Statistical analyses

First, we will compare baseline scores between the treatment group and TAU group on all primary and secondary outcome measurements, using chi-squared tests and two-sample t tests, for categorical and continuous variables, respectively. In order to estimate significant changes over time as a result of the intervention for all primary and secondary outcome measures, we will employ hierarchical linear modelling (HLM). Analyses will be based on an intent-to-treat population, where critically HLM allows the number of observations to vary between participants and effectively handles missing data by calculating estimates of trajectories using maximum likelihood estimation. Time (linear and quadratic), treatment condition, and their interaction will be included in the models, where we will also examine how covariate factors such as age, biological sex, education level, and asylum status explain variance within the data. Here, similar models will be employed for the primary and secondary outcome measures, and we will conservatively correct for multiple comparisons where appropriate. Specifically, the level 1 model will characterize within-patient change over time, and the level 2 model will predict variation of within-patient change over time and between-patient variables.

We will also examine whether treatment success can be predicted from baseline clinical measures and individual differences using machine learning methods, including non-linear random forest regressions and linear ordinary least squares model with lasso regularization (OLS-LASSO).

In regard to qualitative data, interviews of the sub-sample will be transcribed verbatim and will be analyzed using thematic analysis [45]. The thematic analysis approach is a method for identifying, analyzing, and reporting themes within data. The in-depth interviews will be analyzed independently by two researchers, and inter-rater reliability will be calculated. The results from the interviews following the online training tool will be analyzed with the same methodological approach.