MindfulDiary：利用大语言模型支持精神科患者的日记记录
MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
AI总结：
本文提出 MindfulDiary，一款结合大语言模型的移动日记应用，通过状态化对话支持抑郁症患者记录日常，并在四周实地研究中验证其能丰富患者记录并提升精神科医生共情能力。
摘要：
在心理健康领域，大语言模型（LLMs）提供了充满前景的新机遇，但其固有的复杂性和低可控性引发了对其在临床环境中适用性的质疑。我们提出了 MindfulDiary，一款整合大语言模型的移动日记应用，旨在帮助精神科患者通过对话记录日常经历。MindfulDiary 与心理健康专业人士（MHPs）合作设计，采用基于状态的方法，在遵循专家指导方针的同时安全地进行自由形式的对话。通过一项为期四周、涉及 28 名重度抑郁症患者和 5 名精神科医生的实地研究，我们发现 MindfulDiary 支持患者持续丰富其日常记录，并帮助精神科医生通过理解患者的想法和日常情境更好地共情。基于这些发现，我们讨论了在心理健康领域利用大语言模型的意义，弥合技术可行性与临床环境整合之间的鸿沟。
英文摘要：
In the mental health domain, Large Language Models (LLMs) offer promising new opportunities, though their inherent complexity and low controllability have raised questions about their suitability in clinical settings. We present MindfulDiary, a mobile journaling app incorporating an LLM to help psychiatric patients document daily experiences through conversation. Designed in collaboration with mental health professionals (MHPs), MindfulDiary takes a state-based approach to safely comply with the experts' guidelines while carrying on free-form conversations. Through a four-week field study involving 28 patients with major depressive disorder and five psychiatrists, we found that MindfulDiary supported patients in consistently enriching their daily records and helped psychiatrists better empathize with their patients through an understanding of their thoughts and daily contexts. Drawing on these findings, we discuss the implications of leveraging LLMs in the mental health domain, bridging the technical feasibility and their integration into clinical settings.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
