Peer Recovery Coach Training + MHealth Platform for Opioid Overdose

Recruiting at 1 trial location

Overseen By Ana Ventuneac, PHd

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Friends Research Institute, Inc.

Disqualifiers: Disability preventing phone use, others

Compensation: Varies

Number of Visits: Unknown

180 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to assist individuals with opioid use disorder (OUD) by testing new support methods. It will examine whether combining peer support with AI-driven text messages (PRC-supported text + AI-driven CSDH-enhanced text) can improve connections to opioid treatment and social services. Participants may receive texts from recovery coaches and AI, or only AI texts, while a third group will continue with their usual treatment. Individuals who have recently used non-prescription opioids, are interested in starting medication like buprenorphine, and are Black or Latinx living in NYC may be well-suited for this trial. As an unphased trial, this study provides a unique opportunity to explore innovative support methods that could enhance treatment connections and outcomes.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that this intervention is safe?

Research has shown that the AI-driven texting tool used in this study is safe. Studies have found that AI systems, when used properly, help maintain patient safety. As a result, participants are likely to respond well to the AI-enhanced text messaging.

The training for peer recovery coaches (PRCs) follows a proven model, indicating that the approach has been tested and is not expected to cause harm.

In summary, both the AI-driven text and the PRC support rely on methods that have been verified for safety, making them likely to be well-received in this trial. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about these treatments because they bring a fresh approach to tackling opioid overdose recovery. Traditional treatments often rely on medication-assisted therapy and counseling. However, this new approach uses a Peer Recovery Coach (PRC) supported text system combined with an AI-driven, context-sensitive digital health (CSDH) platform. This method not only provides personalized support but also leverages artificial intelligence to enhance communication and engagement, potentially leading to more effective recovery outcomes. Additionally, the AI-driven CSDH-enhanced text messaging stands out by offering tailored, automated support that adapts to the individual's needs, which is a departure from the more static traditional methods.

What evidence suggests that this trial's treatments could be effective for opioid overdose?

This trial will compare different approaches to support individuals with opioid use disorder. Participants in Intervention Arm-1 will receive a combination of peer recovery coach (PRC) supported text check-ins and AI-driven CSDH-enhanced text messaging. Research has shown that combining support from PRCs with smart text messaging can be helpful, as PRCs provide regular check-ins and encouragement, boosting participation in treatment.

In Intervention Arm-2, participants will receive AI-driven CSDH-enhanced text messaging only. One study confirmed this method's ability to offer real-time, personalized support by using artificial intelligence to send messages that consider the user's social situation, making the support feel more relevant and personal.

While both methods are still being tested in this trial, early results suggest they could effectively increase involvement in opioid treatment programs. ^{1 5 6 7 8}

Who Is on the Research Team?

Ana Ventuneac

Principal Investigator

START Treatment and Recovery

Are You a Good Fit for This Trial?

This trial is for Black and/or Latinx individuals over 18 years old, fluent in English, who have used opioids without a prescription within the last month. They must be interested in starting buprenorphine treatment, plan to stay in NYC for at least 3 months, and have a positive drug test or Opioid Use Disorder diagnosis.

Inclusion Criteria

Provision of informed consent

Self-reported non-prescription opioid use <30 days prior to consent

Black and/or Latinx race/ethnicity

Exclusion Criteria

Inability to comprehend text content written at a 3rd grade reading level

I cannot use a mobile phone due to a physical or visual disability.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants receive PRC-supported text check-ins and AI-driven CSDH-enhanced text messaging or AI-driven CSDH-enhanced text messaging only

12 weeks

Ongoing virtual interactions

Follow-up

Participants are monitored for changes in stigma, cost, and service use post-intervention

3 months

What Are the Treatments Tested in This Trial?

Interventions

• AI driven CSDH-enhanced text only
• PRC supported text + AI driven CSDH-enhanced text

Trial Overview The study tests an AI-driven texting tool and video training for peer recovery coaches (PRCs) to see if they help people with opioid use disorder start treatment and access social services. It compares usual care with two tech-supported interventions: one with PRC support texts plus AI texts, another with just AI texts.

How Is the Trial Designed?

Group I: Intervention Arm-2: AI driven CSDH-enhanced text only Experimental Treatment 1 Intervention

Individuals randomized to Arm-2 will receive the AI-driven CSDH-enhanced text messaging only

Group II: Intervention Arm-1: PRC supported text+ AI driven CSDH-enhanced text Experimental Treatment 1 Intervention

Individuals randomized to Arm-1 will receive PRC-supported text check-ins and AI-driven CSDH-enhanced text messaging.

Group III: Control Arm 3- Treatment as Usual Placebo Group 1 Intervention

Individuals randomized to the control arm will receive treatment as usual.

Who Is Running the Clinical Trial?

Friends Research Institute, Inc.

Lead Sponsor

Trials

60

Recruited

22,500+

NYU Langone Health

Collaborator

Trials

1,431

Recruited

838,000+

Nathan Kline Institute for Psychiatric Research

Collaborator

Trials

40

Recruited

3,300+

Published Research Related to This Trial

The Mobile Intervention Kit (MIK) is a tablet-based program that effectively combines overdose prevention training with HIV and HCV testing, showing high acceptability among people who inject drugs in a Bronx outreach program.

Participants demonstrated significant increases in knowledge about overdose prevention and testing procedures after using the MIK, indicating its potential as a valuable tool for addressing opioid overdose and viral infections in underserved communities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mobile Technology to Increase HIV/HCV Testing and Overdose Prevention/Response among People Who Inject Drugs. Aronson, ID., Bennett, A., Marsch, LA., et al.[2020]

The tailored telephone intervention delivered by peers (TTIP-PRO) was well-received by participants, with all eight patients finding it 'very helpful' and showing a significant increase in their knowledge about opioid overdoses, from 69.9% to 93.6% correct responses after the intervention.

While interest in starting medication-assisted treatment (MAT) increased from 8.1 to 9.5 on a 10-point scale, this change was not statistically significant, indicating that further development and testing of TTIP-PRO is needed to effectively encourage MAT enrollment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development and initial testing of a tailored telephone intervention delivered by peers to prevent recurring opioid-overdoses (TTIP-PRO). Winhusen, T., Theobald, J., Lewis, D., et al.[2022]

A technology-assisted education program effectively taught 40 adults at high risk of opioid overdose about opioids and related medications, with significant improvements in test accuracy after each course (p < .001).

Participants completed the program in a median time of 91 minutes, and the learning outcomes were consistent across different backgrounds, indicating the program's broad applicability and potential for reducing overdose risk.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Technology-assisted opioid education for out-of-treatment adults with opioid use disorder. Toegel, F., Novak, MD., Rodewald, AM., et al.[2023]

An educational intervention on opioid overdose delivered through either computer or pamphlet significantly increased participants' knowledge about opioid effects and overdose responses, with the most notable improvement in understanding how to respond to an overdose (from 41.8% to 73.8% correct responses).

The intervention not only improved knowledge but also led to a reduction in risky behaviors, such as using opioids alone, which is a critical factor in overdose risk, and this knowledge was retained at 1 and 3-month follow-ups.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Randomized controlled trial of a computerized opioid overdose education intervention. Dunn, KE., Yepez-Laubach, C., Nuzzo, PA., et al.[2022]

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT06573476

Addressing Racial Disparities in Opioid Overdose Using ... Intervention Arm-2: AI driven CSDH-enhanced text only. Individuals randomized to Arm-2 will receive the AI-driven CSDH-enhanced text messaging only.

2. withpower.com withpower.com/trial/phase-opiate-overdose-11-2024-c8129

Peer Recovery Coach Training + MHealth Platform for ... Trial Overview The study tests an AI-driven texting tool and video training for peer recovery coaches (PRCs) to see if they help people with opioid use disorder ...

3. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC11488086/

Design and development of a machine-learning-driven opioid ... Our ML-driven CDS tool for predicting opioid overdose offers valuable insights for future AI-based CDS tools in healthcare. First, the ...

4. cdn.clinicaltrials.gov cdn.clinicaltrials.gov/large-docs/67/NCT06569667/Prot_SAP_000.pdf

Leveraging social determinants via artificial intelligence ... With NIH support, we have validated a theory-driven, artificial intelligence (AI)-driven texting tool using natural language processing to facilitate real-time ...

5. reporter.nih.gov reporter.nih.gov/project-details/11212721

Improving the prediction of opioid outcomes via automated ... This project addresses these issues by leveraging automated machine learning (AutoML), knowledge graphs (KGs), and generative AI to enhance data ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC7414411/

Role of Artificial Intelligence in Patient Safety Outcomes This systematic review indicates that AI-enabled decision support systems, when implemented correctly, can aid in enhancing patient safety.

7. cdc.gov cdc.gov/nchs/data/series/sr_02/sr2-188.pdf

Enhancing Identification of Opioid-involved Health ... Comprehensive data on opioid-involved emergency department (ED) encounters and inpatient hospitalizations will assist researchers in identifying and testing ...

8. bioelecmed.biomedcentral.com bioelecmed.biomedcentral.com/articles/10.1186/s42234-024-00156-3

Design and development of a machine-learning-driven opioid ... We aimed to design a ML-driven CDS tool to predict opioid overdose risk and gather feedback for its integration into the University of Florida Health (UFHealth)