Stakeholder experiences of a public safety personnel work reintegration program
Bibliographic record
Abstract
Public safety personnel (PSP) are at risk of experiencing operational stress injuries (OSIs). The functional impairments caused by OSIs can contribute to challenges with returning to pre-injury operational requirements. A Canadian municipal policing agency developed a peer-led workplace reintegration program (RP) to assist PSP in their workplace reintegration after an illness or injury. Although this RP has been used internationally, there is a paucity of research on this program and its implementation by PSP organizations. The perspectives of key stakeholders are important for capturing the current state of RPs and future directions for the advocacy, implementation, sustainability, and spread of the RP, and to set the stage for future research. The purpose of this study was to explore the experiences and perspectives of key stakeholders engaged in the creation, implementation, facilitation, and execution of RPs in Alberta, Canada. This will help identify strengths, barriers, facilitators, needs, processes, and attitudes associated with the RPs and direction for future research. A qualitative thematic analysis of focus groups (N=8) involving key stakeholders (N=30) from five PSP organizations with RPs was conducted using a community-engaged research approach as part of a larger mixed-methods study. Four key themes emerged from the participants: (1) Integral elements of success, (2) Integral needs, (3) Key areas of growth, and (4) Evolution of the Program. While RPs are highly regarded by the key stakeholders, it is essential that evidence-based research guide the evaluation, modification, implementation, spread, and scale of RPs globally.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".