DxR Clinician结合SP在医学生临床思维教学中的应用
The Application of DxR Clinical Combined with SP in Clinical Thinking Teaching for Medical Students
陈喜 1阮国竹 1胡海岩1
作者信息
- 1. 海南医学院临床技能实验教学中心 海南 海口 571199
- 折叠
摘要
目的:探讨DxR Clinician虚拟教学结合标准化病人的教学方法在医学生临床思维教学中的应用效果.方法:选取海南医学院2020级临床新医科(1)班和(2)班,分为试验组和对照组,分别采用基于DxR Clinician虚拟教学结合标准化病人教学法和标准化病人教学法,通过临床思维能力、医患沟通能力、心理状态来评价教学效果.结果:试验组学生的临床思维能力、医患沟通能力得分高于对照组;自我感知心理状态得分低于对照组.结论:DxR Clinician虚拟教学结合标准化病人教学方法,适用于三年级临床医学本科生诊断学教学,可有效地培养学生的问诊、临床思维能力,提升医患沟通能力、减轻学生医患沟通时的心理压力,值得在以后的教学中进一步推广使用.
Abstract
Objective:To explore the application effect of DxR Clinical virtual teaching combined with standardized patient teaching methods in clinical thinking teaching for medical students.Method:Class 1 and Class 2 of the 2020 Clinical New Medical Department of Hainan Medical College were selected and divided into an experimental group and a control group.The teaching effects were evaluated based on clinical thinking ability,doctor-patient communication ability,and psychological state using DxR Clinical virtual teaching combined with standardized patient teaching method and standardized patient teaching method,respectively.Result:The clinical thinking ability and doctor-patient communication ability scores of the experimental group students were higher than those of the control group;The self perceived psychological state score was lower than that of the control group.Conclusion:The combination of DxR Clinical virtual teaching and standardized patient teaching methods is suitable for the diagnosis teaching of third grade clinical medical undergraduate students.It can effectively cultivate students'questioning and clinical thinking abilities,improve doctor-patient communication skills,and reduce psychological pressure during doctor-patient communication.It is worth further promoting and using in future teaching.
关键词
DxR/Clinician/虚拟教学/标准化病人/临床思维Key words
DxR Clinic/virtual teaching/standardized patients/clinical thinking引用本文复制引用
基金项目
2022年海南医学院教改项目(HYYB202225)
2023年海南省教育厅高等学校教育教学改革研究项目(HNJG2023-76)
出版年
2024
NETL
NSTL
万方数据