将分类法整合到基于理论的行为改变数字健康干预措施中：一个整体框架。

Integrating Taxonomies Into Theory-Based Digital Health Interventions for Behavior Change: A Holistic Framework.

作者信息

Wang Yunlong, Fadhil Ahmed, Lange Jan-Philipp, Reiterer Harald

机构信息

HCI Group, Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

Department of Information Engineering and Computer Science, University of Trento, Trento, Italy.

出版信息

JMIR Res Protoc. 2019 Jan 15;8(1):e8055. doi: 10.2196/resprot.8055.

Digital health interventions (DHIs) have been emerging in the last decade. Due to their interdisciplinary nature, DHIs are guided and influenced by theories (eg, behavioral theories, behavior change technologies, and persuasive technology) from different research communities. However, DHIs are always coded using various taxonomies and reported in insufficient perspectives. This inconsistency and incomprehensiveness will cause difficulty in conducting systematic reviews and sharing contributions among communities. Therefore, based on existing related work, we propose a holistic framework that embeds behavioral theories, behavior change technique taxonomy, and persuasive system design principles. Including four development steps, two toolboxes, and one workflow, our framework aims to guide DHI developers to design, evaluate, and report their work in a formative and comprehensive way.

数字健康干预措施（DHIs）在过去十年中不断涌现。由于其跨学科性质，DHIs受到来自不同研究领域的理论（如行为理论、行为改变技术和说服技术）的指导和影响。然而，DHIs总是使用各种分类法进行编码，并从不足的角度进行报告。这种不一致性和不全面性将导致进行系统评价以及在不同领域之间分享成果时出现困难。因此，基于现有的相关工作，我们提出了一个整体框架，该框架嵌入了行为理论、行为改变技术分类法和说服系统设计原则。我们的框架包括四个开发步骤、两个工具箱和一个工作流程，旨在指导DHI开发者以一种形成性的、全面的方式设计、评估和报告他们的工作。