Information about life expectancy related to obesity is most important to cat owners when deciding whether to act on a veterinarian's weight loss recommendation
Bibliographic record
Abstract
OBJECTIVE: To determine the relative importance of information communicated to cat owners during veterinarian-client obesity-related conversations. SAMPLE: Cat owner participants recruited via snowball sampling. METHODS: A cross-sectional online questionnaire was distributed to cat owners who owned cats of any weight status. A discrete choice experiment design was used to determine the relative importance of obesity-related attributes to cat owners when receiving information from a veterinarian. RESULTS: A total of 1,095 questionnaires were analyzed. Participating cat owners resided primarily in Canada and the US. Impact on life expectancy was the most important attribute that would encourage participants to pursue weight management for a cat with obesity (relative importance, 32.66%), followed by change to cost of food (20.40%), future quality of life (20.38%), future mobility (14.40%), and risk of developing diabetes (12.15%). CLINICAL RELEVANCE: Findings suggest that cat owners consider the impact on life expectancy to be most important when considering whether to follow a veterinarian's recommendation for their cat to lose weight. When veterinary professionals are communicating about obesity in practice, there is the potential to increase owner engagement in weight management efforts for cats by emphasizing the obesity-related information owners prefer to receive.
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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 | 0.001 | 0.002 |
| 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".