A wrist biosensor-based mHealth suite to support alcohol intervention in young people living with HIV

基于腕部生物传感器的移动医疗套件，支持对感染艾滋病毒的年轻人进行酒精干预

• 批准号: 10678994
• 负责人: Yan Wang
• 金额: $ 9.48万
• 依托单位: FLORIDA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-10 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10678994
• 关键词: Address; Adherence; Adolescent; Affect; Age; Alcohol consumption; Alcohols; Algorithms; Anxiety; Behavioral Research; Behavioral Sciences; Biological Markers; Biosensor; Blood; Blood alcohol level measurement; Caring; Cellular Phone; Chronic Disease; Clinical Trials Design; Cognitive; Computer software; Consumption; Data; Detection; Development; Disease Management; Distal; Ecological momentary assessment; Elements; Ethnic Origin; Feedback; Fostering; Foundations; Funding; Future; Gender Identity; Goals; HIV; HIV Infections; HIV diagnosis; Health; High Prevalence; Hour; Informal Social Control; Intervention; Laboratories; Literature; Medical; Mental Depression; Mental Health; Modeling; Monitor; National Institute on Alcohol Abuse and Alcoholism; Outcome; Participant; Patient Self-Report; Pattern; Persons; Population; Race; Randomized; Reporting; Research; Rewards; Self Management; Subgroup; Substance abuse problem; Symptoms; Testing; Time; Viral; Work; Wrist; Youth; age group; aged; alcohol intervention; biological sex; comorbidity; drinking; emerging adult; follow-up; improved; innovation; mHealth; machine learning algorithm; machine learning model; programs; randomized trial; sensor; sensor technology; substance use; theories; time use; tool; transmission process; wearable device

ABSTRACT 1 Despite the overall decline in new HIV infections in U.S., adolescents and emerging adults aged 13 to 29 2 remain disproportionately affected by HIV who account for 37% of all new HIV diagnoses. Alcohol use is more 3 common among young people living with HIV (YPLWH) than other age groups, creating a significant barrier for 4 mitigating transmission, achieving viral suppression, and reducing comorbidities. Despite the high prevalence 5 of alcohol use and its detrimental consequences in this population, developmentally-tailored intervention 6 targeting alcohol use in YPLWH is rare. Self-management emerged as an important strategy in the context of 7 medical adherence and chronic disease management, with self-monitoring and personalized feedback being 8 two key elements to improve health outcomes including alcohol use. Recent development of wrist alcohol 9 sensors provides a promising tool for self-monitoring and feedback based on objective data. However, two 10 critical challenges must be addressed to leverage biosensors in alcohol intervention for YPLWH. First, without 11 existing analysis software, accurate detection of alcohol use (e.g., start time, consumption level) based wrist 12 sensor data remains a significant barrier. Some literature also suggests that HIV may impact blood alcohol 13 concentration, so a detection algorithm specific to this population is needed. Second, engagement in mobile 14 health (mHealth), including wearables in youth, is suboptimal. To address these challenges and to achieve the 15 overall P01 goal to improve self-management of alcohol use and HIV care among YPLWH, we propose to 16 develop the first wrist biosensor-based mHealth suite for alcohol use monitoring with tailored detection 17 algorithem and optimized engagement strategies for YPLWH. We will conduct a 30-day micro-randomized trial 18 (MRT)--a clinical trial design for developing and optimizing mHealth interventions, to innovatively and efficiently 19 address the challenges. YPLWH will be asked to wear the Skyn biosensor for 30 days and report alcohol use 20 via smartphone-based ecological momentary assessment (EMA). They will also be micro-randomized twice 21 daily to test two empirically-based engagement strategies – reciprocity and personalized feedback. Data from 22 the 30-day MRT will be used to (a) develop and validate machine learning algorithm for alcohol detection 23 based on Skyn data; and (b) test which engagement strategy works better, for whom and under what 24 conditions in facilitating proximal engagement with the sensor. We will also collect alcohol biomarker (i.e., 25 PEth) at 1-month follow up, which will allow us to (c) explore the potential impact of sensor engagement (and 26 thus self-monitoring) on distal alcohol use. By trial end, we will have the first integrated, optimized, and 27 developmentally appropriate biosensor-based mHealth suite for alcohol self-monitoring that can be used as the 28 foundation for future alcohol interventions in YPLWH. Findings from this project may also inform the 29 development of new translational behavioral research model to guide adolescent and YPLWH research 30 agenda by leveraging powerful sensing technology to improve self-management in an engaging manner.

摘要 1尽管美国新感染艾滋病毒的人数总体下降，13至29岁的青少年和初成年人 2仍然不成比例地受到艾滋病毒的影响，占所有新艾滋病毒诊断的37%。酒精使用更多 艾滋病毒感染者（YPLWH）比其他年龄组更常见， 4减轻传播，实现病毒抑制，减少合并症。尽管患病率很高， 5酒精使用及其在这一人群中的有害后果，发展定制的干预 6在YPLWH中针对酒精使用是罕见的。自我管理作为一种重要的战略出现， 7医疗依从性和慢性病管理，自我监测和个性化反馈， 8改善健康结果的两个关键因素，包括酒精使用。腕部酒精的最新发展 9传感器为基于客观数据的自我监测和反馈提供了一个很有前途的工具。然而两 必须解决10个关键挑战，以利用生物传感器对YPLWH进行酒精干预。首先，如果没有 11个现有的分析软件，准确检测酒精使用（例如，开始时间、消耗水平）的手腕 12传感器数据仍然是一个重大障碍。一些文献还表明，艾滋病毒可能会影响血液酒精含量 13浓度，因此需要特定于该群体的检测算法。第二，参与移动的 14健康（mHealth），包括年轻人的可穿戴设备，是次优的。为了应对这些挑战， 15总体P01目标是改善YPLWH中酒精使用的自我管理和艾滋病毒护理，我们建议 16开发第一个基于手腕生物传感器的mHealth套件，用于酒精使用监测和定制检测 17算法和优化的参与策略YPLWH。我们将进行为期30天的微随机试验 18（MRT）--一项用于开发和优化移动健康干预措施的临床试验设计， 19应对挑战YPLWH将被要求佩戴Skyn生物传感器30天，并报告酒精使用情况 20通过基于智能手机的生态瞬时评估（EMA）。他们还将被微随机化两次 每天21次，以测试两种基于经验的参与策略-互惠和个性化反馈。数据从 22 30天的MRT将用于（a）开发和验证用于酒精检测的机器学习算法 23基于Skyn数据;以及（B）测试哪种参与策略更有效，对谁有效，在什么情况下有效 24个条件以促进与传感器的近端接合。我们还将收集酒精生物标志物（即， 25 PEth），这将使我们能够（c）探索传感器接合的潜在影响（以及 26因此自我监测）远端酒精使用。到试验结束时，我们将拥有第一个集成、优化和 27开发适当的基于生物传感器的mHealth套件，用于酒精自我监测，可用作 28为YPLWH未来的酒精干预奠定基础。该项目的调查结果也可能为 29发展新的转化行为研究模式，以指导青少年及青少年爱滋病及家庭健康研究 30议程，利用强大的传感技术，以参与的方式改善自我管理。