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

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.