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Addressing Challenges Children and adolescents Encounter in Securing substance use and mental health Services.

At the ACCESS Lab, we envision a world where every child has early access to needed substance use and mental health interventions.

We focus on developing, testing and implementing digital interventions for risk identification and prevention among adolescents at high risk for substance use and mental disorders. We employ machine learning approaches to identify adolescents at high risk for substance use using large and complex data sources such as the electronic health records and digital software such as games. We are interested in mitigating risk for adolescent substance use and mental disorders through the implementation of effective digital interventions that address barriers in access to care. We are also interested in family-based interventions for the prevention of adolescent substance use.

Our mission is to improve access to care for every adolescent in need of substance use and mental health interventions. We are also committed to developing and implementing culturally-informed interventions that address racial/ethnic disparities.


  • NIDA – National Institute on Drug Abuse
  • CTBH – Center for Technology and Behavioral Health
  • Doris Duke Charitable Foundation
  • NIH AIM-AHEAD – National Institutes of Health Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity
  • Yale Child Study Center
  • Yale Center for Clinical Investigation

Current Projects

  1. Testing the moderating effect family functioning and race/ethnicity on the efficacy of a digital intervention to prevent opioid misuse among older adolescents.
  2. Investigating the utility of machine learning models for substance use prediction among adolescents using complex large datasets from videogames and electronic health record data.
  3. Testing the efficacy of digital interventions among adolescents on the waitlists at outpatient mental health clinics.

Lab Members

Meet the team, collaborators, students and alumni of the ACCESS Lab.