Modeling the impact of stress, caffeine, and sleep on reaction time in Moroccan air traffic control

The study aimed to examine how caffeine intake during the day, sleep patterns, and perceived stress levels influence vigilance among Moroccan air traffic controllers (ATCs). It also assessed the predictive accuracy of the Unified Model of Performance (UMP), provided by the 2B Alert Web tool, in forecasting actual reaction times. Vigilance remains crucial in ATC, where errors can create serious safety hazards. One of the few models developed using the UMP that includes caffeine and sleep data to predict alertness is the 2B Alert Web computer program. Even this model, along with most new methods for predicting fatigue, often overlooks psychological factors like reported stress, which greatly influence daily functioning. The study lasted four days and included thirty-nine undergraduates. At the end of each session, participants completed a 3-min Psychomotor Vigilance Task (PVT) after providing information on caffeine intake, sleep duration, distress levels, and relaxation states. UMP predictions were compared to actual PVT performance. Analyses involved descriptive statistics, principal component analysis, and multiple linear regression. Additionally, a second study with 32 experienced professional ATCOs was conducted to confirm the findings. Reaction time was generally influenced by sleep and caffeine; however, the subgroup “non-responders” showed no benefit and consistently experienced high stress and low restfulness. Regression analysis identified sleep, caffeine, stress, and age as predictors. Stress during the test alone predicted lower reaction times and impacted vigilance. While the widespread influence of caffeine and sleep on cognitive performance is well-documented, excluding psychological stress, especially stress-related factors, may conceal crucial aspects.