The Royal Canadian Mounted Police (RCMP) Study: protocol for a prospective investigation of mental health risk and resilience factors
Bibliographic record
Abstract
The Royal Canadian Mounted Police (RCMP), like all public safety personnel (PSP), are frequently exposed to potentially psychologically traumatic events that contribute to posttraumatic stress injuries (PTSI). Addressing PTSI is impeded by the limited available research. In this protocol paper, we describe the RCMP Study, part of the concerted efforts by the RCMP to reduce PTSI by improving access to evidence-based assessments, treatments and training as well as participant recruitment and RCMP Study developments to date. The RCMP Study has been designed to (1) develop, deploy and assess the impact of a system for ongoing annual, monthly and daily evidence-based assessments; (2) evaluate associations between demographic variables and PTSI; (3) longitudinally assess individual differences associated with PTSI; (4) augment the RCMP Cadet Training Program with skills to proactively mitigate PTSI; and (5) assess the impact of the augmented training condition (ATC) versus the standard training condition (STC). Participants in the STC (n = 480) and ATC (n = 480) are assessed before and after training and annually for 5 years on their deployment date; they also complete brief monthly and daily surveys. The RCMP Study results are expected to benefit the mental health of all participants, RCMP and PSP by reducing PTSI among all who serve.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.068 | 0.014 |
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".