1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Aim  The objective was to describe leisure activity preferences of children with cerebral palsy (CP) and their relationship to participation. Factors associated with greater interest in leisure activities were identified.

Method  Fifty-five school-aged children (36 males, 19 females; mean age 9y 11mo; range 6y 1mo–12y 11mo) with CP (Gross Motor Function Classification System [GMFCS]) level I 62%, level II 22%, level III–IV 16%; 33.3% hemiplegia, 29.6% diplegia, 25.9% quadriplegia, 11.2% other) who could complete the Preferences for Activities of Children (PAC) were recruited.

Results  Social and recreational activities were most preferred, and self-improvement activities were least preferred. Younger age, higher motivation, and IQ predicted interest in active–physical activities (r2=0.39). Negative reaction to failure was associated with less preference for social activities (r2=0.16), whereas increased prosocial behaviours were related to greater preference for recreational (r2=0.13) and self-improvement activities; the latter is also predicted by older age (r2=0.24). Interest in skill-based activities was greater in females and in children who were highly motivated, younger, and had greater motor limitations (r2=0.51). The findings suggest that personal factors and functional abilities influence leisure activity preferences. High preference for certain activities was not always associated with involvement in these activities.

Interpretation  Determination of preferences is inherent to child-centred practice and should, therefore, be part of the evaluation process. Rehabilitation strategies can minimize barriers to leisure participation, such as fear of failure, low motivation, or environmental obstacles.

List of abbreviations

Children’s Assessment of Participation and Enjoyment


Dimensions of Mastery Questionnaire


Preferences for Activities of Children


Parenting Stress Index


Strengths and Difficulties Questionnaire


Vineland Adaptive Behavior Scale

Cerebral palsy (CP) is a disorder of movement and posture causing activity limitations arising from a lesion or abnormality of the immature brain.1,2 Rehabilitation is primarily directed at minimizing motor impairments and maximizing functional independence. Recently, there has been greater emphasis on promoting participation; however, while remediation and adaptive strategies to diminish limitations in mobility and self-care are well established, targeted interventions to promote participation in leisure activities are less well developed.

Participation is defined by the World Health Organization as taking part or being involved in life situations. Specifically, everyday activities within particular domains are grouped into life habits, such as mobility, communication, or self-care. Evaluation tools typically include a range of these activities, which are then combined to represent participation in these related activities. Participation is a concept that is receiving considerable attention, particularly with the adoption and usage of the International Classification of Functioning, Disability, and Health.3 The level of participation in life roles is probably modified by health condition, functional limitations, and personal and environmental factors.4 Leisure is regarded as the time designated for freely chosen activities, performed when not involved in self-care or work (school). Participation in leisure activities is essential in the development of skill competencies, socializing with peers, exploring personal interests, and simply enjoying life.5 Therefore, recognition of the factors that promote leisure participation would assist in developing health promotion strategies.

There is a paucity of studies that have described participation in leisure activities in children with CP. Preliminary studies suggested that these children experience some restriction in their involvement in leisure activities, particularly those that are physical, social, or in the community setting.6–11 A recent review has highlighted several determinants of participation in leisure activities that include activity limitations (difficulties in one or more activities in particular participation domains), personal factors such as age, sex, and socioeconomic status, and environmental factors such as family preferences, and social and resource supports.12

Preference is defined as having a choice between alternatives and the opportunity to choose those alternatives that are most satisfying. It is linked to motivation, with greater motivation associated with a greater likelihood of performing activities of one’s own choosing.13 Children with disabilities may demonstrate interests or preferences in particular leisure activities, but several obstacles may limit actual participation. Personal choices and preferences of activities may, in turn, be influenced by a child’s level of persistence, perception of the task, activity limitations, and past experiences, as well as by environmental barriers.13–15 To date, few studies have described the personal preferences for leisure activities in children with disabilities. Evidence about the preferences of children with CP may help promote child-centred therapeutic approaches. Understanding the incongruities between preference and actual involvement is important, so that rehabilitation professionals can address barriers that limit participation. The objective of this study was to describe leisure activity preferences in school-aged children with CP and to determine the relationship between preferences (‘would like to do’) and actual involvement (‘does do’) in these activities. Factors associated with greater preference for activity subtypes (social, physical, skill-based, recreational, self-improvement) were ascertained.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References


Ninety-five school-aged children with CP participated in a study to describe quality of life16 and participation.10 The methods and measures have already been reported in detail.10,16 This sample is similar in distribution (e.g. CP type, proportion preterm) to that reported by the European17 and Quebec CP registry.18 CP was defined at database entry as described by Badawi et al.19 Only parents who could read English or French were recruited. The study was approved by the hospital’s institutional review board.


Once consent was obtained, an appointment was made for testing at the Montreal Children’s Hospital. Evaluators were blind to medical history and to each other’s findings. A neurologist examined participants. An occupational therapist conducted a semistructured interview with the child and parent. Parents responded to questions from the Vineland Adaptive Behavior Scale (VABS),20 and children participated in completion of the Children’s Assessment of Participation and Enjoyment (CAPE) and the Preferences for Activities of Children (PAC).21 In addition, the Gross Motor Function Measure (GMFM)22 and Gross Motor Function Classification System (GMFCS)23 were performed. A psychologist carried out the Leiter Intelligence Test.24 Parents and children (when feasible) were asked to complete questionnaires on demographic variables, mastery motivation (Dimensions of Mastery Questionnaire, DMQ),25 child behaviour (Strengths and Difficulties Questionnaire [SDQ]),26 quality of life (Pediatric Quality of Life Inventory [PedsQL]; results reported),16,27 and family functioning (Parenting Stress Index [PSI]).28 These measures are age appropriate with acceptable psychometric properties.

Outcome measures and predictor variables

This paper reports on the children’s leisure activity preferences using the PAC test. Children’s own perspectives were obtained; therefore, children who could not actively participate in test completion (owing to language or cognitive limitations, as judged by the parent and research coordinator) were excluded. Fifty-five children (19 females, 36 males) were able to complete the PAC test with minimal assistance from parents. The test contains 50 cards representing typical leisure activities performed in the home and community outside school hours. Children are asked to sort the activity cards into three piles: ‘I would really like to do’, ‘I would sort of like to do’, and ‘I would not like to do at all’. This test has good internal consistency (α=0.67–0.77) within activity domains. The PAC test is performed with the CAPE, whereby the same activities (represented pictorially) are reviewed with the child (and parent), and respondents are asked about intensity of involvement in each activity (how often?) and the level of enjoyment of each; both are scored on an ordinal scale. Reliability ranges from 0.75 to 0.93, and validity has been demonstrated.21,29 The activities in the PAC/CAPE are grouped into five subscales: (1) recreational, (2) active-physical, (3) social, (4) skill-based, and (5) self-improvement. Tests were forward and back translated into French.

Several predictors of leisure preferences were considered, based on conceptual information from the literature on determinants of leisure participation.4,12 These included measures of impairment (cognitive deficits: Leiter-IQ; behaviour: SDQ), activity limitations within domains of participation (motor function: GMFM/GMFCS; VABS), personal factors (age, sex, mastery motivation [DMQ]), and environmental factors (family stress: PSI). For the DMQ (persistence in social, cognitive and motor tasks, negative reaction to failure, mastery pleasure) and the SDQ (prosocial behaviour, emotional, conduct, and peer problems, hyperactivity), we considered each of the subscale scores; we were particularly interested in these dimensions as possible predictor variables.

Statistical analyses

Analyses were performed using the Statistical Analysis Software (SAS Institute, Cary NC, USA) 9.1.3 program. Descriptive statistics was carried out to summarize the participants’ biomedical, functional, and environmental characteristics. Simple Pearson’s product–limit correlation analysis was performed to examine the association between the CAPE and PAC subdomains. Simple and multiple linear regression analyses were carried out for five PAC subdomains to explore their relationship with potential predictors. Residual plots were inspected to verify linearity, normality, and homoscedasticity assumptions for all regression models. Additionally, robust regression was carried to identify potential outliers and leverage points. Collinearity was assessed based on tolerance, variation of inflation, and eigenvalues. The outcome measure (PAC scores) did not have any missing values but the independent variables had a few missing values, with missing cases varying on different variables. Given that the data were missing at random, a list-wise deletion approach was implemented to proceed with complete case analysis, thus ensuring that parameters within regression models were based on the same dataset and standard error estimates. List-wise deletion resulted in a sample of 44, which did not affect the power of the final models (estimated at 0.69, 0.99, 0.81, 0.99, and 0.90 for the five domains). Student’s t-tests were carried out comparing those in the regressions (n=44) and those excluded (n=11) because of missing values with regard to the age at assessment, sex, CP type, GMFCS, IQ, and PAC scores; no significant difference was noted. Regression shrinkage and least angle regression methods were applied as a starting point for further analysis to identify parsimonious models for the PAC response variables. All final models were validated using bootstrapping, with repeated samples of the same size as the original, with replacement. Two thousand replications were produced to estimate bootstrap confidence intervals.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Group characteristics

Of the 95 children originally recruited to this study, 55 (36 males, 19 females) were able to participate actively in completing the PAC test at a mean age of 9 years 11 months (range 6y 1mo–12y 11mo). As expected, most were at GMFCS level I (62%) or II (22%), with only 7% at level V. Table I summarizes group characteristics and performance on measures used. Although most children were ambulatory and able to indicate activity preferences on the PAC test, 25% had an IQ of <70. Furthermore, around half (49–51%) had communication, daily living skills, and adaptive behaviour scores of <78 on the VABS, suggesting activity limitations in these participation domains. A relative strength was socialization skills, with only 25.5% scoring <78. Behavioural difficulties were noted in 25%, with a further 14.6% being borderline. With respect to parental stress, 30.6% of parents had high levels of stress, whereas 18.5% were defensive.

Table I.   Performance on predictor and outcome measures
VariableMeasures usedn (%) or mean (SD); range
Biomedical factors
 Pattern of motor impairmentNeurological examination (spastic subtypes)18 (33.3%) hemiplegia, 16 (29.6%) diplegia, 14 (25.9%) quadriplegia
Body function, activity, and participation
 Behavioural difficultiesStrengths and Difficulties Questionnaire11.4 (6.0), range 0–22
 Intellectual abilitiesLeiter Intelligence ScaleBrief IQ: 82.1 (19.6), range: 38–126; fluid reasoning: 82.7 (18.3), range 50–120
 Motor functionGross Motor Function Measure79.3 (23.0), range 8–100
 Communication Vineland Adaptive Behaviour Scale77.3 (24.8); 20–123
 Socialization86.3 (17.3); 32–117
 Daily living skills72.2 (25.9); 20–112
 Adaptive behaviour74.1 (23.0); 21–116
Personal factors
 SexMale/female36 (65.5%) males, 19 (34.5%) females
 Age at assessmenty:mo9y 11mo (2.0), range 6y 1mo–12y 11mo
 Child’s mastery motivationDimensions of Mastery QuestionnaireTotal motivation: 3.4 (0.5), range 2.4–4.5; total persistence: 3.2 (0.5), range 2.3–4.4
Environmental factors
 Family functioningParental Stress Index73.6 (18.5), range 33–102
 School settingSegregated/integrated25 (46.3%) regular school, 16 (29.7%) special school, 13 (24.1%) regular school with resource support
 Rehabilitation servicesYes/no (last 6mo) 11 (29.1%) no, 42 (76.4%) yes, 1 (1.8%) not specified

Performance on the PAC test

Mean scores on the PAC domains appear in Table II. Children most often preferred social activities followed by recreational activities, with least interest in self-improvement tasks. Formal (structured, preplanned) activities had lower mean preference scores (2.1, SD 0.4) than informal (spontaneous) activities (2.5, SD 0.3). Specific activities identified as being most often preferred (score of 3 by >90% of children) included puzzles, board/card games, arts and crafts, computer/video games, imaginary play, toys, watching TV/movie (recreational domain); individual physical activities (active–physical); talking on the phone, hanging out with friends, listening to music (social); dancing (skill-based); and reading and shopping (self-improvement). Few preferred either track and field or racing, a paid job, or art lessons (score of 3 by <10%). The activities with the lowest mean scores were martial arts (1.71), learning to dance (1.85), track and field, and school clubs (both 1.87). The three activities most preferred by males (mean 2.89–2.92) were going to movies, watching TV/movie, and full-day outings, whereas females most often preferred listening to music, swimming, and going to someone’s house (equivalent to watching TV/movie; mean 2.84–2.95).

Table II.   Association between Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities of Children (PAC) scores
CAPEPACPearson’s r (95% CI)p
  1. CAPE Diversity, the number of different activities involved for a particular domain (how many); CAPE Intensity, frequency of involvement in these activities (how often).

Recreational activities
 DiversityMean 2.5, SD 0.3, range 1.8–3.00.44 (0.20 to 0.63)<0.001
 Intensity0.50 (0.27 to 0.68)<0.001
 Enjoyment0.46 (0.22 to 0.65)<0.001
 DiversityMean 2.3, SD 0.6, range 1.2–3.00.26 (0.00 to 0.49)0.053
 Intensity0.20 (−0.07 to 0.44)0.152
 Enjoyment0.29 (0.02 to 0.53)0.036
Social activities
 DiversityMean 2.7, SD 0.3, range 1.8–3.00.36 (0.10 to 0.57)0.007
 Intensity0.25 (−0.01 to 0.49)0.062
 Enjoyment0.39 (0.13 to 0.60)0.004
 DiversityMean 2.2, SD 0.5, range 1.2–3.00.49 (0.25 to 0.67)<0.001
 Intensity0.44 (0.20 to 0.63)<0.001
 Enjoyment0.38 (0.12 to 0.59)0.005
 DiversityMean 2.1, SD 0.5, range 1.0–3.00.25 (−0.02 to 0.48)0.067
 Intensity0.32 (0.06 to 0.54)0.015
 Enjoyment0.82 (0.71 to 0.89)<0.001

Correlations between level of preference for leisure activities (PAC scores) and actual involvement (intensity scores on the CAPE) in these activities reveals moderate associations for the recreational and skill-based domains (0.44–0.50), with lower correlations for physical, social, and self-improvement domains (Table II). Thus, it appears that these children do engage more in activities that they have most preference for. However, modest correlations suggest that some preferences are not realized, or, conversely, that children are sometimes involved in activities not of their choosing. In particular, preference levels were not significantly related to the diversity (how many) and intensity (how often) of involvement within the active–physical activities, the intensity of social activities, or the diversity of self-improvement activities.

Factors associated with leisure activity preferences

The relationships between age, sex, and severity of motor dysfunction and preference scores were first explored on univariate analyses. Younger children showed a greater preference for active–physical, skill-based, and self-improvement activities than older school-aged children (Pearson’s correlations from −0.33 to −0.43, p=0.01); however, preferences for social and recreational activities were similar (p>0.05) across the 6- to 12-year age span. Skill-based activities, such as swimming, dancing, horseback riding, art, or music lessons, were more likely to be preferred by females (mean 2.44 females vs 2.05 males, p=0.007) and also by children with more severe motor limitations (higher GMFCS score: 2.4 vs 2.0, p=0.005; attending special school: 2.5 vs 2.1, p=0.005). These variables, together with scores on developmental measures, mastery motivation, and parental stress, were considered in multivariate linear regression analyses. The best predictive models for PAC subdomain scores are shown in Table III. Age, sex, and severity of motor limitations continued to predict particular preferences, as noted above. However, other predictor variables emerged in the multivariate models. Two components of mastery motivation were predictive; specifically, a high degree of persistence in motor tasks predicted a greater preference for skill-based activities and active–physical activities. Furthermore, children who are more likely to react negatively to failure were less likely to prefer social activities. It appears as though children with higher IQs more often prefer physical activities, while those with more sociable behaviours were more likely to prefer recreational and self-improvement activities.

Table III.   Best predictive models for Preferences for Activities of Children (PAC) subdomain scores
Outcome measure and predictor variablesr2Parameter estimateBootstrap
(% variance)p valueBeta95% CIEstimateBCa – 95% CI
  1. CI, confidence interval; BCa, bias-corrected and accelerated; GMFM, Gross Motor Function Measure; SDQ, Strengths and Difficulties Questionnaire; DMQ, Dimensions of Mastery Questionnaire; NS, not significant.

 Prosocial behaviours (SDQ)12.50.0200.060.01 to to 0.10
 Age at assessment39.1<0.001−0.08−0.14 to −0.03−0.08−0.13 to −0.02
 Gross motor persistence (DMQ)  0.200.05 to 0.350.200.04 to 0.41
 Leiter brief IQ  0.0070.001 to 0.010.0070.0001 to 0.01
 Negative reaction to failure (DMQ)16.20.007−0.13−0.23 to −0.04−0.13−0.23 to −0.05
 Age at assessment50.8<0.001−0.10−0.16 to −0.05−0.10−0.15 to −0.04
 GMFM score  −0.008−0.01 to −0.002−0.008−0.01 to −0.003
 Sex  −0.32−0.56 to −0.07−0.31−0.56 to −0.07
 Gross motor persistence (DMQ)  0.170.02 to 0.320.160.006 to 0.36
 Prosocial behaviours (SDQ)23.90.0040.100.01 to to 0.17
 Age at assessment  −0.09−0.15 to −0.03−0.09−0.15 to −0.02


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Participation in leisure-time physical, social, and recreational activities has well-established health benefits, in terms of both physical health and social–emotional well-being.9,30,31 Recent studies on children with physical disabilities emphasize that personal preferences in leisure activities directly predict level of participation in these activities.4,32 However, few studies have described leisure activity preferences of children with CP. An appreciation of the interests of children with CP, and of the factors that influence preferences, is important in the development of health promotion initiatives that optimize leisure participation.

Children in our sample most preferred social and recreational activities, and indeed we have previously reported that the intensity of actual participation in these activities is greater than for other leisure activity domains.10 Therefore, these children are most involved in the leisure activities that they prefer. In one study that used the PAC on typically developing school-aged children, preference for social activities was also high.33 Not surprisingly, the lowest preference scores in our sample were for self-improvement activities; nonetheless, intensity of actual participation in these activities (homework, chores, reading) is similar to that of social activities (CAPE intensity 2.9 [SD 0.9] vs 3.1 [SD 0.9]). Preference for active–physical activities was only slightly lower than for social and recreational activities; however, we, and others, have reported that children and young people with CP have lower levels of participation in physical activities than their peers without disability.6,9,10 Correlations between preferences (PAC) and actual involvement in these leisure activities (CAPE) in our study highlight the significant association between high interest in particular activity types (recreational, skill-based) and involvement in these activities. However, these associations were modest for active–physical, social, and self-improvement activities. Similarly, King et al.4 found modest correlations between PAC and CAPE scores for formal (r=0.28) and informal (r=0.31) leisure activities. Of note, high preference for active–physical activities was weakly correlated with enjoyment of these activities, perhaps implying that these children’s physical activity experiences need to be augmented or modified. Collectively, these findings suggest that, for some children, there may be a high interest in particular activities (physical, social) that is not linked with high involvement in these activities. Conversely, greater involvement in particular activities (self-improvement) may be associated with lower personal preference. Therefore, leisure participation may not be optimally based on personal preferences and desires because of particular obstacles limiting participation. Furthermore, children are expected to participate in certain activities, even if they prefer not to.

The child’s age influenced leisure preferences, with older children showing less interest in active–physical, skill-based, and self-improvement activities. It is conceivable that as they get older children become more aware of their difficulties and differences on potentially physically challenging tasks than their peers. Increasing age has been reported to have a similar effect on decreased actual participation in leisure activities in children with physical disabilities.7

Sex also influenced activity preferences, with females indicating greater interest in skill-based activities. Studies that have reported sex effects on leisure participation further emphasize that females participate more than males in more formal, structured activities10 and in a wider diversity of skill-based activities.7 Another study used the PAC test to evaluate preferences on typically developing Israeli and Druze children. Sex was significantly associated, such that Israeli females preferred skill-based activities more than did males.33 Interestingly, this was mediated by cultural context, as this sex effect was not documented in Druze children, although greater preference for social activities in females was noted in both groups.

Children with more severe motor limitations, and those attending special schools, also demonstrated a greater preference for skill-based activities (e.g. swimming, dancing, horseback riding). It is possible that children in segregated schools are provided with greater opportunities and resources to pursue these activities. Perhaps these interests could be further augmented in children with mild motor dysfunction, if given the opportunity, with greater awareness created of adapted community programmes that are available.

Intrinsic motivation is related to our personal beliefs of how well we expect to perform an activity and how much we value that activity, and it is closely linked with our desire to engage in a particular task.13 Mastery motivation is defined by the DMQ developers as the intrinsic drive to explore and master one’s environment. There is an instrumental aspect (the level of motivation to attempt to master a task that is at least moderately challenging) and an expressive aspect (the expressive reactions while working on or upon completing a task). Results indicate that children who persist in doing challenging motor tasks are more likely to prefer active–physical and skill-based activities. Furthermore, children who react negatively to failure show low preferences for social activities. Perception of competency (i.e. ‘Can I do it?’) influences motivation and interest in activities. Gaining confidence in one’s abilities, confronting fear of failure, and allowing failures to occur are avenues that can be pursued by rehabilitation specialists, with respect to promoting greater involvement in physical activities that are important for overall health.34

The value of leisure activities in supporting physical and psychological health in children with disabilities is recognized; nevertheless, the primary focus of rehabilitation for school-aged children with CP is on independence in self-care and mobility and productivity in the school environment.35 Within schools, rehabilitation specialists are mandated to develop educational goals; thus, the importance of promoting home- and community-based leisure participation in children with disabilities may be overlooked or given lower priority. Key barriers to participation in leisure activities for children with physical disabilities include functional limitations, sociodemographic factors, family adaptation, costs, accessibility, programs available, and family and child preferences.4,7,10,12,30 Rehabilitation specialists need to elicit a child’s own preferences and interests when assessing participation in leisure activities, given its importance to actual involvement in these activities.7,33 Once preferences are identified, clinicians should ascertain whether there are modifiable barriers to involvement in the ‘most preferred’ activities. Second, it is important for clinicians to understand the factors that can modify leisure activity preferences when developing strategies to promote participation. For example, the importance of positive social behaviours in promoting interest in recreational activities and of good reasoning skills in enhancing interest in active–physical activities would suggest that efforts to facilitate ongoing skill development in psychosocial domains may enhance preferences for more physically or socially challenging leisure activities. Improving intrinsic mastery motivation by addressing environmental barriers (e.g. access, awareness of adapted programs, peer/teacher/family support) and personal obstacles (e.g. low confidence and expectancy for success, low priority) to choosing to do more challenging leisure activities needs greater consideration.4,30,34

There are a number of limitations to this study. Our sample included children who could actively assist in completion of the PAC test, therefore children with lower cognitive and language abilities were excluded. Future studies may consider using parents as proxy respondents, to better appreciate the leisure preferences of children with more severe limitations. Our results indicate that parental stress and activity limitations across domains were not important predictors of the PAC domains overall. It is possible that with a larger, more heterogeneous sample, these variables may be associated.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Children with CP demonstrate a high level of interest in a variety of leisure activities, especially those that are social and recreational. In turn, these preferences influence involvement in these activities, and, therefore, need to be considered as part of child-centred rehabilitation interventions aimed at promoting leisure participation. Addressing the personal and environmental obstacles to participating in the activities that a child prefers to do, as well as identifying the factors that are limiting interest and greater preference for physical and social activities, are essential to improve the overall health and well-being of children with CP.


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References

Very special thanks to Nick Hall for his efforts in coordination of this study. Thanks to occupational therapists Cynthia Perlman and Amy Brownstein and psychologists Lisa Steinbach, Nancy Marget, Mafalda Porporino, Terry Viola, and Chantal Martel for assistance in testing. We are especially grateful to the parents and children who participated in this study. We also wish to acknowledge the funding support from the Cerebral Palsy International Research Foundation (USA). In addition, we benefited from research infrastructure provided by the Montreal Children’s Hospital Research Institute and the Centre de recherche interdisciplinaire en réadaptation du Montréal métropolitain (CRIR), both funded by the Fonds de la recherche en santé de Québec (FRSQ).


  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Conclusions
  7. Acknowledgements
  8. References
  • 1
    Rosenbaum P, Paneth N, Leviton A, Goldstein M, Bax M. The definition and classification of cerebral palsy. Dev Med Child Neurol 2007; 49(Suppl. 109): 814.
  • 2
    Shevell MI, Bodensteiner JB. Cerebral palsy: defining the problem. Semin Pediatr Neurol 2004; 11: 25.
  • 3
    World Health Organization. International Classification of Functioning, Disability and Health (ICF) 2001. (accessed 15 November 2008).
  • 4
    King G, Law M, Hanna S, et al. Predictors of the leisure and recreation participation of children with physical disabilities: a structural equation modeling analysis. Child Health Care 2006; 35: 20934.
  • 5
    Simpkins SD, Ripke M, Huston AC, Eccles JS. Predicting participation outcomes in out-of-school activities: similarities and differences across social ecologies. New Dir Youth Dev 2005; 105: 5169.
  • 6
    Imms C, Reilly S, Carlin J, Dodd K. Diversity of participation in children with cerebral palsy. Dev Med Child Neurol 2008; 50: 36369.
  • 7
    Law M, King G, King S, et al. Patterns of participation in recreational and leisure activities among children with complex physical disabilities. Dev Med Child Neurol 2006; 48: 33742.
  • 8
    Lepage C, Noreau L, Bernard PM, Fougeyrollas P. Profile of handicap situations in children with cerebral palsy. Scand J Rehabil Med 1998; 30: 26372.
  • 9
    Maher CA, Williams MT, Olds T, Lane AE. Physical and sedentary activity in adolescents with cerebral palsy. Dev Med Child Neurol 2007; 49: 45057.
  • 10
    Majnemer A, Shevell M, Law M, et al. Participation and enjoyment of leisure activities in school-aged children with cerebral palsy. Dev Med Child Neurol 2008; 50: 75158.
  • 11
    Schenker R, Coster W, Parush S. Participation and activity performance of students with cerebral palsy within the school environment. Disabil Rehabil 2005; 27: 53952.
  • 12
    Shikako-Thomas K, Majnemer A, Law M, Lach L. Determinants of participation in leisure activities in children and youth with cerebral palsy: systematic review. Phys Occup Ther Pediatr 2008; 28: 15569.
  • 13
    Watkinson JE, Dwyer SA, Nielson AB. Children theorize about reason for recess engagement: does expectancy-value theory apply? Adapt Phys Activ Q 2005; 22: 17997.
  • 14
    Wigfield A, Eccles JS. Expectancy-value theory of achievement motivation. Contemp Educ Psychol 2000; 25: 6881.
  • 15
    Yalon-Chamovitz S, Mano T, Jarus T, Weinblatt N. Leisure activities during school break among children with learning disabilities: preferences vs. performance. Br J Learn Disabil 2006; 34: 4248.
  • 16
    Majnemer A, Shevell M, Rosenbaum P, Law M, Poulin C. Determinants of life quality in school-age children with cerebral palsy. J Pediatr 2007; 151: 47075.
  • 17
    Cans C. Surveillance of cerebral palsy in Europe: a collaboration of cerebral palsy surveys and registers. Dev Med Child Neurol 2000; 42: 81624.
  • 18
    Shevell MI, Dagenais L, Hall N, REPACQ Consortium. The relationship of cerebral palsy sub-type and functional motor impairment: a population-based study. Dev Med Child Neurol. (Published online 11th March 2009). DOI: 10.1111/j.1469-8749.2009.03269.x.
  • 19
    Badawi N, Watson L, Petterson B, et al. What constitutes cerebral palsy? Dev Med Child Neurol 1998; 40: 52027.
  • 20
    Sparrow SS, Balla DA, Cicchetti DV. Vineland Adaptive Behavior Scales. Circle Pines, MN: American Guidance Service, 1984.
  • 21
    King G, Law M, King S, et al. Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities of Children (PAC). San Antonia, TX: Harcourt Assessment, 2004.
  • 22
    Russell DJ, Rosenbaum PL, Avery LM, Lane M. Gross Motor Function Measure (GMFM-66 & GMFM – 88) User’s Manual. Clinics in Developmental Medicine No. 159. London: Mac Keith Press, 2002.
  • 23
    Palisano R, Rosenbaum P, Walter S, Russell D, Wood E, Galuppi B. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol 1997; 39: 21423.
  • 24
    Roid GH, Miller LJ. Leiter International Performance Scale – Revised. Wood Dale, IL: Stoelting, 1997.
  • 25
    Morgan GA, Leech NL, Barrett KC, Busch-Rossnagel NA, Harmon RJ. The Dimensions of Mastery Questionnaire (manual). Fort Collins, CO: Colorado State University, 2000.
  • 26
    Goodman R, Scott S. Comparing the Strengths and Difficulties Questionnaire and the Child Behavior Checklist: is small beautiful? J Abnorm Child Psychol 1999; 27: 1724.
  • 27
    Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the pediatric quality of life inventory version 4.0 generic core scales in healthy and patient populations. Med Care 2001; 39: 80012.
  • 28
    Abidin RR. Parenting Stress Index (PSI). 3rd edn. Odessa, FL: Psychological Assessment Resources Inc., 1990.
  • 29
    King G, Law M, King S, et al. Measuring children’s participation in recreation and leisure activities: construct validation of the CAPE and PAC. Child Care Health Dev 2006; 33: 2839.
  • 30
    Murphy NA, Carbone PS, the Council on Children with Disabilities. Promoting the participation of children with disabilities in sports, recreation, and physical activities. Pediatrics 2008; 121: 105761.
  • 31
    Salmon J, Owen N, Crawford D, Bauman A, Sallis JF. Physical activity and sedentary behavior: a population-based study of barriers, enjoyment, and preference. Health Psychol 2003; 22: 17888.
  • 32
    Law M, Petrenchik T, King G, Hurley P. Perceived environmental barriers to recreational, community, and school participation for children and youth with physical disabilities. Arch Phys Med Rehabil 2007; 88: 63642.
  • 33
    Engel-Yeger B, Jarus T. Cultural and gender effects on Israeli children’s preferences for activities. Can J Occup Ther 2008; 75: 13948.
  • 34
    Allison KR, Dwyer JJM, Goldenberg E, Fein A, Yoshida KK, Boutilier M. Male adolescents’ reasons for participating in physical activity, barriers to participation, and suggestions for increasing participation. Adolescence 2005; 40: 15570.
  • 35
    Specht J, King G, Brown E, Foris C. The importance of leisure in the lives of persons with congenital physical disabilities. Am J Occup Ther 2002; 56: 43645.