Novel Machine Learning HIV Intervention for Sexual and Gender Minority Young People Who Have Sex With Men (uTECH): Protocol for a Randomized Comparison Trial.

Journal: JMIR research protocols
PMID: 39163591

Abstract

BACKGROUND: Sexual and gender minority (SGM) young people are disproportionately affected by HIV in the United States, and substance use is a major driver of new infections. People who use web-based venues to meet sex partners are more likely to report substance use, sexual risk behaviors, and sexually transmitted infections. To our knowledge, no machine learning (ML) interventions have been developed that use web-based and digital technologies to inform and personalize HIV and substance use prevention efforts for SGM young people.

Authors

  • Ian W Holloway
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Elizabeth S C Wu
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Callisto Boka
    Department of Epidemiology, UCLA Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.
  • Nina Young
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Chenglin Hong
    Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Kimberly Fuentes
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Kimmo Karkkainen
  • Mehrab Beikzadeh
    Department of Computer Science, UCLA Samueli School Of Engineering, University of California, Los Angeles, Los Angeles, CA, United States.
  • Alexandra Avendaño
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Juan C Jauregui
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Aileen Zhang
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Lalaine Sevillano
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Colin Fyfe
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Cal D Brisbin
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Raiza M Beltran
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Luisita Cordero
    Department of Social Welfare, UCLA Luskin School of Public Affairs, University of California, Los Angeles, Los Angeles, CA, United States.
  • Jeffrey T Parsons
    Mindful Designs, Teaneck, NJ, United States.
  • Majid Sarrafzadeh
    Computer Science Department, University of California Los Angeles (UCLA), Los Angeles, CA.

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