IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v38y2018i5p573-583.html
   My bibliography  Save this article

Improving Understanding of Diagnostic Test Outcomes

Author

Listed:
  • Alaina N. Talboy

    (Department of Psychology, University of South Florida, Tampa, FL, USA)

  • Sandra L. Schneider

    (Department of Psychology, University of South Florida, Tampa, FL, USA)

Abstract

Background. Understanding diagnostic test outcomes requires determining the positive predictive value (PPV) of the test, which most laypeople and medical professionals struggle to do. Despite advances found with frequency formats and visual aids, less than 40% of people can typically identify this value. This study tests the impact of using congruent reference classes in problem-question pairings, evaluates the role of numeracy, and assesses how diagnostic value estimates affect the reported likelihood to use the test. Method. A 3 × 2, Pairing (congruent test-focus, congruent condition-focus, incongruent) × Response Format (frequency, percentage) mixed design experiment was conducted, in which participants answered diagnostic questions about 7 medical problems presented in a format focusing either on the reference class of those who test positive or those who have the condition. Answer accuracy, numeracy, and ratings of likelihood to use estimates were assessed. Results. Focusing on the congruent test reference class allowed 87% of participants to consistently identify the PPV, and focusing on the congruent condition reference class led 63% of participants to consistently identify the sensitivity (SEN). Aligning reference classes was especially beneficial for those with lower numeracy, increasing accuracy on problems from 21% for incongruent pairings to 66% for congruent pairings. Ratings of likelihood to use the test were closely tied to participants’ estimates of diagnostic values, regardless of the accuracy of those estimates. Conclusions. Although often overlooked, a straightforward mapping of reference classes from the relevant diagnostic information to the question of interest reduces confusion and substantially increases accuracy in estimates of diagnostic values. These findings can be used to strengthen training in the assessment of uncertainties associated with medical test results.

Suggested Citation

  • Alaina N. Talboy & Sandra L. Schneider, 2018. "Improving Understanding of Diagnostic Test Outcomes," Medical Decision Making, , vol. 38(5), pages 573-583, July.
  • Handle: RePEc:sae:medema:v:38:y:2018:i:5:p:573-583
    DOI: 10.1177/0272989X18758293
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X18758293
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X18758293?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. 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.
    6. 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.
    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:38:y:2018:i:5:p:573-583. 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.