Hysteresis In Mental Workload And Task Performance

Keywords

demand transitions; driving simulation; effort regulation; hysteresis; mental workload; task prioritization

Abstract

Objective: We examine how transitions in task demand are manifested in mental workload and performance in a dual-task setting. Background: Hysteresis has been defined as the ongoing influence of demand levels prior to a demand transition. Authors of previous studies predominantly examined hysteretic effects in terms of performance. However, little is known about the temporal development of hysteresis in mental workload. Method: A simulated driving task was combined with an auditory memory task. Participants were instructed to prioritize driving or to prioritize both tasks equally. Three experimental conditions with low, high, and low task demands were constructed by manipulating the frequency of lane changing. Multiple measures of subjective mental workload were taken during experimental conditions. Results: Contrary to our prediction, no hysteretic effects were found after the high- to low-demand transition. However, a hysteretic effect in mental workload was found within the high-demand condition, which degraded toward the end of the high condition. Priority instructions were not reflected in performance. Conclusion: Online assessment of both performance and mental workload demonstrates the transient nature of hysteretic effects. An explanation for the observed hysteretic effect in mental workload is offered in terms of effort regulation. Application: An informed arrival at the scene is important in safety operations, but peaks in mental workload should be avoided to prevent buildup of fatigue. Therefore, communication technologies should incorporate the historical profile of task demand.

Publication Date

12-1-2016

Publication Title

Human Factors

Volume

58

Issue

8

Number of Pages

1143-1157

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1177/0018720816669271

Socpus ID

84994472162 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84994472162

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