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Research topics and trends in medical education by social network analysis

机译:社会网络分析的医学教育研究主题与趋势

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As studies analyzing the networks and relational structures of research topics in academic fields emerge, studies that apply methods of network and relationship analysis, such as social network analysis (SNA), are drawing more attention. The purpose of this study is to explore the interaction of medical education subjects in the framework of complex systems theory using SNA and to analyze the trends in medical education. The authors extracted keywords using Medical Subject Headings terms from 9,379 research articles (162,866 keywords) published in 1963–2015 in PubMed. They generated an occurrence frequency matrix, calculated relatedness using Weighted Jaccard Similarity, and analyzed and visualized the networks with Gephi software. Newly emerging topics by period units were identified as historical trends, and 20 global-level topic clusters were obtained through network analysis. A time-series analysis led to the definition of five historical periods: the waking phase (1963–1975), the birth phase (1976–1990), the growth phase (1991–1996), the maturity phase (1997–2005), and the expansion phase (2006–2015). The study analyzed the trends in medical education research using SNA and analyzed their meaning using complex systems theory. During the 53-year period studied, medical education research has been subdivided and has expanded, improved, and changed along with shifts in society’s needs. By analyzing the trends in medical education using the conceptual framework of complex systems theory, the research team determined that medical education is forming a sense of the voluntary order within the field of medicine by interacting with social studies, philosophy, etc., and establishing legitimacy and originality.
机译:随着分析学术领域的研究主题的网络和关系结构的研究的兴起,应用网络和关系分析方法(例如社交网络分析(SNA))的研究日益受到关注。这项研究的目的是在使用SNA的复杂系统理论框架内探索医学教育学科之间的互动,并分析医学教育的趋势。作者使用医学主题词从1963–2015年在PubMed中发表的9,379篇研究文章(162,866个关键词)中提取了关键词。他们生成了一个出现频率矩阵,使用加权Jaccard相似度计算了相关性,并使用Gephi软件对网络进行了分析和可视化。按时期单位确定的新出现的主题被确定为历史趋势,并且通过网络分析获得了20个全球级别的主题集群。时间序列分析得出了五个历史时期的定义:清醒阶段(1963–1975),出生阶段(1976–1990),成长阶段(1991–1996),成熟阶段(1997–2005),扩张阶段(2006-2015年)。该研究使用SNA分析了医学教育研究的趋势,并使用复杂系统理论分析了它们的意义。在经过53年的研究期间,医学教育研究随着社会需求的变化而细分,并得到了扩展,改进和变化。通过使用复杂系统理论的概念框架分析医学教育的趋势,研究团队确定医学教育正在通过与社会研究,哲学等互动并建立合法性来形成医学领域的自愿秩序意识和独创性。

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