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

聊天机器人利用机器学习和自然语言处理来实施简短的谈判访谈，以提高参与正义的个人对丁丙诺啡治疗的参与度

• 批准号: 10157712
• 负责人: MICHAEL V PANTALON
• 金额: $ 25.15万
• 依托单位: CENTER FOR PROGRESSIVE RECOVERY, LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10157712
• 关键词: Address; Administrator; Appointment; Area; Artificial Intelligence; Buprenorphine; Caring; Communities; Continuity of Patient Care; Development; Drug Courts; Evidence based intervention; Evidence based treatment; Failure; Focus Groups; General Population; Health; Human; Individual; Intention; Intervention; Interview; Jail; Justice; Life; Machine Learning; Measures; Mediation; Motivation; National Institute of Drug Abuse; Natural Language Processing; Participant; Persons; Pharmaceutical Preparations; Pilot Projects; Population; Prisons; Process; Provider; Randomized; Readiness; Research; Research Priority; Risk; Savings; Secure; Stigmatization; System; Technology; Testing; Toxicology; Training; Urine; addiction; application programming interface; base; brief motivational intervention; buprenorphine treatment; chatbot; commercialization; design; digital; evidence base; high risk; improved; innovation; mobile application; mortality risk; motivational intervention; opioid overdose; opioid use; opioid use disorder; overdose death; overdose risk; primary outcome; probation; probationer; prototype; satisfaction; secondary outcome; system-level barriers; treatment as usual; web app

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.

项目摘要/摘要 从阿片类药物过量中死亡的最大风险的人最不可能得到 挽救生命的药物。从监狱出狱的司法人员的风险最高 用药过量的死亡（比一般人口大8倍），但其中只有1个 个人接受丁丙诺啡（BUP），这是一种安全，有效的药物，已被证明 通过过量服用的人的死亡风险降低了一半。迫切需要促进 这些个体之间的BUP治疗参与度增加。两个最高障碍 为这些人接收BUP是1）系统水平障碍和2）个体低水平 动机。我们先前的研究表明，提供个人水平治疗参与 干预措施增加了个人收到BUP的速度。那是我们的解决方案 通过1）“破坏”，改善了诉讼案件的个人的BUP治疗 通过规避探针系统的部分，系统水平屏障 通过使用人工智能，污名化和减少BUP转介的机会 （AI）基于聊天机器人进行推荐，2）通过 编程聊天机器人以交付BNI本身，而无需训练有素的专业人员。 AIM 1：设计和开发功能性原型聊天机器人，以激发BUP参与度。 里程碑：（a）以人为中心的设计（包括焦点小组）与所有利益相关者； （b） 使用与移动应用程序集成的ML和NLP创建功能性聊天机器人 应用程序程序接口服务器和管理员门户。 AIM 2：进行为期4周的试点研究，并随机分配给BNI Chatbot的60个试验器 或治疗态度（tau）。 假设1。BNI聊天机器人小组将有更高比例的参与者参加 他们的第一个BUP任命比TAU组在4周（主要结果）。 假设2。BNI聊天机器人小组将表现出更高的准备就绪和 尿液毒理学测量的目的 测试，比tau组在4周（次要结果）。 假设3。BNI聊天机器人组将显示出比 tau集团。