Suppr超能文献

理解新证据如何影响从业者对干奶牛疗法的信念:一种使用概率诱导的贝叶斯方法。

Understanding how new evidence influences practitioners' beliefs regarding dry cow therapy: A Bayesian approach using probabilistic elicitation.

作者信息

Higgins H M, Mouncey J, Nanjiani I, Cook A J C

机构信息

Institute of Veterinary Science, University of Liverpool, Leahurst Campus, Chester High Road, Neston, Wirral, CH64 7TE, UK.

Westpoint Veterinary Group, Dawes Farm, Bognor Road, Warnham, West Sussex, RH12 3SH, UK.

出版信息

Prev Vet Med. 2017 Apr 1;139(Pt B):115-122. doi: 10.1016/j.prevetmed.2016.08.012. Epub 2016 Sep 7.

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.

摘要

本研究采用概率诱导法和贝叶斯框架,定量探究从业者在接触新数据后如何合理更新其临床信念。临床背景是抗生素与乳头封闭剂在预防干奶期乳腺感染方面的疗效。虽然大多数从业者能合理更新其临床预期,但大多数人未能从新数据中汲取足够的力量,以至于他们之后的临床信心低于应有的水平。本研究为从业者如何更新信念提供了定量见解。我们讨论了从业者在解读新数据时可能面临的一些心理问题。就新数据可能给临床界带来的影响而言,研究结果对循证医学实践和临床研究具有重要意义。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验