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技术辅助监督协议，以促进 治疗的保真度和更有效地提供循证治疗（EBT）的ADHD在资源不足的 社区设置。该方案（LC 4S）将以基于测量的护理原则为基础。LC4S 将基本监督任务转移到分析和编码治疗的现有机器学习工具 用于保真度的记录（Lyssn; lyssn.io; Tanana等人，2019年）。这些数据将自动集成到一个 建立了符合HIPAA的在线临床仪表板，为治疗师生成绩效报告， supervisors（Care4; www.care4soft.net）。Care 4还将加载在线便利资源， 治疗师，而监督员将接受培训，以根据最佳的 在基于测量的护理中的实践（Martino等人，2016; Schoenwald等人，2009; Webster-Stratton等人， 2014）。本试验将在三个社区精神卫生机构（Psych Solutions，Inc，Behavioral 援助解决方案，犹太社区服务）在迈阿密戴德县，佛罗里达州，为低收入民族/种族 少数民族青年和以前的合作伙伴与研究小组在R 01 MH 106587。在项目的Y 01中，我们 将为LC 4S干预进行一个以经销商为中心的开发过程，该过程从一个彻底的 利用实施研究综合框架进行能力和需求评估; Damschroder等人，2009年），并以知识到行动（K2 A）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，Care 4和调查团队，以验证Care 4的最终接口， 强调以用户为中心的设计。在第一年，我们还将进行一个小型的开放试验，以获得用户的反馈 (12病例，3名主管和6名治疗师），我们将对技术进行最后的调整， 议定书在第2年，我们将进行混合型3实施试点-有效性随机对照 试验（Curran等人，2012年; N=72名青年; 24名青年，8名治疗师，每个机构2名监督员），将随机 将治疗师和青少年分配到LC 4S条件或像往常一样加强监督（ESAU）。两 监督条件将由内部机构的监督人员提供，这些监督人员接受过提供 EBT及其监督的核心要素，并获得专家的每月电话咨询。 该R34试点RCT中的近端目标是逐期保真度评分。远端服务交付 本试验的结果是：（1）EBT实施的质量，（2）标准交付的EBT数量 干预时间框架，和（3）递送速度（即，课程数和完成EBT的天数） 每个案件。为了支持未来的R 01，该R 01测量LC 4S对多个患者结局的影响， EBT，该R34还将侧重于开发和验证适当的研究措施，测试 在不同条件下的污染，并建立LC 4S干预与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.