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Risk Perception, Prevention And Diagnostic Tests

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  • Johanna Etner
  • Meglena Jeleva

Abstract

The objective of this paper is to study the impact of risk perception and diagnostic information on medical prevention decisions. The intertemporal preferences of individuals are represented by a model of recursive rank dependent utility, which has the advantage of allowing risk perceptions to vary over time and with health status. The main results of the paper are the following. Concerning the impact of risk perception on prevention, two types of pessimists have to be distinguished: the moderate pessimists and the fatalists. Both types overestimate the probability of disease, but the fatalists underestimate the reduction of the disease probability by prevention. Risk perception modification after the occurrence of the disease influences prevention decisions. Indeed, we show that moderate pessimists often choose a high level of primary and tertiary prevention, but a moderate pessimist who becomes fatalist after the occurrence of the disease may choose a high level of primary prevention and a low level of tertiary prevention. Copyright © 2012 John Wiley & Sons, Ltd.

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  • Johanna Etner & Meglena Jeleva, 2013. "Risk Perception, Prevention And Diagnostic Tests," Health Economics, John Wiley & Sons, Ltd., vol. 22(2), pages 144-156, February.
    • Handle: RePEc:wly:hlthec:v:22:y:2013:i:2:p:144-156
    DOI: 10.1002/hec.1822
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    References listed on IDEAS

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    Cited by:

    1. Goldzahl, Léontine, 2017. "Contributions of risk preference, time orientation and perceptions to breast cancer screening regularity," Social Science & Medicine, Elsevier, vol. 185(C), pages 147-157.
    2. BOUCKAERT, Nicolas & SCHOKKAERT, Erik, 2013. "Differing types of medical prevention appeal to different individuals," LIDAM Discussion Papers CORE 2013038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Éric Langlais, 2010. "Les criminels aiment-ils le risque ?," Revue économique, Presses de Sciences-Po, vol. 61(2), pages 263-280.
    4. Emmanuelle Augeraud-Véron & Marc Leandri, 2023. "Optimal self-protection and health risk perception: bridging the gap between risk theory and the Health Belief Model," EconomiX Working Papers 2023-12, University of Paris Nanterre, EconomiX.
    5. Courbage, Christophe & Rey, Béatrice & Treich, Nicolas, 2013. "Prevention and precaution," TSE Working Papers 13-445, Toulouse School of Economics (TSE).
    6. Richard Peter, 2021. "A fresh look at primary prevention for health risks," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1247-1254, May.
    7. Sarah Bensalem, 2020. "Self-insurance and Non-concave Distortion Risk Measures," Working Papers hal-02936349, HAL.
    8. Rapp, Thomas, 2014. "Patients' diagnosis decisions in Alzheimer's disease: The influence of family factors," Social Science & Medicine, Elsevier, vol. 118(C), pages 9-16.
    9. Gabriela Zeller & Matthias Scherer, 2023. "Risk mitigation services in cyber insurance: optimal contract design and price structure," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 502-547, April.
    10. Sarah Bensalem & Nicolás Hernández Santibáñez & Nabil Kazi-Tani, 2019. "Prevention efforts, insurance demand and price incentives under coherent risk measures," Working Papers hal-01983433, HAL.
    11. Bensalem, Sarah & Santibáñez, Nicolás Hernández & Kazi-Tani, Nabil, 2020. "Prevention efforts, insurance demand and price incentives under coherent risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 369-386.
    12. Han Bleichrodt, 2022. "The prevention puzzle," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(2), pages 277-297, September.

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