Functional recovery following musculoskeletal injury in hospital workers
Bibliographic record
Abstract
BACKGROUND: Hospital workers are at high risk of work-related musculoskeletal disorders (WRMSDs), but outcomes following such injuries have not been well studied longitudinally. AIMS: To ascertain functional recovery in hospital workers following incident WRMSDs and identify predictors of functional status. METHODS: Cases (incident WRMSD) and matched referents from two hospitals were studied at baseline and at 2 year follow-up for health status [SF-12 physical component summary (PCS)], lost workdays, self-rated work effectiveness and work status change (job change or work cessation). Predictors included WRMSD and baseline demographics, socio-economic status (SES), job-related strain and effort-reward imbalance. Logistic regression analysis tested longitudinal predictors of adverse functional status. RESULTS: The WRMSD-associated risk of poor (lowest quartile) PCS was attenuated from a baseline odds ratio (OR) of 5.2 [95% confidence interval (CI) 3.5-7.5] to a follow-up OR of 1.5 (95% CI 1.0-2.3) and was reduced further in multivariate modelling (OR = 1.4; 95% CI 0.9-2.2). At follow-up, WRMSD status did not predict significantly increased likelihood of lost workdays, decreased effectiveness or work status change. In multivariate modelling, lowest quintile SES predicted poor PCS (OR = 2.0; 95% CI 1.0-4.0) and work status change (OR = 2.5; 95% CI 1.1-5.8). High combined baseline job strain/effort-reward imbalance predicted poor PCS (OR = 1.7; 95% CI 1.1-2.7) and reduced work effectiveness (OR = 2.6; 95% CI 1.6-4.2) at follow-up. CONCLUSIONS: Baseline functional deficits associated with incident WRMSDs were largely resolved by 2 year follow-up. Nonetheless, lower SES and higher combined job strain/effort-reward imbalance predicted adverse outcomes, controlling for WRMSDs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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 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".