AUTHOR=Adegbole Charles , Seilkhanova Togzhan , Bajwa Muhammad Rashid , Smith Rebecca Lee 

TITLE=Unlocking farm-level antimicrobial resistance: a qualitative study of researchers’ experiences and challenges

JOURNAL=Frontiers in Veterinary Science

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2025.1691572

DOI=10.3389/fvets.2025.1691572

ISSN=2297-1769

ABSTRACT=Despite the strong advocacy for innovation in livestock antimicrobial resistance research, a significant knowledge gap exists regarding the social components of livestock AMR research, especially as it concerns researchers. Prior studies have shown a negative perception among farm stakeholders toward antimicrobial resistance research on farms, reducing the effectiveness of such research. Furthermore, the encounters of researchers working on antimicrobial resistance in livestock settings remain underreported. This study aims to understand the experiences of researchers who conduct antimicrobial resistance research using livestock data to identify the social and technical barriers for researchers and highlight improvement opportunities. We used a semi-structured interview format to collect information from 48 researchers who had experience conducting antimicrobial resistance research on U.S. farms. Three themes captured scenarios contributing to the existing limitations around antimicrobial resistance data generated from farm settings: Navigating access and relationships impacts the quality of the research; despite challenges, more farm-level AMR data is needed because it includes crucial metadata; and preserving data integrity requires data sharing protocols. A fourth theme, researchers want to transform data into impact, described researchers’ common use of AMR data and their rationale for needed improved access. To achieve significant advancement in antimicrobial resistance in the near future, it is imperative to address the barriers that hinder access to and sharing of farm-level AMR data through development of policies and best practices.