SBIR Phase I: Addressing Mental Health in Underserved Athletic Populations

The broader impact and commercial potential of this SBIR Phase I project lies in its innovative approach to proactively monitor mental health support for student-athletes, particularly those from underserved communities. Research shows that college athletes face 20 times higher rates of mental health issues than their non-athletic peers, with students of color encountering unique challenges tied to economic, culture, and social constructs.

This product will launch at Historically Black Colleges and Universities (HBCUs), where underfunded institutions, lack of social support, and imposed responsibilities compound the pressures of athletic competition.

This project focuses on developing an AI tool that provides conversational check-ins, identifying language indicative of mental distress. By leveraging minority data, this tool engages student-athletes in a culturally relevant manner, promoting their mental wellness. The primary objective is to train a large language model (LLM) using this data to proactively monitor the health and wellness of these student-athletes.

The bot integrates subjective conversational data with objective clinical surveys through proprietary algorithms, offering a more accurate assessment of mental distress. With a projected revenue of $3 million by year three, this comprehensive approach has the potential to revolutionize mental health support for student-athletes, with broader commercial applications for other vulnerable populations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.