Investigation of the effects of veterinarians’ attire on ratings of trust, confidence, and comfort in a sample of pet owners in Canada
Bibliographic record
Abstract
OBJECTIVE: To examine companion animal owners' perceptions of appropriate veterinarian attire and investigate potential associations between a veterinarian's attire and clients' ratings of trust in, confidence in, and comfort with a veterinarian. SAMPLE: 449 pet owners. PROCEDURES: Participants were randomly assigned to complete a questionnaire containing photos of a male or female model veterinarian photographed in 8 attire types (formal attire, white dress shirt with black pants, white casual shirt with khaki pants, surgical scrubs, white casual shirt with jeans, surgical scrub top with jeans, surgical scrub top with khaki pants, and white laboratory coat with khaki pants). Participants were asked to rate their trust in, confidence in, and comfort with the pictured individual on a response scale of 1 (low) to 7 (high), rank photos according to their preferences for attire, and provide input on the importance of attire and other appearance-related subjects. Attire and gender of photographed individual and participant demographics were investigated for associations with trust, confidence, and comfort scores. RESULTS: Most (317/445 [71%]) respondents indicated veterinarians' attire was important. Attire type was significantly associated with respondents' trust, confidence, and comfort scores. Model veterinarian gender and participant education level were also associated with trust and comfort scores. CONCLUSIONS AND CLINICAL RELEVANCE: Veterinarians' attire is a form of nonverbal communication that is likely to inform clients' first impressions and may influence clients' trust in, confidence in, and comfort with a veterinarian. Veterinary personnel and veterinary management should consider how attire and general appearance represent staff members or their practice.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".