A computational grounded theory based analysis of research on China's old-age social welfare system.
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| Titel: | A computational grounded theory based analysis of research on China's old-age social welfare system. |
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| Autoren: | Agudamu; Graduate School of Social Welfare, Sungkyunkwan University, Seoul, Republic of Korea., Li Y; College of Physical Education, Hunan Normal University, Changsha, China., Mi N; College of Physical Education, Hunan Normal University, Changsha, China., Pan X; College of Physical Education, China University of Mining and Technology, Xuzhou, China. |
| Quelle: | Frontiers in public health [Front Public Health] 2025 Apr 28; Vol. 13, pp. 1556302. Date of Electronic Publication: 2025 Apr 28 (Print Publication: 2025). |
| Publikationsart: | Journal Article; Systematic Review |
| Sprache: | English |
| Info zur Zeitschrift: | Publisher: Frontiers Editorial Office Country of Publication: Switzerland NLM ID: 101616579 Publication Model: eCollection Cited Medium: Internet ISSN: 2296-2565 (Electronic) Linking ISSN: 22962565 NLM ISO Abbreviation: Front Public Health Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Lausanne : Frontiers Editorial Office |
| MeSH-Schlagworte: | Social Welfare* , Grounded Theory* , Research*, Humans ; China ; Aged ; Middle Aged |
| Abstract: | Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Purpose: By the end of 2024, 22% of the Chinese population was aged 60 and above, making old-age social welfare a critical challenge. Despite abundant literature, a gap remains between research and policy. This study applies Nelson's computational grounded theory to systematically analyze China's old-age social welfare research and propose targeted policy priorities. Methods: We searched Chinese literature (2014-2024) from the Wanfang, CNKI, and CQVIP databases. After preprocessing the abstracts, we applied topic modeling using the latent Dirichlet allocation, guided by human analysts. Optimal topics were determined using perplexity and coherence metrics. Researchers then linked each topic to sociologically meaningful concepts to derive abstract policy conclusions. Results: A total of 413 articles met eligibility criteria. Seven topics emerged: (1) the theoretical significance of social welfare policy; (2) enhancing rural old-age care; (3) providing care for special groups; (4) promoting a home-community care model; (5) optimizing precision care through collaborative mechanisms; (6) developing community culture; and (7) establishing supply-driven care services. Notably, topics two and seven dominated the literature. Conclusion: Based on these themes, we propose policy priorities to enhance comprehensive social welfare programs. China's big government model-a top-level design involving diverse stakeholders-may serve as an effective framework for addressing a global aging society marked by rising non-communicable diseases and AI-driven economic growth. Moreover, our computer-assisted approach offers a valuable method for information scientists, aiding policymakers in navigating extensive digital data for more cost-effective and timely decision-making. (Copyright © 2025 Agudamu, Li, Mi and Pan.) |
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| Contributed Indexing: | Keywords: latent Dirichlet allocation; natural language processing; social insurance; social security; topic modeling |
| Entry Date(s): | Date Created: 20250513 Date Completed: 20250513 Latest Revision: 20250514 |
| Update Code: | 20250514 |
| PubMed Central ID: | PMC12066454 |
| DOI: | 10.3389/fpubh.2025.1556302 |
| PMID: | 40356844 |
| Datenbank: | MEDLINE |
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Nájsť tento článok vo Web of Science | Abstract: | Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br />Purpose: By the end of 2024, 22% of the Chinese population was aged 60 and above, making old-age social welfare a critical challenge. Despite abundant literature, a gap remains between research and policy. This study applies Nelson's computational grounded theory to systematically analyze China's old-age social welfare research and propose targeted policy priorities.<br />Methods: We searched Chinese literature (2014-2024) from the Wanfang, CNKI, and CQVIP databases. After preprocessing the abstracts, we applied topic modeling using the latent Dirichlet allocation, guided by human analysts. Optimal topics were determined using perplexity and coherence metrics. Researchers then linked each topic to sociologically meaningful concepts to derive abstract policy conclusions.<br />Results: A total of 413 articles met eligibility criteria. Seven topics emerged: (1) the theoretical significance of social welfare policy; (2) enhancing rural old-age care; (3) providing care for special groups; (4) promoting a home-community care model; (5) optimizing precision care through collaborative mechanisms; (6) developing community culture; and (7) establishing supply-driven care services. Notably, topics two and seven dominated the literature.<br />Conclusion: Based on these themes, we propose policy priorities to enhance comprehensive social welfare programs. China's big government model-a top-level design involving diverse stakeholders-may serve as an effective framework for addressing a global aging society marked by rising non-communicable diseases and AI-driven economic growth. Moreover, our computer-assisted approach offers a valuable method for information scientists, aiding policymakers in navigating extensive digital data for more cost-effective and timely decision-making.<br /> (Copyright © 2025 Agudamu, Li, Mi and Pan.) |
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| ISSN: | 2296-2565 |
| DOI: | 10.3389/fpubh.2025.1556302 |