Hostility in firefighters: personality and mental health
Bibliographic record
Abstract
Purpose – The purpose of this paper is to investigate the contribution of personality factors, especially hostility, as they related to traumatic stress and mental health symptoms in firefighters. Design/methodology/approach – A group of paid-professional firefighters ( n =94) completed a questionnaire study that included a demographic questionnaire, the Impact of Event Scale-Revised, the NEO Five-Factor Inventory-Revised, the Framingham Type A Scale, and the Symptom Checklist-90. Multiple regressions were used to evaluate the relationship between neuroticism or lack of agreeableness with hostility, controlling for Type A, years of service and age. Subsequently, hostility was used to predict traumatic stress and mental health symptoms, controlling for Type A, years of service, age, neuroticism, and lack of agreeableness. Findings – Both neuroticism and lack of agreeableness were determined to be significant predictors of hostility. Further, hostility positively predicted somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, paranoid ideation, psychoticism, Global Severity Index, Positive Symptom Distress Index, and Positive Symptoms Total. Although not significant, trends that hostility also predicted traumatic stress and phobic anxiety were evident. Originality/value – To the knowledge, this is the first study to specifically investigate the impact of hostility on mental health of paid-professional firefighters. In addition, the findings suggest that interventions to screen for and subsequently reduce hostility in firefighters may be beneficial for overall mental health (e.g. anger management training, etc.).
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".