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Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication

Most of the research on Bayesian reasoning aims to answer theoretical questions about the extent to which people are able to update their beliefs according to Bayes' Theorem, about the evolutionary nature of Bayesian inference, or about the role of cognitive abilities in Bayesian inference. Few...

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Autores principales: Navarrete, Gorka, Correia, Rut, Sirota, Miroslav, Juanchich, Marie, Huepe, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585185/
https://www.ncbi.nlm.nih.gov/pubmed/26441711
http://dx.doi.org/10.3389/fpsyg.2015.01327
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author Navarrete, Gorka
Correia, Rut
Sirota, Miroslav
Juanchich, Marie
Huepe, David
author_facet Navarrete, Gorka
Correia, Rut
Sirota, Miroslav
Juanchich, Marie
Huepe, David
author_sort Navarrete, Gorka
collection PubMed
description Most of the research on Bayesian reasoning aims to answer theoretical questions about the extent to which people are able to update their beliefs according to Bayes' Theorem, about the evolutionary nature of Bayesian inference, or about the role of cognitive abilities in Bayesian inference. Few studies aim to answer practical, mainly health-related questions, such as, “What does it mean to have a positive test in a context of cancer screening?” or “What is the best way to communicate a medical test result so a patient will understand it?”. This type of research aims to translate empirical findings into effective ways of providing risk information. In addition, the applied research often adopts the paradigms and methods of the theoretically-motivated research. But sometimes it works the other way around, and the theoretical research borrows the importance of the practical question in the medical context. The study of Bayesian reasoning is relevant to risk communication in that, to be as useful as possible, applied research should employ specifically tailored methods and contexts specific to the recipients of the risk information. In this paper, we concentrate on the communication of the result of medical tests and outline the epidemiological and test parameters that affect the predictive power of a test—whether it is correct or not. Building on this, we draw up recommendations for better practice to convey the results of medical tests that could inform health policy makers (What are the drawbacks of mass screenings?), be used by health practitioners and, in turn, help patients to make better and more informed decisions.
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spelling pubmed-45851852015-10-05 Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication Navarrete, Gorka Correia, Rut Sirota, Miroslav Juanchich, Marie Huepe, David Front Psychol Psychology Most of the research on Bayesian reasoning aims to answer theoretical questions about the extent to which people are able to update their beliefs according to Bayes' Theorem, about the evolutionary nature of Bayesian inference, or about the role of cognitive abilities in Bayesian inference. Few studies aim to answer practical, mainly health-related questions, such as, “What does it mean to have a positive test in a context of cancer screening?” or “What is the best way to communicate a medical test result so a patient will understand it?”. This type of research aims to translate empirical findings into effective ways of providing risk information. In addition, the applied research often adopts the paradigms and methods of the theoretically-motivated research. But sometimes it works the other way around, and the theoretical research borrows the importance of the practical question in the medical context. The study of Bayesian reasoning is relevant to risk communication in that, to be as useful as possible, applied research should employ specifically tailored methods and contexts specific to the recipients of the risk information. In this paper, we concentrate on the communication of the result of medical tests and outline the epidemiological and test parameters that affect the predictive power of a test—whether it is correct or not. Building on this, we draw up recommendations for better practice to convey the results of medical tests that could inform health policy makers (What are the drawbacks of mass screenings?), be used by health practitioners and, in turn, help patients to make better and more informed decisions. Frontiers Media S.A. 2015-09-17 /pmc/articles/PMC4585185/ /pubmed/26441711 http://dx.doi.org/10.3389/fpsyg.2015.01327 Text en Copyright © 2015 Navarrete, Correia, Sirota, Juanchich and Huepe. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Navarrete, Gorka
Correia, Rut
Sirota, Miroslav
Juanchich, Marie
Huepe, David
Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication
title Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication
title_full Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication
title_fullStr Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication
title_full_unstemmed Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication
title_short Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication
title_sort doctor, what does my positive test mean? from bayesian textbook tasks to personalized risk communication
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585185/
https://www.ncbi.nlm.nih.gov/pubmed/26441711
http://dx.doi.org/10.3389/fpsyg.2015.01327
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