ArticleData in brief2021
Dairy farmer perceptions of antibiotic transport and usage in animal agriculture dataset.
Article in Data in brief, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
These data were from semi-structured interviews with dairy farmers. The content of the interviews focused on antibiotic transport and usage on dairy farms. Twenty-seven interviews were conducted in Central New York in 2019. Interviews were recorded and subsequently transcribed for qualitative thematic analysis. Qualitative coding analysis was preformed using ATLAS.ti and content filtered to ensure farmer anonymity. The dataset includes direct quotations from dairy farmers paired with farm and farmer characteristics. Quotations are subdivided thematically into the themes of disease prevention, antibiotic usage, non-antibiotic treatments, antibiotic transport, and environmental residue presence impacts, as structured in Georgakakos et al. [1]. Farm characteristics include management practice, farm size, and farm generation. Farm size was determined by number of lactating cows: small (0-50), medium-small (51-100), medium (101-500), medium-large (501-1000), and large (>1000). Farmer characteristics were farmer age categorized by birth year: Baby Boomer (1946-1964), Gen X (1965-1980), and Millennial (1981-1996). This dataset is particularly promising for longitudinal studies, incorporation of human behaviour into contaminant load models, or for recoding and analysis for themes other than those discussed by Georgakakos et al. [1].
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