Statistical Analysis
viral suppression
SECONDARY
The primary analysis was per intention to treat. We first calculated participants’ monthly mean adherence scores and then analyzed these scores using linear mixed-effects models to assess the difference in mean adherence. Models included a random intercept and slope to account for the correlation within participants. A random intercept accounted for the clustering of individuals in health facilities, indicators defined treatment assignment, the month of analysis time (categorical), and interactions between the 2. Subsequently, we calculated the average difference in mean adherence between months 2 to 6 and 1 to 12 based on contrasts. We estimated odds ratios (ORs) for the difference in the proportion of participants with viral suppression at 6 and 12 months using logistic mixed-effect models. We conducted prespecified adjusted analyses of mean adherence and viral suppression, controlling for facility size, age, and sex. In post hoc sensitivity analyses, we adjusted for facility size, age, sex, self-reported baseline adherence, baseline SSQ-14 score, ART regimen, PHQ-9 score, WHO clinical stage, CD4 cell count, viral suppression, AUDIT-C score, MOS-SS score, and travel cost. We also assessed the difference in change from baseline in SSQ-14 and PHQ-9 scores using the same linear mixed-effects model as described previously but adjusted for the baseline score. We used the logistic mixed-effect models described previously to assess the difference in the proportion of participants with an SSQ-14 score of 9 or higher and a PHQ-9 score of 11 or higher at 3, 6, 9, and 12 months. We repeated analyses of primary and secondary outcomes using a per-protocol analysis, excluding participants who did not receive the allocated intervention and those with missing adherence data between months 2 to 6. Missing data were imputed using multiple imputation by chained equations.