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http://dx.doi.org/10.22650/JKCNR.2019.25.1.80

Research Trends of Articles Published in the Journal of Korean Clinical Nursing Research from 2000 to 2017: Text Network Analysis of Keywords  

Kim, Yeon Hee (Department of Clinical Nursing, University of Ulsan)
Moon, Seong Mi (Department of Nursing, University of Ulsan)
Kwon, In Gak (Graduate School of Clinical Nursing Science, Sungkyunkwan University)
Kim, Kwang Sung (College of Health & Welfare & Nursing, Chungwoon University)
Jeong, Geum Hee (Division of Nursing, Hallym University, Research Institute of Nursing Science)
Shin, Eun Suk (Department of Nursing, Chonnam National University Hospital)
Oh, Hyang Soon (Department of Nursing, Sunchon National University)
Kim, Soo Hyun (Department of Nursing, Inha University)
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Abstract
Purpose: The aim of this study was to identify the research trends of articles published in the Journal of Korean Clinical Nursing Research from 2000 to 2017 by a text network analysis using keywords. Methods: This study analyzed 600 articles. The R program was used for text mining that extracted frequency, centrality rank, and keyword network. Results: From 2000 to 2009, keywords with high-frequency were 'nurse', 'pain', 'anxiety', 'knowledge', 'attitude', and so on. 'Pain', 'nurse', and 'knowledge' showed a high centrality. 'Fatigue' showed no high frequency but a high centrality. Keywords such as 'nurse', 'knowledge', and 'pain' also showed high frequency and centrality between 2010 and 2017. 'Hemodialysis' and 'intensive care unit' were added to keywords with high frequency and centrality during the period. Conclusion: The frequency and centrality of keywords such as 'nurse', 'pain', 'knowledge', 'hemodialysis', and 'intensive care unit' reflect the research trends in clinical nursing between 2000 and 2017. Further studies need to expand the keyword networks by connecting the main keywords.
Keywords
Nursing Research; Clinical Nursing Research; Text Network Analysis; Keyword;
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Times Cited By KSCI : 3  (Citation Analysis)
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