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Language of Uncertainty: the Expression of Decisional Conflict Related to Skin Cancer Prevention Recommendations

Language of Uncertainty: the Expression of Decisional Conflict Related to Skin Cancer Prevention... User-generated information on the Internet provides opportunities for the monitoring of health information consumer attitudes. For example, information about cancer prevention may cause decisional conflict. Yet posts and conversations shared by health information consumers online are often not readily actionable for interpretation and decision-making due to their unstandardized format. This study extends prior research on the use of natural language as a predictor of consumer attitudes and provides a link to decision-making by evaluating the predictive role of uncertainty indicators expressed in natural language. Analyzed data included free-text comments and structured scale responses related to information about skin cancer prevention options. The study identified natural language indicators of uncertainty and showed that it can serve as a predictor of decisional conflict. The natural indicators of uncertainty reported here can facilitate the monitoring of health consumer perceptions about cancer prevention recommendations and inform education and communication campaign planning and evaluation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Cancer Education Springer Journals

Language of Uncertainty: the Expression of Decisional Conflict Related to Skin Cancer Prevention Recommendations

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References (13)

Publisher
Springer Journals
Copyright
Copyright © 2016 by American Association for Cancer Education
Subject
Biomedicine; Cancer Research; Pharmacology/Toxicology
ISSN
0885-8195
eISSN
1543-0154
DOI
10.1007/s13187-016-0985-6
pmid
26781777
Publisher site
See Article on Publisher Site

Abstract

User-generated information on the Internet provides opportunities for the monitoring of health information consumer attitudes. For example, information about cancer prevention may cause decisional conflict. Yet posts and conversations shared by health information consumers online are often not readily actionable for interpretation and decision-making due to their unstandardized format. This study extends prior research on the use of natural language as a predictor of consumer attitudes and provides a link to decision-making by evaluating the predictive role of uncertainty indicators expressed in natural language. Analyzed data included free-text comments and structured scale responses related to information about skin cancer prevention options. The study identified natural language indicators of uncertainty and showed that it can serve as a predictor of decisional conflict. The natural indicators of uncertainty reported here can facilitate the monitoring of health consumer perceptions about cancer prevention recommendations and inform education and communication campaign planning and evaluation.

Journal

Journal of Cancer Education – Springer Journals

Published: Jan 19, 2016

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