Cardiology Division, Department of Internal Medicine, Eastern Virginia Medical School, Sentara Healthcare, Norfolk.
McMaster Education Research, Innovation and Theory Program, McMaster University, Hamilton, Ontario, Canada.
JAMA Netw Open. 2019 Dec 2;2(12):e1918023. doi: 10.1001/jamanetworkopen.2019.18023.
Clinicians use probability estimates to make a diagnosis. Teaching students to make more accurate probability estimates could improve the diagnostic process and, ultimately, the quality of medical care.
To test whether novice clinicians can be taught to make more accurate bayesian revisions of diagnostic probabilities using teaching methods that apply either explicit conceptual instruction or repeated examples.
DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial of 2 methods for teaching bayesian updating and diagnostic reasoning was performed. A web-based platform was used for consent, randomization, intervention, and testing of the effect of the intervention. Participants included 61 medical students at McMaster University and Eastern Virginia Medical School recruited from May 1 to September 30, 2018.
Students were randomized to (1) receive explicit conceptual instruction regarding diagnostic testing and bayesian revision (concept group), (2) exposure to repeated examples of cases with feedback regarding posttest probability (experience group), or (3) a control condition with no conceptual instruction or repeated examples.
Students in all 3 groups were tested on their ability to update the probability of a diagnosis based on either negative or positive test results. Their probability revisions were compared with posttest probability revisions that were calculated using the Bayes rule and known test sensitivity and specificity.
Of the 61 participants, 22 were assigned to the concept group, 20 to the experience group, and 19 to the control group. Approximate age was 25 years. Two participants were first-year; 37, second-year; 12, third-year; and 10, fourth-year students. Mean (SE) probability estimates of students in the concept group were statistically significantly closer to calculated bayesian probability than the other 2 groups (concept, 0.4%; [0.7%]; experience, 3.5% [0.7%]; control, 4.3% [0.7%]; P < .001). Although statistically significant, the differences between groups were relatively modest, and students in all groups performed better than expected, based on prior reports in the literature.
The study showed a modest advantage for students who received theoretical instruction on bayesian concepts. All participants' probability estimates were, on average, close to the bayesian calculation. These findings have implications for how to teach diagnostic reasoning to novice clinicians.
ClinicalTrials.gov identifier: NCT04130607.
临床医生使用概率估计值来做出诊断。教授学生如何更准确地进行贝叶斯概率修正，可以改善诊断过程，并最终提高医疗质量。
测试使用应用明确概念指导或重复示例的教学方法，是否可以教授新手临床医生更准确地进行贝叶斯诊断概率修正。
设计、设置和参与者：一项比较 2 种贝叶斯更新和诊断推理教学方法的随机临床试验。一个基于网络的平台用于同意、随机分组、干预和测试干预效果。参与者包括 2018 年 5 月 1 日至 9 月 30 日从麦克马斯特大学和东弗吉尼亚医学院招募的 61 名医学生。
学生被随机分配到（1）接受关于诊断测试和贝叶斯修正的明确概念指导（概念组），（2）暴露于带有反馈的案例重复示例，了解后测概率（经验组），或（3）没有概念指导或重复示例的对照组。
所有 3 组的学生都接受了基于阴性或阳性测试结果更新诊断概率的能力测试。将他们的概率修正与使用贝叶斯规则和已知测试灵敏度和特异性计算的后测概率修正进行比较。
在 61 名参与者中，22 名被分配到概念组，20 名被分配到经验组，19 名被分配到对照组。大致年龄为 25 岁。有 2 名参与者是一年级学生；37 名是二年级学生；12 名是三年级学生；10 名是四年级学生。概念组学生的平均（SE）概率估计值与其他两组（概念组为 0.4%[0.7%]；经验组为 3.5%[0.7%]；对照组为 4.3%[0.7%]）相比，统计学上更接近贝叶斯概率，差异有统计学意义（P < 0.001）。尽管统计学上有显著差异，但组间差异相对较小，而且所有组的学生的表现都优于文献中的预期。
该研究表明，接受贝叶斯概念理论指导的学生具有适度优势。所有参与者的概率估计值平均接近贝叶斯计算值。这些发现对如何向新手临床医生教授诊断推理具有启示意义。
ClinicalTrials.gov 标识符：NCT04130607。
