Optimization and Evaluation of a Tailored Behavioral eHealth/mHealth Weight Loss Intervention for Cardiac Rehabilitation Patients Using the Multiphase Optimization Strategy

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PROJECT SUMMARY/ABSTRACT Cardiovascular disease (CVD) is the leading cause of death in the United States. Cardiac rehabilitation (CR) is an evidence-based, cost-effective, and widely-available multidisciplinary program that combines supervised exercise with psychoeducation on health behavior change aimed at improving overall health and reducing cardiovascular risk in individuals with established CVD. Despite CR's ample attention to increasing physical activity (PA) and improving diet it produces almost no weight loss (WL). WL would significantly improve the CR patients' health, the majority of who present to CR with obesity. Gold standard in-person behavioral weight loss interventions (BWLs) produce clinically significant WL that improves health and disease risk/severity, but these programs are so burdensome and costly that they are impossible to conduct within existing CR programs. The primary mentor's fully automated 3-month online program, Rx Weight Loss (RxWL), produced clinically significant mean±SD WL of 5.8±4.4 % of initial body weight in physician-referred patients (N=154), 5.8 ±5.2 % in worksites (N=75), and 4.2±5.3 % in community settings (N=230); this was maintained at 6-months. Dr. Goldstein, the candidate, aims to conduct formative work to tailor RxWL for use in CR. She will then use the Multiphase Optimization Strategy (MOST) to rapidly screen 4 innovative eHealth/mHealth intervention components with the potential to improve WL in this special population when combined with the core RxWL program. Following pilot testing with n=20, a fully-powered 24 full factorial experiment with 160 patients (each randomized to receive 0-4 of the components) will be used to test the 4 novel intervention components: (a) a tailored interactive intervention to promote structured PA using a Fitbit; (b) a bite counting device to promote caloric restriction; (c) a Web-based virtual reality (VR) intervention for BWL skills implementation; and (d) virtual meetings to increase WL self-efficacy. By the 6-month follow-up, this design will allow the candidate to determine which components maximize WL and whether there are favorable component combinations. Dr. Goldstein will test which components are (or are not) effective and why or how they exert their effects, which is critical for understanding their mechanism of action (or inaction). Each component will be required to meet a 2% WL optimization criterion for inclusion in the final treatment package. This research will result in a fully- automated BWL treatment package optimized for CR, which will be submitted for testing in a randomized controlled trial (RCT) in an R01 developed during the K23 grant period. Given the candidate's success while earning her PhD from Kent State University and completing an NHLBI-funded Cardiovascular Behavioral Medicine T32 at The Miriam Hospital and Brown University, the candidate will undoubtedly leverage the resources in her exemplary research environment to develop into a successful, independent scientist. Through a robust training plan and innovative research project, Dr. Goldstein will become one of the only independent scientists to use eHealth/mHealth technology to facilitate WL in CVD, specifically CR, patients.