The BestFIT trial: A SMART approach to developing individualized weight loss treatments.
The BestFIT trial: A SMART approach to developing individualized weight loss treatments.
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DOI：
10.1016/j.cct.2016.01.011
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发表时间：
2016-03
影响因子：
2.2
通讯作者：
Jeffery RW
中科院分区：
文献类型：
--
作者：
Sherwood NE;Butryn ML;Forman EM;Almirall D;Seburg EM;Lauren Crain A;Kunin-Batson AS;Hayes MG;Levy RL;Jeffery RW
行为减肥计划可帮助人们实现具有临床意义的体重减轻（起始体重的 8-10%）。尽管数据显示只有一半的参与者实现了这一目标，但“一刀切”的方法是规范的。这种减肥干预科学差距要求采取适应性干预措施，“在正确的时间为正确的人提供正确的治疗”。序贯多重分配随机试验 (SMART) 使用实验设计原则来回答建立适应性干预措施的问题，包括是否、如何或何时改变治疗强度、类型或实施方式。本文描述了 BestFIT 研究的基本原理和设计，这是一项 SMART 旨在评估对减肥治疗反应不佳者进行干预的最佳时机，以及两种治疗方法的相对疗效，以解决阻碍减肥的自我调节挑战：1）通过控制份量膳食（PCM）加强治疗，减少自我调节的需要； 2）转向基于接受的行为治疗（ABT），以提高自我调节能力。主要目的是评估 PCM 与 ABT 相比改变治疗的益处。第二个目标是评估对次优反应者进行干预的最佳时间。 BestFIT 结果将导致基于经验的适应性干预措施的构建，从而优化减肥结果和相关的健康益处。
Behavioral weight loss programs help people achieve clinically meaningful weight losses (8–10% of starting body weight). Despite data showing that only half of participants achieve this goal, a “one size fits all” approach is normative. This weight loss intervention science gap calls for adaptive interventions that provide the “right treatment at the right time for the right person.” Sequential Multiple Assignment Randomized Trials (SMART), use experimental design principles to answer questions for building adaptive interventions including whether, how, or when to alter treatment intensity, type, or delivery. This paper describes the rationale and design of the BestFIT study, a SMART designed to evaluate the optimal timing for intervening with sub-optimal responders to weight loss treatment and relative efficacy of two treatments that address self-regulation challenges which impede weight loss: 1) augmenting treatment with portion-controlled meals (PCM) which decrease the need for self-regulation; and 2) switching to acceptance-based behavior treatment (ABT) which boosts capacity for self-regulation. The primary aim is to evaluate the benefit of changing treatment with PCM versus ABT. The secondary aim is to evaluate the best time to intervene with sub-optimal responders. BestFIT results will lead to the empirically-supported construction of an adaptive intervention that will optimize weight loss outcomes and associated health benefits.