Assessing Differences in Understanding of Companion-Animal Preventive Care between a Veterinary Health Care Team and Pet Owners in a Veterinary Teaching Hospital
Bibliographic record
Abstract
Preventive health care visits to primary care veterinary practices in the United States have been on the decline over the past decade. One of the main factors that has been identified is a lack of understanding by pet owners regarding the importance of preventive care. The Partners for Healthy Pets Opportunity Survey was adapted for use in this study to determine whether there were differences in perceptions of a veterinary health care team between team members and clients, specifically regarding preventive care specifically within the Community Practice service of the Virginia-Maryland College of Veterinary Medicine. Results of this cross-sectional study revealed that the clients and veterinary health care team tended to be aligned in most areas regarding companion-animal preventive care. There were some specific areas that differed, including a disconnect regarding components of feline wellness visits, reliable sources of medical information, and strength of recommendations from the veterinary health care team. The Partners for Healthy Pets Opportunity Survey could be adapted for use in other university-based companion-animal general-practice teaching environments to better understand differences between clients and the veterinary health care team regarding preventive care and thereby improve educational and service goals of primary care veterinary education. Efforts to better understand and mitigate potential communication gaps between pet owners and veterinary health care teams have the potential to improve preventive care not only in university-based practice but also in private clinical 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 | 0.006 | 0.021 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".