네트워크 분석을 통한 암 생존자 지식구조 연구.
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...
| Publicado en: | Journal of Korean Academy of Nursing Vol. 46; no. 1; pp. 50 - 59 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Korean Society of Nursing Science
2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115590222&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115590222 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 20053673 ATS7 jtl: Journal of Korean Academy of Nursing issn: 20053673 maglogo: N pubinfo: dt: 2016 vid: 46 iid: 1 pid: 42744 pub: Korean Society of Nursing Science place: , <Blank> artinfo: ui: 115590222 115590222 115590222 10.4040/jkan.2016.46.1.50 115590222 ppf: 50 ppct: 9 formats: fmt: @attributes: type: P tig: atl: 네트워크 분석을 통한 암 생존자 지식구조 연구. aug: au: 권선영 배가령 affil: 성균관대학교 정보관리연구소 sug: subj: Cancer Survivors Health Knowledge Social Networks Human Content Analysis Cluster Analysis Quality of Life Support, Psychosocial Serial Publications ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: Korean refInfo: holdings: @attributes: islocal: N |
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