Selecting Workload And Stress Measures For Performance Prediction
Abstract
The study of performance, workload, and stress have become a mainstay in the field of Human Factors. These constructs are multi-faceted and are assessed by a variety of measures. In seeking to enhance performance by managing mental workload and stress, it is important for measures to be anchored to meaningful criteria. Workload and stress must be considered with respect to the performance measures that address the most central objectives. While workload and stress research has progressed over the years and includes research across different levels and domains, there has been less effort to link measures to specific performance outcomes. The present study examined four performance metrics from the same task in terms of the workload and stress measures that are most closely associated with, and predictive of them. Results indicated that different sets of workload and stress measures predicted different performance measures, suggesting that measures should also be selected based on the performance criteria of interest.
Publication Date
1-1-2017
Publication Title
Proceedings of the Human Factors and Ergonomics Society
Volume
2017-October
Number of Pages
2042-2046
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1177/1541931213601989
Copyright Status
Unknown
Socpus ID
85042486222 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85042486222
STARS Citation
Teo, G.; Reinerman-Jones, L.; Matthews, G.; Szalma, J.; and Jentsch, F., "Selecting Workload And Stress Measures For Performance Prediction" (2017). Scopus Export 2015-2019. 7062.
https://stars.library.ucf.edu/scopus2015/7062