# DAT18-08 Geographic variation in Opioid Addiction Treatment (GATE) study: Multi-Level Factors Influencing MAT Use, Other Treatment, & Adverse Outcomes among Re-entering Rural and Urban Prisoners

> **NIH NIH R01** · UNIVERSITY OF KENTUCKY · 2024 · $562,683

## Abstract

ABSTRACT: As outlined in DAT18-08, NIDA has a strong interest in understanding treatment utilization among
persons with opioid use disorders (POUDs) as they transition from prison to the community, because treating
individuals with opioid use disorder (OUD) simultaneously improves public health and public safety. Kentucky
is in the midst of an opioid crisis, with many POUDs cycling through the criminal justice system each year. While
evidenced-based medications for addiction treatment (MAT) exist for treating OUD, MAT is underutilized within
prisons, which elevates the risk of relapse and overdose when POUDs are released and re-enter their
communities. Research is scant regarding the multi-level factors associated with offenders’ willingness to initiate
MAT while in prison and their continued engagement in treatment after release. Furthermore, rural and urban
populations have not been compared. In response to NIDA DAT18-08, we propose to conduct the high-impact
Geographic variation in Addiction Treatment (GATE) study, which will address the knowledge gap on multi-level
factors influencing prison-based extended-release injectable naltrexone (XR-NTX) initiation as well as examine
predictors of post-release MAT use and adverse outcomes (i.e., relapse, overdose, recidivism) among both rural
and urban POUDs. This mixed methods study employs a social ecological framework to understand individual
characteristics that influence MAT initiation and adverse outcomes, as well as contexts more distal to the
individual, including social networks and structural factors. The specific aims of the GATE study are: 1) to
identify the individual, personal network, and structural factors associated with XR-NTX initiation in
prison among rural, as compared to urban, POUDs, and 2) to examine the individual, personal network,
and structural factors predicting MAT use, treatment use, and adverse outcomes in the community
among re-entering rural, as compared to urban, POUDs over time. A prospective observational longitudinal
cohort study will be conducted with 500 POUDs, using survey and social network data collected in prison and
at 6- and 12-months post-release to explore multi-level rural-urban variation in key outcomes. In-depth guided
qualitative interviews will be conducted with POUDs, prison-based treatment staff, and social service clinicians.
To maximize rigor and reproducibility, we will employ a concurrent triangulation strategy, whereby qualitative
and quantitative data contribute equally to the analysis and are used for cross-validation. This study is led by a
qualified interdisciplinary team and is the first mixed methods study examining the processes of social influences
that occur in rural and urban social networks as POUDs transition from prison back to geographically diverse
counties. The GATE study will enhance our ability to address the opioid epidemic within the correctional contexts
of prisons and community supervision by informing process improvement...

## Key facts

- **NIH application ID:** 10625330
- **Project number:** 5R01DA048876-05
- **Recipient organization:** UNIVERSITY OF KENTUCKY
- **Principal Investigator:** CARRIE BETH OSER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $562,683
- **Award type:** 5
- **Project period:** 2019-08-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10625330

## Citation

> US National Institutes of Health, RePORTER application 10625330, DAT18-08 Geographic variation in Opioid Addiction Treatment (GATE) study: Multi-Level Factors Influencing MAT Use, Other Treatment, & Adverse Outcomes among Re-entering Rural and Urban Prisoners (5R01DA048876-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10625330. Licensed CC0.

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