ArticleBMC medical education2018
Research topics and trends in medical education by social network analysis.
Article in BMC medical education, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 43 citations in OpenAlex.
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- A Medical Education Research Library: key research topics and associated experts.Medical education online · 2024Article
- The Impact of the Dermal Matrix in Tissue Reconstruction: A Bibliometric Perspective in Plastic Surgery.Journal of functional biomaterials · 2024Review
- Data Analysis of Physician Competence Research Trend: Social Network Analysis and Topic Modeling Approach.JMIR medical informatics · 2023Article
- Bibliometric Analysis for Medical Research.Indian journal of psychological medicine · 2023Article
- Network analysis for estimating standardization trends in genomics using MEDLINE.BMC medical research methodology · 2022Article
- Using theory in health professions education research: a guide for early career researchers.BMC medical education · 2022Article
- A step-by-step guide to creating an academic surgery interest group: Review article.Annals of medicine and surgery (2012) · 2021Review
- Visualization of clinical teaching citations using social network analysis.BMC medical education · 2021Article
- A Network Analysis of Research Topics and Trends in End-of-Life Care and Nursing.International journal of environmental research and public health · 2021Article
- Identification of the Knowledge Structure of Cancer Survivors' Return to Work and Quality of Life: A Text Network Analysis.International journal of environmental research and public health · 2020Article
- Diversity in health professional education scholarship: a document analysis of international author representation in leading journals.BMJ open · 2020Article
- TextRank-based healthcare big data analysis system for text network analysis and trend phase identification.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundAs 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.
methodsThe 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.
resultsNewly 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).
conclusionsThe 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.