Optimization of a mHealth Behavioral Weight Loss Intervention for Young Adults

优化年轻人的移动健康行为减肥干预措施

• 批准号: 10213025
• 负责人: Deborah F. Tate
• 金额: $ 65.89万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-10 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10213025
• 关键词: Address; Adult; Age; Behavior; Behavior Therapy; Behavioral; Body Weight Changes; Body Weight decreased; Body mass index; Characteristics; Clinical; Collection; Competence; Coupled; Decision Making; Development; Diet Monitoring; Dietary intake; Distal; Electronic Mail; Engineering; Epidemic; Ethnic Origin; Experimental Designs; Feedback; Frequencies; Gender; Goals; Individual; Informal Social Control; Internet; Intervention; Life Style; Mediation; Mediator of activation protein; Modeling; Monitor; Morbidity - disease rate; Obesity; Outcome; Overweight; Participant; Persons; Physical activity; Population; Population Heterogeneity; Problem Solving; Public Health; Race; Randomized; Schedule; Science; Specific qualifier value; Structure; Testing; Text Messaging; Time; Treatment Protocols; United States; Update; Weight; Weight Gain; Work; adaptive intervention; alternative treatment; clinically significant; cost; design; digital; digital health; digital intervention; evidence base; experimental study; follow up assessment; follow-up; health data; high risk; improved; individual variation; mHealth; middle age; mortality; multiphase optimization strategy; obesity treatment; public health intervention; randomized trial; remote delivery; skills training; tool; web-based intervention; weight loss intervention; young adult

PROJECT ABSTRACT Obesity has reached epidemic proportions in the United States and is recognized as a major cause of morbidity and mortality. Young adults (18-35 years) are at particularly high risk for weight gain and obesity. In- person behavioral interventions generally produce clinically significant weight losses; however, cost and access limit their potential to reduce obesity at a population level. Although web-based interventions that mimic the structure of weekly face-to-face treatment have proven a viable alternative treatment, weight losses are generally smaller than in-person treatment. Exclusively mobile treatments have been less effective, producing 1-3 kgs over 6 months. Newer digital intervention approaches called “Just-in-Time Adaptive Interventions” (JITAIs) promise to improve upon outcomes by offering adaptive, personalized feedback on behavior “when needed” in “real time,” rather than on a fixed schedule. This “just-in-time,” or JIT, approach is made possible by the emergence of low-cost and widely available digital health tools that allow for the collection of continually updated health data. However, few studies have used JIT approaches in remotely delivered, fully scalable weight loss interventions. Although JITAIs are a potentially transformative approach to delivering obesity interventions, a major obstacle in their development is efficient selection of components and systematic design of an optimized intervention package that produces clinically meaningful weight losses with a population-level strategy. To solve this problem, we will use the Multiphase Optimization Strategy (MOST), an engineering- inspired framework, and a highly efficient experimental design to identify which levels of 5 intervention components contribute meaningfully to change in weight over 6 months among young adults with overweight and obesity. All participants (n=608) will receive a core 6-month weight loss intervention that includes evidence-based lessons, behavioral skills training, and daily weighing. With the goal of determining if greater adaptation will lead to greater weight loss, we will randomize participants to standard versus more adaptive options of 5 additional intervention components: 1) diet monitoring approach (standard vs. simplified), 2) adaptive physical activity goals (weekly vs. daily), 3) decision points for message timing (fixed vs. adaptive), 4) decision rules for message content (standard vs. adaptive), and 5) message choice (no vs. yes). Candidate components have been carefully selected from empirical evidence, tested in our prior studies, or in our pilot micro-randomized trial. Assessments will occur at 0, 3 and 6 months to accomplish the following specific aims: 1) Build an optimized JITAI consisting of the set of intervention components that yield the greatest improvement in weight change among young adults at 6 months; 2) Conduct mediation analyses to test the relationships between the intervention components and hypothesized proximal mediators (self-regulation, competence, relatedness, relevance, autonomy) and more distal behavioral mediators (dietary intake, physical activity, and daily self-weighting); and 3) Conduct exploratory

项目摘要