Neurocognitive Mechanisms Underlying Smartphone-Assisted Prevention of Relapse in Opioid Use Disorder

Study Overview
=================
Brief Summary
-----------------
The proposed clinical trial would evaluate the use of smartphone applications (apps, which have well-established efficacy in reducing cigarette and alcohol use) to prevent relapse among patients receiving medication-assisted treatment for opioid use disorder. In addition to standard app-based self-monitoring of drug use and personalized feedback, project innovation is enhanced by the proposed use of location-tracking technology for targeted, personalized intervention when participants enter self-identified areas of high risk for relapse. Furthermore, the proposed sub-study would use longitudinal functional neuroimaging to elucidate the brain-cognition relationships underlying individual differences in treatment outcomes, offering broad significance for understanding and enhancing the efficacy of this and other app-based interventions.

Detailed Description
-----------------
The rising public health burden of opioid misuse, coupled with high relapse rates among individuals seeking treatment for opioid use disorder, necessitates novel interventions for improving opioid-related treatment response. Mobile technology such as smartphone-based applications (apps) represent one such intervention. Although smartphone apps are effective in reducing cigarette and alcohol use, their efficacy for reducing opioid use has not yet been established. The proposed clinical trial would evaluate the app OptiMAT (Optimizing Medication-Assisted Treatment) to prevent relapse among patients receiving medication-assisted treatment for opioid use disorder. OptiMAT implements two features shown to be effective for reducing substance use: daily self-monitoring of opiate use coupled with personalized feedback. Aim 1 would accrue 255 participants with 1:1 randomization into two arms (OptiMAT vs. Monitoring only) to evaluate differences in monthly opioid use at six months post-enrollment. Aim 2 would enroll a subset of participants (N=120; 60 per arm) into a longitudinal functional neuroimaging (fMRI) study to model the neurocognitive mechanisms underlying individual differences in treatment response. Two putative mechanisms (attentional bias for drug cues and cue-induced craving) promoting abstinence would be studied. Aim 3 would explore the use of location-based geographic ecological momentary assessment (GEMA) for targeted intervention when participants enter self-identified areas of high risk for relapse. Collectively, the proposed aims would (1) evaluate mobile technology applications for reducing opiate use, (2) understand the neurocognitive mechanisms of action to improve upon this and other apps aiming to reduce drug use, and (3) evaluate the role of personalized, contextually-relevant intervention to promote successful treatment outcomes.

Official Title
-----------------
Neurocognitive Mechanisms Underlying Smartphone-Assisted Prevention of Relapse in Opioid Use Disorder

Conditions
-----------------
Ecological Momentary Assessment, Opioid-Related Disorders, Mobile Applications, Opiate Substitution Treatment, Magnetic Resonance Imaging, Craving, Attentional Bias

Intervention / Treatment
-----------------
* Device: Smartphone


Participation Criteria
=================
Eligibility Criteria
-----------------
Inclusion Criteria: Sex: male or female Age: 18 years and older (MRI sub-study): Age: 18-50 years old In Phase I treatment of MAT for opioid-use disorder. (Phase I indicates that patient is receiving no more than one week of take-home medications at each weekly clinic visit.) Must be willing to use a smartphone if randomized to the smartphone intervention arm (MRI sub-study): Native English-speaking Exclusion Criteria: (MRI) Medical history: A history of neurological, cardiovascular, or infectious disease would exclude study participation. A loss of consciousness of 20 or more min or other evidence of brain trauma also would be exclusionary. (MRI) Pregnancy: A positive test for pregnancy prior to fMRI would exclude participation, due to unknown effect of high-field MRI on developing fetus. (MRI) MRI contraindications: Exclusion criteria for MRI include (1) the presence of non-removable internal (e.g., cardiac pacemakers, aneurysm clips, artificial joints) or external (e.g., piercings, orthodontics) ferromagnetic objects; (2) claustrophobia in a confined MRI environment; (3) medications that interfere with hemodynamic coupling (e.g., beta blockers); (4) hypersensitivity to loud noise; or (5) a body circumference exceeding 60cm due to broad shoulders or morbid obesity

Ages Eligible for Study
-----------------
Minimum Age: 18 Years

Sexes Eligible for Study
-----------------
All

Accepts Healthy Volunteers
-----------------
No

Study Plan
=================
How is the study designed?
-----------------

Design Details

Primary Purpose: Treatment
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Participants will be randomized to one of two arms: a Monitor Only arm (aka treatment-as-usual, MAT only) and a Smartphone arm (aka OptiMAT plus MAT).
Masking: Triple


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Smartphone<br>Participants randomized into the Smartphone app arm would use the smartphone app OptiMAT in conjunction with treatment as usual (TAU). Participants would use OptiMAT to complete daily self-assessments of opiate misuse, opiate craving, opiate withdrawal, and mood. The app will personalized feedback for maintaining abstinence goals. The app would also use geographic ecological momentary assessment (GEMA) to intervene via push notification when participants enter areas previously identified as high-risk for opiate use. | Device: Smartphone<br>* Adjunctive Smartphone app for improving MAT outcomes<br>* Other names: OptiMAT, Optimizing MAT;|
| No Intervention: Monitoring Only<br>Participants randomized into the Monitoring Only arm would undergo treatment as usual (TAU) but without the smartphone app. | |

What is the study measuring?
-----------------
Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Urinalysis - Week 0 (Intake) | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 1 day | 
| Urinalysis - Week 1 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 1 week | 
| Urinalysis - Week 2 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 2 weeks | 
| Urinalysis - Week 3 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 3 weeks | 
| Urinalysis - Week 4 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 4 weeks | 
| Urinalysis - Week 5 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 5 weeks | 
| Urinalysis - Week 6 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 6 weeks | 
| Urinalysis - Week 7 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 7 weeks | 
| Urinalysis - Week 8 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 8 weeks | 
| Urinalysis - Week 9 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 9 weeks | 
| Urinalysis - Week 10 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 10 weeks | 
| Urinalysis - Week 11 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 11 weeks | 
| Urinalysis - Week 12 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 12 weeks | 
| Urinalysis - Week 13 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 13 weeks | 
| Urinalysis - Week 14 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 14 weeks | 
| Urinalysis - Week 15 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 15 weeks | 
| Urinalysis - Week 16 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 16 weeks | 
| Urinalysis - Week 17 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 17 weeks | 
| Urinalysis - Week 18 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 18 weeks | 
| Urinalysis - Week 19 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 19 weeks | 
| Urinalysis - Week 20 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 20 weeks | 
| Urinalysis - Week 21 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 21 weeks | 
| Urinalysis - Week 22 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 22 weeks | 
| Urinalysis - Week 23 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 23 weeks | 
| Urinalysis - Week 24 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 24 weeks | 
| Urinalysis - Week 25 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 25 weeks | 
| Urinalysis - Week 26 | Percent of weekly urinalysis tests positive for opioid metabolite other than Suboxone | 26 weeks | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| TLFB - Month 0 (Intake) | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 1 day | 
| TLFB - Month 1 | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 1 month | 
| TLFB - Month 2 | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 2 months | 
| TLFB - Month 3 | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 3 months | 
| TLFB - Month 4 | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 4 months | 
| TLFB - Month 5 | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 5 months | 
| TLFB - Month 6 | Days per Month of self-reported opioid misuse from monthly TimeLine FollowBack calendar over past 30 days | 6 months | 
| Treatment Continuation - Week 1 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 1 week | 
| Treatment Continuation - Week 2 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 2 weeks | 
| Treatment Continuation - Week 3 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 3 weeks | 
| Treatment Continuation - Week 4 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 4 weeks | 
| Treatment Continuation - Week 5 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 5 weeks | 
| Treatment Continuation - Week 6 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 6 weeks | 
| Treatment Continuation - Week 7 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 7 weeks | 
| Treatment Continuation - Week 8 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 8 weeks | 
| Treatment Continuation - Week 9 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 9 weeks | 
| Treatment Continuation - Week 10 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 10 weeks | 
| Treatment Continuation - Week 11 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 11 weeks | 
| Treatment Continuation - Week 12 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 12 weeks | 
| Treatment Continuation - Week 13 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 13 weeks | 
| Treatment Continuation - Week 14 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 14 weeks | 
| Treatment Continuation - Week 15 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 15 weeks | 
| Treatment Continuation - Week 16 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 16 weeks | 
| Treatment Continuation - Week 17 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 17 weeks | 
| Treatment Continuation - Week 18 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 18 weeks | 
| Treatment Continuation - Week 19 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 19 weeks | 
| Treatment Continuation - Week 20 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 20 weeks | 
| Treatment Continuation - Week 21 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 21 weeks | 
| Treatment Continuation - Week 22 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 22 weeks | 
| Treatment Continuation - Week 23 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 23 weeks | 
| Treatment Continuation - Week 24 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 24 weeks | 
| Treatment Continuation - Week 25 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 25 weeks | 
| Treatment Continuation - Week 26 | Binary variable if participant is still in treatment (yes/no). Survival analysis will determine if duration of treatment (i.e. time to treatment discontinuation) differs between study arms | 26 weeks |