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Using Comparison Scenarios to Improve Prenatal Risk Communication

Author

Listed:
  • Stefania Pighin
  • Lucia Savadori
  • Elisa Barilli
  • Rino Rumiati
  • Sara Bonalumi
  • Maurizio Ferrari
  • Laura Cremonesi

Abstract

The present research provides empirical evidence of whether communicating the prenatal risk of chromosomal anomalies using comparison scenarios influences women’s ability to distinguish between different risk levels. In 2 experiments, participants read a description of a hypothetical woman who was learning of the risk of chromosomal anomaly as a result of a prenatal screening test. Both experiments used a 3 (risk level) × 3 (scenario) full between-subjects design. In accordance with the experimental condition, participants were presented with a low (e.g., 1 in 5390), a medium (e.g., 1 in 770), or a high risk value (e.g., 1 in 110). Such risk values were presented either on their own or along with additional information illustrating a comparison scenario that provided 2 numerical comparison points. Participants were asked to evaluate the risk of chromosomal anomaly. In Experiment 2, participants’ numeracy skills were also assessed. Results showed that the use of comparison scenarios results in significant differences in perceived risk across risk levels whereas such differences are not significant without the comparison scenario, but such a technique has differential effects according to participants’ capacity to deal with numbers. Although the technique is beneficial for high-numerate participants, it has no effect on low-numerate participants.

Suggested Citation

  • Stefania Pighin & Lucia Savadori & Elisa Barilli & Rino Rumiati & Sara Bonalumi & Maurizio Ferrari & Laura Cremonesi, 2013. "Using Comparison Scenarios to Improve Prenatal Risk Communication," Medical Decision Making, , vol. 33(1), pages 48-58, January.
  • Handle: RePEc:sae:medema:v:33:y:2013:i:1:p:48-58
    DOI: 10.1177/0272989X12464433
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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. Hsee, Christopher K., 1996. "The Evaluability Hypothesis: An Explanation for Preference Reversals between Joint and Separate Evaluations of Alternatives," Organizational Behavior and Human Decision Processes, Elsevier, vol. 67(3), pages 247-257, September.
    3. 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.
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    1. 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.
    2. 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).

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