uTECH: Machine Learning for HIV Prevention Among Substance Using GBMSM

HIV Infections Clinical Trial

— uTECH  

Official title:

uTECH: Machine Learning for HIV Prevention Among Substance Using GBMSM

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT04710901
• Other study ID #: 19-000805
• Secondary ID: DP2DA049296-01
• Status: Active, not recruiting
• Phase: N/A
• Start date: November 24, 2020
• Est. completion date: May 31, 2024

Study information

• Verified date: August 2023
• Source: University of California, Los Angeles
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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

Description:

The project will occur in two phases. In Phase 1, we will conduct qualitative interviews with gay and bisexual men who have sex with men (GBMSM) using an iterative user-centered design process, which will result in a refined version of the uTECH intervention. In Phase 2, we will conduct a comparative acceptability, appropriateness and feasibility trial with 330 individuals, who will be randomized to (1) receive the uTECH intervention and an existing, evidence-based motivational enhancement intervention for HIV risk and substance use prevention (YMHP) or (2) receive YMHP alone. 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 our previously developed machine learning algorithm, which helps participants understand their technology-use behavior in relation to HIV-risk and substance use.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 388
• Est. completion date: May 31, 2024
• Est. primary completion date: May 31, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Male
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• 18 years of age or older
• Current sexual identity as a sexual minority
• Current gender identity as a gender minority
• Have had anal and/or oral sex with a man in the past 3 months
• Use an illicit substance (such as methamphetamine, cocaine, ecstasy) OR a legal substance (such as alcohol or marijuana) in the past 3 months
• Have had sex while using any substance in the past 3 months
• Use a gay-specific social media/networking/dating app in the past 3 months to seek sexual and drug use partners
• Willing to participate in audio-recorded interviews over Zoom
• Comfortable answering questions in English
• Use an Android or iOS smartphone
• Negative or Unsure about HIV status
• Comfortable with downloading an app that captures a variety of text-based information from their phone over the course of 12-months
• Currently living and/or sleeping in Los Angeles County
• Willing to participate in this study.

Exclusion Criteria:

• Under 18 years of age
• Does not currently identify as a gender or sexual minority
• 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) or legal substance (such as alcohol or marijuana) 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
• Are not willing to participate in audio-recorded interviews over Zoom
• Do not feel comfortable answering questions in English
• Do not use an Android or iOS smartphone
• HIV status is positive
• Do not feel comfortable with downloading an app that captures a variety of text-based information from their phone over the course of 12-months
• Are not currently living and/or sleeping in Los Angeles County
• Am not willing to participate in this study.

Related Conditions & MeSH terms

• HIV Infections
• Implementation Science
• MSM
• Sexually Transmitted Diseases
• Substance Use
• Substance-Related Disorders

Intervention

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.
• 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.
• 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.

Locations

Country	Name	City	State
United States	UCLA	Los Angeles	California

Sponsors (2)

Lead Sponsor	Collaborator
University of California, Los Angeles	National Institute on Drug Abuse (NIDA)

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Perception of Intervention Acceptability [4-item scale, 5-point ordinal response]	Drawing from work of Weiner et al (2017), we will rely on a psychometrically validated implementation science measure called "Acceptability of Intervention Measure (AIM)" that will measure the perception among implementation stakeholders that a given treatment, service, practice, or innovation is agreeable, palatable, or satisfactory. This measure is a 5-item scale with 5-point ordinal response that ranges from "completely disagree" to "completely agree."	12 months
Primary	Perception of Intervention Appropriateness [4-item scale, 5-point ordinal response]	Drawing from work of Weiner et al (2017), we will rely on a psychometrically validated implementation science measure called "Intervention Appropriateness Measure (IAM)" that will measure the perceived fit, relevance, or compatibility of the innovation for a given consumer. This measure is a 4-item scale with 5-point ordinal response that ranges from "completely disagree" to "completely agree."	12 months
Primary	Perception of Intervention Feasibility [4-item scale, 5-point ordinal response]	Drawing from work of Weiner et al (2017), we will rely on a psychometrically validated implementation science measure called "Feasibility of Intervention Measure (FIM)" that will measure the extent to which the intervention or innovation can be successfully used or carried out within this setting. This measure is a 4-item scale with 5-point ordinal response that ranges from "completely disagree" to "completely agree."	12 months