MyPEEPS Mobile LITE: Limited Interaction Efficacy Trial of MyPEEPS Mobile to Reduce HIV Incidence and Better Understand the Epidemiology of HIV among YMSM

项目摘要 迫切需要更好地了解美国艾滋病毒感染的流行病学， 特别是在同性恋、双性恋和其他男男性行为者（MSM）中， 艾滋病毒/艾滋病是结束艾滋病毒流行（EHE）倡议的重要目标。作为对RFA-AI-21-018的直接回应， 这项研究将利用创新技术招募和留住大批高风险、艾滋病毒阴性的年轻人 男男性行为者，重点关注种族/族裔少数男男性行为者和艾滋病毒高流行率 地理区域（称为“热点”）。此外，我们将利用这一群体进行大规模的 临床试验，同时维持标准治疗对照组作为纵向观察队列， 流行病学分析。我们的研究团队定位独特，拥有所有相关专业知识， 这项研究已经成功地招募和保留了12,000多名YMSM， 艾滋病毒连续体的研究（例如，流行病学，干预措施的发展，移动健康，PrEP，临床试验， 创新的地理空间方法）。我们已经取得了具体的成功进行预防研究与YMSM （17-25岁），包括种族和民族多样化的YMSM，我们的目标人口群体。您因前述 以前利用先进的社交媒体广告技术和创新的地理空间分析 瞄准/研究“社区中的社区”，从不同的地理位置接触难以接触的YMSM 区域（例如，农村邮政编码，美国部落土地等）和年轻的年龄（例如，YMSM 13-18岁）。我们将 在36个月的招募期间，利用创新技术招募，然后保留一个大的队列（N = 17-25岁的青年男男性接触者中，大多数是黑人和拉丁美洲人，他们是艾滋病毒传播的高危人群 (e.g.,无避孕套肛交史），此后每6个月随访一次。我们将进行一次全面的 虚拟数字临床试验（具体目标#1）测试MyPEEPS移动的（一种基于证据的mHealth HIV 预防干预）降低艾滋病毒阴性YMSM（17-25岁）的艾滋病毒发病率， 理论驱动的社会、生态和地理空间因素对干预吸收和效果的影响 包括与传统的行为改变模型（如信息动机）相一致的措施 行为模型。一个社会生态理论框架也将指导纵向分析， 在2,500名对照组受试者中进行的观察性队列研究（特定目标#2），旨在评估个体、网络 地理空间和公共政策与艾滋病毒风险和寻求健康行为的相关性（例如，PrEP摄取）比较 艾滋病毒抗体呈阳性的人与未呈阳性的人之间的差异。干预影响。这一发现 研究将对研究和实践产生重要的现实影响。例如，了解如何 个人、网络、地理空间和公共政策因素与艾滋病毒的发病率和中度相关 干预效果将有助于告知应如何以及在何处提供干预。

PROJECT SUMMARY There is a critical need to better understand the epidemiology of HIV acquisition in the United States (US), particularly among cisgender gay, bisexual and other men who have sex with men (MSM), one of the key populations essential to target for End the HIV Epidemic (EHE) initiatives. In direct response to RFA-AI-21-018, this study will use innovative technology to recruit and retain a large cohort of high-risk, HIV-negative young men who have sex with men (YMSM) focusing on racial/ethnic minority YMSM and high HIV prevalence geographic areas (known as “hot spots”). Furthermore, we will leverage this cohort to conduct a large-scale clinical trial while maintaining the standard of care control arm as a longitudinal observational cohort for epidemiologic analyses. Our study team is uniquely positioned and has all the relevant expertise to conduct this study having successfully recruited and retained more than 12,000 YMSM in a full range of research studies across the HIV continuum (e.g., epidemiology, intervention development, mHealth, PrEP, clinical trials, innovative geospatial methods). We have had specific success conducting prevention research with YMSM (17-25 years), including racially and ethnically diverse YMSM, our target demographic group. Further, we have previously leveraged advanced social media advertising techniques and used innovative geospatial analytics to target/study “communities within communities”, reaching hard-to-reach YMSM from diverse geographic areas (e.g., rural zip codes, U.S. tribal lands, etc.) and young ages (e.g., YMSM 13-18 years of age). We will harness innovative technology to recruit, during 36-months of enrollment, and then retain a large cohort (N = 5,000) of 17-25 year old YMSM, the majority being Black and Latino, who are at high-risk of HIV transmission (e.g., history of condomless anal sex) and follow them every 6 months thereafter. We will conduct an entirely virtual, digital clinical trial (Specific Aim #1) testing whether MyPEEPS Mobile (an evidence-based mHealth HIV prevention intervention) reduces HIV incidence among HIV-negative YMSM (17-25 years old) looking at the influence of theory-driven social, ecological, and geospatial factors on intervention uptake and efficacy inclusive of measures that align with traditional models of behavior change such as the Information Motivation Behavior Model. A social-ecological theoretical framework will also guide the analysis of the longitudinal observational cohort study (Specific Aim #2) of the 2,500 control arm participants to assess individual, network, geospatial, and public policy correlates of HIV risk and health seeking behaviors (e.g., PrEP uptake) comparing individuals who become HIV-positive to those who do not. Intervention Implications. The findings from this research will have important real-world implications for research and practice. For example, understanding how individual, network, geospatial, and public policy factors correlate with HIV incidence and moderate intervention effects will help inform how and where interventions should be delivered.