Anxiety and depression predict musculoskeletal disorders in health care workers
Bibliographic record
Abstract
Incidence of musculoskeletal disorders (MSDs) is high among health care workers (HCWs). To determine whether MSDs are associated with preexisting anxiety and/or depression, a case-control study was carried out in female HCWs (56 cases/55 controls). Cases were HCWs with a first-time clinical diagnosis of MSD within the previous 2 years. Occupation, workplace, work shift, direct patient assistance, and anxiety/depression scores (Goldberg scale) were assessed. Increased risk of incident MSDs (multivariate logistic regression) was found in workers with preexisting anxiety/depression compared to those without (OR 5.01; 95% CI 2.20-12.05; p < .01). Other significant risk factors were direct patient assistance (OR 2.59; 95% CI 1.03-6.92; p = .04) and morning work shift (OR 2.47; 95% CI 0.99-6.48; p = .05). Preexisting anxiety/depression was associated with incident MSDs in HCWs, adjusting for occupational exposure risk factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".