Are you doing what you want to do? Leisure preferences of adolescents with cerebral palsy
Bibliographic record
Abstract
OBJECTIVE: This study aimed at describing leisure activity preferences of adolescents with cerebral palsy (CP) and their relationship to participation and to identify factors associated with greater interest in particular leisure activities. METHODS: A cross-sectional design was used. Participants were adolescents (n = 127; 59.5% male; ages 12-19 years old; mean = 15.3; SD = 2.01 years) with CP (GMFCS levels: I 40%, II 33%, III-IV 26%), who could complete the Preferences for Activities of Children (PAC) and other self-report questionnaires. RESULTS: Social (2.53; 0.38) and active-physical activities were most preferred (2.10; 0.42), and self-improvement activities were least preferred (1.93; 0.49). Preference for certain activities was not strongly associated with actual involvement in these activities. Family activity-orientation, family expressiveness, and adolescent's motivation explained 15% of the variance in preferences for social activities, and 37% of the variance in preferences for self-improvement activities. CONCLUSION: Family factors, personal factors, and functional abilities influence leisure preferences. Rehabilitation interventions should consider adolescents' preferences and family dynamics to promote leisure participation.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".