Powerful Feelings: Extending the Extended Parallel Processing Model to Collective Action on Climate Change

Neil Stenhouse

Major Professor: Edward Wile Maibach, PhD, Department of Communication

Committee Members: Emily K. Vraga, Xiaoquan Zhao, Teresa Myers

Merten Hall (formerly University Hall), #2500
July 15, 2015, 11:00 AM to 09:00 AM


The extended parallel processing model (EPPM) is a theory of how individuals’ perceptions of a threat, combined with their perceptions of their own ability to effectively remove the threat, influence their behavioral response (Witte, 1992). Recently, scholars have suggested extending the EPPM to explain responses to the collective threat of climate change (Hart & Feldman, 2014). A key change they suggest to the EPPM is increasing the number of efficacy perceptions in the model, to include both perceived likelihood of political action influencing politicians’ actions, and perceived effectiveness of policy in reducing climate change. In this dissertation, I build on their work by examining two additional kinds of efficacy perceptions. My first study uses data from a large nationally representative survey; the second study is a message experiment conducted on Amazon’s Mechanical Turk service. I find that of all the efficacy beliefs examined, perceived efficacy of government climate policy may have the strongest relationship to political action. Perceptions of the threat of global warming were not strongly related to political action.