AI Mental Health Frontier AI 心理健康前沿——临床 AI 试验前，先把共同设计做成安全门槛 香港一项研究说明，心理健康 AI 不应从模型演示开始，而应先确认真实需求、本地语言、隐私边界与临床协作方式。
AI Mental Health Frontier AI Mental Health Frontier — Co-Design Is the Pre-Trial Safety Gate A Hong Kong study shows why mental-health AI trials should begin with lived-experience needs, local language, privacy boundaries, and explicit adjunct-care constraints.
AI Mental Health Frontier AI 心理健康前沿——安全证据必须随生成式 AI 器械一起交付 FDA 对生成式 AI 心理健康医疗器械的讨论，把问题从模型表现推进到全生命周期的安全证据。
AI Mental Health Frontier AI Mental Health Frontier — The Safety Case Must Ship With the Device The FDA's generative-AI device discussion makes one point clear: mental-health safety must be demonstrated across the product lifecycle, not only at launch.
AI Mental Health Frontier AI 心理健康前沿——偏差审计必须进入临床工作流 一篇新的医疗 AI 偏差综述提醒心理健康产品团队：公平性不能停留在模型报告里，而要在真实工作流中验证。
AI Mental Health Frontier AI Mental Health Frontier — Bias Audits Must Become Workflow Tests A new scoping review maps bias in large AI models for healthcare and points mental-health builders toward subgroup, context, and human-review tests.
AI Mental Health Frontier AI Mental Health Frontier — Safe Evaluation Starts With the Comparator and the Context Two new studies sharpen the same design lesson: mental-health AI needs comparator-specific outcome tests and adversarial context tests before deployment.
AI Mental Health Frontier AI Mental Health Frontier — Chatbot Benefits Depend on the Comparator A new university-student meta-analysis finds modest symptom improvements versus low-intensity comparators, but no reliable incremental effect versus another conversational agent.
AI Mental Health Frontier AI 心理健康前沿——生成式 AI 医疗器械，安全必须贯穿全生命周期 FDA 对生成式 AI 心理健康器械的最新讨论，把问题从模型会不会说话，推进到产品能否持续验证、监测并完成安全交接。
AI Mental Health Frontier AI Mental Health Frontier — FDA's GenAI Device Debate Turns Safety Into a Lifecycle Requirement The FDA's 2026 discussion on generative-AI mental-health devices points builders toward lifecycle evidence, bounded claims, and human escalation—not chatbot novelty.
AI Mental Health Frontier AI Mental Health Frontier — Clinicians Need to Ask How Patients Use AI The new AWARE framework turns patients' chatbot use into a clinical conversation about motivation, attachment, reality, risk, and functioning.
AI Mental Health Frontier AI 心理健康前沿——MentalHealthBench 把对话质量变成可测问题 MentalHealthBench 不再只问模型会不会拒绝危险请求，而是把心理健康对话中的情境理解、用户自主性与行动建议纳入评估。
AI Mental Health Frontier AI Mental Health Frontier — MentalHealthBench Makes Conversation Quality Measurable OpenAI's MentalHealthBench broadens mental-health AI evaluation beyond crisis refusal. The useful shift is turning expert judgment into testable, workflow-level behaviors.
AI Mental Health Frontier AI Mental Health Frontier — Psychoeducation Needs Evidence Boundaries A new cross-sectional analysis of AI-generated EMDR psychoeducation shows why mental-health products need evidence boundaries, source tracing, and clinician review.
AI Mental Health Frontier AI 心理健康前沿——多模态精神状态评估需要人的误差回路 一项新的多模态精神状态评估研究提醒开发者：真正需要产品化的不是一个总诊断分数，而是可供临床人员复核的分域误差回路。
AI Mental Health Frontier AI Mental Health Frontier — Multimodal Assessment Needs a Human Error Loop A new multimodal mental-status benchmark points to a practical design rule: AI assessment should expose domain-level errors for clinician review, not hide behind an overall diagnosis score.
AI Mental Health Frontier AI Mental Health Frontier — Psychiatric Intake Needs Clinician-Grounded QA A new preprint shows why AI-assisted psychiatric intake needs clinician-grounded quality assurance: better information recovery can coexist with unsupported inference and weak safety characterization.
AI Mental Health Frontier AI Mental Health Frontier — High-Risk Conversation Testing Needs Clinical Calibration K-Bench shifts mental-health AI evaluation from comforting replies to calibrated performance across evolving high-risk conversations.
AI Mental Health Frontier AI Mental Health Frontier — Exposure Therapy Needs Human-GenAI Evidence New randomized trials test a human-GenAI single-session exposure intervention for academic anxiety, offering a useful design lesson: measure the care pathway, not just the chatbot.
AI Mental Health Frontier AI Mental Health Frontier — General Models Still Miss the Geriatric Context A blinded benchmark of three large language models shows why late-life depression needs geriatric-specific evaluation, calibrated triage, and human review.
AI Mental Health Frontier AI 心理健康前沿 — 叙事评估仍需要人工校验点 一项 2026 年研究显示，小型微调语言模型能够接近专家完成两类叙事心理学评分；真正的部署重点是边界、验证与人工复核。
AI Mental Health Frontier AI Mental Health Frontier — Narrative Assessment Needs a Human Checkpoint A 2026 study shows fine-tuned small language models can match expert ratings of two narrative-psychology constructs. The deployment lesson is augmentation, validation, and human review—not automated diagnosis.
