SMART Weight Loss Management

智能减肥管理

• 批准号: 9547033
• 负责人: Inbal Billie Nahum-Shani
• 金额: $ 9.42万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9547033
• 关键词: Address; Adult; Behavior; Behavior Therapy; Body Weight decreased; Car Phone; Caring; Cellular Phone; Clinical; Consumption; Counseling; Dependency; Early treatment; Equilibrium; Evidence based treatment; Failure; Guidelines; Health; Heterogeneity; High Prevalence; Individual; Internet; Knowledge; Maintenance; Mediating; Monitor; Motivation; Obesity; Outcome; Overweight; Participant; Pathway interactions; Patients; Policies; Population; Public Health; Randomized; Regulation; Research; Resources; Risk; Self Efficacy; Technology; Testing; Text; Time; Treatment Failure; Weight; cost; cost effectiveness; follow-up; mHealth; mobile application; novel; obesity management; obesity treatment; population health; predictive modeling; primary outcome; programs; public health relevance; randomized trial; response; sound; standard of care; tool; trial design; uptake; weight loss intervention

 DESCRIPTION (provided by applicant): Obesity's high prevalence and costs make it a public health crisis, but current standard of care treatment impedes uptake and depletes resources by taking a one-size-fits-all approach. Guidelines recommend provision of expensive, burdensome treatment components (e.g., counseling, meal replacement) continuously to all consumers regardless of weight loss response. Stepped care that tries less costly evidence-based treatments first, reserving more resource-intensive treatments for suboptimal responders is a logical, equitable population health management strategy. However, stepped care approaches to obesity treatment have not yet incorporated inexpensive, widely available mHealth tools. It is unclear whether conjoint clinical and cost outcomes are better optimized by providing a low cost, low intensity, autonomously controlled mHealth treatment as the initial treatment with risk of nonresponse, or by providing a more costly, traditional obesity treatment with the potential to create a dependency that undermines autonomous motivation. The potential pitfall of beginning with mHealth treatment is that long-term outcome may be poor if nonresponse to initially insufficient treatment allows demoralization to set in. To reduce that risk, we will identify nonresponders earlier than previously has been possible by applying a predictive model derived from our prior mHealth obesity research and will quickly reallocate nonresponders to augmented treatment. We propose to use a novel experimental approach, the SMART (Sequential Multiple Assignment Randomized Trial), to randomize 400 overweight/obese adults to one of two first line treatments, either (1) an app alone (APP), or (2) the app plus coaching (APP +C). Those who do not respond to the first line treatment (i.e., evidenced by failure to lose weight) will be e-randomized to one of two subsequent augmentation tactics, either: (1) Modestly Step-Up: add another mHealth component (e.g., text messages), or (2) Vigorously Step-Up: add both a mHealth component (e.g., texts) and a more traditional component (e.g., coaching, meal replacement). Responders will continue with the same first line treatment for 12 weeks. Assessments will occur at 3, 6, and 12 months to determine (1) whether mHealth or traditional obesity treatment (coaching) is the optimal first line treatment for overweight/obese adults; and (2) whether the optimal response to weight loss failure is to modestly or vigorously augment the first line treatment. As the first stepped care trial to integrate mHealth tools and implement our predictive model of weight loss failure, SMART will be the most temporally and resource efficient strategy evaluated to date.

 描述（由适用提供）：肥胖症的高流行率和成本使其成为公共卫生危机，但是当前的护理水平治疗通过采取一种千篇一律的方法来阻止吸收和耗尽资源。指南建议不断向所有消费者提供昂贵的，易燃的治疗组件（例如，咨询，膳食更换），无论减肥反应如何。踩踏的护理，首先尝试较少成本的基于证据的治疗方法，为次优应答者保留更多的资源密集型处理是一种合乎逻辑，公平的人口健康管理策略。但是，客观治疗的阶梯护理方法尚未纳入廉价，可用的MHealth工具。目前尚不清楚通过提供低成本，低强度，自主控制的MHealth治疗方法作为具有无反应风险的初始治疗，还是通过提供更为昂贵的传统肥胖治疗并提供创造依赖性的潜力，从而使依赖性降低自主动机的潜力，从而更好地优化了联合临床和成本结果。 MHealth治疗开始的潜在陷阱是，如果对最初不足的治疗无反应允许士气低落，那么长期结局可能会降低这种风险。为了降低这种风险，我们将通过应用我们先前的MHEALTH肥胖症研究得出的预测模型，而不是先前的未响应者。我们建议使用一种新型的实验方法，即SMART（顺序多个分配随机试验），将400个超重/肥胖的成年人随机分配到两条第一行处理中之一，即（1）单独使用应用程序（APP），或（2）App Plus Coaching（App +C）。那些对第一行治疗（即，不减肥的证明）的人将被电子随后的一种增强策略之一，要么：（1）适度加速：添加另一个MHealth组件（例如，文本消息），或（2）逐步加强：添加两个Mhealth Components（例如，又有一个传统的文本）和一本餐具（例如，更传统的）（例如，E. comportions）（E. e。响应者将继续进行相同的第一行治疗12周。评估将在3、6和12个月进行，以确定（1）MHealth还是传统的肥胖治疗（教练）是超重/肥胖成年人的最佳第一线治疗； （2）对减肥失败的最佳反应是适度还是剧烈地增强第一行处理。作为整合MHealth工具并实施我们的减肥失败预测模型的第一个阶梯护理试验，SMART将是迄今为止评估的最临时，最有效的策略。