Personal Navigation: The Influence of Personality and Spatial Anxiety on active spatial navigation in a Virtual Reality and Real World environment.

Abstract

Introduction: Navigation is a fundamental cognitive function in daily life, influenced by several separate mechanisms. However, the influence of personality traits on objectively measured navigation performances has hardly been investigated. Therefore, current research has focused on the influence of the Big-Five personality traits and spatial anxiety on actual navigation performances in a virtual reality and a real world environment. Methods: Actual navigation performances have objectively been measured by tracking the number of errors and hesitations of the participants, while they were completing four routes in virtual reality and real world environments. Route and survey knowledge tasks were executed after completion of the routes to verify potential moderation of these cognitive mechanisms on the influence of personality on navigation performances. Personality and spatial anxiety have been measured using the IPIP-100 questionnaire and Lawton’s spatial anxiety scale. Results: Results have indicated that spatial anxiety is a significant negative predictor for navigation performances. A combination of a high level of conscientiousness and survey knowledge has been a significant predictor for improved navigation performances. No significant differences in performances between a virtual reality and a real world environment has been indicated. Discussion: Current research has been an explorative study which has given indications to a negative influence of anxiety mechanisms on navigation abilities due to impaired attentional disengagement to environmental features in the route. Moreover, the beneficial effect of the combination of conscientiousness and survey knowledge have given directions that mental structuring and working memory modulation might enhance path integration while navigating. These results have given a unique contribution to an integrated model predicting enhanced navigation performances.