Dr. Coffman is currently developing and applying methods for analyzing data from biosensors, ecological momentary assessments, and genomics. She aims to identify momentary risk states for physical inactivity and stress, and she works on extending statistical learning/data mining methods to estimate propensity scores in the mediation context. She is developing a method to estimate multi-level propensity scores for continuous exposures.

Dr. Coffman is interested in behavioral health risk factors, namely, diet, substance use, stress, and physical activity (both exercise and reducing sedentary behavior), the causal antecedents of engagement in these behaviors, and the causal effects of these behaviors on health outcomes. Her goal is to examine dynamic causal processes of health behavior change and maintenance, to inform the development of individualized ecological momentary interventions to promote engagement in and maintenance of healthy behaviors. Achieving this goal requires high-resolution data on multiple time scales of observation and at multiple levels of analysis (e.g., environmental, social, behavioral, physiological, genetic).