Leveraging Large Language Models to Enhance Mental Health Literacy and Diversity Awareness in Adolescents: The me_HeLi-D Project

The Erasmus+ project me_HeLi-D (mental health literacy and diversity) aims to promote mental health literacy (MHL) and diversity awareness among adolescents aged 12-15 through a digital program designed to enhance well-being, resilience, and emotional regulation. This paper explores the integration of Large Language Models (LLMs) within the me_HeLi-D project, highlighting their potential to support mental health education and intervention. LLMs, such as GPT4, offer scalable, personalized, and contextually relevant support, making them valuable tools in digital mental health initiatives. The paper discusses the benefits and challenges of using LLMs, including their ability to provide immediate, evidence-based responses and the ethical considerations surrounding data privacy and bias. LLMs can deliver tailored feedback and resources that resonate with the diverse experiences of adolescents, thus fostering a more inclusive and supportive environment for mental health learning. Preliminary findings suggest that LLMs can effectively enhance mental health literacy and support adolescents in managing stress and preventing mental health issues. Furthermore, the interactive nature of these models encourages continuous engagement and learning, making complex mental health concepts more accessible to young audiences. The integration of LLMs also highlights their potential to adapt to different cultural contexts, thus promoting diversity awareness more effectively. The paper concludes with recommendations for future research and the responsible development of LLMs in mental health projects, emphasizing the need for ongoing evaluation and adaptation to meet the evolving needs of adolescents. Ultimately, the integration of LLMs within the me_HeLi-D project underscores their potential as powerful allies in the pursuit of better mental health outcomes and greater diversity awareness among youth.