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The Use of Narrative Evidence and Explicit Likelihood by Decisionmakers Varying in Numeracy

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  • Nathan F. Dieckmann
  • Paul Slovic
  • Ellen M. Peters

Abstract

Decisionmakers are often presented with explicit likelihood assessments (e.g., there is a 10% chance that an attack will occur over the next three months) and supporting narrative evidence in forecasting and risk communication domains. Decisionmakers are thought to rely on both numerical and narrative information to the extent that they perceive the information to be diagnostic, accurate, and trustworthy. In two studies, we explored how lay decisionmakers varying in numeracy evaluated and used likelihood assessments and narrative evidence in forecasts. Overall, the less numerate reported higher risk and likelihood perceptions. In simple probabilistic forecasts without narrative evidence, decisionmakers at all levels of numeracy were able to use the stated likelihood information, although risk perceptions of the less numerate were more affected by likelihood format. When a forecast includes narrative evidence, decisionmakers were better able to use stated likelihood in a percentage as compared to frequency or verbal formats. The more numerate used stated likelihood more in their evaluations whereas the less numerate focused more on the narrative evidence. These results have important implications for risk analysts and forecasters who need to report the results of their analyses to decisionmakers. Decisionmakers varying in numerical ability may evaluate forecasts in different ways depending on the types of information they find easiest to evaluate.

Suggested Citation

  • Nathan F. Dieckmann & Paul Slovic & Ellen M. Peters, 2009. "The Use of Narrative Evidence and Explicit Likelihood by Decisionmakers Varying in Numeracy," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1473-1488, October.
  • Handle: RePEc:wly:riskan:v:29:y:2009:i:10:p:1473-1488
    DOI: 10.1111/j.1539-6924.2009.01279.x
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    Cited by:

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    2. Robin Gregory & Nathan Dieckmann & Ellen Peters & Lee Failing & Graham Long & Martin Tusler, 2012. "Deliberative Disjunction: Expert and Public Understanding of Outcome Uncertainty," Risk Analysis, John Wiley & Sons, vol. 32(12), pages 2071-2083, December.
    3. Ian G. J. Dawson, 2018. "Assessing the Effects of Information About Global Population Growth on Risk Perceptions and Support for Mitigation and Prevention Strategies," Risk Analysis, John Wiley & Sons, vol. 38(10), pages 2222-2241, October.
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    5. Nathan F. Dieckmann & Ellen Peters & Robin Gregory, 2015. "At Home on the Range? Lay Interpretations of Numerical Uncertainty Ranges," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1281-1295, July.
    6. Ellen Peters & P. Sol Hart & Liana Fraenkel, 2011. "Informing Patients," Medical Decision Making, , vol. 31(3), pages 432-436, May.
    7. Nathan F. Dieckmann & Ellen Peters & Robin Gregory & Martin Tusler, 2012. "Making sense of uncertainty: advantages and disadvantages of providing an evaluative structure," Journal of Risk Research, Taylor & Francis Journals, vol. 15(7), pages 717-735, August.
    8. Yasmina Okan & Eva Janssen & Mirta Galesic & Erika A. Waters, 2019. "Using the Short Graph Literacy Scale to Predict Precursors of Health Behavior Change," Medical Decision Making, , vol. 39(3), pages 183-195, April.
    9. Isaac M. Lipkus & Ellen Peters & Gretchen Kimmick & Vlayka Liotcheva & Paul Marcom, 2010. "Breast Cancer Patients’ Treatment Expectations after Exposure to the Decision Aid Program Adjuvant Online: The Influence of Numeracy," Medical Decision Making, , vol. 30(4), pages 464-473, July.
    10. Shoots-Reinhard, Brittany & Goodwin, Raleigh & Bjälkebring, Pär & Markowitz, David M. & Silverstein, Michael C. & Peters, Ellen, 2021. "Ability-related political polarization in the COVID-19 pandemic," Intelligence, Elsevier, vol. 88(C).
    11. Ian G. J. Dawson & Johnnie E. V. Johnson & Michelle A. Luke, 2013. "Helping Individuals to Understand Synergistic Risks: An Assessment of Message Contents Depicting Mechanistic and Probabilistic Concepts," Risk Analysis, John Wiley & Sons, vol. 33(5), pages 851-865, May.
    12. Nathan F. Dieckmann & Robin Gregory & Ellen Peters & Robert Hartman, 2017. "Seeing What You Want to See: How Imprecise Uncertainty Ranges Enhance Motivated Reasoning," Risk Analysis, John Wiley & Sons, vol. 37(3), pages 471-486, March.
    13. Yaniv Hanoch & Jonathan Rolison & Alexandra M. Freund, 2019. "Reaping the Benefits and Avoiding the Risks: Unrealistic Optimism in the Health Domain," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 792-804, April.
    14. Victoria A. Shaffer & Brian J. Zikmund-Fisher, 2013. "All Stories Are Not Alike," Medical Decision Making, , vol. 33(1), pages 4-13, January.
    15. William J. Burns & Ellen Peters & Paul Slovic, 2012. "Risk Perception and the Economic Crisis: A Longitudinal Study of the Trajectory of Perceived Risk," Risk Analysis, John Wiley & Sons, vol. 32(4), pages 659-677, April.
    16. 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.
    17. Ellen Peters & P. Sol Hart & Martin Tusler & Liana Fraenkel, 2014. "Numbers Matter to Informed Patient Choices," Medical Decision Making, , vol. 34(4), pages 430-442, May.
    18. Nathan F. Dieckmann & Robert Mauro & Paul Slovic, 2010. "The Effects of Presenting Imprecise Probabilities in Intelligence Forecasts," Risk Analysis, John Wiley & Sons, vol. 30(6), pages 987-1001, June.

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