LEVERAGING PREDICTIVE ANALYTICS WITHIN SOCIAL NETWORKS TO MAXIMIZE DRUG ANDALCOHOL TREATMENT EFFICACY AND RELAPSE PREVENTION

利用社交网络内的预测分析最大限度地提高药物和酒精治疗的功效并预防复发

• 批准号: 9897501
• 负责人: Wendy Warrington
• 金额: $ 47.17万
• 依托单位: SOBER GRID, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9897501
• 关键词: Abstinence; Aftercare; Alcohol consumption; Alcohol dependence; Alcohol or Other Drugs use; Algorithms; Android; Back; Behavior; Behavioral; Cannabis; Caring; Cellular Phone; Characteristics; Client; Clinical; Communities; Cost Control; Data; Databases; Diagnostic; Drug Addiction; Drug usage; Enhancement Technology; Environment; Exercise; Foundations; Goals; Group Meetings; Health; Health Personnel; Health Services Accessibility; Healthcare Systems; Individual; Insurance; Intelligence; Intervention; Location; Machine Learning; Modeling; Monitor; Motivation; Natural Language Processing; Nicotine; Opiate Addiction; Opioid; Outcome; Participant; Patients; Personality Traits; Pharmaceutical Preparations; Phase; Population; Predictive Analytics; Privatization; Process; Production; Provider; Published Comment; Randomized; Recovery; Relapse; Reporting; Resources; Risk; Sampling; Services; Small Business Innovation Research Grant; Social Network; Social support; Societies; Stream; Substance Addiction; Substance Use Disorder; Substance abuse problem; Support Groups; Surveys; System; Technology; Telephone; Testing; Time; Treatment Efficacy; Underserved Population; Work; Writing; addiction; alcohol relapse; base; cloud based; cost; cost effective; design; disorder later incidence prevention; drug relapse; effective therapy; help-seeking behavior; high risk; high risk population; improved; innovation; insight; machine learning algorithm; marijuana use; medication-assisted treatment; member; mobile application; mobile computing; new technology; opioid use; peer; peer coaching; peer support; phase 2 study; prediction algorithm; preference; prevent; provider intervention; relapse risk; response; satisfaction; sobriety; social; social media; stimulant use; success; telehealth; tool; treatment center; treatment program; treatment services

PROJECT SUMMARY/ABSTRACT Sober Grid™ has developed a smartphone-based mobile application currently in use by over 120,000 individuals worldwide who are in, or seeking, recovery from drug and alcohol addiction. The “Grid”, as it is known, is a mobile-based, social recovery community providing rapid context- specific peer support, efficient help seeking, motivational enhancement exercises, and member ratings of support content – all aimed to prevent relapse. The overarching goal of this phase II project is to extend the current capabilities of the Sober Grid app to achieve a comprehensive social recovery support app featuring intelligent, context appropriate resource matching and 24/7 rapid response peer-coaching that is effective in reducing disordered substance use and is cost effective. We hypothesize that providing this functionality to high-risk members will be acceptable, feasible, increase access to and engagement with resources, and have a positive effect in increasing time to relapse and days of consecutive abstinence. The company’s priority commercial goal is to leverage the insights gained from its large database of information and behaviors recorded in its existing addiction recovery-focused social network, combined with its recently completed SBIR phase I work, to identify users at risk for relapse and deliver tailored lay and professional peer support, telehealth, and provider interventions prompted by near real-time automated risk indicators built into an Enhanced Sober Grid (ESG) solution. The specific goals of this proposed phase II project include: (1) implementing the relapse risk scoring algorithm successfully developed in phase I in a production environment, (2) developing a ML resource relevancy matching algorithm, and (3) using this system to pilot test the feasibility and acceptability as well as to estimate the effect on abstinence of providing peer-coaching and resource information to a national sample of Sober Grid members in recovery from non- alcohol/nicotine substances who are predicted to be at high risk for relapse. We will accomplish our objectives by: (Aim 1) Implementing an accurate, near real-time production risk prediction system; (Aim 2) Developing an enhanced, in-app substance-addiction recovery resource locator; and, (Aim 3) Determining the feasibility, acceptability and estimating the effect size of the proposed ESG among high relapse-risk participants in recovery from opioid, stimulant, or cannabis use. The expected impact of this project is to substantially enhance Sober Grid's ability to deliver effective and timely interventions to the right individuals, at the right time – including those high-need and underserved populations that would otherwise lack access to care and draw considerable resources from the healthcare system. This capability holds the promise to reduce drug and alcohol relapse and the associated negative health impacts at both an individual and societal level while reducing the total cost of providing treatment services.

项目总结/摘要 Sober Grid™开发了一个基于智能手机的移动的应用程序，目前有超过 全世界有12万人正在或正在寻求从毒品和酒精成瘾中康复。 众所周知，“网格”是一个基于移动的社会恢复社区， 具体同伴支持，有效的寻求帮助，动机增强练习，和成员 对支助内容进行评级-所有这些都是为了防止复发。第二阶段的总体目标是 该项目旨在扩展Sober Grid应用程序的当前功能，以实现全面的 社交恢复支持应用程序具有智能，上下文适当的资源匹配和24/7 快速反应同侪辅导，有效减少无序物质使用， 有效我们假设向高风险成员提供此功能是可以接受的， 可行，增加获得和利用资源的机会，并在以下方面产生积极影响 增加复发时间和连续戒断天数。公司的优先事项 商业目标是利用从其庞大的信息数据库中获得的见解， 记录在其现有的成瘾康复为重点的社会网络，结合其 最近完成了SBIR第一阶段工作，以确定有复发风险的用户，并提供量身定制的 和专业的同行支持，远程医疗，和提供者的干预，促使近实时 增强型清醒网格（ESG）解决方案中内置的自动化风险指标。的具体目标 这个建议的第二阶段项目包括：（1）实施复发风险评分算法 在生产环境中成功开发了第一阶段，（2）开发ML资源 利用该系统进行了可行性试验， 可接受性以及估计提供同伴指导对禁欲的影响， 资源信息，以国家样本的清醒网格成员在恢复从非 酒精/尼古丁物质，预计复发风险高。要全面完成 我们的目标是：（目标1）实现准确、近实时的生产风险预测 （目标2）开发一个增强的应用程序内药物成瘾康复资源定位器; 和（目的3）确定的可行性，可接受性和估计的效果大小， 在从阿片类药物、兴奋剂或 使用大麻该项目的预期影响是大大增强Sober Grid的能力， 在正确的时间向正确的人提供有效和及时的干预措施，包括 那些高需求和得不到充分服务的人口，否则他们将无法获得医疗服务， 从医疗保健系统中获得大量资源。这种能力有望减少 药物和酒精复发以及对个人和 在降低提供治疗服务的总成本的同时，