Addressing the Mental Health Needs of Inmates Through Education for Correctional Officers—A Narrative Review
Bibliographic record
Abstract
INTRODUCTION: People with mental illness are overrepresented in correctional facilities. Correctional officers (COs) lack education to respond to inmates with mental illness. A review was conducted of mental health education programs for COs to identify factors related to effectiveness. METHODS: Medical and criminal justice databases were searched for articles describing mental health education for COs. Studies including measurable outcomes were analyzed using an inductive analytic approach. The review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for scoping reviews. Data were synthesized using Moore seven levels of outcomes for continuing professional development education. Findings were grouped by curriculum content and described according to levels of outcome. RESULTS: Of 1492 articles, 11 were included in the analysis. Six described mental health programs, two described skill-specific programs, and three described suicide prevention programs. Programs reviewed content about mental illness, practical skills, included didactic and experiential teaching. The programs achieved level 5 on Moore taxonomy. Programs led to improvements in knowledge, skills, and attitudes among officers; however, improvements declined post-training. Officers were receptive to facilitators with correctional or lived mental health experience. Experiential teaching was preferred. Common themes related to programs' effectiveness included applicability to COs, information retention, program facilitators, and teaching methods. DISCUSSION: There is limited, but positive literature suggesting that education programs are beneficial. The decline in improvements suggests need to ensure sustainability of improvements. This review can guide the planning of future education programs for COs based on continuing professional development best practices.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".