IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v40y2020i6p846-853.html
   My bibliography  Save this article

The Precision-Bias Distinction for Evaluating Visual Decision Aids for Risk Perception

Author

Listed:
  • Jessica K. Witt

Abstract

Risk communication is critically important, for both patients and providers. However, people struggle to understand risks because there are inherent biases and limitations to reasoning under uncertainty. A common strategy to enhance risk communication is the use of decision aids, such as charts or graphs, that depict the risk visually. A problem with prior research on visual decision aids is that it used a metric of performance that confounds 2 underlying constructs: precision and bias. Precision refers to a person’s sensitivity to the information, whereas bias refers to a general tendency to overestimate (or underestimate) the level of risk. A visual aid is effective for communicating risk only if it enhances precision or, once precision is suitably high, reduces bias. This article proposes a methodology for evaluating the effectiveness of visual decision aids. Empirical data further illustrate how the new methodology is a significant advancement over more traditional research designs.

Suggested Citation

  • Jessica K. Witt, 2020. "The Precision-Bias Distinction for Evaluating Visual Decision Aids for Risk Perception," Medical Decision Making, , vol. 40(6), pages 846-853, August.
    • Handle: RePEc:sae:medema:v:40:y:2020:i:6:p:846-853
    DOI: 10.1177/0272989X20943516
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X20943516
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X20943516?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James Alm & Lilith Burgstaller & Arrita Domi & Amanda März & Matthias Kasper, 2023. "Nudges, Boosts, and Sludge: Using New Behavioral Approaches to Improve Tax Compliance," Economies, MDPI, vol. 11(9), pages 1-22, September.
    2. Rocio Garcia-Retamero & Allen Andrade & Joseph Sharit & Jorge G. Ruiz, 2015. "Is Patients’ Numeracy Related to Physical and Mental Health?," Medical Decision Making, , vol. 35(4), pages 501-511, May.
    3. Eric R. Stone & Wändi Bruine de Bruin & Abigail M. Wilkins & Emily M. Boker & Jacqueline MacDonald Gibson, 2017. "Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 612-628, April.
    4. Aysegul Kanay & Denis Hilton & Laetitia Charalambides & Jean-Baptiste Corrégé & Eva Inaudi & Laurent Waroquier & Stéphane Cézéra, 2021. "Making the carbon basket count: Goal setting promotes sustainable consumption in a simulated online supermarket," Post-Print hal-03403040, HAL.
    5. 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.
    6. Alaina N. Talboy & Sandra L. Schneider, 2018. "Improving Understanding of Diagnostic Test Outcomes," Medical Decision Making, , vol. 38(5), pages 573-583, July.
    7. Lyndal J. Trevena & Carissa Bonner & Yasmina Okan & Ellen Peters & Wolfgang Gaissmaier & Paul K. J. Han & Elissa Ozanne & Danielle Timmermans & Brian J. Zikmund-Fisher, 2021. "Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts," Medical Decision Making, , vol. 41(7), pages 834-847, October.
    8. Stefania Pighin & Michel Gonzalez & Lucia Savadori & Vittorio Girotto, 2016. "Natural Frequencies Do Not Foster Public Understanding of Medical Test Results," Medical Decision Making, , vol. 36(6), pages 686-691, August.
    9. Zachary Breig & Paul Feldman, 2024. "Revealing risky mistakes through revisions," Journal of Risk and Uncertainty, Springer, vol. 68(3), pages 227-254, June.
    10. Dafina Petrova & Olga Kostopoulou & Brendan C. Delaney & Edward T. Cokely & Rocio Garcia-Retamero, 2018. "Strengths and Gaps in Physicians’ Risk Communication: A Scenario Study of the Influence of Numeracy on Cancer Screening Communication," Medical Decision Making, , vol. 38(3), pages 355-365, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:40:y:2020:i:6:p:846-853. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.