Assessing risk attitudes among physicians, medical students, and non-medical students with experimental data

• We use experimental data to assess the risk attitudes of physicians, medical and non-medical students • Our sample contains 433 participants, distinguished as follows 159 physicians, 232 non-medical students and 42 medical students • Results show significant variation in risk attitude, regardless of the estimation technique employed • The empirical analysis suggests constant relative risk aversion (CRRA) as the supported representation of risk preferences. • Our findings show that physicians are less risk averse in the monetary domain than any other subject type in the sample Recently, laboratory and field experiments have been increasingly used in health economics to predict the behavior of physicians in connection with different payment systems. However, these studies often employ students as decision-makers, assuming that they are a good proxy for the behavior of real physicians, as no qualitative difference between physicians and students’ decisions is often observed. Employing a large sample of experimental data, we investigate whether attitudes toward risk varied significantly between physicians, medical and non-medical students in the monetary domain. The results show significant variation in risk attitude regardless of the estimation technique employed, suggesting constant relative risk aversion as a supported representation of risk preferences. Finally, physicians were less risk-averse than any other participant type in the sample, suggesting that medical risk attitudes differed from other participants, at least in the monetary domain. Given the difficulty in involving real physicians due to their participation barriers, employing medical and non-medical students in experiments is the second-best option. However, researchers must be careful when designing tasks because choices may differ across various contexts. Additionally, policymakers must be cautious when drawing policy implications from laboratory predictions, not taking it for granted that students’ decisions fully match physicians’ decisions.