Factors associated with social participation and community ambulation in people with osteoarthritis: Findings from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
AIM: Walking in the community allows participation in meaningful activities which positively influences self-rated health and quality of life. Our objective was to identify factors associated with social participation and community ambulation in a representative sample of Canadian adults with osteoarthritis (OA). METHODS: Data were from >3800 participants in the Baseline Tracking Dataset of the Canadian Longitudinal Study on Aging with OA of the hip and/or knee. Outcomes included frequency of participation in 8 community-based activities (past year, social participation), and frequency walking outside the home (past 7 days, community ambulation). Explanatory variables (15 for social participation, 11 for community ambulation) established in previous literature were evaluated. Variables significant in univariate binary logistic regression models were entered into multivariable models. RESULTS: Frequency of social participation was greater for females, and individuals with higher levels of education. Those who were younger, dissatisfied with life, and had difficulty walking 2-3 blocks were less likely to participate. Having fewer chronic conditions, being younger, being single/widowed and being interviewed in spring/summer were associated with more frequent ambulation. Lower self-rated health, difficulty walking 2-3 blocks, pain and being female were associated with less frequent walking outside the home. CONCLUSION: Many factors influence frequency of social participation and community ambulation. The ability to walk short distances is positively associated with both outcomes. This important factor can and should be addressed clinically to improve health and quality of life in people with OA.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| 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".