Personality traits and workplace factors predict professional quality of life among companion-animal veterinary professionals
Bibliographic record
Abstract
Objective: To assess the prevalence of burnout (BO), secondary traumatic stress (STS), and compassion satisfaction (CS) and identify associated individual, clinic, and dog-handling factors among veterinary professionals. Methods: A cross-sectional online questionnaire was distributed to veterinary professionals in Canada and US (2023 to 2024). The questionnaire collected individual, clinic, and dog-handling information and measured ProQOL (BO, STS, CS). Logistic regression models examined associations between these factors and ProQOL. Results: Participants (n = 691) had moderate BO (71.2%), STS (71.8%), and CS (74.3%); 2.4% reported high STS, and none had high BO. Veterinarians had lower odds of moderate/high BO (OR, 0.50; 95% CI, 0.32 to 0.78) and CS (OR, 0.12; 95% CI, 0.021 to 0.64) compared with nonveterinarians. Below-normal personality traits were associated with moderate/high BO and/or STS: extraversion (BO: OR, 2.25; 95% CI, 1.47 to 3.46), agreeableness (BO: OR, 2.02; 95% CI, 1.29 to 3.18; STS: OR, 1.60; 95% CI, 1.07 to 2.39), conscientiousness (BO: OR, 3.91; 95% CI, 2.41 to 6.34; STS: OR, 3.81; 95% CI, 2.47 to 5.88), emotional stability (BO: OR, 1.96; 95% CI, 1.24 to 3.11), and openness (BO: OR, 1.64; 95% CI, 1.05 to 2.56; STS: OR, 1.88; 95% CI, 1.26 to 2.81). Stress-reducing certification was associated with moderate/high BO (OR, 2.04; 95% CI, 1.14 to 3.64). Conclusions: Personality traits and individual factors were associated with ProQOL, whereas handling techniques were not. Clinical Relevance: Findings provide exploratory evidence for workplace strategies to reduce BO and STS and enhance CS while generating hypotheses for future intervention research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".