Understanding the Association Between Osteoarthritis and Social Participation: The Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVE: The focus on disability in osteoarthritis (OA) has largely been on the ability to perform specific activities, which neglects the greater implications for social participation. We investigated the association between OA and social participation, considering activity limitations and instrumental supports as intervening variables in the association. METHODS: Data were from 21,214 respondents, ages 45-85 years, from cycle 1 of the Canadian Longitudinal Study on Aging. The questionnaire elicited information regarding self-reported doctor-diagnosed OA, difficulty with 14 activities, perceived availability and receipt of instrumental supports, and 17 social participation activities. Structural equation modeling was used. The primary outcome was social participation, and the primary predictor was OA. The intervening variables included activity limitations, received instrumental supports, and perceived instrumental supports. Latent variables were developed for intervening and social participation variables. The covariates included age, sex, body mass index, income, education, smoking, and comorbidity count. RESULTS: The mean age of the respondents was 63 years, 51% were female, and 26.5% reported having OA. Two distinct social participation indicators were identified, including social participation-diversity and social participation-intensity. When intervening variables were not considered, minimal/no association was found between OA and social participation. When intervening variables were considered, unique pathways linking OA and social participation were found. The overall negative association between activity limitations and social participation was partially direct and partially buffered by both receipt of and perceived availability of instrumental supports. In the absence of activity limitations, OA was associated with greater social participation. CONCLUSION: Enhanced social participation in people with OA who do not have activity limitations may reflect proactive steps taken by those with mild OA to maintain activity and social engagement. For those with activity limitations, findings highlight the need for interventions to mitigate limitations and draw particular attention to the importance of both provision and awareness of available instrumental supports in maintaining social 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".