The Road to Mental Readiness for First Responders: A Meta-Analysis of Program Outcomes
Bibliographic record
Abstract
OBJECTIVES: First-responder mental health, especially in Canada, has been a topic of increasing interest given the high incidence of poor mental health, mental illness, and suicide among this cohort. Although research generally suggests that resiliency and stigma reduction programs can directly and indirectly affect mental health, little research has examined this type of training in first responders. The current paper examines the efficacy of the Road to Mental Readiness for First Responders program (R2MR), a resiliency and anti-stigma program. METHODS: The program was tested using a pre-post design with a 3-month follow-up in 5 first-responder groups across 16 sites. RESULTS: A meta-analytic approach was used to estimate the overall effects of the program on resiliency and stigma reduction. Our results indicate that R2MR was effective at increasing participants' perceptions of resiliency and decreasing stigmatizing attitudes at the pre-post review, which was mostly maintained at the 3-month follow-up. CONCLUSIONS: Both quantitative and qualitative data suggest that the program helped to shift workplace culture and increase support for others.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.021 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".