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Understanding the Positive Effects of Graphical Risk Information on Comprehension: Measuring Attention Directed to Written, Tabular, and Graphical Risk Information

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  • Chris M. R. Smerecnik
  • Ilse Mesters
  • Loes T. E. Kessels
  • Robert A. C. Ruiter
  • Nanne K. De Vries
  • Hein De Vries

Abstract

Risk communications are an integral aspect of health education and promotion. However, the commonly used textual risk information is relatively difficult to understand for the average recipient. Consequently, researchers and health promoters have started to focus on so‐called decision aids, such as tables and graphs. Although tabular and graphical risk information more effectively communicate risks than textual risk information, the cognitive mechanisms responsible for this enhancement are unclear. This study aimed to examine two possible mechanisms (i.e., cognitive workload and attention). Cognitive workload (mean pupil size and peak pupil dilation) and attention directed to the risk information (viewing time, number of eye fixations, and eye fixation durations) were both measured in a between‐subjects experimental design. The results suggest that graphical risk information facilitates comprehension of that information because it attracts and holds attention for a longer period of time than textual risk information. Graphs are thus a valuable asset to risk communication practice for two reasons: first, they tend to attract attention and, second, when attended to, they elicit information extraction with relatively little cognitive effort, and finally result in better comprehension.

Suggested Citation

  • Chris M. R. Smerecnik & Ilse Mesters & Loes T. E. Kessels & Robert A. C. Ruiter & Nanne K. De Vries & Hein De Vries, 2010. "Understanding the Positive Effects of Graphical Risk Information on Comprehension: Measuring Attention Directed to Written, Tabular, and Graphical Risk Information," Risk Analysis, John Wiley & Sons, vol. 30(9), pages 1387-1398, September.
    • Handle: RePEc:wly:riskan:v:30:y:2010:i:9:p:1387-1398
    DOI: 10.1111/j.1539-6924.2010.01435.x
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    References listed on IDEAS

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    2. Mihai Țichindelean & Monica Teodora Țichindelean & Iuliana Cetină & Gheorghe Orzan, 2021. "A Comparative Eye Tracking Study of Usability—Towards Sustainable Web Design," Sustainability, MDPI, vol. 13(18), pages 1-31, September.
    3. Noel T. Brewer & Melissa B. Gilkey & Sarah E. Lillie & Bradford W. Hesse & Stacey L. Sheridan, 2012. "Tables or Bar Graphs? Presenting Test Results in Electronic Medical Records," Medical Decision Making, , vol. 32(4), pages 545-553, July.
    4. Christopher E. Clarke & Jeff Niederdeppe & Helen C. Lundell, 2012. "Narratives and Images Used by Public Communication Campaigns Addressing Social Determinants of Health and Health Disparities," IJERPH, MDPI, vol. 9(12), pages 1-24, November.
    5. Borozan, Miloš & Loreta, Cannito & Riccardo, Palumbo, 2022. "Eye-tracking for the study of financial decision-making: A systematic review of the literature," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    6. Lyndal J. Trevena & Carissa Bonner & Yasmina Okan & Ellen Peters & Wolfgang Gaissmaier & Paul K. J. Han & Elissa Ozanne & Danielle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts," Medical Decision Making, , vol. 41(7), pages 834-847, October.
    7. T. Soliman & A. MacLeod & J. D. Mumford & T. P. L. Nghiem & H. T. W. Tan & S. K. Papworth & R. T. Corlett & L. R. Carrasco, 2016. "A Regional Decision Support Scheme for Pest Risk Analysis in Southeast Asia," Risk Analysis, John Wiley & Sons, vol. 36(5), pages 904-913, May.
    8. Chris M. R. Smerecnik & Ilse Mesters & Math J. J. M. Candel & Hein De Vries & Nanne K. De Vries, 2012. "Risk Perception and Information Processing: The Development and Validation of a Questionnaire to Assess Self‐Reported Information Processing," Risk Analysis, John Wiley & Sons, vol. 32(1), pages 54-66, January.

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