Analysis Plan
depression, anxiety
REGRESSIONS
First, differences between the included and excluded participants were established using descriptive statistics (mean and SD) and independent 2-tailed LCGA is commonly conducted using statistical software, such as MPlus and SAS; however, recent efforts have made it easier to conduct such analyses in open-source R software [Before investigating the relationship between use and symptom change, descriptive methods were used to explore use data, and regressions were run to understand the predictive values of different patient characteristics (eg, age and baseline severity) on each use metric. Then, to understand how different trajectories relate to use, mixed (between-factors and within-factors) ANOVAs were conducted to examine the role of time and class (PHQ and GAD) membership in use metrics. For the number of log-ins, length of use, number of reviews, number of activities, and percentage of programs viewed, five 3×5 mixed ANOVAs were conducted, with time as within-factor (3 levels: use in the first 4 weeks, 4-8 weeks, and 8-12 weeks) and class as between-factor (5 levels: the 5 trajectories identified). A total of 10 ANOVAs were run, 5 using the depression trajectories and 5 using the anxiety trajectories. All regressions and mixed ANOVAs were run using the R platform.