NCT02990377

Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention

Completed NA Last updated 31 January 2022

What this trial tests

NA trial testing RL-supported IVR intervention in Non-Medical Opioid Use in 459 participants. Completed in 31 December 2021.

Timeline

6 November 2018

Primary endpoint
31 December 2021

31 December 2021

Quick facts

Lead sponsor	University of Michigan
Phase	NA
Status	Completed
Study type	INTERVENTIONAL
Allocation	randomized
Design	parallel
Masking	none
Primary purpose	health services research
Enrollment	459
Start date	6 November 2018
Primary completion	31 December 2021
Estimated completion	31 December 2021
Sites	1 location across United States

Drugs / interventions tested

• RL-supported IVR intervention

Conditions studied

• Non-Medical Opioid Use — all drugs for Non-Medical Opioid Use →

Sponsor

University of Michigan

Who can join

18 and older, any sex, with Non-Medical Opioid Use. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

In recent years in the U.S., problems associated with opioid prescriptions, including non-medical use and overdose, increased to historically unprecedented levels and represent a public health crisis. Emergency departments (EDs) play an important role in opioid prescribing, particularly to individuals at high risk for adverse opioid-related outcomes. The purpose of this study is to determine whether a new mobile health (mhealth) intervention can assist people in the safe use of opioid analgesic (OA) medications after leaving the emergency department (ED).

The specific aims of this project are to: (1) adapt and enhance an existing motivational intervention to decrease non-medical opioid use after an ED visit by optimizing intervention intensity and duration through reinforcement learning (RL); (2) examine the impact of an RL-supported intervention on non-medical opioid use level during the six months post-ED visit; and (3) examine the impact of the RL intervention on the opioid-related behaviors and adverse outcomes of driving after opioid use, overdose risk behaviors, and subsequent opioid-related ED visits. The secondary aims of this project are to: (SA1) examine whether baseline level of non-medical opioid use moderates the effects of the intervention; and (SA2) understand barriers and facilitators of implementation of the intervention based on qualitative interviews with ED patients.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures.
   Piette JD, Thomas L, Newman S, Marinec N, et al · · 2023 · cited 8× · PMID 37432726 · DOI 10.2196/44165