Effect of Teaching Bayesian Methods Using Learning by Concept vs Learning by Example on Medical Students' Ability to Estimate Probability of a Diagnosis A Randomized Clinical Trial
Effect of Teaching Bayesian Methods Using Learning by Concept vs Learning by Example on Medical Students' Ability to Estimate Probability of a Diagnosis A Randomized Clinical Trial
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DOI：
10.1001/jamanetworkopen.2019.18023
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发表时间：
2019-12-01
影响因子：
13.8
通讯作者：
Norman, Geoffrey
中科院分区：
文献类型：
--
作者：
Brush, John E., Jr.;Lee, Mark;Norman, Geoffrey
重要性临床医生使用概率估计来做出诊断。目的探讨临床新手能否通过明确的概念指导或重复举例的教学方法对诊断概率做出更准确的贝叶斯修正。设计、设置和参与者进行了两种贝叶斯更新和诊断推理教学方法的随机临床试验。以网络为基础的平台用于同意、随机、干预和测试干预效果。被试包括从2018年5月1日至9月30日在麦克马斯特大学和东弗吉尼亚医学院招募的61名医学生。干预学生被随机分成：(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)接触关于测试后概率反馈的重复案例(体验组)，或(3)没有概念指导或重复样本的对照条件。对所有3组的学生进行MAIN结果和测量，测试他们根据阴性或阳性测试结果更新诊断概率的能力。结果61名受试者中，22人被分配到概念组，20人被分配给经验组，19人被分配给控制组。年龄约为25岁。两名参与者是一年级的学生，37名二年级的学生，12名三年级的学生和10名四年级的学生。概念组学生的平均(SE)概率估计比其他两组更接近计算的贝叶斯概率(概念，0.4%；[0.7%]；经验，3.5%[0.7%]；对照组，4.3%[0.7%]；P<；.001)。尽管在统计学上有显著差异，但组之间的差异相对较小，根据先前文献中的报告，所有组的学生表现都好于预期。结论和相关性这项研究显示，对于接受贝叶斯概念理论指导的学生来说，这项研究具有一定的优势。所有参与者的概率估计平均接近贝叶斯计算。这些发现对如何向新手临床医生传授诊断推理有一定的启示。
IMPORTANCE 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.OBJECTIVE 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.INTERVENTIONS 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.MAIN OUTCOMES AND MEASURES 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.RESULTS 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.CONCLUSIONS AND RELEVANCE 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.