AI Mental Health Frontier AI 心理健康前沿——类治疗聊天机器人，先过伦理风险测试 一项由临床实践者参与的研究梳理出大语言模型咨询行为的15类伦理风险，为心理健康 AI 建立上线前测试议程。
AI Mental Health Frontier AI Mental Health Frontier — Ethical Risk Tests Must Precede Therapist-Like Chatbots A practitioner-informed study identifies 15 ethical risks in therapist-like LLM behavior, turning vague concerns about AI counseling into concrete pre-deployment tests.
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 心理健康前沿——聊天机器人有没有用，先看比较对象 一项聚焦大学生的系统综述显示，聊天机器人相较低强度对照可能改善抑郁和焦虑，但相较另一款聊天机器人并未显示可靠的增量效果。
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 心理健康前沿——心理测量型 AI 必须先划清同意与验证边界 最新关于生成式 AI 心理测量与职场心理健康监测的综述提醒开发者：测量系统要先解决同意、验证、隐私和人工复核。
AI Mental Health Frontier AI Mental Health Frontier — Psychometric AI Needs a Consent and Validation Boundary New reviews on AI psychometrics and workplace mental-health monitoring point to a practical rule: measurement systems need consent, validation, and human review before they become care infrastructure.
AI Mental Health Frontier AI 心理健康前沿——心理治疗科普必须有证据边界 一项关于 AI 生成 EMDR 科普内容的横断面分析提醒产品团队：心理健康产品需要来源追踪、不确定性表达与临床复核。
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 心理健康前沿——精神科初诊需要临床校准的质量保证 一篇新的预印本把 AI 精神科初诊的真实难题摆到台面上：信息找得更多，并不等于推断更可靠或安全信号解释得更好。
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.
