Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, USA.
Division of Disease Prevention, Virginia Department of Health, Richmond, VA, USA.
AIDS Behav. 2024 Aug;28(8):2708-2718. doi: 10.1007/s10461-024-04405-z. Epub 2024 Jun 13.
PositiveLinks (PL) is a mHealth platform to support care engagement by people with HIV (PWH). Daily reminders prompt the user to report medication adherence, mood, and daily stress. Higher response rate to PL check-ins has been associated with better suppression of viral load over 6-18 months. We conducted a retrospective chart review for a three-year period collecting demographic information, average mood and stress scores, and all viral loads obtained in usual patient care. We performed multivariable logistic regression modeling to identify factors associated with loss of viral load suppression and a time-to-event survival analysis until first unsuppressed viral load stratified by PL usage. Of the 513 PWH included, 103 had at least one episode of viral non-suppression. Low users of PL were more likely to have an unsuppressed viral load with an adjusted Odds Ratio (aOR) of 5.8 (95% CI 3.0-11.5, p < 0.001). Protective factors included older age (aOR 0.96; 95% CI 0.93-0.98, p = 0.003) and income above the federal poverty level (FPL) (aOR 0.996; 95% CI 0.995-0.998, p < 0.001). High PL use was also associated with better viral load suppression (VLS) over time (p < 0.0001 ((aHR) of 0.437 (95% CI 0.290-0.658, p < 0.001)) after adjusting for age and FPL. High stress scores were related to subsequent loss of viral suppression in an exploratory analysis. High check-in response rate on the PL app, older age, and higher income are associated with sustained VLS over time. Conversely, lack of response to check-ins or increased reported stress may signal a need for additional support.
PositiveLinks (PL) 是一个移动医疗平台，旨在支持艾滋病毒感染者（PWH）的护理参与。每日提醒提示用户报告药物依从性、情绪和日常压力。对 PL 签到的更高响应率与病毒载量抑制在 6-18 个月内更好相关。我们进行了一项为期三年的回顾性图表审查，收集人口统计学信息、平均情绪和压力评分，以及在常规患者护理中获得的所有病毒载量。我们进行了多变量逻辑回归建模，以确定与病毒载量抑制丧失相关的因素，并对使用 PL 的时间事件生存分析，直到根据 PL 使用分层的首次未抑制病毒载量。在 513 名 PWH 中，有 103 名至少有一次病毒载量未抑制。PL 的低使用者更有可能出现未抑制的病毒载量，调整后的优势比（aOR）为 5.8（95%CI 3.0-11.5，p<0.001）。保护因素包括年龄较大（aOR 0.96；95%CI 0.93-0.98，p=0.003）和收入高于联邦贫困线（FPL）（aOR 0.996；95%CI 0.995-0.998，p<0.001）。高 PL 使用也与随时间推移更好的病毒载量抑制（VLS）相关（p<0.0001（（aHR）为 0.437（95%CI 0.290-0.658，p<0.001））在调整年龄和 FPL 后。在探索性分析中，较高的压力评分与随后的病毒抑制丧失相关。PL 应用程序上的高签到响应率、年龄较大和较高收入与随时间持续的 VLS 相关。相反，对签到的无响应或报告的压力增加可能表明需要额外的支持。
