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Clinical Reasoning Web‐based Prototypic Module for Tutors Teaching 5th Grade Medical Students : A Pilot Randomized Study

机译:基于临床推理的基于网络的原型模块,适用于指导5年级医学生的导师:一项随机试验

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Abstract Background: At present clinical reasoning skills are not systematically taught in Japanese medical universities. We developed a prototypic preliminary module for clinical tutors to introduce clinical reasoning to Japanese medical students. We hypothesized that tutored medical students would outperform self-study students.Method: Using the web-based Sequential Question and Answer test that rewarded history and differential diagnosis as proxies for clinical reasoning, we compared the pre and posttest scores of 12 randomized fifth grade tutored students at two universities during four tutor-led 1.5-hour web-based seminars using a structured syllabus to 12 randomized self-study students.Results: The tutored and self-study groups' pretest scores were statistically similar at about 40 out of 100 weighted correct points. The tutored students' posttest scores were 62 points, significantly greater (p = 0.007) than the pretest mean 42 points, compared to the self-study students' posttest scores of 52 points, significantly greater (p = 0.012) than pretest mean 40 points. The difference between the two posttest groups was of borderline statistical significance (p = 0.08).Conclusions: We successfully assessed a prototypic module for tutors to introduce clinical reasoning to Japanese medical students. The tutored students achieved higher scores than the self-study students. Further research is needed to exploit the potential of our modular clinical reasoning system.
机译:摘要背景:目前,日本医科大学还没有系统地教授临床推理技能。我们为临床导师开发了原型初步模块,以向日本医学生介绍临床推理。方法:使用基于网络的顺序问答实验,对历史和鉴别诊断给予奖励,作为临床推理的代理,我们比较了12个随机的五年级补习生的考试前后成绩。两所大学的学生在四个由教师指导的1.5小时基于网络的研讨会上,使用结构化教学大纲对12个随机的自学学生进行了研究。结果:在100个加权学生中,有40个在授课和自学组的预测成绩在统计学上相似正确点。接受辅导的学生的测验分数为62分,(p = 0.007)比测验前的平均分数高42分,而接受自学的学生的测验的分数为52分,(p = 0.012)比测验前的平均值高40分。 。两组后期测试之间的差异具有统计学显着性差异(p = 0.08)。结论:我们成功地评估了指导老师的原型模块,以向日本医学生介绍临床推理。受辅导的学生比自学的学生得分更高。需要进一步的研究,以开发我们的模块化临床推理系统的潜力。

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