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Cited by 222Human-Automation Interaction and SafetyErgonomics and Human FactorsEmotion and Mood Recognition

The DOI matches its Crossref record; 228 of the 229 references it cites were found in a registry or an index, and 1 are not checked yet.

Human Mental Workload: A Survey and a Novel Inclusive Definition

Open access
Longo, Luca, Wickens, Christopher D., Hancock, Gabriella, Hancock, P. A.·2022·Frontiers in Psychology
DOI 10.3389/fpsyg.2022.883321PMC PMC9201728
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Abstract

Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics. Uncertainties exist in its characterization, motivating the design and development of computational models, thus recently and actively receiving support from the discipline of Computer Science. However, its role in human performance prediction is assured. This work is aimed at providing a synthesis of the current state of the art in human mental workload assessment through considerations, definitions, measurement techniques as well as applications, Findings suggest that, despite an increasing number of associated research works, a single, reliable and generally applicable framework for mental workload research does not yet appear fully established. One reason for this gap is the existence of a wide swath of operational definitions, built upon different theoretical assumptions which are rarely examined collectively. A second reason is that the three main classes of measures, which are self-report, task performance, and physiological indices, have been used in isolation or in pairs, but more rarely in conjunction all together. Multiple definitions complement each another and we propose a novel inclusive definition of mental workload to support the next generation of empirical-based research. Similarly, by comprehensively employing physiological, task-performance, and self-report measures, more robust assessments of mental workload can be achieved.

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Crossref · 10.3389/fpsyg.2022.883321

Cites

228 of 229 references verified0 citation errors · 0 not checkable

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Figure 1 Distribution of sample articles by type.
Figure 1 Distribution of sample articles by type.CC BY · PubMed Central
Figure 2 Percentage of sample articles by research type.
Figure 2 Percentage of sample articles by research type.CC BY · PubMed Central
Figure 3 Percentage of sample articles by research form.
Figure 3 Percentage of sample articles by research form.CC BY · PubMed Central
Figure 4 Percentage of sample articles by research objective.
Figure 4 Percentage of sample articles by research objective.CC BY · PubMed Central
Figure 5 Percentage of sample articles by research reasoning.
Figure 5 Percentage of sample articles by research reasoning.CC BY · PubMed Central
Figure 6 Distribution of the articles by domain of application.
Figure 6 Distribution of the articles by domain of application.CC BY · PubMed Central
Figure 7 Distribution of the articles by sample size of participants.
Figure 7 Distribution of the articles by sample size of participants.CC BY · PubMed Central
Figure 8 Theories linked to the construct of mental workload organized as a framework.
Figure 8 Theories linked to the construct of mental workload organized as a framework.CC BY · PubMed Central
Figure 9 Synthesis of the main concepts, sub-concepts and their interaction associated with the definitions of mental workload found in the literature. The numbers on top of each arrow refers to one or more definitions in Table 2 in Appendix.
Figure 9 Synthesis of the main concepts, sub-concepts and their interaction associated with the definitions of mental workload found in the literature. The numbers on top of each arrow refers to one or more definitions in Table 2 in Appendix.CC BY · PubMed Central
Figure 10 Distribution of the classes of mental workload measures and their joint application.
Figure 10 Distribution of the classes of mental workload measures and their joint application.CC BY · PubMed Central
Figure 11 Distribution of the application of the sensitivity criteria.
Figure 11 Distribution of the application of the sensitivity criteria.CC BY · PubMed Central
Figure 12 Distribution of the application of the diagnosticity criteria.
Figure 12 Distribution of the application of the diagnosticity criteria.CC BY · PubMed Central
Figure 13 Distribution of the application of the reliability criteria.
Figure 13 Distribution of the application of the reliability criteria.CC BY · PubMed Central
Figure 14 Distribution of the application of the validity criteria.
Figure 14 Distribution of the application of the validity criteria.CC BY · PubMed Central
Figure 15 A novel, inclusive and operational definition of human mental workload.
Figure 15 A novel, inclusive and operational definition of human mental workload.CC BY · PubMed Central
Figure 16 An envisioned framework toward the development of a robust multidimensional mental workload model with high reliability, sensitivity, diagnosticity and validity, with different classes of measures and methods.
Figure 16 An envisioned framework toward the development of a robust multidimensional mental workload model with high reliability, sensitivity, diagnosticity and validity, with different classes of measures and methods.CC BY · PubMed Central

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Citations

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Show all 222 references

Research works printed but not linked: 12

  1. Kahneman, 1973, Attention and Effort, Volume 1063
  2. Physiological metrics of mental workload: a review of recent progress KramerA. F. Multiple-Task Performance1991
  3. Mental workload of the vts operators by utilising heart rate KumS. FurushoM. DuruO. SatirT. TransNav, International Journal on Marine Navigation and Safety od Sea Transportation2007
  4. LazarusR. S. FolkmanS. 28833294Stress, Appraisal, and Coping. Springer Publishing Company1984
  5. Miller, 2001, Workload Measures
  6. Mizobuchi, 2005, Mobile text entry: relationship between walking speed and text input task difficulty, 122
  7. Moray, 2013, Mental Workload: Its Theory and Measurement, Vol. 8
  8. Smiley, 1989, Mental workload and information management, 435
  9. Stanton, 1995, Ecological ergonomics: understanding human action in context, Contemporary Ergon, 165, 62
  10. Woods, 2009, Rasmussen's srk 30 years later: Is human factors best in 3's?, 217
  11. Zajonc, 1984, The interaction of affect and cognition
  12. ZijlstraF. Efficiency in work behaviour: a design approach for modern tools (doctoral dissertation). Retrieved from Repository TU Delft (90-6275-918-1)1993

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Metadata

Authors
Longo, L., Wickens, C. D., Hancock, G., & Hancock, P. A.
Affiliations
  • Technological University Dublin (IE)
  • Colorado State University (US)
  • University of Central Florida (US)
Corresponding author
Longo, Luca
ORCID
Venue
Frontiers in Psychology
Publisher
Frontiers Media SA
Published
2022-06-02
Volume
13
Pages
883321-883321
ISSN
1664-1078 (ISSN-L)
DOI
10.3389/fpsyg.2022.883321
PMC
PMC9201728
OpenAlex
W4281746451
Cited by
222
References
222
Citations by year
2026: 53 · 2025: 72 · 2024: 67 · 2023: 28 · 2022: 2
FWCI
6.33
Type
journal article
Language
en
Update notices
corrigendum (2022-07-26)
Open access
Licence
Locations
  • Frontiers in Psychology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Arrow - TU Dublin (Technological University Dublin) (submittedVersion, cc-by-nc-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion)
Topics
  • Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
  • Social Sciences › Human Factors and Ergonomics › Ergonomics and Human Factors
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Keywords
mental workload, operational definitions, mental workload assessment, self-report measures, physiological indices, neuroergonomics, human performance prediction

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