Title: Characterization of the manifestation of stages and processes of smoking behavior change in health-related social intercourse Abstract Chronic disease management is largely dependent upon individuals? engagement in adoption and modification of one or more health behaviors (e.g. medication adherence, daily exercise, smoking cessation) over long term. Despite prevalence of theory-guided behavior change interventions, behavior modification is oftentimes a chronic, relapsing effort in and of itself. The effect of social relationships and behavior change has been well documented, nonetheless, rarely infused into health interventions. Our understanding of (a) the mechanisms through which such influence affects human behaviors, and (b) how such influence can be harnessed to improve the effectiveness of theory-guided behavioral interventions is limited. In the proposed research, we will develop a set of semi-automated methods to characterize the interrelation between theory driven stages of behavior change and social influence models of human behavior in group settings, as embedded in user generated interactions on a health-related online community. While generally applicable, the methods will be developed based on communications among individuals attempting to quit smoking in an online community, QuitNet, the first online social network for smoking cessation. Advanced text analytics will be used to identify and extract the stages and processes of behavior change. Stage-oriented network affiliation models will then be used to characterize the interdependencies among social actors, behavioral processes, and behavioral states. This research proposal will result in 1) novel methods to incorporate behavioral stages and processes into network models of social influence; 2) scalable techniques to automate identification of behavioral stage through text annotation of user interactions; and 3) new proposals for the development of digital interventions and technology features that harness social ties and theoretical roots to support individuals engaging in health behavior change and chronic disease management.
This project investigates the manifestation of behavior change processes and stages in online social discourse focusing smoking cessation. As a component of the proposed research we will integrate automated text analysis and network models to understand social mechanisms and influence patterns underlying electronically captured peer-to-peer communication related to behavior modification. By enabling the study of content-specific communication events focusing on specific stages of change, the proposed research will provide actionable insights into the development of socio-behavioral interventions that target online communities and consider users? behavioral state and stage. In addition, the research will provide understanding of the specific behavior change processes that trigger certain stage transitions.