MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
This work addresses the problem of integrating complex and low-controllable LLMs into clinical mental health care for psychiatric patients, representing an incremental application of existing technology to a new domain.
The authors tackled the challenge of using Large Language Models (LLMs) in clinical mental health settings by developing MindfulDiary, a mobile journaling app that helps psychiatric patients document daily experiences through conversation, resulting in support for consistent journaling and improved empathy from psychiatrists in a study with 28 patients and five psychiatrists over four weeks.
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.