Cited by 948Human-Automation Interaction and SafetyErgonomics and Human FactorsUsability and User Interface Design

The DOI matches its Crossref record; 406 of the 406 references it cites were found in a registry or an index; none of the 95 sources its claims cite is checked for support yet.

State of science: mental workload in ergonomics

Open access

Abstract

Mental workload (MWL) is one of the most widely used concepts in ergonomics and human factors and represents a topic of increasing importance. Since modern technology in many working environments imposes ever more cognitive demands upon operators while physical demands diminish, understanding how MWL impinges on performance is increasingly critical. Yet, MWL is also one of the most nebulous concepts, with numerous definitions and dimensions associated with it. Moreover, MWL research has had a tendency to focus on complex, often safety-critical systems (e.g. transport, process control). Here we provide a general overview of the current state of affairs regarding the understanding, measurement and application of MWL in the design of complex systems over the last three decades. We conclude by discussing contemporary challenges for applied research, such as the interaction between cognitive workload and physical workload, and the quantification of workload 'redlines' which specify when operators are approaching or exceeding their performance tolerances.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This state-of-science review traces mental workload (MWL) research in ergonomics from definition and measurement to application, arguing that MWL remains a multidimensional and still-nebulous construct. It highlights transport as the dominant applied domain and identifies neuroergonomics and the quantification of workload “redlines” as key future challenges.

Key findings

  • Ergo-Abs searches show MWL references rising from 58 hits in the 1980s to 140 in the 1990s and 191 in the 2000s; the 2000s decade-on-decade increase was 36% for “mental workload” versus 17% for “physical workload” and “workload.”
  • Applied MWL publications increased as a proportion of the field: 26% in the 1980s, 39% in the 1990s, and 46% in the 2000s; transport dominated, especially driving (40 total papers, including 28 in the 2000s), aviation (19), ATC (17), and rail (12).
  • Both overload and underload can degrade performance, with an optimum range of MWL; measurement typically uses primary/secondary task performance, subjective reports (e.g. NASA-TLX, SWAT, RSME), and physiological metrics (e.g. heart rate, heart rate variability, EEG, facial muscle activity, NIRS).
  • The paper reports approximate redlines such as working memory at roughly seven chunks, relational complexity at roughly three interacting relations, tracking bandwidth at roughly one cycle per second, and timeline analysis TR/TA, with Parks and Boucek suggesting errors begin around the 80% level rather than 100%.

Methods

  • Narrative state-of-science review, not an empirical study; no primary data collection or participants are reported.
  • Uses decade-by-decade searches of the Ergo-Abs database for “mental workload,” “physical workload,” and “workload,” plus a title-field search of “mental workload” categorized into broad application areas.
  • Synthesizes conceptual, measurement, and application literature across the 1980s, 1990s, and 2000s, with discussion of current and future challenges.

Limitations

  • Stated: the applied review “is not intended to be an exhaustive review”; application categorization was selective and based on the most obvious theme from title and abstract; database coverage grew over time, partly inflating later counts.
  • Stated: MWL remains “just as nebulous a concept today as it did three decades ago”; research has failed to provide absolute limits on human performance, and underload lacks a widely accepted theory, making its redline especially elusive.
  • Evident from the text: the review is narrative and selective rather than systematic, and the authors note that dissociation among workload measures complicates interpretation and that absolute workload prediction remains difficult.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1080/00140139.2014.956151

Cites

406 of 406 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

71 Not checked yet · 57 No basis given · 28 Own interpretation · 11 Own result

Verify all 95 references — free account

Show all 69 claims

  • Probably not a substantial claim. 68
  • It may state two separate claims as one. 48
98 of 98
  • The paper relies on this without support.

    The Ergo-Abs database search results are representative of the broader MWL literature.

    “A search of Ergo-Abs (the Ergonomics Abstracts online database, which covers international books, journals and conference proceedings across a variety of ergonomics-related fields) over the last three decades (which reflects the vast majority of sources indexed in the database) shows that references to 'mental workload' have increased more than threefold since the 1980s (see Table 1).”
  • The paper relies on this without support.

    The categorisation of publications into application areas based on title and abstract is valid for identifying thematic trends.

    “There is an element of selectivity in this: the categorisation process being necessarily one of independent determination and based on the most obvious theme from the title and abstract of the publication and where the application was the main focus of the paper (as opposed to focusing on a workload metric albeit in a particular application).”
  • The paper relies on this without support.

    The relative increase in MWL hits over comparator terms indicates a genuine increase in prominence rather than only database coverage.

    “This increase no doubt partly reflects the growing coverage of the database in more recent years, as evidenced by equivalent searches for 'physical workload' and 'workload'. Nevertheless, the relative decade-on-decade increase in hits for MWL in the 2000s suggests a more recent prominence over the comparator terms - 36% for 'mental workload' against 17% for 'physical workload' and 'workload'.”
  • The authors state this as an assumption.

    Timeline analysis assumes that workload is proportional to the ratio of the time occupied performing tasks to total time available.

    “In a simplified but readily usable version, it assumes that workload is proportional to the ratio of the time occupied performing tasks to total time available.”
4 of 4

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Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

1 of 1

Citations

Cites

Research works printed but not linked: 21

  1. Aoyama, T., and M.Umemura. 1991. “An Examination of the Mental Workload of Design Work in Offices.” In Towards Human Work: Solutions to Problems in Occupational Health and Safety, edited by M.Kumashiro, and E. D.Megaw, 243–249. London: Taylor & Francis.
  2. Bainbridge L., 1974, Le Travail Humain, 37, 279
  3. Basahel, A. M., M. S.Young, and M.Ajovalasit. 2010. “Effects of Interaction between Physical and Mental Workload on Human Performance.” In Contemporary Ergonomics and Human Factors 2010, edited by M.Anderson, 598–601. London: Taylor & Francis.
  4. 2014, InProceedings of the HFES International Annual Meeting
  5. 2010, Chap. 5.7 in NASA Human Integration Design Handbook (HIDH), 190
  6. Hayashi Y., 1988, Journal of Science of Labour, 64, 257
  7. Hayashi Y., 1987, Journal of Science of Labour, 63, 351
  8. Jarvenpaa, E.1990. “Mental Workload in Different Phases of the Implementation of New Technology: The Implementation of Office Automation as an Example.” In Proceedings of the International Ergonomics Association Conference on Human Factors in Design for Manufacturability and Process Planning , 159–163.
  9. Kuriyagawa, Y., and I. Kageyama. 2003. “A Study on the Evaluation Model of Mental Workload for Drivers.” In Ergonomics in the Digital Age. Proceedings of the XVth Triennial Congress of the International Ergonomics Association and the 7th Joint Conference of the Ergonomics Society of Korea and the Japan Ergonomics Society .
  10. Lenior, T. M. J., and M. P.Gobel. 1997. “Predicting Mental Workload for Train Traffic Control Tasks.” In From Experience to Innovation - IEA ’97. Proceedings of the 13th Triennial Congress of the International Ergonomics Association, edited by P.Seppala, T.Luopajarvi, C. H.Nygard, and M.Mattila, 358–360. Finnish Institut.
  11. Loewenthal, A., M.Chignell, and P.Hancock. 1985. “Use of Mental Workload Measures in Interface Design.” In IEEE 1985 Proceedings of the International Conference on Cybernetics and Society, 624–626. New York: IEEE.
  12. Low, I.2003. “Assessment of the Impact on Mental Workload from Advanced Air Traffic Management Systems: A Diagnostic Tool.” In Ergonomics in the Digital Age. Proceedings of the XVth Triennial Congress of the International Ergonomics Association and the 7th Joint Conference of the Ergonomics Society of Korea and the Japan Ergonomics Society .
  13. Pickup, L., J.Wilson, and T.Clarke. 2003. “Mental Workload of the Railway Signaller.” In Contemporary Ergonomics, edited by P. T.McCabe, 397–402. London: Taylor & Francis.
  14. Schlegel, R. E.1993. “Driver Mental Workload.” In Automotive Ergonomics, edited by B.Peacock, and W.Karwowski, 359–382. London: Taylor & Francis.
  15. Wickens, C., T.Bagnall, M.Gosakan, and B.Walters. 2011. “Modeling Single Pilot Control of Multiple UAVs.” In Proceedings of the 16th International Symposium on Aviation Psychology, available in CD-ROM format edited by M.Vidulich, and P.Tsang. Dayton, OH: Wright State University.
  16. Wickens, C. D., and J. G.Hollands. 2000. Engineering Psychology and Human Performance. 3rd ed.Upper Saddle River, NJ: Pearson.
  17. Wilson, J. R., and J. A.Rajan. 1995. “Human-Machine Interfaces for Systems Control.” In Evaluation of Human Work: A Practical Ergonomics Methodology, edited by J. R.Wilson, and E. N.Corlett, 357–405. London: Taylor & Francis.
  18. Young M. S., 1997, International Journal of Cognitive Ergonomics, 1, 325
  19. Young, M., and N.Stanton. 1998. “What's Skill Got to Do with It? Vehicle Automation and Driver Mental Workload.” In Contemporary Ergonomics 1998, edited by M. A.Hanson, 436–440. London: Taylor & Francis.
  20. Young, M. S., and N. A.Stanton. 2005. “Mental workload.” In Handbook of Human Factors and Ergonomics Methods, edited by N. A.Stanton, A.Hedge, K.Brookhuis, E.Salas, and H. W.Hendrick. Chap. 39. London: Taylor & Francis.
  21. Zijlstra, F. R. H.1993. “Efficiency in Work Behavior. A Design Approach for Modern Tools.” PhD diss., Delft University of Technology. Delft: Delft University Press.

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Metadata

Authors
Young, M. S., Brookhuis, K. A., Wickens, C. D., & Hancock, P. A.
Affiliations
  • Brunel University of London (GB)
  • University of Groningen (NL)
  • University of Central Florida (US)
Corresponding author
Young, Mark S.
Venue
Ergonomics
Published
2014-12-02
Volume
58
Issue
1
Pages
1-17
ISSN
  • 0014-0139 (ISSN-L)
  • 1366-5847
OpenAlex
W2076883103
Cited by
948
References
406
Citations by year
2026: 104 · 2025: 117 · 2024: 85 · 2023: 101 · 2022: 98 · 2021: 102 · 2020: 85 · 2019: 84 · 2018: 65 · 2017: 50 · 2016: 35 · 2015: 19
FWCI
4.95
Type
journal article
Language
en
Open access
Locations
  • Ergonomics (publishedVersion)
  • PubMed (publishedVersion)
  • Journal of International Crisis and Risk Communication Research (submittedVersion)
  • ePrints Soton (University of Southampton) (submittedVersion)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
Funders
National Aeronautics and Space Administration
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 › Human-Computer Interaction › Usability and User Interface Design
Keywords
mental workload, workload measurement, operator performance, complex system design, physical workload, safety-critical systems, human factors
MeSH terms
Cognition, Humans, Ergonomics, Task Performance and Analysis, Workload

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