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Validating the Effectiveness of a Self-Report Tool to Predict Unsafe Behavior of Industrial Workers: A Qeeg Analysis Publisher Pubmed



Shakerian M1, 2 ; Nami M3, 4 ; Jahangiri M5 ; Hasanzadeh J5 ; Alimohammadlou M6 ; Choobineh A1
Authors
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Authors Affiliations
  1. 1. Research Center for Health Sciences, Shiraz University of Medical Sciences, Iran
  2. 2. Department of Occupational Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
  3. 3. Department of Social Sciences, Canadian University Dubai, United Arab Emirates
  4. 4. Brain, Cognition, and Behavior Unit, BrainHub Academy, United Arab Emirates
  5. 5. School of Health, Shiraz University of Medical Sciences, Iran
  6. 6. Faculty of Economic, Management and Social Science, Shiraz University, Iran

Source: International Journal of Occupational Safety and Ergonomics Published:2024


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). 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. 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). 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. © 2024 Central Institute for Labour Protection–National Research Institute (CIOP-PIB).