# Harnessing Social Network Support to Improve Retention in Care and Viral Suppression among Young Black Men in Chicago and Alabama: A Hybrid Type I Effectiveness-Implementation Trial of Project nGage

> **NIH NIH R01** · UNIVERSITY OF CHICAGO · 2023 · $550,447

## Abstract

Abstract
We will conduct a Hybrid Type I effectiveness-implementation randomized controlled trial of the Project nGage
(“nGage”) intervention, an evidence-based, flexible, and tailored intervention that harnesses social support to
promote retention in care and viral suppression (VS) among HIV-positive young Black MSM (YBMSM) aged 18-
35. The study will take place in Chicago, IL, and Alabama (AL), two high-burden areas prioritized in the national
Ending the HIV Epidemic Plan. Existing efforts to improve Continuum of Care outcomes for YBMSM often rely
on newly created network members, e.g., peer navigators, support groups, case managers. Often missing from
these approaches is a focused attempt to harness organic social network supports, i.e., those people who
already offer critical forms of emotional, informational, and instrumental support. In contrast, the nGage
intervention was developed to identify, activate, and harness organic social network support for YBMSM living
with HIV. The intervention uses (1) social network visualization and theory to help men identify a Support
Confidant (SC) to engage in care; (2) the Information-Motivation-Behavioral Skills Model targeted at the SC to
activate and maintain dyadic social support; (3) a linked social support model to target the drivers of retention in
care and VS. Content is delivered via a single face-to-face session and quarterly mini-boosters. nGage's
flexibility ensures that SCs are selected based on their supportive function rather than their role. In a pilot RCT
in Chicago, we demonstrated feasibility, acceptability, and efficacy. To now test effectiveness, N=600 YBMSM
living with HIV in Chicago and AL will be randomized to receive nGage (n=300) or treatment as usual (TAU)
(n=300). We also will enroll 300 SCs. At 12-months post-intervention, we will re-randomize nGage dyads to
continue receiving quarterly mini-boosters (Sustained nGage: n=150) or return to TAU (n=150). Data collection
at baseline, 12, and 24 months will include surveys and electronic medical record (EMR) data. To study
implementation, we will use the Consolidated Framework for Implementation Research (CFIR) as the
determinants framework and RE-AIM as the evaluation framework. The specific aims are to: (Aim 1) Evaluate
the (a) effectiveness of nGage vs. TAU over 12 months in N=600 YBMSM aged 18-35 and (b) value of continuing
nGage over another 12 months (Sustained nGage). The primary outcomes are retention in care and VS, as
measured by EMR data; (Aim 2) Examine if intervention effects (a) vary between Chicago and AL, (b) are
mediated by changes in the Index's motivational readiness, stigma expectancies, and self-efficacy, and (c) are
moderated by Index's mental health and substance use; and (Aim 3) Evaluate the implementation of nGage
using the CFIR and the RE-AIM framework. Guided by the CFIR, we will conduct surveys and focus groups with
key stakeholders to assess the inner and outer settings, implementer and intervention ch...

## Key facts

- **NIH application ID:** 10569099
- **Project number:** 5R01MH125744-03
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** David S. Batey
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $550,447
- **Award type:** 5
- **Project period:** 2021-03-26 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10569099

## Citation

> US National Institutes of Health, RePORTER application 10569099, Harnessing Social Network Support to Improve Retention in Care and Viral Suppression among Young Black Men in Chicago and Alabama: A Hybrid Type I Effectiveness-Implementation Trial of Project nGage (5R01MH125744-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10569099. Licensed CC0.

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