Design and Development of AI Driven Mental Health Support System for Teenagers

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Date

2025

Author

Jacob Zulu, Billy Peter Munyenyembe

Publisher

International Journal of Advances in Scientific Research and Engineering

Abstract

Mental health issues among teenagers are on the rise due to academic stress, social pressures, and the challenges of adolescence. Access to timely and effective mental health support is crucial, yet traditional methods of seeking help may feel intimidating or inaccessible to many young people. This articlefocuses on developing an AI-driven mental health support apptailored for teenagers, aimed at providing a safe, accessible, and personalized platform for emotional well-being. The app leverages artificial intelligence to offer empathetic, real-time support through an AI-powered Chabotthat can engage users in meaningful conversations, detect emotional cues, and provide relevant coping strategies. Key features include a mood-tracking system to help users log and identify emotional patterns, personalized self-care plans, and access to a library of mental health resources. Additionally, the app integrates crisis intervention features, enabling immediate connection to professional support or helplines when high-risk behaviors are detected. Data privacy and security are prioritized, with advanced encryption and authentication mechanisms ensuring sensitive user data remains confidential. The app's user-friendly interface and scalable design make it adaptable to diverse educational and social settings. Regular updates and user feedback loops drive continuous improvements, ensuring the app remains relevant and effective in addressing the mental health needs of teenagers. This innovative AI-driven solution aims to enhance the accessibility, efficiency, and effectiveness of mental health support for teenagers, empowering them to manage their well-being with confidence and fostering a proactive approach to mental health care.

Keywords

artificial intelligencemenmental health support systemmobile based applicationsentiment analysis