Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/47600
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dc.contributor.authorGEURTS, Eva-
dc.contributor.authorMICHIELS, Anouk-
dc.contributor.authorROVELO RUIZ, Gustavo-
dc.date.accessioned2025-10-27T09:11:08Z-
dc.date.available2025-10-27T09:11:08Z-
dc.date.issued2025-
dc.date.submitted2025-10-06T14:34:36Z-
dc.identifier.citationIfac-papersonline (kidlington. Online), 59 (10) , p. 981 -986-
dc.identifier.urihttp://hdl.handle.net/1942/47600-
dc.description.abstractRecognizing Industry 5.0's emphasis on human-centric work, we explored the use of established questionnaires, such as NASA-TLX, SWAT, and IMI, to evaluate well-being in assembly-like tasks. While expensive and invasive sensors can provide detailed insights, our aim was to determine how effectively existing, accessible questionnaires can detect factors like boredom, cognitive load, temporal load, and frustration. This information serves as a relevant contextual resource, enabling manufacturing companies to identify the root causes of well-being threats on the shopfloor, particularly those linked to specific tasks. The results demonstrate that these questionnaires can capture key well-being dimensions, making them valuable for industrial settings. This supports their potential as practical, non-invasive tools for monitoring work-related well-being, aligning with the goals of a human-centered industrial future.-
dc.description.sponsorshipThisresearchwassupportedbyFlandersMake,thestrategicresearchcentreforthemanufacturingindustry, inthe projectWELLFICIENCY.-
dc.language.isoen-
dc.publisherElsevier-
dc.rights2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)-
dc.subject.otherIndustry 40-
dc.subject.otherIndustry 50-
dc.subject.otherWell-being-
dc.subject.otherManufacturing industry-
dc.subject.otherAssembly-
dc.titleEvaluating the Effectiveness of Subjective Questionnaires for Assessing Cognitive Well-Being in Assembly Tasks-
dc.typeJournal Contribution-
local.bibliographicCitation.conferencedateJune 30-July 3-
local.bibliographicCitation.conferencename11th IFAC Conference on Manufacturing Modelling, Management and Control-
local.bibliographicCitation.conferenceplaceTrondheim-
dc.identifier.epage986-
dc.identifier.issue10-
dc.identifier.spage981-
dc.identifier.volume59-
local.bibliographicCitation.jcatA1-
dc.relation.referencesAndr´as, S., Sipos, K., and So´os, A. (2013). Which is harder?-Classification of Happy Cube puzzles. :. Antonaci, F.G., Olivetti, E.C., Marcolin, F., Castiblanco Jimenez, I.A., Eynard, B., Vezzetti, E., and Moos, S. (2024). Workplace well-being in industry 5.0: A worker-centered systematic review. Sensors, 24(17), 5473. Caine, K. (2016). Local standards for sample size at chi. In Proceedings of the 2016 CHI conference on human factors in computing systems, 981–992. Durantin, G., Gagnon, J.F., Tremblay, S., and Dehais, F. (2014). Using near infrared spectroscopy and heart rate variability to detect mental overload. Behavioural brain research, 259, 16–23. Hart, S.G. (2006). Nasa-task load index (nasa-tlx); 20 years later. In Proceedings of the human factors and ergonomics society annual meeting, volume 50, 904–908. Sage publications Sage CA: Los Angeles, CA. Holden, R.J., McDougald Scott, A.M., Hoonakker, P.L., Hundt, A.S., and Carayon, P. (2015). Data collection challenges in community settings: insights from two field studies of patients with chronic disease. Quality of Life Research, 24, 1043–1055. Iriondo Pascual, A., Smedberg, H., H¨ogberg, D., Syberfeldt, A., and L¨amkull, D. (2022). Enabling knowledge discovery in multi-objective optimizations of worker well-being and productivity. Sustainability, 14(9), 4894. Li, C., Lin, S.H., and Chib, A. (2021). The state of wearable health technologies: a transdisciplinary literature review. Mobile Media & Communication, 9(2), 353–376. McAuley, E., Duncan, T., and Tammen, V.V. (1989). Psychometric properties of the intrinsic motivation inventory in a competitive sport setting: a confirmatory factor analysis. Research Quarterly for Exercise and Sport, 60(1), 48–58. doi:10.1080/02701367.1989.10607413. Mu˜noz, S., Iglesias, C.A., Mayora, O., and Osmani, V. ´ (2022). Prediction of stress levels in the workplace using surrounding stress. Information Processing & Management, 59(6), 103064. Park, S., Constantinides, M., Aiello, L.M., Quercia, D., and Van Gent, P. (2020). Wellbeat: A framework for tracking daily well-being using smartwatches. IEEE Internet Computing, 24(5), 10–17. Reid, G.B. and Nygren, T.E. (1988). The subjective workload assessment technique: A scaling procedure for measuring mental workload. In P.A. Hancock and N. Meshkati (eds.), Human Mental Workload, volume 52 of Advances in Psychology, 185–218. North-Holland. doi: https://doi.org/10.1016/S0166-4115(08)62387-0. Setz, C., Arnrich, B., Schumm, J., La Marca, R., Tr¨oster, G., and Ehlert, U. (2010). Discriminating stress from cognitive load using a wearable eda device. IEEE Transactions on Information Technology in Biomedicine, 14(2), 410–417. doi:10.1109/TITB.2009.2036164. Thorvald, P., Lindblom, J., and Andreasson, R. (2019). On the development of a method for cognitive load assessment in manufacturing. Robotics and Computer-Integrated Manufacturing, 59, 252–266. doi: https://doi.org/10.1016/j.rcim.2019.04.012. van Steenbergen, H., Band, G.P., and Hommel, B. (2015). Does conflict help or hurt cognitive control? initial evidence for an inverted u-shape relationship between perceived task difficulty and conflict adaptation. Frontiers in Psychology, 6, 974. Yang, J., Liu, Y., and Morgan, P.L. (2024). Humanmachine interaction towards industry 5.0: Humancentric smart manufacturing. Digital Engineering, 100013.-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.identifier.doi10.1016/j.ifacol.2025.09.166-
local.provider.typePdf-
local.uhasselt.internationalno-
item.contributorGEURTS, Eva-
item.contributorMICHIELS, Anouk-
item.contributorROVELO RUIZ, Gustavo-
item.fullcitationGEURTS, Eva; MICHIELS, Anouk & ROVELO RUIZ, Gustavo (2025) Evaluating the Effectiveness of Subjective Questionnaires for Assessing Cognitive Well-Being in Assembly Tasks. In: Ifac-papersonline (kidlington. Online), 59 (10) , p. 981 -986.-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
crisitem.journal.issn2405-8963-
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