Latent Class Growth Analysis
Latent class models were constructed with an increasing number of classes, from 2 to 8 (Tables S3 and S4). The goodness-of-fit was assessed using Bayesian information criterion for each model to determine the optimal number of classes. In addition, the interpretability of the identified trajectories as well as their clinical meaningfulness were considered when choosing a model. On the basis of Bayesian information criterion index and theoretical considerations, the models with 5 classes were chosen for both the PHQ-9 and GAD-7.