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

项目概要/摘要 进食障碍（Eating Disorders，ED）是一种严重的精神疾病，具有高发病率和高死亡率， 损伤和共病精神病理学。尽管ED的循证治疗一直是 治疗差距很大。事实上，<20%的ED患者接受治疗。我们需要一个 一种新的解决方案，不仅可以识别ED患者，还可以鼓励使用心理健康服务， 解决治疗障碍。我与全国急诊科协会建立了牢固的工作关系， （NEDA），美国“的领先的非营利ED，提供我们集团的在线，循证ED屏幕上 NEDA网站在一年多的时间里，NEDA屏幕完成了超过200，000次。在屏幕受访者中， 绝大多数人的艾德筛查呈阳性，但其中大多数人没有接受治疗， 点击百分比，以了解有关筛选中提供的寻求干预的选项之一的更多信息 反馈我提出了一个研究议程，设计一个对话代理或"聊天机器人"，优化， 通过以下方式增加ED患者对心理健康服务的使用：1）提供 寻求干预的个性化建议; 2）让用户参与动机访谈， 克服护理障碍;以及3）与用户重复登记，以鼓励后续护理。这 研究议程与NIMH对服务研究的关注和对技术驱动方法的兴趣相一致 来促进与护理的接触。我将进行两项研究。首先，我将使用以用户为中心的设计 方法来创建一个原型聊天机器人，并进行可用性测试与成人ED通知聊天机器人 改进（目标1）。其次，我将对完成了以下研究的成人进行随机优化试验： 在NEDA网站上进行筛查，并对艾德呈阳性，但未接受治疗以确定聊天机器人 可行性，并生成关于聊天机器人对初始聊天机器人使用后治疗动机的影响的数据 以及在1个月和3个月随访时使用治疗和精神卫生服务的动机（目标2和3）。这 试验将采用多阶段优化策略框架，使用23全因子设计，随机 将受试者分配到三种拟议干预成分的组合（n = 8种条件），以隔离 活性成分。这些目标支持我的培训计划，在该计划中，我将接受专家指导， 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的高级统计技术（培训 目标4）。我的专家指导团队，沿着华盛顿大学的环境，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 后续R01随机对照试验。这个K08将装备我的技能，成为一个领导者， 解决ED的研究实践和治疗差距，重点是数字创新。

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.