Learning before our Mistakes: Predicting Unintentional Injury by Predicting Error

Unintentional injury remains a significant burden on society and has attracted a broad range of research. Previous injury research has identified a host of risk factors in various injury domains such as inhibitory control, age, cognitive development, and distraction for pedestrian injury. However, much is still left to explore despite extensive work to understand injury etiology. Human error research provides a robust framework to transcend domain-specific prediction by applying performance-shaping factors. In two studies, I examined the impact of several performance-shaping factors on an injury-relevant cross-contextual behavior, multiple object tracking. Specifically, each study examines the impact of task complexity, time pressure, sensory limitations, and nonverbal working memory span on multiple object tracking. The first study examined the impact of performance-shaping factors in an abstract dot tracking task. The second study examined the impact of performance-shaping factors in a pedestrian street-crossing scenario. In both studies, increases in time pressure and sensory limitations were associated with degraded performance and a higher task failure rate. Lower nonverbal working memory spans were also associated with poorer performance and higher failure rates in both studies. In the abstract dot tracking task, an increase in task complexity led to a reduction in performance and increased failure rate, but the relationship was the opposite in the pedestrian scenario. Implications for injury prevention and etiology research are discussed along with future directions.doctoral, Ph.D., Psychology & Communication -- University of Idaho - College of Graduate Studies, 2022-0