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Value-Induced Bias in Medical Decision Making

Center for Community-Based Research, Dana-Farber Cancer Institute, Boston, Massachusetts, adg11{at}cornell.edu, Department of Society, Human Development and Health, Harvard School of Public Health, Boston, Massachusetts, Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia

John C. Hershey, PhD

Operations and Information Management Department, The Wharton School, University of Pennsylvania, Philadelphia

Background. People who exhibit value-induced bias— distorting relevant probabilities to justify medical decisions— may make suboptimal decisions. Objective. The authors examined whether and in what conditions people exhibit value-induced bias. Design. Volunteers on the Web imagined having a serious illness with 2 possible diagnoses and a treatment with the same ``small probability'' of success for each diagnosis. The more serious diagnosis was designed as a clear-cut decision to motivate most subjects to choose treatment; the less serious diagnosis was designed to make the treatment a close-call choice. Subjects were randomized to estimate the probability of treatment success before or after learning their diagnosis. The ``after group'' had the motivation and ability to distort the probability of treatment success to justify their treatment preference. In study 1, subjects learned they had the more serious disease. Consistent with value-induced bias, the after group was expected to give higher probability judgments than the ``before group.'' In study 2, subjects learned they had the less serious disease, and the after group was expected to inflate the probability if they desired treatment and to reduce it if they did not, relative to the before group. Results. In study 1, there was no difference in the mean probability judgment between groups, suggesting no distortion of probability. In study 2, the slope of probability judgment regressed on desire for treatment was steeper for the after group, indicating that distortion of probability did occur. Conclusion. In close-call but not clear-cut medical decisions, people may distort relevant probabilities to justify their preferred choices.

Key Words: value-induced bias • cognitive dissonance • subjective probability • risk perception • wishful thinking.

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