Workplace mental health implementation strategies in public safety organizations: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: This scoping review aims to map workplace mental health implementation strategies in public safety organizations and describe the characteristics, participants, and contexts of these strategies. INTRODUCTION: Workplace mental health implementation strategies are relevant to public safety organizations due to the exposure that many public safety personnel, such as firefighters, paramedics, and police officers, have to psychological trauma in the course of their daily work. While the importance of attending to public safety personnel's mental health has been established, workplace mental health implementation strategies have historically varied in public safety organizations. INCLUSION CRITERIA: This scoping review will address workplace mental health implementation strategies used in public safety organizations. It will exclude studies that do not focus on workplace mental health, do not report on the implementation strategies used, or do not take place in a public safety context. METHODS: Primary studies published in English with any publication date up to the present will be considered. JBI methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will be followed. The search will be carried out in five databases and reference lists will also be searched for additional studies. Duplicates will be removed, and two independent reviewers will screen the titles, abstracts, and full text of the selected studies. Data collection will be performed using a tool developed by the researchers, based on JBI's model instrument for extracting study details, characteristics, and results. A summary of the results will be presented in diagrams, narratives, and tables.
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 | 0.142 | 0.095 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.026 | 0.019 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.056 | 0.015 |
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".