The role of veterinary team effectiveness in job satisfaction and burnout in companion animal veterinary clinics
Bibliographic record
Abstract
OBJECTIVE: To determine the role of veterinary team effectiveness regarding job satisfaction and burnout in companion animal veterinary practice. DESIGN: Cross-sectional observational study. SAMPLE: 48 companion animal veterinary health-care teams. PROCEDURES: 274 team members participated in an online survey. Overall job satisfaction was evaluated with a 1-item measure, and the 3 dimensions of burnout (exhaustion, cynicism, and professional efficacy) were measured with the Maslach Burnout Inventory-General Survey. Team effectiveness was assessed with a survey developed for this study. Demographic and team effectiveness factors (coordinated team environment, toxic team environment, team engagement, and individual engagement) associated with job satisfaction and burnout were evaluated. RESULTS: Overall mean job satisfaction score was 5.46 of 7 (median, 6.00); veterinary technicians and kennel attendants had the lowest scores. According to the Maslach survey results, 22.4% of participants were in the high-risk category for exhaustion, 23.2% were in the high-risk category for cynicism, and 9.3% were in the high-risk category for professional efficacy. A coordinated team environment was associated with increased professional efficacy and decreased cynicism. A toxic team environment was negatively associated with job satisfaction and positively associated with exhaustion and cynicism. Individual engagement was positively associated with job satisfaction and professional efficacy and negatively associated with exhaustion and cynicism. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested the effectiveness of a veterinary team can significantly influence individual team members' job satisfaction and burnout. Practices should pay specific attention to the effectiveness with which their veterinary team operates.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".