Community-Based Care for Minority Adolescents with ADHD: Improving Fidelity with Machine Learning-Assisted Supervision and Fidelity Feedback

项目摘要 拟议的研究将制定和评估一项技术辅助的监督协议，以促进 资源不足的ADHD患者的治疗保真度和更有效的循证治疗(EBT) 社区设置。该议定书(LC4S)将以以测量为基础的护理原则为基础。LC4S 是否会将基本的监督任务转移到现有的分析和编码治疗的机器学习工具 保真度录音(Lyssn；lysn.io；Tanana等人，2019年)。这些数据将自动集成到 建立符合HIPAA标准的在线临床仪表板，为治疗师和 主管(Care4；www.are4soft.net)。Care4还将加载在线促进资源，以 治疗师，而监督员将接受培训，领导每周面对面的监督会议，根据最佳 基于测量的护理实践(Martino等人，2016；Schoenwald等人，2009；Webster-Stratton等人， 2014年)。这项试验将在三家社区精神卫生机构(心理解决方案公司、行为卫生公司)进行 援助解决方案，犹太社区服务)在佛罗里达州迈阿密-戴德县，服务于低收入民族/种族 少数族裔青年，之前在R01 MH106587与研究团队合作。在项目的第01年，我们 将为LC4S干预进行以利益相关者为中心的开发过程，该过程从彻底的 利用实施研究综合框架(CFIR)评估能力和需求 Damschroder等人，2009)，并以知识到行动(K2A)实施科学为指导 框架(Graham等人，2006年)。在这一阶段，我们将每月举行视频会议， 每个机构的开发团队、Care4和调查团队迭代最终的Care4接口 强调以用户为中心的设计。在第一年，我们还将进行一项小型公开试验，以获取用户反馈 (12例、3名监督员和6名治疗师)，我们将对该技术进行最终调整，并 协议。在第二年，我们将进行混合类型3的试点实施-有效性随机控制 试验(Curran等人，2012；N=72名青年；24名青年，8名治疗师，以及每个机构2名主管)将随机 将治疗师和青少年都分配到LC4S条件下或照常加强监督(ESAU)。两者都有 监督条件将由接受过交付培训的内生机构主管提供 EBT及其监督的核心要素，并可每月获得专家的电话咨询。 在这个R34试点RCT中，最近的目标是逐个会话保真度分数。远端服务交付 本试验的结果是：(1)EBT实施的质量；(2)EBT按标准交付的数量 干预时间框架，以及(3)交付速度(即完成EBT的会话数量和天数) 每一箱都是。为了支持未来的R01，该R01衡量了LC4S对多个 EBTS，这一R34还将专注于开发和验证适当的研究措施，测试 不同条件下的污染，并确定LC4S干预相对于ESAU的成本。

Project Summary The proposed study will develop and evaluate a technology-assisted supervision protocol to promote treatment fidelity and more efficient delivery of evidence-based treatment (EBT) for ADHD in under-resourced community settings. The protocol (LC4S) will be grounded in the principles of measurement-based care. LC4S will task-shift basic supervision tasks to an existing machine learning tool that analyzes and codes therapy recordings for fidelity (Lyssn; lyssn.io; Tanana et al., 2019). These data will be automatically integrated into an established HIPAA-compliant online clinical dashboard that produces performance reports for therapists and supervisors (Care4; www.care4soft.net). Care4 also will be loaded with online facilitation resources for therapists, while supervisors will be trained to lead weekly in-person supervision sessions according to best practices in measurement-based care (Martino et al., 2016; Schoenwald et al., 2009; Webster-Stratton et al., 2014). This trial will be conducted in three community mental health agencies (Psych Solutions, Inc, Behavioral Aid Solutions, Jewish Community Services) in Miami-Dade County, FL that serve low income ethnic/racial minority youth and previously partnered with the research team in R01 MH106587. In Y01 of the project, we will conduct a stakeholder-focused development process for the LC4S intervention that begins with a thorough capacity and needs assessment using the Consolidated Framework for Implementation Research (CFIR; Damschroder et al., 2009) and is guided by the Knowledge to Action (K2A) Implementation Science Framework (Graham et al., 2006). In this phase, we will hold monthly videoconference meetings between development teams at each agency, Care4, and the investigative team to iterate the final Care4 interface with an emphasis user-centered design. In year 1, we also will conduct a small open trial to obtain user feedback (12 cases, 3 supervisors, and 6 therapists) on LC4S and we will make final adaptations to the technology and protocol. In year 2, we will conduct a pilot Hybrid Type 3 Implementation- Effectiveness randomized controlled trial (Curran et al., 2012; N=72 youth; 24 youth, 8 therapists, and 2 supervisors per agency) that will randomly assign both therapists and youth to the LC4S condition or enhanced supervision as usual (ESAU). Both supervision conditions will be delivered by endogenous, agency supervisors who are trained in delivery of the EBT and the core elements of its supervision and have access to monthly phone consultation from experts. The proximal target in this R34 pilot RCT is session by session fidelity scores. The distal service delivery outcomes in this trial are: (1) quality of EBT implementation, (2) quantity of EBT delivered in standard intervention time frame, and (3) speed of delivery (i.e., number of sessions and days to EBT completion) for each case. In support of a future R01 that measures the impact of LC4S on patient outcomes across multiple EBTs, this R34 will also focus on developing and validating appropriate study measures, testing for contamination across conditions, and establishing the costs of the LC4S intervention versus ESAU.