Using Technology to Scale Up the Evaluation of Motivational Interviewing

利用技术扩大动机访谈的评估

基本信息

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
项目类别：
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

项目摘要

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因酗酒问题而接受行为干预。2010 年，药物滥用和心理健康服务管理局记录了超过 180 万次针对药物和酗酒问题的治疗，其中许多涉及团体或个人心理治疗。事实上，我们不知道心理治疗等行为干预措施的质量，依赖于通过行为编码进行的人类评估，这是扩大和维持高质量酒精滥用干预措施的主要障碍。人类对行为干预的评估是一个限制因素，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实施解决方案。这项合作研究的重点是自动评估酒精和物质使用障碍的动机访谈 (MI) 保真度，该研究汇集了来自计算机科学的语音信号处理专家和 MI 专家培训师和研究人员。由 R01 支持(AA018673) 方法开发补助金和 R34 (DA034860) 可行性试验。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 的临床流程和变革机制，以及 3）大规模实施，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整个职业生涯。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）、促进技术与技术的集成。临床流程（从计算工具和 MI 临床理论的角度共同审查 MI 会议），并为大规模实施自动化 MI 保真度编码和反馈做好准备（通过心理健康研究网络让大型医疗保健系统中的主要利益相关者参与进来）。 K02 期间进行的研究将： a) 系统地探讨准确的保真度评估需要 MI 会议的哪些部分； b) 对口语的语气和韵律如何调节客户改变谈话与患者结果的关联进行创新过程研究；以及 c) 纳入尖端视觉效果；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，为 MI 治疗师提供快速反馈，最终目标是提高 MI 治疗师的行为干预质量。所有美国人都在与酒精问题作斗争。