Connecting to Support: How Use of an mHealth App Explains Antiretroviral Medication Adherence among People with HIV and Substance Use Disorders (Preprint)

Abstract

BACKGROUND Despite the increasing popularity of mobile health (mHealth) technologies, little is known about which types of mHealth system engagement might affect the maintenance of antiretroviral therapy (ART) among people with HIV (PWH) and substance use disorders (SUD). OBJECTIVE Using longitudinal and detailed system logs and weekly survey data, we tested a mediation model, where mHealth engagement indicators were treated as predictors, substance use and confidence in HIV management as joint mediators, and ART adherence as the outcome. We further distinguished the initiation and intensity of system engagement by mode (expression vs. reception) and by communication levels (intraindividual vs. dyadic vs. network). METHODS Tailored for PWH living with SUD, the mHealth app was distributed among 208 participants aged over 18 from two U.S. health clinics. Supervised by medical professionals, participants received weekly surveys through the app to report their health status and medication adherence data. System use was passively collected through the app, operationalized as transformed click-level data, aggregated weekly, and connected to survey responses with a 7-day lagged window. Linear regression and structure equation models (SEMs) with cluster-robust standard errors were employed for analyses, controlling within-person autocorrelation and group-level error correlations. Racial groups were examined as moderators in the SEMs to address specific research questions. RESULTS We found that 1) intensity, not initiation, of system use, 2) dyadic message expression and reception, and 3) network expression, positively predicted medication adherence via joint mediators (substance use and confidence in HIV management). However, intraindividual reception (i.e., re-reading saved entries for personal motivation) negatively predicts medication adherence via joint mediators. We also found Black participants have distinct usage patterns, suggesting the need to tailor mHealth interventions for this subgroup. CONCLUSIONS These findings highlight the importance of considering the intensity of system engagement, rather than initiation alone, when designing mHealth interventions for PWH and tailoring these systems to Black communities.