Mental health of veterinarians in Canada: Prevalence of outcomes, associations with veterinarian characteristics, and impacts on client perceptions of care
Bibliographic record
Abstract
Poor mental health in medical professionals has been associated with negative consequences for the individual, workplace, and patients/clients. There are reports of poor mental health among veterinarians in several countries, but data in Canada remain sparse. No publications to date have evaluated outcomes of care for veterinary clients or patients relative to the mental health of the veterinarian. This research comprised two projects. First, a survey of veterinarians in Canada to explore the prevalence of perceived stress, anxiety, depression, emotional exhaustion, depersonalization, personal accomplishment, burnout, secondary traumatic stress, compassion satisfaction, and resilience, as well as to explore associated personal, lifestyle, and career characteristics. Second, an in-clinic study of veterinarians and veterinary clients to explore the relationship between the same veterinarian mental health measures and three appointment outcomes: client satisfaction and veterinarian and client perceptions of patient-centeredness (VPCC and CPCC, respectively). \nRelative to the general population, survey participants (n=1403) had higher levels of negative mental health states, and lower resilience; female veterinarians fared poorer than males. Univariable modelling indicated that resilience was positively associated with other positive mental health states, and negatively associated with negative mental states. Among veterinarians in clinical practice (n=1130), a multivariable model predicted positive associations between resilience and overall health, a participant’s satisfaction with support from friends, relationship/partner, and workplace resources. Negative associations with resilience included participant-reported presence of mental illness, being married, in small animal practice, or being in an associate role. Sixty veterinarians participated in the second study. Several associations between veterinarian mental health scores and client satisfaction scores (n=995) were significant, non-linear, and complex. In some models, higher client satisfaction was unexpectedly associated with poor veterinarian mental health, while lower client satisfaction was associated with apparent mental wellness. In multilevel, multivariable models, both VPCC and CPCC (n=977) were positively associated veterinarian compassion satisfaction. However, veterinarian burnout was negatively associated with VPCC, while veterinarian emotional exhaustion (an aspect of burnout) was positively associated with CPCC. These findings suggest that many veterinarians in Canada are experiencing poor mental health, which in turn may impact client outcomes. Cultivating veterinarian resilience represents a promising area for well-being intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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".