Results From a Pilot Study of an Automated Directly Observed Therapy Intervention Using Artificial Intelligence With Conditional Economic Incentives Among Young Adults With HIV.

Journal: Journal of acquired immune deficiency syndromes (1999)
PMID: 38363868

Abstract

BACKGROUND: Despite improvements in antiretroviral therapy (ART) availability, suboptimal adherence is common among youth with HIV (YWH) and can increase drug resistance and poor clinical outcomes. Our study examined an innovative mobile app-based intervention that used automated directly observed therapy (aDOT) using artificial intelligence, along with conditional economic incentives (CEIs) to improve ART adherence and enhance viral suppression among YWH.

Authors

  • Marie C D Stoner
    Women's Global Health Imperative, RTI International, Berkeley, CA, USA.
  • Louis Smith
    Department of Medicine, University of California, San Francisco, CA, USA.
  • Kristin Ming
    Department of Medicine, University of California, San Francisco, CA, USA.
  • Noah Mancuso
    Women's Global Health Imperative, RTI International, Atlanta, GA, USA.
  • Henna Patani
    AIDS Healthcare Foundation, Los Angeles, CA, USA.
  • Adam Sukhija-Cohen
    Sutter Health, Sacramento, CA.
  • Yancy Granados
    AIDS Healthcare Foundation, Los Angeles, CA, USA.
  • Danielle Wagner
    Women's Global Health Imperative, RTI International, Berkeley, CA.
  • Mallory O Johnson
    Department of Medicine, Center for AIDS Prevention Studies, University of California, San Francisco, San Francisco, CA, United States.
  • Sue Napierala
    Women's Global Health Imperative, RTI International, Berkeley, CA, USA.
  • Torsten B Neilands
    Department of Medicine, Center for AIDS Prevention Studies, University of California, San Francisco, San Francisco, CA, United States.
  • Parya Saberi
    Department of Medicine, University of California, San Francisco, CA, USA.

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