International Journal on Science and Technology

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AI ENABLED SOLUTIONS FOR MENTAL HEALTH CARE AND SUPPORT

Author(s) YASH VARDHAN SINGH, TARANPREET KAUR
Country India
Abstract Chatbots are an emerging technology that shows potential for mental health care apps to enable effective and practical evidence-based therapies. As this technology is still relatively new, little is known about recently developed apps and their characteristics and effectiveness.
The integration of Artificial Intelligence (Ai) into mental health care presents transformative opportunities for improving diagnosis, treatment, and access to support. This paper explores the current landscape of AI-enables solutions in Mental Health, focusing on the capabilities, applications, and ethical considerations of technologies such as chatbots, machine learning, natural language processing, and deep learning. AI tools are increasingly used to detect early signs of psychiatric disorders, personalize therapeutic interventions, and support report care delivery, thereby bridging critical gaps in traditional mental health systems. Through a review of recent academic literature, clinical studies, and theoretical frameworks –including the technology Acceptance Model (TAM) , the Biopsychosoical Model and Human-centered AI (HCAI) – the paper examines how AI can enhance engagement, reduce stigma, and deliver cost-effective alternatives to conventional therapy. However, challenges persist, including concerns over algorithmic bias, data privacy, cultural sensitivity, and the lack of human empathy in AI interaction. This paper emphasizes the need for ethically responsible and context-aware AI implementations, guided by interdisciplinary collaboration and continuous evaluation. The study concludes that while AI cannot replace human clinicians, it holds significant potential to augment mental health care and improve outcomes when designed and deployed thoughtfully.
Keywords Artificial Intelligence (AI), Mental Health Care, Chatbots, Machine Learning, Natural Language Processing (NLP), Deep Learning, AI in Psychiatry, Technology Acceptance Model (TAM), Biopsychosocial Model, Human-centered AI (HCAI), Digital Mental Health, AI Ethics, Algorithmic Bias, Data Privacy, Therapeutic Chatbots, AI-assisted Therapy, Personalized Interventions, Evidence-based Therapy, Stigma Reduction, Human-AI Interaction
Field Engineering
Published In Volume 16, Issue 3, July-September 2025
Published On 2025-08-14
DOI https://doi.org/10.71097/IJSAT.v16.i3.6290
Short DOI https://doi.org/g9w9rb
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