Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022)
Abstract Background As China grapples with rapid demographic shifts due to an aging population, the urgency for innovative aged care policies has intensified. Objective This study addresses a significant research gap by employing a text mining approach based on the Term Frequency-Inverse Document Fr...
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| Format: | Article |
| Language: | English |
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BMC
2025-07-01
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| Series: | BMC Geriatrics |
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| Online Access: | https://doi.org/10.1186/s12877-025-06103-4 |
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| author | Zhihan Liu Hebin Li Ziyan Zhang Lu Ping Wenxin Gu Yuan Yao |
| author_facet | Zhihan Liu Hebin Li Ziyan Zhang Lu Ping Wenxin Gu Yuan Yao |
| author_sort | Zhihan Liu |
| collection | DOAJ |
| description | Abstract Background As China grapples with rapid demographic shifts due to an aging population, the urgency for innovative aged care policies has intensified. Objective This study addresses a significant research gap by employing a text mining approach based on the Term Frequency-Inverse Document Frequency (TF-IDF) method, quantitatively analyzing a broad array of policy documents from 2018 to 2022. Methods It identifies key trends and shifts, using core feature words to construct co-occurrence and heterogeneity matrices analyzed via multidimensional scaling techniques. Results Research results from 2018 to 2022 highlight China’s focus on epidemic prevention, integrated care tailored to Chinese contexts, innovative social security and financial products, and the advancement of smart aged care against a backdrop of multifaceted demands. By analyzing policy changes surrounding significant political events and conducting comparative analysis with previous studies, this study delineates the evolution of policy priorities and anticipates future directions, highlighting the need to integrate advanced technologies and financial mechanisms to strengthen service delivery systems. These adjustments not only meet current demands but also strategically position China to navigate the complexities of an aging society. Conclusions This research provides critical insights for global policymakers facing similar demographic challenges, advocating for a resilient, holistic, and inclusive aged care system. |
| format | Article |
| id | doaj-art-a20f3c4ae46a4d3c87b57b8d8557ee00 |
| institution | Kabale University |
| issn | 1471-2318 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Geriatrics |
| spelling | doaj-art-a20f3c4ae46a4d3c87b57b8d8557ee002025-08-20T03:41:59ZengBMCBMC Geriatrics1471-23182025-07-0125111710.1186/s12877-025-06103-4Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022)Zhihan Liu0Hebin Li1Ziyan Zhang2Lu Ping3Wenxin Gu4Yuan Yao5School of Public Administration, Central South UniversitySchool of Public Administration, Central South UniversitySchool of Public Administration, Central South UniversitySchool of Public Administration, Central South UniversitySchool of Public Administration, Central South UniversityBusiness School, Central South UniversityAbstract Background As China grapples with rapid demographic shifts due to an aging population, the urgency for innovative aged care policies has intensified. Objective This study addresses a significant research gap by employing a text mining approach based on the Term Frequency-Inverse Document Frequency (TF-IDF) method, quantitatively analyzing a broad array of policy documents from 2018 to 2022. Methods It identifies key trends and shifts, using core feature words to construct co-occurrence and heterogeneity matrices analyzed via multidimensional scaling techniques. Results Research results from 2018 to 2022 highlight China’s focus on epidemic prevention, integrated care tailored to Chinese contexts, innovative social security and financial products, and the advancement of smart aged care against a backdrop of multifaceted demands. By analyzing policy changes surrounding significant political events and conducting comparative analysis with previous studies, this study delineates the evolution of policy priorities and anticipates future directions, highlighting the need to integrate advanced technologies and financial mechanisms to strengthen service delivery systems. These adjustments not only meet current demands but also strategically position China to navigate the complexities of an aging society. Conclusions This research provides critical insights for global policymakers facing similar demographic challenges, advocating for a resilient, holistic, and inclusive aged care system.https://doi.org/10.1186/s12877-025-06103-4Aged care policiesPolicy quantificationTF-IDF algorithmMultidimensional scalingPolicy cyclicality comparison |
| spellingShingle | Zhihan Liu Hebin Li Ziyan Zhang Lu Ping Wenxin Gu Yuan Yao Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) BMC Geriatrics Aged care policies Policy quantification TF-IDF algorithm Multidimensional scaling Policy cyclicality comparison |
| title | Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) |
| title_full | Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) |
| title_fullStr | Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) |
| title_full_unstemmed | Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) |
| title_short | Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018–2022) |
| title_sort | transforming aged care in china insights from a tf idf based data mining analysis of national policies 2018 2022 |
| topic | Aged care policies Policy quantification TF-IDF algorithm Multidimensional scaling Policy cyclicality comparison |
| url | https://doi.org/10.1186/s12877-025-06103-4 |
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