Statistical analyses
SECONDARY
Descriptive statistics were calculated for baseline demographic measures, retention rates, and all outcomes. The generalized linear model with logit link was used for investigating the predictors for non-completers at 12 weeks and 52 weeks. Primary outcomes were treatment adherence, study retention, treatment satisfaction, and change in ActiGraph-measured daily steps from baseline to 12 weeks. Changes in ActiGraph-measured daily steps from baseline to 52 weeks, ActiGraph-measured daily MVPA minutes from baseline to 12 weeks and baseline to 52 weeks, SSE from baseline to 12 weeks and baseline to 52 weeks, and Fitbit-measured daily steps and active minutes aggregated across the 12-week intervention period and 40-week post-intervention period were secondary outcomes.For the missing ActiGraph accelerometer data, the generalized estimating equation model (GEE) [For the SSE data, the missing data were not in a monotonic pattern and thus assumed to be missing at random (MAR). Multiple imputations were conducted for the missing values based on the Markov Chain Monte Carlo method. The final results from the imputed data were based on 10 imputed data sets [Missing Fitbit step data and corresponding active minutes data were not in a monotonic pattern and thus assumed to be missing at random (MAR), and the aforementioned methods were applied. Two-sample A two-sample 