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J Am Med Inform Assoc 13:608-618 doi:10.1197/jamia.M2115
  • Review Paper
  • The Practice of Informatics

Design Features of Graphs in Health Risk Communication: A Systematic Review

  1. Jessica S Ancker,
  2. Yalini Senathirajah,
  3. Rita Kukafka,
  4. Justin B Starren
  1. Affiliations of the authors: Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, New York, NY (JSA, YS, RK); Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY (RK); Marshfield Clinic Research Foundation, Marshfield, WI (JBS)
  1. Correspondence and reprints: Jessica S. Ancker, MPH, Department of Biomedical Informatics, Columbia University College of Physicians and Surgeons, 622 W. 168th Street, Vanderbilt Clinic 5th Floor, New York, NY 10034. Email: <jsa2002{at}columbia.edu >
  • Received 30 March 2006
  • Accepted 17 June 2006

Abstract

This review describes recent experimental and focus group research on graphics as a method of communication about quantitative health risks. Some of the studies discussed in this review assessed effect of graphs on quantitative reasoning, others assessed effects on behavior or behavioral intentions, and still others assessed viewers’ likes and dislikes. Graphical features that improve the accuracy of quantitative reasoning appear to differ from the features most likely to alter behavior or intentions. For example, graphs that make part-to-whole relationships available visually may help people attend to the relationship between the numerator (the number of people affected by a hazard) and the denominator (the entire population at risk), whereas graphs that show only the numerator appear to inflate the perceived risk and may induce risk-averse behavior. Viewers often preferred design features such as visual simplicity and familiarity that were not associated with accurate quantitative judgments. Communicators should not assume that all graphics are more intuitive than text; many of the studies found that patients’ interpretations of the graphics were dependent upon expertise or instruction. Potentially useful directions for continuing research include interactions with educational level and numeracy and successful ways to communicate uncertainty about risk.

Footnotes

  • Ms. Ancker is supported by Robert Wood Johnson/National Library of Medicine predoctoral fellowship 5T15-LM007079-15.

  • a PsycInfo: controlled terms: decision making, graphical displays, numbers, risk taking, visual displays, risk perception, statistics, comprehension; key words: graph, graphical data, chart, pictogram, numeracy; limits: human; MEDLINE: MeSH headings: decision making, data display, risk taking, statistics, comprehension: key words: graph, computer graphics, health promotion, risk perception, risk communication, pictogram, numeracy; limits: evaluation studies, clinical trial, controlled clinical trial, randomized controlled trial, or validation studies, and human; CINAHL: controlled terms: decision making, risk-taking behavior, graphics, computer graphics, health promotion: key words: risk, graph, risk communication: limits: research; ACM Portal: key words: graphical perception, graphical user interface, human computer interaction, consumer health informatics, interactive health communication, risk, risk communication.

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