Background: Quite often medical students or novice residents have difficulty in ruling out diseases even though they are quite unlikely and, due to this difficulty, such students and novice residents unnecessarily repeat laboratory or imaging tests.
Objective: To explore whether or not a carefully designed short training course teaching Bayesian probabilistic thinking improves the diagnostic ability of medical students.
Participants and methods: Ninety students at 2 medical schools were presented with clinical scenarios of coronary artery disease corresponding to high, low, and intermediate pretest probabilities. The students' estimates of test characteristics of exercise stress test, and pretest and posttest probability for each scenario were evaluated before and after the short course.
Results: The pretest probability estimates by the students, as well as their proficiency in applying Bayes's theorem, were improved in the high pretest probability scenario after the short course. However, estimates of pretest probability in the low pretest probability scenario, and their proficiency in applying Bayes's theorem in the intermediate and low pretest probability scenarios, showed essentially no improvement.
Conclusion: A carefully designed, but traditionally administered, short course could not improve the students' abilities in estimating pretest probability in a low pretest probability setting, and subsequently students remained incompetent in ruling out disease. We need to develop educational methods that cultivate a well-balanced clinical sense to enable students to choose a suitable diagnostic strategy as needed in a clinical setting without being one-sided to the "rule-in conscious paradigm."