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、远程医疗和移动医疗技术） 创造了前所未有的机会来扩大个人适应性服务的范围和影响 患有物质使用障碍 (SUD) 和 HIV 或有风险。虽然服务由自动化软件提供 数字化即时适应性干预措施 (JITAI) 等工具相对便宜，并且可以提供 目前的支持，参与不足仍然是一个主要障碍。人类提供的服务可以是 更有吸引力，但往往更昂贵和繁重。因此，数字化和人性化的融合 提供的服务需要在优点和缺点之间进行权衡，从而需要平衡 针对可扩展性和可持续性的有效性。了解如何最好地利用数字和人力 提供适应性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利用数据来优化干预措施之间的整合 人工提供的低适应强度（例如每周、每月）的成分以及那些 以数字方式交付，具有高强度的适应能力（例如，每分钟或每天）。该组织的长期目标 拟议的项目旨在使科学家能够优化多模态适应性干预（MADI），其中两者 人工交付的和数字的组件会随着时间的推移、在不同的时间尺度上进行排序和调整。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，使个人能够 在不同时间尺度同时随机进行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，以解决新的问题 关于人工提供的服务和数字服务之间的协同作用的问题； （目标 3）制定样本量 计算器使 SUD/HIV 科学家能够计划新颖的实验研究来解决这些问题；和 （目标 4）将这些方法直接交到 SUD/HIV 科学家手中，以便它们可以轻松应用 推进 SUD/HIV 预防、治疗和康复服务。我们将为 SUD/HIV 举办研讨会 科学家并在药物使用、艾滋病毒和方法论方面发表教程和应用。我们将工作 与传播和培训核心一起开发免费的、用户友好的软件，以支持 SUD/HIV 科学家们在自己的工作中采用了新方法。该项目将提供脚手架来支持 证据驱动的人工服务和数字服务的整合和调整，加速了新的 产生有效且可扩展的 SUD/HIV 干预措施。