My research spans both social psychology and quantitative psychology. My social psychological interests focus on coping with stressful life events in the context of close personal relationships. I study situations as diverse as how partners help each other through difficult professional stressors to how individuals cope with the death of a close relationship partner. My most recent research has focused on the links between stress experienced during pregnancy and risk for postpartum depression. Research indicates that postpartum depression risk is related both to social/experiential and physiological factors, and my work has touched on both of these mechanisms. The overarching goal of my work is to understand the ways that social interactions and social cognitions impact the psychological framing of a stressful event and the coping processes it engages.
Partly as a consequence of this work, I have become increasingly interested in understanding health in real-world situations, particularly how to identify solutions to systemic health problems and health disparities. These kinds of issues are complex and don't conform to traditional disciplinary boundaries. I have helped to spearhead efforts to help make Lehigh an example of how interdisciplinary teams of researchers can come together to work on these challenging problems, resulting in the successful proposal of a Community Health faculty cluster, now known as the Community Health Research Group. This group, which is being built around the Community-Based Participatory Research approach, is focusing its efforts on building partnerships with community members to better understand how health problems and solutions look from their perspective, with the hopes of creating more effective and self-sustaining interventions. More information about the Community Health Research Group is available in this press release and this Acumen story. I am currently serving as Director of the Community Health Research Group.
My quantitative interests center on developing and assessing nonlinear statistical models of psychological processes. I am particularly interested in longitudinal nonlinear models that can provide a unique insight into the internal dynamics of psychological processes over time. I have used these methods to examine the time course of grief reactions, identify weekly cycles in social support processes, and pinpoint the contributions of distinct mental processes involved in social judgments. In addition to developing these models, I am interested in assessing and quantifying the payoff of advanced statistical methods over more traditional alternatives.
Burke, C. T., & Perndorfer, C. C. (in press). Negative emotional responses to motherhood-related support receipt during pregnancy predict postpartum depressive symptoms, Anxiety, Stress, and Coping. doi:10.1080/10615806.2015.1092023
Burke, C. T. (2015). Process dissociation models in racial bias research: Updating the analytic method and integrating with signal detection approaches. Group Processes and Intergroup Relations. (Special issue: Enabling a Science of Groups: Statistical and Methodological Advances)
Burke, C. T., & Goren, J. (2014). Self-evaluative consequences of social support receipt: The role of context self-relevance. Personal Relationships, 21, 433-450. doi:10.1111/pere.12039
Lane, S. P., Bluestone, C., & Burke, C. T. (2013). Trajectories of BMI from early childhood through early adolescence: SES and psychosocial predictors. British Journal of Health Psychology, 18, 66-82. doi:10.1111/j.2044-8287.2012.02078.x
Burke, C. T., Shrout, P. E., & Bolger, N. (2007). Individual differences in adjustment to spousal loss: A nonlinear mixed model analysis. International Journal of Behavioral Development, 31, 405-415. doi:10.1177/0165025407077758
Carnelley, K. B., Wortman, C. B., Bolger, N., & Burke, C. T. (2006). The time course of grief reactions to spousal loss: Evidence from a national probability sample. Journal of Personality and Social Psychology, 91, 476-492. doi:10.1037/0022-35220.127.116.116