Using Behavioural Insights to Improve Effectiveness of Digital Weight Loss Interventions

利用行为洞察提高数字减肥干预措施的有效性

• 批准号: 2612245
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2612245
• 关键词: Using; Behavioural; Insights; Improve; Effectiveness

Key words: obesity, health behaviours, digital health, interdisciplinary research, quantitative skillsOver a quarter of adults in the UK are living with obesity, which significantly increases their risk of developing cardiovascular disease, type 2 diabetes, and several types of cancers. It also underpins substantial multimorbidity. Supporting people to lose weight is important to reduce the burden of obesity-related diseases, for individuals and health services. The recent government obesity plan recognises the need to identify interventions to support successful weight loss at scale in a cost-effective way. Digital interventions are promising but their evidence base is limited. There are also particular challenges in encouraging adherence to digital programmes, especially in some subgroups of the population. The project will focus on developing and testing new intervention components, aiming to foster sustained participant engagement. The project is in partnership with Second Nature, a provider of a digitally-delivered behavioural weight management programme that is designed to support people to increase their physical activity and create healthy eating patterns, to achieve sustainable weight loss in a real-world environment. The programme gives participants access to evidence-based educational articles, a registered dietitian or nutritionist, tracking technology, and group support via a smartphone application. It is one of the weight management service providers commissioned by NHS England and local commissioning groups.The DPhil project will have three major components: 1) quantitatively analysing existing data to identify predictors of user engagement and disengagement, 2) conducting and analysing qualitative interviews to understand user experiences, and 3) developing and testing new intervention components in a real-world setting. The project will combine expertise in behavioural science in Oxford and commercial insights from Second Nature to enhance the development of more effective weight loss approaches that can be immediately incorporated into NHS care, thus creating impact on a national scale.

关键词：肥胖，健康行为，数字健康，跨学科研究，定量技能英国超过四分之一的成年人患有肥胖症，这大大增加了他们患心血管疾病，2型糖尿病和几种癌症的风险。它还支持大量的多形态。支持人们减肥对于减轻肥胖相关疾病对个人和卫生服务的负担非常重要。最近的政府肥胖计划认识到需要确定干预措施，以支持以具有成本效益的方式成功减肥。数字干预是有希望的，但其证据基础有限。在鼓励遵守数字方案方面也存在特别的挑战，特别是在人口的某些亚群体中。该项目将侧重于开发和测试新的干预措施组成部分，旨在促进参与者的持续参与。该项目与Second Nature合作，后者是一家提供数字化行为体重管理计划的供应商，旨在支持人们增加身体活动并创造健康的饮食模式，从而在现实环境中实现可持续减肥。该计划使参与者能够通过智能手机应用程序获得循证教育文章，注册营养师或营养师，跟踪技术和团体支持。DPhil项目将有三个主要组成部分：1）定量分析现有数据，以确定用户参与和脱离的预测因素，2）进行和分析定性访谈，以了解用户体验，以及3）在现实世界中开发和测试新的干预组件。该项目将结合联合收割机在行为科学在牛津和商业见解从第二性质，以加强更有效的减肥方法，可以立即纳入国民保健服务的发展，从而在全国范围内产生影响。