Self-monitoring (e.g., of weight, dietary intake, and physical activity) is a core component in evidence-based comprehensive lifestyle interventions for obesity, and greater adherence to self-monitoring has been associated both with better short-term weight loss and long-term weight loss maintenance. Importantly, research has demonstrated that the provision of interventionist feedback on self-monitoring increases adherence to self-monitoring and improves weight loss outcomes. Little empirical evidence exists, however, to provide guidance on how this feedback should be provided. One study conducted in this area demonstrated that intentions to self-monitor differ by feedback complexity, such that too little (and, conversely, too much) feedback reduces future intentions to self-monitor and engage in related health behavior change; however, less is known regarding how the type and complexity of feedback messages affect actual self-monitoring behavior and subsequent weight loss outcomes. Importantly, provision of this feedback also represents a substantial investment of clinician time; research demonstrated that feedback messages incorporating self-monitoring data related to weight, dietary intake, and physical activity can take \~26 minutes per person to compose. Thus, the investigators propose a line of research that aims to optimize the provision of self-monitoring feedback (i.e., identifying the optimal number and type of feedback messages) for supporting adherence to weight-management behaviors. For the current study, the investigators propose to conduct a micro-randomized, factorial trial that will evaluate the proximal impact of different types and amount of feedback on change in weight and weight-related behaviors (e.g., adherence to self-monitoring, caloric goal attainment, physical activity goal attainment). Using a 2x2x2x2 factorial model, participants will be randomized each week for 16 weeks to one of 16 possible feedback conditions, allowing us to efficiently test four feedback components (i.e., feedback on calorie goal attainment, dietary quality, physical activity goal attainment, or on goal setting) in one study. Mixed-effects models will be used to assess the effects of the four specified feedback components on weight change the week after each component is provided (i.e., over the following "study week"). As a secondary aim, the investigators propose to investigate whether the effectiveness of certain types and combinations of feedback is affected by individual or contextual factors. A similar multivariate mixed-effects modeling approach will be used to investigate potential moderators of feedback effectiveness (i.e., age, gender, and race) and whether different combinations of feedback are more effective when individuals are "doing well" in the program compared to when they are not doing well. Finally, time-dependent effects of feedback components (e.g., whether some feedback components are more effective earlier or later in the intervention) will be examined by investigating interactions between time and feedback condition, with time modeled both as a linear and polynomial effect. Results will inform development of an optimized protocol for feedback provision.