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.

项目概要 该提案旨在确定开发数据管理的可行性和可接受性 平台 (DMP) 专为试图识别年轻人饮酒的研究人员和卫生部门量身定制 未就读四年制大学的使用障碍 (AUD)。这是一个紧迫的研究领域；酒精率 年轻人中的滥用高峰。为了方便起见，大多数参与者样本都涉及年轻人 就读于四年制大学。迫切需要开展研究来确定患有 AUD 的年轻人中哪些人不患有 AUD？ 入读四年制大学，为他们提供潜在的干预措施并减少这种情况下的健康不平等 研究。 Facebook 和 Google 等顶尖科技公司已成为开发 DMP 的专家， 定位与产品相关的消费者，这些消费者在统计上有可能点击广告并购买该产品 产品。例如，制药公司可以使用符合 HIPAA 的 DMP 来识别移动设备 由统计上可能患有抑郁症的个人拥有（即“相似的受众群体定位”） 各种健康信息（例如药房声明）、数字行为（例如访问的网站）和人口数据集 帮助准确地改进何时、如何以及何种类型的抑郁症药物或相关广告的投放 每个设备以增加患者的兴趣。然而，据我们所知，不存在可以用来帮助解决问题的 DMP。 识别患有 AUD 的个人，以增加他们参与研究的人数。这意味着卫生部门和 试图识别和招募患有 AUD 的年轻人的研究人员需要亲自招募（即 耗时且缺乏可扩展性）或通过使用 Facebook 和其他广泛的传统 DMP， 效率低下且不是量身定制的（即，它浪费时间和金钱来支付将向许多人展示的广告 没有 OUD）。我们寻求创建（并评估其可行性和可接受性）第一个针对以下情况量身定制的 DMP： 研究人员和卫生部门试图识别未参加 4- 年学院。通过合作伙伴关系和初步研究，我们与行业广告合作开发 在 COVID-19 大流行期间，我们将利用我们团队的经验和数据 NIDA 资助的 SBIR 旨在帮助药物滥用研究人员，NIDA 资助的 R34 则建议患者 会发现这种方法可以接受。除了第一阶段的应用程序之外，这种方法可能会在以后进行扩展（并且 适合几乎所有临床条件）成为第一个已知的 DMP，用于增加参与者的注册 健康相关的研究。