This proposal develops a novel, artificial-intelligence (AI) enabled, mobile treatment delivery method that fulfills the need for a robust, secure, technology-based peer support platform to support patients with opioid use disorders (OUDs). The majority of individuals with OUDs in the United States do not receive any formal substance use treatment, and growing evidence suggests that many OUD patients turn to online social platforms to access peer support and obtain health-related information about addiction and recovery. While engagement with peers before and during recovery is a key component of many evidence-based addiction recovery programs, commonly-used online social platforms (e.g. Reddit) lack effective content moderation, with inappropriate messages ranging from misinformed advice to maliciousness. This lack of oversight precludes a deeper integration of peer support and clinical care. Our mobile platform allows patients to access a tailored support group 24/7, and is augmented with AI tools capable of understanding the emotional sentiment in messages, automatically `flagging' critical or clinically relevant content, creating a scalable system to keep groups safe and constructive. This phase I proposal demonstrates the robustness of these AI tools by adapting them to catch OUD-specific `flags' in peer messages while also examining the adoptability of the platform itself within OUD patients. A subsequent phase II proposal will test tailored, real-time interventions to `flags', allowing the commercialization of a system to harness the engagement and self-disclosure of peer groups in a clinical setting.
Public Health Relevance Statement: PROJECT NARRATIVE The widespread and chronic nature of opioid use disorder (OUD) necessitates investment in highly scalable technology solutions. Our work has the potential to dramatically broaden access to care for patients, particularly those in highly stigmatized and rural communities, while taking an entirely novel approach to patient triaging and tracking through artificial intelligence technology. Such technology has the potential to enable new modalities of treatment and lays the foundation for a more cost-effective, yet personalized, approach to chronic OUD care.
Project Terms: addiction; Adopted; Alcohol or Other Drugs use; Algorithms; Ambulatory Care; American; Artificial Intelligence; barrier to care; base; behavioral health intervention; Caring; Chronic; Clinical; clinical care; clinical infrastructure; clinically relevant; commercialization; Communities; Consent; cost effective; craving; Data; Databases; Development; efficacy testing; Emotional; Ethics; evidence base; experience; Feedback; Foundations; Goals; Health; Health Services Accessibility; Healthcare Systems; Hospitals; improved; Individual; Industry Standard; innovation; Intervention; Interview; Investments; Language; Machine Learning; Mental Health; Methods; mHealth; mobile application; mobile computing; Modality; Modeling; Monitor; Morbidity - disease rate; mortality; Natural Language Processing; Nature; novel; novel strategies; Opioid; opioid use; opioid use disorder; Pain; Participant; Patient Care; Patient Recruitments; Patient Triage; Patients; peer; Peer Group; peer support; personalized approach; Phase; primary outcome; programs; Protocols documentation; Provider; Recording of previous events; Recovery; Recurrence; Relapse; Research Infrastructure; Research Personnel; Resources; Rhode Island; Risk; Rural Community; Sampling; satisfaction; Secure; Security; Self Disclosure; Self Efficacy; Self-Injurious Behavior; Services; Signal Transduction; Small Business Technology Transfer Research; social; social stigma; Source; Speech; standard care; Stigmatization; Support Groups; System; Technology; Testing; Text; Text Messaging; Time; tool; Training; United States; usability; Work
