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Natural Frequencies Do Foster Public Understanding of Medical Tests: Comment on Pighin, Gonzalez, Savadori, and Girotto (2016)

Author

Listed:
  • Michelle McDowell

    (Harding Center for Risk Literacy, Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, Germany)

  • Mirta Galesic

    (Cowan Chair in Human Social Dynamics, Santa Fe Institute, Santa Fe, New Mexico, USA)

  • Gerd Gigerenzer

    (Harding Center for Risk Literacy, Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, Germany)

Abstract

Patients and doctors often need to make decisions based on the results of medical tests. When these results are presented in the form of conditional probabilities, even doctors find it difficult to interpret them correctly. There is over 20 y of research supporting the finding that people are better able to calculate the correct positive predictive value of a test when given information in natural frequencies, as opposed to conditional probabilities. Natural frequencies are one of a few psychological tools that have made it into evidence-based medicine. Recently, Pighin and others (Med Decis Making 2016;36:686–91) argued that natural frequencies could hinder informed decision making, a critique based on a single task and a crude scoring criterion we refer to as the 50%-Split. Our commentary addresses these criticisms based on three analyses. First, we show how the 50%-Split scoring used by Pighin and others misclassifies known errors, such as solely attending to the hit rate (true-positive rate) of the test, as strategies that support understanding. Second, we reanalyze data from 21 additional problems completed by various participant groups to show that their scoring criterion does not support their results in 19 out of 21 cases. Third, we apply the mean deviation scoring method and show that, when given information in natural frequency formats, participants provide estimates that are closer to the correct Bayesian solution than for conditional probability formats. In each analysis, natural frequencies lead to more correct judgements and therefore promote informed decision making relative to conditional probabilities. We welcome further discussions of performance metrics that can provide insight into how the public and therefore patients understand the implications of medical test results.

Suggested Citation

  • Michelle McDowell & Mirta Galesic & Gerd Gigerenzer, 2018. "Natural Frequencies Do Foster Public Understanding of Medical Tests: Comment on Pighin, Gonzalez, Savadori, and Girotto (2016)," Medical Decision Making, , vol. 38(3), pages 390-399, April.
  • Handle: RePEc:sae:medema:v:38:y:2018:i:3:p:390-399
    DOI: 10.1177/0272989X18754508
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    References listed on IDEAS

    as
    1. Krauss, Stefan & Martignon, Laura & Hoffrage, Ulrich, 1999. "Simplifying Bayesian Inference: The General Case," Sonderforschungsbereich 504 Publications 99-23, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    2. Michael Siegrist & Carmen Keller, 2011. "Natural frequencies and Bayesian reasoning: the impact of formal education and problem context," Journal of Risk Research, Taylor & Francis Journals, vol. 14(9), pages 1039-1055, October.
    3. Garcia-Retamero, Rocio & Hoffrage, Ulrich, 2013. "Visual representation of statistical information improves diagnostic inferences in doctors and their patients," Social Science & Medicine, Elsevier, vol. 83(C), pages 27-33.
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