scholarly journals Research Trends on Factors Influencing the Quality of Life of Cancer Survivors: Text Network Analysis and Topic Modeling Approach

2021 ◽  
Vol 21 (4) ◽  
pp. 231
Author(s):  
Jin-Hee Park ◽  
Mison Chun ◽  
Sun Hyoung Bae ◽  
Hee-Jun Kim
Keyword(s):  
Quality Of Life ◽  
Network Analysis ◽  
Cancer Survivors ◽  
Topic Modeling ◽  
Research Trends ◽  
Modeling Approach ◽  
Factors Influencing ◽  
Text Network Analysis

scholarly journals Research trends related to childhood and adolescent cancer survivors in South Korea using word co-occurrence network analysis

2021 ◽  
Vol 27 (3) ◽  
pp. 201-210
Author(s):  
Kyung-Ah Kang ◽  
Sook Jung Han ◽  
Jiyoung Chun ◽  
Hyun-Yong Kim
Keyword(s):  
Quality Of Life ◽  
Network Analysis ◽  
Cancer Survivors ◽  
Intervention Group ◽  
Research Trends ◽  
Support Needs ◽  
Major Research ◽  
Adolescent Cancer ◽  
Search Terms

Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI).Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling.Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life".Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.

scholarly journals Identification of the Knowledge Structure of Cancer Survivors’ Return to Work and Quality of Life: A Text Network Analysis

2020 ◽  
Vol 17 (24) ◽  
pp. 9368
Author(s):  
Kisook Kim ◽  
Ki-Seong Lee
Keyword(s):  
Quality Of Life ◽  
Network Analysis ◽  
Return To Work ◽  
Cancer Survivors ◽  
Knowledge Structure ◽  
Adolescent And Young Adult ◽  
Young Adult Cancer Survivors ◽  
Adult Cancer Survivors ◽  
Text Network Analysis

This study aimed to understand the trends in research on the quality of life of returning to work (RTW) cancer survivors using text network analysis. Titles and abstracts of each article were examined to extract terms, including “cancer survivors”, “return to work”, and “quality of life”, which were found in 219 articles published between 1990 and June 2020. Python and Gephi software were used to analyze the data and visualize the networks. Keyword ranking was based on the frequency, degree centrality, and betweenness centrality. The keywords commonly ranked at the top included “breast”, “patients”, “rehabilitation”, “intervention”, “treatment”, and “employment”. Clustering results by grouping nodes with high relevance in the network led to four clusters: “participants and method”, “type of research and variables”, “RTW and education in adolescent and young adult cancer survivors”, and “rehabilitation program”. This study provided a visualized overview of the research on cancer survivors’ RTW and quality of life. These findings contribute to the understanding of the flow of the knowledge structure of the existing research and suggest directions for future research.

A systematic review examining factors influencing health related quality of life among melanoma cancer survivors

2016 ◽  
Vol 69 ◽  
pp. 189-198 ◽  
Author(s):  
Jean-Francois Hamel ◽  
Madeline Pe ◽  
Corneel Coens ◽  
Francesca Martinelli ◽  
Alexander M.M. Eggermont ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Cancer Survivors ◽  
Health Related Quality ◽  
Melanoma Cancer ◽  
Factors Influencing ◽  
Related Quality ◽  
Health Related

scholarly journals Contextual factors influencing health-related quality of life in African American and Latina breast cancer survivors

2015 ◽  
Vol 9 (3) ◽  
pp. 441-449 ◽  
Author(s):  
Aria M. Miller ◽  
Kimlin Tam Ashing ◽  
Naomi N. Modeste ◽  
R. Patti Herring ◽  
Diadrey-Anne T. Sealy
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
African American ◽  
Cancer Survivors ◽  
Breast Cancer Survivors ◽  
Health Related Quality ◽  
Factors Influencing ◽  
Related Quality ◽  
Health Related

Factors Influencing Quality of Life in Breast Cancer Survivors Before Beginning Exercise and Recreation Therapy

2011 ◽  
Vol 43 (Suppl 1) ◽  
pp. 819
Author(s):  
Elizabeth S. Evans ◽  
Claudio L. Battaglini ◽  
Diane G. Groff ◽  
Edgar W. Shields ◽  
A. C. Hackney
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Cancer Survivors ◽  
Breast Cancer Survivors ◽  
Recreation Therapy ◽  
Factors Influencing

scholarly journals A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling

2021 ◽  
Vol 27 (2) ◽  
pp. 175-185
Author(s):  
Junglim Lee ◽  
Youngji Kim ◽  
Eunju Kwak ◽  
Seungmi Park
Keyword(s):  
Diabetes Mellitus ◽  
Cardiovascular Disease ◽  
Network Analysis ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Topic Modeling ◽  
Diabetes Management ◽  
Research Trends ◽  
The Past ◽  
Text Network Analysis

Purpose: The aim of this study was to identify core keywords and topic groups in the ‘Gestational diabetes mellitus (GDM) and Breastfeeding’ field of research for better understanding research trends in the past 20 years.Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups.Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', ‘fetus’, ‘hypoglycemia’, 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were ‘cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: ‘cardiovascular disease’, ‘obesity’, ‘complication prevention strategy’, ‘support of breastfeeding’, ‘educational program’ and ‘management of GDM’.Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.

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