A Curvilinear Effect of Mental Workload on Mental Effort and Behavioral Adaptability: An Approach With the Pre-Ejection Period. (September 2020)

• Record Type: Journal Article
• Authors: Mallat, Charlotte; Cegarra, Julien; Calmettes, Christophe; Capa, Rémi L.
• Is Part Of: Human factors. Volume 62:Number 6(2020)
• Page Start: 928
• Page End: 939
• Publication Date: 2020-09
• Subjects: workload -- effort -- performance -- cardiovascular reactivity; Human engineering -- Periodicals; 620.82
• DOI: 10.1177/0018720819855919
• Languages: English
• ISSNs: 0018-7208

Abstract

Objective: We tested Hancock and Szalma's mental workload model, which has never been experimentally validated at a global level with the measure of the pre-ejection period (PEP), an index of beta-adrenergic sympathetic impact. Background: Operators adapt to mental workload. When mental workload level increases, behavioral and physiological adaptability intensifies to reduce the decline in performance. However, if the mental workload exceeds an intermediate level, behavioral and physiological adaptability will decrease to protect individuals from excessive perturbations. This decrease is associated with a change in behavioral strategies and disengagement. Method: The experimental task was a modified Fitts' task used in Hancock and Caird. Five levels of task difficulty were computed. Behavioral and physiological adaptability was indexed by the performance with speed–accuracy trade-off and PEP reactivity. Results: A curvilinear effect of task difficulty on PEP reactivity was significant, with high reactivity at the intermediate level but low reactivity at other levels. We observed a linear effect of task difficulty on error rate and a curvilinear effect on movement time. A decline in performance was noted up to the intermediate level, with a speed–accuracy trade-off above this level showing a faster movement time. Conclusion: We observed for the first time behavioral and physiological adaptability as a function of mental workload. Application: The results have important implications for the modeling of mental workload, particularly in the context of the performance-sensitive domain (car driving and air traffic control). They can help guide the design of human–computer interaction to maximize adaptive behavior, that is, the "comfort zone."