title: Understanding how new evidence influences practitioners' beliefs regarding dry cow therapy: A Bayesian approach using probabilistic elicitation.
abstract: This study used probabilistic elicitation and a Bayesian framework to quantitatively explore how logically practitioners' update their clinical beliefs after exposure to new data. The clinical context was the efficacy of antibiotics versus teat sealants for preventing mammary infections during the dry period. While most practitioners updated their clinical expectations logically, the majority failed to draw sufficient strength from the new data so that their clinical confidence afterwards was lower than merited. This study provides quantitative insight into how practitioners' update their beliefs. We discuss some of the psychological issues that may be faced by practitioners when interpreting new data. The results have important implications for evidence-based practice and clinical research in terms of the impact that new data may bring to the clinical community.
authors.affiliation: Institute of Veterinary Science, University of Liverpool, Leahurst Campus, Chester High Road, Neston, Wirral, CH64 7TE, UK. Electronic address: h.higgins@liverpool.ac.uk.
authors.forename: H M
authors.initials: HM
authors.lastname: Higgins
authors.affiliation: Westpoint Veterinary Group, Dawes Farm, Bognor Road, Warnham, West Sussex, RH12 3SH, UK. Electronic address: jon.mouncey@westpointfarmvets.co.uk.
authors.forename: J
authors.initials: J
authors.lastname: Mouncey
authors.affiliation: Westpoint Veterinary Group, Dawes Farm, Bognor Road, Warnham, West Sussex, RH12 3SH, UK. Electronic address: ian.nanjiani@westpointfarmvets.co.uk.
authors.forename: I
authors.initials: I
authors.lastname: Nanjiani
authors.affiliation: Faculty of Health and Medical Sciences, School of Veterinary Medicine, Daphne Jackson Road, Guildford, Surrey, GU2 7AL, UK. Electronic address: alasdair.j.cook@surrey.ac.uk.
authors.forename: A J C
authors.initials: AJ
authors.lastname: Cook
mesh_terms: D000818:Animals; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D019072:Antibiotic Prophylaxis / Q000379:methods / Q000662:veterinary*; D001290:Attitude; D001499:Bayes Theorem; D001729:Bismuth / Q000008:administration & dosage / Q000627:therapeutic use*; D002417:Cattle; D002511:Cephalosporins / Q000008:administration & dosage / Q000627:therapeutic use*; D004739:England; D005260:Female; D006801:Humans; D007774:Lactation; D008414:Mastitis, Bovine / Q000188:drug therapy / Q000517:prevention & control*; D018634:Veterinarians / Q000523:psychology*
chemical_list: D000900:Anti-Bacterial Agents; D002511:Cephalosporins; C010804:bismuth subnitrate; C012813:cephalonium; D001729:Bismuth
keywords: Antimicrobial resistance; Bayesian analysis; Belief updating; Clinical priors; Evidence-based veterinary medicine; Probabilistic elicitation