Pilot Testing an Artificial Intelligence Algorithm That Selects Homeless Youth Peer Leaders Who Promote HIV Testing

TL;DR

This study pilots an AI algorithm to select peer leaders among homeless youth to promote HIV testing, showing increased testing rates and engagement in HIV prevention discussions over three months.

Contribution

It introduces a novel AI-based method for selecting peer change agents in homeless youth populations to enhance HIV testing outreach.

Findings

Significant increase in HIV testing rates over time.

Majority of youth engaged in HIV prevention discussions.

AI-selected peer leaders effectively promoted HIV testing.

Abstract

Objective. To pilot test an artificial intelligence (AI) algorithm that selects peer change agents (PCA) to disseminate HIV testing messaging in a population of homeless youth. Methods. We recruited and assessed 62 youth at baseline, 1 month (n = 48), and 3 months (n = 38). A Facebook app collected preliminary social network data. Eleven PCAs selected by AI attended a 1-day training and 7 weekly booster sessions. Mixed-effects models with random effects were used to assess change over time. Results. Significant change over time was observed in past 6-month HIV testing (57.9%, 82.4%, 76.3%; p < .05) but not condom use (63.9%, 65.7%, 65.8%). Most youth reported speaking to a PCA about HIV prevention (72.0% at 1 month, 61.5% at 3 months). Conclusions. AI is a promising avenue for implementing PCA models for homeless youth. Increasing rates of regular HIV testing is critical to HIV prevention and linking homeless youth to treatment.