Correlation of Work Fatigue and Mental Workload in Train Drivers: A Cross-sectional Study

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Hassanzadeh Rangi Narmin; Jalilian Hamed; Farshad Ali Asghar; Khosravi Yahya

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Journal Paper

Paper Information

Journal: JOURNAL OF RESEARCH IN HEALTH SCIENCES (JRHS) Year:2023 | Volume:23 | Issue:4 Page(s): 1-8

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Title

Correlation of Work Fatigue and Mental Workload in Train Drivers: A Cross-sectional Study

Author(s)

Hassanzadeh Rangi Narmin | Jalilian Hamed | Farshad Ali Asghar | Khosravi Yahya | Issue Writer Certificate

Keywords

Work fatigue

Mental workload

Train driver

Metro

Abstract

Background: Evidence suggests that Train drivers experience a high level of fatigue and Mental workload. The present study aimed to assess overall, physical, and mental fatigue levels and their correlations with the Mental workload in the Metro train operation. Study Design: A cross-sectional study. Methods: This study was conducted on all 1194 Train drivers in the Tehran Metro. The Train drivers completed the Samn-Perelli Fatigue Scale and the Fatigue Assessment Scales at the beginning and end of the shift. In addition, they completed the National Aeronautics and Space Administration Task Load Index in the middle and at the end of the shift. Correlation and regression analyses were performed on the data to test the study hypothesis. Results: Overall, physical, and mental fatigue levels increased significantly at the end of the shift compared to the onset of the shift (P<0. 001). The Mental workload and related dimensions were significantly increased at the end of the shift compared to the middle of the shift (P<0. 001). Mental demand was the most important workload problem among the Train drivers. The highest correlation was found between overall workload and time pressure (R=0. 68, P<0. 001). Conclusion: The Mental workload had a significant correlation with Work fatigue in the Train drivers. Control measures should be focused on the Mental workload and related dimensions, especially mental demand and time pressure. Work fatigue, Mental workload, Train driver, Metro

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