Exploring how veterinary professionals perceive and use grief support resources to support companion animal caregivers in Ontario, Canada
Bibliographic record
Abstract
Objective: The aim of this study was to qualitatively explore veterinary professionals’ use and perceptions of grief resources and services to support companion animal caregivers following companion animal euthanasia.
 Background: The loss of a companion animal can be a source of great sorrow and grief. Like human loss, many companion animal caregivers may seek out and benefit from grief resources, of which veterinary professionals are often important providers. Yet, little is known about how, when or for what reasons veterinary professionals provide these resources.
 Methods: A qualitative study consisting of group and individual interviews involving 38 veterinary professionals and staff from 10 veterinary hospitals in Ontario, Canada was conducted. Verbatim transcripts were evaluated using inductive thematic analysis to identify themes and subthemes.
 Results: Results indicated that typically resources were only provided if a caregiver requested information, or when veterinary professionals recognised that the caregiver may benefit from these resources. To assess a caregiver’s need, participants reported considering their age, the strength of the human-animal bond, their previous and ongoing life circumstances, and their emotional state. Several barriers limiting veterinary professionals’ use of grief resources were also described including perceptions that few adequate resources existed and a lack of knowledge of existing or new resources.
 Conclusion: Overall, findings suggest that there are substantial opportunities to improve and embed a provision of grief resources within the veterinary profession. There is a need to develop adequate resources to meet caregivers’ supportive needs and implement these resources within the greater veterinary profession.
 
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 | 0.000 | 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 | 0.001 |
| 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".