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Articles

Validating the effectiveness of a self-report tool to predict unsafe behavior of industrial workers: a QEEG analysis

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References

  • Salmon PM, Hulme A, Walker GH, et al. The big picture on accident causation: a review, synthesis and meta-analysis of AcciMap studies. Saf Sci. 2020;126:104650.
  • Dodoo JE, Al-Samarraie H. Factors leading to unsafe behavior in the twenty first century workplace: a review. Manag Rev Q. 2019;69(4):391–414.
  • Probst TM, Bettac EL, Austin CT. Accident under-reporting in the workplace. In: Burke RJ, Richardsen AM, editors. Increasing occupational health and safety in workplaces. Cheltenham: Edward Elgar; 2019. p. 30–47.
  • Harsini AZ, Ghofranipour F, Sanaeinasab H, et al. Factors associated with unsafe work behaviours in an Iranian petrochemical company: perspectives of workers, supervisors, and safety managers. BMC Public Health. 2020;20(1):1–13.
  • Shappell S, Detwiler C, Holcomb K, et al. Human error and commercial aviation accidents: an analysis using the human factors analysis and classification system. Hum Factors. 2007;49(2):227–242.
  • Hobbs A, Williamson A. Associations between errors and contributing factors in aircraft maintenance. Hum Factors. 2003;45(2):186–201.
  • Kumar P, Gupta S, Agarwal M, et al. Categorization and standardization of accidental risk – criticality levels of human error to develop risk and safety management policy. Saf Sci. 2016;85:88–98.
  • Huang C, Nivolianitou ZS, editors. Risk analysis based on data and crisis response beyond knowledge. In: Proceedings of the 7th International Conference on Risk Analysis and Crisis Response (RACR 2019); October 15-19, 2019; Athens, Greece. CRC Press; 2019 Oct 11.
  • Krallis D, Csontos A. From Risk Perception to Safe Behavio. Australia: Deloite publications; 2015.
  • Wilson-Donnelly KA, Priest HA, Salas E, et al. The impact of organizational practices on safety in manufacturing: a review and reappraisal. Hum Factors Ergon. 2005;15(2):133–176.
  • Shakerian M, Jahangiri M, Alimohammadlou M, et al. Individual cognitive factors affecting unsafe acts among Iranian industrial workers: an integrative meta-synthesis interpretive structural modeling (ISM) approach. Saf Sci. 2019;120:89–98.
  • Chen J, Song X, Lin Z. Revealing the ‘invisible gorilla’ in construction: estimating construction safety through mental workload assessment. Autom Constr. 2016;63:173–183.
  • Shakerian M, Choobineh A, Jahangiri M, et al. Introducing a new model for individual cognitive factors influencing human error based on DEMATEL approach. Iran J Ergon. 2019;6(4):66–74.
  • Pan D, Zhang Y, Li Z, et al. Effects of cognitive characteristics and information format on teleoperation performance: a cognitive fit perspective. Int J Ind Ergon. 2021;84:103157.
  • Li J, Li H, Wang H, et al. Evaluating the impact of mental fatigue on construction equipment operators’ ability to detect hazards using wearable eye-tracking technology. Autom Constr. 2019;105:102835.
  • Horstmann G, Ansorge U. Surprise capture and inattentional blindness. Cogn. 2016;157:237–249.
  • Das S, Maiti J, Krishna O. Assessing mental workload in virtual reality based EOT crane operations: a multi-measure approach. Int J Ind Ergon. 2020;80:103017.
  • Wanyan X, Zhuang D, Lin Y, et al. Influence of mental workload on detecting information varieties revealed by mismatch negativity during flight simulation. Int J Ind Ergon. 2018;64:1–7.
  • Van Benthem K, Herdman CM. A virtual reality cognitive health screening tool for aviation: managing accident risk for older pilots. Int J Ind Ergon. 2021;85:103169.
  • Patton E. When diagnosis does not always mean disability: the challenge of employees with attention deficit hyperactivity disorder (ADHD). J Workp Behav Health. 2009;24(3):326–343.
  • Hess C, Levy B, Hashmi AZ, et al. Subjective versus objective assessment of cognitive functioning in primary care. J Am Board Fam Med. 2020;33(3):417–425.
  • Cheng EW, Ryan N, Kelly S. Exploring the perceived influence of safety management practices on project performance in the construction industry. Saf Sci. 2012;50(2):363–369.
  • Grant A, Cassidy S. Exploring the relationship between psychological flexibility and self-report and task-based measures of cognitive flexibility. J Context Behav Sci. 2021;1:144–150.
  • Kemper P., Geraets SJ, De Bruijne MC. Assessment of situational awareness. Team resources brought in action to enhance patient safety at the ICU. In Abstract proceedings of the 16th EAWOP Congress 2013. Vol. 2013;2013. p. 751–2.
  • Roche AI, Kroska EB, Denburg NL. Acceptance- and mindfulness-based interventions for health behavior change: systematic reviews and meta-analyses. J Context Behav Sci. 2019;13:74–93.
  • Guo F, Li M, Hu M, et al. Distinguishing and quantifying the visual aesthetics of a product: an integrated approach of eye-tracking and EEG. Int J Ind Ergon. 2019;71:47–56.
  • Brazaitis M, Satas A. Regular short-duration breaks do not prevent mental fatigue and decline in cognitive efficiency in healthy young men during an office-like simulated mental working day: an EEG study. Int J Psychophysiol. 2023;188:33–46.
  • Ke J, Zhang M, Luo X, et al. Monitoring distraction of construction workers caused by noise using a wearable electroencephalography (EEG) device. Autom Constr. 2021;125:103598.
  • Bernhardt KA, Poltavski D. Symptoms of convergence and accommodative insufficiency predict engagement and cognitive fatigue during complex task performance with and without automation. Appl Ergon. 2021;90:103152.
  • Berberian B, Somon B, Sahaï A, et al. The out-of-the-loop brain: a neuroergonomic approach of the human automation interaction. Annu Rev Control. 2017;44:303–315.
  • Reiner M, Gelfeld TM. Estimating mental workload through event-related fluctuations of pupil area during a task in a virtual world. Int J Psychophysiol. 2014;93(1):38–44.
  • Garcia S, Nalven M, Ault A, et al. tDCS as a treatment for anxiety and related cognitive deficits. Int J Psychophysiol. 2020;158:172–177.
  • Karlsen HR, Böckelmann I, Thielmann B. Subjective and objective demands on different types of differential stress inventory. Int Arch Occup Environ Health. 2021;94:1–12.
  • Braarud PØ. Investigating the validity of subjective workload rating (NASA TLX) and subjective situation awareness rating (SART) for cognitively complex human–machine work. Int J Ind Ergon. 2021;86:103233.
  • Jeklin AT, Perrotta AS, Davies HW, et al. The association between heart rate variability: reaction time, and indicators of workplace fatigue in wildland firefighters. Int Arch Occup Environ Health. 2021;94:1–9.
  • Yan S, Wei Y, Tran CC. Evaluation and prediction mental workload in user interface of maritime operations using eye response. Int J Ind Ergon. 2019;71:117–127.
  • Cha K-M, Lee H-C. A novel qEEG measure of teamwork for human error analysis: an EEG hyperscanning study. Nucl Eng Technol. 2019;51(3):683–691.
  • Louis CC, Kneip C, Moran TP, et al. Hormonal contraceptive use moderates the association between worry and error-related brain activity. Int J Psychophysiol. 2021;171:48–54.
  • Shi J, Sun Y, Su H, et al. Risk-taking behavior of drilling workers: a study based on the structural equation model. Int J Ind Ergon. 2021;86:103219.
  • Shakerian M, Choobineh A, Jahangiri M, et al. Is ‘invisible gorilla’ self-reportedly measurable? Development and validation of a new questionnaire for measuring cognitive unsafe behaviors of front-line industrial workers. Int J Occup Saf Ergon. 2019;27(3):1–15.
  • Koessler L, Maillard L, Benhadid A, et al. Automated cortical projection of EEG sensors: anatomical correlation via the international 10–10 system. Neuroimage. 2009;46(1):64–72.
  • Jung T-P, Makeig S, Humphries C, et al. Removing electroencephalographic artifacts by blind source separation. Psychophysiol. 2000;37(2):163–178.
  • Wang D, Chen J, Zhao D, et al. Monitoring workers’ attention and vigilance in construction activities through a wireless and wearable electroencephalography system. Autom Constr. 2017;82:122–137.
  • Zhang X, Yan X, Stylli J, et al. Exploring the effects of EEG signals on collision cases happening in the process of young drivers’ braking. Transp Res Part F Traffic Psychol Behav. 2021;80:381–398.
  • Kamzanova AT, Kustubayeva AM, Matthews G. Use of EEG workload indices for diagnostic monitoring of vigilance decrement. Hum. Factors. 2014;56(6):1136–1149.
  • Koehler S, Lauer P, Schreppel T, et al. Increased EEG power density in alpha and theta bands in adult ADHD patients. J Neural Transm. 2009;116(1):97–104.
  • Hobbs A, Williamson A. Unsafe acts and unsafe outcomes in aircraft maintenance. Ergonomics. 2002;45(12):866–882.
  • Saad JF, Kohn MR, Clarke S, et al. Is the theta/beta EEG marker for ADHD inherently flawed? J Atten Disord. 2018;22(9):815–826.
  • Demos JN. Getting started with neurofeedback. New York: W. W. Norton; 2005.
  • Boutros N, Fraenkel L, Feingold A. A four-step approach for developing diagnostic tests in psychiatry: EEG in ADHD as a test case. J Neuropsychiatry Clin Neurosci. 2005;17(4):455–464.
  • Roh S-C, Park E-J, Park Y-C, et al. Quantitative electroencephalography reflects inattention, visual error responses, and reaction times in male patients with attention deficit hyperactivity disorder. Clin Psychopharmacol Neurosci. 2015;13(2):180.
  • Clarke AR, Barry RJ, Johnstone SJ, et al. EEG development in attention deficit hyperactivity disorder: from child to adult. Clin Neurophysiol. 2019;130(8):1256–1262.
  • Clarke AR, Barry RJ, McCarthy R, et al. EEG evidence for a new conceptualisation of attention deficit hyperactivity disorder. Clin Neurophysiol. 2002;113(7):1036–1044.
  • McFerren A, Riddle J, Walker C, et al. Causal role of frontal-midline theta in cognitive effort: a pilot study. J Neurophysiol. 2021;126(4):1221–1233.
  • Wascher E, Rasch B, Sänger J, et al. Frontal theta activity reflects distinct aspects of mental fatigue. Biol Psychol. 2014;96:57–65.
  • Jokisch D, Jensen O. Modulation of gamma and alpha activity during a working memory task engaging the dorsal or ventral stream. J Neurosci. 2007;27(12):3244–3251.
  • Aguirre-Perez DM, Otero-Ojeda GA, Pliego-Rivero FB, et al. Relationship of working memory and EEG to academic performance: a study among high school students. Int J Neurosci. 2007;117(6):869–882.
  • Sowell ER, Thompson PM, Welcome SE, et al. Cortical abnormalities in children and adolescents with attention-deficit hyperactivity disorder. Lancet. 2003;362(9397):1699–1707.
  • Cunningham S, Scerbo MW, Freeman FG. The electrocortical correlates of daydreaming during vigilance tasks. J Ment Imaging. 2000;24:61–72.
  • Zhang T, Shen D, Zheng S, et al. Predicting unsafe behaviors at nuclear power plants: an integration of theory of planned behavior and technology acceptance model. Int J Ind Ergon. 2020;80:103047.
  • Xu R, Luo F, Chen G, et al. Application of HFACS and grounded theory for identifying risk factors of air traffic controllers’ unsafe acts. Int J Ind Ergon. 2021;86:103228.
  • Ghahramani A, Khalkhali HR. Development and validation of a safety climate scale for manufacturing industry. Saf Health Work. 2015;6(2):97–103.
  • Cabral J, Kringelbach ML, Deco G. Exploring the network dynamics underlying brain activity during rest. Prog Neurobiol. 2014;114:102–131.

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