Evaluating mental workload: A taxonomic approach to evaluation tools based on ISO 10075

Recent technological transitions present in the manufacturing sector are transforming the way operators work, greatly impacting their mental workload and presenting new challenges for the cognitive ergonomics field. In an effort to design and implement human-centered management strategies, it is increasingly necessary to effectively explore and evaluate the various aspects related to mental workload. Despite the maturity of the field, in the existing literature a consensus on defining mental workload remains elusive. To bridge this gap, this paper introduces a comprehensive and holistic definition, drawing inspiration from the ISO 10075 standard. This novel taxonomic framework distinguishes various constructs related to mental workload, clarifying their causes and the consequences they induce. Additionally, an extensive literature analysis was conducted to develop a taxonomy of mental workload assessment tools, outlining their operational principles along with their strengths and weaknesses. This taxonomy can be used as a pragmatic guide for selecting appropriate tools based on specific contexts. Moreover, the existing literature was extensively investigated to ascertain the nature of the correlation-whether positive or negative-between the metrics of these tools and the range of the effects of mental workload fluctuations. This methodological approach addresses the common issue of misinterpreting results from mental workload measurements. In essence, the research seeks to enrich the understanding of mental workload concepts and offers a critical evaluation of its measurement tools. The findings are intended to assist practitioners in the informed selection of measurement tools and to refine data interpretation, thereby facilitating better management of mental workload in manufacturing environments.

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Publication Details

Journal
Applied Ergonomics
Published
2025-10-08
DOI
https://doi.org/10.1016/j.apergo.2025.104659
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
2.44
Controls
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article

Evaluating mental workload: A taxonomic approach to evaluation tools based on ISO 10075

Riccardo Gervasi, Mirco Bartolomei, Michela Balconi, Luca Mastrogiacomo et al.
1 citations
Applied Ergonomics
Human-Automation Interaction and Safety
2.44
article

Evaluating mental workload: A taxonomic approach to evaluation tools based on ISO 10075

Riccardo Gervasi, Mirco Bartolomei, Michela Balconi, Luca Mastrogiacomo, Laura Angioletti, Fiorenzo Franceschini, Carlotta Acconito, Davide Cannizzaro
article en
1 citations

Abstract

Recent technological transitions present in the manufacturing sector are transforming the way operators work, greatly impacting their mental workload and presenting new challenges for the cognitive ergonomics field. In an effort to design and implement human-centered management strategies, it is increasingly necessary to effectively explore and evaluate the various aspects related to mental workload. Despite the maturity of the field, in the existing literature a consensus on defining mental workload remains elusive. To bridge this gap, this paper introduces a comprehensive and holistic definition, drawing inspiration from the ISO 10075 standard. This novel taxonomic framework distinguishes various constructs related to mental workload, clarifying their causes and the consequences they induce. Additionally, an extensive literature analysis was conducted to develop a taxonomy of mental workload assessment tools, outlining their operational principles along with their strengths and weaknesses. This taxonomy can be used as a pragmatic guide for selecting appropriate tools based on specific contexts. Moreover, the existing literature was extensively investigated to ascertain the nature of the correlation-whether positive or negative-between the metrics of these tools and the range of the effects of mental workload fluctuations. This methodological approach addresses the common issue of misinterpreting results from mental workload measurements. In essence, the research seeks to enrich the understanding of mental workload concepts and offers a critical evaluation of its measurement tools. The findings are intended to assist practitioners in the informed selection of measurement tools and to refine data interpretation, thereby facilitating better management of mental workload in manufacturing environments.

Applied ErgonomicsVol. 130
Università Cattolica del Sacro Cuore (IT), Politecnico di Torino (IT), University of Turin (IT)
Openalex Percentile: Top 9%
Human-Automation Interaction and Safety
2.44
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