Mental disorders, suicidal ideation, plans and attempts among Canadian police
Bibliographic record
Abstract
BACKGROUND: Recent investigations have demonstrated a significant prevalence of mental health disorders, including post-traumatic stress disorder (PTSD), and suicidal ideation, plans and attempts among Canadian public safety personnel, including police officers. What remains unknown is the relationship between mental disorders and suicide among sworn police officers, and the prevalence of both among civilian police workers. AIMS: To examine the relationship between suicidal ideation, plans and attempts and positive mental health screens for depression, anxiety, panic disorder, alcohol abuse and PTSD among Canadian sworn and civilian police employees. METHODS: Participants completed an online survey that included self-report screening tools for depression, anxiety, panic disorder, alcohol abuse and PTSD. Respondents were also asked if they ever contemplated, planned or attempted suicide. Between-group (Royal Canadian Mounted Police [RCMP], provincial/municipal police and civilians) differences on mental health screening tools were calculated using Kruskal-Wallis analyses. The relationship between mental disorders and suicidal ideation, plans and attempts was evaluated with a series of logistic regressions. RESULTS: There were 4236 civilian and sworn officer participants in the study. RCMP officers reported more suicidal ideation than other police and scored highest on measures of PTSD, depression, anxiety, stress and panic disorder, which were significantly associated with suicidal ideation and plans but not attempts. Relative to provincial and municipal police, civilians reported more suicide attempts and scored higher on measures of anxiety. CONCLUSIONS: The results identify a strong relationship between mental health disorders and increased risk for suicidal ideation, plans and attempts among sworn and civilian Canadian police employees.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".