An investigation of a workplace-based return-to-work program for shoulder injuries
Bibliographic record
Abstract
The purpose of this study was to investigate and evaluate the current workplace management of rotator cuff injuries in a manufacturing plant. The secondary aims were to examine the impact of the company's return-to-work processes, compare outcomes to current industry standards for work (re)entry and to identify the components that characterized this workplace-based return-to-work (RTW) program. This investigation involved a case study approach comprised of an examination of the program context using interviews, onsite visits, a document review and a retrospective analysis of the RTW experiences of 184 workers with shoulder injuries. Findings revealed that the workplace-based RTW program was consistent with and shaped by the organizational culture of problem solving, knowledge exchange and equitable participation of workers, supervisors and health professionals. These components contributed to the program in achieving the following outcomes for workers with shoulder injuries. One-third of workers were placed on modified duties within three days, 56% of workers who engaged in an early RTW program returned to work within one month. Overall, 87.8% of workers with rotator cuff injuries successfully returned to pre-injury work. The implications of developing capacity for workplace-based programs to manage injuries at work are discussed.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".