Overweight and obesity are major health problems, affecting over two-thirds of US adults. Standard behavioral treatments (SBT), which are the gold standard for mild and moderate obesity, have been adapted for Internet delivery to facilitate dissemination, reduce cost, and overcome barriers to treatment. However, the weight losses obtained via Internet-delivered treatment are about half the size of those obtained via in-person treatment, likely because of the lack of (1) """"""""hands-on"""""""" training in behavioral weight control strategies, and (2) support and guidance from group leaders and peers, both of which are hallmarks of traditional in-person SBT. The goal of this application is to improve Internet-delivered behavioral obesity treatments by developing a virtual reality (VR) system that can be integrated into existing Internet weight control programs, such as those developed by our research team. The VR system will provide the experience of learning and implementing behavioral weight control strategies in controlled virtual settings with the support of a virtual coach that demonstrates skills and provides encouragement. The ability to see skills being used appropriately, practice skills repeatedly, and receive reinforcement, will improve the learning process that takes place. The VR system will: (a) increase awareness of barriers to weight control behaviors, (b) teach skills to cope with these barriers, (c) build confidence using these skills, and (d) increase commitment to using these skills in real-world situations. The design of the VR System is based on Social Cognitive Theory, which states that health behaviors are learned by observing and imitating peers and role models, and by receiving social reinforcement. The VR system we propose to develop will consist of two parts: (a) the VR software engine that is the core, or architecture, of the program, which makes it possible to create interactive VR environments for delivery via the Internet, increases scalability, and improves cost effectiveness of future content development, and (b) the behavioral intervention content, which is delivered via the software engine, and consists of a series of interactive """"""""vignettes"""""""" (i.e., modules) that will teach and reinforce behavioral weight control strategies. The VR system will be designed for integration with existing Internet-delivered behavioral weight loss programs. Typically these programs provide users with a weekly weight loss lessons on topics such as eating in social situations and building environmental cues for physical activity. The VR vignettes will be designed to complement these topics. The vignettes will be set in fully rendered computer generated environments with virtual actors, and will allow the user to fully experience learning and implementing behavioral weight control strategies. A virtual coach will lead the user through each vignette, teach the user behavioral weight control strategies, and help the user cope with any consequences of using behavioral weight control strategies. In Phase I of this project, we will develop the VR software engine and one vignette focused on social eating situations that will be used to conduct initial feasibility and efficacy testing. In Phase II, we plan to develop additional vignettes and test the complete VR system in a RCT of Internet-delivered obesity treatment.
Overweight and obesity are major health problems affecting over two thirds of US adults. Effective behavioral treatments have been adapted for widespread dissemination via the Internet, but the efficacy is suboptimal due to lack of (1) skills training and (2) opportunities for social modeling and reinforcement. We propose to improve Internet-delivered obesity treatment by using a Web-based VR system to provide the experience of learning and implementing behavioral weight control strategies in controlled virtual settings with the support of a virtual coach.
| Thomas, J Graham; Spitalnick, Josh S; Hadley, Wendy et al. (2015) Development of and feedback on a fully automated virtual reality system for online training in weight management skills. J Diabetes Sci Technol 9:145-8 |
