Medical student syndrome: a bayesian reasoning failure
摘要
Medical Student Syndrome (MSS) is often understood as a manifestation of illness anxiety disorder where medical students misinterpret benign symptoms as signs of a serious illness. Current explanations rely heavily on psychological factors; however, these fail to capture the systemic reasoning errors that underly MSS. This paper proposes a mixed model: that MSS results from a combination of the Bayesian reasoning failure of base rate neglect and psychological stressors.
MethodsAn observational cross-sectional study of medical students was conducted
A history of MSS was reported by 56.3% of participants. Diagnostic accuracy was low for both medical scenarios (48.3% correct for differentiating between stroke and migraine; 33.3% for differentiating between pheochromocytoma and panic disorder) and the Bayesian reasoning task (41.1% correct). 71% of students who answered medical questions incorrectly also failed the Bayesian task, suggesting a shared underlying process. 14% of students with a history of MSS answered both questions correctly. Students ranked pathophysiology and symptoms of the presenting complaint as most important in diagnosis, and epidemiology as the least important (mean rank = 8.8/9). Self-analysis of errors showed that most students attributed their mistakes to poor probabilistic reasoning rather than a lack of knowledge.
ConclusionThe findings support the explanation of MSS as partially a statistical reasoning error rather than a purely psychological condition. Training in Bayesian reasoning, integration of epidemiology into diagnostic teaching, and diversification of assessment formats may mitigate MSS and enhance diagnostic accuracy for medical students.