Examining early adherence measures as predictors of subsequent adherence in an intensive longitudinal study of individuals in mutual help groups: One day at a time.

Traditional and machine learning approaches can be used concurrently to examine several methods of predicting EMA adherence based on early assessment completion. Future studies could investigate the use of several algorithms in real time to help improve participant adherence rates by monitoring early adherence and using early assessment completion as features in predictive modeling.