Background: Repetitive negative thinking (RNT) is a key transdiagnostic mechanism underpinning depression and anxiety. Using "just-in-time adaptive interventions" via smartphones may disrupt RNT in real time, providing targeted and personalized intervention.
Objective: This pilot randomized controlled trial evaluates the feasibility, acceptability, and preliminary clinical outcomes and mechanisms of Mello-a fully automated, personalized, transdiagnostic, and mechanistic smartphone intervention targeting RNT in young people with depression and anxiety.
Methods: Participants with heightened depression, anxiety, and RNT were recruited via social media and randomized to receive Mello or a nonactive control over a 6-week intervention period. Assessments were completed via Zoom sessions at baseline and at 3 and 6 weeks after baseline.
Results: The findings supported feasibility and acceptability, with high rates of recruitment (N=55), uptake (55/64, 86% of eligible participants), and retention (52/55, 95% at 6 weeks). Engagement was high, with 90% (26/29) and 59% (17/29) of the participants in the Mello condition still using the app during the third and sixth weeks, respectively. Greater reductions in depression (Cohen d=0.50), anxiety (Cohen d=0.61), and RNT (Cohen d=0.87) were observed for Mello users versus controls. Mediation analyses suggested that changes in depression and anxiety were accounted for by changes in RNT.
Conclusions: The results indicate that mechanistic, targeted, and real-time technology-based solutions may provide scalable and effective interventions that advance the treatment of youth mental ill health.
Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12621001701819; http://tinyurl.com/4d3jfj9f.
Keywords: adolescent; anxiety; depression; just-in-time adaptive interventions; mobile app; mobile phone; repetitive negative thinking; rumination; youth mental health.
©Imogen Bell, Chelsea Arnold, Tamsyn Gilbertson, Simon D’Alfonso, Emily Castagnini, Nicola Chen, Jennifer Nicholas, Shaunagh O’Sullivan, Lee Valentine, Mario Alvarez-Jimenez. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.12.2023.