Background: Effective interventions and commercial programmes for weight loss (WL) are widely available, but most people regain weight. Few effective WL maintenance (WLM) solutions exist. The most promising evidence-based behaviour change techniques for WLM are self-monitoring, goal setting, action planning and control, building self-efficacy, and techniques that promote autonomous motivation (e.g., provide choice). Stress management and emotion regulation techniques show potential for prevention of relapse and weight regain. Digital technologies (including networked-wireless tracking technologies, online tools and smartphone apps, multimedia resources, and internet-based support) offer attractive tools for teaching and supporting long-term behaviour change techniques. However, many digital offerings for weight management tend not to include evidence-based content and the evidence base is still limited. The Project: First, the project examined why, when, and how many European citizens make WL and WLM attempts and how successful they are. Second, the project employed the most up-to-date behavioural science research to develop a digital toolkit for WLM based on 2 key conditions, i.e., self-management (self-regulation and motivation) of behaviour and self-management of emotional responses for WLM. Then, the NoHoW trial tested the efficacy of this digital toolkit in adults who achieved clinically significant (≥5%) WL in the previous 12 months (initial BMI ≥25). The primary outcome was change in weight (kg) at 12 months from baseline. Secondary outcomes included biological, psychological, and behavioural moderators and mediators of long-term energy balance (EB) behaviours, and user experience, acceptability, and cost-effectiveness. Impact: The project will directly feed results from studies on European consumer behaviour, design and evaluation of digital toolkits self-management of EB behaviours into development of new products and services for WLM and digital health. The project has developed a framework and digital architecture for interventions in the context of EB tracking and will generate results that will help inform the next generation of personalised interventions for effective self-management of weight and health.
Obes Facts

中文翻译：

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基于证据的减肥维持数字工具：NoHoW 项目

背景：有效的减肥干预措施和商业计划已广泛应用，但大多数人体重都会反弹。有效的 WL 维护 (WLM) 解决方案很少存在。最有前途的 WLM 循证行为改变技术是自我监控、目标设定、行动规划和控制、建立自我效能以及促进自主动机（例如，提供选择）的技术。压力管理和情绪调节技术显示出预防复发和体重反弹的潜力。数字技术（包括网络无线跟踪技术、在线工具和智能手机应用程序、多媒体资源和基于互联网的支持）为教学和支持长期行为改变技术提供了有吸引力的工具。然而，许多体重管理的数字产品往往不包含基于证据的内容，而且证据基础仍然有限。项目：首先，该项目研究了为什么、何时、有多少欧洲公民进行 WL 和 WLM 尝试，以及它们的成功程度。其次，该项目采用最新的行为科学研究，基于两个关键条件，即行为的自我管理（自我调节和动机）和情绪反应的自我管理，开发了WLM的数字工具包。 WLM。然后，NoHoW 试验测试了该数字工具包对过去 12 个月内达到临床显着 (≥5%) WL（初始 BMI ≥25）的成年人的功效。主要结果是 12 个月时体重 (kg) 相对于基线的变化。次要结果包括生物、心理和行为调节因素以及长期能量平衡（EB）行为的调节因素，以及用户体验、可接受性和成本效益。影响：该项目将直接将欧洲消费者行为、EB 行为数字工具包自我管理设计和评估的研究结果直接纳入 WLM 和数字健康新产品和服务的开发中。该项目开发了 EB 跟踪背景下的干预措施的框架和数字架构，并将产生的结果将有助于为下一代个性化干预措施提供信息，以实现有效的体重和健康自我管理。
肥胖事实