Mobile Peer-Support for Opioid Use Disorders: Refinement of an Innovative Machine Learning Tool-Journal of Psychiatry and Brain Science-CSCIED科技核心评价数据库-手机版

Mobile Peer-Support for Opioid Use Disorders: Refinement of an Innovative Machine Learning Tool

Mobile Peer-Support for Opioid Use Disorders: Refinement of an Innovative Machine Learning Tool

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DOI	10.20900/jpbs.20200001
刊名	Journal of Psychiatry and Brain Science JPBS
年，卷(期)	2020, 5(1)
作者	Caroline R. Scherzer,Megan L. Ranney,Shrenik Jain,Satya Prateek Bommaraju,John Patena,Kirsten Langdon,Evelyn Nimaja,Ernestine Jennings,Francesca L. Beaudoin*,
作者单位	Department of Emergency Medicine, Rhode Island Hospital, 593 Eddy Street, Providence, RI 02903, USA ; 1Department of Emergency Medicine, Rhode Island Hospital, 593 Eddy Street, Providence, RI 02903, USA ; Marigold Health, 2 Ave de Lafayette, Boston, MA 02111, USA ; Department of Psychiatry, Rhode Island Hospital, 593 Eddy Street, Providence, RI 02903, USA ; 5Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 700 Butler Drive, Providence, RI 02906, USA ;
Abstract	Background: The majority of individuals with Opioid Use Disorder (OUD) do not receive any formal substance use treatment. Due to limited engagement and access to traditional treatment, there is increasing evidence that patients with OUDs turn to online social platforms to access peer support and obtain health-related information about addiction and recovery. Interacting with peers before and during recovery is a key component of many evidence-based addiction recovery programs, and may improve self-efficacy and treatment engagement as well as reduce relapse. Commonly-used online social platforms are limited in utility and scalability as an adjunct to addiction treatment; lack effective content moderation (e.g., misinformed advice, maliciousness or “trolling”); and lack common security and ethical safeguards inherent to clinical care. Methods: This present study will develop 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 OUD. Forty adults receiving outpatient buprenorphine treatment for OUD will be asked to pilot a smartphone-based mobile peer support application, the “Marigold App”, for a duration of six weeks. The program will use (1) a prospective cohort study to obtain text message content and feasibility metrics, and (2) qualitative interviews to evaluate usability and acceptability of the mobile platform. Anticipated findings and future directions: The Marigold mobile platform will allow patients to access a tailored chat support group 24/7 as a complement to different forms of clinical OUD treatment. Marigold can keep groups safe and constructive by augmenting chats with AI tools capable of understanding the emotional sentiment in messages, automatically “flagging” critical or clinically relevant content. This project will demonstrate 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.
KeyWord	opioid use disorder; peer support; machine-learning; technology; natural language processing; mobile treatment; application
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引用本文

Caroline R. Scherzer,Megan L. Ranney,Shrenik Jain,Satya Prateek Bommaraju,John Patena,Kirsten Langdon,Evelyn Nimaja,Ernestine Jennings,Francesca L. Beaudoin*. Mobile Peer-Support for Opioid Use Disorders: Refinement of an Innovative Machine Learning Tool, Journal of Psychiatry and Brain Science. 2020; 5; (1). https://doi.org/10.20900/jpbs.20200001.

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