Li Yingying, Mi Na, Pan Xinyue
Graduate School of Social Welfare, Sungkyunkwan University, Seoul, Republic of Korea.
College of Physical Education, Hunan Normal University, Changsha, China.
Front Public Health. 2025 Apr 28;13:1556302. doi: 10.3389/fpubh.2025.1556302. eCollection 2025.
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.
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.
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.
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.
到2024年底，中国60岁及以上人口占比达22%，这使得老年社会福利成为一项严峻挑战。尽管相关文献丰富，但研究与政策之间仍存在差距。本研究运用尼尔森的计算扎根理论，系统分析中国老年社会福利研究，并提出针对性的政策重点。
我们检索了万方、知网和维普数据库中的中国文献（2014 - 2024年）。对摘要进行预处理后，在人工分析的指导下，使用潜在狄利克雷分配进行主题建模。利用困惑度和连贯性指标确定最优主题。研究人员随后将每个主题与具有社会学意义的概念相联系，以得出抽象的政策结论。
共有413篇文章符合纳入标准。出现了七个主题：（1）社会福利政策的理论意义；（2）加强农村养老服务；（3）关爱特殊群体；（4）推广居家 - 社区养老模式；（5）通过协作机制优化精准照护；（6）发展社区文化；（7）建立供给驱动型照护服务。值得注意的是，主题二和主题七在文献中占主导地位。
基于这些主题，我们提出了加强综合社会福利项目的政策重点。中国的大政府模式——一种涉及多方利益相关者的顶层设计——可能成为应对以非传染性疾病增加和人工智能驱动经济增长为特征的全球老龄化社会的有效框架。此外，我们的计算机辅助方法为信息科学家提供了一种有价值的方法，有助于政策制定者在海量数字数据中进行筛选，以做出更具成本效益和及时性的决策。
