UTECH: Machine Learning for HIV Prevention Among Substance Using GBMSM

Summary

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 sexual and gender minority people who have sex with men 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

Conditions

• Sexually Transmitted Diseases
• HIV Infections
• Implementation Science
• Substance Use
• MSM

Interventions

BEHAVIORAL

uTECH + YMHP

uTECH intervention utilizes a machine learning algorithm that leverages baseline data, individual social media use patterns, and strategic opportunistic learning questions to "push" messages to participants that offer strategic content about biomedical and behavioral HIV prevention. In addition, participants in this arm will also receive the YMHP intervention, which provides a four-session, evidence-based Motivational Enhancement intervention developed as part of the Young Men's Health Project (YMHP) and delivered via Zoom. Participants complete the four-session intervention during the first three months of their enrollment in the study.

BEHAVIORAL

YMHP

YMHP intervention provides a four-session evidence-based Motivational Enhancement intervention developed as part of the Young Men's Health Project (YMHP) and delivered via Zoom. Participants complete the four-session intervention during the first three months of their enrollment in this study. Months 3-12 are inactive.

BEHAVIORAL

uTECH

uTECH intervention utilizes a machine learning algorithm that leverages baseline data, individual social media use patterns, and strategic opportunistic learning questions to "push" messages to participants that offer strategic content about biomedical and behavioral HIV prevention.

Sponsors & Collaborators

• National Institutes of Health (NIH)

  collaborator NIH

• National Institute on Drug Abuse (NIDA)

  collaborator NIH

• University of California, Los Angeles

  lead OTHER

Study Design

Allocation

RANDOMIZED

Purpose

PREVENTION

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Sex

MALE

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2020-11-24

Primary Completion

2024-05-31

Completion

2024-05-31

Countries

• United States

Study Locations