Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach

BackgroundStudies on competency in medical education often explore the acquisition, performance, and evaluation of particular skills, knowledge, or behaviors that constitute physician competency. As physician competency reflects social demands according to changes in the medi...

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Main Authors: So Jung Yune, Youngjon Kim, Jea Woog Lee
Format: Article
Language:English
Published: JMIR Publications 2023-07-01
Series:JMIR Medical Informatics
Online Access:https://medinform.jmir.org/2023/1/e47934
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author So Jung Yune
Youngjon Kim
Jea Woog Lee
author_facet So Jung Yune
Youngjon Kim
Jea Woog Lee
author_sort So Jung Yune
collection DOAJ
description BackgroundStudies on competency in medical education often explore the acquisition, performance, and evaluation of particular skills, knowledge, or behaviors that constitute physician competency. As physician competency reflects social demands according to changes in the medical environment, analyzing the research trends of physician competency by period is necessary to derive major research topics for future studies. Therefore, a more macroscopic method is required to analyze the core competencies of physicians in this era. ObjectiveThis study aimed to analyze research trends related to physicians’ competency in reflecting social needs according to changes in the medical environment. MethodsWe used topic modeling to identify potential research topics by analyzing data from studies related to physician competency published between 2011 and 2020. We preprocessed 1354 articles and extracted 272 keywords. ResultsThe terms that appeared most frequently in the research related to physician competency since 2010 were knowledge, hospital, family, job, guidelines, management, and communication. The terms that appeared in most studies were education, model, knowledge, and hospital. Topic modeling revealed that the main topics about physician competency included Evidence-based clinical practice, Community-based healthcare, Patient care, Career and self-management, Continuous professional development, and Communication and cooperation. We divided the studies into 4 periods (2011-2013, 2014-2016, 2017-2019, and 2020-2021) and performed a linear regression analysis. The results showed a change in topics by period. The hot topics that have shown increased interest among scholars over time include Community-based healthcare, Career and self-management, and Continuous professional development. ConclusionsOn the basis of the analysis of research trends, it is predicted that physician professionalism and community-based medicine will continue to be studied in future studies on physician competency.
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spelling doaj.art-1fbafe27cca64d9e8349e0971c89365d2023-08-29T00:04:50ZengJMIR PublicationsJMIR Medical Informatics2291-96942023-07-0111e4793410.2196/47934Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling ApproachSo Jung Yunehttps://orcid.org/0000-0002-2567-0444Youngjon Kimhttps://orcid.org/0000-0002-0445-526XJea Woog Leehttps://orcid.org/0000-0001-8112-407X BackgroundStudies on competency in medical education often explore the acquisition, performance, and evaluation of particular skills, knowledge, or behaviors that constitute physician competency. As physician competency reflects social demands according to changes in the medical environment, analyzing the research trends of physician competency by period is necessary to derive major research topics for future studies. Therefore, a more macroscopic method is required to analyze the core competencies of physicians in this era. ObjectiveThis study aimed to analyze research trends related to physicians’ competency in reflecting social needs according to changes in the medical environment. MethodsWe used topic modeling to identify potential research topics by analyzing data from studies related to physician competency published between 2011 and 2020. We preprocessed 1354 articles and extracted 272 keywords. ResultsThe terms that appeared most frequently in the research related to physician competency since 2010 were knowledge, hospital, family, job, guidelines, management, and communication. The terms that appeared in most studies were education, model, knowledge, and hospital. Topic modeling revealed that the main topics about physician competency included Evidence-based clinical practice, Community-based healthcare, Patient care, Career and self-management, Continuous professional development, and Communication and cooperation. We divided the studies into 4 periods (2011-2013, 2014-2016, 2017-2019, and 2020-2021) and performed a linear regression analysis. The results showed a change in topics by period. The hot topics that have shown increased interest among scholars over time include Community-based healthcare, Career and self-management, and Continuous professional development. ConclusionsOn the basis of the analysis of research trends, it is predicted that physician professionalism and community-based medicine will continue to be studied in future studies on physician competency.https://medinform.jmir.org/2023/1/e47934
spellingShingle So Jung Yune
Youngjon Kim
Jea Woog Lee
Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach
JMIR Medical Informatics
title Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach
title_full Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach
title_fullStr Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach
title_full_unstemmed Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach
title_short Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach
title_sort data analysis of physician competence research trend social network analysis and topic modeling approach
url https://medinform.jmir.org/2023/1/e47934
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