Within-Person Pain Variability and Mental Health in Older Adults With Osteoarthritis: An Analysis Across 6 European Cohorts
Bibliographic record
Abstract
Pain is a key symptom of osteoarthritis (OA) and has been linked to poor mental health. Pain fluctuates over time within individuals, but a paucity of studies have considered day-to-day fluctuations of joint pain in relation to affective symptoms in older persons with OA. This study investigated the relationship of pain severity as well as within-person pain variability with anxiety and depression symptoms in 832 older adults with OA who participated in the European Project on OSteoArthritis (EPOSA): a 6-country cohort study. Affective symptoms were examined with the Hospital Anxiety and Depression Scale, pain severity was assessed with the Western Ontario and McMaster Universities OA Index and the Australian/Canadian Hand Osteoarthritis Index, and intraindividual pain variability was measured using pain calendars assessed at baseline, 6, and 12 to 18 months. Age-stratified multiple linear regression analyses adjusted for relevant confounders showed that more pain was associated with more affective symptoms in older-old participants (74.1-85 years). Moreover, older-old participants experienced fewer symptoms of anxiety (ratio = .85, 95% confidence interval [CI], .77-.94), depression (ratio = .90, 95% CI, .82-.98), and total affective symptoms (ratio = .87, 95% CI, .79-.94) if their pain fluctuated more. No such association was evident in younger-old participants (65-74.0 years). These findings imply that stable pain levels are more detrimental to mental health than fluctuating pain levels in older persons. PERSPECTIVE: This study showed that more severe and stable joint pain levels were associated with anxiety and depressive symptoms in older persons with OA. These findings emphasize the importance of measuring pain in OA at multiple time points, because joint pain fluctuations may be an indicator for the presence of affective symptoms.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".