DIGITAL TRANSFORMATIONS IN THERAPY: A COMPREHENSIVE REVIEW OF ARTIFICIAL INTELLIGENCE AND VIRTUAL REALITY-BASED INTERVENTIONS IN THE TREATMENT OF ANXIETY AND DEPRESSIVE DISORDERS (2020–2024) - Dagmara Gładysz; Joanna Barwacz; Magdalena Adamik; Layla Settaf-Cherif; Katarzyna Malinowska; Elhatra Settaf-Cherif (International Journal of Innovative Technologies in Social Science, 2025)
Research Objectives: This comprehensive systematic review and meta-analysis aim to critically evaluate the clinical evidence regarding the efficacy, feasibility, and cost-effectiveness of Artificial Intelligence (AI)- and Virtual Reality (VR)-based interventions in the treatment and monitoring of Anxiety Disorders (AD) and Major Depressive Disorder (MDD) between 2020 and 2024. The study focuses on two primary pillars of innovation: AI tools (Generative AI chatbots, natural language processing, crisis prediction) and VR technologies (Exposure Therapy, VR-enhanced Behavioral Activation, mindfulness training, bio/neurofeedback). Additionally, the review analyzes ethical, legal, social, and implementation (ELSI) barriers that must be addressed to achieve large-scale deployment. Methods: A scoping review of the scientific literature was conducted across databases including PubMed, Scopus, and Google Scholar, applying inclusion criteria that covered Randomized Controlled Trials (RCTs), systematic reviews, and meta-analyses published from January 2020 to July 2024. Seven key meta-analyses and eighteen RCTs were analyzed in detail, focusing on effect sizes (Hedges’ g). Risk of bias and regulatory frameworks were also assessed. Main Findings: AI demonstrated high scalability (g = 0.52-0.61 for chatbots (Li et al., 2023)), showing short-term efficacy comparable to traditional digital interventions. A key factor was the integration of Generative AI models that enhanced the therapeutic alliance, as well as NLP-based predictive systems. VR, in turn, provided an experiential depth (presence) essential for effectiveness in specific phobias and social anxiety (g = 0.75-0.88 (Wang et al., 2024)), particularly in VRET and VR-BA models. Major barriers included issues of Explainable AI (XAI), algorithmic bias, and technological integration with healthcare systems (EHR). Conclusions: Digital technology is becoming an integral part of psychiatric care. The future lies in blended care models that combine the scalability of AI with the immersive depth of VR under clinical supervision. Long-term RCTs and clear regulatory frameworks concerning ethics and legal liability must be established prior to widespread implementation.