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A Test of Numeric Formats for Communicating Risk Probabilities

Author

Listed:
  • Cara L. Cuite

    (Food Policy Institute, Rutgers, The State University of New Jersey, New Brunswick, cuite@aesop.rutgers.edu)

  • Neil D. Weinstein

    (Department of Family and Community Medicine, University of Arizona College of Medicine, Phoenix)

  • Karen Emmons

    (Harvard School of Public Health, Dana Farber Cancer Center, Boston, Massachusetts)

  • Graham Colditz

    (Alvin J. Site-man Cancer Center, Washington University School of Medicine, St. Louis, MO)

Abstract

Background. Because people frequently encounter information about the probability of health risks, there is a need for research to help identify the best formats for presenting these probabilities. Methods. Three waves of participants were recruited from visitors to a cancer-related Internet site. Participants were presented with a hypothetical scenario that required them to perform 2 mathematical operations of the types that might be encountered in discussions of risk. Each wave encountered different operations. The operations used were compare, halve, triple, add, sequence, and tradeoff. Three numeric formats for communicating risk likelihoods were tested: percentages (e.g., 12%), frequencies (e.g., 12 in 100), and 1 in n (e.g., 1 in 8), and many levels of risk magnitude were crossed with the 3 formats. Results. The total sample of 16,133 individuals represented an overall participation rate of 36.1%. Although the relative performance of the formats varied by operation, aggregated across operations, the percentage and frequency formats had higher overall accuracy rates than the 1-in-n format (57% and 55% v. 45%, respectively). Participants with less education, African Americans, Hispanics, and women had more difficulty with the mathematical operations. Discussion. Percentage and frequency formats facilitate performance of simple operations on risk probabilities compared with the 1-in-n format, which should usually be avoided.

Suggested Citation

  • Cara L. Cuite & Neil D. Weinstein & Karen Emmons & Graham Colditz, 2008. "A Test of Numeric Formats for Communicating Risk Probabilities," Medical Decision Making, , vol. 28(3), pages 377-384, May.
    • Handle: RePEc:sae:medema:v:28:y:2008:i:3:p:377-384
    DOI: 10.1177/0272989X08315246
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    References listed on IDEAS

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    1. Steven Woloshin & Lisa M. Schwartz & Stephanie Byram & Baruch Fischhoff & H. Gilbert Welch, 2000. "A New Scale for Assessing Perceptions of Chance," Medical Decision Making, , vol. 20(3), pages 298-307, July.
    2. Michael Siegrist, 1997. "Communicating Low Risk Magnitudes: Incidence Rates Expressed as Frequency Versus Rates Expressed as Probability," Risk Analysis, John Wiley & Sons, vol. 17(4), pages 507-510, August.
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    Cited by:

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    2. Milou Kievik & Ellen F.J. ter Huurne & Jan M. Gutteling, 2012. "The action suited to the word? Use of the framework of risk information seeking to understand risk-related behaviors," Journal of Risk Research, Taylor & Francis Journals, vol. 15(2), pages 131-147, February.
    3. repec:cup:judgdm:v:3:y:2008:i:7:p:528-546 is not listed on IDEAS
    4. Eric R. Stone & Wändi Bruine de Bruin & Abigail M. Wilkins & Emily M. Boker & Jacqueline MacDonald Gibson, 2017. "Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 612-628, April.
    5. Suk, Kwanho & Hwang, Sanyoung & Jeong, Yunjoo, 2022. "The 1-in-X effect in perceptions of risk likelihood differences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 170(C).
    6. Biswas, Dipayan & Pechmann, Cornelia, 2012. "What do these clinical trial results mean? How product efficacy judgments are affected by data partitioning, framing, and quantification," Organizational Behavior and Human Decision Processes, Elsevier, vol. 117(2), pages 341-350.
    7. Michael H. Birnbaum & Kathleen Johnson & Jay-Lee Longbottom, 2008. "Tests of Cumulative Prospect Theory with graphical displays of probability," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 3(7), pages 528-546, October.
    8. Yasmina Okan & Eric R. Stone & Wändi Bruine de Bruin, 2018. "Designing Graphs that Promote Both Risk Understanding and Behavior Change," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 929-946, May.

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