Federal Institute of Education, Science and Technology of São Paulo, Capivari, Brazil.
Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, Brazil.
J Med Internet Res. 2021 Jul 12;23(7):e24278. doi: 10.2196/24278.
Health professionals initiating mobile health (mHealth) interventions may choose to adapt apps designed for other activities (eg, peer-to-peer communication) or to employ purpose-built apps specialized in the required intervention, or to exploit apps based on methods such as the experience sampling method (ESM). An alternative approach for professionals would be to create their own apps. While ESM-based methods offer important guidance, current systems do not expose their design at a level that promotes replicating, specializing, or extending their contributions. Thus, a twofold solution is required: a method that directs specialists in planning intervention programs themselves, and a model that guides specialists in adopting existing solutions and advises software developers on building new ones.
The main objectives of this study are to design the Experience Sampling and Programmed Intervention Method (ESPIM), formulated toward supporting specialists in deploying mHealth interventions, and the ESPIM model, which guides health specialists in adopting existing solutions and advises software developers on how to build new ones. Another goal is to conceive and implement a software platform allowing specialists to be users who actually plan, create, and deploy interventions (ESPIM system).
We conducted the design and evaluation of the ESPIM method and model alongside a software system comprising integrated web and mobile apps. A participatory design approach with stakeholders included early software prototype, predesign interviews with 12 health specialists, iterative design sustained by the software as an instance of the method's conceptual model, support to 8 real case studies, and postdesign interviews.
The ESPIM comprises (1) a list of requirements for mHealth experience sampling and intervention-based methods and systems, (2) a 4-dimension planning framework, (3) a 7-step-based process, and (4) an ontology-based conceptual model. The ESPIM system encompasses web and mobile apps. Eight long-term case studies, involving professionals in psychology, gerontology, computer science, speech therapy, and occupational therapy, show that the method allowed specialists to be actual users who plan, create, and deploy interventions via the associated system. Specialists' target users were parents of children diagnosed with autism spectrum disorder, older persons, graduate and undergraduate students, children (age 8-12), and caregivers of older persons. The specialists reported being able to create and conduct their own studies without modifying their original design. A qualitative evaluation of the ontology-based conceptual model showed its compliance to the functional requirements elicited.
The ESPIM method succeeds in supporting specialists in planning, authoring, and deploying mobile-based intervention programs when employed via a software system designed and implemented according to its conceptual model. The ESPIM ontology-based conceptual model exposes the design of systems involving active or passive sampling interventions. Such exposure supports the evaluation, implementation, adaptation, or extension of new or existing systems.
健康专业人员在启动移动健康 (mHealth) 干预措施时,可以选择改编专为其他活动设计的应用程序(例如,点对点通信),或者使用专门针对所需干预措施的定制应用程序,或者利用基于经验抽样法 (ESM) 的应用程序。专业人员的另一种方法是创建自己的应用程序。虽然基于 ESM 的方法提供了重要的指导,但当前的系统并未在促进复制、专业化或扩展其贡献的水平上公开其设计。因此,需要一种双重解决方案:一种方法可以指导专家自行规划干预计划,另一种模型可以指导专家采用现有解决方案,并就构建新解决方案向软件开发人员提供建议。
本研究的主要目标是设计体验抽样和编程干预方法 (ESPIM),以支持专家部署 mHealth 干预措施,并设计 ESPIM 模型,以指导健康专家采用现有解决方案并为软件开发人员提供构建新解决方案的建议。另一个目标是设计和实施一个软件平台,使专家成为实际规划、创建和部署干预措施的用户(ESPIM 系统)。
我们与利益相关者一起进行了 ESPIM 方法和模型的设计和评估,以及一个包含集成的网络和移动应用程序的软件系统。采用参与式设计方法,包括早期软件原型、对 12 名健康专家的预设计访谈、迭代设计、软件作为概念模型实例的支持、对 8 个实际案例研究的支持以及设计后的访谈。
ESPIM 包括:(1)一套 mHealth 体验抽样和基于干预的方法和系统需求;(2)一个四维度规划框架;(3)一个基于七步的过程;(4)一个基于本体的概念模型。ESPIM 系统包括网络和移动应用程序。八项长期案例研究涉及心理学、老年学、计算机科学、言语治疗和职业治疗方面的专业人员,表明该方法使专家能够通过相关系统实际成为规划、创建和部署干预措施的用户。专家的目标用户是被诊断患有自闭症谱系障碍的儿童的父母、老年人、研究生和本科生、儿童(8-12 岁)和老年人的护理人员。专家们报告说,他们能够在不修改原始设计的情况下创建和进行自己的研究。对基于本体的概念模型的定性评估表明,其符合所引出的功能要求。
当通过根据其概念模型设计和实现的软件系统使用时,ESPIM 方法成功地支持专家规划、创作和部署基于移动的干预计划。ESPIM 基于本体的概念模型公开了涉及主动或被动抽样干预的系统设计。这种公开支持新系统或现有系统的评估、实施、适应或扩展。