Ulises Techera’s research while affiliated with University of Colorado Boulder and other places

Hazard recognition is a fundamental skill required for nearly all construction injury prevention activities. Unfortunately, researchers have consistently found that work crews identify and discuss less than half of the hazards that they face in a typical work period. Fatigue has shown to compromise workers attention and reaction capabilities. However, the effect of fatigue on hazard recognition (HR) performance has not been previously studied. This paper studies this relationship by leveraging empirical data collected from 155 electrical power transmission and distribution line (TD) workers in the U.S. The level of fatigue of TD workers was assessed using the psychomotor vigilance test (PVT) and their ability to identify hazards was documented by the visual inspection of three different construction scenarios. Spearman correlation statistical analyses were performed, and the results indicate a negative correlation between fatigue and HR ability (r = - 0.21, p=0.015). These results emphasize the importance of improving fatigue management in construction to improve awareness and prevent injuries. Additionally, collecting data in the field enhanced the ecological validity of this work, complementing laboratory studies, and providing confidence that the relationship is pervasive in the field.

Within the construction industry, electrical transmission and distribution workers (TD workers) account for one of the highest fatality rates. Because of the hazardous nature of the work, there is little margin for human error. Previous research shows that fatigue exacerbates human error, thus representing a critical safety factor for TD work. Although researchers have studied the causes and consequences of fatigue in laboratory settings and in other industries, there is no research specific to TD worker fatigue. To address this knowledge gap and explore the principal fatigue causes and consequences as recognized by the workers; 143 TD power company workers were interviewed using a standardized questionnaire. Additionally, fatigue identification and mitigation techniques relevant to TD work and the impact of fatigue in accident causation were discovered. The results revealed that TD workers perceive extreme temperatures and long shifts to be the principal causes of their fatigue, resulting in reduced work pace and the loss of attention as the primary consequences. The results suggest that fatigue laboratory research may not directly apply to field conditions.

This study investigated the empirical relationship between measures of construction safety climate dimensions and safety performance. A comprehensive review of existing literature of construction safety climate was conducted to: (1) review the questionnaires used to measure safety climate dimensions in the construction industry; (2) identify the salient dimensions of safety climate; and (3) establish a consistent definition of each safety climate dimension. Then, a statistical meta-analysis of the empirical relationship between construction safety climate dimensions and safety performance was performed. 107 studies were reviewed, and 11 studies were included in the meta-analysis. The review indicated that 14 construction safety climate dimensions were commonly used to assess safety climate. Of the 14 dimensions, five— supervisor’s safety role (r = 0.30, 95% CI = 0.07 to 0.50), management commitment to safety (r = 0.27, 95% CI = 0.23 to 0.31), safety rules and procedures (r = 0.25, 95% CI = 0.12 to 0.37), individual responsibility to health and safety (r = 0.23, 95% CI = 0.17 to 0.31, and training (r = 0.10, 95% CI = 0.03 to 0.17)—were identified as commonly used predictors of injury rates. The results can be used by researchers and practitioners in this burgeoning field to standardize the assessment of safety climate and to validate the use of safety climate as a predictor of safety performance.

The increasing commitment to safety over the last two decades has contributed to a 67% decline in recordable incident rates. The rate of fatalities, however, has recently increased. Human factors, like fatigue, strongly relate to fatalities. The prediction of fatigue would allow for an early intervention, thus mitigating safety risk. The literature suggests several potential predictors of fatigue onset; however, each of these was mainly studied in isolation, in laboratory settings, and their predictive validity in the construction industry remains unknown. The authors hypothesized that a set of measurable factors can predict construction worker fatigue. A field study of 252 US construction workers was conducted in which potential predictors and fatigue levels were assessed, and the first fatigue predictive models for construction workers were created. The models presented low to medium predictivity, demonstrating that laboratory research and results obtained from other occupations do not directly apply to the construction industry. Furthermore, fatigue predictive models showed to differ among trades. These models will serve the industry to better manage fatigue; however, further research in this area is needed.

Objective: The study objective was to statistically codify empirical occupational fatigue literature into a systems model depicting causal factors of fatigue; interrelationships among causal factors; outcomes of fatigue; and interrelationships among outcomes. Methods: The objective was achieved via a comprehensive and systematic review of existing literature and the first statistical meta-analysis of occupational fatigue. Results: The drivers of fatigue with the greatest effect sizes include sleep deprivation and work environment factors such as noise, vibration, and temperature. The most significant outcomes of fatigue include short-term cognitive and physical degradation and, to a lesser extent, error, injury, and illness. Conclusions: Although there is a great deal of occupational fatigue literature, there is a dearth of replication and validations studies. Researchers are also encouraged to address knowledge gaps like the relationship between worker relationships and fatigue.

Many of the greatest catastrophes caused by human error such as Three Mile Island, Chernobyl and Exxon Valdez occurred after extended hours of work when the levels of fatigue among workers were extremely high. Fatigue, which recent research has identified as a principal precursor of many construction accidents, has not been managed well because the leading and lagging indicators are difficult to measure and manage. This paper provides the first comprehensive overview of fatigue measurement strategies adapted to the construction industry which focuses on both leading and lagging indicators and on subjective and objective metrics using the most recent technology. The paper includes a description of each measurement method, the implementation of the metric, and the reliability and accuracy of the metric based on field trials. Recommendations are presented for the most efficient and reliable means of measuring fatigue based on the validation of the methods and their applicability to the construction industry. These findings will inform the industry and future researchers about how different fatigue measurement tools may be used to serve as indicators of performance, safety, or as variables in an experiment. Finally, this paper reveals areas where additional research can be conducted.