Article ; Online: A qualitative survey approach to investigating beef and dairy veterinarians' needs in relation to technologies on farms.
Animal : an international journal of animal bioscience
2024 Volume 18, Issue 4, Page(s) 101124
Abstract: Globally, farmers are being increasingly encouraged to use technologies. Consequently, veterinarians often use farm data and technologies to provide farmers with advice. Yet very few studies have sought to understand veterinarians' perceptions of data ... ...
Abstract | Globally, farmers are being increasingly encouraged to use technologies. Consequently, veterinarians often use farm data and technologies to provide farmers with advice. Yet very few studies have sought to understand veterinarians' perceptions of data and technologies on farms. The aim of this study was to understand veterinarians' experiences and opinions on data and technology on beef and dairy farms. An online qualitative survey was conducted with a convenience sample of 36 and 24 veterinarians from the United Kingdom and Ireland, respectively. The data were analysed using reflexive thematic analysis to generate four themes: (1) Improving veterinary advice through data; (2) Ensuring stock person skills are retained; (3) Longevity of technology; and (4) Solving social problems on farms. We show that technologies and data can make veterinarians feel more confident in the advice they give to farmers. However, the quality and quantity of data collected on cattle farms were highly variable. Furthermore, veterinarians were concerned that farmers can become over-reliant on technologies by not using their stockperson skills. As herd sizes increase, technologies can help to improve working conditions on farms with multiple employees of various skillsets. Veterinarians would like innovations that can help them to demonstrate their competence, influence farmers' behaviour, and ensure sustainability of the beef and dairy industries. |
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MeSH term(s) | Humans ; Cattle ; Animals ; Farms ; Veterinarians ; Farmers ; Surveys and Questionnaires ; Dairying ; Technology |
Language | English |
Publishing date | 2024-03-07 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2257920-5 |
ISSN | 1751-732X ; 1751-7311 |
ISSN (online) | 1751-732X |
ISSN | 1751-7311 |
DOI | 10.1016/j.animal.2024.101124 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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