ArticleVeterinary medicine international2025
Knowledge, Attitudes, Practices and Risk Perceptions of Antimicrobial Use and Resistance Among Small-Scale Fish Farmers in Cameroon.
Article in Veterinary medicine international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Knowledge, attitudes, and practices on antibiotic use and resistance among fish farmers in Kwara State, North Central, Nigeria.BMC veterinary research · 2026Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antimicrobial resistance (AMR) is a complex public health problem that is caused mainly by the inappropriate use of antimicrobial agents. The rational use of antimicrobial agents, which is the main strategy for preventing AMR, can be achieved through farmers' knowledge and behaviour. Hence, this study aimed to assess the knowledge, attitudes and practices of fish farmers regarding antimicrobial use (AMU), AMR and their perceptions (KAPP) of the risk of the emergence of AMR in Cameroon. A cross-sectional study of 364 fish farmers was performed in the Adamawa, Centre, Littoral, South and West Regions using a questionnaire. Descriptive statistics were used to summarise the data. To compare group differences, the Kruskal-Wallis and Wilcoxon tests were run at a significance level of 0.05. Pearson correlation and linear regression were used to determine the directionality, magnitude and nature of the relationships among variables. Overall, the survey revealed poor knowledge of AMU (0.47 ± 0.19) and AMR (0.30 ± 0.29). The attitudes towards and practices of AMU were also poor (0.40 ± 0.28 and 0.47 ± 0.11, respectively). However, the level of risk perception of the emergence of AMR by the fish farmers was fair (0.50 ± 0.29). Locality, age, professional experience, educational level of the fish farmer, training in fish farming and presence of health agents on the farm were associated (
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