KMID : 1004620190250010080
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Clinical Nursing Research 2019 Volume.25 No. 1 p.80 ~ p.90
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Research Trends of Articles Published in the Journal of Korean Clinical Nursing Research from 2000 to 2017: Text Network Analysis of Keywords
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Kim Yeon-Hee
Moon Seong-Mi Kwon In-Gak Kim Kwang-Sung Jeong Geum-Hee Shin Eun-Suk Oh Hyang-Soon Kim Soo-Hyun
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Abstract
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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.
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KEYWORD
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Nursing Research, Clinical Nursing Research, Text Network Analysis, Keyword
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