Berry Alice, McClellan Carey, Wanless Ben, Walsh Nicola
University of the West of England, Bristol, United Kingdom.
getUBetter, Bristol, United Kingdom.
JMIR Form Res. 2022 Mar 8;6(3):e32669. doi: 10.2196/32669.
Musculoskeletal conditions such as joint pain are a growing problem, affecting 18.8 million people in the United Kingdom. Digital health interventions (DHIs) are a potentially effective way of delivering information and supporting self-management. It is vital that the development of such interventions is transparent and can illustrate how individual components work, how they link back to the theoretical constructs they are attempting to change, and how this might influence outcomes. getUBetter is a DHI developed to address the lack of personalized, supported self-management tools available to patients with musculoskeletal conditions by providing knowledge, skills, and confidence to navigate through a self-management journey.
The aim of this study was to map a logic model of behavior change for getUBetter to illustrate how the content and functionality of the DHI are aligned with recognized behavioral theory, effective behavior change techniques, and clinical guidelines.
A range of behavior change models and frameworks were used, including the behavior change wheel and persuasive systems design framework, to map the logic model of behavior change underpinning getUBetter. The three main stages included understanding the behavior the intervention is attempting to change, identifying which elements of the intervention might bring about the desired change in behavior, and describing intervention content and how this can be optimally implemented.
The content was mapped to 25 behavior change techniques, including information about health consequences, instruction on how to perform a behavior, reducing negative emotions, and verbal persuasion about capability. Mapping to the persuasive system design framework illustrated the use of a number of persuasive design principles, including tailoring, personalization, simulation, and reminders.
This process enabled the proposed mechanisms of action and theoretical foundations of getUBetter to be comprehensively described, highlighting the key techniques used to support patients to self-manage their condition. These findings provide guidance for the ongoing evaluation of the effectiveness (including quality of engagement) of the intervention and highlight areas that might be strengthened in future iterations.
诸如关节疼痛等肌肉骨骼疾病是一个日益严重的问题，在英国影响着1880万人。数字健康干预措施（DHIs）是传递信息和支持自我管理的一种潜在有效方式。至关重要的是，此类干预措施的开发要透明，能够说明各个组成部分如何运作，它们如何与试图改变的理论结构相联系，以及这可能如何影响结果。getUBetter是一种数字健康干预措施，旨在通过提供知识、技能和信心，帮助肌肉骨骼疾病患者完成自我管理过程，解决患者缺乏个性化、有支持的自我管理工具的问题。
本研究的目的是绘制getUBetter行为改变的逻辑模型，以说明数字健康干预措施的内容和功能如何与公认的行为理论、有效的行为改变技术和临床指南相一致。
使用了一系列行为改变模型和框架，包括行为改变轮和说服系统设计框架，来绘制支撑getUBetter的行为改变逻辑模型。三个主要阶段包括了解干预措施试图改变的行为，确定干预措施的哪些要素可能带来期望的行为改变，以及描述干预内容及其最佳实施方式。
内容被映射到25种行为改变技术，包括关于健康后果的信息、如何执行行为的指导、减少负面情绪以及关于能力的言语说服。映射到说服系统设计框架说明了一些说服设计原则的使用，包括定制、个性化、模拟和提醒。
这一过程能够全面描述getUBetter的拟议作用机制和理论基础，突出了用于支持患者自我管理病情的关键技术。这些发现为持续评估干预措施的有效性（包括参与质量）提供了指导，并突出了未来迭代中可能需要加强的领域。
