Literature DB >> 26963414

[A Study on the Knowledge Structure of Cancer Survivors based on Social Network Analysis].

Sun Young Kwon1, Ka Ryeong Bae2.   

Abstract

PURPOSE: The purpose of this study was to identify the knowledge structure of cancer survivors.
METHODS: For data, 1099 articles were collected, with 365 keywords as a Noun phrase extracted from the articles and standardized for analyzing. Co-occurrence matrix were generated via a cosine similarity measure, and then the network analysis and visualization using PFNet and NodeXL were applied to visualize intellectual interchanges among keywords.
RESULTS: According to the result of the content analysis and the cluster analysis of author keywords from cancer survivors articles, keywords such as 'quality of life', 'breast neoplasms', 'cancer survivors', 'neoplasms', 'exercise' had a high degree centrality. The 9 most important research topics concerning cancer survivors were 'cancer-related symptoms and nursing', 'cancer treatment-related issues', 'late effects', 'psychosocial issues', 'healthy living managements', 'social supports', 'palliative cares', 'research methodology', and 'research participants'.
CONCLUSION: Through this study, the knowledge structure of cancer survivors was identified. The 9 topics identified in this study can provide useful research direction for the development of nursing in cancer survivor research areas. The Network analysis used in this study will be useful for identifying the knowledge structure and identifying general views and current cancer survivor research trends.

Entities:  

Keywords:  Knowledge; Neoplasms; Social network analysis; Survivors

Mesh:

Year:  2016        PMID: 26963414     DOI: 10.4040/jkan.2016.46.1.50

Source DB:  PubMed          Journal:  J Korean Acad Nurs        ISSN: 2005-3673            Impact factor:   0.984


  3 in total

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

Authors:  Kisook Kim; Seung Gyeong Jang; Ki-Seong Lee
Journal:  Int J Environ Res Public Health       Date:  2021-01-04       Impact factor: 3.390

2.  Network analysis based on big data in social media of Korean adolescents' diet behaviors.

Authors:  JongHwi Song; SooYeun Yoo; JunRyul Yang; SangKyun Yun; YunHee Shin
Journal:  PLoS One       Date:  2022-08-25       Impact factor: 3.752

3.  Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study.

Authors:  Hyun-Yong Kim; Kyung-Ah Kang; Suk-Jung Han; Jiyoung Chun
Journal:  J Med Internet Res       Date:  2022-02-01       Impact factor: 5.428

  3 in total

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