Predicting the effectiveness of the online clinical clerkship curriculum: Development of a multivariate prediction model and validation study.
Predicting the effectiveness of the online clinical clerkship curriculum: Development of a multivariate prediction model and validation study.
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DOI：
10.1371/journal.pone.0263182
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
Kikukawa M
中科院分区：
文献类型：
--
作者：
Kuroda N;Suzuki A;Ozawa K;Nagai N;Okuyama Y;Koshiishi K;Yamada M;Kikukawa M
随着科学技术的进步，人们对在线医学教育的期望越来越高。然而，无法预测在线临床实习课程的有效性。为了开发预测模型，我们在日本进行了全国横断面调查。 2020 年 5 月至 6 月和 2021 年 2 月至 3 月期间对日本医学生进行了社交媒体调查。我们使用前者作为推导数据集，后者作为验证数据集。我们向学生询问了三个方面的问题：1）与面对面相比，在线临床见习中从每种教育方法（讲座、医学测验、作业、口头报告、观察医生实践、临床技能实践、参加专业间会议以及与医生互动讨论）中学习的机会，2）在线平台上出现技术问题的频率，以及 3）作为结果衡量标准的满意度和动机。我们在 2020 年 5 月至 6 月期间对 1,671 名医科学生进行的横断面研究中，开发了一个基于满意度和动机的多变量预测模型的评分系统。我们通过 2021 年 2 月至 3 月期间对 106 名医科学生的横断面研究外部验证了该评分，并评估了其预测性能。推导数据集中的最终预测模型包括八个变量（讲座频率、医学测验、口头报告、对医生实践的观察、临床技能实践、参加专业间会议、与医生的互动讨论和技术问题）。我们将使用推导数据集创建的预测模型应用于验证数据集。基于受试者工作特征曲线下面积的预测性能值为满意度 0.69（敏感性 0.50；特异性 0.89）和动机 0.75（敏感性 0.71；特异性 0.85）。我们根据学生的满意度和动机开发了在线临床见习课程有效性的预测模型。我们的模型将准确预测和提高在线临床见习课程的有效性。
Given scientific and technological advancements, expectations of online medical education are increasing. However, there is no way to predict the effectiveness of online clinical clerkship curricula. To develop a prediction model, we conducted cross-sectional national surveys in Japan. Social media surveys were conducted among medical students in Japan during the periods May–June 2020 and February–March 2021. We used the former for the derivation dataset and the latter for the validation dataset. We asked students questions in three areas: 1) opportunities to learn from each educational approach (lectures, medical quizzes, assignments, oral presentations, observation of physicians’ practice, clinical skills practice, participation in interprofessional meetings, and interactive discussions with physicians) in online clinical clerkships compared to face-to-face, 2) frequency of technical problems on online platforms, and 3) satisfaction and motivation as outcome measurements. We developed a scoring system based on a multivariate prediction model for satisfaction and motivation in a cross-sectional study of 1,671 medical students during the period May–June 2020. We externally validated this scoring with a cross-sectional study of 106 medical students during February–March 2021 and assessed its predictive performance. The final prediction models in the derivation dataset included eight variables (frequency of lectures, medical quizzes, oral presentations, observation of physicians’ practice, clinical skills practice, participation in interprofessional meetings, interactive discussions with physicians, and technical problems). We applied the prediction models created using the derivation dataset to a validation dataset. The prediction performance values, based on the area under the receiver operating characteristic curve, were 0.69 for satisfaction (sensitivity, 0.50; specificity, 0.89) and 0.75 for motivation (sensitivity, 0.71; specificity, 0.85). We developed a prediction model for the effectiveness of the online clinical clerkship curriculum, based on students’ satisfaction and motivation. Our model will accurately predict and improve the online clinical clerkship curriculum effectiveness.
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