基于案例学习教学方法在医学统计学教学中实施效果的荟萃分析

The analysis of case-based learning in the teaching effectiveness of medical statistics

目的 运用荟萃分析的方法定量评价基于案例学习（case-based learning,CBL）教学方法和基于讲授学习（lecture-based learning,LBL）教学方法亦称传统教学方法2种教学方法在医学统计学教学中的应用效果.方法 计算机检索中国知网（China National Knowledge Infrastructure,CNKI）、万方数据库、维普数据库中有关基于案例学习教学方法和传统教学方法在我国医学统计学课程中应用的文献,末次检索时间是2016年8月.按照纳入与排除标准筛选文章,提取资料并对纳入的文献进行质量评价后,采用Stata 13.0软件进行荟萃分析.结果 本研究共纳入11篇文献,均采用实验研究方法.其中,实验组即案例教学组涉及1286名学生,对照组即基于讲授学习组涉及1208名学生.实验组学生在期末考试成绩（WMD=3.75,95％CI=2.39 ～5.10,z=5.43,P＜0.001）、综合应用能力测试成绩（WMD=3.72,95％CI=2.37 ～5.06,z =5.43,P＜0.001）、教学方法满意度（RR=1.27,95％CI=1.18 ～1.37,z=6.15,P＜0.001）、统计学学习兴趣（RR=1.32,95％CI-1.20 ～ 1.45,z=5.62,P＜0.001）和统计学学习重要性（RR =1.27,95％CI=1.14～1.43,z =2.49,P=0.013）方面的评分均优于对照组学生.结论 基于案例学习教学方法提高了医学生医学统计学课程的学习兴趣和学习成绩,基于案例学习教学方法在医学统计学课程中的实施效果优于基于讲授学习教学方法.

Objective To quantitatively assess the results of applying case-based learning （CBL） and lecture-based learning （LBL） in medical statistics by using meta-analysis.Methods CNKI,Wanfang database,VIP database were searched for articles on CBL versus LBL in medical statistical education in China,data last updated in August 2016.According to the inclusion and exclusion criteria,the authors extracted data,assessed the quality of included studies and performed a quantitative data synthesis using stata13.0 software.Results Eleven studies （1286 treatments and 1208 controls） were finally included.Compared with LBL,CBL was superior in final exam scores （WMD =3.75,95％ CI =2.39 ～ 5.10,z =5.43,P ＜ 0.001）,comprehensive application ability test score （WMD =3.72,95％ CI =2.37 ～ 5.06,z =5.43,P ＜ 0.001）,the satisfaction degree of teaching methods （RR =1.27,95％ CI =1.18 ～ 1.37,z =6.15,P ＜0.001）,the interest of statistical learning （RR =1.32,95％ CI =1.20 ～ 1.45,z =5.62,P ＜ 0.001）,the importance of statistical learning （RR =1.27,95％ CI =1.14 ～ 1.43,z =2.49,P =0.013）,there were statistical significance.Conclusions The effect of CBL outweighs which of LBL in medical statistics education in China,CBL improved the learning interest and academic performs of medical statistics.