Kern L, Doherty M E
J Med Educ. 1982 Feb;57(2):100-4. doi: 10.1097/00001888-198202000-00004.
Sixty-five senior medical students chose symptom information that would allow them to assess which of two diagnoses was more appropriate for hypothetical patients. Although Bayes' theorem should have governed their data selection, 83 percent of the subjects did not choose the symptom information required for Bayesian computation. Instead, they showed an overwhelming tendency to seek data relevant to a single disease, while ignoring information related to an equally plausible alternative diagnosis. The tendency for subjects to select diagnostically irrelevant information in such tasks has been labeled "pseudodiagnosticity." The effect result from the difficulty of simultaneously evaluating the relevance of a single symptoms in relation to single diagnosis. Medical educators might incorporate classroom demonstrations of the pseudodiagnosticity effect in order to increase students' accuracy in differential diagnosis.
65名高年级医学生选择了症状信息，以便他们评估两种诊断中哪一种更适合假设的患者。尽管贝叶斯定理本应指导他们的数据选择，但83%的受试者没有选择贝叶斯计算所需的症状信息。相反，他们表现出一种压倒性的倾向，即寻求与单一疾病相关的数据，而忽略与同样合理的替代诊断相关的信息。受试者在这类任务中选择与诊断无关信息的倾向被称为“伪诊断性”。这种效应源于同时评估单一症状与单一诊断相关性的困难。医学教育工作者可能会在课堂上展示伪诊断性效应，以提高学生在鉴别诊断中的准确性。
