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http://dx.doi.org/10.14408/KJEMS.2022.26.2.019

Identifying research trends in the emergency medical technician field using topic modeling  

Lee, Jung Eun (Department of Emergency Medical Technology, Dongnam Health University)
Kim, Moo-Hyun (Department of Emergency Medical Technology, Dongnam Health University)
Publication Information
The Korean Journal of Emergency Medical Services / v.26, no.2, 2022 , pp. 19-35 More about this Journal
Abstract
Purpose: This study aimed to identify research topics in the emergency medical technician (EMT) field and examine research trends. Methods: In this study, 261 research papers published between January 2000 and May 2022 were collected, and EMT research topics and trends were analyzed using topic modeling techniques. This study used a text mining technique and was conducted using data collection flow, keyword preprocessing, and analysis. Keyword preprocessing and data analysis were done with the RStudio Version 4.0.0 program. Results: Keywords were derived through topic modeling analysis, and eight topics were ultimately identified: patient treatment, various roles, the performance of duties, cardiopulmonary resuscitation, triage systems, job stress, disaster management, and education programs. Conclusion: Based on the research results, it is believed that a study on the development and application of education programs that can successfully increase the emergency care capabilities of EMTs is needed.
Keywords
EMT; Topic modeling; Text mining; Research trend;
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Times Cited By KSCI : 8  (Citation Analysis)
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