A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.

ABSTRACT:

Importance

The mechanisms by which engagement with internet-delivered psychological interventions are associated with depression and anxiety symptoms are unclear.

Objective

To identify behavior types based on how people engage with an internet-based cognitive behavioral therapy (iCBT) intervention for symptoms of depression and anxiety.

Design, setting, and participants

Deidentified data on 54 604 adult patients assigned to the Space From Depression and Anxiety treatment program from January 31, 2015, to March 31, 2019, were obtained for probabilistic latent variable modeling using machine learning techniques to infer distinct patient subtypes, based on longitudinal heterogeneity of engagement patterns with iCBT.

Interventions

A clinician-supported iCBT-based p

SUBMITTER: Chien I 

PROVIDER: S-EPMC7368176 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature