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A Network Analysis of Research Topics and Trends in End-of-Life Care and Nursing

Kisook Kim, Seung Gyeong Jang and Ki-Seong Lee
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Kisook Kim: Department of Nursing, Chung-Ang University, Seoul 06974, Korea
Seung Gyeong Jang: College of Nursing, The Catholic University of Korea, Seoul 06649, Korea
Ki-Seong Lee: Da Vinci College of General Education, Chung-Ang University, Seoul 06974, Korea

IJERPH, 2021, vol. 18, issue 1, 1-15

Abstract: This study identified the trends in end-of-life care and nursing through text network analysis. About 18,935 articles published until September 2019 were selected through searches on PubMed, Embase, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. For topic modeling, Latent Dirichlet Allocation (K = 8) was applied. Most of the top ranked topic words for the degree and betweenness centralities were consistent with the top 1% through the semantic network diagram. Among the important keywords examined every five years, “care” was unrivaled. When analyzing the two- and three-word combinations, there were many themes representing places, roles, and actions. As a result of performing topic modeling, eight topics were derived as ethical issues of decision-making for treatment withdrawal, symptom management to improve the quality of life, development of end-of-life knowledge education programs, life-sustaining care plan for elderly patients, home-based hospice, communication experience, patient symptom investigation, and an analysis of considering patient preferences. This study is meaningful as it analyzed a large amount of existing literature and considered the main trends of end-of-life care and nursing research based on the core subject control and semantic structure.

Keywords: text mining; semantics; nursing methodology research; terminal care (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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