A randomized trial testing digital medicine support models for mild-to-moderate alcohol use disorder

Andrew Quanbeck, Ming Yuan Chih, Linda Park, Xiang Li, Qiang Xie, Alice Pulvermacher, Samantha Voelker, Rachel Lundwall, Katherine Eby, Bruce Barrett, Randall Brown

Research output: Contribution to journalArticlepeer-review

Abstract

This paper reports the results of a hybrid effectiveness-implementation randomized trial that systematically varied levels of human oversight required to support the implementation of a digital medicine intervention for persons with mild-to-moderate alcohol use disorder (AUD). Participants were randomly assigned to three groups representing possible digital health support models within a health system: self-monitored use (SM; n = 185), peer-supported use (PS; n = 186), or a clinically integrated model CI; (n = 187). Across all three groups, the percentage of self-reported heavy drinking days dropped from 38.4% at baseline (95% CI [35.8%, 41%]) to 22.5% (19.5%, 25.5%) at 12 months. The clinically integrated group showed significant improvements in mental health and quality of life compared to the self-monitoring group (p = 0.011). However, higher attrition rates in the clinically integrated group warrant consideration in interpreting this result. Results suggest that making a self-guided digital intervention available to patients may be a viable option for health systems looking to promote alcohol risk reduction. This study was prospectively registered at clinicaltrials.gov on 7/03/2019 (NCT04011644).

Original languageEnglish
Article number248
Journalnpj Digital Medicine
Volume7
Issue number1
DOIs
StatePublished - Dec 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health Informatics
  • Computer Science Applications
  • Health Information Management

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