# A Chatbot Utilizing Machine Learning and Natural Language Processing to Implement the Brief Negotiation Interview to Improve Engagement in Buprenorphine Treatment among Justice-Involved Individuals

> **NIH NIH R43** · CENTER FOR PROGRESSIVE RECOVERY, LLC · 2020 · $251,500

## Abstract

PROJECT SUMMARY/ABSTRACT
The people at greatest risk of dying from an opioid overdose are the least likely to get
life-saving medication. Justice-involved individuals coming out of prison have the highest risk
of death by overdose (8x greater than the general population), yet only 1 in 20 of these
individuals receive buprenorphine (bup), a safe, effective medication that has been shown to
reduce a person’s risk of death by overdose by half. There is an urgent need to facilitate an
increase in bup treatment engagement among these individuals. Two of the top barriers to
receiving bup for these individuals are 1) system level barriers and, 2) low levels of individual
motivation. Our prior research shows that delivering individual level treatment engagement
interventions increase the rate at which individuals receive bup. Thus, our solution is to
improve engagement in bup treatment among justice-involved individuals by 1) “disrupting”
system level barriers by circumventing the pieces of the probation system that are
stigmatizing and reduce the chances of a bup referral by using an artificial intelligence
(AI)-based chatbot to make the referral, and 2) addressing low individual motivation by
programming the chatbot to deliver the BNI itself, without the need for a trained professional.
Aim 1: Design and develop a functional prototype chatbot to motivate bup engagement.
Milestones: (a) human-centered design (including focus groups) with all stakeholders; and (b)
creation of a functional chatbot using ML and NLP that is integrated with a mobile application,
an application program interface server, and an administrator portal.
Aim 2: Conduct a 4-week pilot study with 60 probationers randomly assigned to BNI Chatbot
or Treatment-as-Usual (TAU).
Hypothesis 1. The BNI Chatbot group will have a higher percentage of participants attending
their first bup appointment than the TAU group at 4 weeks (Primary outcome).
Hypothesis 2. The BNI Chatbot group will demonstrate higher ratings of readiness and
intention to engage in bup treatment, and lower opioid use, as measured by urine toxicology
tests, than the TAU group at 4 weeks (Secondary outcomes).
Hypothesis 3. The BNI Chatbot group will demonstrate higher ratings of satisfaction than the
TAU group.

## Key facts

- **NIH application ID:** 10157712
- **Project number:** 1R43DA051267-01A1
- **Recipient organization:** CENTER FOR PROGRESSIVE RECOVERY, LLC
- **Principal Investigator:** MICHAEL V PANTALON
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $251,500
- **Award type:** 1
- **Project period:** 2020-09-30 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10157712

## Citation

> US National Institutes of Health, RePORTER application 10157712, A Chatbot Utilizing Machine Learning and Natural Language Processing to Implement the Brief Negotiation Interview to Improve Engagement in Buprenorphine Treatment among Justice-Involved Individuals (1R43DA051267-01A1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10157712. Licensed CC0.

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