Skip Navigation
Skip to contents

RCPHN : Research in Community and Public Health Nursing

OPEN ACCESS
SEARCH
Search
Advanced Search
mobile menu button

Search

Page Path
HOME > Search
2 "Semantics"
Filter
Filter
Article category
Keywords
More +
Publication year
Authors
More +
Original Articles
Co-occurrence Network Analysis of Keywords in Geriatric Frailty
Young Ji Kim, Soong Nang Jang, Jung Lim Lee
J Korean Acad Community Health Nurs. 2018;29(4):429-439.   Published online December 31, 2018
DOI: https://doi.org/10.12799/jkachn.2018.29.4.429
  • 1,631 View
  • 9 Download
  • 3 Citations
AbstractAbstract PDF
PURPOSE
The aim of this study is to identify core keyword of frailty research in the past 35 years to understand the structure of knowledge of frailty.
METHODS
10,367 frailty articles published between 1981 and April 2016 were retrieved from Web of Science. Keywords from these articles were extracted using Bibexcel and social network analysis was conducted with the occurrence network using NetMiner program.
RESULTS
The top five keywords with a high frequency of occurrence include ‘disability’, ‘nursing home’, ‘sarcopenia’, ‘exercise’, and ‘dementia’. Keywords were classified by subheadings of MeSH and the majority of them were included under the healthcare and physical dimensions. The degree centralities of the keywords were arranged in the order of ‘long term care’ (0.55), ‘gait’ (0.42), ‘physical activity’ (0.42), ‘quality of life’ (0.42), and ‘physical performance’ (0.38). The betweenness centralities of the keywords were listed in the order of depression’ (0.32), ‘quality of life’ (0.28), ‘home care’ (0.28), ‘geriatric assessment’ (0.28), and ‘fall’ (0.27). The cluster analysis shows that the frailty research field is divided into seven clusters: aging, sarcopenia, inflammation, mortality, frailty index, older people, and physical activity.
CONCLUSION
After reviewing previous research in the 35 years, it has been found that only physical frailty and frailty related to medicine have been emphasized. Further research in psychological, cognitive, social, and environmental frailty is needed to understand frailty in a multifaceted and integrative manner.

Citations

Citations to this article as recorded by  
  • A content analysis of research on technology use for teaching mathematics to students with disabilities: word networks and topic modeling
    Mikyung Shin, Min Wook Ok, Sam Choo, Gahangir Hossain, Diane P. Bryant, Eunyoung Kang
    International Journal of STEM Education.2023;[Epub]     CrossRef
  • Artificial intelligence in customer relationship management: literature review and future research directions
    Cristina Ledro, Anna Nosella, Andrea Vinelli
    Journal of Business & Industrial Marketing.2022; 37(13): 48.     CrossRef
  • Mining the sociome for Health Informatics: Analysis of therapeutic lifestyle adherence of diabetic patients in Twitter
    Gael Pérez-Rodríguez, Martín Pérez-Pérez, Florentino Fdez-Riverola, Anália Lourenço
    Future Generation Computer Systems.2020; 110: 214.     CrossRef
Text Network Analysis of Newspaper Articles on Life-sustaining Treatments
Eun Jun Park, Dae Woong Ahn, Chan Sook Park
J Korean Acad Community Health Nurs. 2018;29(2):244-256.   Published online June 30, 2018
DOI: https://doi.org/10.12799/jkachn.2018.29.2.244
  • 1,953 View
  • 8 Download
  • 5 Citations
AbstractAbstract PDF
PURPOSE
This study tried to understand discourses of life-sustaining treatments in general daily and healthcare newspapers.
METHODS
A text-network analysis was conducted using the NetMiner program. Firstly, 572 articles from 11 daily newspapers and 258 articles from 8 healthcare newspapers were collected, which were published from August 2013 to October 2016. Secondly, keywords (semantic morphemes) were extracted from the articles and rearranged by removing stop-words, refining similar words, excluding non-relevant words, and defining meaningful phrases. Finally, co-occurrence matrices of the keywords with a frequency of 30 times or higher were developed and statistical measures—indices of degree and betweenness centrality, ego-networks, and clustering—were obtained.
RESULTS
In the general daily and healthcare newspapers, the top eight core keywords were common: “patients,”“death,”“LST (life-sustaining treatments),”“hospice palliative care,”“hospitals,”“family,”“opinion,” and “withdrawal.” There were also common subtopics shared by the general daily and healthcare newspapers: withdrawal of LST, hospice palliative care, National Bioethics Review Committee, and self-determination and proxy decision of patients and family. Additionally, the general daily newspapers included diverse social interest or events like well-dying, euthanasia, and the death of farmer Baek Nam-ki, whereas the healthcare newspapers discussed problems of the relevant laws, and insufficient infrastructure and low reimbursement for hospice-palliative care.
CONCLUSION
The discourse that withdrawal of futile LST should be allowed according to the patient's will was consistent in the newspapers. Given that newspaper articles influence knowledge and attitudes of the public, RNs are recommended to participate actively in public communication on LST.

Citations

Citations to this article as recorded by  
  • Understanding global research trends in the control and prevention of infectious diseases for children: Insights from text mining and topic modeling
    Won‐Oak Oh, Eunji Lee, Yoo‐jin Heo, Myung‐Jin Jung, Jihee Han
    Journal of Nursing Scholarship.2024; 56(4): 606.     CrossRef
  • Images of Nurses Appeared in Media Reports Before and After Outbreak of COVID-19: Text Network Analysis and Topic Modeling
    Min Young Park, Seok Hee Jeong, Hee Sun Kim, Eun Jee Lee
    Journal of Korean Academy of Nursing.2022; 52(3): 291.     CrossRef
  • Identifying the Knowledge Structure and Trends of Outreach in Public Health Care: A Text Network Analysis and Topic Modeling
    Sooyeon Park, Jinkyung Park
    International Journal of Environmental Research and Public Health.2021; 18(17): 9309.     CrossRef
  • Using Text Network Analysis for Analyzing Academic Papers in Nursing
    Chan Sook Park
    Perspectives in Nursing Science.2019; 16(1): 12.     CrossRef
  • Network text analysis of medical tourism in newspapers using text mining: The South Korea case
    Sohyeon Kim, Won Seok Lee
    Tourism Management Perspectives.2019; 31: 332.     CrossRef
RCPHN : Research in Community and Public Health Nursing
Editorial Office
College of Nursing, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
E-mail: office@rcphn.org

© Korean Academy of Community Health Nursing.
TOP