Assessing the Relative Impact of Diverse Stressors among Public Safety Personnel
Bibliographic record
Abstract
Public Safety Personnel (PSP; e.g., correctional workers and officers, firefighters, paramedics, police officers, and public safety communications officials (e.g., call center operators/dispatchers)) are regularly exposed to potentially psychologically traumatic events (PPTEs). PSP also experience other occupational stressors, including organizational (e.g., staff shortages, inconsistent leadership styles) and operational elements (e.g., shift work, public scrutiny). The current research quantified occupational stressors across PSP categories and assessed for relationships with PPTEs and mental health disorders (e.g., anxiety, depression). The participants were 4820 PSP (31.7% women) responding to established self-report measures for PPTEs, occupational stressors, and mental disorder symptoms. PPTEs and occupational stressors were associated with mental health disorder symptoms (ps < 0.001). PSP reported substantial difficulties with occupational stressors associated with mental health disorder symptoms, even after accounting for diverse PPTE exposures. PPTEs may be inevitable for PSP and are related to mental health; however, leadership style, organizational engagement, stigma, sleep, and social environment are modifiable variables that appear significantly related to mental health.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".