Cargando…
Analyzing Community Care Research Trends Using Text Mining
PURPOSE: This study utilized text mining to analyze research trends around community care, which focuses on improving patients’ quality of life by lessening the financial burden on caregivers and relieving patient discomfort. METHODS: To examine research trends by community care stage, Section 1 is...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297196/ https://www.ncbi.nlm.nih.gov/pubmed/35873091 http://dx.doi.org/10.2147/JMDH.S366726 |
_version_ | 1784750423737892864 |
---|---|
author | Park, Yoonseo Park, Sewon Lee, Munjea |
author_facet | Park, Yoonseo Park, Sewon Lee, Munjea |
author_sort | Park, Yoonseo |
collection | PubMed |
description | PURPOSE: This study utilized text mining to analyze research trends around community care, which focuses on improving patients’ quality of life by lessening the financial burden on caregivers and relieving patient discomfort. METHODS: To examine research trends by community care stage, Section 1 is set from 2017 to 2019, when the community care was implemented, and Section 2 from 2020 to 2021, after the end of the community care. Papers used for the analysis were extracted using the Korea Citation Index (KCI); a total of 132 articles were selected and subjected to text mining analysis. RESULTS: First, the main community care research areas included work, housing, economy, disability, and mind. Second, from 2017 to 2019, there was considerable interest in community care centered on households, and main keywords, such as nursing, family, and experience, appeared. Third, from 2020 to the present, there was high interest in community care centered on disabilities, and keywords, such as space, business, and Seoul City, appeared. CONCLUSION: The results reveal the changing issues, with the implementation of community care. Overall, research has tended to focus on social and welfare systems, rather than health and medical systems. In the future, local, community-integrated health and medical care systems should be restructured and regional delivery systems established to make them more accessible. |
format | Online Article Text |
id | pubmed-9297196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-92971962022-07-21 Analyzing Community Care Research Trends Using Text Mining Park, Yoonseo Park, Sewon Lee, Munjea J Multidiscip Healthc Original Research PURPOSE: This study utilized text mining to analyze research trends around community care, which focuses on improving patients’ quality of life by lessening the financial burden on caregivers and relieving patient discomfort. METHODS: To examine research trends by community care stage, Section 1 is set from 2017 to 2019, when the community care was implemented, and Section 2 from 2020 to 2021, after the end of the community care. Papers used for the analysis were extracted using the Korea Citation Index (KCI); a total of 132 articles were selected and subjected to text mining analysis. RESULTS: First, the main community care research areas included work, housing, economy, disability, and mind. Second, from 2017 to 2019, there was considerable interest in community care centered on households, and main keywords, such as nursing, family, and experience, appeared. Third, from 2020 to the present, there was high interest in community care centered on disabilities, and keywords, such as space, business, and Seoul City, appeared. CONCLUSION: The results reveal the changing issues, with the implementation of community care. Overall, research has tended to focus on social and welfare systems, rather than health and medical systems. In the future, local, community-integrated health and medical care systems should be restructured and regional delivery systems established to make them more accessible. Dove 2022-07-15 /pmc/articles/PMC9297196/ /pubmed/35873091 http://dx.doi.org/10.2147/JMDH.S366726 Text en © 2022 Park et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Park, Yoonseo Park, Sewon Lee, Munjea Analyzing Community Care Research Trends Using Text Mining |
title | Analyzing Community Care Research Trends Using Text Mining |
title_full | Analyzing Community Care Research Trends Using Text Mining |
title_fullStr | Analyzing Community Care Research Trends Using Text Mining |
title_full_unstemmed | Analyzing Community Care Research Trends Using Text Mining |
title_short | Analyzing Community Care Research Trends Using Text Mining |
title_sort | analyzing community care research trends using text mining |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297196/ https://www.ncbi.nlm.nih.gov/pubmed/35873091 http://dx.doi.org/10.2147/JMDH.S366726 |
work_keys_str_mv | AT parkyoonseo analyzingcommunitycareresearchtrendsusingtextmining AT parksewon analyzingcommunitycareresearchtrendsusingtextmining AT leemunjea analyzingcommunitycareresearchtrendsusingtextmining |