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 in troduces 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 tax onomy 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 correla tion—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.
Evaluating mental workload: A taxonomic approach to evaluation tools based on ISO 10075 / Bartolomei, Mirco; Gervasi, Riccardo; Acconito, Carlotta; Angioletti, Laura; Cannizzaro, Davide; Balconi, Michela; Mastrogiacomo, Luca; Franceschini, Fiorenzo. - In: APPLIED ERGONOMICS. - ISSN 0003-6870. - STAMPA. - 130:(2026), pp. 1-24. [10.1016/j.apergo.2025.104659]
Evaluating mental workload: A taxonomic approach to evaluation tools based on ISO 10075
Mirco, Bartolomei;Riccardo, Gervasi;Luca, Mastrogiacomo;Fiorenzo, Franceschini
2026
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 in troduces 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 tax onomy 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 correla tion—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.File | Dimensione | Formato | |
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APPLIED ERGONOMICS v.130, n.104659, pp.1-24, Mental Workload (MB RG CA LA MB DC LM FF).pdf
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https://hdl.handle.net/11583/3003795