US University launches Machine Learning for HIV Prevention Among Substance Using GBMSM

Photo by Markus Spiske

The University of California, Los Angeles is conducting the clinical trial uTECH: Machine Learning for HIV Prevention Among Substance Using GBMSM (uTECH).

This project seeks to develop and test the acceptability, appropriateness and feasibility of uTECH, a novel social media "big data" machine learning intervention for HIV-negative substance using GBMSM that aims to reduce HIV transmission risk by integrating biomedical and behavioral risk reduction strategies, including pre-exposure prophylaxis (PrEP) for HIV prevention and medication assisted treatment (MAT) for substance use harm reduction.

uTECH is innovative in that it includes both core intervention modules and highly personalized intervention content based on participants' social media use. The tailored intervention content can be delivered via text message or Facebook messenger. This content relies on the previously developed machine learning algorithm, which helps participants understand their technology-use behavior in relation to HIV-risk and substance use.

It is planned to include 335 participants.

Actual study start date is November 24, 2020. The researchers expect to complete the study by May 31, 2024.

Among the exclusion criteria are:

  • Under 18 years of age
  • Does not currently identify as a man or transgender man
  • Have not had anal and/or oral sex with a man in the past 3 months
  • Have not used an illicit substance (such as methamphetamine, cocaine, ecstasy) in the past 3 months
  • Have not had sex while using any substance in the past 3 months
  • Have not used a gay-specific social media/networking/dating app in the past 3 months to seek sexual and drug use partners

and others.

The location of the study is as follows (further details can be found here Los Angeles, United States.

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