Incentives to Decrease Opioid Use - Pilot

Substance-Related Disorders Clinical Trial

Official title:

Encouraging Opioid Abstinence Behavior: Incentivizing Inputs and Outcomes - Pilot

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04235582
• Other study ID #: 19-1095
• Status: Completed
• Phase: N/A
• Start date: August 25, 2020
• Est. completion date: May 15, 2021

Study information

• Verified date: January 2021
• Source: Aurora Health Care
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The purpose of this study is to address two key questions in the literature on incentives for substance use. The first question is whether it is more effective to directly incentivize the outcome of interest - drug abstinence - or to incentivize behaviors that are inputs into the production of abstinence. This study will compare two versions of the incentive program: one that incentivizes inputs to achieving abstinence and one that incentivizes the outcome of abstinence. The second question is how to optimize the size of incentives over time to maximize incentive effectiveness. This will be done by randomly varying the size and timing of incentives offered to participants in both the Inputs and Outcomes groups. The incentive amounts will then be varied across participants and time to fit a structural model of abstinence behaviors over time. The model will be used to describe the optimal shape of incentives over time.

Description:

Numerous studies have tested whether providing incentives to encourage abstinence from drugs can further reduce drug abuse in a drug-treatment setting. The results are promising: Incentives to reduce opioid abuse increase the average duration of abstinence by 25 - 60% relative to medication and counseling alone. Similar effects have been demonstrated repeatedly across a wealth of populations, substance-abuse disorders, and payment methodologies. Despite evidence that incentives are effective and the increasing need for effective approaches to combat the addiction crisis, incentive programs have not been widely implemented. A key barrier is that while the benefits are largely borne by patients and taxpayers, there are large logistical costs that must be borne by clinics: most existing incentive programs involve manual, in-person measurement of behaviors, and prize or voucher purchase and delivery by clinic staff. The significant clinic-level legwork necessary to set up these programs, including setting up behavioral and payment tracking systems, training staff, etc., have prevented the programs from scaling widely. In sum, prior experience has consistently shown that incentives increase duration of treatment and decrease substance abuse, but the logistical complications remain a hurdle to implementation. This will be the first randomized evaluation of an innovative, scalable incentives program for opioid addiction delivered through a mobile application. The application, which was developed by our implementing partner, DynamiCare Health, provides a "turnkey" solution that health clinics can easily prescribe. The app enables remote monitoring of behavior; for example, drug tests can be administered in patients' homes, as patients submit "selfie-videos" showing them taking saliva drug tests, which are then verified by trained remote staff. Treatment adherence can similarly be checked through GPS tracking for on-site methadone pharmacotherapy. The efficacy of this approach has not been tested rigorously before. This study will address two key knowledge gaps in the logistics of existing incentive program design for opioid addiction. First, the first technology t for remote monitoring of abstinence behavior for opioid use will be tested. Remote monitoring of abstinence from cigarettes and alcohol has been integral in reducing the costs and extending the potential reach of incentive programs for people with nicotine/tobacco and alcohol use disorders (e.g. to vulnerable or rural populations), and this study promises to do the same for opioid addiction. The second gap is in remote delivery of incentives. After a behavior is verified, the app will deliver incentives to patients as cash available on a linked debit card. The delay between monitoring of the target behavior and the delivery of financial incentives has been shown to be a significant moderator of treatment effect size. This technology allows patients to receive incentives almost immediately following the undertaking of the incentivized behavior: a first in incentives for opioid addiction. Another novel feature of this design is that can allow assessment of a gap in the literature on incentive delivery: comparing both the isolated effects of incentives and of the monitoring needed to implement an incentive program. In addition to a control group, this study includes both monitoring groups and incentives groups. While existing literature on incentives for addiction has included either a monitoring group or a control group, this is the first to include both, such that a comparison can be made between incentives that are distal (inputs) and proximal (outcome) to the targeted abstinence behavior. Finally, this study will directly address two key open questions in the literature on incentives for drug-users. The first question is whether it is more effective to directly incentivize the outcome of interest - drug abstinence - or to incentivize behaviors that are inputs into the production of abstinence. Similarly designed studies did not detect different effects on abstinence from incentivizing treatment attendance and incentivizing cocaine abstinence among cocaine users (both were effective): however, not only was this study for a different substance use disorder, but because of differential rates of test submission among these two groups, the results were not conclusive. This study will similarly compare two versions of the incentive program: one that incentivizes inputs to achieving abstinence, and one that incentivizes the outcome of abstinence. To address differential test submission rates, the impacts of the intervention will be measured via urine drug-tests administered identically to patients in both treatments. The second question is how to optimize the size of incentives over time to maximize incentive effectiveness. This will be assessed by randomly varying the size and timing of incentives offered to participants in both the Inputs and Outcomes groups. The variation in incentive amounts across participants and time to fit a structural model of abstinence behaviors over time. The model will be used to describe the optimal shape of incentives over time. The results of this intervention will be directly relevant for potential users of this or similar mobile applications for incentive provision among people with opioid-use disorders, including insurers, treatment facilities, and governments.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 36
• Est. completion date: May 15, 2021
• Est. primary completion date: May 1, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion

1. Age at least 18 years old;

2. Meet DSM-5 opioid use disorder criteria as evidenced by an opioid disorder CPT code F11 (opioid related disorders);

3. Have access to a smartphone (iOS or Android) with data plan and willing to download DynamiCare app;

4. Are in day (PHP) or partial day (IOP) AODA treatment in Aurora Health's Behavioral Health Program;

5. Are currently prescribed or will be prescribed within 1-4 days oral buprenorphine for their OUD;

6. Are likely to be helped by contingency management because at least ONE of the

following conditions is true:

1. Were first enrolled in day or partial day opioid treatment no longer than 1 week prior to providing informed consent.

2. Currently using non-medical opioids.

3. Regularly missing scheduled AODA appointments.

7. Understands English.

Exclusion Criteria:

1. Have evidence of active (non-substance related) psychosis that might impair participation as determined by the PI.

2. Has significant cognitive impairment that might confound participation as determined by the PI or are so significantly cognitively impaired that they have a legal guardian. Note that pregnant women are not excluded from participating in the study

Related Conditions & MeSH terms

• Behavior Therapy
• Disease
• Opioid-Related Disorders
• Substance-Related Disorders

Intervention

Behavioral:
• App + Inputs Contingency Management
The app has programmed contingencies whereby incentives can be earned for behaviors that are inputs to abstaining from drug use (e.g., attending psychotherapy or taking SUD psychopharmacology).
• App + Outcomes Contingency Management
The app has programmed contingencies whereby incentives can be earned for outcomes of abstaining from drug use (e.g., drug-negative saliva samples on saliva opioid tests).

Locations

Country	Name	City	State
United States	University of California - Santa Cruz	Berkeley	California
United States	University of Chicago	Chicago	Illinois
United States	Aurora Psychiatric Hospital	Wauwatosa	Wisconsin

Sponsors (3)

Lead Sponsor	Collaborator
Aurora Health Care	University of California, Berkeley, University of Chicago

Country where clinical trial is conducted

United States, 

References & Publications (5)

Benishek LA, Dugosh KL, Kirby KC, Matejkowski J, Clements NT, Seymour BL, Festinger DS. Prize-based contingency management for the treatment of substance abusers: a meta-analysis. Addiction. 2014 Sep;109(9):1426-36. doi: 10.1111/add.12589. Epub 2014 May 23. — View Citation

Kurti AN, Davis DR, Redner R, Jarvis BP, Zvorsky I, Keith DR, Bolivar HA, White TJ, Rippberger P, Markesich C, Atwood G, Higgins ST. A Review of the Literature on Remote Monitoring Technology in Incentive-Based Interventions for Health-Related Behavior Change. Transl Issues Psychol Sci. 2016 Jun;2(2):128-152. — View Citation

Lussier JP, Heil SH, Mongeon JA, Badger GJ, Higgins ST. A meta-analysis of voucher-based reinforcement therapy for substance use disorders. Addiction. 2006 Feb;101(2):192-203. Review. — View Citation

Petry NM, Alessi SM, Carroll KM, Hanson T, MacKinnon S, Rounsaville B, Sierra S. Contingency management treatments: Reinforcing abstinence versus adherence with goal-related activities. J Consult Clin Psychol. 2006 Jun;74(3):592-601. — View Citation

Schottenfeld RS, Chawarski MC, Pakes JR, Pantalon MV, Carroll KM, Kosten TR. Methadone versus buprenorphine with contingency management or performance feedback for cocaine and opioid dependence. Am J Psychiatry. 2005 Feb;162(2):340-9. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Continuous Abstinence From Opioid Use	The primary endpoint is the longest period of continuous abstinence from illicit opioids, where abstinence is measured using lab-verified in-person urine-tests, saliva tests, or subject reporting (in the absence of urine testing).	Time = 4 weeks
Primary	Continuous Abstinence From Opioid Use	The primary endpoint is the longest period of continuous abstinence from illicit opioids, where abstinence is measured using lab-verified in-person urine-tests, saliva tests, or subject reporting (in the absence of urine testing).	Time = 8 weeks
Primary	Opioid-negative Saliva Tests at Week 12	The primary endpoint is the % of opioid-negative saliva or urine tests in each group at Week 12	Time = 12 weeks