Putative risk and resiliency factors among Royal Canadian Mounted Police cadets
Bibliographic record
Abstract
Objective Mental health disorders are prevalent among active-duty Royal Canadian Mounted Police (RCMP) officers. The current study was designed to assess whether RCMP cadets commencing the Cadet Training Program are inherently at greater risk of developing mental health challenges by statistically comparing cadet putative risk and resiliency scores to scores from young adult populations. The study was also designed to assess for sociodemographic differences in putative risk and resiliency variables among RCMP cadets in order to facilitate future comparisons. Methods Cadets ( n = 772; 72.2% men) completed self-report measures of several putative risk variables (i.e., anxiety sensitivity, fear of negative evaluation, pain anxiety, illness and injury sensitivity, intolerance of uncertainty, and state anger) and resiliency. Scores were statistically compared to samples from Canadian, American, Australian, and European young adult populations. Results Cadets had statistically significantly lower scores on all putative risk variables and statistically significantly higher resiliency scores compared to the young adult populations. In the cadet sample, there were statistically significant differences in putative risk and resiliency variables across gender and sex. Conclusion Cadets’ significantly lower scores on putative risk variables and higher scores on resiliency suggest that they may be psychologically strong; as such, it may be that the nature of police work, as opposed to inherent individual differences in risk and resiliency, accounts for active-duty RCMP officers’ comparatively higher prevalence of mental health disorders over time. Clinical Trial Registration : ClinicalTrials.gov , Identifier NCT05527509.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".