The process of extracting latent factors from survey data using factor analysis is used commonly in the psychology literature to diagnose underlying psychological conditions like depression from questionnaires. This research aims to apply the same techniques (namely principal-component factor analysis) to identify the components of risk perception that drive the variation in often seemingly unrelated attitudes of farmers in the Karoo. Multiple analyses on samples extracted from two waves of longitudinal data are conducted in order to verify the variable structure of risk components in the community and Cronbach's alpha is used as a reliability measure to test the degree to which the variables that constitute each extracted component measure a single construct. These tests provide insight into the efficacy with which the survey questions are measuring intended aspects of a population and has implications for survey design. Because the data spans four years in the population under consideration and new variables are included in the second wave of questioning, the effect that new, severe threats have on the structure of risk components are also estimated.