Prevalence of mental health outcomes among Canadian veterinarians
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence of perceived stress, burnout, depression, anxiety, compassion fatigue, compassion satisfaction, resilience, and suicidal ideation among Canadian veterinarians and compare results with those for other populations. SAMPLE: 1,403 veterinarians across Canada. PROCEDURES: The study represented a cross-sectional online survey. The questionnaire incorporated validated psychometric instruments to measure perceived stress, burnout, depression, anxiety, compassion fatigue, and resilience as well as questions regarding suicidal ideation. Means and relative proportions in categories of severity were compared between genders as well as with normative data for the general population and results for veterinarians in the United Kingdom. RESULTS: Approximately 10% of Canadian veterinarians (n = 1,403) completed the survey. Relative to the general population, survey participants had significantly higher mean scores for subscales of burnout and compassion fatigue, anxiety, and depression and significantly lower mean resilience. Relative to males, females had significantly higher mean scores for perceived stress, emotional exhaustion, burnout, secondary traumatic stress, anxiety, and depression and significantly lower mean resilience. Participants also had higher mean scores for anxiety and depression relative to results for United Kingdom veterinarians. The 12-month prevalence of suicidal ideation for participants was 26.2%, which was substantially higher than the estimated prevalence for the general international population (2.1% to 10.0%). CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that the mental health of Canadian veterinarians was poor, compared with the mental health of the general population. These results should serve as a call to action for tools and educational programs directed at supporting veterinarian mental wellness in Canada, with special attention paid to the disparate needs of the genders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".