挖掘人工智能素养、健康信息素养与AIGC健康信息采纳行为之间的作用关系、影响机制、组态路径是进一步优化人智交互过程与规范信息行为的基础。文章尝试通过多阶段实验法、结构方程模型、组态分析法对人工智能素养、健康信息素养与AIGC健康信息采纳的影响关系进行分析。研究发现：人工智能素养和健康信息素养对AIGC健康信息采纳具有积极影响，且感知系统质量和感知信息质量是其重要的影响路径，这进一步扩展了信息采纳模型；感知知识共识也可以通过作用感知系统质量和感知信息质量驱动信任和AIGC健康信息采纳，这体现了个体对人工智能生成内容的多源信息验证关系。此外，在以信任和感知系统质量主导的信任-系统主导构型采纳模式以外，还包含伦理导向构型和评估导向构型两种采纳模式，这也为规范AIGC健康信息采纳行为提供了方向和依据。

Exploring the relationships, mechanisms, and configurational paths between artificial intelligence literacy, health information literacy, and AIGC health information adoption is fundamental for optimizing human-AI interaction processes and standardizing information behaviors. This paper employs multi-stage experiments, structural equation modeling, and configurational analysis to examine the influence of artificial intelligence literacy, health information literacy, and AIGC health information adoption. Research findings indicate that artificial intelligence literacy and health information literacy have a positive impact on the adoption of AIGC health information, and perceived system quality and perceived information quality are important influencing paths, which further expand the information adoption model. At the same time, perceived knowledge consensus can also drive trust and the adoption of AIGC health information by acting on perceived system quality and perceived information quality, which reflects the multi-source information verification relationship of individuals towards AI-generated content. In addition, configuration analysis reveals that, apart from the trust-system dominant configuration adoption mode led by trust and perceived system quality, there are two other adoption modes, namely the ethics-oriented configuration and the evaluation-oriented configuration. This also provides a directional basis for regulating the adoption behavior of AIGC health information.