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. We therefore aimed to develop a fully automated online obesity treatment that would produce clinically significant weight losses (i.e., ? 5 % of initial body weight) when delivered online in a variety of settings. Our 3-month program, Rx Weight Loss (RxWL), produced clinically significant meanSD weight losses of 5.84.4 % of initial body in patients referred by physician (N=154), 5.8 5.2 % in worksites (N=75), and 4.25.3 % in community settings (N=230). These weight losses were largely maintained at 6-month follow-up. Given these positive results, healthcare stakeholders have expressed a desire to pursue dissemination of RxWL. In order to maximize the public health impact of disseminating RxWL and similar programs, 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. Despite promising mean weight losses, only about half of participants treated online achieve weight losses of > 5%. Furthermore, the health benefits of weight loss are dose dependent; optimizing RxWL to produce larger mean weight losses would therefore enhance its health benefits. Optimizing RxWL would also provide a template for optimizing other online treatments. Because digital health technology evolves rapidly, we 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 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. After initial testing with N=32 to refine and finalize the intervention components with feedback from advisory boards, N=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 us 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) we will 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.
When delivered online, behavioral obesity treatments have the potential to reach large numbers of individuals with overweight/obesity and produce significant improvements in health and wellbeing. In order to maximize the public health benefit of disseminating these treatments online, this study 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, after a 12-month online behavioral obesity treatment.
