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Effect of Framing as Gain versus Loss on Understanding and Hypothetical Treatment Choices: Survival and Mortality Curves

Author

Listed:
  • Katrina Armstrong

    (Department of Medicine, University of Pennsylvania School of Medicine, Leonard Davis Institute of Health Economics, University of Pennsylvania, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, University of Pennsylvania Cancer Center)

  • J. Sanford Schwartz

    (Department of Medicine, University of Pennsylvania School of Medicine, Leonard Davis Institute of Health Economics, University of Pennsylvania, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, University of Pennsylvania Cancer Center)

  • Genevieve Fitzgerald

    (Department of Medicine, University of Pennsylvania School of Medicine)

  • Mary Putt

    (Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, University of Pennsylvania Cancer Center)

  • Peter A. Ubel

    (Department of Medicine, University of Pennsylvania School of Medicine, Leonard Davis Institute of Health Economics, University of Pennsylvania, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, University of Pennsylvania Cancer Center, Philadelphia Veterans Affairs Medical Center)

Abstract

Background . Presentation of information using survival or mortality (i.e., incidence) curves offers a potentially powerful method of communication because such curves provide information about risk over time in a relatively simple graphic format. However, the effect of framing as survival versus mortality on understanding and treatment choice is not known. Methods . In this study, 451 individuals awaiting jury duty at the Philadelphia City Courthouse were randomized to receive 1 of 3 questionnaires: (1) survival curves, (2) mortality curves, or (3) both survival and mortality curves. Each questionnaire included a brief description of a hypothetical treatment decision, survival curve graphs and/or mortality curve graphs presenting the outcome of the treatment, and questions measuring understanding of the information contained in the graphs and preference for undergoing treatment. After completing a brief practice exercise, participants were asked to answer questions assessing their ability to interpret single points on a curve and the difference between curves, and then to decide whether they would choose to undergo preventive surgery for 3 different scenarios in which the benefit of surgery varied. Results . Participants who received only survival curves or who received both survival and mortality curves were significantly more accurate in answering questions about the information than participants who received only mortality curves (P

Suggested Citation

  • Katrina Armstrong & J. Sanford Schwartz & Genevieve Fitzgerald & Mary Putt & Peter A. Ubel, 2002. "Effect of Framing as Gain versus Loss on Understanding and Hypothetical Treatment Choices: Survival and Mortality Curves," Medical Decision Making, , vol. 22(1), pages 76-83, February.
    • Handle: RePEc:sae:medema:v:22:y:2002:i:1:p:76-83
    DOI: 10.1177/0272989X0202200108
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    References listed on IDEAS

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    1. Levin, Irwin P. & Schneider, Sandra L. & Gaeth, Gary J., 1998. "All Frames Are Not Created Equal: A Typology and Critical Analysis of Framing Effects," Organizational Behavior and Human Decision Processes, Elsevier, vol. 76(2), pages 149-188, November.
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    2. 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.
    3. Steven J. Stanton & Crystal Reeck & Scott A. Huettel & Kevin S. LaBar, 2014. "Effects of induced moods on economic choices," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(2), pages 167-175, March.
    4. Avineri, Erel & Owen D. Waygood, E., 2013. "Applying valence framing to enhance the effect of information on transport-related carbon dioxide emissions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 48(C), pages 31-38.
    5. 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.
    6. Louis Anthony (Tony) Cox, 2015. "Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks," Risk Analysis, John Wiley & Sons, vol. 35(10), pages 1892-1910, October.
    7. Brian J. Zikmund‐Fisher & Angela Fagerlin & Peter A. Ubel, 2005. "What's Time Got to Do with It? Inattention to Duration in Interpretation of Survival Graphs," Risk Analysis, John Wiley & Sons, vol. 25(3), pages 589-595, June.
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    9. Biroli, Pietro & Bosworth, Steven J. & Della Giusta, Marina & Di Girolamo, Amalia & Jaworska, Sylvia & Vollen, Jeremy, 2020. "Framing the Predicted Impacts of COVID-19 Prophylactic Measures in Terms of Lives Saved Rather Than Deaths Is More Effective for Older People," IZA Discussion Papers 13753, Institute of Labor Economics (IZA).

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