Methods for Optimizing the Integration of Adaptive Human-Delivered and Digital SUD/HIV Services

自适应人工交付和数字 SUD/HIV 服务集成的优化方法

• 批准号: 10640292
• 负责人: Inbal Billie Nahum-Shani
• 金额: $ 41.99万
• 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/10640292
• 关键词: AIDS prevention; Acceleration; Address; Area; Behavioral; Clinical; Collaborations; Computer software; Data; Data Analytics; Development; Drug usage; Educational workshop; Effectiveness; Electronic Health Record; Experimental Designs; Generations; Goals; HIV; Hand; Health Technology; Human; Hybrids; Individual; Intervention; Joints; Journals; Methodology; Methods; Modality; Monitor; Motivation; National Institute of Drug Abuse; Patients; Peer Review; Persons; Publishing; Randomized; Risk; Sample Size; Scientist; Sequential Multiple Assignment Randomized Trial; Services; Software Tools; Specialist; Statistical Methods; Substance Use Disorder; Therapeutic; Time; Training; Work; adaptive intervention; analytical method; design; digital; digital delivery; digital intervention; digital technology; experimental study; flexibility; individualized prevention; innovation; intervention program; mHealth; multimodality; novel; prevention service; randomized trial; recovery services; scaffold; service delivery; substance use; synergism; telehealth; tool; treatment services; trial design; user friendly software; user-friendly

PROJECT SUMMARY: PROJECT 2 Advances in digital technologies (e.g., electronic health records, telehealth, and mobile health technologies) have created unprecedented opportunities to extend the reach and impact of adaptive services for individuals with or at risk for substance use disorders (SUD) and HIV. While services delivered by automated software tools, such as digital just-in-time adaptive interventions (JITAIs), are relatively inexpensive and can deliver support in the moment, insufficient engagement remains a major barrier. Human delivery of services can be more engaging but often more expensive and burdensome. Hence, the integration of digital and human- delivered services requires a trade-off between benefits and drawbacks that necessitates balancing effectiveness against scalability and sustainability. Understanding how to best leverage digital and human modalities to deliver adaptive interventions is critical for building effective and scalable SUD/HIV services. A major challenge is determining how best to use data to optimize the integration between intervention components that are human-delivered with a low intensity of adaptation (e.g., weekly, monthly) and those that are digitally delivered with a high intensity of adaptation (e.g., every minute or day). The long-term goal of the proposed project is to enable scientists to optimize Multimodality Adaptive Interventions (MADIs), in which both human-delivered and digital components are sequenced and adapted over time, at different time scales. To achieve this long-term goal, we will: (Aim 1) Develop a new, flexible trial design in which individuals can be randomized simultaneously to human-delivered and digital interventions at different time scales; (Aim 2) Develop new statistical methods for use with data from the new experimental design to address novel questions about synergies between human-delivered and digital services; (Aim 3) Develop sample size calculators to enable SUD/HIV scientists to plan novel experimental studies to address these questions; and (Aim 4) Place these methods directly into the hands of SUD/HIV scientists so that they can be readily applied to advance SUD/HIV prevention, treatment, and recovery services. We will conduct workshops for SUD/HIV scientists and publish both tutorials and applications in drug-use, HIV, and methodology outlets. We will work with the Dissemination and Training Core to develop free, user-friendly software that will enable SUD/HIV scientists to employ the new method in their own work. This project will provide the scaffolding to support evidence-driven integration and adaptation of human-delivered and digital services, accelerating a new generation of effective and scalable SUD/HIV interventions.

项目摘要：项目2 数字技术的进步（例如电子健康记录，远程医疗和移动健康技术） 已经创造了前所未有的机会，以扩大自适应服务对个人的影响和影响 有或有药物使用障碍（SUD）和HIV的风险。自动软件提供的服务 工具，例如数字即时自适应干预措施（JITAI），相对便宜，可以交付 目前的支持，参与度不足仍然是一个主要障碍。人类服务的服务可能是 更具吸引力，但通常更昂贵和繁重。因此，数字和人类的整合 交付的服务需要在福利和缺点之间进行权衡，这需要平衡 防止可伸缩性和可持续性的有效性。了解如何最好地利用数字和人类 提供自适应干预措施的方式对于建立有效且可扩展的SUD/HIV服务至关重要。一个 主要挑战是确定如何最好地使用数据来优化干预之间的集成 由低强度的适应性（例如，每周，每月）和那些人提供的组成部分 以高强度的适应性（例如每一分钟或一天）进行数字交付。长期目标 拟议的项目是使科学家能够优化多型自适应干预措施（MADIS），其中两者都 在不同的时间尺度上，对人提供的和数字组件进行了测序和调整。到 实现这一长期目标，我们将：（目标1）开发一种新的灵活的试验设计，个人可以在其中成为 在不同时间尺度上同时与人送和数字干预措施同时进行随机分组； （目标2） 开发新的统计方法与新实验设计的数据一起使用，以解决新颖 关于人类服务和数字服务之间的协同作用的问题； （目标3）发展样本量 计算器使SUD/HIV科学家能够计划新的实验研究以解决这些问题；和 （目标4）将这些方法直接放在SUD/HIV科学家的手中，以便可以轻松地应用它们 推进预防SUD/HIV，治疗和恢复服务。我们将为SUD/HIV举办研讨会 科学家并在药物使用，艾滋病毒和方法论中发表教程和应用。我们将工作 借助传播和培训核心，可以开发免费，用户友好的软件，以启用SUD/HIV 科学家在自己的工作中采用新方法。该项目将提供脚手架以支持 循证驱动的整合和适应人类和数字服务，加速了新的 产生有效且可扩展的SUD/HIV干预措施。