Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations
Perception of health risk can affect medical decisions and health behavior change. Yet the concept of risk is a difficult one for the public to grasp. Whether perceptions of risk affect decisions and behaviors often relies on how messages of risk magnitudes (i.e., likelihood) are conveyed. Based on...
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Published in | Medical decision making Vol. 27; no. 5; p. 696 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
United States
01.09.2007
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Subjects | |
Online Access | Get more information |
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Summary: | Perception of health risk can affect medical decisions and health behavior change. Yet the concept of risk is a difficult one for the public to grasp. Whether perceptions of risk affect decisions and behaviors often relies on how messages of risk magnitudes (i.e., likelihood) are conveyed. Based on expert opinion, this article offers, when possible, best practices for conveying magnitude of health risks using numeric, verbal, and visual formats. This expert opinion is based on existing empirical evidence, review of papers and books, and consultations with experts in risk communication. This article also discusses formats to use pertaining to unique risk communication challenges (e.g., conveying small-probability events, interactions). Several recommendations are suggested for enhancing precision in perception of risk by presenting risk magnitudes numerically and visually. Overall, there are little data to suggest best practices for verbal communication of risk magnitudes. Across the 3 formats, few overall recommendations could be suggested because of 1) lack of consistency in testing formats using the same outcomes in the domain of interest, 2) lack of critical tests using randomized controlled studies pitting formats against one another, and 3) lack of theoretical progress detailing and testing mechanisms why one format should be more efficacious in a specific context to affect risk magnitudes than others. Areas of future research are provided that it is hoped will help illuminate future best practices. |
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ISSN: | 0272-989X |
DOI: | 10.1177/0272989X07307271 |