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

基本信息

批准号：
10304696
负责人：
Yan Wang
金额：
$ 11.94万
依托单位：
FLORIDA STATE UNIVERSITY
依托单位国家：
美国
项目类别：
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/10304696
关键词：
Address Adherence Adolescent Affect 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 Machine Learning Medical Mental Depression Mental Health Modeling Monitor National Institute on Alcohol Abuse and Alcoholism Outcome Participant Patient Self-Report Pattern Population Race Randomized Reporting Research Rewards Self Management Subgroup Substance abuse problem Symptoms Testing Time Viral Work Wrist Youth age group aged alcohol intervention base biological sex comorbidity drinking emerging adult follow-up improved innovation mHealth machine learning algorithm programs randomized trial sensor sensor technology substance use time use tool transmission process wearable sensor technology

项目摘要

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.

抽象的 1 尽管美国新发艾滋病毒感染人数总体下降，但 13 至 29 岁的青少年和新兴成年人 2 人仍然受到艾滋病毒影响，占所有新诊断艾滋病毒的 37%。 3 感染艾滋病毒的年轻人 (YPLWH) 比其他年龄组更常见，这对 4 尽管患病率很高，但仍能减少传播、抑制病毒并减少合并症。 5 酒精使用及其对该人群的有害后果，针对发展的干预措施 6 针对 YPLWH 的饮酒情况很少出现自我管理作为重要策略的情况。 7 医疗依从性和慢性病管理，包括自我监测和个性化反馈 8 改善健康结果的两个关键要素包括饮酒的最新发展。 9 传感器提供了一种很有前景的基于客观数据的自我监控和反馈工具。首先，必须解决利用生物传感器对 YPLWH 进行酒精干预的 10 个关键挑战。现有11个分析软件，基于手腕准确检测酒精使用情况（例如开始时间、消耗程度） 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中的酒精含量。 13 集中，因此需要针对该人群的检测算法其次，移动端的参与度。 14 健康（移动健康），包括青少年的可穿戴设备，不足以应对这些挑战并实现目标。 15 总体 P01 目标是改善 YPLWH 的饮酒自我管理和艾滋病毒护理，我们建议 16 开发首个基于腕部生物传感器的 mHealth 套件，用于通过定制检测来监测酒精使用情况针对 YPLWH 的 17 种算法和优化参与策略我们将进行为期 30 天的微观随机试验。 18 (MRT)——用于开发和优化移动医疗干预措施的临床试验设计，以创新和高效的方式 19 号应对挑战。 YPLWH 将被要求佩戴 Skyn 生物传感器 30 天并报告饮酒情况。 20 通过基于智能手机的生态瞬时评估（EMA），它们也将被微随机化两次。每天 21 日测试两种基于经验的参与策略 - 互惠和个性化反馈数据。 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) 测试哪种参与策略对谁以及在什么情况下效果更好促进与传感器的近端接触的 24 种条件我们还将收集酒精生物标记物（即， 25 PEth）在 1 个月的随访中，这将使我们能够（c）探索传感器参与的潜在影响（以及 26 因此自我监测）在试用结束时，我们将进行第一个集成、优化和分析。 27 适合发育的基于生物传感器的 mHealth 套件，用于酒精自我监测，可用作 28 YPLWH 未来酒精干预基金会该项目的调查结果也可能为 YPLWH 提供信息。 29 开发新的转化行为研究模型来指导青少年和 YPLWH 研究 30 议程利用强大的传感技术以一种引人入胜的方式改善自我管理。