Longitudinal assessment of psychological distress and its determinants in a sample of firefighters based in Montreal, Canada
Bibliographic record
Abstract
Introduction: Firefighters face elevated risks of common mental health issues, with distress rates estimated at around 30%, surpassing those of many other occupational groups. While exposure to potentially traumatic events (PTEs) is a well-recognized risk factor, existing research acknowledges the need for a broader perspective encompassing multidimensional factors within the realm of occupational stress. Furthermore, this body of evidence heavily relies on cross-sectional studies. This study adopts an intensive longitudinal approach to assess psychological distress and its determinants among firefighters. Methods: Participants were recruited from 67 fire stations in Montreal, Canada, meeting specific criteria: full-time employment, smartphone ownership, and recent exposure to at least one PTE, or first responder status. Subjects underwent a telephone interview and were directed to use an app to report depressive, post-traumatic, and generalized anxiety symptoms every 2 weeks, along with work-related stressors, social support, and coping styles. Analyses involved 274 participants, distinguishing between those exceeding clinical thresholds in at least one distress measure (the "distressed" subgroup) and those deemed "resilient." The duration and onset of distress were computed for the distressed group, and linear mixed models were employed to evaluate determinants for each psychological distress variable. Results: Clinical psychological distress was observed in 20.7% of participants, marked by depressive, post-traumatic, and anxiety symptoms, often within the first 4-week reference period. Contextual factors (operational climate, social support, solitude) and individual factors (coping style, solitude and lifetime traumatic events in private life) exhibited more significant impacts on psychological distress than professional pressures within the firefighters' work environment. Discussion: This study reports lower rates of psychological distress than previous research, possibly attributable to sample differences. It highlights that reported symptoms often represent a combined and transient layer of distress rather than diagnosable mental disorders. Additionally, determinants analysis underscores the importance of interpersonal relationships and coping mechanisms for mental health prevention interventions within this worker group. The findings carry implications for the development of prevention and support programs for firefighters and similar emergency workers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.001 | 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".