Cross-sectional survey of cat handling practices in veterinary clinics throughout Canada and the United States
Bibliographic record
Abstract
OBJECTIVE: To assess handling techniques commonly used during routine examinations and procedures used for calm, fearful, and aggressive cats by veterinarians and nonveterinarian staff at Canadian and US veterinary practices and to evaluate demographic factors associated with those handling techniques. SAMPLE: 310 veterinarians and 944 nonveterinarians who handle cats at Canadian and US veterinary practices. PROCEDURES: An online questionnaire was developed to evaluate respondent demographics and use of common cat handling practices and techniques. A snowball sampling method was used to send a link to the questionnaire to members of Canadian and US veterinary-affiliated groups. Descriptive statistics were generated; logistic regression was used to identify demographic factors associated with the use of minimal and full-body restraint with scruffing during routine examination and procedures for fearful and aggressive cats. RESULTS: Full-body restraint was used to handle cats of all demeanors, although its frequency of use was greatest for fearful and aggressive cats. Veterinarians and nonveterinarians who graduated from veterinary training programs before 2006 were less likely to use full-body restraint for cats of all demeanors, compared with nonveterinarians who did not graduate or graduated between 2006 and 2015. Other factors associated with decreased use of full-body restraint included working at an American Association of Feline Practitioners-certified practice and working at a Canadian practice. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that full-body restraint is commonly used to handle cats. Further research is necessary to determine whether current handling recommendations are effective in decreasing stress for cats during veterinary visits.
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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 | 0.002 | 0.009 |
| 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".