Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{187125,
        author = {Shikha Dutta and Nidhi Chandrakar},
        title = {Review on AI-Powered Chatbots for Mental Health Support},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {5840-5846},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187125},
        abstract = {The growing prevalence of mental health disorders worldwide has intensified the demand for accessible, affordable, and stigma-free psychological support. In response, artificial intelligence (AI)–powered chatbots have emerged as innovative tools capable of delivering mental health interventions through natural language conversations. This review synthesizes empirical and theoretical research published over the past fifteen years (2010–2025) to evaluate the efficacy, usability, ethical considerations, and design features of AI-driven chatbots for mental health support. A systematic analysis of more than twenty peer-reviewed studies and meta-analyses reveals that chatbots utilizing cognitive behavioral therapy (CBT), mindfulness, and supportive dialogue frameworks can significantly reduce symptoms of depression and anxiety, enhance user engagement, and improve emotional well-being. Furthermore, these interventions demonstrate potential in supplementing traditional therapy, particularly for populations with limited access to professional mental health care. However, the review also highlights critical challenges, including limited long-term evidence, small sample sizes, lack of standardized evaluation metrics, and concerns regarding privacy, data protection, and algorithmic bias. Despite users reporting high satisfaction and perceived empathy from chatbot interactions, the absence of consistent clinical oversight raises questions about safety, accuracy, and ethical accountability. Engagement patterns and design elements such as personalization, brevity, and conversational empathy were identified as major determinants of effectiveness.},
        keywords = {artificial intelligence, chatbots, mental health, cognitive behavioral therapy, digital interventions, psychological well-being, user engagement, ethics},
        month = {November},
        }