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Fuzzy‐Trace Theory, Risk Communication, and Product Labeling in Sexually Transmitted Diseases

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  • Valerie F. Reyna
  • Mary B. Adam

Abstract

Health care professionals are a major source of risk communications, but their estimation of risks may be compromised by systematic biases. We examined fuzzy‐trace theory's predictions of professionals' biases in risk estimation for sexually transmitted infections (STIs) linked to: knowledge deficits (producing underestimation of STI risk, re‐infection, and gender differences), gist‐based mental representation of risk categories (producing overestimation of condom effectiveness for psychologically atypical but prevalent infections), retrieval failure for risk knowledge (producing greater risk underestimation when STIs are not specified), and processing interference involving combining risk estimates (producing biases in post‐test estimation of infection, regardless of knowledge). One‐hundred‐seventy‐four subjects (experts attending a national workshop, physicians, other health care professionals, and students) estimated the risk of teenagers contracting STIs, re‐infection rates for males and females, and condom effectiveness in reducing infection risk. Retrieval was manipulated by asking estimation questions in two formats, a specific format that “unpacked” the STI category (infection types) and a global format that did not provide specific cues. Requesting estimates of infection risk after relevant knowledge was directly provided, isolating processing effects, assessed processing biases. As predicted, all groups of professionals underestimated the risk of STI transmission, re‐infection, and gender differences, and overestimated the effectiveness of condoms, relative to published estimates. However, when questions provided better retrieval supports (specified format), estimation bias decreased. All groups of professionals also suffered from predicted processing biases. Although knowledge deficits contribute to estimation biases, the research showed that biases are also linked to fuzzy representations, retrieval failures, and processing errors. Hence, interventions that are designed to improve risk perception among professionals must incorporate more than knowledge dissemination. They should also provide support for information representation, effective retrieval, and accurate processing.

Suggested Citation

  • Valerie F. Reyna & Mary B. Adam, 2003. "Fuzzy‐Trace Theory, Risk Communication, and Product Labeling in Sexually Transmitted Diseases," Risk Analysis, John Wiley & Sons, vol. 23(2), pages 325-342, April.
  • Handle: RePEc:wly:riskan:v:23:y:2003:i:2:p:325-342
    DOI: 10.1111/1539-6924.00332
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    References listed on IDEAS

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    1. Valerie F. Reyna & Allan J. Hamilton, 2001. "The Importance of Memory in Informed Consent for Surgical Risk," Medical Decision Making, , vol. 21(2), pages 152-155, April.
    2. Rosenberg, M.J. & Davidson, A.J. & Chen, J.-H. & Judson, F.N. & Douglas, J.M., 1992. "Barrier contraceptives and sexually transmitted diseases in women: A comparison of female-dependent methods and condoms," American Journal of Public Health, American Public Health Association, vol. 82(5), pages 669-674.
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    Cited by:

    1. Claire M. White & Michaela Gummerum & Yaniv Hanoch, 2015. "Adolescents’ and Young Adults’ Online Risk Taking: The Role of Gist and Verbatim Representations," Risk Analysis, John Wiley & Sons, vol. 35(8), pages 1407-1422, August.
    2. Emily A. Elstad & Anne Sutkowi-Hemstreet & Stacey L. Sheridan & Maihan Vu & Russell Harris & Valerie F. Reyna & Christine Rini & Jo Anne Earp & Noel T. Brewer, 2015. "Clinicians’ Perceptions of the Benefits and Harms of Prostate and Colorectal Cancer Screening," Medical Decision Making, , vol. 35(4), pages 467-476, May.
    3. David A. Broniatowski & Valerie F. Reyna, 2020. "To illuminate and motivate: a fuzzy-trace model of the spread of information online," Computational and Mathematical Organization Theory, Springer, vol. 26(4), pages 431-464, December.
    4. Deniz Marti & David A. Broniatowski, 2020. "Does gist drive NASA experts’ design decisions?," Systems Engineering, John Wiley & Sons, vol. 23(4), pages 460-479, July.

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