A focus group study of veterinarians' and pet owners' perceptions of the monetary aspects of veterinary care
Bibliographic record
Abstract
OBJECTIVE: To compare veterinarians' and pet owners' perceptions of client expectations with respect to the monetary aspects of veterinary care and identify challenges encountered by veterinarians in dealing with pet owners' expectations. DESIGN: Qualitative study based on focus group interviews. PARTICIPANTS: 6 pet owner focus groups (32 owners) and 4 veterinarian focus groups (24 companion animal veterinarians). PROCEDURES: Independent focus group sessions were conducted with standardized open-ended questions and follow-up probes. Content analysis was performed on the focus group discussions. RESULTS: Pet owners expected the care of their animal to take precedence over monetary aspects. They also expected veterinarians to initiate discussions of costs upfront but indicated that such discussions were uncommon. Veterinarians and pet owners differed in the way they related to discussions of veterinary costs. Veterinarians focused on tangibles, such as time and services. Pet owners focused on outcome as it related to their pet's health and well-being. Veterinarians reported that they sometimes felt undervalued for their efforts. A suspicion regarding the motivation behind veterinarians' recommendations surfaced among some participating pet owners. CONCLUSIONS: Results suggested that the monetary aspects of veterinary care pose barriers and challenges for veterinarians and pet owners. By exploring clients' expectations, improving communication, educating clients, and making discussions of cost more common, veterinarians may be able to alleviate some of the monetary challenges involved in veterinarian-client-patient interactions.
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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 | 0.024 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".