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SMART 研究方案:一项序贯多项适应性随机对照试验,旨在优化体重管理。

SMART: Study protocol for a sequential multiple assignment randomized controlled trial to optimize weight loss management.

机构信息

Feinberg School of Medicine, Department of Preventive Medicine, Northwestern University, Chicago, IL, United States.

Survey Research Center, Institute for Social Research, University of Michigan Ann Arbor, Ann Arbor, MI, United States.

出版信息

Contemp Clin Trials. 2019 Jul;82:36-45. doi: 10.1016/j.cct.2019.05.007. Epub 2019 May 23.

Abstract

BACKGROUND

Stepped care is a rational resource allocation approach to reduce population obesity. Evidence is lacking to guide decisions on use of low cost treatment components such as mobile health (mHealth) tools without compromising weight loss of those needing more expensive traditional treatment components (e.g., coaching, meal replacement). A sequential multiple assignment randomization trial (SMART) will be conducted to inform the development of an empirically based stepped care intervention that incorporates mHealth and traditional treatment components.

OBJECTIVE

The primary aim tests the non-inferiority of app alone, compared to app plus coaching, as first line obesity treatment, measured by weight change from baseline to 6 months. Secondary aims are to identify the best tactic to address early treatment non-response and the optimal treatment sequence for resource efficient weight loss.

STUDY DESIGN

Four hundred participants, 18-60 years old with Body Mass Index between 27 and 45 kg/m will be randomized to receive a weight loss smartphone app (APP) or the app plus weekly coaching (APP + C) for a 12 week period. Those achieving <0.5 lb. weight loss on average per week, assessed by wireless scale at 2, 4, and 8 weeks, will be classified as non-responders and re-randomized once to step-up modestly (adding another mHealth component) or vigorously (adding mHealth and traditional treatment components) for the remaining treatment period. Weight will be assessed in person at baseline, 3, 6, and 12 months.

SIGNIFICANCE

Results will inform construction of an obesity treatment algorithm that balances weight loss outcomes with resource consumption.

摘要

背景

阶梯式护理是一种合理的资源分配方法,可降低人群肥胖率。缺乏证据来指导使用低成本治疗手段(例如移动健康 (mHealth) 工具)的决策,而不会影响需要更昂贵传统治疗手段(例如辅导、代餐)的患者的减重效果。将进行一项序贯多项分配随机试验 (SMART),为开发基于实证的阶梯式护理干预措施提供信息,该干预措施将纳入 mHealth 和传统治疗手段。

目的

主要目的是测试仅使用应用程序(app)与使用 app 加辅导(app + C)作为一线肥胖治疗手段相比,在体重减轻方面是否不劣于后者,以从基线到 6 个月的体重变化来衡量。次要目的是确定解决早期治疗无反应的最佳策略以及资源高效减肥的最佳治疗顺序。

研究设计

将 400 名年龄在 18-60 岁之间、BMI 介于 27 和 45 kg/m 之间的参与者随机分为接受减肥智能手机应用程序(APP)或 APP 加每周辅导(APP + C)的治疗组,治疗期为 12 周。通过无线秤在第 2、4 和 8 周评估每周平均减重 <0.5 磅的参与者被归类为无反应者,并在治疗结束前再次随机分为适度升级(增加另一个 mHealth 组件)或大力升级(增加 mHealth 和传统治疗组件)组。基线、3、6 和 12 个月将进行体重评估。

意义

研究结果将为构建一种肥胖治疗算法提供信息,该算法将平衡减肥效果和资源消耗。

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