August 27, 2012
We would like to congratulate Stephanie Lanza, Runze Li, and Jingyun (Michael) Yang of The Methodology Center and Megan Piper of the University of Wisconsin’s Center for Tobacco Research and Intervention, who were recently awarded an R01 from the National Cancer Institute. The project, Advancing Tobacco Research by Integrating Systems Science and Mixture Models, will integrate time-varying effect models and latent class analysis in order to identify subgroups of smokers who experience the process of nicotine withdrawal differently. This research will facilitate the development of time-varying interventions to meet the needs of individual smokers.
Although the collection of ecological momentary assessment (EMA) data has become popular in tobacco research, the wealth of information embedded in such data sets remains largely untapped. Only very recently have new systems-science approaches, like time-varying effect models, become available for analysis of EMA data, offering the potential to address complex questions about the dynamics of the smoking-cessation process. Integrating time-varying effect models and latent class analysis will advance knowledge of how different smoking-cessation treatments work, for whom, and when. Research results will guide future smoking-cessation interventions.
Read about a special issue of Nicotine and Tobacco Research on new methods for tobacco research. (The call for articles is open until October 1, 2012.)