Daily survey participation and positive changes in mental health symptom scores among Royal Canadian Mounted Police Cadets
Bibliographic record
Abstract
Introduction: Royal Canadian Mounted Police (RCMP) officers self-report high levels of mental health disorder symptoms, such as alcohol use disorder, generalized anxiety disorder, major depressive disorder, panic disorder, and posttraumatic stress disorder. Participation in regular mental health monitoring has been associated with improved mental health disorder symptom reporting and may provide an accessible tool to support RCMP mental health. The current study assessed relationships between self-reported mental health disorder symptoms and the completion of daily surveys (i.e., daily mental health disorder symptom monitoring) by RCMP cadets during the Cadet Training Program (CTP). Methods: = 394; 76.1% men) in the Standard Training Program who completed the 26-week CTP and daily self-monitoring surveys, as well as full mental health assessments at pre-training (i.e., starting the CTP) and pre-deployment (i.e., ~2 weeks prior to deployment to the field). Symptoms of alcohol use disorder, generalized anxiety disorder, major depressive disorder, panic disorder, and posttraumatic stress disorder were assessed. Changes in mental health disorder symptom reporting from pre-training to pre-deployment were calculated. Spearman's rank correlations were estimated for number of daily surveys completed and change in mental health disorder symptom scores between pre-training and pre-deployment. Results: There were statistically significant inverse relationships between number of daily surveys completed and number of mental health disorder symptoms reported; specifically, cadets who completed more daily surveys during CTP reported fewer symptoms of alcohol use disorder, generalized anxiety disorder, major depressive disorder, panic disorder, and posttraumatic stress disorder. Conclusion: An inverse correlation between number of daily surveys completed and mental health disorder symptom scores indicated that participation in daily mental health monitoring was associated with improvements in self-reported mental health disorder symptoms between pre-training and pre-deployment. Regular self-monitoring of mental health disorder symptoms may help to mitigate mental health challenges among RCMP cadets and officers.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".