Determining Contributing Factors for Passenger Airline Pilot Perceived Fatigue

Fatigue is a recurring concern for pilots and continues to be a common contributing cause of aircraft accidents. The purpose of the dissertation was to determine factors that influence fatigue in commercial airline pilots. The ability to accurately associate fatigue in pilots before a flight begins could have a profound and meaningful impact on aviation safety. Seven factors were identified in the literature review as having possible predictive capabilities of perceived fatigue in pilots working for passenger carriers, including time awake, perceived stress, sleep quality, hours of sleep, age, typically scheduled start time, and hours on duty. An electronic survey instrument was used to gather quantitative data from U.S. passenger-carrying airline pilots. Data collected from 271 responses were randomly assigned to two separate groups. First, a regression equation was created utilizing half of the data collected from a survey instrument. The regression identified that age, hours on duty, and sleep quality (JSS) were significant independent variables (IVs) contributing to fatigue. Next, the regression equation was used to create predicted values of perceived fatigue. Then the second half of the dataset was used to validate if the equation could be utilized to identify contributing factors for passenger airline pilots\u27 perceived fatigue. Data were created with the regression equation and compared to perceived fatigue. The model was a moderate fit for the second data set. The analysis identified age as a negative predictor, indicating that fatigue (FSS) decreases as age increases. Age also had the smallest effect size of the significant IVs. These two items, while counterintuitive, are possibly explained by variances in schedules between pilot seniority. Sleep Quality (JSS) had the most significant effect on fatigue, while hours on duty had a larger effect than age but a smaller effect than sleep quality. Four variables studied were not significant predictors of fatigue and were not used in model creation: time awake, perceived stress, hours of sleep, and typically scheduled start time. Safely operating a flight involves weighing the implications of fatigue and other possible hazards resulting in many possible predictive factors. Heinrich’s domino theory was used to derive the fatigue factors in this dissertation. The significant predictor variables, age, hours on duty, and sleep quality form a potential “domino” for a fatigue- related accident. These fatigue factors may not cause an accident but could be a “domino” in a series of factors. While some fatigue factors have been studied, the factors studied in this dissertation have not previously been studied in the same way by creating a model with this population. Additionally, previous fatigue studies have not typically researched U.S.- based passenger-carrying pilots. Analyzing risks associated with fatigue in passenger- carrying pilots at commercial airlines is particularly complex because many factors can influence fatigue, including scheduling software, union contracts, and norms and practices. Airlines and regulators could use the prediction equation to potentially reduce fatigue-related risks. The equation created can predict fatigue in advance of scheduled flights and serve as a starting point for future fatigue researchers