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Research Article
Issue Date: September/October 2016
Published Online: July 28, 2016
Updated: January 01, 2021
Health-Promoting Physical Activity of Children Who Use Assistive Mobility Devices: A Scoping Review
Author Affiliations
  • Tracy L. Jirikowic, PhD, OTR/L, FAOTA, is Associate Professor, Division of Occupational Therapy, Department of Rehabilitation Medicine, University of Washington, Seattle; tracyj@uw.edu
  • Cheryl I. Kerfeld, PhD, PT, is Acting Assistant Professor, Division of Physical Therapy, Department of Rehabilitation Medicine, University of Washington, Seattle
Article Information
Assistive Technology / Health and Wellness / Obesity / Pediatric Evaluation and Intervention / Rehabilitation, Participation, and Disability / Special Issue: Research Articles
Research Article   |   July 28, 2016
Health-Promoting Physical Activity of Children Who Use Assistive Mobility Devices: A Scoping Review
American Journal of Occupational Therapy, July 2016, Vol. 70, 7005180050. https://doi.org/10.5014/ajot.2016.021543
American Journal of Occupational Therapy, July 2016, Vol. 70, 7005180050. https://doi.org/10.5014/ajot.2016.021543
Abstract

Children with physical disabilities who use assistive mobility devices (AMDs) are at risk for obesity and other secondary health conditions. Habitual physical activity is one lifestyle factor that may prevent obesity and contribute to overall health, and an active lifestyle in childhood improves prospects for lifelong healthy behaviors. Child, family, and environmental facilitators and barriers influence health-promoting physical activity (HPPA) for children without disabilities, but comparable models and levels of understanding for children who use AMDs are lacking. In this scoping review, we identified a similar set of child, family, and environmental facilitators and barriers relevant to HPPA participation among children who use AMDs. Noted gaps in the literature included limited reporting of AMD use, inconsistent HPPA definitions, and inadequate measurement tools for children who are nonambulatory. The identified child, family, and environmental factors provide a framework for occupational therapy practitioners and interprofessional teams to develop HPPA opportunities and interventions for an underserved population.

Children with physical disabilities are more likely to be sedentary and, therefore, to have lower levels of health-promoting physical activity (HPPA) and higher rates of obesity than children without disabilities (Buffart, Roebroeck, Rol, Stam, & van den Berg-Emons, 2008; Maher, Williams, Olds, & Lane, 2007; Rimmer & Rowland, 2008). Obesity rates for children with disabilities ages 2–17 yr are approximately 38% higher than for children without disability (Centers for Disease Control and Prevention [CDC], 2010). For children with disabilities, obesity represents a critical risk factor for developing or worsening of secondary problems, such as fatigue and pain, which can further exacerbate impaired mobility and participation in daily activities (Rimmer, Rowland, & Yamaki, 2007). Chronic and secondary impairments associated with sedentary behaviors and obesity in children and adolescents with disabilities often continue into adulthood, further restricting options for exercise, leisure activities, and productive work (Rimmer et al., 2007) and contributing to even higher rates of obesity (36%) later in life (CDC, 2010).
Engagement in HPPA is a lifestyle factor that can prevent or mitigate secondary conditions, such as obesity, fatigue, pain, and osteoporosis (Rimmer, Chen, McCubbin, Drum, & Peterson, 2010). Regular HPPA can improve a child’s health and function, regardless of the presence of a chronic disease or disability (U.S. Department of Health and Human Services [HHS], 2008), providing physical (e.g., aerobic capacity, balance, flexibility, strength) and psychological (e.g., functional independence, self-esteem, social integration, life satisfaction) benefits (Durstine et al., 2000; Rimmer & Rowland, 2008). Physically active lifestyles in childhood are associated with greater adherence to exercise and physical activity in adulthood (Rimmer et al., 2010).
Children who use assistive mobility devices (AMDs; e.g., wheelchairs, walkers, crutches, canes) may experience even greater restrictions in HPPA, and mobility impairments place both children and adults at higher risk for obesity and other secondary health problems (Bandini, Curtin, Hamad, Tybor, & Must, 2005; Gorter, Noorduyn, Obeid, & Timmons, 2012). In the United States, more than 6.8 million people living outside of institutions used AMDs, including 145,000 children younger than age 18 yr (Kaye, Kang, & Laplante, 2000). Approximately 40,000 children and youth ages 13–16 yr used AMDs to help get around in school settings: 30,760 used wheelchairs; 6,000 used crutches; 1,480 used canes; and 9,090 used walkers (Wagner, Newman, Cameto, & Levine, 2006).
Promotion of HPPA and its subsequent physical and mental health benefits for children of all ages and abilities is a national public health priority (CDC, 2008, 2010; HHS, 2008, 2016). Health and well-being are linked to the occupations in which people participate in HPPA, and health promotion is a component of occupational therapy’s scope of practice (American Occupational Therapy Association, 2014). Daily routines, habits, and lifestyle choices that include and incorporate HPPA can enhance physical and mental health and well-being and contribute to a reduction in secondary health conditions, such as obesity (Reingold & Jordan, 2013).
Determinants associated with obesity in people with disabilities are complex (Fox, Witten, & Lullo, 2014). In recent systematic reviews, researchers have reported child, family, and environmental facilitators of and barriers to HPPA among children with physical disabilities (Bloemen, Backx, et al., 2015; Shields, Synnot, & Barr, 2012). Factors related to HPPA have also been examined among children with cerebral palsy (Keawutan, Bell, Davies, & Boyd, 2014). However, to date, in most studies, researchers have examined children who were ambulatory without the use of AMDs, or clear indicators of physical function or AMD use were not addressed. A knowledge gap exists regarding what helps or hinders HPPA participation in this subgroup of children with physical disabilities. HPPA has been identified as an important lifestyle factor that can prevent obesity and secondary health conditions among children with disabilities (McPherson, Keith, & Swift, 2014). A better understanding of facilitators and barriers, specifically those that may be modifiable, can inform research and clinical interventions to help children who use AMDs engage in HPPA as part of their daily routines, habits, and lifestyles.
Method
Design
Scoping reviews have become a common approach to reviewing broad questions in health research evidence (Arksey & O’Malley, 2005). We completed a scoping review of peer-reviewed literature and full-text dissertations and theses following guidelines presented by Levac, Colquhoun, and O’Brien (2010)  to explore facilitators of and barriers to HPPA among children who use AMDs. A systematic protocol regarding this scoping review was developed a priori, including search strategy, inclusion and exclusion criteria, data extraction, and data analysis.
Search Strategy
With the help of an experienced librarian, we completed a search of the following electronic databases to identify relevant studies: PubMed, CINAHL, Eric, Cochrane, Medline, Embase, PsycINFO, ProQuest, and Pedro. Hand searches were made of publications related to the topic. We also searched reference lists of primary articles and relevant systematic and scoping reviews.
Search terms were selected on the basis of common conditions associated with use of AMDs, types of AMDs, and outcomes of interest (e.g., physical activity, obesity) as well as associated child, family, and environmental determinants. The following search terms were used: developmental disability, disability, obesity, physical activity, sedentary, lifestyle, children, facilitators, barriers, environment, fitness, overweight, body mass index (BMI), exercise, parent factors, child factors, determinants, cerebral palsy, spina bifida, spinal cord injury, Duchenne’s muscular dystrophy, juvenile rheumatoid arthritis, arthrogryposis, traumatic brain injury, orthopedic impairment, assistive mobility device, assistive technology, wheelchair, walkers, crutches, and canes. For one example of a search strategy using the PubMed database, see Supplemental Appendix A, available online at http://otjournal.net; navigate to this article, and click on “Supplemental Materials.”
Studies were included if (1) factors were investigated that supported or hindered participation in habitual physical activities; (2) participants included children ages 6–18 years with a physical disability who used an AMD or parents, caregivers, or community services providers (e.g., teachers, community programs); (3) they were completed between January 1, 2005, and December 1, 2015; and (4) they were written in English. Excluded studies were systematic reviews (but the studies identified by the review were assessed), study protocols and intervention studies, and articles that did not classify the functional ability of a child or were not explicit about the participants’ use of an AMD.
Data Extraction
The flow diagram (Figure 1) details the study selection process (Moher, Liberati, Tetzlaff, Altman, & the PRISMA Group, 2009). A database in Excel (Microsoft Corp., Redmond, WA) was created for data entry and management, which enabled the identification of study similarities, study differences, and gaps in the literature. We screened and assessed full-text articles for eligibility. We independently extracted study characteristics, including authors, location, design, outcome measures, participant numbers, children’s age range, sex, type of disability, level of function, AMD use, and factors that facilitate or hinder HPPA of children who use AMDs. We reached consensus through discussion without any discrepancies for the final study selection process.
Figure 1.
Flow diagram detailing the study selection process.
Figure 1.
Flow diagram detailing the study selection process.
×
Data Analysis
We used an ecological model influenced by person, environment, and occupation (Bronfenbrenner, 1978; Law et al., 1996; Rimmer, 2006) as well as the International Classification of Functioning, Disability and Health (World Health Organization [WHO], 2001) frameworks to define and categorize the child, family, and environmental facilitators and barriers potentially influencing HPPA in children who use AMDs and the presumably complex interplay among the developing child, the family, and the environmental contexts in which the child is involved. Child factors were internal personal characteristics, including physical body structures and function (that may be primary or secondary impairments related to the child’s disability) and psychological function encompassing child attitudes and knowledge about HPPA, child interests and motivation, and perceived self-efficacy. Family factors included characteristics of the family structure; demographics (e.g., resources, socioeconomic status); and parent attitudes, values, and knowledge about child HPPA and the impact that it has on the child’s participation in HPPA. Environmental factors were defined as characteristics and qualities of the physical and social environment, including HPPA opportunities that were inclusive or specialized and those done formally or informally in the home, school, and community. Specifically, these factors involved access to programs, physical barriers in the built environment, attitudes, and the availability of specialized services and social supports. After identifying pertinent facilitators and barriers from each full-text study reviewed, we categorized them as child, family, or environmental factors. Discrepancies were resolved through discussion and consensus.
Results
The initial database search resulted in 6,326 articles. After duplications were removed and titles and abstracts were screened, 186 full-text articles were assessed for eligibility. When inclusion and exclusion criteria were applied, 19 articles were included in the qualitative synthesis (Figure 1). Studies were published between 2005 and 2015; the studies had varied qualitative and quantitative study designs, outcome measures, types of diagnosis, sample sizes and ages, and ways of reporting the participants’ function or use of AMDs (Table 1).
Table 1.
Articles Included in the Synthesis
Articles Included in the Synthesis×
StudyLocationDesignMeasuresDemographicsType of DisabilityAMD Level of Function
1. Anderson, Bedini, & Moreland (2005) United StatesQualitativeSemistructured interviewsChildren, N = 14 girls.
Age range = 10–16 yr; M = 13 yr.
CP (n = 6), SB (n = 5),
OI (n = 2), other (n = 1)
None (n = 1), walker (n = 2), manual wheelchair (n = 7), power wheelchair (n = 3)
2. Bloemen, Verschuren, et al. (2015) NetherlandsQualitativeSemistructured interviewsParents, n = 44; children, n = 44 (25 boys, 19 girls).
Age range = 4–18 yr.
SBTotal ambulatory (n = 3), community ambulatory (n = 8), household ambulatory (n = 6), nonambulatory (n = 27)
3. Carter et al. (2014) United KingdomQualitativeObservation, focus group, interviewParents, n = 10; children, n = 37; siblings n = 2; stakeholders, n = 14.Wheelchair
4. Hunter (2009) United StatesQualitativeSemistructured interviewsParents, n = 23; children, n = 23 (13 boys, 10 girls).
Age range = 9–17 yr; M = 14 yr.
SB (n = 16), CP (n = 4), Calder regression (n = 1), SCI (n = 1), multiple spinal leaks (n = 1)Wheelchair
5. King et al. (2013) Australia, Canada, United StatesCross-sectional surveyCAPEChildren, N = 1,076 (611 boys, 465 girls).
Age range = 6–20 yr.
CPGMFCS: 358 Level 1, 405 Levels 2 and 3, 313 Levels 4 and 5
6. Lauruschkus, Westbom, Hallström, Wagner, & Nordmark (2013) SwedenCross-sectional surveyFrequencyChildren, N = 364 (218 boys, 146 girls).
Age range = 7–17 yr.
CPGMFCS: 158 Level 1, 71 Level 2, 28 Level 3, 59 Level 4, 48 Level 5
7. Lauruschkus, Nordmark, & Hallström (2015) SwedenQualitativeFocus group, interviewChildren, N = 16 (7 boys, 9 girls).
Age range = 8–11 yr; M = 9 yr.
CPGMFCS: 11 Level 1 and 2, 2 Level 3, 2 Level 4, 1 Level 5
8. Law, Petrenchik, King, & Hurley (2007) CanadaCross-sectional surveyCHIEF, ASK, SDQChildren, N = 427 (229 boys, 198 girls).
Age range = 6–14 yr.
CP, SB, ABI, DD<25% ASK
9. Luther (2010) United StatesQualitativeSemistructured interviewsChildren, N = 12 (6 boys, 6 girls).
Age range = 6–12 yr; M = 10 yr, 1 mo.
SBWheelchair
10. Maher, Williams, Olds, & Lane (2007) AustraliaCross-sectional surveyPAQ–AChildren, N = 112 (76 boys, 36 girls).
Age range = 11–17 yr; M = 13 yr, 11 mo.
CPGMFCS: 42 Level 1, 27 Level 2, 10 Level 3, 17 Level 4, 15 Level 5
11. Majnemer et al. (2008) CanadaCross-sectional surveyCAPE, GMFM, GMFCS, Leiter, PedsQL, DMQ, SDQ, IOF, PSIChildren, N = 67 (42 boys, 25 girls).
Age range = 6–12 yr.
CPGMFCS: 59% Level 1, 23% Level 2, 18% Levels 3–5
12. Ortiz-Castillo (2011) United StatesCross-sectional surveyPASIPD, PADSChildren, N = 93 (56 boys, 37 girls).
Age range = 12–18 yr.
CP (n = 28), SB (n = 21), MD (n = 16), SCI (n = 9), other (n = 19)Manual wheelchair (n = 46), power wheelchair (n = 31), crutches (n = 14), walker (n = 11), cane (n = 4)
13. Palisano et al. (2009) United StatesCross-sectional surveyCAPE, GMFCSChildren, N = 500 (277 boys, 223 girls).
Age range = 6–21 yr; M = 12 yr, 4 mo.
CPGMFCS: 128 Level 1, 126 Level 2, 94 Level 3, 71 Level 4, 81 Level 5
14. Rose, McDonnell, & Ellis (2007) United StatesCross-sectional surveyAuthor questionnaire, minutes of PETeachers, n = 35; children, n = 170.
M age = 15 yr, 8 mo.
Multiple disabilities, intellectual disabilities, orthopedic impairments, ABI30% severe multiple disabilities, 47.6% intellectual disabilities
15. Shields & Synnot (2014) AustraliaQualitativeTwo-question surveySport and recreation personnel, N = 24.
16. Shields, Synnot, & Kearns (2015) AustraliaCross-sectional surveyCAPEChildren, N = 286 (177 boys, 109 girls).
Age range = 6–18 yr; M = 11 yr, 5 mo.
Physical (n = 77), intellectual (n = 67), multiple (n = 93), other (n = 49)26.9% mild, 23.4% moderate, 12.6% severe
17. Shikako-Thomas et al. (2013) CanadaCross-sectional surveyGMFM, GMFCS, MACS, VABS–II, CAPE, PAC, FES, SPPA, DMQ, SDQ, ECEQChildren, N = 187 (110 boys, 75 girls).
Age range = 12–20 yr; M = 15 yr, 4 mo.
CPGMFCS: 55 Level 1, 45 Level 2, 13 Level 3, 19 Level 4, 39 Level 5
18. Vogts, Mackey, Ameratunga, & Stott (2010) New ZealandCross-sectional surveyCHIEFParents, n = 32; children, n = 32 (15 boys, 17 girls).
Age range = 6–16 yr; M = 10 yr, 1 mo.
CPGMFCS: 23 Levels 1 and 2, 5 Level 3, 4 Level 5
19. Wiart, Darrah, Kelly, & Legg (2015) CanadaQualitativeSemistructured interviewsProgram staff, n = 36; parents, n = 13 (children’s age range = 7–17 yr).CP (n = 9), SB (n = 2), DCD (n = 1), thoracic lipoma (n = 1)GMFCS: 8 Levels 1 and 2, 1 Level 3, 3 Level 4, 1 Level 4 and 5
Table Footer NoteNote. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.
Note. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.×
Table 1.
Articles Included in the Synthesis
Articles Included in the Synthesis×
StudyLocationDesignMeasuresDemographicsType of DisabilityAMD Level of Function
1. Anderson, Bedini, & Moreland (2005) United StatesQualitativeSemistructured interviewsChildren, N = 14 girls.
Age range = 10–16 yr; M = 13 yr.
CP (n = 6), SB (n = 5),
OI (n = 2), other (n = 1)
None (n = 1), walker (n = 2), manual wheelchair (n = 7), power wheelchair (n = 3)
2. Bloemen, Verschuren, et al. (2015) NetherlandsQualitativeSemistructured interviewsParents, n = 44; children, n = 44 (25 boys, 19 girls).
Age range = 4–18 yr.
SBTotal ambulatory (n = 3), community ambulatory (n = 8), household ambulatory (n = 6), nonambulatory (n = 27)
3. Carter et al. (2014) United KingdomQualitativeObservation, focus group, interviewParents, n = 10; children, n = 37; siblings n = 2; stakeholders, n = 14.Wheelchair
4. Hunter (2009) United StatesQualitativeSemistructured interviewsParents, n = 23; children, n = 23 (13 boys, 10 girls).
Age range = 9–17 yr; M = 14 yr.
SB (n = 16), CP (n = 4), Calder regression (n = 1), SCI (n = 1), multiple spinal leaks (n = 1)Wheelchair
5. King et al. (2013) Australia, Canada, United StatesCross-sectional surveyCAPEChildren, N = 1,076 (611 boys, 465 girls).
Age range = 6–20 yr.
CPGMFCS: 358 Level 1, 405 Levels 2 and 3, 313 Levels 4 and 5
6. Lauruschkus, Westbom, Hallström, Wagner, & Nordmark (2013) SwedenCross-sectional surveyFrequencyChildren, N = 364 (218 boys, 146 girls).
Age range = 7–17 yr.
CPGMFCS: 158 Level 1, 71 Level 2, 28 Level 3, 59 Level 4, 48 Level 5
7. Lauruschkus, Nordmark, & Hallström (2015) SwedenQualitativeFocus group, interviewChildren, N = 16 (7 boys, 9 girls).
Age range = 8–11 yr; M = 9 yr.
CPGMFCS: 11 Level 1 and 2, 2 Level 3, 2 Level 4, 1 Level 5
8. Law, Petrenchik, King, & Hurley (2007) CanadaCross-sectional surveyCHIEF, ASK, SDQChildren, N = 427 (229 boys, 198 girls).
Age range = 6–14 yr.
CP, SB, ABI, DD<25% ASK
9. Luther (2010) United StatesQualitativeSemistructured interviewsChildren, N = 12 (6 boys, 6 girls).
Age range = 6–12 yr; M = 10 yr, 1 mo.
SBWheelchair
10. Maher, Williams, Olds, & Lane (2007) AustraliaCross-sectional surveyPAQ–AChildren, N = 112 (76 boys, 36 girls).
Age range = 11–17 yr; M = 13 yr, 11 mo.
CPGMFCS: 42 Level 1, 27 Level 2, 10 Level 3, 17 Level 4, 15 Level 5
11. Majnemer et al. (2008) CanadaCross-sectional surveyCAPE, GMFM, GMFCS, Leiter, PedsQL, DMQ, SDQ, IOF, PSIChildren, N = 67 (42 boys, 25 girls).
Age range = 6–12 yr.
CPGMFCS: 59% Level 1, 23% Level 2, 18% Levels 3–5
12. Ortiz-Castillo (2011) United StatesCross-sectional surveyPASIPD, PADSChildren, N = 93 (56 boys, 37 girls).
Age range = 12–18 yr.
CP (n = 28), SB (n = 21), MD (n = 16), SCI (n = 9), other (n = 19)Manual wheelchair (n = 46), power wheelchair (n = 31), crutches (n = 14), walker (n = 11), cane (n = 4)
13. Palisano et al. (2009) United StatesCross-sectional surveyCAPE, GMFCSChildren, N = 500 (277 boys, 223 girls).
Age range = 6–21 yr; M = 12 yr, 4 mo.
CPGMFCS: 128 Level 1, 126 Level 2, 94 Level 3, 71 Level 4, 81 Level 5
14. Rose, McDonnell, & Ellis (2007) United StatesCross-sectional surveyAuthor questionnaire, minutes of PETeachers, n = 35; children, n = 170.
M age = 15 yr, 8 mo.
Multiple disabilities, intellectual disabilities, orthopedic impairments, ABI30% severe multiple disabilities, 47.6% intellectual disabilities
15. Shields & Synnot (2014) AustraliaQualitativeTwo-question surveySport and recreation personnel, N = 24.
16. Shields, Synnot, & Kearns (2015) AustraliaCross-sectional surveyCAPEChildren, N = 286 (177 boys, 109 girls).
Age range = 6–18 yr; M = 11 yr, 5 mo.
Physical (n = 77), intellectual (n = 67), multiple (n = 93), other (n = 49)26.9% mild, 23.4% moderate, 12.6% severe
17. Shikako-Thomas et al. (2013) CanadaCross-sectional surveyGMFM, GMFCS, MACS, VABS–II, CAPE, PAC, FES, SPPA, DMQ, SDQ, ECEQChildren, N = 187 (110 boys, 75 girls).
Age range = 12–20 yr; M = 15 yr, 4 mo.
CPGMFCS: 55 Level 1, 45 Level 2, 13 Level 3, 19 Level 4, 39 Level 5
18. Vogts, Mackey, Ameratunga, & Stott (2010) New ZealandCross-sectional surveyCHIEFParents, n = 32; children, n = 32 (15 boys, 17 girls).
Age range = 6–16 yr; M = 10 yr, 1 mo.
CPGMFCS: 23 Levels 1 and 2, 5 Level 3, 4 Level 5
19. Wiart, Darrah, Kelly, & Legg (2015) CanadaQualitativeSemistructured interviewsProgram staff, n = 36; parents, n = 13 (children’s age range = 7–17 yr).CP (n = 9), SB (n = 2), DCD (n = 1), thoracic lipoma (n = 1)GMFCS: 8 Levels 1 and 2, 1 Level 3, 3 Level 4, 1 Level 4 and 5
Table Footer NoteNote. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.
Note. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.×
×
We examined an almost equal number of qualitative and quantitative studies that included authors from a variety of different countries. Qualitative phenomenological techniques and cross-sectional studies were more the norm. The Children’s Assessment of Participation and Enjoyment (CAPE; King et al., 2004) measure was used most frequently with the quantitative cross-sectional studies of HPPA participation. Sample sizes and mean age of study participants varied. All studies included children ages 6–18 yr; however, the final age span was 4–20 yr because we did not exclude studies if the majority of participants were in the targeted age range. We only included studies that identified in some way the functional level of the child and reported or implied use of an AMD or type of AMD used. Figure 2 illustrates identified child, family, and environmental factors; highlights and examples are provided in the sections that follow.
Figure 2.
Child, family, and environmental factors, with corresponding articles from Table 1 in parentheses.
Note. AMD = assistive mobility device; SES = socioeconomic status.
Figure 2.
Child, family, and environmental factors, with corresponding articles from Table 1 in parentheses.
Note. AMD = assistive mobility device; SES = socioeconomic status.
×
Child Factors
Several child facilitators and barriers reflecting body structures and function, personal factors, and psychological factors influenced HPPA participation. The child’s physical level of function was a major factor in patterns of participation, with multiple studies indicating that children with more severe physical disability (e.g., Gross Motor Function Classification Scale [GMFCS; Palisano et al., 1997 ] Levels 3 and 4 and, particularly, Level 5) participated less frequently in active play, leisure, and recreational activities (King et al., 2013; Lauruschkus, Westbom, Hallström, Wagner, & Nordmark, 2013; Law, Petrenchik, King, & Hurley, 2007; Maher et al., 2007; Majnemer et al., 2008; Palisano et al., 2009; Shields, Synnot, & Kearns, 2015; Shikako-Thomas et al., 2013). Child age was also significant; as children got older, their participation in HPPA generally decreased (King et al., 2013; Lauruschkus et al., 2013; Law et al., 2007; Luther, 2010; Maher et al., 2007; Palisano et al., 2009; Shields et al., 2015). Personal factors, such as changing interests and motivation, accentuated by additional physical factors were barriers that emerged in association with age. For example, perceived differences in abilities compared with peers without disabilities became more pronounced as activities became more competitive or skill-based. Physical factors, such as overweight or obesity, also contributed to declining interest in and motivation to engage in HPPA over time and preferences for more sedentary activities (Bloemen, Verschuren, et al., 2015; Luther, 2010). Children’s perceived competence (e.g., as an athlete), motivation, and attitude about HPPA (e.g., perceived health benefits or positive feelings about the activity—“It’s good for me,” or “I feel good when I am active”) were influential HPPA facilitators (Anderson, Bedini, & Moreland, 2005; Bloemen, Verschuren, et al., 2015; Carter et al., 2014; Lauruschkus, Nordmark, & Hallström, 2015; Majnemer et al., 2008; Ortiz-Castillo, 2011).
Family Factors
Family factors included financial resources, transportation, time, concerns about safety, and the availability and presence of family members to engage in the activity with the child or to provide physical assistance with personal care before, during, or after the activity (e.g., changing clothes, transferring the child; Hunter, 2009; King et al., 2013; Luther, 2010; Shields & Synnot, 2014; Vogts, Mackey, Ameratunga, & Stott, 2010; Wiart, Darrah, Kelly, & Legg, 2015). Parent attitudes about HPPA, the perceived relative value of HPPA, and family priorities influenced children’s participation (Carter et al., 2014; Hunter, 2009). For example, some parents valued sport participation and competition, which facilitated more intense and frequent child HPPA participation, whereas other parents valued the social benefits of the activity over and above physical health benefits. Parent engagement in HPPA and opportunities to engage in outings and activities as a family, the latter of which were often limited, were additional factors influencing child HPPA participation.
Environmental Factors
Several physical and social factors in the environment influenced HPPA. Parents and children described a lack of information about programs or generally limited opportunities as barriers to HPPA participation (Anderson et al., 2005; Bloemen, Verschuren, et al., 2015; Luther, 2010; Shields et al., 2015; Wiart et al., 2015). Some programs and facilities lacked necessary physical access or specialized equipment (Hunter, 2009; Law et al., 2007; Luther, 2010; Shields & Synnot, 2014; Vogts et al., 2010; Wiart et al., 2015) or adequate personnel resources to meet the individual needs of the child. For example, staff members in community programs were unable to provide physical assistance for children or did not have the knowledge and skills to adapt activities to match specific needs and capabilities of children (Bloemen, Verschuren, et al., 2015; Luther, 2010; Rose, McDonnell, & Ellis, 2007; Shields & Synnot, 2014; Vogts et al., 2010; Wiart et al., 2015).
The presence of social benefits and supports for children and families was a strong HPPA facilitator (Carter et al., 2014; Hunter, 2009; Lauruschkus et al., 2015; Ortiz-Castillo, 2011; Wiart et al., 2015). For example, supportive peers, group activities, and role models were social factors that contributed to engagement in HPPA. The benefits of a social network that included opportunities to interact with other parents and welcoming environments were factors reported by parents as positive and beneficial in relation to their child’s physical activity engagement. Among school and community providers, inadequate training and support to meet the needs of children with severe disabilities were a notable barrier (Carter et al., 2014; Shields & Synnot, 2014; Wiart et al., 2015). Rose et al. (2007)  reported that many special educators found it difficult to support HPPA because they did not have professional training to adequately meet the HPPA needs of children with multiple and severe disabilities. Macrolevel influences were also evident. Policy- and organization-level supports influenced factors such as physical accessibility, staffing (e.g., availability of adaptive physical education specialists), program structure (e.g., inclusive or specialized), and other resources needed to develop, implement, and sustain community-based opportunities, programs, and activities (Anderson et al., 2005; Rose et al., 2007; Shields & Synnot, 2014; Vogts et al., 2010).
Discussion
Research specific to factors affecting HPPA participation among children who use AMDs is limited. The quantitative and qualitative studies examined in this scoping review demonstrated that, as for other children with disabilities, a complex array of child, family, and environmental facilitators and barriers affects HPPA participation among children who use AMDs.
The interplay of various child, family, and environmental factors clearly needs to be addressed when examining outcomes and developing lifestyle interventions that facilitate children’s engagement in HPPA. This holistic and context-oriented perspective is inherent in occupational therapy theory and practice as well as contemporary rehabilitation frameworks that guide assessment and intervention (Law et al., 1996; Rimmer, 2006; WHO, 2001). Child personal factors, such as motivation, self-perception, and preferences, were important HPPA facilitators. This finding suggests that it is critical to harness child interests and strengths to guide engagement in successful experiences that promote confidence, self-esteem, and feelings of equity among peers (Rimmer & Rowland, 2008). Studies of HPPA interventions for children with physical disabilities in which researchers reported positive findings indicated that child-focused motivational strategies (e.g., self-monitoring, positive reinforcement) are desirable intervention features (McPherson et al., 2014).
Age and severity of disability were nonmodifiable factors described as barriers to children’s HPPA. The timing of interventions in adolescence or earlier may be critical to counteract effects of disease progression and to prevent secondary conditions (e.g., obesity) that can further affect children’s motivation, perceptions of self-efficacy, and ultimately interest in HPPA participation. Attention to HPPA as a positive health behavior during key transitions may help reinforce self-determination around lifestyle choices, engage children and youth in decision making about HPPA on the basis of their interests, and build sustainable routines and habits that incorporate HPPA (Reingold & Jordan, 2013).
Severity of disability also influenced HPPA participation with increasing disparities among participants who were ambulatory, who were ambulatory and used an AMD, and who were nonambulatory and used an AMD. Severity of disability also overlapped with family and environmental factors. For example, children who were more dependent on parents for personal care often needed more help with transportation, assistance with transitions to and from the activity (e.g., dressing, showering after swimming), and specific adaptations to participate fully in the activity. When barriers increased because of limited trained staff or resources, participation became more contingent on parent time and resources. Occupational therapists and other rehabilitation professionals (e.g., physical therapists, therapeutic recreation specialists) can lend expertise and can collaborate in finding ways to enhance fit among the child, activity, and environment in relation to HPPA and to develop individualized physical activity programs (Bloeman et al., 2015b; Rimmer & Rowland, 2008; Sharp, Dunford, & Seddon, 2012). Collective and specialized knowledge of musculoskeletal and neurodevelopmental conditions and other factors can help practitioners facilitate physical performance and safety, promote the use of assistive technologies, and adapt the task or environment in ways that can facilitate HPPA in different home, school, and community environments.
Multiple family-level factors emerged related to values, resources (e.g., time, financial resources), and general information about or knowledge of HPPA opportunities and programs. Family-centered interventions that help children and families map available opportunities and resources for HPPA may be a useful way to explore activities and programs across different settings. Understanding where HPPA fits among other family priorities and demands as well as time, financial resources, and other constraints is an important strategy to find ways to include HPPA within daily routines and habits. A lifestyle intervention reported by Orban, Erlandsson, Edberg, Önnerfält, and Thorngren-Jerneck (2014)  demonstrated how family factors were targeted in a weight-reduction program for preschoolers. Although the intervention did not significantly change the children’s BMI, the time that the parents and children spent engaged in physical activities increased, suggesting that families were responsive to changes in routines and daily activities to promote child health.
Environmental facilitators and barriers concerning the built environment and attitudes were evident. Specific laws and policies regarding accessibility as well as resources to develop, support, and sustain inclusive and specialized sport, recreation, and leisure programs were presumably variable given that studies were from multiple countries. The need to advocate for built environments that are universally designed, accessible, and usable by children who use AMDs was clear to continue reducing physical barriers to HPPA. Individual- and organization-level interventions, such as training for community providers, may also help shift attitudes and knowledge to create more opportunities for children who use AMDs, improve the social environment, and develop programs with necessary resources and equipment to facilitate successful HPPA participation for children who use AMDs (Rimmer & Rowland, 2008).
Limitations
This review has limitations. Several studies in which researchers examined facilitators and barriers among children with disabilities were excluded because information or data that described children’s level of physical function or use of AMDs were not provided. Physical activity was also defined inconsistently. We used a broader definition of physical activity using or embedded in terms such as participation, physical activity, habitual physical activity, leisure, recreation, and sport activities. Several studies described children’s participation patterns and types of activities (e.g., using the CAPE), but HPPA was not the specific area of focus. HPPA was embedded in leisure, play, and recreation activities, and it was difficult to discern the quality of active participation or whether children experienced exercise benefits over and above other benefits (e.g., social). Studies in which researchers examined the physiological aspects of physical activity and exercise benefits often excluded children who were not ambulatory or those with more significant physical disabilities (e.g., GMFCS > Level 3), likely because of lack of validated measures for children who are nonambulatory, and therefore were not included in this review.
The larger population-based studies provided information about patterns and frequency of activities and were able to show the influence of basic demographics (e.g., severity of impairment and age). However, they did not address modifiable factors that influence HPPA to provide information that would inform interventions. The qualitative studies illustrated family and child experiences, which provided valuable information about why children may or may not participate in different types of HPPA, but these studies were limited by a lack of systematic measurement of facilitators and barriers. Important directions for future research include mixed-methods approaches that quantify HPPA facilitators and barriers and account for the complex interplay among child, family, and environmental factors and individual experiences, as well as the development of valid measurement tools to gauge HPPA intensity and quality for children who use AMDs (Gorter et al., 2012).
Implications for Occupational Therapy Practice
The findings of the study have the following implications for occupational therapy practice:
  • Occupational therapy practitioners have a role in promoting HPPA as part of a healthy lifestyle for children with disabilities to prevent obesity and other secondary health conditions.

  • A complex interplay of factors influence HPPA among children who use AMDs. Using core skills, occupational therapy practitioners can evaluate, modify, and support child, family, and environmental factors to facilitate HPPA that matches individual and family needs and preferences. This can help establish early habits that may have lifelong implications for obesity management or prevention.

  • Organization- and population-based interventions may be useful to promote HPPA in home, school, and community contexts as part of a comprehensive, interprofessional approach to prevent obesity in children who use AMDs. These interventions include advocating for and developing accessible and flexible community-based programs and shaping high-quality personnel.

Conclusion
Children who use AMDs can benefit from HPPA participation as a lifestyle component to prevent obesity and other secondary health conditions (McPherson et al., 2014). Research on the topic reveals relevant child, family, and environmental facilitators and barriers as well as gaps relating to HPPA definitions, measurement, and reported AMD use. Findings from this review have implications for future research as well as clinical intervention components and approaches to help facilitate HPPA as part of a healthy lifestyle for children who use AMDs.
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Figure 1.
Flow diagram detailing the study selection process.
Figure 1.
Flow diagram detailing the study selection process.
×
Figure 2.
Child, family, and environmental factors, with corresponding articles from Table 1 in parentheses.
Note. AMD = assistive mobility device; SES = socioeconomic status.
Figure 2.
Child, family, and environmental factors, with corresponding articles from Table 1 in parentheses.
Note. AMD = assistive mobility device; SES = socioeconomic status.
×
Table 1.
Articles Included in the Synthesis
Articles Included in the Synthesis×
StudyLocationDesignMeasuresDemographicsType of DisabilityAMD Level of Function
1. Anderson, Bedini, & Moreland (2005) United StatesQualitativeSemistructured interviewsChildren, N = 14 girls.
Age range = 10–16 yr; M = 13 yr.
CP (n = 6), SB (n = 5),
OI (n = 2), other (n = 1)
None (n = 1), walker (n = 2), manual wheelchair (n = 7), power wheelchair (n = 3)
2. Bloemen, Verschuren, et al. (2015) NetherlandsQualitativeSemistructured interviewsParents, n = 44; children, n = 44 (25 boys, 19 girls).
Age range = 4–18 yr.
SBTotal ambulatory (n = 3), community ambulatory (n = 8), household ambulatory (n = 6), nonambulatory (n = 27)
3. Carter et al. (2014) United KingdomQualitativeObservation, focus group, interviewParents, n = 10; children, n = 37; siblings n = 2; stakeholders, n = 14.Wheelchair
4. Hunter (2009) United StatesQualitativeSemistructured interviewsParents, n = 23; children, n = 23 (13 boys, 10 girls).
Age range = 9–17 yr; M = 14 yr.
SB (n = 16), CP (n = 4), Calder regression (n = 1), SCI (n = 1), multiple spinal leaks (n = 1)Wheelchair
5. King et al. (2013) Australia, Canada, United StatesCross-sectional surveyCAPEChildren, N = 1,076 (611 boys, 465 girls).
Age range = 6–20 yr.
CPGMFCS: 358 Level 1, 405 Levels 2 and 3, 313 Levels 4 and 5
6. Lauruschkus, Westbom, Hallström, Wagner, & Nordmark (2013) SwedenCross-sectional surveyFrequencyChildren, N = 364 (218 boys, 146 girls).
Age range = 7–17 yr.
CPGMFCS: 158 Level 1, 71 Level 2, 28 Level 3, 59 Level 4, 48 Level 5
7. Lauruschkus, Nordmark, & Hallström (2015) SwedenQualitativeFocus group, interviewChildren, N = 16 (7 boys, 9 girls).
Age range = 8–11 yr; M = 9 yr.
CPGMFCS: 11 Level 1 and 2, 2 Level 3, 2 Level 4, 1 Level 5
8. Law, Petrenchik, King, & Hurley (2007) CanadaCross-sectional surveyCHIEF, ASK, SDQChildren, N = 427 (229 boys, 198 girls).
Age range = 6–14 yr.
CP, SB, ABI, DD<25% ASK
9. Luther (2010) United StatesQualitativeSemistructured interviewsChildren, N = 12 (6 boys, 6 girls).
Age range = 6–12 yr; M = 10 yr, 1 mo.
SBWheelchair
10. Maher, Williams, Olds, & Lane (2007) AustraliaCross-sectional surveyPAQ–AChildren, N = 112 (76 boys, 36 girls).
Age range = 11–17 yr; M = 13 yr, 11 mo.
CPGMFCS: 42 Level 1, 27 Level 2, 10 Level 3, 17 Level 4, 15 Level 5
11. Majnemer et al. (2008) CanadaCross-sectional surveyCAPE, GMFM, GMFCS, Leiter, PedsQL, DMQ, SDQ, IOF, PSIChildren, N = 67 (42 boys, 25 girls).
Age range = 6–12 yr.
CPGMFCS: 59% Level 1, 23% Level 2, 18% Levels 3–5
12. Ortiz-Castillo (2011) United StatesCross-sectional surveyPASIPD, PADSChildren, N = 93 (56 boys, 37 girls).
Age range = 12–18 yr.
CP (n = 28), SB (n = 21), MD (n = 16), SCI (n = 9), other (n = 19)Manual wheelchair (n = 46), power wheelchair (n = 31), crutches (n = 14), walker (n = 11), cane (n = 4)
13. Palisano et al. (2009) United StatesCross-sectional surveyCAPE, GMFCSChildren, N = 500 (277 boys, 223 girls).
Age range = 6–21 yr; M = 12 yr, 4 mo.
CPGMFCS: 128 Level 1, 126 Level 2, 94 Level 3, 71 Level 4, 81 Level 5
14. Rose, McDonnell, & Ellis (2007) United StatesCross-sectional surveyAuthor questionnaire, minutes of PETeachers, n = 35; children, n = 170.
M age = 15 yr, 8 mo.
Multiple disabilities, intellectual disabilities, orthopedic impairments, ABI30% severe multiple disabilities, 47.6% intellectual disabilities
15. Shields & Synnot (2014) AustraliaQualitativeTwo-question surveySport and recreation personnel, N = 24.
16. Shields, Synnot, & Kearns (2015) AustraliaCross-sectional surveyCAPEChildren, N = 286 (177 boys, 109 girls).
Age range = 6–18 yr; M = 11 yr, 5 mo.
Physical (n = 77), intellectual (n = 67), multiple (n = 93), other (n = 49)26.9% mild, 23.4% moderate, 12.6% severe
17. Shikako-Thomas et al. (2013) CanadaCross-sectional surveyGMFM, GMFCS, MACS, VABS–II, CAPE, PAC, FES, SPPA, DMQ, SDQ, ECEQChildren, N = 187 (110 boys, 75 girls).
Age range = 12–20 yr; M = 15 yr, 4 mo.
CPGMFCS: 55 Level 1, 45 Level 2, 13 Level 3, 19 Level 4, 39 Level 5
18. Vogts, Mackey, Ameratunga, & Stott (2010) New ZealandCross-sectional surveyCHIEFParents, n = 32; children, n = 32 (15 boys, 17 girls).
Age range = 6–16 yr; M = 10 yr, 1 mo.
CPGMFCS: 23 Levels 1 and 2, 5 Level 3, 4 Level 5
19. Wiart, Darrah, Kelly, & Legg (2015) CanadaQualitativeSemistructured interviewsProgram staff, n = 36; parents, n = 13 (children’s age range = 7–17 yr).CP (n = 9), SB (n = 2), DCD (n = 1), thoracic lipoma (n = 1)GMFCS: 8 Levels 1 and 2, 1 Level 3, 3 Level 4, 1 Level 4 and 5
Table Footer NoteNote. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.
Note. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.×
Table 1.
Articles Included in the Synthesis
Articles Included in the Synthesis×
StudyLocationDesignMeasuresDemographicsType of DisabilityAMD Level of Function
1. Anderson, Bedini, & Moreland (2005) United StatesQualitativeSemistructured interviewsChildren, N = 14 girls.
Age range = 10–16 yr; M = 13 yr.
CP (n = 6), SB (n = 5),
OI (n = 2), other (n = 1)
None (n = 1), walker (n = 2), manual wheelchair (n = 7), power wheelchair (n = 3)
2. Bloemen, Verschuren, et al. (2015) NetherlandsQualitativeSemistructured interviewsParents, n = 44; children, n = 44 (25 boys, 19 girls).
Age range = 4–18 yr.
SBTotal ambulatory (n = 3), community ambulatory (n = 8), household ambulatory (n = 6), nonambulatory (n = 27)
3. Carter et al. (2014) United KingdomQualitativeObservation, focus group, interviewParents, n = 10; children, n = 37; siblings n = 2; stakeholders, n = 14.Wheelchair
4. Hunter (2009) United StatesQualitativeSemistructured interviewsParents, n = 23; children, n = 23 (13 boys, 10 girls).
Age range = 9–17 yr; M = 14 yr.
SB (n = 16), CP (n = 4), Calder regression (n = 1), SCI (n = 1), multiple spinal leaks (n = 1)Wheelchair
5. King et al. (2013) Australia, Canada, United StatesCross-sectional surveyCAPEChildren, N = 1,076 (611 boys, 465 girls).
Age range = 6–20 yr.
CPGMFCS: 358 Level 1, 405 Levels 2 and 3, 313 Levels 4 and 5
6. Lauruschkus, Westbom, Hallström, Wagner, & Nordmark (2013) SwedenCross-sectional surveyFrequencyChildren, N = 364 (218 boys, 146 girls).
Age range = 7–17 yr.
CPGMFCS: 158 Level 1, 71 Level 2, 28 Level 3, 59 Level 4, 48 Level 5
7. Lauruschkus, Nordmark, & Hallström (2015) SwedenQualitativeFocus group, interviewChildren, N = 16 (7 boys, 9 girls).
Age range = 8–11 yr; M = 9 yr.
CPGMFCS: 11 Level 1 and 2, 2 Level 3, 2 Level 4, 1 Level 5
8. Law, Petrenchik, King, & Hurley (2007) CanadaCross-sectional surveyCHIEF, ASK, SDQChildren, N = 427 (229 boys, 198 girls).
Age range = 6–14 yr.
CP, SB, ABI, DD<25% ASK
9. Luther (2010) United StatesQualitativeSemistructured interviewsChildren, N = 12 (6 boys, 6 girls).
Age range = 6–12 yr; M = 10 yr, 1 mo.
SBWheelchair
10. Maher, Williams, Olds, & Lane (2007) AustraliaCross-sectional surveyPAQ–AChildren, N = 112 (76 boys, 36 girls).
Age range = 11–17 yr; M = 13 yr, 11 mo.
CPGMFCS: 42 Level 1, 27 Level 2, 10 Level 3, 17 Level 4, 15 Level 5
11. Majnemer et al. (2008) CanadaCross-sectional surveyCAPE, GMFM, GMFCS, Leiter, PedsQL, DMQ, SDQ, IOF, PSIChildren, N = 67 (42 boys, 25 girls).
Age range = 6–12 yr.
CPGMFCS: 59% Level 1, 23% Level 2, 18% Levels 3–5
12. Ortiz-Castillo (2011) United StatesCross-sectional surveyPASIPD, PADSChildren, N = 93 (56 boys, 37 girls).
Age range = 12–18 yr.
CP (n = 28), SB (n = 21), MD (n = 16), SCI (n = 9), other (n = 19)Manual wheelchair (n = 46), power wheelchair (n = 31), crutches (n = 14), walker (n = 11), cane (n = 4)
13. Palisano et al. (2009) United StatesCross-sectional surveyCAPE, GMFCSChildren, N = 500 (277 boys, 223 girls).
Age range = 6–21 yr; M = 12 yr, 4 mo.
CPGMFCS: 128 Level 1, 126 Level 2, 94 Level 3, 71 Level 4, 81 Level 5
14. Rose, McDonnell, & Ellis (2007) United StatesCross-sectional surveyAuthor questionnaire, minutes of PETeachers, n = 35; children, n = 170.
M age = 15 yr, 8 mo.
Multiple disabilities, intellectual disabilities, orthopedic impairments, ABI30% severe multiple disabilities, 47.6% intellectual disabilities
15. Shields & Synnot (2014) AustraliaQualitativeTwo-question surveySport and recreation personnel, N = 24.
16. Shields, Synnot, & Kearns (2015) AustraliaCross-sectional surveyCAPEChildren, N = 286 (177 boys, 109 girls).
Age range = 6–18 yr; M = 11 yr, 5 mo.
Physical (n = 77), intellectual (n = 67), multiple (n = 93), other (n = 49)26.9% mild, 23.4% moderate, 12.6% severe
17. Shikako-Thomas et al. (2013) CanadaCross-sectional surveyGMFM, GMFCS, MACS, VABS–II, CAPE, PAC, FES, SPPA, DMQ, SDQ, ECEQChildren, N = 187 (110 boys, 75 girls).
Age range = 12–20 yr; M = 15 yr, 4 mo.
CPGMFCS: 55 Level 1, 45 Level 2, 13 Level 3, 19 Level 4, 39 Level 5
18. Vogts, Mackey, Ameratunga, & Stott (2010) New ZealandCross-sectional surveyCHIEFParents, n = 32; children, n = 32 (15 boys, 17 girls).
Age range = 6–16 yr; M = 10 yr, 1 mo.
CPGMFCS: 23 Levels 1 and 2, 5 Level 3, 4 Level 5
19. Wiart, Darrah, Kelly, & Legg (2015) CanadaQualitativeSemistructured interviewsProgram staff, n = 36; parents, n = 13 (children’s age range = 7–17 yr).CP (n = 9), SB (n = 2), DCD (n = 1), thoracic lipoma (n = 1)GMFCS: 8 Levels 1 and 2, 1 Level 3, 3 Level 4, 1 Level 4 and 5
Table Footer NoteNote. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.
Note. ABI = acquired brain injury; AMD = assistive mobility device; ASK = Activities Scale for Kids; CAPE = Children’s Assessment of Participation and Enjoyment; CHIEF = Craig Hospital Inventory of Environmental Factors; CP = cerebral palsy; DCD = developmental coordination disorder; DD = developmental disability; DMQ = Dimensions of Mastery Questionnaire; ECEQ = European Child Environment Questionnaire; FES = Family Environment Scale; GMFCS = Gross Motor Function Classification Scale; GMFM = Gross Motor Function Measure; IOF = Impact on Family Scale; M = mean; MACS = Manual Ability Classification System; MD = muscular dystrophy; OI = osteogenesis imperfecta; PAC = Preferences for Activities of Children; PADS = Physical Activity Determinants Scale; PAQ–A = Physical Activity Questionnaire for Adolescents; PASIPD = Physical Activity Scale for Individuals with Disabilities; PE = Physical Education; PedsQL = Pediatric Quality of Life Inventory; PSI = Parenting Stress Index; SB = spina bifida; SCI = spinal cord injury; SDQ = Strengths and Difficulties Questionnaire; SPPA = Self-Perception Profile for Adolescents; VABS–II = Vineland Adaptive Behavior Scales—Second Edition.×
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