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基于游戏的学习来提高诊断准确性:一个试点随机对照试验

Daniel J Morgan^1,2, Laura Scherer^3,4,5, Lisa Pineles¹

¹Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA.

Diagnosis (Berlin, Germany)

|January 29, 2024

概括

在线基于游戏的学习 (GBL) 显著提高了医疗专业人员的诊断准确性. 这种教育方法显示了长达三个月的持久效果,增强了诊断推理技能.

科学领域:

医学教育医学教育
诊断推理诊断推理
数字学习技术数字学习技术

背景情况:

诊断推理是临床医生的关键技能.
传统的医学教育方法可能无法完全优化诊断技能的发展.
需要创新的方法来加强临床决策.

研究的目的:

评估基于游戏的在线学习 (GBL) 对改善诊断推理的有效性.
用自然频率和反来评估GBL的影响.
在一组多元化的医疗专业人员中进行试点研究.

主要方法:

一个多中心随机对照试验,将在线GBL与传统教育进行比较.
参与者包括医学学生,住院医生,医生和护士执业人员.
诊断准确度是使用现实的病例简介来衡量的.

主要成果:

与对照组相比,GBL组在训练后立即显示出明显更高的诊断准确度得分 (59.4比37.6,p=0.0005).
在GBL组中,在1个月和3个月的随访中,准确度的提高仍然存在.
大多数参与者发现GBL令人愉快,并推它,认为它改善了测试解释.

结论:

一次基于在线游戏的单一学习会话大大提高了医疗学员和执业临床医生的诊断准确度.
GBL对诊断推理技能的积极影响持续了三个月.
GBL代表了增强临床诊断能力的有希望的工具.

关键词:

医学诊断医学诊断医学诊断医学教育医学教育基于游戏的在线学习.

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