# Opioid use disorder, cognition, and recovery: An investigation of neuropsychological change and associated recovery outcomes in buprenorphine and methadone treated patients [SUPPLEMENT]

> **NIH NIH F32** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $15,632

## Abstract

(F.220) 7. Project Summary/Abstract
Opioid use disorder (OUD) accounts for 70% of the global disease burden attributable to drug use disorder,
affects ~2 million American adults, and is the leading reason for receipt of drug treatment. Pharmacotherapies
for OUD (RxOUD) are essential first-line treatment options that markedly facilitate recovery, and include the
opioid agonist treatments (OAT) methadone (MET) and buprenorphine (BUP). Fortunately, government efforts
have greatly expanded access to these lifesaving treatments. As OUD and OAT rates rise, characterization of
the patients undergoing these treatments and the factors influencing their recovery is crucial. Neurological
abnormalities are one of the most prevalent classes of secondary disease in OUD. Neurocognitive dysfunction
is linked to poorer recovery outcomes and OUD-related deficits span a broad range of cognitive domains.
Evidence indicates improvement with remission. Yet, the cognitive trajectories of BUP and MET treated OUD
patients are largely unknown. Given the cognitive deficits accompanying OUD and OAT, and the role of
cognition in addiction recovery, characterizing neurocognition during OAT and its relationship to OUD recovery
has clinically relevant implications. This area of study can ultimately inform novel therapeutic approaches for
enhancing OUD treatment and recovery. As a first step in this line of work, this prospective study seeks to
enhance our understanding of cognitive change during OAT and its relationship to multifaceted measures of
recovery (quality of life and opioid use frequency) in an ecologically valid sample of BUP and MET patients.
This 3-year mentored project aims (1) to determine if cognition improves, declines, or remains static after 6
weeks of OAT, and whether these cognitive trajectories are specific to cognitive domain or OAT group, (2) to
investigate whether cognitive trajectories predict 10-week recovery outcomes, and evaluate the influence of
group and treatment-relevant measures on cognition-recovery relationships. The ultimate goal of this line of
work is to assess RxOUD-specific and OUD-general cognitive trajectories, their neural substrates, and
recovery outcomes via prospective controlled investigation. Accordingly, this study also aims (3) to
demonstrate the feasibility of developing a similar but more comprehensive study. In addition to contributing to
a limited literature, this project can ultimately provide an important foundation for future research and inform
the development of cognitive rehabilitation treatments that complement RxOUD and enhance recovery
outcomes. The scientific aims support training in 3 competency areas: (1) treatment/recovery research, (2)
longitudinal design and implementation, and (3) OUD. Training will be fulfilled with the expert guidance of Drs.
John Kelly (sponsor), Bettina Hoeppner (co-sponsor), Roger Weiss and Randi Schuster (consultants). The
training and experience provided by this award will serve as a ...

## Key facts

- **NIH application ID:** 10405308
- **Project number:** 3F32DA047741-03S1
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Lauren A Hoffman
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $15,632
- **Award type:** 3
- **Project period:** 2022-02-01 → 2022-03-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10405308

## Citation

> US National Institutes of Health, RePORTER application 10405308, Opioid use disorder, cognition, and recovery: An investigation of neuropsychological change and associated recovery outcomes in buprenorphine and methadone treated patients [SUPPLEMENT] (3F32DA047741-03S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10405308. Licensed CC0.

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