Integrating Community Based Participatory Research and Machine Learning Methods to Predict Youth Substance Use Disorders for Urban Cities in New Jersey


This project aims to create more accurate predictions on substance use disorders among youth in urban communities using Community-Based Participatory Research methods, geospatial analysis, and machine learning. Our goals are to collect local and individual-level data in Paterson and East Orange, New Jersey, train and involve youth in the study design, and use longitudinal methods to develop a database to track substance use outcomes among youth aged 15-21.


Funding source

NIDA (National Institute on Drug Abuse) Racial Equity Visionary Award (DP1DA058982; PI: Ijeoma Opara)