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Using IoT devices for sensor-based monitoring of employees' mental workload: Investigating managers' expectations and concerns.
- Source :
-
Applied ergonomics [Appl Ergon] 2022 Jul; Vol. 102, pp. 103739. Date of Electronic Publication: 2022 Mar 10. - Publication Year :
- 2022
-
Abstract
- Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European countries (Germany, United Kingdom, Spain) about their expectations and concerns regarding sensor-based monitoring of employee mental workload. The data confirm the relevance of expectations regarding improvements of workplace design and employee well-being, as well as concerns about restrictions of employees' privacy and sovereignty, for the implementation of workload monitoring. Furthermore, Bayesian regression models show that the examined expectations have a substantial positive association with managers' willingness to support workload monitoring in their company. Privacy concerns are identified as a significant barrier to the acceptance of workload monitoring, both in terms of their prevalence among managers and their strong negative relationship with monitoring support.<br /> (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Subjects :
- Attitude
Bayes Theorem
Humans
Workload
Motivation
Workplace
Subjects
Details
- Language :
- English
- ISSN :
- 1872-9126
- Volume :
- 102
- Database :
- MEDLINE
- Journal :
- Applied ergonomics
- Publication Type :
- Academic Journal
- Accession number :
- 35279467
- Full Text :
- https://doi.org/10.1016/j.apergo.2022.103739