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

BACKGROUND: Being diagnosed with cancer during childhood or adolescence can disrupt important periods in an individual’s physical, psychosocial, and spiritual development and potentially reduce the quality of life (QOL) after treatment. Research is urgently required to improve the QOL for child and...

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Autores principales: Kim, Hyun-Yong, Kang, Kyung-Ah, Han, Suk-Jung, Chun, Jiyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848247/
https://www.ncbi.nlm.nih.gov/pubmed/35103615
http://dx.doi.org/10.2196/32309
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author Kim, Hyun-Yong
Kang, Kyung-Ah
Han, Suk-Jung
Chun, Jiyoung
author_facet Kim, Hyun-Yong
Kang, Kyung-Ah
Han, Suk-Jung
Chun, Jiyoung
author_sort Kim, Hyun-Yong
collection PubMed
description BACKGROUND: Being diagnosed with cancer during childhood or adolescence can disrupt important periods in an individual’s physical, psychosocial, and spiritual development and potentially reduce the quality of life (QOL) after treatment. Research is urgently required to improve the QOL for child and adolescent cancer survivors, and it is necessary to analyze the trends in prior research reported in international academic journals to identify knowledge structures. OBJECTIVE: This study aims to identify the main keywords based on network centrality, subgroups (clusters) of keyword networks by using a cohesion analysis method, and the main theme of child and adolescent cancer survivor–related research abstracts through topic modeling. This study also aims to label the subgroups by comparing the results of the cohesion and topic modeling. METHODS: A text network analysis method and topic modeling were used to explore the main trends in child and adolescent cancer survivor research by structuring a network of keyword (semantic morphemes) co-occurrence in the abstracts of articles published in 5 major web-based databases from 2016 to 2020. A total of 1677 child and adolescent cancer survivor–related studies were used for data analyses. Data selection, processing, and analyses were also conducted. RESULTS: The top 5 keywords in terms of degree and eigenvector centrality were risk, control interval, radiation, childhood cancer treatment, and diagnosis. Of the 1677 studies used for data analyses, cluster 1 included 780 (46.51%) documents under risk management, cluster 2 contained 557 (33.21%) articles under health-related QOL and supportive care, and cluster 3 consisted of 340 (20.27%) studies under cancer treatment and complications. CONCLUSIONS: This study is significant in that it confirms the knowledge structure based on the main keywords and cross-disciplinary trends in child and adolescent cancer survivor research published in the last 5 years worldwide. The primary goal of child and adolescent cancer survivor research is to prevent and manage the various aspects of the problems encountered during the transition to a normal life and to improve the overall QOL. To this end, it is necessary to further revitalize the study of the multidisciplinary team approach for the promotion of age-specific health behaviors and the development of intervention strategies with increased feasibility for child and adolescent cancer survivors.
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spelling pubmed-88482472022-03-10 Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study Kim, Hyun-Yong Kang, Kyung-Ah Han, Suk-Jung Chun, Jiyoung J Med Internet Res Original Paper BACKGROUND: Being diagnosed with cancer during childhood or adolescence can disrupt important periods in an individual’s physical, psychosocial, and spiritual development and potentially reduce the quality of life (QOL) after treatment. Research is urgently required to improve the QOL for child and adolescent cancer survivors, and it is necessary to analyze the trends in prior research reported in international academic journals to identify knowledge structures. OBJECTIVE: This study aims to identify the main keywords based on network centrality, subgroups (clusters) of keyword networks by using a cohesion analysis method, and the main theme of child and adolescent cancer survivor–related research abstracts through topic modeling. This study also aims to label the subgroups by comparing the results of the cohesion and topic modeling. METHODS: A text network analysis method and topic modeling were used to explore the main trends in child and adolescent cancer survivor research by structuring a network of keyword (semantic morphemes) co-occurrence in the abstracts of articles published in 5 major web-based databases from 2016 to 2020. A total of 1677 child and adolescent cancer survivor–related studies were used for data analyses. Data selection, processing, and analyses were also conducted. RESULTS: The top 5 keywords in terms of degree and eigenvector centrality were risk, control interval, radiation, childhood cancer treatment, and diagnosis. Of the 1677 studies used for data analyses, cluster 1 included 780 (46.51%) documents under risk management, cluster 2 contained 557 (33.21%) articles under health-related QOL and supportive care, and cluster 3 consisted of 340 (20.27%) studies under cancer treatment and complications. CONCLUSIONS: This study is significant in that it confirms the knowledge structure based on the main keywords and cross-disciplinary trends in child and adolescent cancer survivor research published in the last 5 years worldwide. The primary goal of child and adolescent cancer survivor research is to prevent and manage the various aspects of the problems encountered during the transition to a normal life and to improve the overall QOL. To this end, it is necessary to further revitalize the study of the multidisciplinary team approach for the promotion of age-specific health behaviors and the development of intervention strategies with increased feasibility for child and adolescent cancer survivors. JMIR Publications 2022-02-01 /pmc/articles/PMC8848247/ /pubmed/35103615 http://dx.doi.org/10.2196/32309 Text en ©Hyun-Yong Kim, Kyung-Ah Kang, Suk-Jung Han, Jiyoung Chun. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 01.02.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Kim, Hyun-Yong
Kang, Kyung-Ah
Han, Suk-Jung
Chun, Jiyoung
Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
title Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
title_full Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
title_fullStr Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
title_full_unstemmed Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
title_short Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
title_sort web-based research trends on child and adolescent cancer survivors over the last 5 years: text network analysis and topic modeling study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848247/
https://www.ncbi.nlm.nih.gov/pubmed/35103615
http://dx.doi.org/10.2196/32309
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