Work outcomes in public safety personnel after potentially traumatic events: A systematic review
Bibliographic record
Abstract
BACKGROUND: It is well documented that public safety personnel are exposed to potentially traumatic events (PTEs) at elevated frequency and demonstrate higher prevalence of trauma-related symptoms compared to the general population. Lesser studied to date are the organizational consequences of workplace PTE exposure and associated mental health outcomes such as acute/posttraumatic stress disorder (ASD/PTSD), depression, and anxiety. METHODS: The present review synthesizes international literature on work outcomes in public safety personnel (PSP) to explore whether and how PTE and trauma-related symptoms relate to workplace outcomes. A total of N = 55 eligible articles examining PTE or trauma-related symptoms in relation to work outcomes were systematically reviewed using best-evidence narrative synthesis. RESULTS: Three primary work outcomes emerged across the literature: absenteeism, productivity/performance, and costs to organization. Across n = 21 studies of absenteeism, there was strong evidence that PTE or trauma-related symptoms are associated with increased sickness absence. N = 27 studies on productivity/performance demonstrated overall strong evidence of negative impacts in the workplace. N = 7 studies on cost to organizations demonstrated weak evidence that PTE exposure or trauma-related mental health outcomes are associated with increased cost to organization. CONCLUSIONS: Based on available evidence, the experience of workplace PTE or trauma-related symptoms is associated with negative impact on PSP occupational functioning, though important potential confounds (e.g., organizational strain and individual risk factors) remain to be more extensively investigated.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".