Process Model of Emotion Regulation-Based Digital Intervention for Emotional Problems: A mixed methods feasibility study
Qu, D.; Liu, D.; Cai, C.; Yu, J.; Zhang, Q.; Liu, K.; Zhang, X.; Wei, Z.; Tan, J.; Cui, Z.; Zhang, X.; chen, R.
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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, corresponding to the urgent call for remote mental health service. It is one of a few studies which adapted from theoretical models with effective intervention techniques. The first part involved 11 professional mental health practitioners giving feedback on the feasibility; while the second part involved a single-arm study with 32 participants recruited online, who went through the seven intervention sessions. The questionnaires were collected before, after, 14-days after and 30-days after the intervention. Moreover, 10 participants were invited to semi-structured interviews. Practitioners thought the TEA showed high professionalism (8.91/10) and is suitable for treating emotional symptoms (8.09/10). The Generalized estimating equation (GEE) model showed that the TEA significantly reduced their psychological symptoms, while the effects of the intervention were retained for 30-day post intervention (Cohens d >1). Thematic analysis revealed three main themes about future improvement, including content improvement, interaction improvement and bug-fixing. Taken together, current study supported the effectiveness of TEA, with the potential to address the urgent need for remote mental health service. Future randomized controlled trials to confirm the effectiveness are required.
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