Process model of emotion regulation-based digital intervention for emotional problems

Abstract

Background: To address the lack of mental health practitioners in developing countries, the current study explored the feasibility of a newly developed self-guided digital intervention program TEA (training for emotional adaptation) in alleviating depressive and anxiety symptoms, as one of a few studies which adapted from theoretical models with effective intervention techniques. Methods: The first part of this study involved 11 professional mental health practitioners giving feedback on the feasibility of the TEA; while the second part involved a mixed-method single-arm study with 32 participants recruited online, who went through the seven intervention sessions within 14 days. The questionnaires were collected before, after, 14 days after, and 30 days after intervention. Additionally, 10 participants were invited to semi-structured interviews regarding their suggestions. Results: Practitioners thought that the TEA showed high professionalism (8.91/10) and is suitable for treating emotional symptoms (8.09/10). The generalized estimating equation model showed that the TEA significantly reduced participants' depressive and anxiety symptoms, while the effects of the intervention remained 30 days post intervention (Cohen's d > 1). Thematic analysis revealed three main themes about future improvement, including content improvement, interaction improvement, and bug-fixing. Conclusions: To address the current needs for digital mental health intervention programs to account for the insufficient availability of mental health services in China, the current study provides preliminary evidence of the effectiveness of TEA, with the potential to address the urgent need for remote mental health services. Trial registration: The study was registered at the Chinese Clinical Trial Register (ChiCTR), with number [ChiCTR2200065944].

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