Participation predictors for leisure‐time physical activity intervention in children with cerebral palsy
Bibliographic record
Abstract
AIM: To determine the predictors of magnitude of change in response to a participation-focused leisure-time physical activity intervention in children with cerebral palsy (CP) using the ParticiPAte CP protocol. METHOD: We included 33 children (16 males, 17 females) aged 8 to 12 years (mean age=10y, SD=1y 6mo) with CP with pre/postintervention data from a wait-list randomized trial. The hypothesized linear predictors of change in primary outcomes (Canadian Occupational Performance Measure [COPM]-performance and COPM-satisfaction, Belief in Goal Self-Competence Scale (BiGSS), and minutes per day moderate-to-vigorous physical activity [MVPA]) were: age; Gross Motor Function Classification System level; comorbid autism spectrum disorder (ASD); Goal Attainment Scaling T score; Problems in Schools Questionnaire; Physical Activity Climate Questionnaire; Motives for Physical Activities Measure-Revised; and stage of behaviour change. Multivariable models were selected using the Bayesian information criterion. RESULTS: Overcoming barriers to participation, age, and comorbid ASD explained 49% of the variance in change in COPM-performance. Being motivated by interest and/or enjoyment and age explained 32% of the variance in change in COPM-satisfaction. Being motivated by physical activity competence or appearance (extrinsic motivation) explained 24% of the variance in change in BiGSS. Parental autonomy supportiveness, overcoming barriers to participation, appearance motivation, and baseline MVPA explained 59% of the variance in change in MVPA. INTERPRETATION: These findings support a behaviour paradigm for conceptualizing physical activity in children with CP. WHAT THIS PAPER ADDS: Children who met their treatment goals showed a greater increase in physical activity participation. Children who were more intrinsically motivated by physical activity at baseline improved more. Being older and having a comorbid diagnosis of autism spectrum disorder were associated with an attenuated effect of the therapy.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".