Don't ignore the tough questions: A qualitative investigation into occupational stressors impacting veterinarians' mental health.
Bibliographic record
Abstract
Objective: To explore Canadian clinical veterinarians' perspectives of occupational stressors. Although extant research has emphasized quantitative reporting of workplace stressors in veterinary medicine, a qualitative approach can lend depth and context. Procedure: One-on-one interviews were conducted with 25 veterinarians at the 2016 Canadian Veterinary Medical Association Conference. Results: Thematic analysis revealed 9 occupational stressor themes: nature of the profession, veterinary relationships, client interactions, inadequate personal finances, early-career veterinarian strain, practice-owner strain, onus of responsibility, self-described personal characteristics, and moral stressors and moral distress. Participants also discussed perceived implications of these stressors. Conclusion: This study contributes to knowledge on veterinarians' mental health and discusses recommendations for mitigating occupational stressors to promote veterinarian well-being. Clinical relevance: Understanding the occupational stressors that clinical veterinarians experience and the effects of these occupational stressors can lead to more targeted and comprehensive strategies to support veterinarians' mental well-being in a clinical setting.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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) | 0.000 | 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".