Acts of lone extremism are on the rise, yet little is known about who commits these acts. Research in this area has failed to delineate by extremist subtype. This has led to the misconception these acts and actors present with such variance psychosocially that they cannot be predicted. The purpose of this research was to assess whether statistically significant relationships exist between lone extremist subtypes on the psychosocial variables of mental illness, substance use, and having radicalized friends or family members. The conceptual framework for this study was De La Corte's psychosocial principles of terrorism, which addressed the social and political influences of terrorism with the complex psychosocial constructs that may exist. The Profiles of Individual Radicalization in the United States was chosen as the dataset and includes de-identified individual-level information on 1,865 extremists. The research questions that guided this study sought to determine if significant differences exist between 4 lone extremist subtypes across 4 psychosocial variables. Crosstabulation analysis and multiple chi-square tests for independence were used to test the relationship between categorical variables. Statistically significant relationships were found among each lone extremist subtype and having radicalized family members and friends (p=.00). In terms of mental illness, far left extremists were the only extremist subtype that yielded a significant relationship (p=.00). Also, a significant relationship was found between substance use and far right (p=.00), far left (p=.01), and single issue (p=.04) extremists. In terms of social change, this research presented support for studying lone extremism by subtype and also provided a foundation towards constructing a predictive model.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-7731 |
| Date | 01 January 2019 |
| Creators | LaMontagne, Tamara Marie |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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