Status
Conditions
Treatments
About
Emotional Distress, such as anxiety and depression, is an essential issue worldwide. There have been several evidence-based psychotherapies that are effective in improving emotional distress, such as Acceptance and Commitment Therapy (ACT). However, the scarcity of professionals and the imbalance in the distribution of mental health resources prevent individuals in need from accessing immediate and effective help.
Artificial intelligence (AI) has the potential to promote this problem. The existing studies have provided preliminary support for the application of AI in mental health interventions. One such model, Emohaa, a generated AI model, has been examined for its effectiveness in adult emotional distress. However, despite the limited reliability of the single-group design, parallel randomized controlled trials are scarce to validate this finding further. This present study is to fill this gap.
This study aims to examine the effectiveness of the generated AI (Emohaa) in reducing emotional distress, including anxiety and depression, compared with group ACT and waitlist. In this parallel randomized controlled trial, it is hypothesized that (1) Compared with the waitlist, Emohaa and group ACT could significantly improve participants' emotional distress, including anxiety and depression symptoms; (2) Emohaa would lead to a greater reduction in anxiety and depression symptoms compared with group ACT.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Primary purpose
Allocation
Interventional model
Masking
80 participants in 3 patient groups
Loading...
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal