Exploring veterinarians’ use of practices aimed at understanding and providing emotional support to clients during companion animal euthanasia in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: During companion animal euthanasia, support of clients is equally important as the medical care of the companion animal and requires a clear and developed understanding of clients' feelings, needs and expectations. Yet, veterinarians may not be fully exploring such topics. METHODS: A 65-item online questionnaire was developed and distributed to veterinarians (n=368) in Ontario to explore veterinarians' use of practices aimed at understanding and providing support during companion animal euthanasia. Measures included veterinarians' use of previously identified communication and support practices, empathy, years in practice and amount of time scheduled for euthanasia appointments. Data were analysed using descriptive statistics and multivariable regression. RESULTS: Veterinarians reported consistently providing emotional support but inconsistently implementing practices that may assist in enhancing their understanding of clients' expectations, previous or emotional experiences. Veterinarians' empathy scores, years in practice and the amount of time scheduled for euthanasia were positively associated with use of these practices. CONCLUSION: Providing adequate time (ideally >30 min) for euthanasia appointments may assist in efforts to understand clients' experiences, expectations and emotions, and provide support. Combining empathy, hands-on and self-care training in veterinary curriculum may also be valuable in improving the comfort level and skill of veterinarians in providing compassionate care.
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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 | 0.000 | 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".