Using Technology to Scale Up the Evaluation of Motivational Interviewing

利用技术扩大动机访谈的评估

• 批准号: 8863672
• 负责人: David Charles Atkins
• 金额: $ 14.26万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8863672
• 关键词: Acoustics; Addictive Behavior; Alcohol abuse; Alcohol consumption; Alcohol or Other Drugs use; Alcohols; Algorithmic Software; American; Appointment; Area; Behavior Therapy; Behavioral; Cellular Phone; Client; Clinic; Clinical; Clinical Investigator; Code; Cognitive; Collaborations; Computer Simulation; Computer software; Computers; Data; Discipline; Electrical Engineering; Emerging Technologies; Empathy; Engineering; Evaluation; Feedback; Future; Goals; Grant; Group Psychotherapy; Health Services; Healthcare; Healthcare Systems; Human; Individual; Institute of Medicine (U.S.); Interdisciplinary Study; Intervention; Intervention Studies; Judgment; K-Series Research Career Programs; Knowledge; Language; Life; Linguistics; Machine Learning; Mental Health; Mentors; Methods; Modeling; Monitor; Outcome; Patients; Pharmaceutical Preparations; Process; Professional counselor; Property; Psychologist; Psychotherapy; Reading; Records; Reporting; Research; Research Personnel; Role; Scientist; Semantics; Services; Signal Transduction; Societies; Software Tools; Solutions; Speech; Substance Use Disorder; Supervision; System; Technology; Technology Assessment; Telephone; Time; Training; Translating; Translations; United States; United States Department of Veterans Affairs; United States National Institutes of Health; United States Substance Abuse and Mental Health Services Administration; Vision; Visual; Work; alcohol intervention; alcohol related problem; alcohol use disorder; base; behavior change; career development; computer science; computerized tools; design; disease classification; drinking; economic cost; experience; global health; high risk; implementation science; improved; innovation; method development; mortality; motivational enhancement therapy; novel; public health relevance; scale up; signal processing; skills; statistics; success; technology development; text searching; theories; tool; visual feedback

 DESCRIPTION: Millions of Americans are receiving behavioral interventions for problematic alcohol use. In 2010, the Substance Abuse and Mental Health Services Administration documented over 1.8 million treatment episodes for drug and alcohol problems, many involving group or individual psychotherapy. What is the quality of these interventions? In truth, we have no idea. To evaluate the quality of behavioral interventions such as psychotherapy researchers rely on human evaluation through behavioral coding, which is a major impediment to scaling up and sustaining high-quality interventions for alcohol abuse in large-scale implementation. Human evaluation of behavioral interventions is a rate-limiting factor, and a technological solution is needed that incorporates human expertise but does not rely on human judgment as the evaluation tool. The current K02 career development proposal builds on interdisciplinary research focused on automating the evaluation of motivational interviewing (MI) fidelity for alcohol and substance use disorders. This collaborative research brings together speech signal processing experts from engineering and statistical text- mining experts from computer science with MI expert trainers and researchers. The work is currently supported by an R01 (AA018673) methods development grant and an R34 (DA034860) feasibility trial. Career development activities will encompass additional training, experience, and collaboration in three areas: 1) technical tools and methods (speech signal processing, statistical text-mining, and machine learning), 2) clinical process and change mechanisms of MI, and 3) large-scale implementation. A team of senior mentors, who are nationally and internationally recognized experts in each of the three core areas, will oversee the career development activities. These activities have been designed to deepen knowledge in key topics (course work, directed reading), develop applied skills (hands-on work with speech signal processing, statistical text-mining, and machine learning), advance integration of technology with clinical process (co- reviewing MI sessions from the view of computational tools and MI clinical theory), and prepare for large-scale implementation of automated MI fidelity coding and feedback (engage key stakeholders in large healthcare systems via the mental health research network). Research conducted during the K02 will: a) systematically explore how much and which portion(s) of MI sessions are needed for accurate fidelity assessment; b) conduct innovative process research on how tone and prosody of spoken language moderate the association of client change talk with patient outcome; and, c) incorporate cutting-edge visual design in developing an automated fidelity feedback report for MI therapists. This career development award will support, enhance, and move forward research developing automated clinical support tools to provide rapid feedback to MI therapists. The ultimate goal is to improve the quality of behavioral interventions for all Americans struggling with alcohol problems.

 描述：数以百万计的美国人正在接受针对酗酒问题的行为干预。 2010 年，药物滥用和心理健康服务管理局记录了超过 180 万起药物和酒精问题治疗案例，其中许多涉及团体或个人心理治疗。这些干预措施的质量如何？事实上，我们不知道。为了评估心理治疗等行为干预措施的质量，研究人员依赖于通过行为编码进行的人类评估，这是在大规模实施中扩大和维持高质量的酗酒干预措施的主要障碍。人类对行为干预的评估是一个速率限制因素，需要一种结合人类专业知识但不依赖人类判断作为评估工具的技术解决方案。 当前的 K02 职业发展提案建立在跨学科研究的基础上，重点是自动评估酒精和药物滥用障碍的动机访谈 (MI) 保真度。这项合作研究汇集了工程领域的语音信号处理专家、计算机科学领域的统计文本挖掘专家以及 MI 专家培训师和研究人员。这项工作目前得到 R01 (AA018673) 方法开发资助和 R34 (DA034860) 可行性试验的支持。职业发展活动将包括三个领域的额外培训、经验和协作：1）技术工具和方法（语音信号处理、统计文本挖掘和机器学习），2）MI 的临床过程和变化机制，3）大规模实施。一个由三个核心领域的国内和国际公认专家组成的高级导师团队将监督职业发展活动。这些活动旨在加深关键主题的知识（课程作业、定向阅读）、培养应用技能（语音信号处理、统计文本挖掘和机器学习的实践）、推进技术与临床过程的集成（从计算工具和 MI 临床理论的角度共同审查 MI 课程），并为大规模实施自动化 MI 保真度编码和反馈做好准备（让大型医疗保健系统中的主要利益相关者参与进来）。 通过心理健康研究网络）。 K02 期间进行的研究将： a) 系统地探讨需要多少 MI 会话以及哪些部分来进行准确的保真度评估； b) 对口语语气和韵律如何调节来访者变革谈话与患者治疗结果之间的关联进行创新过程研究； c) 将尖端的视觉设计融入为 MI 治疗师开发自动保真度反馈报告中。 该职业发展奖将支持、加强和推进自动化临床支持工具的研究开发，为心肌梗死治疗师提供快速反馈。最终目标是提高所有与酒精问题作斗争的美国人的行为干预质量。