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: 10267870
• 负责人: Inbal Billie Nahum-Shani
• 金额: $ 44.42万
• 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/10267870
• 关键词: AIDS prevention; Address; Area; Behavioral; Clinical; Collaborations; Computer software; Data; Data Analytics; Development; Drug usage; Educational workshop; Effectiveness; Electronic Health Record; Equilibrium; 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; Recovery; Risk; Sample Size; Scientist; Sequential Multiple Assignment Randomized Trial; Services; Software Tools; Specialist; Statistical Methods; Substance Use Disorder; Technology; Therapeutic; Time; Training; Work; adaptive intervention; analytical method; design; digital; digital intervention; experimental study; flexibility; individualized prevention; innovation; intervention program; mHealth; multimodality; novel; randomized trial; scaffold; service delivery; substance use; synergism; telehealth; tool; 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.

项目概要：项目2 数字技术的进步（例如，电子健康记录、远程保健和移动的保健技术） 创造了前所未有的机会，扩大了适应性服务对个人的影响和影响， 有物质使用障碍（SUD）和艾滋病毒或有物质使用障碍和艾滋病毒风险的患者。虽然自动化软件提供的服务 数字化即时适应性干预（JITAIs）等工具相对便宜， 在目前的支持方面，参与不足仍然是一个主要障碍。人力资源服务可以 更吸引人，但往往更昂贵和负担。因此，数字化和人性化的融合- 提供的服务需要在利益和缺点之间进行权衡，这需要平衡 有效性与可扩展性和可持续性之间的差距。了解如何最好地利用数字和人力资源 提供适应性干预措施的模式对于建立有效和可扩展的可持续性发展/艾滋病毒服务至关重要。一 一个主要的挑战是确定如何最好地利用数据来优化干预之间的整合 以低适应强度由人递送的组分（例如，每周，每月）和那些 是以高适应强度数字化传递的（例如，每一分钟或每一天）。的长期目标 拟议的项目是使科学家能够优化多模态适应性干预（MADI），其中 人工交付和数字组件在不同的时间尺度上随着时间的推移进行排序和调整。到 为了实现这一长期目标，我们将：（目标1）开发一种新的、灵活的试验设计， 在不同的时间尺度上同时随机接受人工干预和数字干预;（目标2） 开发新的统计方法，用于新实验设计的数据，以解决新的 关于人工交付和数字服务之间协同作用的问题;（目标3）确定样本规模 计算器，使SUD/HIV科学家能够计划新的实验研究来解决这些问题; (Aim 4）将这些方法直接交给SUD/HIV科学家，以便他们可以随时应用 推进SUD/艾滋病毒预防、治疗和康复服务。我们将举办关于SUD/HIV的讲习班 科学家和出版教程和应用在药物使用，艾滋病毒，和方法出口。我们将 与传播和培训中心合作，开发免费、用户友好的软件， 科学家们在他们自己的工作中使用这种新方法。本项目将提供脚手架支撑 以证据为驱动的人工交付和数字服务的整合和调整，加速新的 制定有效和可扩展的可持续性青年发展/艾滋病毒干预措施。