Statistical analysis
depression, anxiety
REGRESSION, SECONDARY
To evaluate secondary outcomes from the embedded randomization trial, analyses were conducted in Stata 14.2 on an intention-to-treat basis, meaning that data were retained from all participants who were included in the study, regardless of adherence, so as to maintain experimental control of the study outcomes. Multiple imputation by chained equations (20 datasets) was employed, conducted separately for each condition to preserve interactions (HP vs. TAU), and using the following predictors in addition to symptom scores as decided a priori: age, sex, participation in MI (yes/no), and clinic (A vs. B). Using the multiply imputed data, change in depression symptoms, anxiety, and the total unhealthy lifestyle behaviors score was analyzed in a linear mixed-effects regression framework. These models were fitted using maximum likelihood estimation and included a random intercept and the fixed effects of time (baseline = 0, 10 weeks = 1), group (TAU =  0, HP = 1), and the time × group interaction. Standardized effects are reported in terms of Cohen’s d. Between-group effect sizes were calculated as the time × group coefficient divided by the pooled observed endpoint standard deviation, and within-group effects were calculated as the model-implied change score divided by the observed change score’s standard deviation. For the d statistic, absolute values around 0.20 are usually regarded as small, 0.50 as moderate, and 0.80 as large (Cohen, 