Appraisal of Washington State workers' compensation‐based return‐to‐work programs and suggested system improvements: A survey of workers with permanent impairments
Bibliographic record
Abstract
BACKGROUND: Following a work-related permanent impairment, injured workers commonly face barriers to safe and successful return to work (RTW). Examining workers' experiences with the workers' compensation (WC) system could highlight opportunities to improve RTW outcomes. Objectives included summarizing workers': (1) appraisal of several WC-based RTW programs, and (2) suggestions for vocational rehabilitation and WC system improvements to promote safe and sustained RTW. METHODS: In telephone interviews, 582 Washington State workers with work-related permanent impairments were asked whether participation in specified WC-based RTW programs helped them RTW and/or stay at work. Suggestions for program and system improvements were solicited using open-ended questions; qualitative content analysis methods were used to inductively code responses. RESULTS: Most respondents reported positive impacts from RTW program participation; for example, 62.5% of vocational rehabilitation participants reported it helped them RTW, and 51.7% reported it helped them stay at work. Among 582 respondents, 28.0% reported that no change was needed to the WC system, while 57.6% provided suggestions or critiques. Reduce delays/simplify process/improve efficiency was the most frequent WC system theme-mentioned by 34.9%. Among 120 vocational rehabilitation participants, 35.8% reported that no change was needed to vocational rehabilitation, while 46.7% (N = 56) provided suggestions or critiques. More worker choice/input into the vocational retraining plan was the most frequent vocational rehabilitation theme-mentioned by 33.9%. CONCLUSIONS: This study's findings suggest that there is substantial room for improvement in workers' experience with the WC system. In addition, injured workers' feedback may reflect opportunities to reduce administrative burden and to improve worker health and RTW outcomes.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".