Assessing the Perceptions and Impact of Critical Incident Stress Management Peer Support among Firefighters and Paramedics in Canada
Bibliographic record
Abstract
Relative to the general population, public safety personnel (PSP) appear at an increased risk of developing mental health challenges as a result of repeated exposure to potentially psychologically traumatic events (PPTEs). To help mitigate the impact of PPTEs on PSP mental health, many PSP agencies have implemented diverse peer support despite limited empirical evidence. The current study was designed to expand the empirical evidence surrounding peer support by investigating one of the most widely used and structured peer support resources: Critical Incident Stress Management (CISM). Specifically, the current study with integrated firefighters and paramedics assessed (a) the prevalence of mental disorders; (b) perceptions of high fidelity CISM peer support; and (c) the comparative associations of CISM with high fidelity (n = 91) versus unknown fidelity (n = 60) versus no CISM (n = 64) and mental health. Results indicated that (a) mental disorders are prevalent among PSP irrespective of gender, age, and years of service; (b) participants perceived CISM peer support as offering beneficial and valuable tools (e.g., skills and coping strategies); and (c) high fidelity CISM environments offer some mental health benefits to individuals who screen positive for alcohol use disorder and generalized anxiety disorder. Overall, the current study offers novel information that can inform future directions for evidence-based peer support and policy decisions designed to support the mental health of PSP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".