Abstract
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.