Developing an Optimized Conversational Agent or "Chatbot" to Facilitate Mental Health Services Use in Individuals with Eating Disorders

开发优化的会话代理或“聊天机器人”以促进饮食失调患者使用心理健康服务

• 批准号: 10170441
• 负责人: Ellen E. Fitzsimmons-Craft
• 金额: $ 17.91万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10170441
• 关键词: Address; Adult; Caring; Clinical; Data; Development; Eating Disorders; Ensure; Environment; Evidence based treatment; Exposure to; Facebook; Feedback; Fostering; Future; Goals; Health Services Accessibility; Health Services Research; Health Technology; Human; Impairment; Improve Access; Individual; Intervention; Investigational Therapies; Learning; Machine Learning; Mental Health; Mental Health Services; Mental disorders; Mentorship; Morbidity - disease rate; Motivation; National Institute of Mental Health; Participant; Partnership Practice; Prognosis; Psychopathology; Randomized; Randomized Controlled Trials; Recommendation; Relapse; Research; Respondent; Services; Strategic Planning; Symptoms; Techniques; Technology; Testing; Text Messaging; Time; Training; Training Support; Universities; Washington; Work; barrier to care; chatbot; comorbidity; computer program; design; digital; digital health; evidence base; experience; follow-up; health service use; implementation science; innovation; interest; longitudinal analysis; mortality; motivational enhancement therapy; multiphase optimization strategy; novel; personalized intervention; programs; prototype; screening; service delivery; severe mental illness; skills; social stigma; success; trial design; usability; user centered design; web site

PROJECT SUMMARY/ABSTRACT Eating disorders (EDs) are serious mental illnesses associated with high morbidity and mortality, clinical impairment, and comorbid psychopathology. Although evidence-based treatments for EDs have been established, the treatment gap is wide. Indeed, <20% of individuals with EDs receive treatment. We need a novel solution not only to identify individuals with EDs but also to encourage mental health services use and address treatment barriers. I have established a strong working relationship with the National EDs Association (NEDA), the U.S.'s leading non-profit for EDs, to offer our group's online, evidence-based EDs screen on the NEDA website. Over one year, the NEDA screen was completed >200,000 times. Among screen respondents, the vast majority screen positive for an ED, but of those, most are not in treatment, and only a small percentage click to learn more about one of the options for seeking intervention presented in the screening feedback. I propose a research agenda to design a conversational agent or “chatbot” that is optimized to increase mental health services use among individuals with EDs through such features as: 1) providing a personalized recommendation for seeking intervention; 2) engaging the user in motivational interviewing to overcome barriers to care; and 3) repeated check-ins with the user to encourage follow-up with care. This research agenda aligns with NIMH's focus on services research and interest in technology-driven approaches to promote engagement with care. I will conduct two studies. First, I will utilize a user-centered design approach to create a prototype chatbot and conduct usability testing with adults with EDs to inform chatbot refinements (Aim 1). Second, I will conduct a randomized optimization trial with adults who have completed screening on the NEDA website and screen positive for an ED but are not in treatment to determine chatbot feasibility and to generate data on the effect of the chatbot on motivation for treatment post-initial chatbot use and motivation for treatment and mental health services use at 1- and 3-month follow-ups (Aims 2 & 3). This trial will employ the Multiphase Optimization Strategy framework, using a 23 full factorial design, to randomly assign participants to a combination of the three proposed intervention components (n=8 conditions) to isolate the active ingredients. These aims support my training plan in which I will receive expert mentorship and training in: services research and implementation science (Training Goal 1); user-centered design and usability testing, as well as exposure to machine learning (Training Goal 2); novel trial designs (Training Goal 3); and advanced statistical techniques for analyzing longitudinal trial and digital innovation data (Training Goal 4). My expert mentorship team, along with the environment of Washington University, will ensure my success. Results from the proposed study will be used to optimize the chatbot, which I will then test in a subsequent R01 randomized controlled trial. This K08 will equip me with the skills to become a leader in addressing the research-practice and treatment gaps for EDs, with a focus on digital innovations.

项目摘要/摘要 饮食失调（ED）是与高发病率和死亡率高有关的严重精神疾病 障碍和合并症的心理病理学。尽管基于循证的ED治疗已经 建立的治疗差距很大。确实，<20％的ED患者接受治疗。我们需要一个 新颖的解决方案不仅是为了识别具有ED的人，还鼓励心理健康服务使用和 解决治疗障碍。我已经与国家EDS协会建立了牢固的工作关系 （NEDA），美国领先的ED非营利组织，以在线提供我们小组的在线循证EDS屏幕 NEDA网站。一年多，NEDA屏幕完成了> 200,000次。在屏幕受访者中， ED的绝大多数屏幕是正面的，但其中大多数都不在治疗中，只有很小的 点击百分比点击以了解更多有关寻求筛查中介绍的干预措施的选择之一 反馈。我提出了一个研究议程来设计对话代理或“聊天机器人”，该议程已优化为 通过以下功能，增加具有EDS的人的心理健康服务的使用：1）提供 寻求干预的个性化建议； 2）让用户参与激励面试 克服护理障碍； 3）与用户重复进行检查，以鼓励随访。 研究议程与NIMH专注于服务研究和对技术驱动方法的兴趣保持一致 促进照顾的参与。我将进行两项研究。首先，我将使用以用户为中心的设计 创建原型聊天机器人并与ED成人进行可用性测试以通知聊天机器人的方法 改进（目标1）。其次，我将向已完成的成年人进行随机优化试验 在NEDA网站和屏幕上筛选ED呈阳性，但没有在治疗中确定聊天机器人 可行性并生成有关聊天机器人对治疗后聊天机器人治疗动机影响的数据 和治疗和心理健康服务的动机在1个月和3个月的随访中使用（目标2和3）。这 试验将使用23个完整阶乘设计采用多相优化策略框架进行随机 将参与者分配为三个提出的干预组件（n = 8条件）的组合，以分离 活跃的诱因。这些目的支持我的培训计划，在这些计划中，我将获得专家的精力和 培训：服务研究和实施科学（培训目标1）；以用户为中心的设计和 可用性测试以及接触机器学习（培训目标2）；新颖的试验设计（培训目标 3）;以及用于分析纵向试验和数字创新数据（培训）的高级统计技术 目标4）。我的专家Mentalship团队以及华盛顿大学的环境将确保我的 成功。拟议研究的结果将用于优化聊天机器人，然后我将在 随后的R01随机对照试验。这个K08将使我具备成为领导者的技能 针对ED的研究实践和治疗差异，重点是数字创新。