The demand for psychological counseling has grown significantly in recent years, particularly with the global outbreak of COVID-19, which has heightened the need for timely and professional mental health support. Online psychological counseling has emerged as the predominant mode of providing services in response to this demand. In this study, we propose the Psy-LLM framework, an AI-based system leveraging Large Language Models (LLMs) for question-answering in online psychological consultation. Our framework combines pre-trained LLMs with real-world professional Q&A from psychologists and extensively crawled psychological articles. The Psy-LLM framework serves as a front-end tool for healthcare professionals, allowing them to provide immediate responses and mindfulness activities to alleviate patient stress. Additionally, it functions as a screening tool to identify urgent cases requiring further assistance. We evaluated the framework using intrinsic metrics, such as perplexity, and extrinsic evaluation metrics, with human participant assessments of response helpfulness, fluency, relevance, and logic. The results demonstrate the effectiveness of the Psy-LLM framework in generating coherent and relevant answers to psychological questions. This article concludes by discussing the potential of large language models to enhance mental health support through AI technologies in online psychological consultation.

翻译：近年来，特别是在新冠疫情全球爆发后，人们对心理咨询的需求显著增长，对及时、专业的心理健康支持的需求也随之提升。在线心理咨询已成为满足这一需求的主要服务模式。在本研究中，我们提出了Psy-LLM框架，这是一个基于AI的系统，利用大语言模型（LLMs）进行在线心理咨询中的问答。该框架将预训练的大语言模型与心理专家的真实专业问答数据以及大规模抓取的心理文章相结合。Psy-LLM框架可作为医疗专业人员的前端工具，使其能够提供即时回应和正念活动以缓解患者压力。此外，它还可作为筛查工具，识别需要进一步援助的紧急病例。我们通过内在评估指标（如困惑度）和外在评估指标进行框架评估，并请人类参与者对回应的有用性、流畅性、相关性和逻辑性进行评价。结果表明，Psy-LLM框架能够为心理问题生成连贯且相关的问答内容。本文最后讨论了通过AI技术利用大语言模型增强在线心理咨询中心理健康支持的潜力。