Chapter
Nov 9, 2020
Construction Research Congress 2020

Influence of Critical Variables on Prefrontal Cortex Activity in Hazard Search

Publication: Construction Research Congress 2020: Safety, Workforce, and Education

ABSTRACT

The prefrontal cortex is considered to play an important role in the safety inspection. Little, yet, is known about individuals’ brain activity and its related factors during the hazard search process. This research aims to explore the influence of related variables on the prefrontal cortex activity. Forty-seven participants performed the hazard search task in a civil engineering laboratory presenting the common construction safety hazards, including fall, strike-by, fire protection, and poor housekeeping. A wearable near-infrared spectroscopy (NIRS) system was used to measure their hemodynamic responses in the prefrontal cortex. Site familiarity, safety knowledge, and risk tolerance were investigated as predictors of the oxygenated hemoglobin responses in the prefrontal cortex through hierarchical regression modeling. We found that the explanatory variables distinguished significantly (p<0.05) the concentration changes of oxygenated hemoglobin (ΔO2Hb) in the medial prefrontal cortex during hazard search. Site familiarity accounted for 16.6% of the variance of ΔO2Hb in the medial prefrontal cortex and made the largest contribution to it. The findings lay a foundation for further exploring individuals’ brain activity during hazard recognition and finding out the associate influence variables. That will serve safety managers’ purpose of figuring out effective measures for improving the employees’ safety inspection performance.

Get full access to this article

View all available purchase options and get full access to this chapter.

REFERENCES

Ali, A., Kamaruzzaman, S., and Sing, G. (2010). A Study on causes of accident and prevention in Malaysian construction industry. Editorial Board/Sidang Editor.
Bonetti, L. V., Hassan, S. A., Lau, S.-T., et al. (2018). Oxyhemoglobin changes in the prefrontal cortex in response to cognitive tasks: A systematic review. International Journal of Neuroscience, 1-9.
Buckner, R. L., and Krienen, F. M. (2013). The evolution of distributed association networks in the human brain. Trends in Cognitive Sciences, 17(12), 648-665. https://doi.org/10.1016/j.tics.2013.09.017
Causse, M., Peysakhovich, V., and Mandrick, K. (2017). Eliciting sustained mental effort using the Toulouse N-back Task: prefrontal cortex and pupillary responses. In Advances in Neuroergonomics and Cognitive Engineering(pp. 185-193): Springer.
Chi, C.-F., Chang, T.-C., and Ting, H.-I. (2005). Accident patterns and prevention measures for fatal occupational falls in the construction industry. Applied ergonomics, 36(4), 391-400.
Delpy, D. T., Cope, M., van der Zee, P., et al. (1988). Estimation of optical pathlength through tissue from direct time of flight measurement. Physics in Medicine & Biology, 33(12), 1433.
Dzeng, R.-J., Lin, C.-T., and Fang, Y.-C. (2016). Using eye-tracker to compare search patterns between experienced and novice workers for site hazard identification. Safety Science, 82, 56-67.
Eiter, B. M., Bellanca, J. L., Helfrich, W., et al. (2017). Recognizing mine site hazards: identifying differences in hazard recognition ability for experienced and new mineworkers. Paper presented at the International Conference on Applied Human Factors and Ergonomics.
Golovina, O., Teizer, J., and Pradhananga, N. (2016). Heat map generation for predictive safety planning: Preventing struck-by and near miss interactions between workers-on-foot and construction equipment. Automation in construction, 71, 99-115.
Haluik, A. (2016, 6-11 March 2016). Risk perception and decision making in hazard analysis: improving safety for the next generation of electrical workers. Paper presented at the 2016 IEEE IAS Electrical Safety Workshop (ESW).
Haslam, R. A., Hide, S. A., Gibb, A. G., et al. (2005). Contributing factors in construction accidents. Applied ergonomics, 36(4), 401-415.
Heeger, D. J., and Ress, D. (2002). What does fMRI tell us about neuronal activity? Nature Reviews Neuroscience, 3(2), 142.
Hoshi, Y., Kobayashi, N., and Tamura, M. (2001). Interpretation of near-infrared spectroscopy signals: a study with a newly developed perfused rat brain model. Journal of applied physiology, 90(5), 1657-1662.
Hosseini, S. H., Bruno, J. L., Baker, J. M., et al. (2017). Neural, physiological, and behavioral correlates of visuomotor cognitive load. Scientific Reports, 7(1), 8866.
Hwang, H.-J., Lim, J.-H., Kim, D.-W., et al. (2014). Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces. Journal of Biomedical Optics, 19(7), 077005.
Jiang, L., Yu, G., Li, Y., et al. (2010). Perceived colleagues’ safety knowledge/behavior and safety performance: Safety climate as a moderator in a multilevel study. Accident Analysis & Prevention, 42(5), 1468-1476. https://doi.org/10.1016/j.aap.2009.08.017
Kaskutas, V., Dale, A. M., Lipscomb, H., et al. (2013). Fall prevention and safety communication training for foremen: Report of a pilot project designed to improve residential construction safety. Journal of Safety Research, 44, 111-118. https://doi.org/10.1016/j.jsr.2012.08.020
Kowalski-Trakofler, K. M., and Barrett, E. A. (2003). The concept of degraded images applied to hazard recognition training in mining for reduction of lost-time injuries. Journal of Safety Research, 34(5), 515-525.
Leff, D. R., Orihuela-Espina, F., Elwell, C. E., et al. (2011). Assessment of the cerebral cortex during motor task behaviours in adults: a systematic review of functional near infrared spectroscopy (fNIRS) studies. Neuroimage, 54(4), 2922-2936.
Li, R. Y. M., Chau, K. W., Lu, W., et al. (2019). A Research Agenda for Neuroactivities in Construction Safety Knowledge Sharing, Hazard Identification and Decision Making. Paper presented at the International Conference on Applied Human Factors and Ergonomics.
Liao, P.-C., Sun, X., Liu, M., et al. (2017). Influence of visual clutter on the effect of navigated safety inspection: a case study on elevator installation. International journal of occupational safety and ergonomics, 1-15.
Menzel, N. N., and Shrestha, P. P. (2012). Social marketing to plan a fall prevention program for latino construction workers. American Journal of Industrial Medicine, 55(8), 729-735.
Mohammed, S. H., Habtewold, T. D., Tegegne, B. S., et al. (2019). Dietary and non-dietary determinants of linear growth status of infants and young children in Ethiopia: Hierarchical regression analysis. PloS one, 14(1), e0209220.
Namian, M., Albert, A., and Feng, J. (2018). Effect of Distraction on Hazard Recognition and Safety Risk Perception. Journal of Construction Engineering and Management, 144(4), 04018008.
Oliva, A., and Torralba, A. (2007). The role of context in object recognition. Trends in Cognitive Sciences, 11(12), 520-527.
Petrocelli, J. V. (2003). Hierarchical multiple regression in counseling research: Common problems and possible remedies. Measurement and evaluation in counseling and development, 36(1), 9-22.
Quaresima, V., Ferrari, M., Torricelli, A., et al. (2005). Bilateral prefrontal cortex oxygenation responses to a verbal fluency task: a multichannel time-resolved near-infrared topography study. Journal of Biomedical Optics, 10(1), 011012.
Radmacher, S. A., and Martin, D. J. (2001). Identifying significant predictors of student evaluations of faculty through hierarchical regression analysis. The Journal of psychology, 135(3), 259-268.
Richter, T. (2006). What is wrong with ANOVA and multiple regression? Analyzing sentence reading times with hierarchical linear models. Discourse processes, 41(3), 221-250.
Scholkmann, F., Kleiser, S., Metz, A. J., et al. (2014). A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage, 85, 6-27.
Shao, B., Hu, Z., Liu, Q., et al. (2019). Fatal accident patterns of building construction activities in China. Safety Science, 111, 253-263. https://doi.org/10.1016/j.ssci.2018.07.019
Shin, J., Kwon, J., Choi, J., et al. (2017). Performance enhancement of a brain-computer interface using high-density multi-distance NIRS. Scientific Reports, 7(1), 16545.
Starkweather, C. K., Gershman, S. J., and Uchida, N. (2018). The Medial Prefrontal Cortex Shapes Dopamine Reward Prediction Errors under State Uncertainty. Neuron, 98(3), 616-629.e616. https://doi.org/10.1016/j.neuron.2018.03.036
Vinodkumar, M. N., and Bhasi, M. (2010). Safety management practices and safety behaviour: Assessing the mediating role of safety knowledge and motivation. Accident Analysis & Prevention, 42(6), 2082-2093. https://doi.org/10.1016/j.aap.2010.06.021
Wang, J., Zou, P. X., and Li, P. P. (2016). Critical factors and paths influencing construction workers’ safety risk tolerances. Accident Analysis & Prevention, 93, 267-279.
Wolf, M., Wolf, U., Toronov, V., et al. (2002). Different Time Evolution of Oxyhemoglobin and Deoxyhemoglobin Concentration Changes in the Visual and Motor Cortices during Functional Stimulation: A Near-Infrared Spectroscopy Study. Neuroimage, 16(3, Part A), 704-712. https://doi.org/10.1006/nimg.2002.1128
Wong, C. H., Chuah, C. Y., Kui, S. B., et al. (2016). The effect of personality traits and demographic characteristics towards risk tolerance and investment decision making. UTAR,
Yoshino, K., Oka, N., Yamamoto, K., et al. (2013). Functional brain imaging using near-infrared spectroscopy during actual driving on an expressway. Frontiers in Human Neuroscience, 7(882).
Zhang, S., Boukamp, F., and Teizer, J. (2015). Ontology-based semantic modeling of construction safety knowledge: Towards automated safety planning for job hazard analysis (JHA). Automation in construction, 52, 29-41. https://doi.org/10.1016/j.autcon.2015.02.005

Information & Authors

Information

Published In

Go to Construction Research Congress 2020
Construction Research Congress 2020: Safety, Workforce, and Education
Pages: 250 - 257
Editors: Mounir El Asmar, Ph.D., Arizona State University, David Grau, Ph.D., Arizona State University, and Pingbo Tang, Ph.D., Arizona State University
ISBN (Online): 978-0-7844-8287-2

History

Published online: Nov 9, 2020
Published in print: Nov 9, 2020

Permissions

Request permissions for this article.

Authors

Affiliations

Qing-Wen Zhang, Ph.D. [email protected]
Dept. of Construction Management, School of Civil Engineering, Tsinghua Univ., Beijing. E-mail: [email protected]
Pin-Chao Liao [email protected]
Associate Professor, Dept. of Construction Management, School of Civil Engineering, Tsinghua Univ., Beijing. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$180.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$180.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share