PDF(Pubmed)
Abstract：
BACKGROUND: Digitally delivered weight loss programmes can provide a convenient, potentially cheaper, and scalable treatment option for people who may need to lose weight. However, outcomes are often inferior to in-person interventions in the long-term. This trial will use principles from the Multiphase Optimisation Strategy (MOST) framework to test whether it can enhance the effectiveness of a commercial digital behavioural weight loss programme. This trial aims to identify an optimised combination of four intervention components to enhance weight loss over a 24-week period. We will also explore which components contribute to improvements in participant retention and engagement with the programme.
METHODS: Approximately 1400 adults with a BMI > 21 kg/m2 will be enrolled and randomised to one of 16 experimental conditions in a 24 factorial cluster design. The trial will test four intervention components: an introductory video call with the health coach, drop-in webchat sessions with the health coach, goal setting statements, and food diary review and feedback. All participants will receive the core digital behavioural weight loss programme and up to four new intervention components. Participation in the trial will last for 24 weeks. The primary outcome will be weight change at 16 weeks. Other outcomes, measured at 4, 16, and 24 weeks, include programme drop-out and engagement (number of interactions with the three main app functions). Fidelity and acceptability will be assessed using data on component adherence and self-report questionnaires. Decision-making for the enhanced programme will be based on components that contribute to at least a minimal improvement in weight loss, defined as ≥ 0.75kg, alone or in combination with other components.
CONCLUSIONS: The factorial design is an efficient way to test the efficacy of behavioural components alone, or in combination, to improve the effectiveness of digital weight loss programmes. This trial will test the implementation of the MOST framework in an industry setting, using routinely collected data, which may provide a better way to refine and evaluate these types of interventions in a model of continuous service improvement.
BACKGROUND: Trial registration: ISRCTN, ISRCTN14407868. Registered 5 January 2024, 10.1186/ISRCTN14407868.
METHODS: Approximately 1400 adults with a BMI > 21 kg/m2 will be enrolled and randomised to one of 16 experimental conditions in a 24 factorial cluster design. The trial will test four intervention components: an introductory video call with the health coach, drop-in webchat sessions with the health coach, goal setting statements, and food diary review and feedback. All participants will receive the core digital behavioural weight loss programme and up to four new intervention components. Participation in the trial will last for 24 weeks. The primary outcome will be weight change at 16 weeks. Other outcomes, measured at 4, 16, and 24 weeks, include programme drop-out and engagement (number of interactions with the three main app functions). Fidelity and acceptability will be assessed using data on component adherence and self-report questionnaires. Decision-making for the enhanced programme will be based on components that contribute to at least a minimal improvement in weight loss, defined as ≥ 0.75kg, alone or in combination with other components.
CONCLUSIONS: The factorial design is an efficient way to test the efficacy of behavioural components alone, or in combination, to improve the effectiveness of digital weight loss programmes. This trial will test the implementation of the MOST framework in an industry setting, using routinely collected data, which may provide a better way to refine and evaluate these types of interventions in a model of continuous service improvement.
BACKGROUND: Trial registration: ISRCTN, ISRCTN14407868. Registered 5 January 2024, 10.1186/ISRCTN14407868.
摘要：
背景：数字化减肥计划可以提供方便，可能更便宜，以及可能需要减肥的人的可扩展治疗选择。然而,从长期来看,结果通常不如面对面干预.该试验将使用多相优化策略（MOST）框架中的原则来测试它是否可以提高商业数字行为减肥计划的有效性。该试验旨在确定四种干预成分的优化组合，以在24周内增强体重减轻。我们还将探讨哪些组件有助于改善参与者的保留和参与该计划。
方法：将招募约1400名BMI>21kg/m2的成年人，并随机分配到24因子聚类设计中的16个实验条件之一。该试验将测试四个干预组件：与健康教练的介绍性视频通话，与健康教练进行网络聊天，目标设定声明，和食物日记审查和反馈。所有参与者将获得核心数字行为减肥计划和最多四个新的干预组件。参与试验将持续24周。主要结果是16周时的体重变化。其他成果,在4、16和24周测量，包括程序退出和参与（与三个主要应用程序功能的交互次数）。保真度和可接受性将使用组件依从性数据和自我报告问卷进行评估。增强计划的决策将基于至少有助于减轻体重的最小改善的组成部分，定义为≥0.75kg，单独或与其他组件组合。
结论：析因设计是测试单独行为成分功效的有效方法，或组合，提高数字化减肥方案的效果。该试验将测试MOST框架在行业环境中的实施情况，使用常规收集的数据，这可以提供一种更好的方法来完善和评估这些类型的干预措施，以持续服务改进的模型。
背景：试用注册：ISRCTN，ISRCTN14407868。注册日期为2024年1月5日，10.1186/ISRCTN14407868。
方法：将招募约1400名BMI>21kg/m2的成年人，并随机分配到24因子聚类设计中的16个实验条件之一。该试验将测试四个干预组件：与健康教练的介绍性视频通话，与健康教练进行网络聊天，目标设定声明，和食物日记审查和反馈。所有参与者将获得核心数字行为减肥计划和最多四个新的干预组件。参与试验将持续24周。主要结果是16周时的体重变化。其他成果,在4、16和24周测量，包括程序退出和参与（与三个主要应用程序功能的交互次数）。保真度和可接受性将使用组件依从性数据和自我报告问卷进行评估。增强计划的决策将基于至少有助于减轻体重的最小改善的组成部分，定义为≥0.75kg，单独或与其他组件组合。
结论：析因设计是测试单独行为成分功效的有效方法，或组合，提高数字化减肥方案的效果。该试验将测试MOST框架在行业环境中的实施情况，使用常规收集的数据，这可以提供一种更好的方法来完善和评估这些类型的干预措施，以持续服务改进的模型。
背景：试用注册：ISRCTN，ISRCTN14407868。注册日期为2024年1月5日，10.1186/ISRCTN14407868。
