Health outcomes of psychosocial stress within firefighters: A systematic review of the research landscape
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Much of the research surrounding firefighter health has concerned the hazards intuitively associated with the occupation, such as physical, thermal, and chemical risks. However, an additional aspect of their work environment, psychosocial stressors, has begun to attract a growing level of attention. Work-related psychosocial stress may best be described as mental and emotional strain caused by a combination of workplace events and characteristics, and the objective of our review was to identify the health outcomes associated with these stressors in firefighters. METHODS: A systematic review was performed of studies reporting on the psychosocial stressors and the associated health outcomes experienced by firefighters. Data sources included the MEDLINE, PsychInfo, and CINAHL databases. RESULTS: Twenty-nine studies met the inclusion criteria. Upon analysis, we found that firefighters experienced a range of psychosocial stressors (including interpersonal conflict and concerns over organizational fairness) and observed that these stressors were associated with a number of health-related outcomes that could be arranged into six areas: depression-suicidality, non-depressive mental health problems, burnout, alcohol use disorders, sleep quality, and physiological parameters and somatic disorders. CONCLUSION: Our findings strongly suggest that work-related psychosocial stressors can affect the health and well-being of those in the fire service, and highlight that interventions meant to address these psychosocial risk factors should focus upon promoting self-esteem, enhancing self-efficacy, and strengthening social support.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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 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".