A Focus Group Study of Canadian Dairy Farmers' Attitudes and Social Referents on Antimicrobial Use and Antimicrobial Resistance
Bibliographic record
Abstract
As part of broader actions to combat antimicrobial resistance (AMR), health authorities have promoted the reduction of antimicrobial use (AMU) in food animals. Farmers' attitudes and receptivity to reduction of AMU appear to be variable and context specific. Our research objectives were to gain insight into Canadian dairy farmers' attitudes toward AMU, AMR, and AMU-reduction in the dairy industry, and to explore drivers and barriers to change AMU, including the influence of social referents. We conducted seven focus groups with 42 farmers in two provinces of Canada (New Brunswick and Ontario) and used thematic analysis to identify, analyze, and report patterns in the data. Our results indicate that farmers usually rely on their previous experience and judgement of individual cases of disease when making decisions related to AMU. External referents included other farmers, family members, and veterinarians. However, veterinarians were generally only consulted for unusual cases. Participants in this study expressed that maintaining cattle welfare is their responsibility, and that they were not willing to jeopardize animal welfare in order to reduce AMU. In addition, farmers regarded the cost of investment in improved facilities to prevent disease as an important barrier to reduce AMU. Finally, the majority of participants considered themselves to be low users of antimicrobials and perceived a small role of AMU on dairy farms in AMR. In conclusion, farmers from this study showed self-reliance to decide about AMU on their farms and considered animal-related and economic factors in these decisions. There was a general lack of knowledge of how to reduce AMU without investing in facilities, and there is an opportunity to motivate increased involvement of the veterinarian in AMU-related decisions. These results should be considered to design and refine antimicrobial stewardship programs for dairy farms.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".