09-08-2021 | ORIGINAL PAPER
App-Based Mindfulness Training for Adolescent Rumination: Predictors of Immediate and Cumulative Benefit
Gepubliceerd in: Mindfulness | Uitgave 10/2021Log in om toegang te krijgen
Rumination is a transdiagnostic risk factor for depression and anxiety, which surge during the adolescent years. Mindfulness training—with its emphasis on metacognitive awareness and present-moment attention—may be effective at reducing rumination. Mindfulness apps offer a convenient, engaging, and cost-effective means for accessing mindfulness training for teens. Despite their increasing popularity among adolescents, no study to date has investigated which teens are well-suited to app-based mindfulness training.
Eighty adolescents (M age = 14.01 years, 45% girls) with elevated rumination were enrolled in a 3-week trial of app-based mindfulness training. Repeated daily ecological momentary assessment (EMA) surveys assessed problem-focused and emotion-focused rumination immediately prior to and following each mindfulness exercise. Elastic net regularization (ENR) models tested baseline predictors of “immediate” (post-mindfulness exercise) and “cumulative” (post-3-week intervention) benefit from app-based mindfulness training.
Ninety percent (72/80) of adolescents completed the 3-week trial, and the mean number of mindfulness exercises completed was 28.7. Baseline adolescent characteristics accounted for 14–25% of the variance in outcomes (i.e., reduction in problem-focused or emotion-focused rumination). Higher baseline rumination, and lower emotional suppression, predicted better immediate and cumulative outcomes. In contrast, female gender and older age predicted better immediate, but not cumulative, outcomes. Differences in results across outcome timeframes (immediate vs. cumulative) are discussed.
Findings from this study highlight the potential of data-driven approaches to inform which adolescent characteristics may predict benefit from engaging with an app-based mindfulness training program. Additional research is needed to test these predictive models against a comparison (non-mindfulness) condition.