Predicting Time on Prolonged Benefits for Injured Workers with Acute Back Pain
Bibliographic record
Abstract
INTRODUCTION: Some workers with work-related compensated back pain (BP) experience a troubling course of disability. Factors associated with delayed recovery among workers with work-related compensated BP were explored. METHODS: This is a cohort study of workers with compensated BP in 2005 in Ontario, Canada. Follow up was 2 years. Data was collected from employers, employees and health-care providers by the Workplace Safety and Insurance Board (WSIB). Exclusion criteria were: (1) no-lost-time claims, (2) >30 days between injury and claim filing, (3) <4 weeks benefits duration, and (4) age >65 years. Using proportional hazard models, we examined the prognostic value of information collected in the first 4 weeks after injury. Outcome measures were time on benefits during the first episode and time until recurrence after the first episode. RESULTS: Of 6,657 workers, 1,442 were still on full benefits after 4 weeks. Our final model containing age, physical demands, opioid prescription, union membership, availability of a return-to-work program, employer doubt about work-relatedness of injury, worker's recovery expectations, participation in a rehabilitation program and communication of functional ability was able to identify prolonged claims to a fair degree [area under the curve (AUC) = .79, 95% confidence interval (CI) .74-.84]. A model containing age, sex, physical demands, opioid prescription and communication of functional ability was less successful at predicting time until recurrence (AUC = .61, 95% CI .57, .65). CONCLUSIONS: Factors contained in information currently collected by the WSIB during the first 4 weeks on benefits can predict prolonged claims, but not recurrent claims.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| 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".