Play and Be Happy? Leisure Participation and Quality of Life in School-Aged Children with Cerebral Palsy
Bibliographic record
Abstract
The objective of this study was to examine the association between leisure participation and quality of life (QoL) in school-age children with cerebral palsy (CP). Leisure participation was assessed using the Children's Assessment of Participation and Enjoyment (CAPE) and QoL using the Pediatric Quality of Life Inventory (PedsQL). Pearson correlation coefficients were calculated to examine the association between CAPE and PedsQL scores, and a multiple linear regression model was used to estimate QoL predictors. Sixty-three children (mean age 9.7 ± 2.1 years; 39 male) in GMFCS levels I-V were included. Intensity of participation in active-physical activities was significantly correlated with both physical (r = 0.34, P = 0.007) and psychosocial well-being (r = 0.31, P = 0.01). Intensity and diversity of participation in skill-based activities were negatively correlated with physical well-being (r = -0.39, P = 0.001, and r = -0.41, P = 0.001, resp.). Diversity and intensity of participation accounted for 32% (P = 0.002) of the variance for physical well-being and 48% (P < 0.001) when age and gross motor functioning were added. Meaningful and adapted leisure activities appropriate to the child's skills and preferences may foster QoL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".