Examining mental health knowledge, stigma, and service use intentions among Royal Canadian Mounted Police cadets
Bibliographic record
Abstract
Background: Royal Canadian Mounted Police (RCMP) officers experience an elevated risk for mental health disorders due to inherent work-related exposures to potentially psychologically traumatic events and occupational stressors. RCMP officers also report high levels of stigma and low levels of intentions to seek mental health services. In contrast, very little is known about the levels of mental health knowledge and stigma of RCMP cadets starting the Cadet Training Program (CTP). The current study was designed to: (1) obtain baseline levels of mental health knowledge, stigma against peers in the workplace, and service use intentions in RCMP cadets; (2) determine the relationship among mental health knowledge, stigma against peers in the workplace, and service use intentions among RCMP cadets; (3) examine differences across sociodemographic characteristics; and (4) compare cadets to a sample of previously surveyed serving RCMP. Methods: = 772) starting the 26-week CTP. Cadets completed questionnaires assessing mental health knowledge, stigma against coworkers with mental health challenges, and mental health service use intentions. Results: s < 0.001). Female cadets reported statistically significantly higher scores on mental health knowledge and service use and lower scores on stigma compared to male cadets. Mental health knowledge and service use intentions were statistically significantly positively associated. For the total sample, stigma was inversely statistically significantly associated with mental health knowledge and service use intentions. Conclusion: The current results indicate that higher levels of mental health knowledge were associated with lower stigma and higher intention to use professional mental health services. Differences between cadets and serving RCMP highlight the need for regular ongoing training starting from the CTP, designed to reduce stigma and increase mental health knowledge. Differences between male and female cadets suggest differential barriers to help-seeking behaviors. The current results provide a baseline to monitor cadet mental health knowledge and service use intentions and stigma as they progress throughout their careers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".