Factors Associated with Participation in Physical Activity Among Canadian School-Aged Children with Autism Spectrum Disorder: An Application of the International Classification of Functioning, Disability and Health
Bibliographic record
Abstract
We have a limited understanding of the socioenvironmental factors associated with participation in physical activity among school-aged children with autism spectrum disorder (ASD), particularly regarding how the school environment may influence their participation. Using the International Classification of Functioning, Disability and Health (ICF) as a framework, this study examined the effect of body functions and structure, activity, and personal factors on in-school physical activity; and whether in-school physical activity, considered a socioenvironmental factor, is associated with out-of-school physical activity (i.e., participation) among elementary school-aged children (6–13 years of age) with ASD. Parents of 202 children with ASD (78.2% boys; Mage = 9.4 years) completed an online survey, as part of a larger study, to assess their child’s functioning and physical activity in- and out-of-school. Results indicated that the majority of children (85.1%) did not meet physical activity guidelines. In-school physical activities significantly predicted out-of-school physical activities including leisure-time moderate-to-vigorous physical activity (R2 = 0.27, F(10,154) = 5.67, p < 0.001) and meeting the physical activity guidelines (R2 = 0.23, Χ2 (10) = 31.9, p < 0.001). These findings underscore the importance of supporting children with ASD to be physically active in school, which may impact physical activity levels out-of-school.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".