Recovery Expectations Predict Recovery in Workers With Back Pain but Not Other Musculoskeletal Conditions
Why this work is in the frame
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Bibliographic record
Abstract
STUDY DESIGN: Prospective cohort study. OBJECTIVE: We examined whether recovery expectations predict future return-to-work in workers filing injury claims for a variety of musculoskeletal conditions. SUMMARY OF BACKGROUND DATA: Recovery expectations seem to influence recovery and return-to-work after back pain, but their role in other compensable conditions is uncertain. METHODS: All workers' compensation claimants receiving time-loss benefits for a musculoskeletal condition and undergoing return-to-work assessment were enrolled. Claimants completed a work-related recovery expectations questionnaire. Outcomes during the 1-year follow-up included surrogate indicators of timely return-to-work (days until suspension of time-loss benefits) and recovery (claim closure). Analysis included multivariable Cox regression. RESULTS: The sample consisted of 1040 claimants of whom 298 (29%) had back pain, 461 (44%) had sprains, strains, or pain of other body parts besides the back, 234 (23%) had specific injuries such as fracture, dislocation, or amputation, and 47 (5%) had other compensable conditions such as carpal tunnel syndrome or knee internal derangement. The majority of participants had chronic conditions (mean duration >6 mo). Negative work-related recovery expectations were consistently associated with slower suspension of time-loss benefits (Hazard Ratio 0.83) and slower claim closure (Hazard Ratio 0.84) in claimants with back pain, but associations in other diagnostic groups were inconsistent and not statistically significant. Associations were slightly larger within the group of claimants with back pain of less than 3-month duration. CONCLUSIONS: Recovery expectations provide some information for predicting future recovery in workers filing injury claims for back pain, but do not seem to predict recovery in claimants with other musculoskeletal conditions.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it