Artificial intelligence (AI)-enabled digital interventions, including Generative AI (GenAI) and Human-Centered AI (HCAI), are increasingly used to expand access to digital psychiatry and mental health care. This PRISMA-ScR scoping review maps the landscape of AI-driven mental health (mHealth) technologies across five critical phases: pre-treatment (screening/triage), treatment (therapeutic support), post-treatment (remote patient monitoring), clinical education, and population-level prevention. We synthesized 36 empirical studies implemented through early 2024, focusing on Large Language Models (LLMs), machine learning (ML) models, and autonomous conversational agents. Key use cases involve referral triage, empathic communication enhancement, and AI-assisted psychotherapy delivered via chatbots and voice agents. While benefits include reduced wait times and increased patient engagement, we address recurring challenges like algorithmic bias, data privacy, and human-AI collaboration barriers. By introducing a novel four-pillar framework, this review provides a comprehensive roadmap for AI-augmented mental health care, offering actionable insights for researchers, clinicians, and policymakers to develop safe, effective, and equitable digital health interventions.

翻译：人工智能（AI）赋能的数字干预，包括生成式人工智能（GenAI）和以人为中心的人工智能（HCAI），正日益广泛地应用于扩展数字精神病学与心理健康护理的可及性。本项遵循PRISMA-ScR指南的范围综述，描绘了人工智能驱动的心理健康（mHealth）技术在五个关键阶段的应用全景：治疗前（筛查/分诊）、治疗中（治疗支持）、治疗后（远程患者监测）、临床教育以及人群层面的预防。我们综合分析了截至2024年初实施的36项实证研究，重点关注大型语言模型（LLMs）、机器学习（ML）模型以及自主对话代理。关键应用场景涉及转诊分诊、共情沟通增强以及通过聊天机器人和语音代理实现的AI辅助心理治疗。尽管其益处包括缩短等待时间和提高患者参与度，我们也探讨了算法偏见、数据隐私以及人机协作障碍等反复出现的挑战。通过引入一个新颖的四支柱框架，本综述为AI增强的心理健康护理提供了一份全面的路线图，为研究人员、临床医生和政策制定者开发安全、有效且公平的数字健康干预措施提供了可行的见解。