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Understanding High-Stakes Consumer Decisions: Mammography Adherence Following False-Alarm Test Results

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  • Barbara E. Kahn

    (The Wharton School, University of Pennsylvania, 3730 Walnut Street, Philadelphia, Pennsylvania 19104)

  • Mary Frances Luce

    (The Wharton School, University of Pennsylvania, 3730 Walnut Street, Philadelphia, Pennsylvania 19104)

Abstract

Consumers often have to decide whether to acquire information in high-stakes decision domains. We study women in mammography waiting rooms to test how a “false-alarm” result (i.e., an indication that a malady is present when a “more accurate” follow-up test reveals it is not) affects willingness to get retested. In Study 1 we show that, given a false-alarm result, life-threatening test consequences are associated with more disutility for future testing than when test consequences are less significant; this does not hold for normal test results. In Study 2 in the mammography context, we show that patients receiving a false-alarm result experienced more stress, were less likely to believe that a positive mammography result indicated cancer, and more likely to delay mammography than patients receiving normal results unless they were also told that they may be vulnerable to breast cancer in the future. We show that delays in planned adherence following a false-alarm result can be mitigated by an information intervention. Finally, we have preliminary evidence that a previous history of false-positive results can cause a consumer to both react more negatively to emotional stress and respond more positively to coping information.

Suggested Citation

  • Barbara E. Kahn & Mary Frances Luce, 2003. "Understanding High-Stakes Consumer Decisions: Mammography Adherence Following False-Alarm Test Results," Marketing Science, INFORMS, vol. 22(3), pages 393-410, April.
  • Handle: RePEc:inm:ormksc:v:22:y:2003:i:3:p:393-410
    DOI: 10.1287/mksc.22.3.393.17737
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    Cited by:

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    2. Freling, Traci H. & Yang, Zhiyong & Saini, Ritesh & Itani, Omar S. & Rashad Abualsamh, Ryan, 2020. "When poignant stories outweigh cold hard facts: A meta-analysis of the anecdotal bias," Organizational Behavior and Human Decision Processes, Elsevier, vol. 160(C), pages 51-67.
    3. Carolina Werle, 2011. "The Determinants of Preventive Health Behavior: Literature Review and Research Perspectives," Working Papers hal-00638266, HAL.
    4. Camacho, N.M.A. & de Jong, M.G. & Stremersch, S., 2014. "The Effect of Customer Empowerment on Adherence to Expert Advice," ERIM Report Series Research in Management ERS-2014-005-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Hanna van Loo, 2010. "More freedom of choice but less preference satisfaction in parametric situations," Rationality and Society, , vol. 22(2), pages 237-252, May.
    6. Nir Douer & Joachim Meyer, 2023. "Quantifying Retrospective Human Responsibility in Intelligent Systems," Papers 2308.01752, arXiv.org.
    7. Carolina Werle, 2011. "The Determinants of Preventive Health Behavior: Literature Review and Research Perspectives," Working paper serie RMT - Grenoble Ecole de Management hal-00638266, HAL.
    8. Burson, Katherine A. & Faro, David & Rottenstreich, Yuval, 2010. "ABCs of principal-agent interactions: Accurate predictions, biased processes, and contrasts between working and delegating," Organizational Behavior and Human Decision Processes, Elsevier, vol. 113(1), pages 1-12, September.
    9. Aaker, Jennifer L. & Lee, Angela Y., 2006. "Understanding Regulatory Fit," Research Papers 1910, Stanford University, Graduate School of Business.
    10. Junbo Son & Yeongin Kim & Shiyu Zhou, 2022. "Alerting patients via health information system considering trust-dependent patient adherence," Information Technology and Management, Springer, vol. 23(4), pages 245-269, December.
    11. Stremersch, Stefan, 2008. "Health and marketing: The emergence of a new field of research," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 229-233.
    12. Yang, Zhiyong & Freling, Traci & Sun, Sijie & Richardson-Greenfield, Pam, 2022. "When do product crises hurt business? A meta-analytic investigation of negative publicity on consumer responses," Journal of Business Research, Elsevier, vol. 150(C), pages 102-120.
    13. Camacho, Nuno & De Jong, Martijn & Stremersch, Stefan, 2014. "The effect of customer empowerment on adherence to expert advice," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 293-308.
    14. Araña, Jorge E. & León, Carmelo J., 2009. "Understanding the use of non-compensatory decision rules in discrete choice experiments: The role of emotions," Ecological Economics, Elsevier, vol. 68(8-9), pages 2316-2326, June.
    15. Adam Duhachek & Anne T. Coughlan & Dawn Iacobucci, 2005. "Results on the Standard Error of the Coefficient Alpha Index of Reliability," Marketing Science, INFORMS, vol. 24(2), pages 294-301, July.
    16. Özge Karanfil & John Sterman, 2020. "“Saving lives or harming the healthy?” Overuse and fluctuations in routine medical screening," System Dynamics Review, System Dynamics Society, vol. 36(3), pages 294-329, July.
    17. Zhiyong Yang & Ritesh Saini & Traci Freling, 2015. "How Anxiety Leads to Suboptimal Decisions Under Risky Choice Situations," Risk Analysis, John Wiley & Sons, vol. 35(10), pages 1789-1800, October.

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