A survey of veterinarian mental health and resilience in Ontario, Canada.
Bibliographic record
Abstract
Our goal was to help address a lack of mental health research on Canadian veterinarians through estimation of the prevalence of depression, anxiety, compassion fatigue, burnout, and resilience in veterinarians in Ontario. We conducted a cross-sectional study using an online survey that investigated demographics, mental health, self-reported overall health, and satisfaction with sources of support. Validated, psychometric scales were used to measure depression, anxiety, burnout, compassion fatigue, and resilience. The mental health indices of participating veterinarians were in line with those of veterinarians in other regions, and reflective of poorer mental health compared to the general population. The scores for females tended towards poorer mental health relative to males. Reported levels of burnout and secondary traumatic stress were of particular concern. These results can be used to support evidence-based interventions to help veterinarians and veterinary students build their resilience so that they may better thrive in the face of occupational stresses.
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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 | 0.001 | 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) | 0.000 | 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".