Impact of persistent pain symptoms on work absence, health status and employment 18 months following disabling work-related injury or illness
Bibliographic record
Abstract
OBJECTIVES: While most individuals physically injured at work will make a complete medical recovery, a portion of workers will experience persistent pain following their injury. This study estimated persistent pain prevalence and its association with health and return-to-work outcomes 18 months following the incidence of a disabling work-related injury. METHODS: We studied 1131 workers disabled by a work-related injury who were recruited from a sampling frame of disability benefit claimants in Ontario, Canada. Work injuries and claim benefits characteristics from administrative data were linked with measures of work status, pain symptoms, and physical and mental health obtained from telephone interviews completed 18 months postinjury. Associations of persistent pain symptoms with health and employment outcomes 18 months postinjury were estimated using multinomial and linear regression. RESULTS: Roughly 30% of participants reported no pain symptoms in the previous 4 weeks, 45% reported mild pain symptoms and 25% reported severe pain symptoms accompanied by substantial functional impairment. Workers with severe pain symptoms were more likely to not be currently working at 18 months (33%) vs those without pain symptoms (16%), and had poorer self-reported physical and mental health. Workers with severe pain symptoms had higher probabilities of benefit durations of 12-18 months (OR=9.35), higher lost-earnings costs (~47.7% higher) and higher healthcare expenditure costs at 18 months (~125.9% higher) compared with those with no pain symptoms. CONCLUSIONS: Persistent pain symptom prevalence 18 months postinjury is high among workers disabled by a work-related injury and associated with substantial functional impairment and longer wage replacement benefit duration.
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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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".