分析"十四五"时期我国国家层面痴呆症防治政策的文本特征，揭示政策工具、利益相关者与政策力度的分布规律及内在关联，为政策体系的优化完善提供依据。

检索2021—2025年国家层面发布的痴呆症防治相关政策文本，构建包含"政策工具-利益相关者-政策力度"的三维分析框架，运用内容分析法进行编码，通过Cohen's Kappa系数检验编码信度。采用MAXQDA 2022软件从政策工具类型（供给型、环境型、需求型）、利益相关者（政府部门、医疗机构、卫生人员等六类主体）及政策力度（1~5分）三个维度进行量化统计分析。

共纳入痴呆症防治相关政策文本15份，得到政策工具编码276条，编码质量一致性良好（三维度Kappa系数分别为0.85、0.80、0.82）。单维度分析显示，环境型工具占比最高（122条，44.20%），供给型工具次之（113条，40.94%），需求型工具占比显著偏低（41条，14.86%）；政策注意力集中于医疗机构（73条，30.80%）和政府部门（71条，29.96%），而对社会资本（18条，7.59%）和卫生人员（16条，6.75%）关注度较低；政策平均力度偏低（2.80分），表现为三部委及以上联合发文（6份）与各部委单独发文（5份）并存，双部委发文政策缺失。交叉分析显示，政策工具在各主体间分布不均，医疗机构（73条）和政府部门（71条）承接最多，卫生人员（16条）与社会资本（18条）最少；三类工具平均力度为需求型2.55分、环境型2.34分、供给型2.20分，需求型政策工具中价格服务力度最高（4.50分）但仅4条。三维分析中，环境型工具总力度最高（306分），需求型最低（116分）；主体总力度以医疗机构（139分）和政府部门（122分）居前，卫生人员最低（30分）。

我国痴呆防治政策体系呈现"规划密集、供给启动、需求不足、力度偏弱"的结构性特征，政策工具配置偏重供给，对需求关注不足，执行主体集中于医疗机构与政府部门，政策力度整体偏低且连续性不足，需从工具均衡性、主体覆盖面和力度连续性方面持续优化。

This study analyzes the textual characteristics of China's national-level dementia prevention and treatment policies during the "14th Five-Year Plan" period, reveals the distribution patterns and intrinsic relationships among policy instruments, stakeholders, and policy intensity, and provides a basis for optimizing and improving the policy system.

National-level policy texts related to dementia prevention and treatment issued from 2021 to 2025 were retrieved; a three-dimensional analytical framework comprising "policy tools-stakeholders-policy intensity" was constructed; content analysis was employed for coding; and coding reliability was tested using Cohen’s Kappa coefficient. MAXQDA 2022 was used to conduct quantitative statistical analysis across three dimensions: policy instrument types (supply-oriented, environment-oriented, and demand-oriented), stakeholders (six categories including government departments, medical institutions, and healthcare personnel), and policy intensity (1-5 points).

A total of 15 policy texts related to dementia prevention and treatment were included, yielding 276 policy instrument codes, with good coding reliability (the three-dimensional kappa coefficients are 0.85, 0.82, and 0.82, respectively). Unidimensional analysis showed that environmental-oriented tools have the highest proportion (122 codes, 44.20%), followed by supply-oriented tools (113 codes, 40.94%), and demand-oriented tools have a significantly lower proportion (41 codes, 14.86%); policy attention was focused on medical institutions (73 codes, 30.80%) and government departments (71 codes, 29.96%), while social capital (18 codes, 7.59%) and health personnel (16 codes, 6.75%) had lower levels of attention; the average policy intensity was relatively low (2.80 points), manifested by the coexistence of six joint documents issued by three or more ministries and five separate documents issued by each ministry, and the lack of policies issued by the dual ministries and commissions. Cross analysis showed that policy tools were unevenly distributed among different entities, with medical institutions (73 codes) and government departments (71 codes) undertaking the most, while health personnel (16 codes) and social capital (18 codes) undertaking the least; the average strength of the three types of tools was 2.55 points for demand type, 2.34 points for environmental type, and 2.20 points for supply type. The price service strength in the demand-oriented tools was the highest (4.50 points), but only 4 codes were available. In 3D analysis, environmental tools had the highest total strength (306 points), while demand based tools had the lowest (116 points); medical institutions (139 points) and government departments (122 points) ranked first in terms of overall strength, while health personnel had the lowest (30 points).

The policy system for the prevention and treatment of dementia in China presents structural characteristics of "intensive planning, supply start-up, insufficient demand and weak strength". The allocation of policy tools focuses more on supply, with insufficient attention to demand. The executing entities are concentrated in medical institutions and government departments, and the overall policy intensity is low and lacks continuity. Continuous optimization is needed in terms of tool balance, subject coverage, and intensity continuity.