Impact of multiple stressors on cognitive performance : towards a predictive model
Abstract
Professionals operating in high risk, demanding environments often face multiple stressors that influence cognitive functioning. While many studies have examined single stressors, real-world situations typically involve several stressors occurring simultaneously. This thesis aims to develop and validate a theoretical model to understand and predict the combined effects of multiple stressors on cognitive performance. The proposed model integrates a combined Stressor Load model into a Cognitive Performance model. The Cognitive Performance model assumes that performance follows an inverted U shaped curve as a function of Task Demand, which is defined as the sum of Task Load (the inherent demand of the task) and combined Stressor Load. Interactions between stressors are assumed to depend on the extent to which underlying mechanisms overlap or not, particularly whether they compete for physiological resources, cognitive resources, or both. Depending on this overlap, interactions can be additive, antagonistic, or synergistic. Shifts in Task Demand caused by combined stressors can therefore improve, impair, or leave performance unchanged. Four studies addressed two research questions: (1) how combined stressors affect cognitive performance, and (2) how well the model predicts these effects. Studies in Chapters 2–4 examined stressor combinations with either distinct or shared mechanisms. Overall, evidence for the interaction effects was limited. In several studies, stressors were not effective in producing an effect or were not always in the predicted direction. Some stressors (e.g., noise bursts, and acute social stress) unexpectedly improved performance, whereas others (e.g., heat load, sleep deprivation) caused a performance decline. These findings prevented firm conclusions about the validity of the combined Stressor Load model. The final study (Chapter 5) examined whether performance follows the assumed inverted U-shape as function of Task Demand by varying Task Load within an individual. Although most participants showed performance decline at high Task Load, heat‑induced Stressor Load did not produce the expected shift in performance. Overall, the model could not reliably predict cognitive performance under multiple stressor conditions. The findings suggest that the model may be too simplistic, as humans are adaptive and capable of adjusting to varying levels of Stressor- and Task Load. This thesis proposes incorporating mental state as an additional internal factor that can alter the shape of the performance curve rather than merely shifting the position along the axis.
Fields of Study & Subjects
Human-Automation Interaction and Safety
Sleep and Work-Related Fatigue
Occupational Health and Performance
Publication details
- Publication date
- 23 February 2026
- Language
- EN
- Document type
- Thesis