Journal List > J Korean Acad Nurs > v.46(1) > 1003177

Kwon and Bae: A Study on the Knowledge Structure of Cancer Survivors based on Social Network Analysis

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.

Figures and Tables

Figure 1

Change in the number of researches for cancer survivors by year.

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Figure 2

The PFnet(q=n-1, r=∞) visualization of the 365 node co-occurrence network.

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Table 1

Search Queries and Results on Web of Science

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Table 2

Research Journals and Articles about 6 Facets and Queries on Web of Science (N=1,099)

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Table 3

Frequencies of Keywords in 1099 Cancer Survivors Researches (N=6,543)

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rTBC=Triangle betweeness centrality (normalized); Hub/Auth=Hub & authorities; Clu=Cluster.

Notes

CONFLICTS OF INTEREST The authors declared no conflict of interest.

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