Working…
COVID-19 is an emerging, rapidly evolving situation.
Get the latest public health information from CDC: https://www.coronavirus.gov.

Get the latest research information from NIH: https://www.nih.gov/coronavirus.
ClinicalTrials.gov
ClinicalTrials.gov Menu

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

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT02990377
Recruitment Status : Recruiting
First Posted : December 13, 2016
Last Update Posted : November 12, 2019
Sponsor:
Collaborator:
National Institute on Drug Abuse (NIDA)
Information provided by (Responsible Party):
Amy S.B. Bohnert, University of Michigan

Brief Summary:

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.


Condition or disease Intervention/treatment Phase
Non-Medical Opioid Use Behavioral: RL-supported IVR intervention Not Applicable

Detailed Description:

The proposed study will test the efficacy of an interactive voice response (IVR) and reinforcement learning (RL) supported motivational intervention delivered after an emergency department (ED) visit to participants with recent non-medical OA use who receive an OA in the ED or who are prescribed an OA at ED discharge, compared to enhanced usual care (EUC). In the intervention condition, IVR calls will ask participants to report information about their health and medications using their touch-tone phone, and based on their responses they may receive brief or extended motivational messages during the IVR call, or they may be assigned to receive a 20 minute motivational enhancement session with a study therapist over the phone. Because the most helpful intensity of intervention is unknown and likely to vary between patients, the project will use an artificial intelligence strategy called reinforcement learning (RL). The RL system will continuously "learn" from the success of prior actions in similar situations with similar patients in order to select the action most likely to reduce non-medical opioid use for each participant during each call.

The proposed study will screen ~ 5,600 ED patients to enroll 600 ED participants in the randomized controlled trial (RCT). Participants will be randomized to the intervention condition (n=300) or to EUC (n=300). All participants will be re-assessed at 1, 3 and 6 months post-ED visit for level of non-medical OA use and related outcomes. The RCT will be complemented by qualitative interviews to inform later implementation.

Layout table for study information
Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 600 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Health Services Research
Official Title: Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention
Actual Study Start Date : November 6, 2018
Estimated Primary Completion Date : November 2020
Estimated Study Completion Date : July 2021

Arm Intervention/treatment
Experimental: RL-supported IVR intervention
Participants in the intervention group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED plus the RL-supported IVR intervention.
Behavioral: RL-supported IVR intervention
Participants in the intervention group receive interactive voice response calls where they are asked to report information about their health and medications using their touch-tone phone. Based on their responses, participants may receive brief or extended motivational messages during the call, or they may be assigned to receive a 20 minute motivational enhancement session with a study therapist over the phone.

No Intervention: Enhanced Usual Care
Participants in the enhanced usual care group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED.



Primary Outcome Measures :
  1. Level of Non-Medical Opioid Use [ Time Frame: Change over time (1-, 3-, and 6-months post-ED visit) ]
    The Current Opioid Misuse Measure (COMM) assesses opioid use that is more than prescribed, for non-pain-related reasons, borrowing medications, obtaining medications from sources other than doctors, etc., on a 5-point Likert scale of "Never" to "Very Often." The primary outcome will be a measure of severity created by summing the items.


Secondary Outcome Measures :
  1. Emergency Department (ED) Utilization [ Time Frame: Change over time (1-, 3-, and 6-months post-ED visit) ]
    ED use will be assessed with adapted items from the Treatment Service Review. A count of visits will be measured for the six months of follow-up.

  2. Driving after consuming opioids [ Time Frame: Change over time (1-, 3-, and 6-months post-ED visit) ]
    The investigators have adapted an item from the National Survey of Drinking and Driving Attitudes and Behaviors to apply to opioids. Frequency is assessed with a 5-point Likert scale and will be examined as a categorical variable for each follow-up assessment.

  3. Overdose Risk Behaviors [ Time Frame: Change over time (1-, 3-, and 6-months post-ED visit) ]
    The investigators have developed a measure based on items from the published literature on heroin overdose by adding risk factors specific to opioid analgesics. This measure will be a summary score of all items for each follow-up assessment.



Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.


Layout table for eligibility information
Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • Presenting at the study site emergency department (ED) for a pain related complaint
  • Past 3-month non-medical opioid analgesic (OA) use
  • Receiving an OA in the ED, or being given an OA prescription to fill after leaving the ED

Exclusion Criteria:

  • Unable to perform informed consent
  • Presenting for pain related to acute cancer therapy
  • DSM-V moderate or severe opiate (heroin or OA) use disorders (4+ symptoms), or experiencing tolerance and withdrawal symptoms
  • Unable to read/understand English
  • Lives 50+ miles from the study site
  • Acute risk for self-harm at the time of recruitment
  • Currently pregnant

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02990377


Contacts
Layout table for location contacts
Contact: Amy S Bohnert, Ph.D. 734-845-3638 amybohne@med.umich.edu
Contact: Jenny Chen, M.P.H. 734-222-7671 chenjs@med.umich.edu

Locations
Layout table for location information
United States, Michigan
University of Michigan Medical Center Recruiting
Ann Arbor, Michigan, United States, 48109
Contact: Amy S Bohnert, Ph.D.    734-845-3638    amybohne@med.umich.edu   
Contact: Laura Thomas, L.M.S.W./M.P.H.    734-615-4223    thlaura@med.umich.edu   
Sub-Investigator: Satinder Singh Baveja, Ph.D.         
Sub-Investigator: Frederic Blow, Ph.D.         
Sub-Investigator: Karen Farris, Ph.D.         
Sub-Investigator: Mark Ilgen, Ph.D.         
Sub-Investigator: John Piette, Ph.D.         
Sub-Investigator: Mary Janevic, Ph.D.         
Sub-Investigator: Mahshid Abir, M.D.         
Sponsors and Collaborators
University of Michigan
National Institute on Drug Abuse (NIDA)
Investigators
Layout table for investigator information
Principal Investigator: Amy S Bohnert, Ph.D. University of Michigan
Layout table for additonal information
Responsible Party: Amy S.B. Bohnert, Associate Professor, University of Michigan
ClinicalTrials.gov Identifier: NCT02990377    
Other Study ID Numbers: R01DA039159 ( U.S. NIH Grant/Contract )
First Posted: December 13, 2016    Key Record Dates
Last Update Posted: November 12, 2019
Last Verified: November 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

Layout table for additional information
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Amy S.B. Bohnert, University of Michigan:
Opioid Analgesics
Opioid Safety
Emergency Department
Motivational Enhancement
Interactive Voice Response
Reinforcement Learning
mHealth