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（由申请人提供）：肥胖的高患病率和高成本使其成为一场公共卫生危机，但目前的护理治疗标准通过采取一刀切的方法阻碍了吸收并耗尽了资源。指南建议提供昂贵、繁重的治疗。持续向所有消费者提供咨询、代餐等，无论减肥反应如何。首先尝试成本较低的循证治疗，为反应不佳的人保留更多资源密集型治疗是一种阶梯式护理。然而，肥胖治疗的阶梯式护理方法尚未纳入廉价、广泛使用的移动医疗工具，目前尚不清楚是否可以通过提供低成本、低强度、自主控制来更好地优化联合临床和成本结果。移动健康治疗作为初始治疗存在无反应的风险，或者提供成本更高的传统肥胖治疗，有可能产生破坏自主动机的依赖。开始使用移动健康治疗的潜在陷阱是长期结果可能不佳。如果没有回应最初治疗不足会导致士气低落。为了降低这种风险，我们将通过应用从我们之前的移动健康肥胖研究中得出的预测模型，比以前更早地识别无反应者，并迅速将无反应者重新分配给我们建议使用的增强治疗。一种新颖的实验方法，SMART（序贯多重分配随机试验），将 400 名超重/肥胖成年人随机分配到两种一线治疗中的一种，要么 (1) 单独使用应用程序 (APP)，要么 (2)应用程序加辅导（APP +C）。那些对一线治疗没有反应（即减肥失败）的人将被电子随机分配到以下两种增强后续策略之一：（1）适度步骤-Up：添加另一个 mHealth 组件（例如短信），或 (2) 大力升级：添加 mHealth 组件（例如文本）和更传统的组件（例如辅导、膳食）应答者将继续接受相同的一线治疗 12 周，评估将在第 3、6 和 12 个月时进行，以确定 (1) 移动健康或传统肥胖治疗（指导）是否是超重/肥胖成人的最佳一线治疗； （2）对于减肥失败的最佳反应是适度还是大力加强一线治疗作为整合移动医疗工具和实施我们的减肥失败模型的第一步护理试验，SMART 将是最重要的。迄今为止评估了时间和资源有效的策略。