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Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not?

Author

Listed:
  • Fangyuan Tian

    (Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Hongxia Li

    (Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
    School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Shuicheng Tian

    (Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Chenning Tian

    (Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Jiang Shao

    (School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

(1) Background: As a world-recognized high-risk occupation, coal mine workers need various cognitive functions to process the surrounding information to cope with a large number of perceived hazards or risks. Therefore, it is necessary to explore the connection between coal mine workers’ neural activity and unsafe behavior from the perspective of cognitive neuroscience. This study explored the functional brain connectivity of coal mine workers who have engaged in unsafe behaviors (EUB) and those who have not (NUB). (2) Methods: Based on functional near-infrared spectroscopy (fNIRS), a total of 106 workers from the Hongliulin coal mine of Shaanxi North Mining Group, one of the largest modern coal mines in China, completed the test. Pearson’s Correlation Coefficient ( COR ) analysis, brain network analysis, and two-sample t -test were used to investigate the difference in brain functional connectivity between the two groups. (3) Results: The results showed that there were significant differences in functional brain connectivity between EUB and NUB among the frontopolar area ( p = 0.002325), orbitofrontal area ( p = 0.02102), and pars triangularis Broca’s area ( p = 0.02888). Small-world properties existed in the brain networks of both groups, and the dorsolateral prefrontal cortex had significant differences in clustering coefficient ( p = 0.0004), nodal efficiency ( p = 0.0384), and nodal local efficiency ( p = 0.0004). (4) Conclusions: This study is the first application of fNIRS to the field of coal mine safety. The fNIRS brain functional connectivity analysis is a feasible method to investigate the neuropsychological mechanism of unsafe behavior in coal mine workers in the view of brain science.

Suggested Citation

  • Fangyuan Tian & Hongxia Li & Shuicheng Tian & Chenning Tian & Jiang Shao, 2022. "Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not?," IJERPH, MDPI, vol. 19(1), pages 1-21, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:1:p:509-:d:716867
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    References listed on IDEAS

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    1. Tong, Ruipeng & Yang, Xiaoyi & Li, Hongwei & Li, Jianfei, 2019. "Dual process management of coal miners’ unsafe behaviour in the Chinese context: Evidence from a meta-analysis and inspired by the JD-R model," Resources Policy, Elsevier, vol. 62(C), pages 205-217.
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. Kevin Cyle Phillips & Derek Verbrigghe & Alex Gabe & Brittany Jauquet & Claire Eischer & Tejin Yoon, 2020. "The Influence of Thermal Alterations on Prefrontal Cortex Activation and Neuromuscular Function during a Fatiguing Task," IJERPH, MDPI, vol. 17(19), pages 1-17, October.
    4. Qiao, Wanguan & Liu, Quanlong & Li, Xinchun & Luo, Xixi & Wan, YuLong, 2018. "Using data mining techniques to analyze the influencing factor of unsafe behaviors in Chinese underground coal mines," Resources Policy, Elsevier, vol. 59(C), pages 210-216.
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    Cited by:

    1. Yu, Kai & Zhou, Lujie & Jin, Weiqiang & Chen, Yu, 2024. "Prediction of coal mine risk based on BN-ELM: Gas risk early warning including human factors," Resources Policy, Elsevier, vol. 98(C).
    2. Fangyuan Tian & Hongxia Li & Shuicheng Tian & Jiang Shao & Chenning Tian, 2022. "Effect of Shift Work on Cognitive Function in Chinese Coal Mine Workers: A Resting-State fNIRS Study," IJERPH, MDPI, vol. 19(7), pages 1-21, April.

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