Kopelovich Sarah L, Buck Benjamin E, Tauscher Justin, Lyon Aaron R, Ben-Zeev Dror
Department of Psychiatry & Behavioral Sciences, University of Washington School of Medicine, 1959 NE Pacific Street, Box 356560, Seattle, WA 98195-6560 USA.
J Technol Behav Sci. 2024;9(1):35-45. doi: 10.1007/s41347-024-00385-y. Epub 2024 Jan 13.
Integrating mobile health (mHealth) interventions into settings that serve diverse patient populations requires that prerequisite professional competencies are delineated and that standards for clinical quality assurance can be pragmatically assessed. Heretofore, proposed mHealth competencies have been broad and have lacked a framework to support specific applications. We outline the meta-competencies identified in the literature relevant to mHealth interventions and demonstrate how these meta-competencies can be integrated with population- and intervention-related competencies to help guide a pragmatic approach to competency assessment. We present a use case based on -an evidence-based mHealth intervention designed for individuals with serious mental illness and currently being implemented in geographically and demographically diverse community behavioral health settings. Subsequent to identifying the cross-cutting competencies relevant to the target population (outpatients experiencing psychotic symptoms), substratal intervention (Cognitive Behavioral Therapy for psychosis), and treatment modality (mHealth), we detail the development process of an mHealth fidelity monitoring system (mHealth-FMS). We adhered to a published sequential 5-step process to design a fidelity monitoring system that aligns with our integrated mHealth competency framework and that was guided by best practices prescribed by the Treatment Fidelity Workgroup of the National Institutes of Health Behavior Change Consortium. The mHealth-FMS is intended to enhance both clinical and implementation outcomes by grounding the mHealth interventionist and the system of care in which they operate in the core functions, tasks, knowledge, and competencies associated with system-integrated mHealth delivery. Future research will explore acceptability and feasibility of the mHealth-FMS.
将移动健康（mHealth）干预措施整合到为不同患者群体服务的环境中，需要明确必备的专业能力，并切实评估临床质量保证标准。在此之前，所提出的移动健康能力要求较为宽泛，且缺乏支持具体应用的框架。我们概述了文献中确定的与移动健康干预相关的元能力，并展示了这些元能力如何与人群和干预相关能力相结合，以帮助指导一种切实可行的能力评估方法。我们提出了一个基于循证移动健康干预措施的用例，该措施是为患有严重精神疾病的个体设计的，目前正在地理和人口结构各异的社区行为健康环境中实施。在确定了与目标人群（出现精神病症状的门诊患者）、底层干预（针对精神病的认知行为疗法）和治疗方式（移动健康）相关的交叉能力之后，我们详细介绍了移动健康保真度监测系统（mHealth-FMS）的开发过程。我们遵循已发表的五步流程来设计一个保真度监测系统，该系统与我们的综合移动健康能力框架相一致，并以美国国立卫生研究院行为改变联盟治疗保真度工作组规定的最佳实践为指导。移动健康保真度监测系统旨在通过将移动健康干预人员及其运作的护理系统建立在与系统集成移动健康服务相关的核心功能、任务、知识和能力基础上，来提高临床和实施效果。未来的研究将探索移动健康保真度监测系统的可接受性和可行性。
