Why you should read this article:

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To understand how Bayesian methods update knowledge by incorporation of prior knowledge into the interpretation of research findings and summaries of evidence to date

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To gain an introduction to the application of Bayes’ theorem via examples of conditional probability and clinical applications

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To stimulate an understanding and interest in the Bayesian approach among nurse researchers to ensure its wider application in nursing research

Background The Bayesian approach to updating scientific knowledge involves using a probability distribution to describe a prior belief concerning an outcome of interest and combines this with some new information to create a posterior probability distribution to describe the updated current knowledge.

Aim To introduce the application of Bayes’ theorem, using the conditional probability example of the Monty Hall problem and two examples of the clinical application of a Bayesian approach.

Discussion Bayesian approaches enable the incorporation of prior knowledge into the interpretation of research findings and summaries of evidence to date. Bayesian approaches are being incorporated into most clinical trials.

Conclusion Bayesian approaches to interpreting the results of a diagnostic test and a clinical trial highlight the utility of these approaches to clinical nursing and the application of evidence-based practice.

Implications for practice Stimulation of an understanding and interest in the Bayesian approach among nurse researchers should lead to its wider application in nursing research.