20 16.5 3.1 Min = 11, Max = 23 t (34) = 2.01 p = .053 d = .67 Number of Kin 7.7 2.5 Min = 3, M ax = 11 6.1 2.1 Min = 3, Max = 10 t (34) = 2.02 p = .051 d = .67 Number of G rown ups 9.0 2.7 Min = 2, Max = 17 6 .0 2.7 Min = 2, Max = 11 { t (34) = 2.25 } { p = .03 } d = .75 Number of P eers 13.2 5.1 Min = 6, Max = 20 16.4 2.3 Min = 13, Max = 21 { t ( 34) = 2.35 } { p = .03 } d = .78 Number of Weak Ties 5.1 3.6 Min = 0, Max = 13 6.7 4.3 Min = 0, Max = 15 t (34) = 1.27 p = .21 d = .42 Average Strength of Tie Mdn = 2.2 Min = 1.3, Max = 2.8 Mdn = 2.1 Min = 1.3, Max = 2.6 U = 133.5 p = .37 r = .15 *Da ta are Mean, SD unless otherwise reported When comparing youth in the clinical and typically developing groups, statistically significant differences were found in the number of grown ups named in the networks. The two groups also had statistically signifi cant differences in the number of unrelated youth (peers) named in the networks. Youth in the clinical group had fewer peers and more adults in their network. In addition, differences approached statistical significance for the number of network members wh o are the same gender ( p = .053), as well as for the number of kin in the network ( p = .051).

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72 Analysis of Structural Network Variables In comparing the clinical and typically developing groups, no statistically significant differences were found in the st Table 3 3 presents results from analyses of structural network variables. Table 3 3. Structural network variables for youth in clinical and comparison groups Structural network variable Youth with disability ( n = 19)* Typi cally developing youth ( n = 17)* Group differences ( p < .05) Effect size Density 55.6 21.9 Min = 14.7 Max = 88.0 62.3 17.6 Min = 38.7 Max = 94.0 t (34) = .990 p = .33 d = 33 Average Number of Ties Mdn = 6.3 Min = 1.8 Max = 10.6 Mdn = 7.3 Min = 4. 4 Max = 11.3 U = 186.5 p = .43 r = .13 Number of Ties of Most Central 14.6 4.1 Min = 4.0 Max = 20.0 14.7 2.8 Min = 11.0 Max = 19.0 t (34) = .058 p = 95 d = .02 Average Number of Ties for All Siblings* Mdn = 10.5 Min = 6.0 Max = 19.0 Mdn = 9.0 Min = 5.0 Max = 19.0 U = 118.0 p = .52 r = .09 Average Number of Ties in Support Network Mdn = 7.4 Min = 2.4 Max = 13.3 Mdn = 8.2 Min = 5.3 Max = 13.3 U = 193.5 p = .31 r = .17 *Data are Mean, SD unless otherwise reported *For youth with disability, n = 16 A secondary structural variable (Relationship of Most Central) was calculated for descriptive purposes only and was not tested for association to participation. The most central person was a family member for 9 (47.4%) youth in the clinical group and 8 (47.1%) in the comparison group. exact test was used to compare groups with no significant differences ( p = 1.00) found with regard to youth having a sibling occupy the most central or connected position in the network.

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73 Analysis of Network Support Variables No differences were found for the two groups with regard to support provided by either the network as a whole, or from the most centrally connected (degree centrality) individuals in the network. Table 3 4 presents analyses of developmental and social support variables. Table 3 4. Network support variables for youth in clinical and comparison groups Network support variables Youth with disability ( n = 19)* Typically developing youth ( n = 17)* Group differences ( p < .05) Effect size Size of sup port network Mdn = 12.3 Min = 6.0 Max = 19.0 Mdn = 9.8 Min = 5.0 Max = 24.0 U = 142.0 p = .53 r = .08 Multiplexity of Support F rom Top 3 Central 13.4 3.9 Min = 6.0 Max = 19.0 13.4 3.6 Min = 7.0 Max = 18.0 t (34) = .035 p = 97 d = .01 Developmental Support F rom Network 34.1 7.8 Min = 22.0 Max = 46.0 35.4 9.0 Min = 22.0 Max = 55.0 t (34) = .487 p = 63 d = 16 Social Support From Network Mdn = 34.7 Min = 20.0 Max = 73.3 Mdn = 30.7 Min = 16.0 Max = 80.0 U = 126.0 p = .26 r = .19 Developmenta l Support From Most Central Mdn = 57.1 Min = 0.0 Max = 100.0 Mdn = 68.9 Min = 25.0 Max = 88.0 U = 171.5 p = .75 r = .05 Social Support From Most Central Mdn = 83.3 Min = 0.0 Max = 100.0 Mdn = 58.3 Min = 0.0 Max = 100.0 U = 138.0 p = .44 r = .13 Multip lexity of Support From Most Central Mdn = 64.3 Min = 0.0 Max = 100.0 Mdn = 64.3 Min = 14.0 Max = 86.0 U = 152.0 p = .76 r = .06 *Data are Mean, SD unless otherwise reported

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74 Summary of Experiment 1: Differences in Network Composition, Structure and Sup port both structural and compositional differences when compared networks of typically lly significant group differences were found for two compositional variables only, with two additional compositional network variables approaching statistical significance. No significant group differences were found regarding network structure or network support. Table 3 5 provides a brief overview of group differences for notable network variables. Table 3 5. Overview of group differences for network variables Network variable Group difference ( p < .05) Number of Same Gender p = .053 Number of Kin p = .051 Number of Grown ups p = .03 Number of Peers p = .03 Experiment 2: Relationship of Social Network to Participation Statistical Procedures Used for Testing Correlations We hypothesized that both network composition and network structure would be related to participation. This research entailed the testing of multiple correlations, which increased likelihood of observation of statistically significant correlations brought about by the testing of multiple correlations In order to address the inc reased potential for Type 1 error, we chose to use less robust non parametric statistics, and to set statistical significance at the more conservative p value of less than 0.01. All combinations of network and participation variables were tested for assoc iation using non

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75 coefficients were calculated. Afterwards, scatter plots were inspected for all combinations of significant correlations. When statistically significant correlations were identi fied for the study sample ( N = 36), correlations were further tested for each group. This was done so as to ascertain the strength of association for the clinical group. It was felt that knowledge regarding strong correlations for the clinical group might assist in drawing conclusions that might be used to guide development of testable interventions. Results of Correlation Analyses of Network Variables and Participation Dimensions Of the 19 network variables tested, 4 variables had significant associations to participation. Of these 4 network variables, 3 were compositional variables and 1 was a structural variable. No significant relationships were observed for network support variables. However, additional relationships were observed when the threshold of significance was dropped to p < .05. Observations at this level are reported only for the purpose of contributing to analysis of any trends in relationships that may exist. Table 3 6 summarizes relationships observed. Compositional network variables of Num ber of Peers and Number of Same Gender had positive associations with CAPE scores regarding participation Intensity and With Whom. Higher numbers of peers and same gender alters corresponded with more frequent activity engagement, and activity engagement o ccurring less often alone or with family. Number of Kin was negatively associated with CAPE scores for Intensity, With Whom and Where. Higher numbers of kin in the network corresponded with less frequent activity engagement and more activity engagement alo ne or with family number of grown ups in the network, the number of weak ties in the network (the

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76 number of people the youth only knows a little or by name and sight ) and the average strength of tie (how well the youth knows people on the network) within the network. Table 3 6. Overview of relationships of social network variables to participation dimensions of Diversity, Intensity, With Whom and Where Participatio n dimension Network variable Diversity Intensity Whom Where Number of Same Gender ns positive, ( p < .01) ns ns Number of Kin ns negative, ( p < .01) negative, ( p < .01) negative, ( p < .01) Number of Grown Ups ns ns ns ns Number of Peers ns ns p ositive, ( p < .01) positive, ( p < .05) Number of Weak Ties ns ns ns ns Average Strength of Tie ns ns ns ns Density ns ns ns ns Average Number of Ties ns positive, ( p < .05) ns ns Number of Ties of Most Central ns ns ns negative, ( p < .01) Averag e Number of Ties of All Siblings ns ns ns ns Average Number of Ties of Support Network ns ns ns ns Size of Support Network ns positive, ( p < .05) ns ns Multiplexity of Support from Top 3 Central ns ns ns ns Developmental Support f rom Network ns ns ns ns Social Support from Network ns positive, ( p < .05) ns ns Developmental Support from Most Central ns positive, ( p < .05) ns ns Social Support from Most Central ns ns ns ns Multiplexity of Support from Most C entral ns ns ns ns ns = not significant

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77 Only one structural network variable was observed to have a significant relationship to participation. The level of connectedness (Number of Ties) of the most k had strong associations with where activity occurs. The more connections the most central person had, the more significant relationships to participation were observed for n etwork support variables. Additionally, no significant network relationships were found for CAPE Diversity scores. Correlation and Regression Analyses of Network Variables and Participation Dimensions by Activity Type In order to better understand network relationships to participation, participation variables were assessed in greater detail. Relationships were not only examined with regard to the activity dimensions of Diversity, Intensity, With Whom and Where as presented previously in Table 3 6. Rather, each of these activity dimensions was further broken down into Overall activities, activities that fall into the Informal domain, and Recreational, Physical, and Social activity types. For example, the participation dimension of Intensity (the frequency a ctivities are engaged in) was further broken down into five separate participation variables of (a) Overall Intensity, (b) Informal Intensity, (c) Recreational Intensity, (d) Physical Intensity, and (e) Social Intensity. For all significant and notable co rrelations between network variables and more detailed participation variables, simple linear regressions were calculated to predict priori sample size calculations for regression using one predictor variable indicated that a minimum sample size of 35 participa nts was needed to detect medium to large effects ( R 2 at a probability level of p < .05 with a statistical power level of at least 0.8. Assumptions

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78 necessary for calculating linear regressions were checked for all linear regressions reported in this dissertation. Independence of errors (residuals) was confirmed by the Durbin Watson statistic for all regressions. All variables used in the regression calculations were free of severe outliers (cases with standardized residuals 3). Homoscedasticity was visually assessed using scatter plot inspection for c onstant spread of the observed residuals plotted against predicted values of the residuals. All regression calculations reported met all assumptions necessary for the calculation. Significance was set at p < .05 for regression calculations. In the next sec tions, correlation statistics are presented followed by calculations for linear regressions for all statistically significant correlations. Results of correlation and regression analyses are organized by type of network variable (e.g. compositional, struct ural, support). Results of correlation and linear regression calculations for compositional network variables are presented first, followed by results for structural network variables, and then finally network support variables. Network Composition and Pa rticipation Correlations for Compositional Network Variables and Participation The frequency with which youth engaged in social activity (Social Intensity) was positively related to number of network members who were the same gender. The more people in the network that were the same gender, the more often the youth engaged in social activities. How often youth engaged in spontaneous types of activities (Informal Intensity) and physical activities (Physical Intensity) was negatively related to Number of Kin. The more kin in the network, the less often youth engaged in spontaneous (Informal Intensity) and physical activities (Physical Intensity). Number of Kin was also strongly related to whom the youth engaged with during social activities (Social With

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79 Whom), and where general and spontaneous activities occurred (Overall Where and and spontaneous activities occurred (Physical Intensity and Informal Intensity), and the more ofte n social activities occur with family (Social With Whom). More kin also meant Where and Informal Where). Notably, associations for Number of Kin and Overall Intensity approa ched statistical significance. Details of correlation statistics for compositional variables are presented on Table 3 8. Linear Regressions for Compositional Network Variables Simple linear regressions were calculated for all compositional network variable s with significant correlations. Regression was also calculated for the association that ap proached statistical significance Based on power calculations for simple linear regressions, only statistically significant regression equations with R 2 eported as predictive. Number of Same Gender predicted Social Intensity CAPE scores. Each additional alter who was the same gender as the youth resulted in a 0.083 increase of Social Intensity score, indicating more frequent engagement in social activitie s. Number of Kin was found to predict CAPE scores for Social With Whom, Social Where, Overall Where and Informal Where. Increased number of kin predicted lower With Whom and Where CAPE scores. Lower Where and lower Social With Whom scores correspond to mor occurring with family. Number of Peers also predicted Social With Whom scores, which increased 0.05 with each additional network member who was a peer (neither related to t he youth nor a grown up). Higher With Whom scores correspond to greater amounts of

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80 social activities occurring with unrelated individuals. This regression was calculated with removal of one case whose observed residual was greater than 3 for the observed CAPE score (Social With Whom). Regression statistics are presented on Table 3 7. Table 3 7. Regression calculations based on network composition variables CAPE Variable Regression statistics Prediction equation Social Intensity F (1,34) = 7.94 p = .008 R 2 = .19 2.247 + .083 (Number of Same Gender) Social With Whom F (1,34) = 12.184 p = .001 R 2 = .26 3.407 .099 (Number of Kin) Overall Where F (1,34) = 9.999 p = .003 R 2 = .23 3.532 .081 (Number of Kin) Informal Where F (1,34) = 10.337 p = .003 R 2 = .23 3.416 .089 (Number of Kin) Recreational Where F (1,34) = 10.337 p = .003 R 2 = .23 3.416 .089 (Number of Kin) Social With Whom F (1,33) = 11.63 p = .002 R 2 = .26 2.015 + .05 (Number of Peers)

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81 Table 3 8. Correlations for compositional network variables and participation ( p < 01) Participation variable Number of Same Gender Number of Kin Number of Peers Intensity Overall ns* rho (34) = .417 p = .011 rho (17) = .490 p = .03 rho (15) = .257 p = .32 ns Informal ns { rho (34) = .481 p = .003 } rho (17) = .491 p = .03 rho (15) = .385 p = .13 ns Recreational ns n s ns Physical ns { rho (34) = .484 p = .003 } rho (17) = .476 p = .04 rho (15) = .315 p = .22 ns Social { rho (34) = .447 p = .006 } rho (17) = .47 8 p = .04 rho (15) = .345 p = .18 ns ns With Whom Social ns { rho (34) = .508 p = .002 } rho (17) = .502 p = .03 rho (15) = .306 p = .23 { rho (34) = .440 p = .007 } rho (17) = .320 p = .18 rho (15) = .134 p = .61 Where Overall ns { rho (34 ) = .520 p = .001 } rho (17) = .432 p = .07 rho (17) = .376 p = .14 ns Informal ns { rho (34) = .520 p = .001 } rho (17) = .392 p = .10 rho (17) = .427 p = .09 rho (34) = .369 p = .027 rho (17) = .413 p = .08 rho (15) = .162 p = .54 Recreational ns Ns ns Physical ns Ns ns Social ns { rho (34) = .524 p = .001 } rho (17) = .421 p = .07 rho (17) = .577 p =.015 ns ns = not significant

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82 Network Structure and Participation: Correlations and Linear Regression For youth in the siblings (Average Number of Ties for All Siblings) was strongly associated with how often they engage in recreational activities (Recreational Intensity) as well as activities in general (Overall Intensity). The more connections the siblings had, the more often the youth in the comparison group engaged in these activities. This relationship was not observed for youth in the clinical group; nor was it observed for the sample as a whole. The location of where recreational activity occurs (Recreational Where) was strongly associated with the degree of connectedness of the most central person in the network ( Number of Ties of Most Central). When the most connected network members were highly connected t o others in the network, youth were more likely to engage in 9 details correlation analyses for the structural network variables and participation. Table 3 9 Correlations for structural network variable s and participation ( p < .01) Participation Intensity Average Number of Ties for All Siblings (n = 33) Participation Where Number of Ties of Most Central Overall rho (31) = .401 p = .02 rho (14 ) = .185 p = .49 { rho (15 ) = .657 p = .004 } Over all ns* Informal rho (31) = .395 p = .023 rho (14) = .013 p = .96 { rho (15) = .605 p = .01 } Informal ns Recreational rho (31) = .387 p = .03 rho (14) = .254 p = .34 { rho (15) = .671 p = .003 } Recreational { rho (34) = .475 p = .003 } rho (17) = .394 p = .10 { rho (15) = .62 p = .007 } Physical ns Physical ns Social ns Social ns Clinical group; Comparison group; ns = not significant

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83 A simple linear regression was calculated to predict CAPE Recreational Where scores based on Number of Ties of Most Central. A significant regression equation was found predicting Recreational Where ( F (1,34) = 8.161, p = .007, R 2 =.19). Predicted Recreational Where is equal to 3.088 .072 (Number of ties of most central). For youth in the sam ple, Recreational Where scores decreased 0.072 with each additional connection the most central (connected) individual had to others in the network. Lower Recreational Where scores correspond to more recreational activities occurring at home or at a relati Network Support and Participation: Correlations and Linear Regressions No statistically significant relationships were found for network support variables and participation. However, several weak relationships ( p < .05 but p > 01) were observed and are reported. In general, having greater numbers of network members that offered developmental and or social support was weakly linked to more frequent activity engagement (Overall Intensity, Informal Intensity, and Physical Intensity). The relationsh ip between Size of Support Network and Physical Intensity approached statistical significance ( p = .011) for the clinical group. Networks offering more social support (Social Support From Network) were weakly linked to more frequent activity engagement (Ov erall Intensity, Informal Intensity, and Recreational Intensity) for the entire study sample and the comparison group. However, for the clinical group and the sample as a whole, higher Developmental Support From Most Central had weak associations with grea ter amounts of social activity (Social Intensity). Table 3 10 details the notable relationships ( p < .05 but p found for Network Support and participation.

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84 No statistically significant regression equations were observed with an R 2 greater than 0.19 for network support variables. Network support variables could not be used to predict CAPE participation scores for this study sample. Summary of Experiment 2: Relationship of Social Network to Participation The primary correlation hypothesis, that both n etwork composition and structure have significant relationships to participation, was supported by the series of correlation analyses conducted in this study. Both compositional and structural network variables predicted CAPE Where scores, with only compos itional network variables predicting Intensity and With Whom scores. No statistically significant relationships were found for network support variables and participation.

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85 Table 3 10. Correlations for network support variables and participation ( p < .0 1) Participation Intensity Size of Support Network Social Support From the Network Developmental Support From Most Central Overall rho (34) = .376 p = .02 rho (17) = .326 p = .17 rho (15) = .512 p = .04 rho (34) = .356 p = .03 rho (17) = .2 90 p = .23 rho (15) = .506 p = .04 ns Informal rho (34) = .349 p = .04 rho (17) = .298 p = .22 rho (15) = .455 p = .07 rho (34) = .357 p = .03 rho (17) = .300 p = .21 rho (15) = .498 p = .04 ns Recreational ns rho (34) = .387 p = .0 2 rho (17) = .321 p = .18 rho (15) = .516 p = .03 ns Physical rho (34) = .352 p = .04 rho (17) = .570 p = .011** rho (15) = .354 p = .16 ns ns Social n s ns rho (34) = .382 p = .02 rho (17) = 538 p = .02 rho (15) = 257 p = .32 *Notable relationship of p < .05 but p **Approaches statistical significance of p < .01

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86 CHAPTER 4 EXPERIENCES AND PERCEPTIONS OF SOCIAL NETWORKS This chapter begins with a more in depth introduction to qualitative methods. This is followed by a description of the interview procedures and findings from the cognitive interview conducted with the youth in the clinical group. Interview findings correspond to Specific aim 1b and its related research question. Specific Aim 1. Identification and desc ription of aspects of the social network for youth growing up with cognitive disabilities related to development (clinical youth) and typically developing youth. Specific Aim 1b: Explore social network experiences and understanding of youth in the clinica l group through cognitive interview. Research question: How do the youth with disability understand and experience their social networks? Introduction to Qualitative Inquiry Qualitative inquiry involves the naturalistic and systematic collection and analys is of data obtained from the observable world. It seeks to achieve explanation with a goal of discovering understanding of the complexities of social conditions and processes Qualitative data collection involves spending time with participa nts, interactin g with them interviewing and observing. The inductive nature of qualitative analysis necessitates an iterative process of data collection that enables the researcher to pursue emergent salient concepts generated by study participants This process facilit ates the development of robust conceptualizations (Charmaz, 2006). Qualitative analysis involves more than cataloging or enumerating qualitative data (Sandelowski & Barroso, 2003). Rather, qualitative analysis involves a process of qualifying or interpret ing the data whereby the words of the respondents are systematically broken down into smaller more manageable parts ( i.e. coded),

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87 synthesized and then observed for the presence of patterns or themes (Boeije, 2010). Through this process of reducing and synt hesizing the data abstractions of core concepts are discovered. Sandelowski and colleagues (2003) put forth a continuum of data analysis representing the degree of abstraction conducted in qualitative analysis (Figure 4 1 ; adapted from Sandelowski et al. 2003 [ Page 908 Figure 1] ). Their continuum was used to analysis as a thematic description where illumination of the experiences of the youth was the goal of the qualitative analysis. A nalysis used in thematic descriptio n incorporates concepts developed in situ from the data. At this level, themes used to organize the data come f rom existing literature or remain at the level of everyday language but have been used to reframe a phenomena, event or case ( Sandelowski et al. 2003 ). The qualitative analysis used in this study focused on discoveri ng and detailing the subtleties and nuances of patterns within the social perceptions and experiences of youth in the clinical sample. Figure 4 ) continuum of qualitative analysis

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88 Qualitative Methods When conducting qualitative research, it is important to acknowledge the personal lenses of the researchers and how these lenses impact the research process (Patton, 2002). The pri ncipal investigator (PI) has both personal and professional experience with cognitive disabilities related to development. The PI is a health professional trained in working with youth and families with hidden disabilities and is accustomed to advocating f or them. All primary interviews with youth in the clinical group were conducted by the PI who had professional experience in dealing with individuals with emotional and or arousal state regulation difficulties. This clinical expertise, combined with the le vel of trust afforded to the researcher based on professional training, enabled candid inquiry into what were at times unpleasant social experiences for the young participants. insider role of the researcher the PI was careful to gather data as recommended by Asselin (2003). Data was experiences of those being studied. The insider vantage of the PI was balanced by the outsider vantage of the research assistant. The research assistant was present for most data collection and involved in all stages of qualitative data analysis. Qualitative Data Collection Following completion of all quantitative data collection and validation of network visualization, youth in the clinical group participated in a semi structured cognitive interview. The timing of the cognitive interview gave study researchers the opportunity to build rapport with the youth through engagement in playful activities such as jumping,

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89 catching and other coordination tasks. Additionally, the process of social network data collection afforded opportunity for the youth to talk to the researcher about the people in his or her world. The timing and setting of the qualitative data c ollection added to the level of trust afforded to the researcher. As in quantitative data collection, interviews were also conducted in a private and comfortable setting. These factors contributed to the level of trust afforded study researchers during the interviews. Resultantly, the tone of the interviews was collaborative and participants were at ease when discussing their social network experiences. Table 4 1. Guiding questions and probes for cognitive interview from the perspective of youth with disabilities. Table 4 1 details interview que stions Questions & Probes 1. Tell me about ___ (p eople in various network positions; groups) 2. What are your experiences with ___ (person; group)? What sorts of things do you do with ____? Who decides what you do? What happens when you want to do something different? 3. nnected, acts like a bridge between groups, is all alone). What are your experiences with ____ (person) ? How would you describe ___ (person) How does he interact with others in the network? How about with others not pictured your network? What sorts of t hings does this person do with those around him? 4. (If applicable) What are your experiences with (network member known through sibling) ? What are your experiences with your siblings other friends? Why do you like/prefer to hang out with ____? 5. (If no t yet already answered) Tell me about how you met and became close with your closest friend(s)

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90 structural network metrics were used to individualize the interview. An example of the k member group experiences (i.e. integration into the network). Questions on the interview guide only served as an initial guide. As respondents brought up topics sa lient to their social network experiences, the researcher followed topics on interviews with subsequent participants. The iterative process of data collection, analysis an d then modifications to what was being asked allowed study researchers to use emergent understandings in the collection of subsequent qualitative data. This process of dynamic data collection and analysis enabled the researchers to refine their thinking ba sed on findings from earlier interviews. It enabled pursuit of salient concepts generated by study participants, which contributed to the robustness of themes developed (Charmaz, 2006 ). Analysis of Qualitative Interview Data This study utili ze d exploratory thematic analysis The analytic goal was to accurately depict, through descriptive themes or patterns of responses, the social network experiences of youth in the clinical group. Thematic analysis provided a means of interpretation whereby recurrent patte rns of meaning were identified through an iterative process of de contextualization and re contextualization of the textual data (Boyatzis, 1998). The p rocess of data analysis involved systematically searc hing, segmenting, and arranging and rearranging the interview transcripts, field notes, and

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91 words. Strategies for Enhancing Trustworthiness of Findings Multiple strategies were utilized to enhance trustworthiness of findin gs. All interviews were audio recorded, transcribed verbatim and checked for accuracy. Field notes were used to record immediate impressions following interviews and analytic memos were recorded to note and refine emergent conceptualizations. Interviews we re initially read as a whole and sections selected for fuller examination. These interview selections, along with field notes, analytic memos and selected quotes were gathered for initial coding based on similarity and conversational meaning Using these i nitial categories, transcripts were again read and analyzed for conceptual development and supportive data for each theme was identified. Whenever feasible, two researchers were present for data collection. Analytic debriefing was used following interview completion in order to refine emerging conceptualizations and develop follow up or subsequent questions. Additionally the two researchers conducted coding independently. After independently coding, data was discussed for meaning and codes chosen. Codes we re also compared for similarity in coding and discrepancies were resolved. Strategies to enhance validity of findings also included use of frequent discussions, continuous comparison of the transcripts to developing concepts, and checking of emergent conce ptualization with others trained in qualitative inquiry. Additionally, analyzed data was brought before an outside interdisciplinary group of qualitative researchers for checking of developing ideas

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92 Overview of Qualitative Findings Two primary themes em erged from the cognitive interviews, Forming Networks and Group Engagement. The theme F orming Networks elucidates strategies used by youth in the clinical group in making new friends and expanding their networks. The th eme Group Engagement illustrates soci al negotiations used within peer interactions, difficulties with group processes, and the impact of language and communication issues on social exchanges. Forming Networks Theme Youth networks do not just happen. They are the result of multiple influences that include arbitrary classroom assignments and school zoning, parental and societal guidance as to safety oriented behaviors and what types of kids to befriend, as well as active agency on the part of the child. When initially describing formation of th eir networks, almost all youth began the discussion by using societally ascribed labels such included language communication difficulties had great difficulty expanding on the meanings of such labels, with one youth simply repeating initial responses when probed. Other youth simply provided multiple examples of social exchanges with little elaboration. Some youth were thoughtful in their responses and able to be insightful in as sessing their social network experiences. Strategies for Increasing Social Connections Several youth had developed strategies for increasing their social connectedness. Some strategies were based on well scripted social exchanges more common amongst young er children. From one 12 year old

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93 connections, the social and linguistic immaturity with which it was pursued was evident. This respondent reported: I would go to them and like just, if they were like alone I would hang out with them. If we were real, like if we were nice to each other and we liked each other the n I would ask if they would be my friend. Such exchanges are reminiscent of social scripts used by young children or interjected into therapeutic social stories used to prepare youth on the autism spectrum for upcoming social exchanges. Other strategies described by the youth to increase social connections included benevolence in befriending the new kids, youth describing this strategy were aware of the fact that having a ne circle of friends. Respondents reached out to the new kids even when the new kid was e youth proudly described a strategy recently and they [netw ork alters from another grade] just got a new girl from Social Dismissal The same youth relayed experiences indicating the slowness by which the youth had received acceptance from classmates known for several y ears. In describing alters been in the school with several of the same youth since early elementary. This respondent spoke of actively reaching out to classmates and the resultant rejection.

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94 Youth: t is like one thing I throw out there. Interviewer: So how do they respond when you throw it out there? Youth: Others Reachi ng Out In response to questions asking how groups of nodes on the network visualization came to be included in the network, some youth described experiences of their network alters reaching out to them. The follo wing is from a ninth grader who listed a gro up of 12 th graders in the network. Interviewer: What are your sort of experiences with the seniors, these guys? Youth: They just came up to me and started talking to me, especially [classmate], [the classmate] just came to me. Interviewer: And what sorts of things do you do with them? Youth: what we do. While this youth described a level of active agency in forming the network, other youth described network formation as more of a pa ssive experience. In discussing Finding Similarities Several youth described favorite friends in terms of similarities to themselves. Developmentally consistent with the age range, youth found similarities beyond shared experiences of disability. From an interview with a 13 year old:

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95 Interviewer: Youth: Interviewer: H ? Youth: since Pre K Interviewer: Well, Youth: Cause [friend] is like the nicest. Interviewer: [Friend is] the nicest; d o y ou have a lot in common with [friend] ? Youth: MmHmm. We both have some kin d of mental disord er or like [long pause] [friend] we both have like, we can understand each other. Parents also contributed to the ascription to the cultural norms associated with iagnosis. From an interview with a youth on the autism spectrum: Interviewer: So, who is your closest friend here [interviewer pointing to a section of the network visualization]? Yo uth: was in 7 th grade and I was in 5 th grade Parent: [Friend] there. It is very interesting. They are tight. Understanding Social Self Some youth were well aware of their social difficulties and or their constrained social ties. When asked what one participant would do if the participant wanted to meet From a yo uth with diagnosis of ADD: basics [regarding social skills] or else I might not functio n real well.

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96 This youth understood that the family offered connectedness and opportunity to practice social skills in larger social arenas that were judged by the youth to be safer for such practice. Other youth recognized that siblings played a role in b uilding their social how they have learned to advocate for themselves in order to tak e advantage of their bling and the brother as a source to be tapped for increasing social engagement. Some youth had insight into their social difficulties. These youth understood that parents, teachers and society expected them to be socially engage d; and that somehow they were falling short of these expectations. Some approached understanding of their social difficulties with an appreciable level of self acceptance. From a youth with a youth with ASD attributed constraints in his social network to his own social behavior. Interviewer: Now did your brothe r ever help you make new friends or meet new people? Youth: No Interviewer: How come? Youth:

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97 Applying Social Rules Respondents conveyed stories that shed light onto t heir interpretation of social rules and norms. Not surprisingly, some youth had difficulty in applying social rules. Cognitive disabilities can include impairment in attention, executive functioning, abstraction, perception and or reasoning; any of which c an impact ability to interpret and apply social rules. Use of social rules described by some youth was rigid or concrete. When this was observed, there was little to no indication that the youth had attended to nuances of the social situation, or that they had modified social rules to fit the situation. Some youth over interactions. When being asked about the people on the edges of the network that the youth did not know as well, one youth misapplication of social rules p ertaining to social intrusion served to constrain Other youth internalized social norms provided to them. Another youth described how he applied social rules in deciding not to get to o close to a group of classmat es In asking another youth about a n etwork member who was on the edge of the

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98 Interviewer: What about [peer]; he is off on his own Youth: He is good for me to like Paren t: [Peer] is more mature, his mom is a doctor and he has a more career oriented path, not girlfriend oriented. He is more di rected. I would love for [peer] In conveying concerns regarding social safety, one yo uth talked at length about the need to be wary of sexual predators and others who could bring him harm. This concept was extended to emotional hurt and social rejection. This youth talked about a need to remain emotionally vigilant. Youth: h with everything I always view things from the worst possible point of view, so that way I can give them [peers] trust but still be prepared if this [disappointment] actually happened Interviewer: To stay alert? Is it working? Youth: Yeah Parent: [Interje cting] Sometimes I wonder if it works to his detriment. Ummm like, I get that at times it keeps others out. Weighing Social Rules A few youth verbalized understanding of social norms, b ut chose to overlook the norms when a good friend did not meet socially ascribed standards. From one From a social difficulties was based on comprehension of his own social shortcomings. has some an

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99 concrete manner. They were able to make judgments regarding the rules that allowed them to expand t heir social network. Parental Building of the Social Network Not all youth who described easy or comfortable engagement within their social networks had assisted in actively creating their network. The mother of one youth who was almost 14 years old spoke hearing how her youth had described social network experiences. During this discussion, the mother confirmed that the youth was at ease engaging and socially negotiating with members of the network. However, she reported that the network described by her youth was a network that she had basically built for him as a young became anxious at the thought of actively building a social network at school. She went on to convey stories of how her youth resisted encouragements to venture out of his comfortable social circle in order to get to know new peers. Reportedly, this youth could go multiple days in school without et social goals with her youth. The agreed upon goal was that the youth would talk to at lea st one person per day at school; t he goal was not often met. This mother felt that social anxiety when discussing the social network with the youth, this youth gave no indication of loneliness of feelings of isolation. The youth was animated and detailed in describing comfortable interactions with network alters. Another mother, in observing her high was surprised to note that her own social network looked almost iden

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100 insight gained by the mother, after which she verbalized feeling a need to assist her youth in expanding identified same aged peers who her youth could do more things wit h. This mother felt that she still needed to actively facilitate development of her high social network. Group Engagement Theme Egalitarian Peer Groups Several youth conveyed stories of being part of a peer group that used consensus in c hoosing what to do or talk about. These youth described themselves as active and autonomous participants in the group. They brought up new ideas, felt comfortable bringing up new topics, and reported that they could leave and join other groups of peers whe Youth who were part of an egalitarian group were able to describe the process of social negotiation. These youth actively engaged in the social negotiations within their groups; they were integrated member as follows: Interviewer: So what happens when someone wants to do something different? Youth: nd do the thing they want and then they [do what we] want and visa versa Interviewer: What happens when you want to do something different or talk about something different?

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101 Youth: it off Despite difficulties with language and communication inherent to his diagnoses, another youth was able to describe experiences o f compromising with peers. Interviewer: What happens when you want to hang out with the new kids? Youth: Interviewer: So does the new kid come to you? Or do you go to the new kids? Youth: We kind of like [are] kind of like a republic. Interviewer: What does that mean? Youth: sometimes Avoiding Social Negotiations Not all youth had a high a level of active agency within their peer groups. Som e youth used passive strategies in order to get along within their peer group. In responding to questions regarding what happens when the youth wished to talk about or do something different from the peer group, one youth with diagnosis of ADD responded as follows: a choice. I know that [attempting to change the This y outh actively chose to avoid social negotiations. He was also a youth who felt as if he did not have any friends at school despite his desire for peer friendships. Another youth with ASD described his strategy for avoiding social negotiations. Interviewer : What happens when they [peer group] want to talk about or do something that you are not interested in? What do you do? Youth:

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102 Interviewer: Move away, do you go to any other people? Or do you just physically m ove away? Interviewer: While his strategy was physically active, he described a strategy that was socially passive, and at times utilized social avoidance. These youth described lower level s of active involvement in their peer groups. Interactions described illustrate some of the reasons why youth with disability can be perceived as being on the periphery of their peer groups. Verbal Strategies groups, but had to work hard to do so. From a youth with ADD in discussing social t keep a conversation going for long. I In discussing interactions with a close peer, a different youth described interactions as follows: Interviewer: sometimes not. What Youth: Well, if he [friend], well I try and make him happy, but he just [trails off; long pause] Interviewer: What does that m Youth: I try and talk about something that will make him happy Interviewer: You change the subject? Youth: MmHmm [indicating yes] Interviewer: Does that work?

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103 Youth: Not really, no. These youth took on the role of social fa cilitators in order to ensure they had someone to engage with. They did this even when it was difficult or s ocially forced and awkward. The following exchange is from the same youth in discussing interactions with other classmates: Interviewer: What happen about? Youth: Interviewer: Youth: Yeah. Interviewer: What happens if you want to talk about somethin about? Youth: flaws. Interviewer: What does that mean? Youth: [it] i t makes me seem annoying. Interviewer: What makes you seem annoying? Youth: something else. social diffi culties stemmed from his habit of forcing his way into conversations. She reported that he did this with peers as well as adults. The mother felt that the youth did not know how to not be annoying during social interactions. In clinical terms, the mother i ndicated that the youth did not have an adequate set of social skills. Notably, this forthcoming with information, she misplaced pauses and had blunted intonations within

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104 h er verbal discourse, which contributed to her being p erceived as having some social awkwardness. Language Communication Issues Consistent with the diagnoses of youth in the study sample, some youth verbalized their difficulties related to language and comm unication processing. A they are usually talking about something o remain actively engaged in the social processes of their peer groups. A different youth with diagnosis of ADD described it as follows: When it came to something that we would um [pause], [friend 1] and [friend 2] would talk about it and I would just list en in and see if I, if anything made sense to me that I would like to talk about. In the moment awareness of conversational comprehension difficulties enabled this youth to use a socially appropriate strategy that helped the youth remain integrated with t he peer group. This youth simply waited until the topic changed before verbally conversation and see if it, it peaked my interests and then I would get into the conversa employed by the youth who described his insistence on making others talk about things Processing lags did not just impact interactions with peers. These social processing lags also occurred when interacting with siblings. For some youth, sibling interactions would take on undertones of exclusion for the youth with cognitive

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105 disabilities. Some sibling exclu sions were brought on or exacerbated because of the just overhearing and making commen ts when they say something odd most eac h other, like weird code names. social exci tement resulted in him being the outsider. He conveyed the story as if he were accustomed to his brother regularly engaging Communication and processing difficulties associated with cognitive impairments th eir ability to read in the moment social interactions. For others, the sheer language load was enough to take them out of social collaborations. Youth who had developed some insight into the shortcoming of their social and or communication skills were able to employ socially acceptable strategies that helped keep them from becoming socially ostracized. While some youth operated on the fringe of their social groups, others have managed to develop skill sets needed to foster socially supportive and inclusive peer groups. Summary Despite language/communication, attention and emotional regulation difficulties, all but one youth was able to actively participate in the cognitive interview. Details of the n the emergence of two primary themes, Forming Ne tworks and Group Engagement. As a whole, youth

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106 interviewed demonstrated unexpected levels of insight into their own social difficulties and resultant social strategies. Limitations in Qualitative Inquiry Th ere are several threats to validity inherent in qualitative research. In this study strategies of member checking and follow up interviews were used to clarify and build understanding of emergent concepts. Member checking is a technique used by qualitative researchers to improve the credibility, validity and transferability of study findings (Schwartz Shea, 2006). In this study, member checking involved researchers asking subsequent study participants about emergent concepts in order to check construction o f emergent meanings against the meanings ascribed by youth in the clinical sample. The use of multiple coders was employed whereby consensus was sought when developing codes and concepts. These emerging concepts were discussed regularly amongst professiona l peers and then brought before an interdisciplinary group of researchers trained in qualitative inquiry. Additionally, all like setting. These settings afforded participants a more comfortab le and natural context for discussing intimacies of their social interactions. the scope of qualitative inquiry and the extent of member checking and follow up conducted. Beca use this dissertation research was unfunded and utilized multiple analytic methods, the decision was made to limit qualitative analysis to the clinical group. Qualitative analysis was also limited to the level of thematic analysis where the goal of analysi s was to explicate detail and nuances of the social network experiences of the youth. This research met that goal. However, additional detail can be gained and

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107 nuances further explicated in future research. Future qualitative research can also incorporate experiences and perceptions of typically developing youth and compare to findings from the clinical group.

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108 CHAPTER 5 DISCUSSION Individually considered, each diagnosis included in our study (LD, ADD and ASD) is heterogenic in nature. The diagnoses of LD ADD and ASD are based on the qualitative presence of a minimum number of qualifying symptoms from a range of symptoms specified. Despite symptomatic heterogeneity, LD, ADD and ASD are neurobiological disorders related to development that affect how the b rain receives, processes and responds to information. Clinical group participants had sensorimotor difficulties. Eighty four percent of had sensory processing difficulties as measured on the AASP (sensory assessment). Sensory processing difficulties manif est as atypical behavioral responses to environmental stimulation. Within social contexts, they may react differently from peers and can have awkward physical and/or social mannerisms. Sensory processing differences can cause youth to respond to situations differently than those around them ( Parham & Mailloux, 2010 ). Motor impairments were also observed in the clinical sample. Sixty eight percent had mild coordination difficulties that placed them in the 6 25 th percentile range on the BOT 2 (motor assessm ent), and 21% had at least moderate coordination difficulties placing them below the 6 th percentile. Scores on PedsQL TM sub scales reflected the cognitive nature of impairments inherent to diagnoses of LD, ADD and ASD, as well as the high incidence of co occurring motor difficulties observed in the clinical sample. Cognitive Functioning scores were lowest of all domains with a median score of 41.7 out of 100. Physical Functioning scores were highest (but remained below the clinical cut point) with a media n score of 75 out of 100. Median Social, School and Emotional Functioning

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109 scores were 45, 50 and 60 respectively. Youth in this study sample had PedsQL TM scores indicative of clinical difficulties in all areas of functioning measured. Participation differe nces were not surprising in light of the sensorimotor difficulties (e.g. physical and sensory processing) observed in the youth from the clinical sample. Differences in Participation Results from comparison of CAPE assessment scores indicate that youth in the clinical group participate in activities with a narrower range of individuals (With Whom) and do so in a narrower range of locations (Where) than youth in the typically developing comparison group. Lower CAPE With Whom scores are indicative of proporti onally more activities being engaged in alone or with family. Lower Where home. Youth in the clinical group also engaged in fewer types of physical activities (Physical D iversity) than youth in the typically developing group, and they did so less frequently (Physical Intensity). Individual capacity (and impairment) is a significant predictor of participation levels (King et al., 2006). Because of the wide ranging impairmen ts of youth in the study sample, differences in participation were expected. Our study findings are consistent with differences in participation patterns observed by Hilton, Crouch and Israel (2008). In their study involving 52 youth with high functioning ASD and 53 typically developing youth, these researchers also used the CAPE assessment to measure and compare participation. In addition to findings of statistically lower With Whom and Where scores (similar to observations in our research), Hilton and col leagues found statistically significant differences in 8 of 9 measurements of activity Diversity, and 5 of 9 measurements of activity Intensity. Notably, they found no difference in levels of

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110 participation Enjoyment between youth with high functioning ASD and controls. This was reported for all types of activities except for more structured Formal activities, which the youth with ASD did not enjoy as well as comparison youth. The differences in participation observed in our study are also consistent with f indings reported in the literature spanning a wider range of disabilities. For youth with physical disabilities, participation is restricted and declines with increasing functional impairments (Imms, 2008). Significant direct predictors of participation ex tend beyond cultural activities (King et al., 2006). Supportive relationships for the child (e.g social support from the network) have been found to be a significant indirect predictor of participation (King et al., 2006). Greater support from close friends and meaningful adults, such as teacher and parents, is associated with stronger child pre ferences for activities, which in turn boosts activity participation (King et al., 2006). Differences have also been reported in participation patterns of children with mild motor impairments such as developmental coordination disorder (DCD). Youth with D CD have differences in home, school and community participation (Chen & Cohn, motivation to participate in both physical and social activities (Dunn & Watkins on 2002). These youth perceive themselves to be less physically and athletically, as well as less academically and socially, competent than their more coordinated peers (Rose, Larkin & Berger, 1997; Skinner & Piek, 2001). They report lower self esteem and higher anxiety (Skinner et al., 2001). Chen and Cohn (2003) suggest that perceived lack of

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111 competence can hinder motivation for activity participation, contributing to restrictions in participation. They concluded that children with DCD are at risk for reduced social par ticipation, physically based recreational participation in the community (e.g. sports clubs) and school based physical social activities (Chen et al., 2003). Notably, 84% of youth in our clinical group had motor behaviors consistent with indication of DCD. While we did not measure self esteem or anxiety, some parents of youth in the clinical sample A reduction in childhood and adolescent participation has the potential to result in f ar reaching limitations well beyond the number and range of activity engagements. Participation in meaningful activities within social contexts provides opportunity for de velopment and, in the long term enhances and imp roves health and well being ( Law, St einwender & Leclair 1998). Remediation of participation limitations of youth growing up with disabilities has the potential for gains in health and psychological well being. Differences in Social Networks Supportive networks have been linked to psycholog ical well being (Turner, 1981). Social support has been modeled using social networks since the 1980s. T he adoption of a social network paradigm has been used to focus investigation on how the flow of resources is directed to the individual in need, and ho w the composition and configuration of network ties impact the flow of supp ort and or resources ( Faber et al. 2002). In their review of t he social support literature Fa ber and Wasserman (2002) concluded that the body of evidence as a whole indicates that support networks do provide health benefits, and that these benefits can be both physical and psychological. T hese authors urged social support researchers to attend to characteristics of the social

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112 network, specifically the network character istics of conn ectivity, density and strength of tie. Social networks are a potential source of additional supports and resources. Youth with disabilities often need additional supports and resources associated with disability related impairments. This research explored network compositional and structural connections to participation, with appreciation for the potential need for additional supports to facilitate participation of youth in the clinical group. We hypothesized that the social networks of youth in the clinica l group would be different from the networks of youth in the typically developing group. Specifically, we hypothesized differences in both network composition and network structure. Only compositional differences were found in the networks of the two study groups. Youth in the clinical group had higher numbers of adults and fewer numbers of peers named in their networks. Findings of fewer peers in the networks of clinical youth are consistent with the literature regarding peer network differences for youth having a wide range of disabilities. Fewer peers have been reported for youth who are multiply impaired (Harty et al, 2007), youth with autism (Chamberlin et al., 2007), students with physical and mobility impairments (Anderson, Madill, Warren & Vargo, 199 6) and youth with vision impairments (Kef, 1997). Our hypothesis regarding structural network differences was not supported. We did not detect structural network differences using metrics derived from methods of egocentric network analysis methods (i.e. PN A). Previous research has reported structural differences in the networks surrounding individuals with disabilities using methods other than PNA. Harty and colleagues (2007) utilized a structured clinical

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113 interview tool the Social Networks Inventory, to i nspect density and size of youth with multiple disabilities. They found that the youth with disabilities had few close ties. Chamberlin, Kassari and Rotheram Fuller (2007) utilized a mixed method approach that included use of whole network analysis to inve stigate social network effects on classroom social involvement of children with ASD. They reported youth with ASD to be less centrally located within the classroom network when compared to typically developing classmates. While our study findings supporte d the hypothesis regarding differences in network composition, we did not detect differences in network support characteristics of the two groups. Developmental and social supports are generally considered important resources to be afforded young people. I t is conceivable that regardless of disability status, parents of both typically developing and chronically impaired youth work to create highly supportive environments for their children. Despite an absence of findings regarding differences in support net works, no conclusions can be made regarding require additional supports that are reflec ted in their networks (Harty et al 2007; Anderson et al., 1996). The small sample size of this study limited our ability to detect differences in variables with smaller effects. Discussion of Social Network Links to Participation Social networks are linked to multiple human activities and social phenomena. The literature on interperso nal health behavior is extensive in linking social relationships and network effects to well being, health and health behavior for a variety of populations (Heaney et al., 2002; Lewis, DeVellis & Sleath, 2003; Rimer, 2003; Wenzel, Glanz & Lerman, 2003). So cial networks and interpersonal relationships act upon people to

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114 enhance the health and development of individuals, groups, and communities through the provision of support, coping skills, emotional connection, and organization (Berkman et al., 2000; Cohen et al., 2007; Heaney et al., 2002; Litwin, 20 06). This study explored network links to the social phenomena of participation, which has also been linked to health and well being ( Law et al. 1998). It was hypothesized that social network compositions and structures would be linked to participation. This research supported the hypothesis and began to explicate the ways in which social networks are linked to participation. Compositional Network Links to Participation Compositional network variables of (a) N umber of Same Gender and (b) Number of Peers positively predicted CAPE Social Int ensity and Social With Whom scores respectively. Higher With Whom scores represent a broader range of individuals that the respondent is participating with; youth with higher Social With Whom scores engaged in social activities with proportionally more non relatives. Higher Intensity scores indicate more frequent activity engagement. As the number of same gender alters increased, so too did the frequency of social activities. Additionally, w hen youth in the study sample had higher number of peers in their networks, they engaged in social activities more frequently. Youth in the clinical sample had fewer peers, which was reflected in lower Social With Whom scores. Youth in the c linical group engaged in social activities with proportionally more kin. Notably, the number of kin in the network had strong negative correlations with Social Whom score s ; youth who named with more kin in their network engaged in social activities with p roportionally fewer non relatives. While the number of kin named in the networks of study sample youth did not differ significantly between the clinical and

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115 typically developing groups, the difference did approach statistical significance ( p = .051). The narrower range of social participation for youth in the clinical group is reflective of the number of kin. While it stands to reason that the number of kin and the number of unrelated peers may be inversely related, no conclusions can be drawn as to the network effect of being born to a large family. While we could not control for bias due to family size, this bias was addressed in the way the networks were generated. Youth were instructed t o limit close alters to 15 alters. Additionally, they were reminded that they could only choose 15 alters to represent the range of individuals they do things with or hang out with. Structural Network Links to Participation One structural network variable did have strong correlations to participation for the study sample. The Number of Ties of Most Central had strong negative correlations with CAPE Recreational Where scores. When the most connected network members were highly connected to others in the net work, youth engaged in proportionally more central individuals include parents and/or siblings, which was the case in 61 % of the sample. Notably, being related to the mo st connected person(s) on the network was not associated with disability status (refer to Analysis of Structural Network Variables section previously presented in this chapter). Network Support Links to Participation We did not find statistically signifi cant relationships for network support variables and participation with significance set to p = .01. However, correlation trends for 3 of 7

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116 network suppor t variables point to potential relationships to CAPE Intensity scores. The network support variables o f (a) Size of Support Network, (b) Social Support From the Network, and (c) Developmenta l Support From Most Central had correlation strengths ranging from rho = .35 to rho = .39 with p values > .01 but < .05 To account for the increased likelihood of cha nce observation of statistically significant correlations brought about by the testing of multiple correlations, results were analyzed for trends i n association (Motulsky, 1995). In addition, so as to guard against Type I error, the decision was made to se t the p value at the more stringent 0.01 (rather than 0.05) This decision was made despi te power analysis that indicated a sample size of 36 could detect at least moderate strength correlations ( r = .33) with a 2 tailed probability of 0.05, and large corr elations ( r = .51) with a 2 tailed probability of 0.01 Based on the extensive literature linking network social support to a range of positive health and developmental outcomes, it remains plausible that future investigations ( where sample size is increas ed and or the scope of network variables refined ) could detect the presence and nature of network support links to participation. Conceptualizing, operationalizing, and investigating the multi faceted constructs of the social environment and activity parti cipation is a complicated endeavor. This youth growing up with cognitive disabilities related to development and typically developing youth. It also begins to elucidate distinctions in relationships between nuanced aspects of the social network and activity participation. Social networks remain potential targets of intervention for desired rehabilitation outcomes. Questions persist as to which aspects of the social networ ks hold the most potential for targeting.

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117 Discussion of Qualitative Findings For youth, social network experiences are formed within the socially ascribed bounds of family, school and neighborhood. This qualitative inquiry provided insights into salient a spects of social network experiences for the youth with cognitive disabilities. Commonalities in the disability experiences of youth in the clinical group were sought through cognitive interview. This was done for the purpose of gaining detailed understand ing of social experiences and perceptions within the context of their social networks, which was found to be different from networks of typically developing youth in the comparison group. alitative portion of this study gave voice to the youth growing up with cognitive impairment. Several youth were able to clearly articulate their decision making process as they negotiated their adolescent social world. Interviewing youth with cognitive an d related language impairments posed several challenges for us. There were times that the was being asked. Multiple iterations of reworded questions were often required in or der to generate answers that responded to the question being asked. Youth in the clinical group described varying levels of active agency in developing their social networks. Surprisingly, no trends were found regarding the he level of active agency described in building their social networks. (Clinical diagnoses are sometimes conceptualized as proxies for an spoke of egalitarian interac diagnostic criterion includes reciprocal social and communication impairments, was able

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118 to form a social network where peer interactions included social compromise and negotiation (a relatively high l evel social skill involving social and communicative reciprocity). Conversely, a youth with diagnosis of LD and another with a diagnosis of ADD (neither diagnostic criterion includes social impairment) used highly scripted language in describing social int eractions and social reasoning. Scripted language involves use of specif ic verbal routines, which can be used because many social events have socially expected sequences of interactions (Fivush & Slackman, 1986). Use of scripted language is a strategy empl oyed by individuals typically considered more impaired, such as those with ASD (Hilton, 2010). Unaware of the meaning of social silences, some respondents described feeling a need to fill the void with conversation. These youth described seemingly forced social to the nuances of social interactions. Lack of attention to social nuances can contribute to instances of missed cues. These cues can convey missed messages o f social censorship or rejection, such as extended periods of group silence. These uses of forced verbalizations likely served to further ostracize the youth, rather than to integrate them into the group. The youth who described using forced conversation did not have a history of receiving formal social skills training. Social skills training explicitly addresses skills needed to dissect group interactions and interact more comfortably and appropriately within social situations (Hilton, 2010). Intervention s for social skills training are most effective when parents are highly involved in the social skills training (Benson, Karloff, Siperstein, 2008). In formal social skills training, parents play an important role in

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119 identifying key areas to address and ens uring follow through of newly learned social skills in the everyday goings on of the youth (Hilton, 2010). Unfortunately, some parents can have difficulty assisting their child in developing social skills, in part due to their own level of social skill F rom the qualitative interviews, parents described instances of actively working in our study included (a) facilitating contact with select peers, (b) encouraging the ir youth to get to know certain classmates based on characteristics of the classmate [ e.g. college bound], (c) open discussions with the youth about the need to expand the tively the strategies employed by some parents of the clinical sample appeared to be used on an almost daily basis. Expanded Understanding of Quantitative Data Fr om Qualitative Data Quantitative differences were found in the social networks of youth in the clinical group. Disability related impairments of clinical youth likely contributed to observed differences in network composition, specifically the lower number of peers in the network. Qualitative interviews shed light on the ways that performance differences, such as delayed social processing or use of immature scripted conversation, impacted I n our study, for typically developing youth in the comparison group who had strongly and positively correlated with Recreational Intensity, Informal Intensity and Overall I ntensity CAPE scores. Having siblings who interacted with more of the

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120 spontaneous activities more frequently. This effect was not observed for youth in the clinical group, despite no significant difference in the Average Number of Ties for All Siblings between the two groups. During qualitative interviews, one youth actually to self advocate in order to participate Youth in the clinical group named more kin in their networks than youth in the typically developing group; differences approached statistical significance ( p = .051). From parental responses to the cognitive inter view, it was evident that parents of youth in the clinical group valued supportive extended family. Having more kin in the network Numbers of kin in the network may be infl uenced by parental value placed on having in developing peer relationships. Quantitative findings point to the predictive power of the number of connections held by the most central individual(s) in the network. Having highly connected central individuals in the network, and having higher numbers of kin in the network, predicted CAPE participation scores indicative of some amount of constraint with regard to social /community integration (lower CAPE Where scores). Several youth in the clinical sample described valued activity engagement with family, extended family, and close family friends who functioned as extended family. They spoke of these interactions in tones indicating that they place high value of family centered interactions while speaking of peer interactions in more matter of fact tones. While supportive networks

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121 are generally understood to be beneficial, having overly supportive networks can potentially c onstrain the type of social risk taking (e.g. meeting new people, moving in network. Family heavy networks may be more comfortable networks. I n addition, youth with disab ilities were found to have more adults named in their networks. Many youth in the clinical sample described difficult and awkward social interactions. Adults and relatives may be more understanding of such social awkwardness. Qualitative data served to hu manize quantitative findings regarding social up with cognitive disabilities related to development. Differences in social participation extended beyond measures of activity engagement. Rather, fundamental differences were found in the way youth from the clinical group understood and resultantly participated within their social networks. Qualitative findings shed light on the complexities of the social and disability contexts in which these youth are growing up. Differences in social, perceptual and communication abilities inherent to the when fundamental social, perceptual and communication skills had been bolstered by everyday world. The majority of c and disability contexts. Several did so in hopes of aiding their child.

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122 Potential Clinical Utility of Methods of Social Network Analysis Both the process of SNA and the resultant network visualization served as useful network visualizations helped parents and youth organize their unde rstandings of the While a couple parents had difficulty seeing how SNA might be helpful in their everal parents found the process of social network analysis, which included review of the network visualization, to be worthwhile. A few parents indicated that the SNA helped them understand who was important to their child. were already there. We knew [the youth] had them, but seeing who [the youth] put in [the : [th he map did help me understand who he felt he was most connected to then not connect [to] or just casual acquaintances. I s interesting how he perceives the people. Other parents had not previously conceptualized the people their youth enga ged with you I never thought about it [as] a network, but it

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123 able to look at the network visualization and better articulate the nature of relationships For other went on to point out the perceived social success to her youth. In addressing her child, Several other parents took advantage of arose during the SNA and or review of the network visualization. On a return appointment for completion of data collection, one parent made a point of letting study researchers know how she followed up on topics dis cussed during the SNA conducted as part of the first meeting with researchers: [The SNA] was really useful because of the conversation we had in the car as we have and it was supportive relationships are and Youth Responses to SNA Youth in the clinical group were generally excited to see their network visualizations. They were easily engaged in discussion that basically allowed them to analyze their social world. Youth from the clinical group engaged in an average of approximately 20 minutes discussion regarding their network and network experiences. This is contrasted with the moderate to mild interest in the social network visualizations

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124 from youth in the typically dev eloping group. These youth were initially curious about their network visualizations, but for the most part, did not remain eager to analyze or describe nuances of their network. In general they described their networks using more matter of fact tones with shorter and more succinct descriptions. Many youth in this group reported that they were not surprised by their network visualizations and that the visualizations did not provide them with new insights or information regarding their social world. When des cribing their social networks and experiences from the network visualization, some youth from the clinical group spontaneously gained insight. Some even formed social interaction plans reflective of newly gained insights. In discussing the relative central how by providing the most central classmate with something, that central classmate could so quickly get many other kids involved. He then formulated a plan to initiate a food fight by supplying that c entral classmate with his excess lunch. Conclusions Regarding Clinical Use of Methods of Social Network Analysis Socia l network analysis and the resultant netwo rk visualization create a tangible active en has the potential to be a powerful mea ns of facilitating social integration beyond t he supportive family network. H owever, creating the social map/network visualization was a tedious and cumbersome process that taxed the attention of the youth in the clinical group. The cognitive and attention load involved in asking adolescents to respon d to 300 relational tie questions was more than some youth could handle well. Eight of the

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125 36 participants (22%) noted errors when asked to validate their network from the network visualization s Of the eight youth who made the errors, six (75%) were youth from the clinical group. Because the relational tie questions were at the limit of what the youth could tolerate, compositional network questions could not be asked via the network software tool (Egonet). Resultantly, powerful features of the software, su ch as the ability to graphically map adults versus peers, were not an option for use when interviewing youth in this study. Clinical application of methods of SNA will require diligent use of strategies to overcome potential barriers to accurate completio n of network questionnaires. However, as evidenced by parental and clinical youth responses, the process of SNA has the potential to be a clinically useful framework for approaching interventions targeting social integration and functioning. As put by one parent of a youth who had received potentially be used to assist the youth in deve loping strategies to use hard won social skills for effective navigation within his or her social network. The fact that the social network software is freely available to Internet users removes a potential barrier to clinical application of SNA technique s. Additionally, youth were happy to interact with the computer in responding to social network questions; the computer helped to keep the youth engaged with the network questionnaire. The youth enjoyed the immediate generation of their network visualizati on upon questionnaire completion; it was often viewed as a reward for their diligence in completing the network

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126 questionnaire. Network visualizations created a concrete framework to aid understanding of abstract relational concepts and difficult to perceiv e social processes. Importantly, parents of youth in the clinical group spontaneously used the network interview and resultant visualization as an avenue to begin or extend conversation with their youth regarding complexities of social functioning. Clinic al use of SNA can potentially provide clinicians a framework from which to provide education and training for parents and youth with social difficulties related to LD, ADD or ASD. Future studies can focus on systematically testing methods of SNA as interve ntions for youth with social difficulties related to cognitive impairments. Limitations The majority of l imitations to the qualitative analysis were discussed in the previous chapter However, we did not inquire as to which youth if any in the clinical s ample had a history significant for receiving formalized social skills training. Lack of knowledge of this was an additional limitation to the analysis of the qualitative interview data. Social skills training may conceivably influence social strategies e mployed by the recipient. Variability was observed in the use of social strategies employed by youth in the clinical group Quantitative analysis was limited by the sample size which hinder ed ability to generalize findings and detect mode st relationships Sample size was constrained by the limited resources of unfunded dissertation research and the choice to engage in mixed method inquiry involving PNA and cognitive interviews. The use of PNA and cognitive interview s provide d extensive information about e ach respondent. Our study utilized a convenience sample primarily drawn from a city containing a ma jor research university with an academic health center. Parents of study participants

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127 were versed in health and disability related information pertinent to their child. Many sing resources for their child; and many were eager for their child to successfully access his or her own social resources. While this bias aided in recruitment and data collect ion, findings may not be as generalizable to other contexts. The exploratory nature of this research resulted in large numbers of variables and correlation analyses. This challenged ability to focus study findings. As an exploratory investiga tion, a fundam ental objective was to identify areas for further study Study findings involving siblings were limited because sibling age and genders were not further investigated; future investigations could focus on sibling roles within the social networks of youth wi th disabilities Additional a reas to focus future research include further elucidation of social network links to participation and testing clinical use of methods of PNA as an intervention. Such a clinical intervention can be tested with adolescents and a dults whose conditions result in social participation difficulties. Conclusion Social networks are linked to participation. This study expands understanding of the ways in which social networks are linked to participation for youth with cognitive/informat ion processing difficulties associated with learning, attention or autism spectrum disorders. Gaining understanding of the social networks of rehabilitation clients can provide a framework by which clinicians might guide integration of hard won skills Ado ption of the social network paradigm has the potential to provide rehabilitation professions a language useful for describ ing and understand ing the social co ntext of participation. Methods of SNA have the potential to become useful in the assessment of soc ial participation and integration of individuals with disabling conditions.

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128 Not all clients are able to easily transition from rehabilitation services to successful interpersonal relationships and integration with in their communities. The steps by which s ocial and community integration occurs remain elusive for many in practice and remains to be elucidated in research. For youth requiring social skills training, the practice and theoretical paradigm of SNA has the potential to inform the steps to social pa rticipation and, by extension inclusion

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129 APPENDIX NETWORK VISUALIZATIONS 11 14 years old Clinical Comparison SRS score: 49 Central: peer SRS score: 44 Central: mother, father, sibling SRS s core: 92 Central: mother SRS score: 42 Central: father

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130 11 14 years old Clinical Comparison SRS score: 74 Central: peer & teacher SRS score: 37 Central: sibling 1, sibling 2, peer, adult frie nd of parents SRS score: 85 Central: peer SRS score: 49 Central: peer 57 are considered clinically significant ; lower scores indicate mo re coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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131 11 14 years old Clinical Comparison SRS score: 54 Central: teacher SRS score: 40 Central: mother, sibling SRS score: 57 Central: mother & sibling SRS score: 44 Central: peer 57 are con sidered clinically significant ; lower scores indicate more coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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132 11 14 years old Clinical Compari son SRS score: 86 Central: sibling SRS score: 39 Central: sibling SRS score: 98 Central: sibling 1, sibling 2 SRS score: 53 Central: mother Note: Developmental Coordina 57 are considered clinically significant ; lower scores indicate more coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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133 11 14 years old Clinic al Comparison SRS score: 77 Central: pastor SRS score: 40 Central: father SRS score: 108 Central: pastor 15 16 year old Comparison SRS score: 52 Central: peer Note: D 57 are considered clinically significant ; lower scores indicate more coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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134 11 14 years old 15 16 years old Clinical Comparison SRS score: 64 Central: mother SRS score: 41 Central: peer 15 16 years old SRS score: 36 Central: peer Clinical SRS: 57 Central: cousin Note: 57 are considered clinically significant ; lower scores indicate more coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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135 15 16 years old Clinical Comparison SRS score: 60 Central: sibling & peer SRS score: 42 Central: sibling SRS score: 64 Central: peer SRS score: 37 Central: sibling Note: 57 are considered clinically significant ; lower scores indicate more coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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136 15 16 years old Clinical Comparison SRS score: 51 Central: mother, grandmother & peer SRS score: 36 Central: peer SRS score: 81 Central: father SRS score: 40 Central: cousin Note: Developm 57 are considered clinically significant ; lower scores indicate more coordination difficulties Social Responsiveness Scale (SRS) scores 60 are considered clinically significant; higher scores indicate more social difficulties.

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137 15 16 years old Clinica l Comparison SRS score: 73 Central: sibling SRS score: 36 Central: mother, sibling, peer 1, peer 2 SRS score: 73 Central: sibling 15 16 years old Clinical SRS score: 81 Cen tral: father clinically significant; lower scores indicate more coordination difficulties. Social Responsiveness Scale t; higher scores indicate more social difficulties.

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138 LIST OF REFERENCES Ameri can Psychiatric Association. (2000). Diagnostic and statisti cal manual of mental disorders, 4 th edition, Text Revision. Washington, DC: Author Anderson, M. P., Madill, H. M., Warr en, S. A., & Vargo, J. W. (1996). Social support and barriers to post secondary education: Experiences of students with physical disabilities in Canada. British Journal of Occupational Therapy, 59( 12 ), 575 580. Asselin, M. E. (2003). Insider research: Issu es to consider when doing qualitative research in your own setting. Journal for Nurses in Staff Development 19 (2), 99 103. Berkman, L. F., Glass, T., Brissette, I., & Seeman, T. E. (2000). From social integration to health: Durkheim in the new millennium. Social Science in Medicine, 51 843 857. Benson P, Karlof K, Siperstein G. (2008). Maternal involvement in the education of young children with autism spectrum disorders. Autism, 12 (1), 47 63. Bernard, H. R. (2006). Research methods in anthropology: Quali tative and quantitative approaches, 4 th ed. Lanham, MD: AltaMira Press. Blum, R. W., Resnick, M. D., Nelson, R., & St Germaine, A. (1991). Family and peer issues among adolescents with spina bifida and cerebral palsy. Pediatrics, 88 280 285. Blythe, S. G. (2006). Releasing educational potential through movement: A summary of individual studies carried out using the INPP Test Battery and Developmental Exercise Programme for use in schools with children with special needs. Child Care in Practice, 11 (4) 415 432. doi: 10.1080/13575270500340234 Boeije, H. (2010). Analysis in qualitative research. Thousand Oaks, CA: Sage Publication, Inc. Boyatzis, R. E. (1998) Transforming qualitative information: Thematic analysis and code development. Thousand Oaks, CA: Sage Publications. Brown, C. E., & Dunn, W. (2002). Adolescent/Adult Sensory P rofile user's manual San Antonio, TX: The Psychological Corporation. Bryant, B. K. (1994). How does social support function in childhood? In F. Nestmann & K. Hurrelmann (Eds.), Hea lth behavior and health education: Theory, research, and practice (pp. 23 35). Berlin; New York: Walter de Gruyter.

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139 Center s for Disease Control and Prevention, Autism and Developmental Disabilities Monitoring Network Surveillance Year 2008 Principal Inves tigators (2012). Prevalence of autism spectrum disorders Autism and Developmental Disabilities Network, 14 sites, United States, 2008. Surveillance Summaries, 61 (SS03), 1 19. Retrieved from http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6103a1.htm?s_cid=ss6103a1_w Chamberlain, B., Kasari, C., & Rotheram Fuller, E. (2007). Involvement or isolation? The social networks of children with autism in regular classrooms. Journal of Autism and Developmental Disorders, 37, 230 242. Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. Thousand Oaks, CA: Sage Publications, Inc. Chen, H. F., & Cohn, E. S. (2003). Social participation for child ren with developmental coordination disorder: Conceptual, evaluation and intervention considerations. Physical & Occupational Therapy in Pediatrics, 23 (4). 61 78. Cohen, J. (1988). Statistical power analysis for the behavioral sciences, 2 nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates. Cohen, S., & Lemay, E. P. (2007). Why would social networks be linked to affect and health practices? Health Psychology, 26 410 417. Cole, M. B., & Donohue, M. V. (2011). Social participation in occupational contexts: In s chools, clinics, and communities. Thorofare, NJ: S lack Inc. Constantino, J. N., & Gruber, C. P. (2005). Social responsiveness scale: Manual Los Angeles, CA: Western Psychological Services. Corder, G. W., & Foreman, D. I. (2009). Nonparametric statistics f or non statisticians: A step by step approach. Hoboken, NJ: John Wiley & Sons, Inc. Creswell, J. W., & Plano Clark, V. C. (2007). Designing and conducting mixed methods research. Thousand Oaks, CA: Sage Publications, Inc. Christakis, N. A., & Fowler, J. H. (2010). Social network sensors for early detection of contagious outbreaks. PLoS ONE, 5(9), e12948. doi:10.1371/journal.pone.0012948 Dumont, M., & Provost, M. A. (1999). Resilience in adolescents: Protective role of social support, coping strategies, self esteem, and social activities on experience of stress and depression. Journal of Youth and Adolescence, 28(3) 343 366. Dunn, J. C., & Watkinson, E. J. (2002). Considering mo tivation theory in the study o f developmental coordination disorder. In S. A. Cer mak & D. Larkin (Eds.), Devel opmental coordination disorder (pp. 185 199). Albany, NY: Delmar Thomson Learning.

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140 Faber, A. D., & Wasserman, S. (2002). Social support and social networks: Synthesis and review. Social Networks and Health, 8, 29 72. Fivush, R. & Slackman, E. A. (1986). The acquisition and development of scripts. In K. Nelson (Ed.), Event knowledge: Structure and function in development (pp. 71 96). Hillsdale, NJ: Erlbaum. Forsyth, R., & Jarvis, S. (2002). Participation in childhood. Child: Car e, Health & Development, 28, 277 279. Freeman, L. C. (1979). Centrality in social networks I: Conceptual clarification. Social Networks, 1, 215 239. Garrison Wade, D. F., & Lehmann, J. P. (2009). A conceptual framework for abilities transition to community college. Community College Journal of Research and Practice, 33, 417 445. Goddard, S. (2005). Eugine, OR: Fern Ridge Press. Godde, M., & Engfer, A. (1994). C hildren's social networks and the development of social competence: a longitudinal analysis. In F. Nestmann, & K. Hurrelmann (Eds.), Social networks and social support in childhood and adolescence (pp. 191 216). Berlin; New York: Walter de Gruyter. Goodma n, R. (1997). The Strengths and Difficulties Questionnaire: a research note. Journal of Child Psychology and Psychiatry, 38, 581 586. Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed method evaluation designs Educational Evaluation and Policy Analysis, 11(3) 255 274. Gutman, S. A., McCreedy, P., & Heisler, P. (2004). The psychosocial deficits of children with regulatory disorders: Identification and treatment. Occupational Therapy in Mental Health, 20(2), 1 32. Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods Riverside, CA: University of California, Riverside Retrieved from http://faculty.ucr.edu/~hanneman/ Harty, M., Joseph, L ., Wilder, J., & Rajaram, P. (2007). Social support and families with disabilities: towards positive family functioning. South African Journal of Occupational Therapy, 37 18 21. Retrieved from htt p://www.up.ac.za/dspace/handle/2263/6237 Heaney, C. A., & Israel, B. A. (2002). Social networks and social support. In K. Glanz, B. K. Rimer, & F. M. Lewis (Eds.), Health Behavior and Health Education: Theory, Research, and Practice (pp. 185 209). San Fra ncisco, CA: Jossey Bass.

PAGE 141

141 Heyman, B., Swain, J., Gillman, M., Handyside, E. C., & Newman, W. (1997). Alone in the crowd: how adults with learning difficulties cope with social network problems. Social Science & Medicine, 44(1), 41 53. Hilton, C. L. (2010). Social skills for children with an autism spectrum disorder. In H. M. Kuhaneck, & R. Watling (Eds.), Autism: A comprehensive occupational therapy approach, 3 rd ed. (pp. 333 364). Bethesda, MD: AOTA Press. Hilton, C. L., Crouch, M. C., & Israel, H. (2008). Out of school participation patterns in children with high functioning autism spectrum disorders. American Journal of Occupational Therapy, 62 (5) 554 563. Huang, I. C., Thompson, L. A., Chi, Y. Y., Knapp, C. A., Revicki, D. A., Seid, M., & Shenkman, E. A (2009). The linkage between pediatric quality of life and health Value in Health, 12 (5) 773 781 Imms, C. (2008). Children with cerebral palsy participate: A review of the lit erature. Disability and Rehabilitation, 30 (24). 1867 1884. Institute of Medicine (1997). Enabling America: Assessing the role of rehabilitation science and engineering Washington, DC: The National Academies Press. Kazak, A. E., & Marvin, R. S. (1984). Dif ference s, difficulties and adaptation: S tress and social networks in families with a handicapped child. Family Relations, 33, 67 77. Kef, S. (1997). The personal networks and social supports of blind and visually impaired adolescents. Journal of Visual Imp airment and Blindness, 91 236 244. King G., Law M., Hanna S., King S., Hurley P., Rosenbaum P. Petrenchik T. (2006): Predictors of the leisure and recreation participation of children With physical disabilities: A structural equation m odel ing a nalysis Children's Health Care, 35 ( 3 ) 209 234 http://dx.doi.org/10.1207/s15326888chc3503_2 King, G. A., Law, M., King, S., Hurley, P., Hanna, S., Kertoy, M., & Rosenbaum, P. (2007). Measurin g children's participation in recr eation and leisure activities: C onstruct validation of the CAPE and PAC. Child: Care, Health and Development, 33 28 39. King, G., Law, M., King, S., Hurley, P., Rosenbaum, P., Hanna, S., Young, N. (2004). Children's Ass essment of Participation and Enjoyment & Preferences for Activities of C hildren manual San Antonio, TX: Harcourt Assessment, Inc. Knoke, D., & Yang, S. (2008) Social network analysis, 2 nd ed Thousand Oaks, CA: Sage Publications, Inc. Law, M., Steinwender S., & Leclair, L. (1998) Occupation, health, and well being. Canadian Journal of Occupational Therapy, 65 81 91.

PAGE 142

142 Law, M., Feinkelman, S., Hurley, P., Rosenbaum, P., King, S., King, G., & Hanna, S. (2004). Participation of childr en with physical disabil ities: R elationships with diagnosis, physical function, and demographic variables. Scandinavian Journal of Occupational Therapy (11) 156 162. C. E., (2010). Autism s pectrum disorder and co occurring developmental, psychiatric, and medical conditions among children in multiple populations of the United States. Journal of Developmental & Behavioral Pediatrics, 31 (4), 267 275. Lewis, M. A., DeVellis, B. M., & Sleath, B. (2003). Social influence and interpersonal communication in health behavior. In K. Glanz, B. K. Rimer, & F. M. Lewis (Eds.), Health Behavior and Health Education: Theory, Research, and Practice (pp. 240 264). San Francisco, CA: Jossey Bass. Liao, T. F. ( Social network analysis, 2 nd ed., (pp. vii viii). Thousand Oaks, CA: Sage Publications, Inc. Limbers, C. A., Ripperger Suhler, J., Heffer, R. W., & Varni, J. W. (2011). Patient reported Pediatric patients with Attention Defi cit/Hyperactivity Disorder and comorbid psychiatric d isorders: Feasibility, reliability and validity. Value in Health, 14, 521 530. Litwin, H. (2006). The path to well being among elderly Arab Isralis. Journal of Cross Cultural Gerontology,21, 25 40. McAndrew, I. (1979). Adolescents and young people with spina bifida. Developmental Medicine and Child Neurology, 21, 619 629. McCarty, C. (2002). Measuring structure in personal networks. Journal of Social Structure, 3(1). Retrieved from http://www.cmu.edu/joss/content/articles/volume3/McCarty.html McCarty, C., Killworth, P. D., & Rennell, J. (2007). Impact of methods for reducing respondent burden on personal network structural measures. Social Networks, 29, 300 315. McCarty, C., Molina, J. L., Aguilar, C., & Rota, L. (2007). A comparison of social network mapping and personal network visualiz ation. Field Methods, 19, 145 162. McPhillips, M., Hepper, P. G., & Mulhern, G. (2000). Effects of replicating primary reflex movements on specific reading difficulties in children: A randomized, double blind controlled trial. The Lancet, 355 (9203), 537 54 1. Motulsky, H. (1995). Intuitive biostatistics New York, NY: Oxford University Press, Inc.

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143 Mutti, M., Martin, N. A., Sterling, H., & Spalding, N. (2011). Quick N eurol ogical Screening T est, 3 rd ed. manual. Ann Arbor, MI: Academic Therapy Publications. Nat ional Institutes of Mental Health (2011). disorder. NIH Publication No. 11 5511. Washington, DC: Government Printing Office. Nestmann, F., & Hurrelmann, K. (1994). Child and adolescent research as a challenge and opport unity for social support theory, measurement, and intervention: A nd visa versa. In Nestmann, F., & Hurrelmann, K. (Eds.), Social Networks and Social Support in Childhood and Adolescence, (pp. 1 20). Berlin; New York: de Gruyter. Ochs, E., Kremer Sadlik, T. Solomon, O., & Sirota, K. G. (2001). Inclusion as social practice: V iews of children with autism. Social Development, 10(3), 399 419. Orr, A. C., & Hammig, S. B. (2009). Inclusive postsecondary strategies for teaching students with learning disabilities: A review of the literature. Learning Disability Quarterly, 32, 181 196. Oswald, H., Krappmann, L., Uhlendorff, H., & Weiss, K. (1994). Social relationships and support among peers during middle childhood. In F. Nestmann & K. Hurrelmann (Eds.), Social Net works and Social Support in Childhood and Adolescence, (pp. 171 189). Berlin; New York: Walter de Gruyter. Parham, L. D., & Mailloux, Z. (2010). Sensory integration. In Case J. C. (Eds.), Occupational Therapy for Children, 6 th ed., (p p. 325 372). Maryland Heights, MO: Mosby Elsevier. Parten, M. B. (1932). Social participation among pre school children. Journal of Abnormal and Social Psychology, 27, 243 269. Pastor, P N., & Reuben, C. A. (2008). Diagnosed attention deficit hyperactivit y disorder and learning disability: United States, 2004 2006. National Center for Health Statistics Vital and Health Statistics, 10 (237) Retrieved from http://www.cdc.gov/nchs/data/series/sr_10/sr10_206.pdf Patton, M. Q. (2002). Qualitative Research and Evaluation Methods Thousand Oaks, CA : Sage Publications Pescosolido, B. A., & Levy, J. A. (2002). The role of social networks in health, illness, diseas e and healing: The accepting present, the forgotten past, and the dangerous potential for a complacent future. In J. A. L evy, & B. A. Pescosolido (Eds.) Social Networks & Health, 8 (pp. 3 25). London: Elsevier. Rimer, B. (2003). Perspectives on interperson al theories of health behavior. In Glanz, K., Rimer, B. K., & Lewis, F. M. (Eds.), Health behavior and health education: Theory, research, and practice (pp. 144 184). San Francisco, CA: Jossey Bass.

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144 R ose, B., Larkin, D., & Berger, B. G. (1997). Coordinatio n and gender influences on the perceived competence of children. Adapted Physical Activity Quarterly 12 210 221. Sandelowski, M., & Barroso, J. (2003). Classifying the findings in qualitative studies. Qualitative Health Research, 13(7), 905 923. doi : 10. 1177/1049732303253488 Schwartz Shea, P. (2006). Judging quality: Evaluative criteria and epistemic communities. In D. Yanow, & P. Schwartz Shea (Eds.) Interpretation and Method: Empirical Research Methods and the Interpretive Turn (pp. 89 113). Armonk, NY : M. E. Sharpe, Inc. Scott, J. (2000). Social network analysis: A handbook (2nd ed.). London: Sage Publications, Ltd. Shikako Thomas, K., Majnemer, A., Law, M., & Lach, L. (2008). Determinants of participation in leisure activities in children and youth w ith cere bral palsy: S ystematic review. Physical & Occupational Therapy in Pediatrics, (28) 155 169. Skar, R. N. L. (2003). Peer and adult relationships of adolescents with disabilities. Journal of Adolescence, 26, 635 649. Skinner, R. A., & Piek, J. P. (2 001). Psychosocial impli cations of poor motor coordina tion in children and adolescents. Human Movement Science 20 73 94. Smart, J. (2009). Disability, society, and the individual Austin, TX: Pro Ed, Inc. Stevenson, C. J., Pharoah, P. O. D., & Stevenson, R. (1997). Cerebral palsy the transition from youth to adulthood. Developmental Medicine & Child Neurology, 39 336 342. Strine, T. W ., Lesesne, C. A., Okoro, C. A., McGuire, L. C., Chapman, D. P., Balluz, L. S., & Mokdad, A. H. (2006). Emotional and be havioral difficulties and impairments in everyday functioning among children with a history of attention deficit/hyperactivity disorder. Preventing Chronic Disease, 3 (2). Retrieved from http ://www.cdc.gov/pcd/issues/2006/apr/05_0171.htm Tardy, C. (1985). Social support measurement. American Journal of Community Psychology, 13 (2), 187 202. Taylor, M., Houghton, S., & Chapman, E. (2004). Primitive reflexes and attention deficit/hyperactivit y disorder: Developmental origins of classroom dysfunction. International Journal of Special Education, 19 (1). Retrieved from http://www.internationaljournalo fspecialeducation.com/articles.cfm?y=2004&v=19 &n=1

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145 Teitelbaum,O., Benton, T., Shah, P. K., Prince, A., Kelly, J. L., & Teitelbaum P. (2004) Eshkol Wachman movement notation in diagnosis: The early detection of Asperger's syndrome Proceedings of the Na tional Academy of Sciences of the United States of America. 101 (32), 11909 11914. doi: 10.1073/pnas.0403919101 Tinsley, H. E. A., & Eldredge, B. D. (1995). Psychological benefits of leisure participation: A taxo nomy of leisure activities based on their need gratifying properties. Journal of Counseling Psychology, 42, 123 132. Turner, R. J. (1981). Social support as a contingency in psychosocial well being. Journal of Health and Social Behavior, 22( December), 357 367. Valente, T. W., Hoffman, B. R., Ritt Olson, A., Lichtman, K., & Johnson, A. (2003). Effects of a social network method for groups assignment strategies on peer led tobacco prevention programs in schools. American Journal of Public Health, 93(11), 1837 1843. Varni, J. W., Seid, M., & Kurtin, P. S. (2001). PedsQL 4.0: Reliability and validity of the Pediatric Quality of Life Inventory Version 4.0 Generic Core Scales in healthy and patient populations. Medical Care, 39, 800 812. Varni, J. W., Seid, M ., & Rode, C. A. (1998). The PedsQL TM : Measurement model for the Pediatric Quality of Life Inventory. Medical Care, 37 (2), 126 139. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York: Cambridge University Press. Wellman, B., & Berkowitz, S. D. (1988). Social structures: A network approach. Cambridge, UK: Cambridge University Press. Wenzel, L., Glanz, K., & Lerman, C. (2003). Stress, coping, and health behavior. In K. Glanz, B. K. Rimer, & F. M. Lewis (Eds.), Heal th behavior and health education: Theory, research, and practice (pp. 210 239). San Francisco, CA: Jossey Bass. Whiteneck, G., & Dijkers, M.P. ( 2009 ). Difficult to measure constructs: C onceptual and methodological issues concerning participation and enviro nmental factors. Archives of Physical Medicine and Rehabilitation, 90 (Suppl 1), S22 S35. Wilson, B. N., Crawford, S. G., Green, D., Roberts, G., Aylott, A., & Kaplan, B. J. (2009). Psychometric properties of the revised developmental coordination disorder questionnaire. Physical & Occupational Therapy in Pediatrics, 29 (2), 184 204. World Health Organization (2001). International classification of functioning, disability and health. Geneva, Switzerland: WHO Press.

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146 World Health Organization (2002). Toward a common language for functioning, disability and health: ICF. Retrieved from http://www.who.int/classifications/icf/training/icfbeginnersguide.pdf World Health Organizati on (2007). International classification of functioning, disability and health: Children & youth version: ICF CY. Geneva, Switzerland: WHO Press. Zero to Three (2005). Diagnostic classification of mental health and developmental disorders of infancy and ear ly childhood; DC: 0 3R. Arlington, VA: Zero to Three.

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147 B IOGRAPHICAL SKETCH Consuelo Kreider received her Bachelor of Health Science in Occupational Therapy from the University of Florida in 1989. She practiced for 18 years as a clinical occupational thera rehabilitation science doctoral program in August 2007. Concurrent with her doctoral studies, she was awarded a Master of Health Science in Occupational Therapy in 2009. In January 20 06, Consuelo joined the faculty of the University of Florida Department of Occupational Therapy as an adjunct lecturer. Here, she taught year round in the Master of Occupational Therapy program as she pursued her doctoral studies. Consuelo has presented at several state, national and international conferences and has co authored 2 articles published in peer reviewed journals. As a doctoral student, she spearheaded pursuit of an interdisciplinary research project focusing on developing a multi level model of support for undergraduate students with learning disabilities at the University of Florida. She began engagement in this 4 year federally sponsored project in February 2013 as a co principal investigator. Upon completion of her PhD program, Consuelo will pursue a career in research and teaching. Consuelo has been married to her husband, David Kreider, for 23 years. They have three children, Dominick, age 14, Jocelyn, age 12, and Natalie, age 10.