Integrating Community Based Participatory Research and Machine Learning Methods to Predict Youth Substance Use Disorders for Urban Cities in New Jersey
Mission
This project aims to create more accurate predictions on substance use disorders among youth in urban communities using Community-Based Participatory Research (CBPR) methods, geospatial analysis, and machine learning. Our goals are to (1) collect local and individual-level data in Paterson and East Orange, New Jersey, (2) train and involve youth, as citizen scientists, in study design, and (3) use longitudinal methods to develop a databased to track substance use outcomes among youth aged 15-21.
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Funding source
Robert Wood Johnson Foundation (RWJF) Reinvesting in Racial and Indigenous Health Equity Research Grant and Yale Donor Funding (PI: Ijeoma Opara).
