Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor (SPEAC) for Adults with Emotional Distress

针对患有情绪困扰的成年人的经过 PST 培训的语音人工智能咨询师 (SPEAC) 的研究

• 批准号: 10611145
• 负责人: Olusola A. Ajilore
• 金额: $ 108.87万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-03 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10611145
• 关键词: Address; Adult; Affect; Amygdaloid structure; Anxiety; Area; Artificial Intelligence; Attitude; Brain; Clinical; Cognition; Cognitive; Computer software; Development; Devices; Dorsal; Dose; Emotional; Emotions; Engineering; Enrollment; Evaluation; Face; Focus Groups; Functional Magnetic Resonance Imaging; Functional disorder; Future; Generalized Anxiety Disorder; Health; Health Promotion; Health Resources; Human; Image Analysis; Intelligence; Lateral; Length; Machine Learning; Measurement; Measures; Mediating; Mental Depression; Mental Health; Mental Health Services; Moods; Names; Neurosciences; Outcome; Participant; Patient Outcomes Assessments; Patient Self-Report; Patients; Personal Satisfaction; Persons; Phase; Prefrontal Cortex; Problem Solving; Procedures; Process Measure; Productivity; Professional counselor; Protocols documentation; Psychotherapy; Public Health; Quality of life; Questionnaires; Randomized; Randomized Clinical Trials; Research; Secure; Specific qualifier value; Stress; Surveys; Symptoms; Techniques; Testing; Therapeutic; Time; Training; Translating; Treatment Efficacy; United States National Institutes of Health; Voice; Voice Training; Waiting Lists; active control; active method; anxiety symptoms; arm; base; behavioral health intervention; clinical decision support; cognitive control; connected care; coping; cost; depressive symptoms; digital medicine; disability; efficacy testing; emotional distress; experience; follow up assessment; formative assessment; improved; innovation; insight; intelligent agent; iterative design; knowledge base; meetings; neural circuit; neuromechanism; new technology; novel; pilot test; problem solving therapy; prototype; recruit; relating to nervous system; social stigma; targeted treatment; theories; treatment arm; treatment optimization; usability; user centered design; virtual; virtual health

PROJECT SUMMARY BACKGROUND: Depression and anxiety are the leading causes of disability and lost productivity, and are often underdiagnosed and undertreated owing to access, cost, and stigma barriers. Novel and scalable psychotherapies are urgently needed. Advances in artificial intelligence (AI) offer a transformative opportunity to develop intelligent voice assistants as virtual health agents accessible on personal devices. Meanwhile, major advances in human neuroscience have fueled a paradigm shift to study brain mechanisms underlying behavioral health interventions. OBJECTIVES: Leveraging our collaborative team’s transdisciplinary expertise in these emerging areas, we will develop and rigorously test a novel voice-enabled, AI virtual agent named Lumen, trained on Problem Solving Therapy (PST), for patients with moderate, untreated depressive and/or anxiety symptoms. We will investigate the effect of Lumen on engagement of a priori neural targets—amygdala for emotional reactivity and dorsal lateral prefrontal cortex (DLPFC) for cognitive control—as putative mechanisms. DESIGN/ METHODS: The project has 2 phases. In the R61 phase (years 1-2), we will further develop Lumen building on the current prototype and conduct iterative user-centered design evaluations that include focus groups, scenario-based clinician evaluations, and a formative user study with 20 participants. We will pilot test Lumen in a 2-arm randomized clinical trial (RCT, Study 1), with 60 participants with depression and/or anxiety randomized in a 2:1 ratio to receive PST with Lumen (n=40) on a secure study iPad or be on a waitlist (n=20). At weeks 0 and 14, participants will complete functional magnetic resonance imaging (fMRI) to assess neural target engagement as well as validated surveys of patient-reported outcomes (e.g., depressive and anxiety symptoms, functioning, quality of life). In addition, they will complete naturalistic end-of-day assessments of mood, stress, appraisal and coping for 7 days every 2 weeks. If the Go milestone criteria are met, the R33 phase (years 3-5) will include a 3-arm RCT (Study 2) with 200 new participants randomized in a 2:1:1 ratio to 1 of 3 arms: Lumen (n=100), waitlist control (n=50), and in-person PST as active control (n=50). Participants will complete baseline and follow-up assessments using a refined measurement protocol based on Study 1. SPECIFIC AIMS: R61 aims are to (1) establish the functionality, usability, and treatment fidelity of Lumen; and (2) demonstrate feasibility, acceptability, and neural target engagement according to pre-specified Go milestone criteria. R33 aims are to (1) confirm neural target engagement by a superiority test (primary) comparing the Lumen and waitlist control arms and a noninferiority test (secondary) comparing the Lumen and in-person PST arms; and (2) examine the relationships of target engagement to outcomes. The results will provide the basis for future confirmatory efficacy testing of Lumen. IMPACT: This project’s public health impact lies in that a mechanistically tested, PST-trained AI agent could bring proven psychotherapy to people with depression/anxiety who do not seek professional help or who desire more personalized, connected care.

项目摘要 背景：抑郁和焦虑是残疾和生产力下降的主要原因， 由于获取、费用和耻辱障碍，往往诊断不足和治疗不足。新颖且可扩展 迫切需要心理治疗。人工智能（AI）的进步提供了一个变革性的机会 开发智能语音助手作为个人设备上可访问的虚拟健康代理。同时， 人类神经科学的重大进展推动了研究大脑机制的范式转变， 行为健康干预。优势：利用我们合作团队的跨学科专业知识 在这些新兴领域，我们将开发并严格测试一种新型的语音智能虚拟代理， Lumen，接受过问题解决疗法（PST）的培训，适用于中度、未经治疗的抑郁症和/或 焦虑症状我们将研究Lumen对先验神经靶点-杏仁核参与的影响 情绪反应和背外侧前额叶皮层（DLPFC）的认知控制-作为假定 机制等设计/方法：分2个阶段进行。在R61阶段（1 - 2年），我们将进一步 在当前原型的基础上开发Lumen，并进行以用户为中心的迭代设计评估， 包括焦点小组、基于ECOMO的临床医生评估和有20名参与者的形成性用户研究。我们 我将在一项2组随机临床试验（RCT，研究1）中对Lumen进行初步测试，有60名抑郁症患者参与 和/或焦虑以2：1的比例随机分配，在安全研究iPad上接受PST with Lumen（n = 40），或在 waitlist（n = 20）。在第0周和第14周，参与者将完成功能性磁共振成像（fMRI）， 评估神经目标接合以及患者报告结果的有效调查（例如，抑郁 和焦虑症状、功能、生活质量）。此外，他们将完成自然主义的结束日 每2周进行7天的情绪、压力、评价和应对评估。如果Go里程碑标准为 满足，R33阶段（第3 - 5年）将包括一项3组RCT（研究2），其中200名新受试者随机分配至 3个组中的1个组的比例为2：1：1：Lumen（n = 100）、等待列表对照组（n = 50）和作为主动对照组的亲自PST（n = 50）。 参与者将使用基于以下内容的精确测量方案完成基线和随访评估： 研究1.具体目标：R61的目标是（1）建立 管腔;和（2）根据预先规定，证明可行性、可接受性和神经靶点接合 执行里程碑标准。R33的目的是（1）通过优效性检验（主要）确认神经目标接合 比较管腔对照组和等待列表对照组，以及比较管腔对照组和等待列表对照组的非劣效性检验（次要）。 亲自PST武器;（2）检查目标参与结果的关系。结果将 为将来Lumen的确认有效性测试提供基础。影响：该项目的公共卫生影响 一个经过机械测试、经过PST训练的人工智能代理人可以为患有以下疾病的人带来经过验证的心理治疗： 抑郁症/焦虑症患者不寻求专业帮助或希望获得更个性化、更有联系的护理。