# Peer-Delivered, Behavioral Activation Intervention to Improve Polysubstance Use and Retention in Mobile Telemedicine OUD Treatment in an Underserved, Rural Area

> **NIH NIH R01** · UNIV OF MARYLAND, COLLEGE PARK · 2022 · $2,357,873

## Abstract

Background. More than 50% of rural counties in the US do not have a single buprenorphine-waived provider,
and approximately 10% of people in the US live more than 10 miles away from their nearest prescriber.
Compounding the devastating effects of the opioid use disorder (OUD) crisis in underserved, rural areas is
increasing polysubstance use, notably stimulant use disorder co-occurring with OUD. Since 2019, our team
has filled a void of rural addiction treatment practitioners in underserved rural Maryland areas by providing
buprenorphine for OUD treatment with the use of telemedicine (TM) aboard a mobile treatment unit (MTU). Our
team has demonstrated the effectiveness of the TM-MTU model in reducing opioid use by 32.8% at three-
months. Yet, 92% of patients in the past year presented with polysubstance use at intake, approximately
half with OUD and stimulant use. Further, treatment retention is a challenge, amplified by polysubstance use;
less than 60% of patients were retained at three-months. Reinforcement-based approaches, such as
contingency management, have empirical support for improving treatment retention and stimulant use, yet
have low adoption in community settings due to organizational and provider barriers, including cost. A
behavioral reinforcement-based approach, such as behavioral activation (BA), which aims to increase positive
reinforcement through rewarding, substance-free behaviors, may be a promising effective and sustainable
strategy to improve both OUD treatment retention and polysubstance use, particularly stimulant use. Further,
our team has demonstrated that it is feasible to train peer recovery specialists (PRSs) in BA. Preliminary
Studies. This proposal builds upon our team’s prior studies demonstrating the feasibility, acceptability, and
effectiveness of: 1) the TM-MTU model reaching rural communities hard hit by the OUD crisis and
polysubstance use; 2) integrating PRS support on the TM-MTU; and 3) a PRS-delivered BA intervention (“Peer
Activate”) for improving treatment retention and reducing polysubstance use, including OUD and stimulant use.
Approach. Building upon this work, we propose a randomized Type 1 hybrid effectiveness-implementation trial
(n=180) to evaluate the PRS-delivered BA intervention on the MTU (Peer Activate-MTU) compared to
enhanced treatment as usual (ETAU; facilitated referrals and general peer support) on the following over 12-
months: (1) effectiveness outcomes: a) OUD treatment retention (primary: chart review of appointment
attendance); b) polysubstance use (co-primary: urinalysis of co-occurring use of ≥2 substances); and c)
buprenorphine adherence (secondary: urinalysis and pharmacy refill); (2) implementation outcomes, including
feasibility, acceptability, fidelity, and adoption guided by RE-AIM; (3) cost of implementing and sustaining Peer
Activate-MTU and its economic value relative to ETAU. Implications. This proposal is designed to lead to a
potentially scalable model for improving O...

## Key facts

- **NIH application ID:** 10578063
- **Project number:** 1R01DA057443-01
- **Recipient organization:** UNIV OF MARYLAND, COLLEGE PARK
- **Principal Investigator:** Sarah M. Kattakuzhy
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,357,873
- **Award type:** 1
- **Project period:** 2022-09-30 → 2025-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10578063

## Citation

> US National Institutes of Health, RePORTER application 10578063, Peer-Delivered, Behavioral Activation Intervention to Improve Polysubstance Use and Retention in Mobile Telemedicine OUD Treatment in an Underserved, Rural Area (1R01DA057443-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10578063. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*