Understanding how new evidence influences practitioners’ beliefs regarding dry cow therapy: A Bayesian approach using probabilistic elicitation
| Autor: | J Mouncey, Alasdair J. C. Cook, I Nanjiani, H.M. Higgins |
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| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Bayesian probability Applied psychology Alternative medicine Context (language use) computer.software_genre 01 natural sciences Veterinarians 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Food Animals medicine Animals Humans Lactation 030212 general & internal medicine 0101 mathematics Mastitis Bovine Preventive healthcare Antiinfective agent business.industry Probabilistic logic Bayes Theorem Antibiotic Prophylaxis Anti-Bacterial Agents Cephalosporins Clinical research Attitude England Cattle Female Animal Science and Zoology Bayesian framework Data mining business Bismuth computer |
| Zdroj: | Preventive veterinary medicine |
| ISSN: | 0167-5877 |
| DOI: | 10.1016/j.prevetmed.2016.08.012 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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