Digital Health and Engagement—Looking Behind the Measures and Methods

Low real-world engagement with digital mental health therapy programs and apps is a perennial concern that is only now receiving due research attention. The study by Chien et al 1 is a welcome addition to the literature given its focus on understanding the association between patient engagement, an internet-based cognitive behavioral therapy intervention for depression and anxiety, and clinical outcomes. Using a probabilistic latent variable model to infer distinct subtypes of patients based on their interaction with the internet-based cognitive behavioral therapy program, the authors identify 5 clusters of patients: low engagers, late engagers, high engagers with rapid disengagement, high engagers with moderate decrease, and highest engagers. Overall, the results are consistent with the literature on digital health engagement: highest engagers represented just 10.6% of the sample.