Rules of “Engagement”

CHAPTER FIVE

Rules of “Engagement”: Addressing Participation and Functional Performance in Children with Intellectual and Developmental Disabilities Lisa A. Daunhauer*,1, Brianne Gerlach-McDonald†, Mary A. Khetani{ *Human Development and Family Studies, Colorado State University, Fort Collins, Colorado, USA † Doctoral Candidate, Human Development and Family Studies, Colorado State University { Assistant Professor, Occupational Therapy, Colorado State University 1 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 2. Indicators of Child Functioning 2.1 What is Participation and Functional Performance? 2.2 Indicators of Child Functioning Summary 3. Review of Participation and Functional Performance Measures for Children with IDDs 3.1 How Do We Measure Children's Participation? 3.2 How Do We Measure Children's Functional Performance? 3.3 Assessment That Combines Children's Participation and Functional Performance 4. Discussion 4.1 Parsing Participation 4.2 Proxy Reporting 4.3 Sampling Considerations References

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Abstract A primary goal of research in the field of intellectual and developmental disabilities (IDDs) is to help individuals with IDDs achieve optimal outcomes so that they are able to engage in life in ways that are individually meaningful. However, in order to achieve this goal, researchers need to be able to accurately define and measure participation and related concepts. This review examines the operationalization and measurement

International Review of Research in Developmental Disabilities, Volume 47 ISSN 2211-6095 http://dx.doi.org/10.1016/B978-0-12-800278-0.00005-1

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of both participation and functional performance in children with IDDs. We also discuss issues to be addressed and directions for future research.

1. INTRODUCTION The past decade has brought renewed appeals for translational research that will yield effective intervention outcomes for individuals with intellectual and developmental disabilities (IDDs; e.g., McCabe, Hickey, & McCabe, 2011; McCabe & McCabe, 2011). A major focus of these calls is improving the life outcomes of children with IDDs as indicated by their engagement in everyday life. Intervention science in this particular area will hinge in large part on the selection of appropriate measures relevant to these outcomes (Castro & Pinto, 2013). For intervention studies to adequately address the life outcomes of children with IDD, researchers need to select measures that best capture concepts relevant to “life engagement.” Contributing to this challenge is the ability for researchers to operationalize and measure these concepts. There are several recognized methods of describing, diagnosing, and classifying clinical problems for children with IDD to guide intervention. However, over the past decades, researchers from a rehabilitation science perspective began to argue that traditional diagnostic systems for people with disabilities in general, including children with IDDs, make the individual’s diagnosis the “primary unit” of focus in determining intervention needs despite the known variability in how specific children with disabilities may function. For example, two children with Down syndrome (DS) may present differently in some domains (e.g., self-regulation), whereas children with different diagnoses may share similar characteristics (e.g., children with autism spectrum disorder (ASD) and DS may display similar challenges in planning skills or have similar preferences for school-based activities). Therefore, in addition to traditional diagnoses, functional frameworks that address how a person engages in life are critically needed to guide assessment of children’s needs for services and supports that will improve their engagement in everyday tasks and activities, and to evaluate intervention effects. Despite rapid advancements in the classification and measurement of children’s functioning, there is critical need for improved uptake of this new information beyond disability and rehabilitation venues. To our knowledge, evidence regarding the broader state of inquiry on measuring

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children’s functioning has not been formally introduced within the IDD literature for the purpose of advancing intervention research in the field. To date, this topic has attained a foothold, albeit a modest one, in the field of IDDs. For example, in the American Journal of Intellectual and Developmental Disability, 13% of research articles published used measures of functioning as outcome variables in the years 2012 and 2013. Similarly, during this same period, four research articles in this journal included adaptive behavior measures, a related concept. Additionally, three literature reviews published in the journal during this time frame addressed activity performance, community participation, and/or adaptive behavior, respectively. Clearly, greater knowledge about how to conceptualize and measure outcomes related to engagement in everyday life among children with IDD has the potential to significantly advance the design of intervention research involving individuals with IDD. Therefore, this chapter aims to introduce key concepts of children’s engagement in everyday life and ways of measuring these concepts in research involving individuals with IDDs. This review will: 1. Differentiate the concepts of participation and functional performance (activity) as indicators of children’s engagement in life activities; 2. Appraise assessments used to measure outcomes in these domains; and 3. Explore issues related to intervention research addressing these outcomes. By meeting the above-described aims, it is our intention to ignite cross talk about key concepts related to children’s functioning by developmental scientists and rehabilitation scientists who can collaboratively improve the methodological rigor of intervention research regarding children with IDD in both fields.

2. INDICATORS OF CHILD FUNCTIONING The International Classification of Function (ICF), and the more recently developed ICF version for Children and Youth (ICF-CY), reflects the most current international frameworks of disability (World Health Organization [WHO], 2001, 2007). Moreover, these frameworks represent decades of evolving work that created a paradigm shift. This shift represented a move away from primarily focusing on the medical or genetic causes of a disabling condition such as the genetic problem that causes Fragile X to a greater focus on the functional consequences of a disability condition (e.g., difficulty with making friends or the amount and type of adaptations needed optimize classroom behavior). The ICF conceptualizes

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the effects of disabling conditions as occurring in three domains: body structure/body functions, activity, and participation. At each level of functioning, the ICF model implies a dynamic interplay between an individual and the context in which he or she is operating that may or may not produce disablement. Specifically, this interplay between an individual’s contextual factors (e.g., architecture, terrain, social attitudes, and social structures), personal factors (e.g., age, gender, and coping styles), and their disability can enable or disable the individual (World Health Organization [WHO], 2007). For example, a child with William’s syndrome may functionally have no challenges during recess when his social strengths help create many opportunities for play, while in the classroom his drive for sociability may interfere with individual work to the extent that oneon-one assistance from an adult is needed in order to complete classroom activities. Therefore, interventions could potentially target any of the model’s components. Consequently, the ICF-CY has far-reaching implications for assessment, intervention, and policy (Simeonsson et al., 2003; Fig. 5.1).

2.1. What is Participation and Functional Performance? A significant drawback to both the ICF and ICF-CY is the ambiguity in use of the terms activity and participation that has resulted in multiple

Health condition (e.g., disability, disease, disorder)

Body structures and functions

Environmental factors

Activities

Participation

Personal factors

Figure 5.1 The ICF model (World Health Organization [WHO], 2001, 2013). Reproduced with the permission of the publisher.

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interpretations of these concepts. In order to clarify the conceptual content of activity and participation components in the ICF, Badley (2008) developed distinguishing characteristics to provide clarification. Examples of activities according to Badley’s interpretation of the ICF include dressing, grooming, walking, etc., while participation entails work, recreation, education, community involvement, etc. Nonetheless, considerable debate about how to use ICF language has continued and it has been criticized for being inadequate for guiding measure development (Dijkers, 2010). 2.1.1 Participation Operationalized Participation, as defined by The World Health Organization’s ICF, is an individual’s engagement in an array of life situations varying from the simple to the complex, including education, employment, leisure, social relationships, and community living (World Health Organization [WHO], 2001). For the purpose of this review, participation will be operationalized as the “involvement in a life situation” (Badley, 2008) such as playing with friends or attending school. 2.1.2 Why is Participation Important to Understand and Measure? A child’s ability to participate in everyday activities in the home, school, and the community is a basic right and widely accepted indicator of children’s health and well being (United Nations, 2006). Participation in a variety everyday situations—such as attending story time at the library or meeting friends— is associated with more positive developmental outcomes in children with both typical development (e.g., Burchinal et al., 2000) and those with IDDs (King, Imms, et al., 2013; King, Shields, Imms, Black, & Arden, 2013). Recent research highlights that children with IDD demonstrate significantly more limitations and different patterns of participation in everyday life than their peers without disabilities (e.g., King, Imms, et al., 2013; King, Shields, et al., 2013; Law et al., 2013; Verschuren, Wiart, & Ketelaar, 2013). Importantly, recent evidence highlights that this risk of limited participation in everyday life activities extends into adulthood for individuals with IDD (Taylor & Hodapp, 2012) and that less varied and frequent participation may be associated with poor outcomes in other areas such as maladaptive behavior (Dykens, 2007). While the concept of participation is still in relatively early stages of its application to children with IDDs, it is an area of focus in both research and intervention in the body of inquiry that encompasses rehabilitation science (e.g., Palisano et al., 2012).

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2.1.3 Functional Performance Operationalized Given the confusion related to the use and overuse of the term “activity,” and the influence of Haley, Coster, Ludlow, Haltiwanger, and Andrellos (1992) discussion of function and capabilities, in this review, we chose to use functional performance to describe performance of those activities common to all children—such as self-care, mobility, language, and social interaction—that occur in a child’s home, school, and other natural contexts. As such, for the purpose of this review, functional performance will be used to describe activity performance, but in a specified range of everyday activities ubiquitous in childhood. It should be noted that the concept of functional performance shares some similarities and differences to the concept of adaptive behavior. Adaptive behavior is defined as “ability to meet daily living responsibilities and respond to the needs of others, including conceptual, practical, and social skills that people need to function in their everyday lives” (Ditterline & Oakland, 2009, p. 45). Consequently, participation in life situations is clearly supported by one’s propensity for adaptive behavior. However, researchers from a rehabilitation science perspective (Coster, Deeney, Haltiwanger, & Haley, 1998) have maintained that measures of adaptive behavior in children with developmental disabilities (DD) do not focus on information regarding specific levels of challenges, as well as information regarding assistance, and adaptations across various contexts (Coster et al., 1998). As researchers in the field of IDDs well know, the concept of adaptive behavior has gone through its own evolution and is now a part of the definition of ID. (Ditterline & Oakland, 2009; Schalock, Keith, Verdugo, & Gomez, 2010). Therefore, it serves a clear and critical purpose. Functional performance is not a part of the definition of ID; however, proponents of measuring functional performance have argued that this concept aligns well with intervention goals for a wide range of interventionists as the focus is on optimizing outcomes as opposed to determining whether or not functional performance is developing in a typical manner (Haley et al., 1992). 2.1.4 Why is Functional Performance Important to Understand and Measure? The connection of functional performance to participation in everyday life is presumed in the ICF model’s conceptualization of the relationship between participation and activity (World Health Organization [WHO], 2007) and is being substantiated through research. A recent study by Khetani, Graham, & Alvord (2013) found that difficulties in functional performance of activities such as mobility, toileting, feeding, speech, safety awareness, and friendship

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were associated with greater restrictions in participation for preschool-aged children who with IDDs or at risk for a developmental delay.

2.2. Indicators of Child Functioning Summary Overall, despite some conceptual ambiguity, the ICF redefined how we think about disability, functional performance (activities), and participation (Simeonsson et al., 2003; World Health Organization [WHO], 2001). Furthermore, both the ICF and ICF-CY have advanced thinking about the multiple pathways to interventions for optimizing life outcomes of children with disabilities. In IDD research as in rehabilitation science, there is science being conducted at all of these levels (e.g., mice model research at the body structure level), research on functional performance (e.g., adaptive or maladaptive behavior), and research on participation (e.g., life outcomes such as time spent engaged in work). The development of the ICF and the evolution of the concepts of both participation and functional performance has underscored the importance that stakeholders—researchers, service providers, individuals with disabilities and their families—place on meaningful engagement in everyday life. However, more work is still needed. It is becoming apparent that models like the ICF hold relevance in the lives of children and families. However, there is critical need to accurately measure these concepts in order to build and test effective interventions that address these outcomes. While the ICF model may benefit from refining these terms, in recent years, measures have been developed to quantitatively examine these concepts. Below, we examine measures of participation and functional performance with a focus on applications in research on school-aged children with IDDs. Then, we examine issues related to measuring these concepts and make recommendations for future research.

3. REVIEW OF PARTICIPATION AND FUNCTIONAL PERFORMANCE MEASURES FOR CHILDREN WITH IDDs In this section, we included both measures of participation and functional performance that: (a) conceptually map onto the ICF model and the aforementioned operationalization of both participation and/or functional performance, and (b) have been used specifically with children with IDDs in early childhood through school age. Furthermore, to remain focused on these concepts in IDD research, we did not include research focusing solely on mobility challenges.

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3.1. How Do We Measure Children's Participation? As currently conceptualized in rehabilitation science, participation is a complex concept (Coster & Khetani, 2008; Whiteneck & Dijkers, 2009). First, there is growing consensus that the WHO definition of participation as “involvement in life situations” is insufficient to guide measurement development (Coster & Khetani, 2008). Also complicating measurement is the diversity in the number and types of dimensions and activity structure (Coster et al., 2012) and an understanding that appraisal of participation is closely linked with appraisal of the child’s broader environment including: family characteristics (e.g., parental education, household income), physical, social, cultural, and temporal features of environments (Bronfenbrenner & Morris, 2006; Kramer & Hammel, 2011). In order to build and test pathways of participation outcomes for children with IDD, there is a need for comprehensive, detailed, and feasible assessments of children’s participation and environmental impact on participation for large-scale outcomes research, program assessment, and intervention planning purposes (Bedell, Khetani, Cousins, Coster, & Law, 2011). 3.1.1 The Participation and Environment Measure for Children and Youth The Participation and Environment Measure for Children and Youth (PEM-CY; Coster et al., 2012) was developed with these challenges in mind. The development process incorporated parent input to drive decisions about relevant content and scaling of the measure while maintaining the goal of designing a comprehensive and feasible instrument for use in population-level research (Coster et al., 2012). To design this measure, the researchers gathered information about parental perceptions regarding their children’s participation in activities, environmental supports and barriers to participation, and strategies employed to promote participation (Bedell et al., 2011). Their study findings provided implications for designing the PEM-CY to include environmental features not depicted in ICF-CY (World Health Organization [WHO], 2011) such as a child’s relationship with family members and babysitters or therapists, as well as the physical environment. This preliminary research also highlighted the need for multiple dimensions of assessment since parents described appraising their child’s participation both in terms of frequency and level of involvement in activities. The environment descriptions incorporated environmental factors, activity demands, and resources.

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The PEM-CY in its current format is a parent-report assessment of child participation that includes home (10 items), school (5 items), and community (10 items) domains. For each item in the domains, a parent assesses participation frequency (8-point Likert scale from never to daily), involvement (5-point scale from minimally involved to very involved) and whether the parent indicates that this is a desired area for change (Coster et al., 2011). The parent then rates each item for two additional areas: (1) perceived impact of environmental factors and activity demands (e.g., physical layout of the context, the child’s relationship with family members, social demands of the activity, etc.) on child’s participation for each item with four response options (from not an issue to usually makes harder) and (2) resources needed or available to facilitate participation (also with four options: not needed usually yes, sometimes yes/sometimes no, usually no). The psychometric testing of the assessment included a sample of over 576 children from 5 to 17 years of age with typical development (n ¼ 294) and disabilities (n ¼ 282). The majority of the children with disabilities had reported developmental, speech/language, or intellectual delays, although children with orthopedic impairments and emotional impairments were included as well (Coster et al., 2011). Psychometric testing found that the PEM-CY had moderate to very good internal consistency and test–retest reliability; a negative association between desire for change and environmental supportiveness; and that the measure could detect significant differences in home, school, and community participation when comparing children with and without disabilities on all participation and environment summary scores (for details, see Coster et al., 2011). Further validation of the PEM-CY indicates moderate to good concurrent validity of the environment sections when compared to the Craig Hospital Inventory of Environmental Factors for Children–Parent Version (Khetani, Cliff, Schelly, Daunhauer, & Anaby, 2014). 3.1.2 Applications of the PEM-CY Bedell et al. (2013) examined patterns of community participation and environmental factors that impacted participation for children with and without disabilities. Their primary outcome measure was the PEM-CY. The community summary scores incorporate participation frequency, percent never participates, involvement, percent that parents desire change, and percent total environmental supportiveness. The PEM-CY psychometric testing sample of 576 parents or guardians in the United States and Canada was utilized. The demographics were similar for the children with disabilities and children without disabilities, including DD such as developmental delays,

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intellectual delays, and ASD, as well as other disabilities such as emotional impairment and children without disabilities. The sample was predominantly white (81%) with most children being under 12 years old and living in households with income greater than $80,000. Results indicated significant group differences on all participation summary scores. Overall, children with disabilities were less involved in community activities and participated less frequently than typical children. Differences were not found in items that were linked to structured activities, such as religious activities or working for pay. An important predictor for participation was the children’s preference, motivation, and enjoyment of the activities. Notably, parents of children with disabilities desired more change in their child’s participation than children without disabilities. The results of their study provided implicates that greater efforts are needed to promote participation in children with disabilities, although the results have limited generalizability to a broader population. Further research is needed to examine the influence of type and severity of a developmental disability and what facilitates or constrains participation in a representative sample (Bedell et al., 2013). Finally, the Young Children’s Participation and Environment Measure (YC-PEM), modeled after the PEM-CY but tailored for use by parents of children 0–5 years of age, is currently undergoing psychometric validation (Khetani et al., 2013). 3.1.3 Children's Assessment of Participation and Enjoyment The Children’s Assessment of Participation and Enjoyment (CAPE; King et al., 2007) is a 55-item parent-reported measure focusing on participation outside of mandated schooling for children with disabilities. Relevant participation as defined by the authors can be “formal” or “informal.” Formal participation includes participating in activities such as organized sports, youth groups, or art lessons that involve structure. King et al. (2009) further defined formal participation as including organized structure, rules, goals, and frequently having a leader (e.g., a child’s participation in a soccer team). Informal participation was described King et al. (2009) as spending time doing: hobbies, chores, unstructured physical activities, and reading. Informal participation is, as described by King et al. (2009), typically spontaneous and initiated by the child. There are five dimensions of participation assessed: diversity, intensity (e.g., level of involvement), with whom, where, and enjoyment. The domains are scored incorporating three levels including overall participation, domains reflecting formal and informal participation, and participation in five types of activities: recreational, social, active

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physical, skill-based, and self-improvement. The measure is considered appropriate for children with and without disabilities between 6 and 21 years of age (King et al., 2007; Law et al., 2006). The CAPE does not assess environmental modifications, or other aids and assistance. The CAPE also does not incorporate factors that may influence participation, such as family or environmental characteristics that may influence a child’s choices (Law et al., 2006). King et al. (2007) examined the construct validity in 427 children between 6 and 15 years of age with physical disabilities. The authors found that the key CAPE domains correlated with existing measures (e.g., physical environment, classmate, support, and child cognitive functioning; for details, see King et al., 2007). 3.1.4 Application of the CAPE The CAPE has been utilized frequently to assess participation in children with cerebral palsy (CP; Badia, Longo, Orgaz, & Gomez-Vela, 2013; Bult et al., 2013; Imms, Reilly, Carlin, & Dodd, 2008; Longo, Badia, & Orgaz, 2013; Majnemer et al., 2008). Studies that characterized participation in children with CP indicated that they participated in a range of activities (Majnemer et al., 2008). However, the activities were more likely to be undemanding in terms of developmental and/or physical skills, and there was little participation in community-based activities (Majnemer et al., 2008). Researchers also have examined predictors of participation using the CAPE (Badia et al., 2013; Bult et al., 2013; Longo et al., 2013). One study found that both environment and child characteristics more strongly predicted participation than family characteristics (Longo et al., 2013). Badia et al. (2013) also examined participation as a key outcome measure for quality of life (QOL) in Spanish children and adolescents. The intensity and enjoyment of participation in informal activities had a positive, significant impact on the QOL. Furthermore, psychological well being was most influenced by enjoyment and participation domains of the CAPE (Badia et al., 2013). Bult et al. (2013) conducted a longitudinal study to examine which family and environmental variables measured at 2 years of age predicted participation in activities of school-aged children with CP. Findings indicated that movement ability was a significant predictor for children’s participation in both formal and informal activities. Social skills were most predictive for informal activities. The type of childcare was the only environmental variable predictive of participation and in informal activities only (Bult et al., 2013).

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The CAPE has been examined in individuals with CP and across cultures in children with and without disabilities (Anastasiadi & Tzetzis, 2013; Imms et al., 2008; King, Imms, et al., 2013; King, Shields, et al., 2013; Ullenhag et al., 2012). Studies on children with CP in Australia, Canada, and the United States suggested that there were more geographical similarities in participation than differences (Imms et al., 2008; King, Imms, et al., 2013; King, Shields, et al., 2013). However, in a study on children with and without disabilities, children with disabilities were found to have geographical differences in Sweden, Norway, and the Netherlands. The authors suggested that differences may be due to the variability in the education system of the countries included in the study (Ullenhag et al., 2012). The CAPE has also been used for assessment of participation and enjoyment in youth with other disabilities. King, Imms, et al. (2013) and King, Shields, et al. (2013) compared participation in children with intellectual disabilities and typically developing children in Australia using the CAPE and the Preferences for Activities of Children (PAC) questionnaire. Children with intellectual disabilities (n ¼ 38; mean age ¼ 12.3 years) participated in fewer physical and skill-based activities than their typically developing peers. The authors stated that further investigation on how participation is influenced by both the environment and child factors is needed. The CAPE has been used with more neurogenetic syndromes as well. Wuang and Su (2012) used the CAPE to assess participation of adolescents with DS. Findings revealed that there was greater participation in informal activities and limited diversity of activities and limited intensity. Higher cognitive and motor function was associated with higher enjoyment and social engagement in activities (Wuang & Su, 2012). The CAPE has also been utilized to examine participation in children with autism (Hilton, Crouch, & Isreal, 2008; Hochhauser & Engel-Yeger, 2010; Potvin, Snider, Prelock, Kehayia, & Wood-Dauphinee, 2013). For example, researchers found that content validity and test–retest reliability (r > 0.70) of the CAPE was adequate for a sample of 30 children with autism ages 7–13 (Potvin et al., 2013). Hochhauser and Engel-Yeger also used the CAPE to assess children with high functioning autism were compared to typically developing children. Children with autism had a more limited range of activities, and performed less often and mostly performed activities alone and in their home (Hochhauser & Engel-Yeger, 2010). Wuang, Ho, & Su, (2013) used the CAPE to assess an occupational therapy home-based intervention program in a randomized controlled child for children with intellectual disabilities. The CAPE was given at 10 and

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20 weeks of a 20-week program. Participants included 114 children between ages 6 and 12 years diagnosed with an intellectual disability. Participants were randomly assigned to the occupational therapy home program group or the no occupational home therapy group. Results indicated significant differences in activity participation in children who received the occupational therapy home program versus the children who did not (Wuang et al., 2013). This study indicates how the CAPE can be used to assess changes in participation who receive intervention services. A limitation of the use the CAPE includes that it is not known whether the assessment is applicable to all intellectual or developmental disability diagnoses as it was validated with children who have physical disabilities (for a review see King et al., 2007). Furthermore, for children with autism, future investigation is needed to understand the interpretation of the results of the CAPE for program development for this population (Potvin et al., 2013). In summary, the CAPE has been utilized across various cultures to assess the participation of children with disabilities. 3.1.5 The Assistance to Participate Scale and the Child and Adolescent Scale of Participation and Applications The Assistance to Participation Scale is a succinct parent-reported assessment specifically focuses how much assistance a school-aged receives from a caregiver to participate in play and leisure activities (Bourke-Taylor, Law, Howie, & Pallant, 2009). The standardization sample (n ¼ 152) was made up of children 5–18 years of age with autism, physical disability, or intellectual/learning disability. Bourke-Taylor et al. (2009) reported initial research that supports the psychometrics (adequate internal consistency, factor structure, and construct validity). Furthermore, additional testing with Rasch analysis has supported the instrument (Bourke-Taylor & Pallant, 2013). It contains eight items to address play and leisure: television viewing, listening to music, playing alone inside the house, playing alone outside the house, sharing time with a friend at home, sharing time with a friend at the friend’s home, spending time at a playground or outdoor recreational area, and attending an organized recreational club (e.g., dance lessons or soccer). Items are scored on a Likert scale of 1–5 with 1 indicating unable to participate and 5 indicating able to participate independently). To date, research applications have focused on characterizing how higher need for assistance in children with CP positively correlates with equipment expenses for their families (Bourke-Taylor, Cotter, & Stephan, 2013) and how a child’s need for assistance relates to aspects of mothers’ well being (Bourke-Taylor, Pallant, Law, & Howie, 2013).

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3.1.6 The Child and Adolescent Scale of Participation The Child and Adolescent Scale of Participation (CASP; Bedell, 2006, 2009; Bedell & Coster, 2008) is a parent-report assessment on participation that was developed specifically through integrating parent feedback and aligning the assessment domains conceptually with the ICF with the exception of not addressing learning. Therefore, the CASP examines participation and restriction of participation in home, school, and community life situations as compared to same-aged peers. While the author included both children with brain injuries and those with other disabilities in the standardization (Bedell, 2004), the research applications of the CASP have to date predominantly focused on children with brain injuries Bedell & Coster (2008); Bedell & McDougall (2013). Notably, a youth-report version of this assessment has been recently developed with findings indicating that youths report significantly higher participation than their parents reported for them (McDougall, Bedell, & Wright, 2013).

3.1.7 Summary of Participation Measures We have reviewed research examining the measurement of participation in groups with IDDs that has focused primarily on characterizing levels of participation and relevant factors. The majority of these measures take the perspective of a parent or educator (e.g., PEM-CY). However, recently McDougall et al. (2013) has developed an assessment of participation to include perspectives from the actual youths being studied. Major applications of these assessments indicate that children with IDDs have significant limitations in aspects of participation (e.g., Bedell et al., 2013) and may experience specific limitations in participation such as limited community involvement (e.g., Bedell et al., 2013; Majnemer et al., 2008). One area for further consideration will be the selection of appropriate comparison groups when researchers ask questions related to how a specific disability may engage in participation. In the comparative studies in this section, the researchers chose to compare a disability group with a TD group matched for CA, but not developmental status or mental age (MA). This strategy helps us understand the effect of experience (time) on outcomes. If participation interacts with cognitive performance, this approach of matching groups by CA in contrast to MA (e.g., a MA-matched group with idiopathic IDDs) may confound findings related to participation for a specific disability group (Dykens & Hodapp, 2007). Finally, to our knowledge, only one study examining how participation changes in relationship to intervention for children with IDD exists (Wuang

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et al., 2013). In this study, the CAPE was found capable of detecting change in response to intervention for children with IDDs.

3.2. How Do We Measure Children's Functional Performance? Given that functional performance is likely the foundation that supports children’s participation (Khetani et al., 2013; World Health Organization [WHO], 2001), there is a growing need to measure and document changes in functional performance that occur during or following intervention (Haley, Raczek, Coster, Dumas, & Fragala-Pinkham, 2005). In the past, both researchers and practitioners in the field of intervention/rehabilitation struggled with measuring functional performance in children with disabilities who may have diverse challenges and needs. While adaptive behavior measures existed, researchers emphasized that they lacked more precise information on functional performance (e.g., Haley et al., 1992). In response to this need, measures of functional performance were developed including the Functional Independence Measure for Children (Msall et al., 1994), and another that has become gold standard in pediatric intervention/ rehabilitation—the Pediatric Evaluation of Disability Inventory (PEDI; Haley et al., 1992) and the recently revised PEDI (PEDI-CAT; Haley et al., 2010). 3.2.1 Pediatric Evaluation of Disability Inventory The original PEDI was designed for use by parents, educators, or clinicians to measure the functional performance of children with disabilities from 6 months to 7.5 years of age. Capability, that is what a child can do in an ideal situation, and performance, what a child can do in the actual environment, is measured within the domains of self-care, mobility, and social function. The self-care scale consists of subdomains including: eating, hair brushing, washing, dressing, tooth brushing, and toileting. The mobility scale examines transfer skills, such as getting in and out of a chair, and body transport activities, such as use of stairs or carrying objects during locomotion. The social function domain focuses on the individual within their family and culture by examining the ability to comprehend and communicate, as well as interacting with peers and engaging in play (Haley et al., 1992). The PEDI is distinguished from a developmental model in that it does not focus on children reaching specific motor, cognitive, and social developmental milestones. Instead, the PEDI focuses on characterizing children carrying out everyday activities (Haley et al., 2010).

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The PEDI assesses a child’s ability to perform functional skills, broken out from the simple to the complex, and addresses performance by including levels of caregiver assistance and modification (Haley et al., 1992). Therefore, the Functional Skills and Caregiver Assistance Scale domains are used to measure the level of independence performance the child demonstrates, as well as the level of assistance required. The PEDI allows for flexibility in the use of scales dependent on the relevant context for the individual, such as only examining the mobility scale or examining the caregiver assistance scale. The PEDI has been used in many studies involving children with diverse diagnoses, such as CP, musculoskeletal disorders, and DS (Chen, Tseng, Hu, & Koh, 2010; Kao, Kramer, Liljenquist, Tian, & Coster, 2012; Wiley, Meinzen-Derr, Grether, Choo, & Hughes, 2012). The PEDI is also a valid assessment tool to examine treatment effectiveness, with a number of studies focusing on mobility in CP (e.g., Verkerk et al., 2013). The assessment also has been utilized to measure change in functional performance outcomes for children in intervention programs (Haley et al., 2010). Cross cultural comparisons have also been made as the PEDI has been translated into multiple languages. In one example, Chen et al. (2010) performed a comparison among Taiwanese typically developing children and American children. Results showed that internal consistency and inter-rater reliability was high. Group differences existed in the self-care and social function domains. The authors speculated that child-rearing practices in different cultures would be important for clinicians to consider when developing intervention programs (Chen et al., 2010). 3.2.2 Application of the PEDI Applications of the PEDI are intended for evaluation of individuals or groups in rehabilitation and to detect, as well as quantify, functional performance deficits or delays and can also be used as an outcome measure for program evaluation in research, rehabilitation, or educational settings. For example, the PEDI has been utilized by Blauw-Hospers, Dirks, Hulshof, Bos, and Hadders-Algra (2011) to evaluate a new intervention called the Coping and Caring for Infants with Special Needs (COPCA). In this study, the COPCA was compared to a traditional infant physical therapy in 46 infants with high risk for developmental disorders. The COPCA focused on parent coaching to promote infants to produce motor behaviors. The outcomes were assessed at 3, 6, and 18 months with the Alberta Infant Motor Scales, Mental Developmental Index (MDI) of the Bayley Scales of Infant

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Development (BSID-II), and neurological examination in addition to the PEDI. Results indicated that for children with CP, the PEDI demonstrated positive outcomes with COPCA intervention in the mobility domain. Also, there was a positive correlation with more spent time on communication during the intervention positively associated with self-care domain on PEDI. More time spent on challenging infant to produce motor behavior was associated with lower self-care scores and social domain scores (Blauw-Hospers et al., 2011). The PEDI provided the researchers in this case some effective variables to evaluate the effectiveness of the intervention and help them understand how variations in intervention administration were related to outcomes. In another example, Eigsti, Chandler, Robinson, and Bodkin (2010) examined how the PEDI, in comparison the Mullen Scales of Early Learning (MSEL), would measure change for children receiving early intervention services. The MSEL is a traditional developmental measure that focuses on developmental skills in areas such as expressive language. The study included 34 participants who had received the ENRICH early intervention services in Denver. Measures were taken at 18, 31, and 53 months. A multivariate analysis of variance was used in addition to three change indices. The ES was defined as the difference between the baseline mean and follow-up mean divided by the baseline standard deviation. Standard response mean and minimal detectable change were the other two measures. Results indicated that the only significant scores involved the social scales. The PEDI Social Function Scale standard scores were better able to detect change than both the MSEL Expressive and Receptive Language scales. This study had a small sample size and lack of randomization. There is limited research on intervention outcome measures relating to change and functional performance on children with IDD. More comparative research would be beneficial to assess how effective the PEDI is for evaluating change in intervention services (Eigsti et al., 2010). Some other examples of the application of the PEDI involve usage for descriptive purposes. Wiley et al. (2012) used the PEDI as a functional assessment for individuals with cochlear implants and disabilities. Results demonstrated that receptive language played a role in social functioning for the population. They concluded that using the PEDI was informative for treatment in providing information for specific targeted interventions and program planning (Wiley et al., 2012). In another study, Rogac, Meznaric, Zeviani, Sperl, and Neubauer (2011) used the PEDI for evaluation in children with mitochondrial disease. The PEDI findings indicated

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that there are heterogeneous functional outcomes for children with the disease. The authors highlighted that the PEDI findings provided data that laboratory testing or tasks could not provide in regards to measuring functional outcomes. The authors concluded that functional measures should be a necessary part of evaluation or children with mitochondrial disease because they provide information for clinicians and caregivers regarding potential modifications of environment, social help, and rehabilitation treatments (Rogac et al., 2011). Verkerk et al. (2013) used the PEDI (Dutch version) to assess independence in everyday activities in preschoolers born with very low birth weight without CP (VLBW, n ¼ 143). Data was also obtained from the psychomotor-development index (PDI), and the MDI of the Bayley Scales of Infant Development (2nd edition; BSID-II). The predictive value of the PDI and the MDI were found to be limited. However, results supported the use of the PEDI to monitor functional performance among everyday activities for children with disabilities. The authors suggested that assessment with the PEDI be completed at the entry of school to help develop interventions to support the children in participation in their everyday environments. More research is needed on use of the PEDI and the effect of intervention to improve performance in everyday activities (Verkerk et al., 2013).

3.2.3 Development and Application of the PEDI-CAT The more recently developed PEDI-CAT incorporated feedback on the original PEDI and added a multidimensional computer version that was called the PEDI-MCAT. Users suggested improvements regarding the original PEDI to address: the length of the assessment, relevance to a broader age group, and difficulties for clinicians to complete questions about homebased activities. The PEDI-CAT included items from the mobility and self-care subdomains and had been shown to be accurate and precise (Haley, Pengsheng, Ludlow, & Fragala-Pinkham, 2006). The PEDI-CAT also was developed to reduce response burden and reflect relevance for broader ages (Haley et al., 2010). Coster, Deeney, Haltiwanger, and Haley (2008) and Coster, Haley, Ni, Dumas, and Fragala-Pinkham (2008) examined score agreement, precision, validity, and response burden on a prototype of the PEDI-CAT in the self-care and social functioning scales. The item response theory was used to create item pools to match the estimated functional level of the child. Results of their analysis demonstrated that response burden was reduced, as well as providing accurate and

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valid estimates of functional capabilities (Coster, Deeney, et al., 2008; Coster, Haley, et al., 2008). Haley et al. (2011) examined the accuracy and precision of the PEDICAT among a normative population (n ¼ 2205) and a population with disabilities (n ¼ 617) among ages 0–21 years. A new domain, called Responsibility, was created from the original Caregiver Assistance domain to more intuitively assess how the child or caregiver manages complex tasks such as preparing a meal and planning a weekly schedule. Analyses indicated that the four domains of the PEDI-CAT met precision requirements for clinical practice and research for children with functional performance difficulties (Haley et al., 2011). Dumas et al. (2012) conducted the first study on children with and without disabilities on the PEDI-CAT. The study included 50 children with varying disabilities and 52 children without a disability. The PEDI-CAT was found to reduce test length and provide a precise score by tailoring the items for the difficulty of the child, allowing for administration time to be less than 15 min. The results showed that the PEDI-CAT was able to discriminate between groups of children with and without disabilities, providing information about relative functional strengths and deficits. The authors found high reliability and evidence of validity, with a demonstration of test–retest reliability (Dumas et al., 2012). In examining whether the PEDI-CAT could differentiate functional profiles of individuals with differing disabilities, Kao et al. (2012) compared children with ASDs (n ¼ 108), IDDs (n ¼ 150), and those with typical development matched for CA (TD; n ¼ 2,205) utilizing the Social/Cognitive, Daily Activities, and Responsibility Domains with three cross-sectional age groups of 5, 10, and 15 years of age, respectively. There were no statistically significant results when comparing responses of children with ASD and IDD across all age groups. In addition, unlike Dumas et al.’s (2012) findings for differences between children with and without disabilities, there were no statistically significant differences the groups of 5-year olds across all domains; however, significant differences between groups were found in older ages (e.g., 10 years of age). The ASD group had significantly lower scores in all domains in both the 10-year-old and 15-year-old groups than children without disabilities. The authors interpreted their findings to indicate that the PEDI-CAT focuses on functional performance rather than adaptive behavior and incorporated whatever methods the individual uses, including nonverbal communication and assistive devices. The authors did not have information regarding the participant’s cognitive developmental status, so the authors were unable to control for the influence of cognitive

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performance. The absence of a significant difference on the Social and Cognitive domain scores may suggest that their general cognitive functioning was similar. In the future, more specific group matching for MA, and detailed diagnostic inclusion criteria for the ASD would be helpful in ruling out potential confounds. The authors emphasized that the PEDI-CAT allows for differentiation of children with ASD from those without disabilities; however, differing diagnoses did not result in significantly different functional performance profiles for this study (Kao et al., 2012). 3.2.4 Functional Independence Measure for Children (WeeFIM; Msall et al., 1994) The WeeFIM measures functional performance in the areas of self-care (feeding, grooming, dressing, and bathing), continence, transfers, locomotion, communication, and social skills using either parent-report or observation for children 3–8 years of age. In scoring the WeeFIM, a 7-point ordinal scale is used (1 ¼ complete dependence to 7 ¼ complete independence) with a total score of 126 (Msall et al., 1994). The WeeFIM has been reported to have strong inter-rater reliability and concurrent validity (Ottenbacher et al., 1996, 1997, respectively). Importantly, in a group of toddlers to school-aged children (n ¼ 44), it has been found to have strong concurrent reliability with the PEDI (r  0.88) in the major domains of self-care, mobility, and communication (Zivani et al., 2001). While the WeeFIM is reported less frequently than the PEDI in the literature, it is notable for being used in large, population-based descriptive studies in Australia. For example, it has been used to characterize functional performance patterns of school-aged children with DS (n ¼ 211) in Australia (Leonard, Msall, Bower, Tremont, & Leonard, 2002). Similarly, it has been used to characterize strengths and challenges of having a sibling with IDD (n ¼ 322; Mulroy, Robertson, Aiberti, Leonard, & Bauer, 2008). The WeeFIM has been used to examine outcomes related to an aquatic therapy program in a pilot study (10–17 year-olds with CP; n ¼ 10 treatment; 10 ¼ 10 control; Dorval, Tetreault, & Caron, 1996). In this study, investigators were unable to demonstrate lasting effects of the program using either the WeeFIM or a measure of self-esteem; however, the study was underpowered. Cernak, Stevens, Price, and Shumway-Cook (2008) used the WeeFIM to document progress in functional performance related to a treadmill-training program in a single-case study of a 13-year-old with cerebellar ataxia. Finally, researchers have used the WeeFIM to demonstrate that all domains, with the exception of “Transfers” are sensitive to measuring

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change in functional skills over a 1-year period in children ages 11–87 months with mixed DD such as DS developmental disorder and intellectual disability (n ¼ 250; Ottenbacher et al., 2000). 3.2.5 Summary of Functional Performance Measures Different activities and varying environmental contexts interact with IDD to provide opportunities and challenges for children when performing functional tasks. The PEDI, PEDI-CAT, and WeeFIM were designed to evaluate outcomes in functional performance and develop support for an individual. While these measures show promise in demonstrating intervention effects (Eigsti et al., 2010), further research is needed. Specifically, studies examining how functional measures such as the PEDI and PEDI-CAT may inform research intervention outcomes in contrast to measures of development and adaptive behavior. Moreover, there may be merit to employing multiple instruments to create the most accurate representation of a child’s performance in everyday activities (Kao et al., 2012). Finally, it is not clear whether the PEDI, PED-CAT, or WeeFIM can differentiate between diagnoses (Kao et al., 2012), but the PEDI-CAT can discriminate between typically developing children and children with mixed disabilities (Dumas et al., 2012). Some may argue that demonstrating change in functional performance over time rather than differentiating between diagnostic categories may be the ultimate goal of research in this area (Lollar & Simeonsson, 2005). However, given that some diagnostic groups respond differentially to intervention (e.g., children with DS, Yoder, Woynaroski, Fey, & Warren, 2014) and groups were matched by CA instead of developmental status (MA), more research is needed.

3.3. Assessment That Combines Children's Participation and Functional Performance 3.3.1 The School Function Assessment The School Function Assessment (SFA) evaluates both a student’s participation and functional activity performance in a school environment (Coster, Mancini, & Ludlow, 1999). Identifying and understanding patterns of school function in children with IDDs may be critical because effective engagement in school serves as a foundation for academic learning and achievement. School function involves “a student’s ability to perform important functional activities that support or enable participation in the academic and related social aspects of an educational program” (Coster et al., 1998, p. 2). Examples of school function include using school-related materials appropriately (such

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as writing tools), the ability to move around the school environment independently, the ability to manage self-care and personal needs, and requesting assistance when needed (Coster et al., 1998). A clarification is made between school function and academic learning. Academic learning involves mastering reading, mathematics, and science (Coster et al., 1998). With foundational school function skills, students are able to engage in academic learning without the need for assistance or accommodations. The SFA is comprised of three domains: (I) Participation, (II) Task Supports, and (III) Activity Performance. Participation, evaluates the level at which students participate within the school context (e.g., classroom and playground). Task Supports examines the amount of assistance or help from an adult and adaptations (modifications) that are currently made available to the student during key tasks (e.g., remembering the teacher’s instructions). Activity performance assesses a student’s consistency in performing specific physical and cognitive tasks (e.g., carrying lunch tray). The SFA was standardized on a population of over 300 students with various disabilities attending kindergarten through sixth grade across 112 different sites in the United States using Rasch Item Response Theory methodology. The SFA has demonstrated content and construct validity (Coster et al., 1998). It also has adequate test–retest reliability (r  0.82–0.98) and inter-rater reliability (r > 0.63; Coster et al., 1998; Davies, Soon, Young, & Clausen-Yamaki, 2004). Authors also report adequate content and construct validity measured across multiple studies with disability related service professionals (Coster et al., 1998; Hwang, Davies, Taylor, & Gavin, 2002). 3.3.2 Application of the SFA To date, studies on children with IDDs using the SFA have focused on using it to characterize the specific populations of focus and to examine predictors of function. Leung et al. (2011) evaluated activity and participation using the Vineland Adaptive Behavior Scales (VABS) and SFA in a population of preschoolers with DD (n ¼ 54, 37 males, 17 females; mean age ¼ 66 months) and age-matched typically developing children (n ¼ 54, 34 males, 20 females; mean age ¼ 65 months). Results indicated that the participants with DD had lower scores on both the VABS and the SFA. The authors concluded that preschoolers with DD had poorer adaptive functioning and school participation than the control group. By conducting a bivariate correlation analysis, variables significantly associated with the VABS or SFA scores were then used in multiple regression analysis. Determinants of activity and participation from this analysis included motor proficiency,

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social skills, and ADHD-related symptoms. A limitation of this study was that it only included children who were in an integrated preschool and may not be generalizable to other preschools. Furthermore, the models only accounted for 35–35% of variance in activity and participation, which indicates there are other factors that play a role in activity and participation (Leung et al., 2011). Wuang, Su, and Su (2011) investigated the relationship between executive function, measured by the Wisconsin Card Sorting Test (WCST) and school functions, measured by the School Function Assessment-Chinese Version (SFA-C), in children with developmental coordination disorder (DCD). Participants included 71 children with DCD (41 males and 30 females; mean age ¼ 9.02 years, SD ¼ 0.60) and 70 children (37 males and 33 females; mean age ¼ 8.74 years, SD ¼ 0.79) matched for gender and age. Children with DCD scored lower than the control group on eight SFA-C subscales including: Travel, Recreational Movement, Manipulation with Movement, Using Materials, Written Work, Task and Behavior, Maintaining and Changing Positions, and Participation. Most of the subscales of the SFA-C were significantly correlated with the subscales of the WCST, indicating that executive function is associated with school function and further investigation is warranted to better understand this relationship (Wuang et al., 2011). Our own team used the SFA to characterize the nature of school participation and predictors of performance of functional tasks in the school context for 26 elementary students with DS (mean age ¼ 7.86 years; SD ¼ 1.75; Daunhauer, Fidler, & Will, 2014). Students participated in assessments of cognitive status and language development. Their teachers completed the SFA (Coster et al., 1998) questionnaire and a standardized questionnaire on executive functioning. Results indicated that students demonstrated a pronounced pattern of assistance and adaptation-related needs across various domains of school function. This pattern included the participants having significantly more difficulty in Cognitive-Behavioral Tasks in contrast to Physical Tasks. Areas of greatest challenge included: Safety, Behavior Regulation, Task Behavior/Completion, and Following Social Conventions. In addition, the strongest predictor of overall school function was found to be student executive function skills, as reported by teacher (adjusted R2 ¼ 47, p ¼ 0.003). Findings from this study will inform future intervention for elementary school students with DS. In seeking to understand predictors of school function in children with CP, Huang, Tseng, Chen, Shieh, & Lu, (2013) examined school-aged

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children with CP (n ¼ 167) using the Chinese version of the SFA. The researchers found that the best predictors for performance of cognitivebehavioral tasks were: intellectual disability, prosocial behavior, having an assistant in school, educational placement, and level of fine motor impairment, with the combination of these factors accounting for 73% of the variance. The best predictors for physical task performance were: receiving speech therapy, having diplegia, have a domestic helper, and level of (fine and gross) motor impairment, with the combination of these factors accounting for 83% of the variance. The authors also argued that their findings highlight the role that assistance and accommodations (e.g., from a school assistant) may have in creating optimal functional performance. Gates, Otsuka, Sanders, and McGee-Brown (2008) assessed the relationship between SFA and a parent-report measure of gross motor function in everyday life, the Pediatric Outcomes Data Collection Instrument (PODCI), to determine whether PODCI findings correlated with findings on the SFA. Participants included 102 children diagnoses with CP (60 males, 42 females, M ¼ 11 years 8 months). Results revealed a strong association between the SFA and PODCI, particularly with PODCI items that indicated how much assistance a child needed with motor tasks (e.g., amount of assistance need to sit or stand). Treatment programs examining multiple functional goals at the same time require the ability to assess participation dimension in multiple settings, such as in a clinical setting, at home, in the community, or at school (Gates et al., 2008). This study demonstrated how the SFA could be utilized with other measures in contexts other than school, such as the clinic, to provide information about the child’s performance in a school setting.

3.3.3 Summary of the SFA Applications The SFA is notable for connecting the concepts of participation, task support, and activity (functional) performance. Recent research using the SFA has highlighted that it correlates with other measures of function such as the VABS and PODCI (Gates et al., 2008; Leung et al., 2011) and that we are beginning to understand predictors of school function that may provide targets for intervention (Daunhauer et al., 2014; Huang et al., 2013; Wuang et al., 2011). Given the findings highlighted in this review, potential targets to improve school function include executive functioning and contextual factors such as a school (classroom) assistant.

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4. DISCUSSION Recent research focusing on children with IDDs has highlighted many disparities in regards to the frequency, level of involvement, and types of participation they engage in when compared to other groups, as well as challenges in functional performance thought to a foundation of participation. In this chapter, we reviewed current knowledge regarding measurement of both functional performance and participation in children with IDDs. Participation is often consistently defined as the engagement in life situations such as learning and play. However, this definition can be interpreted in a gamut of ways and further refinement is needed. For the purpose of this review, rather than using the ICF term activity (World Health Organization [WHO], 2001, 2007) which can be confusing due to its omnipresence in both research, assessments, and popular media, we incorporated the term functional performance to include those activities common to all children such as dressing and feeding based on Haley et al.’s (1992) discussion of function and capabilities. Despite the challenges of operationalization, the ICF and the evolution of the concept of participation has underscored the importance stakeholders—researchers, service providers, individuals with disabilities, and their families—place on meaningful participation in everyday life.

4.1. Parsing Participation In order to move the measurement, and eventually outcomes, of participation forward for children with IDDs, clearly it would be helpful for researchers to reach a high level of agreement regarding the operationalization of participation and activity/functional performance (Whiteneck, 2010). The various interpretations of these terms were reflected in a systematic review examining variables involved in participation frequency in leisure activities across children with different diagnoses. Bult, Verschuren, Jongmans, Lindeman, and Ketelaar (2011) found that important factors related to participation in these activities included: gender, cognitive, language, and manual abilities, and gross motor functions. The authors highlighted that participation was examined with a multitude of measures. The measures of participation included in this systematic review comprised of participation measures (CAPE), as well as measures of functional performance (PEDI) and adaptive behavior (VABS). Given the soft boundaries of the term participation, it is understandable that this important array of measurements would be categorized under the term of

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participation. The confusion in defining participation, in particular, can also be viewed as reflecting the highly complex, multifaceted, and perhaps very human nature of the concept (Granulund, 2013). A deeper consensus regarding the operationalization of participation will support effective intervention research and outcomes for this population (Whiteneck, 2010).

4.2. Proxy Reporting Also, related to the issue of rigorous measurement is the issue of proxy reporting. Use of reports from parents, other caregivers, and teachers is common in research characterizing children with IDD, especially given the level of involvement of caregivers in their children’s lives (e.g., King, Imms, et al., 2013; King, Shields, et al., 2013). However, as emphasized by McDougall et al.’s (2013) findings that adolescents reported significantly different participation than their parents, proxy reporting is an imperfect response to the challenging problem of accurately reflecting the voices and opinions of individuals, particularly developmental younger children, with IDD. While challenging, nonetheless, based on the human rights framework driving improvements for life outcomes for individuals with IDD (McCabe et al., 2011; McDonald, 2012) using an aspect of measurement that considers the individual child’s voice must be considered when possible for both research and intervention. It is possible, that perhaps with accommodations or assistive technology, that researchers can at least start to gauge the perceptions of the focus population in areas such as level of enjoyment when performing an activity such as cooking or participating in a particular event such as family graduation (McDonald, 2012). Including the individual child’s voice in measurement of both participation and functional performance could be a critical element to guide intervention and intervention planning.

4.3. Sampling Considerations Another important consideration related to measurement is the choice and use of sample groups in research examining and validating participation measures and whether the current array of assessments of participation can adequately assess disability-specific samples in children with IDDs (e.g., children with fragile X syndrome). Most of the participation and functional performance assessments examined in this review utilized disability-general standardization samples. For example, in analyzing the psychometric properties of the PEM-CY, Coster et al. (2011) studied a mixed group of children

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who varied widely in both age and disabilities (e.g., developmental delay 26% and orthopedic impairment 19%). So, is it advisable for a researcher from the field of IDD to adopt participation measures such as these? To date, researchers are discovering evidence that these assessments are reliable with IDD populations such as children with ASD (e.g., Potvin et al., 2013). Also, researchers are highlighting outcomes and potential targets for interventions (Daunhauer et al., 2014; Wuang & Su, 2012) through conducting within-group analyses. Using this approach, researches have discovered within-syndrome strengths and challenges. For example, Wuang and Su (2012) found that children with DS had more participation in informal activities than formal activities and Daunhauer et al. (2014) found a specific profile of strengths (e.g., motor abilities) and challenges (e.g., safety awareness and behavioral regulation) in elementary-aged students with DS. As highlighted in the Summary of Participation Measures, the considerations become stickier when defining comparison groups. The choice of a comparison group is often a lively topic of conversation amongst IDD researchers (Dykens & Hodapp, 2007). In the past approximately two decades, IDD researchers have discovered and been steeped in characterizing phenotypic profiles (e.g., Fidler, Hepburn, & Rogers, 2005) to meet the charge to develop disability-specific interventions through studying carefully defined groups classified by characteristics such as genotype (Guralnick, 2005). As described earlier in this review, it is helpful to remember that the primary goal of assessing participation and functional performance is to understand strengths and challenges to guide and evaluate intervention related to engagement in everyday life rather than to understand whether or not performance is developing in typical manner. Given the potentially informative data IDD researchers could obtain from use of these measures, it appears that by following Guralnick’s (2005) caveat to utilize carefully defined samples, along with adding healthy dose of conservatism and continual evaluation of coming research, that using these assessments is indeed warranted by researchers in the field of IDD. In summary, the needs of individuals with IDDs and their families must be held at the forefront of research conducted in this area. Currently, research indicates that children with IDDs experience limitations in participation (e.g., King, Imms, et al., 2013; King, Shields, et al., 2013; Law et al., 2013; Verschuren et al., 2013) that are likely moderated by challenges in functional performance (e.g., Khetani et al., 2013) and environmental factors (Anaby, Law, et al., 2014; Khetani et al., 2013). These restrictions in

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engagement may extend into adulthood (Taylor & Hodapp, 2012). Answering research questions regarding the participation and functional performance needs of the current and coming generation of individuals with IDDs will have many challenges as outlined above. However, there is also the potential through the study of participation (e.g., involvement, supports) along with carefully defined samples, and perhaps further conversation and collaboration between disciplines, that we will be able to transform our current thinking regarding outcomes for this population.

REFERENCES Anaby, D., Law, M., Bedell, G., Khetani, M., Avery, L., & Teplicky, R. (2014). The mediating role of the environment in explaining participation of children and youth with and without disabilities across home, school and community. Archives of Physical Medicine and Rehabilitation, 95, 908–917. http://dx.doi.org/10.1016/j.apmr.2014.01.005. Anastasiadi, I., & Tzetzis, G. (2013). Construct validation of the Greek version of the Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities of Children (PAC). Journal of Physical Activity & Health, 10, 523–532. Badia, M., Longo, E., Orgaz, M. B., & Gomez-Vela, M. (2013). The influence of participation in leisure activities on quality of life in Spanish children and adolescents with cerebral palsy. Research in Developmental Disabilities, 34, 2864–2871. http://dx.doi.org/ 10.1016/j.ridd.2013.06.017. Badley, E. (2008). Enhancing the conceptual clarity of the activity and participation components of the International Classification of Functioning, Disability, and Health. Social Science & Medicine, 66, 2335–2345. http://dx.doi.org/10.1016/j.socscimed.2008.01.026. Bedell, G. M. (2004). Developing a follow-up survey focused on participation of children and youth with acquired brain injuries after discharge from inpatient rehabilitation. NeuroRehabilitation, 19, 191–205. Bedell, G. (2006). Research update: The Child and Adolescent Scale of Participation. Brain Injury Professional, 3, 14. Bedell, G. (2009). Further validation of the Child and Adolescent Scale of Participation (CASP). Developmental Neurorehabilitation, 12, 342–351. http://dx.doi.org/10.1080/ 17518420903087277. Bedell, G., & Coster, W. (2008). Measuring participation of school-aged children with traumatic brain injuries: Considerations and approaches. The Journal of Head Trauma Rehabilitation, 23, 220–229. http://dx.doi.org/10.1097/01.HTR.0000327254.61751.e7. Bedell, G., Coster, W., Law, M., Liljenquist, K., Kao, Y. C., Teplicky, R., et al. (2013). Community participation, supports, and barriers of school-age children with and without disabilities. Archives of Physical Medicine and Rehabilitation, 94, 315–323. http://dx.doi. org/10.1016/j.apmr.2012.09.024. Bedell, G. M., Khetani, M. A., Cousins, M. A., Coster, W. J., & Law, M. C. (2011). Parent perspectives to inform development of measures of children’s participation and environment. Archives of Physical Medicine and Rehabilitation, 92, 765–773. http://dx.doi.org/ 10.1016/j.apmr.2010.12.029. Bedell, G., & McDougall, J. (2013). The Child and Adolescent Scale of Environment (CASE): Further validation with youth who have chronic health conditions. Early on line publication Developmental Neurorehabilitation. http://dx.doi.org/10.3109/ 17518423. 2103.855273.

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