ArticleHeliyon2022
Cognitive demands and mental workload: A filed study of the mining control room operators.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Leveraging Wearable Sensors in Virtual Reality Driving Simulators: A Review of Techniques and Applications.Sensors (Basel, Switzerland) · 2024Pooled it
- Visual working memory training enhances simulated mine monitoring performance: the modulating role of memory growth potential.Cognitive research: principles and implications · 2026Trial
- High-resolution thermal infrared dataset for airborne person detection in SAR missions.Scientific data · 2026Article
- Classroom-Integrated Kettlebell Training: Effects on Motor Performance, Attention, and Health in Primary School Children.The Journal of school health · 2026Article
- Occupational injuries, mental workload and coping strategies among the nursing workforce in the Eastern Region of Ghana: a multi-centre study.BMC nursing · 2025Article
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Authors and funding
4 authors.
Funding
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Abstract
Cognitive demand and mental workload assessment are essential for the optimal interaction of human-machine systems. The aim of this study was to investigate the cognitive demands and mental workload as well as the relationship between them among the mining control room operators. This cross-sectional study was performed on 63 control room operators of a large mining plant located in Iran. Cognitive demands and mental workload were assessed using cognitive task analysis (CTA) and NASA Task Load Index (NASA-TLX), respectively and the analysis was performed using SPSS version 21. Independent samples T-test, Mann-Whitney U test and multivariate linear regression were used for data analysis. Twelve cognitive demands were extracted after observing the tasks and conducting semi-structured interviews with the control room staff. The mean scores of total cognitive demands and MWL were 6.60 and 72.89, respectively, and these two indicators showed a positive and significant correlation (r = 0.286; P = 0.023). The participants' demographic characteristics such as age, education, and work experience did not affect mental workload, but the two cognitive demands (memory and defect detection) affected MWL. High cognitive demands and mental workload indicate poor interaction between humans and machines. Due to the effect of memory load and defect detection on mental workload, it is recommended to assign cognitive tasks based on memory and defect detection to the machine to reduce the mental workload and improve human-machine interaction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.