DIGITAL MENTAL HEALTH INTERVENTIONS: ASSESSING THE EFFICACY OF AI-BASED THERAPY FOR GENERALIZED ANXIETY DISORDER

Abstract

This research paper investigates the efficacy of AI-based therapy in managing Generalized Anxiety Disorder (GAD) and compares its effectiveness with traditional therapist-led Cognitive Behavioral Therapy (CBT). With the increasing prevalence of anxiety disorders and limited access to professional mental health services, AI-driven interventions have emerged as a promising alternative. However, their therapeutic potential, long-term impact, and ethical implications remain underexplored. The primary objective of this study is to evaluate AI-based therapy’s ability to reduce GAD symptoms, assess patient engagement and adherence, and examine ethical considerations related to digital mental health interventions. To achieve this, the study employs mixed-methods research design, incorporating both quantitative and qualitative approaches. A randomized controlled trial (RCT) was conducted with 200 participants diagnosed with GAD, divided into two groups: one receiving AI-based therapy and the other undergoing traditional CBT. Standardized anxiety assessment tool, the GAD-7 scale measured symptom changes in pre- and post-intervention scores. Additionally, user engagement data (session completion rates, dropout rates) and qualitative feedback from participant interviews offered insights into patient experiences and satisfaction. By analyzing the effectiveness and limitations of AI-driven mental health interventions, this research contributes to the evolving landscape of digital mental healthcare. The findings would inform clinicians, policymakers, and AI developers on the role of artificial intelligence in mental health treatment, highlighting its potential to enhance accessibility while addressing ethical and therapeutic challenges.