<b>THE EFFECTS OF EXTERNAL STRESSORS ON CONSTRUCTION WORKERS’ SAFETY PERFORMANCE</b>
Creators: name: Pooladvand, Shiva
Publisher: name: Purdue University Graduate School
Year: 2024
Subjects: classificationCode: 400599
subject: Civil engineering not elsewhere classified
classificationCode: 400504
subject: Construction engineering
classificationCode: 520505
subject: Social psychology

description: Construction workers often suffer from excessive stress from working in dynamic and complex hazard-rich environments. These workers are subject to experiencing diverse external stressors, which can increase their involvement in risk-taking behaviors by increasing human error, referring to individuals’ misperceptions and misjudgment. Task, social, and environmental stressors are the most common external stressors that can negatively impact workers’ safety performance. Task stressors mainly occur when the projects fall behind schedule which puts workers under productivity and mental demand. In addition, workers are exposed to social stressors due to the inherently social environment of construction job sites requiring collaborative efforts. Such workers also suffer from environmental stressors as they mainly need to perform construction tasks outdoors in extreme environments. There is a paucity of research to empirically examine how such external stressors may affect workers’ situational awareness and risk-taking behaviors. Therefore, the overall goal of this dissertation is to <i>examine the theoretical foundations and empirical evidence of changes in workers’ decision dynamic in the construction industry when exposed to task (e.g., productivity pressure and mental demand), social (e.g., peer pressure), and environmental (e.g., heat stress) stressors.</i>To accomplish this, a series of studies were conducted to investigate the effects of task, social, and environmental stressors on workers’ situational awareness and hazard identification skills. To do so, taking advantage of novel technologies, this study developed immersive mixed reality (MR) and augmented virtuality (AV) simulating high-risk construction tasks. Such environments were integrated with several wearable sensing technologies to measure individuals’ cognitive responses and decision dynamics while completing the tasks under different stressors. The findings demonstrated that external stressors reduce worker situational awareness, impair their cognitive processes, and negatively affect their safety performance.Such findings were then utilized to develop an intelligent and comprehensive AI-based predictive system to identify at-risk workers imposed to external stressors. This system translates physiological, cognitive, and biomechanical metrics into AI-identified predictors of three types of external stressors; localizes workers, and assesses risks of being injured in real-time which will then dictate the urgency of providing any intervention. These analyses are then used to identify and propose tailored safety interventions.This dissertation contributes to the existing body of knowledge by adopting innovative approaches to empirically study the extent to which external stressors may affect workers’ decision dynamics by examining the changes in their situational awareness, risk-taking, and safety performance measures. In addition, this work contributes to practice by raising awareness about the adverse effects of several cognitive biases due to such stressors, such as risk compensation, cognitive tunneling, and impaired attentional distribution, which can undermine the efficacy of safety interventions in the construction industry. It highlights the critical role of these cognitive biases in safety practices and the necessity of educating safety professionals and workers about how psychological factors can impact safety on the job site and potential ways to mitigate these potential negative impacts. Further, the developed AI-based predictive system breaks new ground by identifying at-risk workers, assessing potential risks, and recommending safety interventions.