Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Mayo Clinic, Rochester, MN, USA.
AIDS Behav. 2022 Jul;26(7):2229-2241. doi: 10.1007/s10461-021-03569-2. Epub 2022 Jan 11.
HIV researchers use short messaging service (SMS)-based surveys to monitor health behaviors more closely than what would be possible with in-person assessment. Benefits are tempered by nonresponse to completing surveys. Understanding response patterns and their associated study participant characteristics would guide more tailored use of SMS-based surveys for HIV studies. We examined response to weekly 7-item SMS surveys administered as part of an HIV prevention trial. Using Mixture hidden Markov models (MHMM), we identified the underlying response patterns shared by subgroups of participants over time and quantified the association between these response patterns and participant characteristics. Three underlying response patterns were identified; responders, responders with phone-related errors, and non-responders. Non-responders versus responders were more likely to be younger, male, cis-gender, Black and Latinx participants with histories of homelessness, incarceration, and social support service utilization. Responders with phone-related errors compared to non-responders were more likely to be Black, Latinx, female, students, and have a history of incarceration and social support service utilization. More nuanced results from MHMM analyses better inform what strategies to use for increasing SMS response rates, including assisting in securing phone ownership/service for responders with phone-related errors and identifying alternative strategies for non-responders. Actively collecting and monitoring non-delivery notification data available from SMS gateway service companies offers another opportunity to identify and connect with participants when they are willing but unable to respond during follow-up.
艾滋病毒研究人员使用基于短消息服务（SMS）的调查来更密切地监测健康行为，这比面对面评估所能做到的更加有效。但是，由于无法完成调查，这一优势受到了限制。了解响应模式及其相关的研究参与者特征将指导更有针对性地使用基于 SMS 的调查来进行 HIV 研究。我们研究了作为艾滋病毒预防试验的一部分，每周通过 7 项短信调查的回复情况。使用混合隐马尔可夫模型（MHMM），我们确定了随时间变化的参与者亚组之间共享的基本响应模式，并量化了这些响应模式与参与者特征之间的关联。确定了三种基本的响应模式：响应者、有手机相关错误的响应者和非响应者。非响应者与响应者相比，更有可能是年轻、男性、顺性别、黑人以及拉丁裔参与者，他们有过无家可归、监禁和社会支持服务利用的经历。与非响应者相比，有手机相关错误的响应者更有可能是黑人、拉丁裔、女性、学生，并且有过监禁和社会支持服务利用的经历。来自 MHMM 分析的更细致的结果更好地说明了使用哪些策略来提高 SMS 响应率，包括协助有手机相关错误的响应者获得手机所有权/服务，并为非响应者确定替代策略。积极收集和监测来自 SMS 网关服务公司的未送达通知数据，为在随访期间愿意但无法回复的参与者提供了另一个联系和联系他们的机会。
