The Practical, Robust Implementation and Sustainability (PRISM)-capabilities model for use of Artificial Intelligence in community-engaged implementation science research.

Journal: Implementation science : IS
Published Date: Aug 7, 2025

Abstract

BACKGROUND: Community-engaged research (CER) leverages knowledge, insights, and expertise of researchers and communities to address complex public health challenges and improve community well-being. CER fosters collaboration throughout all research phases, from problem identification and implementation to evaluation. Artificial Intelligence (AI) could enhance the collaborative process by improving data collection, analysis, insight, and engagement, while preserving research ethics. By integrating AI into CER, researchers could enhance their capacity to work collaboratively with communities, making research more efficient, inclusive, and impactful. However, careful consideration must be given to the ethical and social implications of AI to ensure that it supports the goals of CER. This paper introduces the PRISM-Capabilities model for AI to promote a human-centered approach that emphasizes collaboration, transparency, and inclusivity when using AI within CER.

Authors

  • Nabila El-Bassel
    Columbia University School of Social Work (NEB, JLD, EW, LG, TH, VF, DAGE, SNB); Department of Statistics Columbia University (EA, TZ); School of Public Health at the University of North Texas Health Science Center (STW); National Institute on Drug Abuse (RC); Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute (ANCC); Columbia University Information Technology (MC, PD, MA); Albert Einstein College of Medicine (DL); City University of New York School of Public Health (NS, TH); Department of Public Health Sciences, Biostatistics, University of Miami (DF).
  • James David
    School of Social Work, Columbia University, New York City, United States.
  • Trena I Mukherjee
    School of Social Work, Columbia University, New York City, United States.
  • Maneesha Aggarwal
  • Elwin Wu
  • Louisa Gilbert
  • Scott Walters
    School of Public Health, University of North Texas Health Science Center, Fort Worth, United States.
  • Redonna Chandler
  • Tim Hunt
  • Victoria Frye
  • Aimee Campbell
    Department of Psychiatry, Columbia University Irving Medical Center, New York City, United States.
  • Dawn A Goddard-Eckrich
    School of Social Work, Columbia University, New York City, United States.
  • Katherine Keyes
    Department of Epidemiology, Columbia Mailman School of Public Health, New York City, United States.
  • Shoshana N Benjamin
  • Raymond Balise
    University of Miami, Department of Public Health Sciences, Biostatistics, Miami, Florida, United States.
  • Smaranda Muresan
    Department of Computer Science, Barnard College, New York City, United States.
  • Eric Aragundi
  • Marc Chen
  • Parixit Davé
  • David Lounsbury
  • Nasim Sabounchi
  • Dan Feaster
  • Terry Huang
    Center for Systems and Therapeutics, Gladstone Institutes, San Francisco, CA 94158, USA.
  • Tian Zheng

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