Rapid Evaluation of Innovative Intervention Components to Maximize the Health Benefits of Behavioral Obesity Treatment Delivered Online: An Application of Multiphase Optimization Strategy

Decades of research have demonstrated that behavioral obesity treatments can produce clinically significant weight losses that improve health and disease risk/severity. However, these treatments have not been disseminated widely due to high costs and lack of qualified providers. The investigators therefore aim to develop and test a fully automated online obesity treatment that would produce clinically significant weight losses (i.e., ≥ 5 % of initial body weight) when delivered online. In order to maximize the public health impact of online obesity treatment, and advance the science of online behavioral intervention in general, it is imperative to evaluate innovative behavioral intervention components with the potential to optimize weight loss outcomes. Because digital health technology evolves rapidly, this research will use the Multiphase Optimization Strategy (MOST) framework to most quickly and efficiently determine which, if any, of 5 innovative intervention components, alone or in combination, increases the proportion of patients achieving a ≥5% weight loss, and mean weight loss, of the online Rx Weight loss (RxWL) program at 12- months. The 5 intervention components to be tested are: (a) Web-based virtual reality intervention for training in basic behavioral weight loss skills; tailored interactive intervention targeting (b) structured physical activity and (c) dysregulated eating; (d) a platform for social interaction including opportunities for friendly competition, and (e) interactive video feedback with content tailored to the unique needs of each participant and a focus on dietary skills. A sample of 384 individuals with BMI ≥ 25 will be randomized to receive RxWL and 0-5 of the experimental intervention components in a full factorial experiment. This design will allow the investigators to determine which intervention components maximize weight loss and whether there are favorable combinations of components. In addition, by evaluating the effects of each component on proximal outcomes (i.e., mediators) it will be possible learn not only which components are (or are not) effective but also why or how they exert their effects. This project advances the science of behavioral obesity treatment, and will directly impact the care of patients receiving RxWL.