Statistical Analysis
Descriptive statistics were used to summarize the sociodemographic characteristics and study outcomes of the participants at each time point. Baseline characteristics and study outcomes (1) between the intervention and control groups and (2) between participants who completed the study and those who did not (dropouts) were compared using Fisher exact tests for categorical variables or an independent samples The intention-to-treat principle was applied. Linear mixed effects models were used to assess the differential change in continuous outcomes (ie, scores on the CSES, SESS, and DASES). Similarly, generalized linear mixed effects models with logit links were used to analyze the binary outcomes (ie, intention to have chemsex, actual engagement in chemsex, undergone HIV testing, undergone other STI testing, practice of condomless sex during non-chemsex, and practice of condomless sex during chemsex in the last 3 months). Time, group, and interaction between group and time were included as independent variables. Mixed effects models can accommodate missing data and do not require imputation of missing observations, providing a natural way to deal with missing values or dropouts. For the main analysis, no covariates were put in the models. To supplement the main analysis, complete case analysis was conducted. Statistical analysis was performed using SPSS version 25.0 (IBM Corp, Armonk, NY). All statistical tests were 2-tailed, with a 5% level of statistical significance. The data set and analyses were checked by 2 researchers.