Conversational artificial intelligence can already independently engage in brief conversations with clients with psychological problems and provide evidence-based psychological interventions. The main objective of this study is to improve the effectiveness and credibility of the large language model in psychological intervention by creating a specialized agent, the VCounselor, to address the limitations observed in popular large language models such as ChatGPT in domain applications. We achieved this goal by proposing a new affective interaction structure and knowledge-enhancement structure. In order to evaluate VCounselor, this study compared the general large language model, the fine-tuned large language model, and VCounselor's knowledge-enhanced large language model. At the same time, the general large language model and the fine-tuned large language model will also be provided with an avatar to compare them as an agent with VCounselor. The comparison results indicated that the affective interaction structure and knowledge-enhancement structure of VCounselor significantly improved the effectiveness and credibility of the psychological intervention, and VCounselor significantly provided positive tendencies for clients' emotions. The conclusion of this study strongly supports that VConselor has a significant advantage in providing psychological support to clients by being able to analyze the patient's problems with relative accuracy and provide professional-level advice that enhances support for clients.

翻译：对话式人工智能已能独立与心理问题来访者进行简短对话并提供循证心理干预。本研究的主要目标是通过创建专用代理VCounselor，提升大语言模型在心理干预中的有效性与可信度，以解决ChatGPT等主流大语言模型在领域应用中存在的局限性。我们通过提出新型情感交互结构与知识增强结构实现了这一目标。为评估VCounselor，本研究比较了通用大语言模型、微调大语言模型及VCounselor的知识增强大语言模型。同时，通用大语言模型与微调大语言模型也被赋予虚拟形象，以代理形式与VCounselor进行对比。比较结果显示，VCounselor的情感交互结构与知识增强结构显著提升了心理干预的有效性与可信度，且其能明显为来访者情绪提供正向引导。研究结论有力证明，VCounselor能相对准确地分析患者问题并提供专业级建议，在增强对来访者支持方面具有显著优势，从而在提供心理支持时展现出关键价值。