Examples may include systems science approaches (e.g., computational modeling and simulation, network analysis, and engineering control methods) to
conceptualize prevention at the micro - or macro-levels of analyses;
alternative intervention
designs for when randomization is not possible; new methods for optimization of interventions; adaptive interventions and SMART
designs; and innovative analytic approaches including time varying effect models, and models for incorporating intensive longitudinal data and / or real time data capture in prevention science research.