Comparative Analysis of Artificial Intelligence-Based and Traditional Human Therapies in Mental Health Care

Abstract

This study explores the comparative effectiveness and user perception of Artificial Intelligence (AI)-based therapies versus traditional human therapies in addressing mental health concerns among young adults in the Delhi-NCR region. With AI’s increasing integration into global mental health frameworks, this research aims to understand user preferences, emotional needs, and psychological distress levels within emerging hybrid therapeutic models. A correlational survey design was adopted, involving 120 participants aged 18–45 years. Data were collected using the DASS-42 scale and a self-constructed questionnaire. Findings revealed a significant preference for human therapists, particularly among individuals experiencing moderate to severe psychological distress, due to the perceived value of empathy and emotional responsiveness. Conversely, participants with lower distress levels showed greater openness to AI-based therapy, appreciating its accessibility, anonymity, and cost-effectiveness. Gender differences and prior exposure to AI tools also influenced preferences. The study concludes that while AI therapy offers promising avenues for expanding mental health access, it cannot fully substitute human connection, especially in cases of acute psychological need. The study advocates for emotionally intelligent AI systems and integrated human-AI therapeutic models tailored to individual needs, contributing to the evolving discourse on inclusive and hybrid digital mental health care.