20位心理障碍者访谈揭示大模型在心理健康中的实际使用与边界
A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMs
- 用户按需使用大模型，用于即时缓解、无评判交流等场景
- 模型对轻中度困扰有效，但无法处理危机与复杂情感问题
- 强调设计需明确边界，适合辅助支持而非替代专业治疗
大型语言模型（LLMs）越来越多地被用于心理健康支持，但人们对患有心理障碍的人如何使用它们、如何评估其有效性，以及他们期待的设计改进仍知之甚少。我们对英国20位有心理障碍且曾使用过LLMs进行心理支持的个体进行了半结构化访谈。通过反思性主题分析，发现参与者以条件性和情境化的方式使用LLMs：追求即时响应、避免评判、自主披露、认知重构和关系互动。同时，他们基于过往治疗经验设定了清晰界限：LLMs在轻至中度情绪困扰时有效，但在危机、创伤或复杂社会情感情境下不足。本研究提供了关于心理障碍者真实使用体验的实证洞察，强调边界设定是其安全角色的核心，并提出了将它们负责任地融入照护生态系统的相关设计与治理方向。
原文摘要 · Abstract (English)
Large Language Models (LLMs) are increasingly used for mental health support, yet little is known about how people with mental health challenges engage with them, how they evaluate their usefulness, and what design opportunities they envision. We conducted 20 semi-structured interviews with people in the UK who live with mental health conditions and have used LLMs for mental health support. Through reflexive thematic analysis, we found that participants engaged with LLMs in conditional and situational ways: for immediacy, the desire for non-judgement, self-paced disclosure, cognitive reframing, and relational engagement. Simultaneously, participants articulated clear boundaries informed by prior therapeutic experience: LLMs were effective for mild-to-moderate distress but inadequate for crises, trauma, and complex social-emotional situations. We contribute empirical insights into the lived use of LLMs for mental health, highlight boundary-setting as central to their safe role, and propose design and governance directions for embedding them responsibly within care ecosystem.
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