A scalable mental health intervention for depressive symptoms: evidence from a randomized controlled trial and large-scale real-world studies - Jianjie Xu; Zhuo Rachel Han; Xiangxi Lv; Lu Chen; Ningning Mao; Mengyu Miranda Gao; Hanyi Zhang; Yueqin Hu; Shaozheng Qin; James J. Gross; Zhanjun Zhang (npj Digital Medicine)
Abstract Depressive symptoms pose a serious global threat to well-being, highlighting the need for scalable mental health interventions. E-mental health interventions offer promising population-level solutions, yet few are grounded in theory or tested on large samples. This study utilizes an innovative e-mental health intervention based on the Extended Process Model of Emotion Regulation and examines the effectiveness of this theory-based intervention across a randomized controlled trial (RCT, N = 187; Chinese Clinical Trial Registry: ChiCTR2400081964; registration date: March 18th, 2024) and two extensive real-world studies (N study 2 = 11,554, N study 3 = 44,018) conducted with adults in China. The RCT confirmed the efficacy of this intervention, and both of the real-world e-mental health intervention studies showed a decrease in depressive symptoms (35–36%) and an increase in well-being (14–16%) over 21 days. These findings highlight the potential of theory-based e-mental health interventions as scalable solutions for early depression intervention and prevention, offering substantial societal and economic advantages.