“I’m pulling through because of you”: injured workers’ perspective of workplace factors supporting return to work under the Saskatchewan Workers’ Compensation Board scheme
Bibliographic record
Abstract
Background: Research demonstrates sustained return to work (RTW) by individuals on medical leave is influenced by personal and job resources and job demands. Relatively few studies have been conducted in the workers' compensation context that is known to have longer absence durations for RTW. Aims: This study sought to illuminate workers' experience as they returned to work following a work injury that was either psychological in nature or involved more than 50 days of disability, with a focus on the co-worker, supervisor, and employer actions that supported their return. Methods: Workers in Saskatchewan, Canada, with a work-related psychological or musculoskeletal injury, subsequent disability, and who returned to work in the last three years, were invited to complete an online survey comprising of free-text questions. Thematic analysis was used to explore participants' experiences. Results: Responses from 93 individuals were analysed. These revealed that persistent pain, emotional distress, and loss of normal abilities were present during and beyond returning to work. Almost two-thirds indicated that the supervisors' and co-workers' support was critical to a sustained return to work: their needs were recognized and they received autonomy and support to manage work demands. By contrast, one-third indicated that the support they expected and needed from supervisors and employers was lacking. Conclusions: Workers returning to work lacked personal resources but co-workers' and supervisors' support helped improve confidence in their ability to RTW. Supervisors and employers should acknowledge workers' experiences and offer support and autonomy. Likewise, workers can expect challenges when returning to work and may benefit from cultivating supportive relationships with co-workers and supervisors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".