Analysis of pre-course learning situation of postgraduates in the selection of evidence-based medicine course at Peking University Health Science Center

Objective To understand the basic evidence-based knowledge mastery of postgraduates before the course of the network Meta-analysis of Peking University Health Science Center.Methods This study focused on graduate students who attended the Evidence Integration and Application: Network Meta-analysis C...

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Bibliographic Details
Main Authors: ZHANG Meng, LIU Fengqi, WU Shanshan, WU Tao, SUN Feng
Format: Article
Language:zho
Published: Editorial Office of New Medicine 2024-07-01
Series:Yixue xinzhi zazhi
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Online Access:https://yxxz.whuznhmedj.com/futureApi/storage/attach/2407/6mnRGPVvFIUnp9jKnnb63z5fI8FPGYXJse3tE5YM.pdf
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Summary:Objective To understand the basic evidence-based knowledge mastery of postgraduates before the course of the network Meta-analysis of Peking University Health Science Center.Methods This study focused on graduate students who attended the Evidence Integration and Application: Network Meta-analysis Course from 2021 to 2023. Questionnaires were used to assess students' knowledge of network Meta-Analysis and attitudes related to the course, and comparisons were made between master's and doctoral students using the Kruskal-Wallis H test.Results A total of 84 students participated in the survey, including 54 master's students and 30 doctoral students. Students who enrolled in the course had a certain level of competence in literature searching and reading skills before taking the course, with no statistically significant differences between master's and doctoral students (P>0.05). Students had a basic understanding of fundamental course terms, but displayed relative weaknesses in the knowledge of the specific application of Meta-analysis, with proportions ranging from 46.67% to 61.11% of students reporting unfamiliarity with these aspects. Compared to doctoral students, master's students exhibited a reduced comprehension of differences between systematic review and traditional review (P=0.014), and basic steps to implement evidence-based medicine (P
ISSN:1004-5511