Measuring children’s participation in recreation and leisure activities: construct validation of the CAPE and PAC
Bibliographic record
Abstract
There is a need for psychometrically sound measures of children's participation in recreation and leisure activities, for both clinical and research purposes. This paper provides information about the construct validity of the Children's Assessment of Participation and Enjoyment (CAPE) and its companion measure, Preferences for Activities of Children (PAC). These measures are appropriate for children and youth with and without disabilities between the ages of 6 and 21 years. They provide information about six dimensions of participation (i.e. diversity, intensity, where, with whom, enjoyment and preference) and two categories of recreation and leisure activities: (i) formal and informal activities; and (ii) five types of activities (recreational, active physical, social, skill-based and self-improvement). This paper presents information about the performance of the CAPE and PAC activity type scores using data from a study involving 427 children with physical disabilities between the ages of 6 and 15 years. Intensity, enjoyment and preference scores were significantly correlated with environmental, family and child variables, in expected ways. Predictions also were supported with respect to differences in mean scores for boys vs. girls, and children in various age groups. The information substantiates the construct validity of the measures. The clinical and research utility of the measures are discussed.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".