KNOWLEDGE AND ATTITUDE OF FARMERS TOWARDS ANTIMICROBIAL RESISTANCE IN ASIA: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Background: Antimicrobial resistance is a severe threat to public and environmental health. The agricultural sector contributes significantly to resistance, where antimicrobials are used as prophylaxis, growth promoters, and for treatment. A series of studies have been conducted to assess farmers' knowledge and attitude levels with varying results, particularly in Asia, one of the world's largest producers of livestock products. Purpose: To review the pooled estimated level of knowledge and attitude towards antimicrobial use and resistance in Asia. Methods: A literature search was conducted according to PRISMA in Scopus, PubMed, Google Scholar, and Embase for studies up to 30 April 2023. Quality was assessed using the Newcastle-Ottawa Scale (NOS) for cross-sectional studies. Outcomes were further categorized into constructs under knowledge and attitude. Random-effect meta-analysis was conducted using STATA 17. Results: 11 studies and 2131 subjects were included with fair to excellent quality. From the meta-analysis, the following knowledge and attitude levels were estimated: definition [55.7% (95%CI: 37.3%-74%)] and cause [60.6% (95%CI: 40.5%-80.6%)] of antimicrobial resistance; the negative impact of antimicrobials [62.6% (95%CI: 16.9%-100.0%)]; use of antimicrobials for treatment [47.8% (95%CI: 6.1%-89. 4%)], prophylaxis [58.5% (95%CI: 28.5%-88.5%)], growth promoter [39% (95%CI: 23.1%-54.9%)]; discontinuation of antimicrobials upon improving conditions [42.5% (95%CI: 15.4%-69.5%)]. Conclusions: Farmers in Asia have moderate knowledge of antimicrobial resistance but still exhibit attitudes that support resistance.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| 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".