Does gradually returning to work improve time to sustainable work after a work-acquired musculoskeletal disorder in British Columbia, Canada? A matched cohort effectiveness study
Bibliographic record
Abstract
OBJECTIVE: This study investigates if gradual return to work (GRTW) is associated with full sustainable return to work (RTW) for seriously injured workers with a musculoskeletal disorder (MSD), in British Columbia, Canada. METHODS: This is an effectiveness study using a retrospective cohort study design. Accepted workers' compensation lost-time claims were extracted for workers with an MSD who were on full work disability for at least 30 days, between 2010 and 2015 (n=37 356). Coarsened exact matching yielded a final matched cohort of 12 494 workers who experienced GRTW at any point 30 days post-injury and 12 494 workers without any GRTW. The association between GRTW and sustainable RTW through to end of 12 months was estimated with multivariable quantile regression. RESULTS: Workers who were provided with GRTW experienced more time-loss days until sustainable RTW between the 2nd and 5th months after the first time-loss day (<50th quantile of time loss), but less time-loss days until sustainable RTW between the 6th and 12th months of work disability (70th quantile of time loss), with the largest effect for women, workers with soft-tissue injuries and workers in the manufacturing or trades sector (all in the 60th and 70th percentile, after 6-7 months of time loss). CONCLUSIONS: For seriously injured workers with at least 30 days of disability due to a work-acquired MSD, the effect of GRTW becomes apparent at longer disability durations (more than 6 months), with larger beneficial effects for women, workers with soft-tissue injuries and for trade and manufacturing sectors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".