Police staff and mental health: barriers and recommendations for improving help-seeking
Bibliographic record
Abstract
Mental disorders are prevalent among public safety personnel (PSP) yet many people working across public safety professions appear reluctant to seek care for mental health-related concerns. Given the prevalence and impact of compromised mental health on these populations, finding ways to increase use of psychological support for police staff and officers is necessary. We conducted an interview and focus groups (n= 9) with police service members (n= 33) to examine the barriers police officers (n= 25) and communicators (n= 8) report facing when seeking treatment, and their suggestions for improving access to treatment. We identified three main barriers: stigma, worries about confidentiality, and occupation-specific experience with people in the community who present in mental distress. Three suggestions emerged from our participants that may improve current mental health support, namely, ensuring confidentiality, easy-to-use electronic resources, and access to occupation-specific content. We discuss the implications of our results with suggestions for policy and practice.
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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 | 0.023 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".