Date of Award
Master of Arts (MA)
Dr. Nicole Drumhiller
This study furthers research on political leaders through the lens of integrative complexity. Integrative complexity has been used as a measurement tool in political psychology for more than four decades. This study will further research on one of the most challenging endeavors facing integrative complexity scholars – an agreed upon automated scoring system. The subjects are Hillary Clinton and Donald Trump who are the leading candidates for their respective political parties in the 2016 United States presidential election. The study will use the automated integrative complexity scoring system developed by Conway et al. (2014) to analyze selected content from 2016 debate transcripts, issue position speeches, and terrorism related interview questions from June 2015 through March 2016 to measure the integrative complexity levels of both subjects during the campaign. Findings are consistent with previous research that liberal politicians generally score higher than their conservative counterparts on integrative complexity. The findings also support previous research that leaders exhibit decreased integrative complexity during stressful situations. The findings did not support previous evidence that leaders operate at decreased integrative complexity levels while campaigning. The study ultimately furthers the body of research evolving the latest automated integrative complexity scoring system.
Romero, Angela M., "Integrative Complexity of 2016 Presidential Candidates as an Indicator of Future Decision Making" (2016). Master's Capstone Theses. 108.
*Please note that the Recommended Citation provides general information for citation.
This citation may not be appropriate for your discipline. To locate the correct citation style for APUS programs and receive citation help, visit http://apus.libguides.com/programstyleguides .