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Does Iconicity in Pictographs Matter? The Influence of Iconicity and Numeracy on Information Processing, Decision Making, and Liking in an Eye‐Tracking Study

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  • Christina Kreuzmair
  • Michael Siegrist
  • Carmen Keller

Abstract

Researchers recommend the use of pictographs in medical risk communication to improve people's risk comprehension and decision making. However, it is not yet clear whether the iconicity used in pictographs to convey risk information influences individuals’ information processing and comprehension. In an eye‐tracking experiment with participants from the general population (N = 188), we examined whether specific types of pictograph icons influence the processing strategy viewers use to extract numerical information. In addition, we examined the effect of iconicity and numeracy on probability estimation, recall, and icon liking. This experiment used a 2 (iconicity: blocks vs. restroom icons) × 2 (scenario: medical vs. nonmedical) between‐subject design. Numeracy had a significant effect on information processing strategy, but we found no effect of iconicity or scenario. Results indicated that both icon types enabled high and low numerates to use their default way of processing and extracting the gist of the message from the pictorial risk communication format: high numerates counted icons, whereas low numerates used large‐area processing. There was no effect of iconicity in the probability estimation. However, people who saw restroom icons had a higher probability of correctly recalling the exact risk level. Iconicity had no effect on icon liking. Although the effects are small, our findings suggest that person‐like restroom icons in pictographs seem to have some advantages for risk communication. Specifically, in nonpersonalized prevention brochures, person‐like restroom icons may maintain reader motivation for processing the risk information.

Suggested Citation

  • Christina Kreuzmair & Michael Siegrist & Carmen Keller, 2017. "Does Iconicity in Pictographs Matter? The Influence of Iconicity and Numeracy on Information Processing, Decision Making, and Liking in an Eye‐Tracking Study," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 546-556, March.
  • Handle: RePEc:wly:riskan:v:37:y:2017:i:3:p:546-556
    DOI: 10.1111/risa.12623
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    1. Brian J. Zikmund-Fisher & Holly O. Witteman & Mark Dickson & Andrea Fuhrel-Forbis & Valerie C. Kahn & Nicole L. Exe & Melissa Valerio & Lisa G. Holtzman & Laura D. Scherer & Angela Fagerlin, 2014. "Blocks, Ovals, or People? Icon Type Affects Risk Perceptions and Recall of Pictographs," Medical Decision Making, , vol. 34(4), pages 443-453, May.
    2. Nina Horstmann & Andrea Ahlgrimm & Andreas Glöckner, 2009. "How Distinct are Intuition and Deliberation? An Eye-Tracking Analysis of Instruction-Induced Decision Modes," Discussion Paper Series of the Max Planck Institute for Behavioral Economics 2009_10, Max Planck Institute for Behavioral Economics.
    3. Daniel A. Hamstra & Skyler B. Johnson & Stephanie Daignault & Brian J. Zikmund-Fisher & Jeremy M. G. Taylor & Knoll Larkin & Alexander Wood & Angela Fagerlin, 2015. "The Impact of Numeracy on Verbatim Knowledge of the Longitudinal Risk for Prostate Cancer Recurrence following Radiation Therapy," Medical Decision Making, , vol. 35(1), pages 27-36, January.
    4. Deb Feldman-Stewart & Michael D. Brundage & Vladimir Zotov, 2007. "Further Insight into the Perception of Quantitative Information: Judgments of Gist in Treatment Decisions," Medical Decision Making, , vol. 27(1), pages 34-43, January.
    5. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
    6. Rocio Garcia-Retamero & Mirta Galesic & Gerd Gigerenzer, 2010. "Do Icon Arrays Help Reduce Denominator Neglect?," Medical Decision Making, , vol. 30(6), pages 672-684, November.
    7. Rebecca Hess & Vivianne H. M. Visschers & Michael Siegrist, 2011. "Risk communication with pictographs: The role of numeracy and graph processing," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(3), pages 263-274, April.
    8. Carmen Keller & Christina Kreuzmair & Rebecca Leins-Hess & Michael Siegrist, 2014. "Numeric and graphic risk information processing of high and low numerates in the intuitive and deliberative decision modes: An eye-tracker study," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 420-432, September.
    9. Angela Fagerlin & Catharine Wang & Peter A. Ubel, 2005. "Reducing the Influence of Anecdotal Reasoning on People’s Health Care Decisions: Is a Picture Worth a Thousand Statistics?," Medical Decision Making, , vol. 25(4), pages 398-405, July.
    10. Garcia-Retamero, Rocio & Galesic, Mirta, 2010. "Who proficts from visual aids: Overcoming challenges in people's understanding of risks," Social Science & Medicine, Elsevier, vol. 70(7), pages 1019-1025, April.
    11. Nina Horstmann & Andrea Ahlgrimm & Andreas Glöckner, 2009. "How distinct are intuition and deliberation? An eye-tracking analysis of instruction-induced decision modes," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(5), pages 335-354, August.
    12. Isaac M. Lipkus & Greg Samsa & Barbara K. Rimer, 2001. "General Performance on a Numeracy Scale among Highly Educated Samples," Medical Decision Making, , vol. 21(1), pages 37-44, February.
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