uTECH: Machine Learning for HIV Prevention Among Substance Using GBMSM
Last updated on July 2021Recruitment
- Recruitment Status
- Recruiting
- Estimated Enrollment
- Same as current
Summary
- Conditions
- HIV Infections
- Implementation Science
- MSM
- Sexually Transmitted Diseases
- Substance Use
- Type
- Interventional
- Phase
- Not Applicable
- Design
- Allocation: RandomizedIntervention Model: Parallel AssignmentMasking: None (Open Label)Primary Purpose: Prevention
Participation Requirements
- Age
- Between 18 years and 125 years
- Gender
- Only males
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 comparativ...
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 receive the uTECH intervention or an existing, evidence-based motivational enhancement intervention for HIV risk and substance use prevention (Young Men's Health Project). 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.
Tracking Information
- NCT #
- NCT04710901
- Collaborators
- National Institute on Drug Abuse (NIDA)
- Investigators
- Not Provided
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