A prospective study of mental health care for comorbid depressed mood in older adults with painful osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Comorbid depression is common among adults with painful osteoarthritis (OA). We evaluated the relationship between depressed mood and receipt of mental health (MH) care services. METHODS: In a cohort with OA, annual interviews assessed comorbidity, arthritis severity, and MH (SF-36 mental health score). Surveys were linked to administrative health databases to identify mental health-related visits to physicians in the two years following the baseline interview (1996-98). Prescriptions for anti-depressants were ascertained for participants aged 65+ years (eligible for drug benefits). The relationship between MH scores and MH-related physician visits was assessed using zero-inflated negative binomial regression, adjusting for confounders. For those aged 65+ years, logistic regression examined the probability of receiving any MH-related care (physician visit or anti-depressant prescription). RESULTS: Analyses were based on 2,005 (90.1%) individuals (mean age 70.8 years). Of 576 (28.7%) with probable depression (MH score < 60/100), 42.5% experienced one or more MH-related physician visits during follow-up. The likelihood of a physician visit was associated with sex (adjusted OR women vs. men = 5.87, p = 0.005) and MH score (adjusted OR per 10-point decrease in MH score = 1.63, p = 0.003). Among those aged 65+, 56.7% with probable depression received any MH care. The likelihood of receiving any MH care exhibited a significant interaction between MH score and self-reported health status (p = 0.0009); with good general health, worsening MH was associated with increased likelihood of MH care; as general health declined, this effect was attenuated. CONCLUSIONS: Among older adults with painful OA, more than one-quarter had depressed mood, but almost half received no mental health care, suggesting a care gap.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".