Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Public Health. 2024 Nov 4;12:1475867. doi: 10.3389/fpubh.2024.1475867. eCollection 2024.
Progress in developing artificial intelligence (AI) products represented by large language models (LLMs) such as OpenAI's ChatGPT has sparked enthusiasm for their potential use in mental health practice. However, the perspectives on the integration of LLMs within mental health practice remain an underreported topic. Therefore, this study aimed to explore how mental health and AI experts conceptualize LLMs and perceive the use of integrating LLMs into mental health practice.
In February-April 2024, online semi-structured interviews were conducted with 21 experts (12 psychiatrists, 7 mental health nurses, 2 researchers in medical artificial intelligence) from four provinces in China, using snowballing and purposive selection sampling. Respondents' discussions about their perspectives and expectations of integrating LLMs in mental health were analyzed with conventional content analysis.
Four themes and eleven sub-themes emerged from this study. Firstly, participants discussed the (1) practice and application reform brought by LLMs into mental health (fair access to mental health services, enhancement of patient participation, improvement in work efficiency and quality), and then analyzed the (2) technological-mental health gap (misleading information, lack of professional nuance and depth, user risk). Based on these points, they provided a range of (3) prerequisites for the integration of LLMs in mental health (training and competence, guidelines for use and management, patient engagement and transparency) and expressed their (4) expectations for future developments (reasonable allocation of workload, upgrades and revamps of LLMs).
These findings provide valuable insights into integrating LLMs within mental health practice, offering critical guidance for institutions to effectively implement, manage, and optimize these tools, thereby enhancing the quality and accessibility of mental health services.
以 OpenAI 的 ChatGPT 为代表的人工智能 (AI) 产品的发展取得了进展，引发了人们对其在心理健康实践中应用的热情。然而，将大语言模型 (LLM) 整合到心理健康实践中的观点仍然是一个报道较少的话题。因此，本研究旨在探讨心理健康和 AI 专家如何概念化 LLM，并感知将 LLM 整合到心理健康实践中的使用。
2024 年 2 月至 4 月，采用滚雪球和目的抽样法，从中国四个省份招募了 21 名专家（12 名精神科医生、7 名精神科护士、2 名医学人工智能研究员）进行在线半结构式访谈。使用常规内容分析法分析受访者对将 LLM 整合到心理健康中的观点和期望的讨论。
本研究提出了四个主题和十一个子主题。首先，参与者讨论了 LLM 给心理健康带来的（1）实践和应用改革（公平获得心理健康服务、增强患者参与度、提高工作效率和质量），然后分析了（2）技术-心理健康差距（误导性信息、缺乏专业细微差别和深度、用户风险）。在此基础上，他们提出了一系列（3）将 LLM 整合到心理健康中的前提条件（培训和能力、使用和管理指南、患者参与和透明度），并表达了他们对未来发展的（4）期望（合理分配工作量、升级和改进 LLM）。
这些发现为将 LLM 整合到心理健康实践中提供了有价值的见解，为机构有效实施、管理和优化这些工具提供了关键指导，从而提高了心理健康服务的质量和可及性。
