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Frequency or Probability? A Qualitative Study of Risk Communication Formats Used in Health Care

Author

Listed:
  • Marilyn M. Schapira

    (Department of Medicine, Medical College of Wisconsin, Milwaukee, and the Center for Health Services Management and Research and Veterans Administration Medical Center, Lexington, Kentucky)

  • Ann B. Nattinger

    (Department of Medicine, Medical College of Wisconsin, Milwaukee, and the Center for Health Services Management and Research and Veterans Administration Medical Center, Lexington, Kentucky)

  • Colleen A. McHorney

    (Department of Medicine, Medical College of Wisconsin, Milwaukee, and the Center for Health Services Management and Research and Veterans Administration Medical Center, Lexington, Kentucky)

Abstract

Background . The communication of probabilistic outcomes is an essential aspect of shared medical decision making. Methods . The authors conducted a qualitative study using focus groups to evaluate the response of women to various formats used in the communication of breast cancer risk. Findings . Graphic discrete frequency formats using highlighted human figures had greater salience than continuous probability formats using bar graphs. Potential biases in the estimation of risk magnitude were associated with the use of highlighted human figures versus bar graphs and the denominator size in graphics using highlighted human figures. The presentation of uncertainty associated with risk estimates caused some to loose trust in the information, whereas others were accepting of uncertainty in scientific data. Conclusion . The qualitative study identified new constructs with regard to how patients process probabilistic information. Further research in the clinical setting is needed to provide a theoretical justification for the format used when presenting risk information to patients.

Suggested Citation

  • Marilyn M. Schapira & Ann B. Nattinger & Colleen A. McHorney, 2001. "Frequency or Probability? A Qualitative Study of Risk Communication Formats Used in Health Care," Medical Decision Making, , vol. 21(6), pages 459-467, December.
    • Handle: RePEc:sae:medema:v:21:y:2001:i:6:p:459-467
    DOI: 10.1177/0272989X0102100604
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    References listed on IDEAS

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    1. Branden B. Johnson, 1999. "Ethical Issues in Risk Communication: Continuing the Discussion," Risk Analysis, John Wiley & Sons, vol. 19(3), pages 335-348, June.
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    Cited by:

    1. Paul C. Price & Grace A. Carlock & Sarah Crouse & Mariana Vargas Arciga, 2022. "Effects of icon arrays to communicate risk in a repeated risky decision-making task," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 17(2), pages 378-399, March.
    2. Luca Congiu, 2023. "Framing Effects in the Elicitation of Risk Aversion: An Experimental Study," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(1), pages 321-352, March.
    3. John A. Edwards & Frank J. Snyder & Pamela M. Allen & Kevin A. Makinson & David M. Hamby, 2012. "Decision Making for Risk Management: A Comparison of Graphical Methods for Presenting Quantitative Uncertainty," Risk Analysis, John Wiley & Sons, vol. 32(12), pages 2055-2070, December.
    4. John Fountain & Philip Gunby, 2010. "Comparing Ambiguous Inferences When Probabilities are Imprecise," Working Papers in Economics 10/08, University of Canterbury, Department of Economics and Finance.
    5. Jose Luis Pinto-Prades & Jorge E. Martinez Perez & Jose María Abellán Perpiñán, 2006. "The influence of the Ratio Bias phenomenon on the elicitation of Standard Gamble utilities," Working Papers 06.16, Universidad Pablo de Olavide, Department of Economics.
    6. Carmen Keller & Michael Siegrist, 2009. "Effect of Risk Communication Formats on Risk Perception Depending on Numeracy," Medical Decision Making, , vol. 29(4), pages 483-490, July.
    7. Michael Yu & Tomás Lejarraga & Cleotilde Gonzalez, 2012. "Context‐Specific, Scenario‐Based Risk Scales," Risk Analysis, John Wiley & Sons, vol. 32(12), pages 2166-2181, December.
    8. Carissa Bonner & Lyndal J. Trevena & Wolfgang Gaissmaier & Paul K. J. Han & Yasmina Okan & Elissa Ozanne & Ellen Peters & Daniëlle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles," Medical Decision Making, , vol. 41(7), pages 821-833, October.
    9. Casey Canfield & Wändi Bruine de Bruin & Gabrielle Wong-Parodi, 2017. "Perceptions of electricity-use communications: effects of information, format, and individual differences," Journal of Risk Research, Taylor & Francis Journals, vol. 20(9), pages 1132-1153, September.
    10. van der Bles, Anne Marthe & van der Liden, Sander & Freeman, Alessandra L. J. & Mitchell, James & Galvao, Ana Beatriz & Spiegelhalter, David J., 2019. "Communicating uncertainty about facts, numbers, and science," EMF Research Papers 22, Economic Modelling and Forecasting Group.
    11. repec:cup:judgdm:v:17:y:2022:i:2:p:378-399 is not listed on IDEAS
    12. 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.
    13. Karl Schlag & James Tremewan, 2021. "Simple belief elicitation: An experimental evaluation," Journal of Risk and Uncertainty, Springer, vol. 62(2), pages 137-155, April.
    14. Vivianne H. M. Visschers & Ree M. Meertens & Wim W. F. Passchier & Nanne N. K. De Vries, 2009. "Probability Information in Risk Communication: A Review of the Research Literature," Risk Analysis, John Wiley & Sons, vol. 29(2), pages 267-287, February.
    15. Toshio Fujimi & Masahide Watanabe & Hirokazu Tatano, 2021. "Public trust, perceived accuracy, perceived likelihood, and concern on multi-model climate projections communicated with different formats," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(5), pages 1-20, June.
    16. Jose-Luis Pinto-Prades & Jorge-Eduardo Martinez-Perez & Jose-Maria Abellan-Perpinan, 2006. "The influence of the ratio bias phenomenon on the elicitation of health states utilities," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 1, pages 118-133, November.
    17. Mark Harrison & Carlo A. Marra & Nick Bansback, 2017. "Preferences for ‘New’ Treatments Diminish in the Face of Ambiguity," Health Economics, John Wiley & Sons, Ltd., vol. 26(6), pages 743-752, June.
    18. Marilyn M. Schapira & Susan L. Davids & Timothy L. McAuliffe & Ann B. Nattinger, 2004. "Agreement Between Scales in the Measurement of Breast Cancer Risk Perceptions," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 665-673, June.
    19. Schlosser, Ann E., 2018. "What are my chances? An imagery versus discursive processing approach to understanding ratio-bias effects," Organizational Behavior and Human Decision Processes, Elsevier, vol. 144(C), pages 112-124.
    20. 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.
    21. repec:cup:judgdm:v:1:y:2006:i::p:118-133 is not listed on IDEAS

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