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Ratio Format Shapes Health Decisions: The Practical Significance of the “1-in-X†Effect

Author

Listed:
  • Miroslav Sirota

    (Department of Psychology, University of Essex, Colchester, Essex, UK)

  • Marie Juanchich

    (Department of Psychology, University of Essex, Colchester, Essex, UK)

Abstract

Prior research found that “1-in-X†ratios led to higher and less accurate subjective probability than “N-in-X*N†ratios or other formats, even though they featured the same mathematical information. It is unclear, however, whether the effect transfers into health decisions, and the practical significance of the effect is undetermined. Based on previous findings and risk communication theories, we hypothesized that the 1-in-X effect would occur and transfer into relevant decisions. We also tested whether age, gender, and education differences would moderate the 1-in-X effect on decision making. We conducted 3 well-powered experiments ( n = 1912) using a sample from the general adult UK population to test our hypotheses, estimated the effect, and excluded a possible methodological explanation for such a transfer. In hypothetical scenarios, participants decided whether to travel to Kenya given the chance of contracting malaria (experiment 1) and whether to take recommended steroids given the side effects (experiments 2 and 3). Across the experiments, we replicated a small to medium 1-in-X effect on the perceived probability (Hedge’s g = −0.36; 95% confidence interval [CI], −0.47 to −0.24; z = −6.18; P

Suggested Citation

  • Miroslav Sirota & Marie Juanchich, 2019. "Ratio Format Shapes Health Decisions: The Practical Significance of the “1-in-X†Effect," Medical Decision Making, , vol. 39(1), pages 32-40, January.
    • Handle: RePEc:sae:medema:v:39:y:2019:i:1:p:32-40
    DOI: 10.1177/0272989X18814256
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    References listed on IDEAS

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    1. Stefania Pighin & Lucia Savadori & Elisa Barilli & Laura Cremonesi & Maurizio Ferrari & Jean-François Bonnefon, 2011. "The 1-in-X Effect on the Subjective Assessment of Medical Probabilities," Medical Decision Making, , vol. 31(5), pages 721-729, September.
    2. Saima Ghazal & Edward T. Cokely & Rocio Garcia-Retamero, 2014. "Predicting biases in very highly educated samples: Numeracy and metacognition," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(1), pages 15-34, January.
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    Cited by:

    1. 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).
    2. Maria Michela Dickson & Giuseppe Espa & Rocco Micciolo & Lucia Savadori, 2024. "Numerical format and public perception of foreign immigration growth rates," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-17, October.

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