ArticleAntibiotics (Basel, Switzerland)2023
Article in Antibiotics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Understanding how veterinarians' knowledge, attitudes, and practices influence antibiotic prescription: a systematic review of survey studies.BMC veterinary research · 2025Pooled it
- "Not a problem because we drench for it": the management of liver fluke on sheep farms.Frontiers in veterinary science · 2026Article
- A qualitative content analysis exploring the portrayal of antibiotic use and antibiotic resistance in UK smallholding print media.Frontiers in veterinary science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Antimicrobial resistance (AMR) is a global health and development threat, with calls for the optimisation of antimicrobial use (AMU) in the treatment of both humans and animals prevalent across national and international policy. Rapid, low-cost and readily available diagnostics that specifically identify pathogens and their antimicrobial susceptibility profiles have been identified as essential parts of this optimisation process, yet questions over the assumed utility of novel rapid technology as a cornerstone of tackling agricultural AMU still exist. To understand whether this technology may support the optimisation of AMU in the treatment of animal disease, this study qualitatively examines the discourse between veterinarians, laboratory representatives, veterinary researchers and (cattle) farmers within three participatory events concerning diagnostic testing on UK farms, to offer a critical examination of the interaction between veterinary diagnostic practice and agricultural AMU. Veterinarian-led discussion suggested that veterinary rationales for engaging with diagnostic testing are nuanced and complex, where veterinarians (i) were driven by both medical and non-medical motivators; (ii) had a complex professional identity influencing diagnostic-test engagement; and (iii) balanced a multitude of situated contextual factors that informed "gut feelings" on test choice and interpretation. In consequence, it is suggested that data-driven diagnostic technologies may be more palatable for veterinarians to promote to their farm clients in the pursuit of better and more sustainable AMU, whilst also being in synergy with the emerging preventative role of the farm veterinarian.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.