Empirical evidence, and the emergence of direct-to-consumer markets for genetic and medical tests, indicate that there is a disconnect between the testing preferences of doctors and patients. To gain insight into this dichotomy, we contrast the testing preferences implied by a normative (expected utility) model with those implied by a behavioral (prospect theory) model that accounts for anticipated emotions (e.g., rejoicing and misery) and probability distortions. Among other findings, we isolate a “reassurance effect” whereby patients will want to test more for severe, hard-to-treat diseases that have a lower probability of occurrence. We also show that probability distortions (as conventionally captured by an inverse S-shaped transformation function) tend to decrease the discrepancy between the testing preferences of doctors and patients. Our analysis also suggests product and promotional tactics for firms operating in the direct-to-consumer testing market. For example, these firms might benefit from introducing less reliable tests (with higher probability of false negative) for severe and less treatable diseases. By highlighting the potential for such manipulative tactics, this research can support further ethical and regulatory discussions.
Jeeva Somasundaram is currently a Postdoctoral Research Fellow in Behavioral Economics at the National University of Singapore. He obtained his PhD in Management (Decision Sciences) from INSEAD, France (2012-16). Jeeva’s research focusses on developing and applying psychologically realistic decision models to solve contemporary real world business and policy problems in high stake domains such as environment and medicine. He uses a variety of techniques such as (axiomatic and analytical) modelling, preference measurement, lab and field experiments for his research. You can find more about him at http://www.jeevasomasundaram.com/.
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