Understanding the Role of Empathy and Gender on EMS Clinician Occupational Stress and Mental Health Outcomes
Bibliographic record
Abstract
BACKGROUND: Emergency Medical Service (EMS) clinicians experience high levels of occupational stress due to long hours, short staffing, and patient deaths, among other factors. While gender has been partially examined, little is known regarding the role of empathy on occupational stress and mental health (MH) outcomes among EMS clinicians. Therefore, the current study examines the moderating role of empathy and, separately, gender on associations between occupational stress and mental health. METHODS: an anonymous, electronic survey. Information on clinician demographics, and validated measures of occupational stress, burnout, and MH outcomes were collected. Empathy was assessed using the Toronto Empathy Scale (TEQ). Descriptive/bivariate statistics were conducted for variables of interest. Separate multivariable regression models evaluated associations between occupational stress and mental health outcomes. Empathy and gender were examined as potential moderators using interactions. RESULTS: A total of 568 EMS clinicians completed the survey. High levels of mental health difficulties were reported (34.0% anxiety, 29.2% depression, 48.6% burnout). Increased occupational stress was associated with increased anxiety (OR =1.08, 95% CI 1.05-1.10), depression (OR = 1.09, 95% CI 1.06-1.10), and burnout (OR = 1.10, 95% CI 1.07-1.12). No moderation analyses were significant. Greater resilience was associated with lower depression, anxiety, and burnout. CONCLUSION: EMS clinicians, much like other first responders, experience considerable occupational stress, of which is associated with mental health difficulties and burnout. Findings underscore the need for intervention programs aimed at reducing the impact of occupational stress and the promotion of resilience. Continuing to understand the full scope of EMS mental health, including the role of resilience, is imperative, particularly in light of future public emergencies.
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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 | 0.001 | 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) | 0.000 | 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".