NSF Award
2431230
Public and community mental health services, which provide essential support and treatment for individuals with behavioral health conditions, have a profound impact on communities and millions of individuals across the United States. Un- or under-treated, significant mental illnesses are among the biggest sources of years lost to disability and economic burden in the United States. Communities served by public and community mental health services represent some of the most vulnerable in our society and can benefit greatly from the development of data-driven intelligent technologies. This planning grant focuses on strengthening and empowering peer-led organizations in public and community mental health services. As the behavioral health workforce crisis deepens, there is a growing imperative to expand and enhance the role of peer providers in public behavioral health, particularly within underfunded and technologically under-resourced peer-led agencies. These organizations, vital for delivering a diverse range of support to address individual holistic needs, including social, physical, emotional, and environmental by offering individual peer support, self-help groups, education and training, navigation to legal advocacy, face significant challenges due to inadequate technological infrastructure and reliance on low-tech service delivery methods. <br/><br/>This planning grant builds on our ongoing partnership with Collaborative Support Programs of New Jersey (CSPNJ), a state-wide, peer-led community-based behavioral health agency, which is known for its innovative work serving people with complex behavioral health, social and economic challenges. We will work together to create community-centered AI solutions that meet the needs of both peer service providers and recipients in resource-constrained peer-led public mental health services. We aim to build a collective understanding of community needs, success criteria, and challenges, and facilitate rapid prototyping of proven AI solutions through participatory methods. Leveraging multidisciplinary expertise in Human-computer Interaction (HCI), Artificial Intelligence (AI), mental health, and social work, and in close collaboration with our community partners, this planning grant will help us gain a robust understanding of (1) how service providers and recipients perceive success in peer-run community mental health services and the challenges they face in achieving such success. Based on these insights, we will (2) collaboratively identify specific AI-driven technologies that could be piloted in Stage 2 to enhance the capabilities of safety-net peer-run organizations. This will empower them to better meet the needs of underserved communities and potentially serve a broader population, thereby strengthening their impact in the community mental health sector.<br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>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.
