A Novel Platform to Identify and Treat Transitional Age Youth With Alcohol Use Disorder

识别和治疗患有酒精使用障碍的过渡年龄青少年的新平台

• 批准号: 10761094
• 负责人: Renee Garett
• 金额: $ 27.06万
• 依托单位: ELEVATEU
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10761094
• 关键词: 21 year old; Address; Adherence; Advertisements; Advertising; Age; Alcohol abuse; Area; Artificial Intelligence; Behavior; COVID-19 pandemic; COVID-19 risk; Charge; Clinical; Communication; Consumption; Control Groups; Data; Data Set; Devices; Eligibility Determination; Enrollment; Environment; European Union; Facebook; Funding; Health; Health Benefit; Health Insurance Portability and Accountability Act; Individual; Industry; Infrastructure; Intervention; Laws; Learning; Machine Learning; Marketing; Mental Depression; Methods; Modeling; National Institute of Drug Abuse; Nature; Participant; Patients; Persons; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacy facility; Phase; Pilot Projects; Population; Prevalence; Privacy; Process; Public Health; Research; Research Personnel; Respondent; Sampling; Services; Shoes; Small Business Innovation Research Grant; Surveys; Technology; Time; Visit; Vulnerable Populations; Work; Youth; acceptability and feasibility; alcohol misuse; alcohol related consequences; alcohol use disorder; artificial intelligence method; binge drinking; college; commercialization; cost; data de-identification; data management; design; digital; experience; feasibility testing; handheld mobile device; health inequalities; improved; interest; machine learning model; model design; novel; outreach; participant enrollment; prevent; recruit; stay-at-home order; substance use; technology development; wasting; web site; young adult; young adult alcohol use

Project Summary This proposal seeks to determine the feasibility and acceptability of developing a data management platform (DMP) tailored for researchers and health departments attempting to identify young adults with alcohol use disorder (AUD) who are not enrolled in 4-year colleges. This is an urgent area of research; rates of alcohol misuse peak among young adults. Due to convenience, most participant samples have involved young adults enrolled in 4-year colleges. Research is urgently needed to identify young adults with AUD who are not enrolled in 4-year colleges to provide them with potential interventions and reduce the health inequity of this research. Top technology companies, such as Facebook and Google, have become experts at developing DMPs that target consumers relevant to a product who are statistically likely to click on advertisements and purchase the product. For example, pharmaceutical companies can use a HIPAA-compliant DMP to identify mobile devices owned by individuals statistically likely to have depression (i.e., “look-alike audience targeting) by referencing a variety of health (e.g., pharmacy claims), digital behavior (e.g, websites visited) and demographic datasets to help improve precisely when, how, and what type of depression medication or related advertisement to deliver to each device to increase patient interest. However, to our knowledge, no DMP exists that can be used to help identify individuals with AUD to increase their enrollment in research. This means that health departments and researchers attempting to identify and enroll young adults with AUD need to either recruit in person (which is time-consuming and lacks scalability) or through the use of Facebook and other broad traditional DMPs, which is inefficient and not tailored (i.e., it wastes time and money paying for ads that will be shown to many people without OUD). We seek to create (and evaluate the feasibility and acceptability of) the first DMP tailored for researchers and health departments attempting to identify young adults with AUD who are not enrolled in 4- year colleges. Through partnerships and preliminary research we have developed with industry advertising partners during the COVID-19 pandemic, we will leverage our team’s experience and data from previous NIDA-funded SBIRs to help substance use researchers, and a NIDA-funded R34 suggesting that patients would find this approach acceptable. Beyond this Phase 1 application, this approach might later be scaled (and tailored to almost all clinical conditions) to be the first known DMP for increasing enrollment of participants to health-related research.

项目摘要 该建议旨在确定开发数据管理的可行性和可接受性 为研究人员和卫生部门量身定制的平台（DMP）试图识别酒精的年轻人 使用未入学的4年大学的使用障碍（AUD）。这是一个紧迫的研究领域；酒精速率 滥用年轻人的峰值。由于便利，大多数参与的样本涉及年轻人 参加了4年的大学。迫切需要进行研究才能识别出没有AUD的年轻人 入学4年的大学，为他们提供潜在的干预措施并减少健康不平等 研究。 诸如Facebook和Google之类的顶级技术公司已成为开发DMP的专家 与产品相关的目标消费者在统计上有可能点击广告并购买 产品。例如，制药公司可以使用符合HIPAA的DMP来识别移动设备 通过统计学上的个人拥有抑郁症（即“与观众相似的目标））拥有 健康的多样性（例如，药房索赔），数字行为（例如，访问的网站）和人口数据集 有助于精确改善何时，如何和哪种类型的抑郁症药物或相关广告以交付 到每个设备增加患者兴趣。但是，据我们所知，不存在可用于帮助的DMP 确定具有AUD的人以增加研究入学率。这意味着卫生部门和 试图识别和招募有AUD的年轻人需要亲自招募的研究人员（就是 耗时且缺乏可扩展性）或通过使用Facebook和其他广泛的传统DMP， 效率低下且不量身定制（即，它浪费了时间和金钱为许多人展示的广告支付费用 没有OUD）。我们寻求创建（并评估）第一个针对的DMP的可行性和可接受性 研究人员和卫生部门试图识别未入学4-的年轻人的年轻人 年学院。通过伙伴关系和初步研究，我们与行业广告开发了 在Covid-19大流行期间的合作伙伴，我们将利用团队的经验和以前的数据 NIDA资助的Sbirs可帮助吸毒研究人员，而NIDA资助的R34表明患者 可以发现这种方法可以接受。除了此阶段1应用程序之外，该方法稍后可能会缩放（并且 根据几乎所有临床状况量身定制）是将参与者入学到的第一个已知DMP 与健康有关的研究。