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Research topics and trends in medical education by social network analysis
BACKGROUND: 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 intera...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6154904/ https://www.ncbi.nlm.nih.gov/pubmed/30249248 http://dx.doi.org/10.1186/s12909-018-1323-y |
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author | Ji, Young A Nam, Se Jin Kim, Hong Gee Lee, Jaeil Lee, Soo-Kyoung |
author_facet | Ji, Young A Nam, Se Jin Kim, Hong Gee Lee, Jaeil Lee, Soo-Kyoung |
author_sort | Ji, Young A |
collection | PubMed |
description | BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12909-018-1323-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6154904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61549042018-09-26 Research topics and trends in medical education by social network analysis Ji, Young A Nam, Se Jin Kim, Hong Gee Lee, Jaeil Lee, Soo-Kyoung BMC Med Educ Research Article BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12909-018-1323-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-24 /pmc/articles/PMC6154904/ /pubmed/30249248 http://dx.doi.org/10.1186/s12909-018-1323-y Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Ji, Young A Nam, Se Jin Kim, Hong Gee Lee, Jaeil Lee, Soo-Kyoung Research topics and trends in medical education by social network analysis |
title | Research topics and trends in medical education by social network analysis |
title_full | Research topics and trends in medical education by social network analysis |
title_fullStr | Research topics and trends in medical education by social network analysis |
title_full_unstemmed | Research topics and trends in medical education by social network analysis |
title_short | Research topics and trends in medical education by social network analysis |
title_sort | research topics and trends in medical education by social network analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6154904/ https://www.ncbi.nlm.nih.gov/pubmed/30249248 http://dx.doi.org/10.1186/s12909-018-1323-y |
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