Knowledge, attitudes and influencers of North American dog‐owners surrounding antimicrobials and antimicrobial stewardship
Bibliographic record
Abstract
OBJECTIVES: To quantify the individual influences of antimicrobial cost, method of administration and drug importance in human medicine on dog-owner antimicrobial preference, and determine knowledge, attitudes and influencers of dog-owners surrounding antimicrobials and antimicrobial stewardship. MATERIALS AND METHODS: Data were collected through an online survey targeting three dog-owner participant groups. These consisted of individuals residing in: (1) Canada, (2) USA and (3) any country recruited through an educational social media site. USA and Canadian participants were financially compensated. Conjoint analysis was used to quantify the influence of antimicrobial cost, method of administration and drug importance in human medicine. Descriptive and analytical statistics were used for data evaluation. RESULTS: A total of 809 surveys were completed. Antimicrobial cost accounted for 47% of dog-owner preferences, followed by method of administration (31%) and drug importance in human medicine (22%). All groups preferred lower cost drugs that were administered once by injection. Participants were more likely to prefer drugs considered "very important" in human medicine, except for the social media participants, who preferred drugs that were "not at all important." Most respondents (86%) reported antimicrobial resistance as important in human medicine and 29% believed antimicrobial use in pets posed a risk for antimicrobial resistance in humans. Participants recruited through social media, and those in the highest education category, were significantly more likely to report antimicrobial use in pets as a risk to people. CLINICAL SIGNIFICANCE: Cost was the most important factor in dog-owner antimicrobial preferences. There is a need for dog-owner antimicrobial stewardship education.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".