@article{ref1,
title="Validating the effectiveness of a self-report tool to predict unsafe behavior of industrial workers: a QEEG analysis",
journal="International journal of occupational safety and ergonomics",
year="2024",
author="Shakerian, Mahnaz and Nami, Mohammad and Jahangiri, Mehdi and Hasanzadeh, Jafar and Alimohammadlou, Moslem and Choobineh, Alireza",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="OBJECTIVEs. Unsafe behavior (UB) is defined as the likelihood of intentionally or unintentionally deviating from pre-defined plans. This study aims to investigate the validation of a self-report tool for measuring workers' cognitive-based UB using quantitative electroencephalography (QEEG). <br><br>METHODS. The cognitive-based unsafe behavior questionnaire (CUBQ) was completed by 632 front-line workers in a manufacturing industry to identify differences in the backgrounds of the subjects regarding UBs. Two groups were then selected as extreme groups and QEEG was conducted based on the international 10-20 electrode placement. <br><br>RESULTS. The mean values of absolute power (AP), alpha/beta ratio (ABR) and alpha/gamma ratio (AGR) from brain oscillations in different regions of the cortex were significantly different between the studied groups (p < 0.05). Additionally, these values were found to be significantly correlated with slips, lapses and mistakes, as measured by certain scales of the CUBQ (p < 0.05). <br><br>CONCLUSIONS. The findings of this study indicated differences in brain oscillation activities among industrial workers with different UB backgrounds. These results confirm the effectiveness of CUBQ as a proactive tool for safety practitioners to predict industrial workers' UBs.<p /> <p>Language: en</p>",
language="en",
issn="1080-3548",
doi="10.1080/10803548.2024.2330249",
url="http://dx.doi.org/10.1080/10803548.2024.2330249"
}