Who engages? Machine learning insights into digital mindfulness-based intervention for generalized anxiety disorder.

ABSTRACT:

Background

Although mindfulness ecological momentary interventions (MEMI) appear effective in alleviating worry symptoms, treatment engagement remains suboptimal. Determining baseline variables of MEMI over self-monitoring placebo (SM) can inform tailored interventions for individuals with generalized anxiety disorder (GAD).

Method

Machine meta-learning methods (ML) were applied to predict two-week engagement (log-transformed number of prompts completed) among individuals randomized to MEMI or SM (N = 110). Sixteen baseline variables comprised the predictor set: clinical, demographic, process, and executive functioning (EF) factors. Random forest using a five-fold nested cross-validation approach mitigated overfitting. X-learner meta-algorithms estimated conditional average

SUBMITTER: Zainal NH 

PROVIDER: S-EPMC12933389 | biostudies-literature | 2026 Apr

REPOSITORIES: biostudies-literature