[目的/意义]生成式人工智能（GenAI）产品的迅速发展彻底改变了人类与人工智能的交互模式，深入挖掘用户-GenAI交互中自我披露行为的动因及模式有助于理解该情境下用户自我披露的多样性和复杂性，为探索人智交互中的用户信息行为提供新视角。[方法/过程]基于CASA范式、社会渗透理论和心智感知理论，利用系统性主题分析对20名GenAI用户的访谈数据进行编码分析。[结果/结论]用户-GenAI交互中的自我披露行为动因分为环境、技术以及用户三个维度，自我披露行为模式分为层次增长型、层次稳定性和层次消退型三种模式。通过分析用户自我披露的动因与模式，为优化“以人为本”的GenAI设计提供了参考，有助于针对不同类型的用户进行更为精准和有效的体验优化。

[Purpose/significance] The rapid development of Generative Artificial Intelligence (GenAI) products has completely transformed the interaction patterns between humans and artificial intelligence. In-depth exploration of the motives and patterns of self-disclosure in user-GenAI interactions helps to understand the diversity and complexity of user self-disclosure in this context, providing a new perspective for exploring user information behavior in human-intel⁃ligence interaction. [Method/process] Based on the CASA paradigm, social penetration theory, and mind perception theory, systematic thematic analysis was conducted on interview data from 20 GenAI users. [Result/conclusion] The study found that the motives for self-disclosure in user-GenAI interactions can be divided into three dimensions: envi⁃ronmental, technological, and user-related. Moreover, the patterns of self-disclosure in user-GenAI interactions can be categorized into three types: increasing disclosure layer, stable disclosure layer, and decreasing disclosure layer. By ana⁃lyzing the motives and patterns of user self-disclosure, it provides references for optimizing "people-centered" GenAI design, which is helpful for more precise and effective experience optimization for different types of users.