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A Bayesian perspective on constructing a written assessment of probabilistic clinical reasoning in experienced clinicians

Overview of attention for article published in Journal of Evaluation in Clinical Practice, October 2015
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Article details
Title
A Bayesian perspective on constructing a written assessment of probabilistic clinical reasoning in experienced clinicians
Published in
Journal of Evaluation in Clinical Practice, October 2015
DOI 10.1111/jep.12469
Pubmed ID
Authors
Abstract

Decision-making performance assessments have proven problematic for assessing clinical reasoning. A Bayesian approach to designing an advanced clinical reasoning assessment is well grounded in mathematical and cognitive theory and may offer significant psychometric advantages. Probabilistic logic plays an important role in medical problem solving, and performances on Bayesian-type tasks appear to be causally-related to the ability to make sound clinical decisions. A validity argument is used to guide the design of an assessment of medical reasoning using clinical probabilities. The practical advantage of using a Bayesian approach to item design relates to the fact that probability theory provides a rationally optimal method for managing uncertain information and provides the criteria for objective correct answer scoring. Potential item formats are discussed.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Other 6 17%
Student > Ph. D. Student 5 14%
Lecturer 4 11%
Student > Bachelor 3 8%
Lecturer > Senior Lecturer 2 6%
Other 6 17%
Unknown 10 28%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 14 39%
Psychology 2 6%
Arts and Humanities 1 3%
Mathematics 1 3%
Nursing and Health Professions 1 3%
Other 4 11%
Unknown 13 36%