[目的/意义]文章抽取健康信息规避影响因素，并结合模糊ISM-MICMAC模型，分析健康信息规避影响因 素的关联路径与层级关系，丰富了健康信息规避影响因素相关理论与实践研究，为相关健康服务机构解决用户健 康信息规避行为提供策略思考。[方法/过程]结合前人研究结论及理论基础，文章通过小组讨论和专家咨询确定 15个影响因素，结合模糊ISM解释结构模型、MICMAC交叉矩阵相乘法明确影响因素的关联路径及分类关系，并 提出对应的优化策略。[结果/结论]研究发现，健康信息素养作为独立群因素对健康信息规避影响程度最深；认知 冲突、行为改变、信息可靠度等自发群因素对系统整体性影响较小；而风险威胁感知、情绪调节作为依赖群因素具 有较高依赖性、低驱动力特点，易受其它因素影响，因此其它因素的有效解决将对该因素群的解决产生积极的促 进作用。

 [Purpose/significance] The influencing factors of health information avoidance were extracted, and the cor? relation path and hierarchical relationship of the influencing factors of health information avoidance were analyzed based on the fuzzy ISM MICMAC model, which enriched the theoretical and practical research on the influencing fac? tors of health information avoidance, and provided strategic thinking for the relevant health service institutions to solve the health information avoidance behavior of users. [Method/process] Combined with previous research conclusions and theoretical basis, 15 influencing factors were determined through group discussion and expert inquiry, and the cor? relation path and classification relationship of influencing factors were clarified by fuzzy ISM interpretation structure model and MICMAC cross matrix multiplication, and corresponding optimization strategies were proposed. [Result/ conclusion] The results show that health information literacy as an independent group factor has the greatest influence on health information avoidance. Cognitive conflict, behavior change, information reliability and other spontaneous group factors have little impact on the system integrity, but network security risks have a greater impact on the upper factors. However, risk threat perception and emotion regulation, as dependent group factors, are characterized by high dependence and low driving force, and are easily affected by other factors. Therefore, effective solution of other factors will have a positive promoting effect on the solution of this factor group.