Psychological health and safety of criminal justice workers: a scoping review of strategies and supporting research
Bibliographic record
Abstract
BACKGROUND: People working in the criminal justice system face substantial occupational stressors due to their roles involving high-risk situations, trauma exposure, heavy workloads, and responsibility for public safety. Consequently, they have a higher prevalence of mental health problems than the general population. Employees identifying as women, Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer, Intersexual, Asexual, and all others (2SLGBTQIA+), or Black, Indigenous, and People of Color (BIPOC), may experience additional stressors due to discrimination, harassment, and systemic barriers to seeking and receiving support. Psychoeducational and psychosocial programs have shown mixed effectiveness for preventing or reducing occupational stress, emphasizing the urgent need for multi-level, comprehensive, system-wide approaches. This scoping review aimed to capture and consolidate recommendations from strategies, frameworks, and guidelines on supporting the psychological health of criminal justice workers. RESULTS: The scoping review of 65 grey and 85 academic literature records presents recommendations aimed at improving the psychological health and safety of criminal justice system workers. Findings were mapped by occupational groups to the Social-Ecological Model and accounted for factors across the individual, interpersonal, institutional, and policy levels. The most common recommendation across all criminal justice occupational groups was workplace mental health training to reduce stigma, encourage help-seeking, prepare workers for traumatic incidents, and promote culturally responsive approaches. At the individual level, physical health, healthy lifestyle choices, and coping strategies were widely recommended. Interpersonal interventions, including peer support and models emphasizing wraparound care, were also recommended. Institutional factors such as fair workloads, safe working conditions, and harassment-free workplaces were emphasized. At the policy level, presumptive coverage policies and adequate funding for staffing needs were highlighted. CONCLUSION: This scoping review captured intersecting strategies and recommendations, consisting primarily of individual- and institutional-level supports and services. Fewer records discussed the need to address structural and policy considerations such as labor shortages, patchy mental health benefits, underfunding, and discrimination. The review highlights the need for shared responsibility across different levels, providing a framework for improving the psychological health and safety of criminal justice workers.
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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 | 0.021 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.029 | 0.024 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".