Association Between Depressive Symptoms and Self-Reported Physical Activity in Persons With Knee Osteoarthritis
Bibliographic record
Abstract
Objective Depressive symptoms are common in patients with knee osteoarthritis (KOA) and reduce energy, motivation, and movement; thus, declines in physical activity (PA) could worsen as clinical disease progresses. The objective was to evaluate the longitudinal relationship between depressive symptoms and self-reported PA over time among persons with KOA. Methods The sample included Osteoarthritis Initiative participants (N = 2602) with radiographic disease (Kellgren-Lawrence grade ≥ 2). Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CES-D; score ≥ 16) at baseline and first 3 follow-up visits. Self-reported PA was assessed with the Physical Activity Scale for the Elderly (PASE) at the first 4 follow-up visits. Marginal structural models controlling for time-invariant and time-varying confounders evaluated the longitudinal relationship between depressive symptoms and PASE z scores. Results Depressive symptoms were associated with lower PA (β −0.09; 95% CI −0.20 to 0.01) over time, but the relationship was not statistically significant. When including depressive symptoms-by-time interactions, the relationship was nonlinear from the first to fourth follow-up visit: visit 1 = −0.18 (95% CI −0.33 to −0.02), visit 2 = −0.05 (95% CI −0.22 to 0.11), visit 3 = −0.01 (95% CI −0.19 to 0.16), and visit 4 = −0.11 (95% CI −0.29 to 0.08). However, the interaction terms were not statistically significant. Conclusion Depressive symptoms may contribute to worse self-reported PA levels in persons with KOA. Future research should determine whether lower physical function is a further sequela of decreased PA related to depressive symptoms.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".