Leisure participation–preference congruence of children with cerebral palsy: a Children's Assessment of Participation and Enjoyment International Network descriptive study
Bibliographic record
Abstract
AIM: To examine participation-preference congruence, regional differences in participation-preference congruence, and predictors of whether children with cerebral palsy participate in preferred activities. METHOD: The sample (n=236) included 148 males and 88 females aged 10 to 13 years, living in Victoria, Australia (n=110), Ontario (n=80), or Quebec (n=46), Canada. Ninety-nine (41.9%) were classed at Gross Motor Function Classification System (GMFCS) level I; 89 (37.7%) at GMFCS level II/III; and 48 (20.3%) at GMFCS level IV/V. Participants completed the Children's Assessment of Participation and Enjoyment and Preferences for Activity of Children questionnaires. Regional comparisons were performed using one-way analyses of variance and factors influencing participation-preference congruence were explored using multiple linear regression. RESULTS: The proportion of children doing non-preferred activities in each activity type was generally low (2-17%), with only one regional difference. Higher proportions were not doing preferred active physical (range 23.2-29.1% across regions), skill-based (range 21.7-27.9% across regions), and social activities (range 12.8-14.5% across regions). GMFCS level was the most important predictor associated with not doing preferred activities. INTERPRETATION: Children with cerebral palsy did not always participate in preferred active physical and skill-based activities. Understanding discrepancies between preferences and actual involvement may allow families and rehabilitation professionals to address participation barriers.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".