Continual Optimization and Personalization of Just-in-Time Adaptive Interventions for SUD Prevention, Treatment, and Recovery

针对 SUD 预防、治疗和恢复的及时适应性干预措施的持续优化和个性化

• 批准号: 10640293
• 负责人: SUSAN A MURPHY
• 金额: $ 48.07万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10640293
• 关键词: AIDS prevention; Adult; Affect; Algorithms; Artificial Intelligence; Bayesian Method; Behavioral Medicine; Behavioral Sciences; COVID-19; Cellular Phone; Collaborations; Computer software; Data; Devices; Drug usage; Educational workshop; Effectiveness; Effectiveness of Interventions; Explosion; Generations; Goals; HIV; Health Technology; Individual; Intervention; Journals; Learning; Location; Methodology; Modernization; Motivation; Participant; Peer Review; Persons; Play; Population; Prevention strategy; Psychological reinforcement; Publishing; Recovery; Research; Role; Scientist; Services; Societies; Stress; Substance Use Disorder; Testing; Time; Training; Variant; Work; Writing; Youth; adaptive intervention; craving; delivery vehicle; design; digital; digital delivery; digital health; digital intervention; digital technology; disorder prevention; effective intervention; individualized prevention; intervention cost; intervention delivery; mHealth; opioid epidemic; overpopulation; person centered; population based; post-pandemic; prevention service; preventive intervention; recovery services; response; service intervention; simulation; smart watch; substance use; therapy design; treatment response; treatment services; trend; unnecessary treatment; user friendly software; user-friendly; wearable device; young adult

PROJECT SUMMARY: PROJECT 3 In the modern, post-pandemic world, digital technology is becoming an increasingly important vehicle for the delivery of substance use disorder (SUD) and HIV prevention, treatment, and recovery services. The long-term goal of the proposed project is to enable digital health technology to deliver intervention services with unprecedented effectiveness and sustainability. We propose to integrate ideas from behavioral science and artificial intelligence to develop methodology for (1) continual optimization of just-in-time adaptive digital health interventions in response to societal changes and evolving population treatment needs and (2) personalized just-in-time adaptive digital health interventions to each individual's evolving treatment needs. This will enable a second generation of just-in-time adaptive digital health interventions with enhanced and highly sustainable effectiveness. To achieve this long-term goal, we will: (Aim 1) Promote sustainable intervention effectiveness and engagement by integrating approaches from artificial intelligence — namely reinforcement learning — to develop algorithms that continually optimize mobile health interventions over time; (Aim 2) Meet differential individual needs by generalizing Aim 1 algorithms to construct and continually optimize person-specific mobile health interventions; (Aim 3) Test, evaluate, and refine the algorithms developed in Aims 1 and 2 in extensive simulations; and (Aim 4) Disseminate the developed algorithms so that they can be readily applied in SUD/HIV prevention, treatment, and recovery. We will conduct workshops for SUD/HIV scientists and publish both tutorials and new research in SUD, HIV, and methodology venues. We will work with the Dissemination and Training Core to develop free, user-friendly software that will enable SUD/HIV scientists to develop, optimize, and evaluate their own just-in-time adaptive digital health interventions.

项目摘要：项目 3 在大流行后的现代世界，数字技术正在成为日益重要的工具 提供物质使用障碍 (SUD) 和艾滋病毒预防、治疗和康复服务。 拟议项目的目标是使数字医疗技术能够提供干预服务 我们建议将行为科学的思想与实践相结合。 人工智能开发方法用于（1）持续优化即时自适应数字健康 为应对社会变化和不断变化的人口治疗需求而采取的干预措施；(2) 个性化 针对每个人不断变化的治疗需求的及时适应性数字健康干预措施将成为可能。 第二代即时适应性数字健康干预措施，具有增强且高度可持续的特点 有效性。为了实现这一长期目标，我们将：（目标 1）促进可持续的干预有效性。 通过整合人工智能（即强化学习）的方法来提高参与度 （目标 2）满足差异 通过推广 Aim 1 算法构建并持续优化针对个人的移动设备来满足个性化需求 健康干预措施；（目标 3）广泛测试、评估和完善目标 1 和 2 中开发的算法 模拟；以及（目标 4）传播开发的算法，以便它们可以轻松应用于 SUD/HIV 我们将为 SUD/HIV 科学家举办研讨会并出版这两个研讨会。 我们将与传播和方法论领域合作。 Training Core 开发免费、用户友好的软件，使 SUD/HIV 科学家能够开发、优化、 并评估他们自己的及时适应性数字健康干预措施。