Participation in Leisure Activities among Canadian Children with Arthritis: Results from a National Representative Sample
Bibliographic record
Abstract
OBJECTIVE: To describe the level of participation in leisure activities among children and youth with arthritis, as well as to identify the sociodemographic (age, sex, family income), disease-related (functional limitations, disease duration, pain, medication use, child's need for assistance), and contextual factors (use of rehabilitation services, proximity of local recreation facilities, cost of activities) that may be associated. METHODS: Data from the Participation and Activity Limitation Survey (PALS) 2006, a Canadian postcensus survey, was analyzed. Bivariate and multivariable linear regression analyses were applied to examine the associations between the sample's level of participation in leisure activities, and sociodemographic, disease-related, and contextual characteristics. RESULTS: In Canada in 2006, an estimated 4350 children ranging in age from 5 to 14 years were living with arthritis. Fifty-six percent of parents reported that arthritis restricted their child's participation in leisure activities. Bivariate analysis showed that the availability of local recreational facilities, the affordability of activities, and the child not requiring any assistance were all associated (modified Bonferroni correction α < 0.005) with greater participation in various types of leisure activities. Multiple linear regressions showed that higher family income (β 0.47, 95% CI 0.09, 0.85) and greater perceived pain (β 0.59, 95% CI 0.07, 1.10) were positively associated with involvement in informal leisure. CONCLUSION: Our findings underline the importance of considering contextual factors in developing treatment plans aimed at improving participation in leisure activities among children with arthritis. Future longitudinal studies targeting children living with arthritis could provide pertinent information on participation over fluctuations in disease status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".