International Journal of Science, Engineering and TechnologyAuthors: Ayush D. Yadav, Neelima S. Ambekar
Abstract: Anxiety disorders represent a major global mental health concern, exacerbated by limited access to professional care, social stigma, and economic constraints. Advances in artificial intelligence (AI), extensive language models (LLMs), have enabled the development of conversational agents capable of delivering scalable psychological support. However, most existing AI-based mental health systems operate in isolation from physiological, nutritional, and clinical oversight factors, limiting their clinical reliability and ethical robustness. This paper proposes a hybrid AI-driven mental health support framework that integrates an LLM-based conversational agent delivering cognitive-behavioral therapy (CBT) interventions with physiological and nutritional risk screening and structured human therapist oversight. The framework is designed to provide accessible, personalized, and ethically governed anxiety management while mitigating risks associated with fully automated systems. The paper details the system architecture, methodological design, dataset selection strategy, and evaluation metrics, positioning the proposed framework as a comprehensive and deployment-oriented model for AI-assisted anxiety management.
DOI: http://doi.org/10.5281/zenodo.20766551
