Literature DB >> 23465201

Visual representation of statistical information improves diagnostic inferences in doctors and their patients.

Rocio Garcia-Retamero1, Ulrich Hoffrage.   

Abstract

Doctors and patients have difficulty inferring the predictive value of a medical test from information about the prevalence of a disease and the sensitivity and false-positive rate of the test. Previous research has established that communicating such information in a format the human mind is adapted to-namely natural frequencies-as compared to probabilities, boosts accuracy of diagnostic inferences. In a study, we investigated to what extent these inferences can be improved-beyond the effect of natural frequencies-by providing visual aids. Participants were 81 doctors and 81 patients who made diagnostic inferences about three medical tests on the basis of information about prevalence of a disease, and the sensitivity and false-positive rate of the tests. Half of the participants received the information in natural frequencies, while the other half received the information in probabilities. Half of the participants only received numerical information, while the other half additionally received a visual aid representing the numerical information. In addition, participants completed a numeracy scale. Our study showed three important findings: (1) doctors and patients made more accurate inferences when information was communicated in natural frequencies as compared to probabilities; (2) visual aids boosted accuracy even when the information was provided in natural frequencies; and (3) doctors were more accurate in their diagnostic inferences than patients, though differences in accuracy disappeared when differences in numerical skills were controlled for. Our findings have important implications for medical practice as they suggest suitable ways to communicate quantitative medical data.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23465201     DOI: 10.1016/j.socscimed.2013.01.034

Source DB:  PubMed          Journal:  Soc Sci Med        ISSN: 0277-9536            Impact factor:   4.634


  25 in total

1.  From reading numbers to seeing ratios: a benefit of icons for risk comprehension.

Authors:  Elisabet Tubau; Javier Rodríguez-Ferreiro; Itxaso Barberia; Àngels Colomé
Journal:  Psychol Res       Date:  2018-06-21

2.  Benefits and harms of selective oestrogen receptor modulators (SERMs) to reduce breast cancer risk: a cross-sectional study of methods to communicate risk in primary care.

Authors:  Jennifer G McIntosh; Jesse Minshall; Sibel Saya; Adrian Bickerstaffe; Nadira Hewabandu; Ashleigh Qama; Jon D Emery
Journal:  Br J Gen Pract       Date:  2019-11-28       Impact factor: 5.386

Review 3.  Perspectives on the 2 × 2 Matrix: Solving Semantically Distinct Problems Based on a Shared Structure of Binary Contingencies.

Authors:  Hansjörg Neth; Nico Gradwohl; Dirk Streeb; Daniel A Keim; Wolfgang Gaissmaier
Journal:  Front Psychol       Date:  2021-02-09

4.  Improving the Understanding of Publicly Reported Healthcare-Associated Infection (HAI) Data.

Authors:  Max Masnick; Daniel J Morgan; Mark D Macek; John D Sorkin; Jessica P Brown; Penny Rheingans; Anthony D Harris
Journal:  Infect Control Hosp Epidemiol       Date:  2016-08-30       Impact factor: 3.254

5.  Presentation of Diagnostic Information to Doctors May Change Their Interpretation and Clinical Management: A Web-Based Randomised Controlled Trial.

Authors:  Yoav Ben-Shlomo; Simon M Collin; James Quekett; Jonathan A C Sterne; Penny Whiting
Journal:  PLoS One       Date:  2015-07-06       Impact factor: 3.240

6.  Effects of visualizing statistical information - an empirical study on tree diagrams and 2 × 2 tables.

Authors:  Karin Binder; Stefan Krauss; Georg Bruckmaier
Journal:  Front Psychol       Date:  2015-08-26

Review 7.  How well do health professionals interpret diagnostic information? A systematic review.

Authors:  Penny F Whiting; Clare Davenport; Catherine Jameson; Margaret Burke; Jonathan A C Sterne; Chris Hyde; Yoav Ben-Shlomo
Journal:  BMJ Open       Date:  2015-07-28       Impact factor: 2.692

8.  Toward an ecological analysis of Bayesian inferences: how task characteristics influence responses.

Authors:  Sebastian Hafenbrädl; Ulrich Hoffrage
Journal:  Front Psychol       Date:  2015-08-04

9.  Visual aids improve diagnostic inferences and metacognitive judgment calibration.

Authors:  Rocio Garcia-Retamero; Edward T Cokely; Ulrich Hoffrage
Journal:  Front Psychol       Date:  2015-07-16

10.  Natural frequencies improve Bayesian reasoning in simple and complex inference tasks.

Authors:  Ulrich Hoffrage; Stefan Krauss; Laura Martignon; Gerd Gigerenzer
Journal:  Front Psychol       Date:  2015-10-14
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