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 — 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 Mental Health Frontier — Safety Testing Must Follow the Conversation A clinically validated framework shows why mental-health chatbot evaluation must probe multi-turn behavior, not just single answers.
AI Mental Health Frontier AI 心理健康前沿——使用已经跑在治理之前 澳大利亚最新证据显示，心理健康行业已经日常使用通用 AI 处理文档，但复杂照护中的准确性、隐私与治理仍未跟上。
AI Mental Health Frontier AI Mental Health Frontier — Adoption Is Ahead of Governance New Australian evidence shows mental-health AI is already routine for administrative work, making governance and complexity-aware evaluation urgent.
AI Mental Health Frontier AI Mental Health Frontier — ‘AI Psychosis’ Is a System-Safety Question The emerging discussion of AI psychosis shifts attention from model personality to the safety of human-AI mental-health systems.
AI Mental Health Frontier AI Mental Health Frontier — Implementation Starts With Professional Logics A new qualitative study of an LLM-enhanced mental-health chatbot shows why implementation depends on reconciling professional roles, evidence, workflow, and accountability—not just model quality.
AI Mental Health Frontier AI 心理健康前沿——伦理评估必须跟着完整照护路径走 一篇最新研究提醒开发者：心理健康 AI 的安全性不能只看模型功能，而要看它嵌入整条照护路径后的表现。
AI Mental Health Frontier AI Mental Health Frontier — Ethical Evaluation Must Follow the Whole Care Path A new ethical evaluation of AI-supported mental-health applications points builders toward workflow-level evidence, not feature-level claims.
AI Mental Health Frontier AI 心理健康前沿 — 心理健康 AI 需要按风险分层部署 SAMHSA 最新政策报告给出一个实用提醒：心理健康 AI 的治理应由任务风险、人工监督和证据决定，而不是由界面是否流畅决定。
AI Mental Health Frontier AI Mental Health Frontier — Mental-Health AI Needs Risk-Tiered Deployment A new SAMHSA policy paper makes the deployment lesson concrete: mental-health AI should be governed by task risk, human oversight, and evidence—not by how fluent the interface feels.
