Non-Medical Opioid UseNCT02990377
Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention
A study testing RL-supported IVR intervention in people with Non-Medical Opioid Use, run by University of Michigan at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Non-Medical Opioid Use
- What is being tested?
- RL-supported IVR intervention
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 459 participants
- Where
- 1 siteUnited States
- Study dates
- 6 Nov 2018to 31 Dec 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
United States1 site
University of Michigan Medical Center
Ann Arbor, Michigan, 48109
About this study
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.
Read the 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.
- Conditions
- Non-Medical Opioid Use
- Being tested
- RL-supported IVR intervention
- Keywords
- Opioid Analgesics, Opioid Safety, Emergency Department, Motivational Enhancement, Interactive Voice Response, Reinforcement Learning, mHealth
- Medical subject headings
- Emergencies
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
RL-supported IVR interventionBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| RL-supported IVR intervention | Experimental | 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. Receives: Behavioral: RL-supported IVR intervention |
| Enhanced Usual Care | No intervention | Participants in the enhanced usual care group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Level of Non-Medical Opioid Use
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.
Measured: Change over time (1-, 3-, and 6-months post-ED visit)
Secondary outcomes (3)
Emergency Department (ED) Utilization
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.
Measured: Change over time (1-, 3-, and 6-months post-ED visit)
Driving after consuming opioids
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.
Measured: Change over time (1-, 3-, and 6-months post-ED visit)
Overdose Risk Behaviors
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.
Measured: Change over time (1-, 3-, and 6-months post-ED visit)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Dec 2016 (estimated)
- Study start6 Nov 2018
- Primary completion31 Dec 2021
- Study completion31 Dec 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Non-Medical Opioid UseStudies of the same condition, open and under way.
- More trials run by University of MichiganThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 459 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Michigan
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute on Drug Abuse (NIDA)
- Responsible party
- Principal investigator, Amy S.B. Bohnert, University of Michigan
- Investigators
- Amy S Bohnert, Ph.D., Principal investigator, University of Michigan
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02990377
- Sponsor's protocol ID
- R01DA039159
- Status last verified
- Jan 2022
- First submitted
- 2 Dec 2016
- Last updated
- 31 Jan 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Piette JD, Thomas L, Newman S, Marinec N, Krauss J, Chen J, Wu Z, Bohnert ASB. 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. J Med Internet Res. 2023 Jul 11;25:e44165. doi: 10.2196/44165.
PubMed 37432726
Study at a glance
From the registry record, last updated by the sponsor on 31 Jan 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention
- ClinicalTrials.gov ID
- NCT02990377
- Acronym / sponsor ID
- R01DA039159
- Conditions
- Non-Medical Opioid Use
- Keywords
- Opioid Analgesics, Opioid Safety, Emergency Department, Motivational Enhancement, Interactive Voice Response, Reinforcement Learning, mHealth
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 459 participants (actual)
- Lead sponsor
- University of MichiganUniversity, hospital or other
- Collaborators
- National Institute on Drug Abuse (NIDA)
- Study start
- 6 Nov 2018 (actual)
- Primary completion
- 31 Dec 2021 (actual)
- Study completion
- 31 Dec 2021 (actual)
- First posted
- 13 Dec 2016 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| RL-supported IVR intervention | Experimental | Behavioral: RL-supported IVR interventionParticipants 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. |
| Enhanced Usual Care | No intervention | –Participants in the enhanced usual care group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- 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
Key exclusion criteria (7 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| RL-supported IVR interventionParticipants 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. | Behavioural | RL-supported IVR intervention |
Primary outcome
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.
3 secondary outcomes
Emergency Department (ED) Utilization
Time frame: Change over time (1-, 3-, and 6-months post-ED visit)
Driving after consuming opioids
Time frame: Change over time (1-, 3-, and 6-months post-ED visit)
Overdose Risk Behaviors
Time frame: Change over time (1-, 3-, and 6-months post-ED visit)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 31 Jan 2022.
- Derived from this study: PubMed 37432726Piette JD, Thomas L, Newman S, Marinec N, Krauss J, Chen J, Wu Z, Bohnert ASB. 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. J Med Internet Res. 2023 Jul 11;25:e44165. doi: 10.2196/44165.
- Individual participant dataSharing planned: No
Related trials for Non-Medical Opioid Use
Not yet recruiting
Theory-based Social Media Intervention for Non-medical Use of Prescription Opioids in Young Adults
Young Adults, Past-3-month Non-medical Use of Prescription Opioids
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Amy S Bohnert, Ph.D. principal investigator
University of Michigan
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing RL-supported IVR intervention in people with Non-Medical Opioid Use, run by University of Michigan at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 31 Jan 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Level of Non-Medical Opioid Use (time frame: Change over time (1-, 3-, and 6-months post-ED visit)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02990377, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 31 Jan 2022.