Courtney Keyi Lee¹ and Jonathan Thamrun², ¹USA, ²California State Polytechnic University, USA

Recent years have seen an increase in mental health challenges, particularly depression and anxiety, exacerbated by barriers such as stigma, cultural differences, and the lack of readily accessible treatment. This paper proposes an AI-driven journaling app as a solution to address these issues by offering personalized, culturally sensitive, and engaging mental health support. The app leverages Natural Language Processing (NLP) and adaptive learning to generate tailored prompts and advice, fostering emotional awareness and self-reflection. Key challenges included interpreting complex emotions and addressing cultural and generational nuances. These were tackled through dynamic AI models, curated datasets, and iterative refinement. Experiments tested the app's accuracy in emotion detection and its ability to adapt advice to diverse contexts, achieving promising results in relevance and cultural alignment. By integrating inclusivity and real-time feedback, this app offers a practical, scalable tool for mental well-being, making it an accessible alternative to traditional mental health support.

Natural Language Processing, Flutter, Emotional Analysis, Dart