بررسي باركاري و ارتباط آن با خستگي در ميان لكوموتيورانان بخش نيروي كشش راه آهن جمهوري اسلامي ايران

Investigating workload and its relationship with fatigue among train drivers in Keshesh section of Iranian Railway Company

مقدمه: ازجمله مشاغل پرمسووليت در صنعت?ريلي، شغل لكوموتيوراني است. لكوموتيوران نيازمند عملكردهاي شناختي متعددي از قبيل توجه مستمر، شناسايي اشيا ، حافظه، برنامه?ريزي و تصميم?گيري مي?باشد. سطوح بالاي خستگي ازجمله علل ايجاد حوادث توسط لكوموتيورانان است. عوامل متعددي بر افزايش خستگي لكوموتيورانان اثرگذار مي?باشد كه باركاري از مهم?ترين اين فاكتورها است. لذا هدف از مطالعه حاضر، بررسي باركاري لكوموتيورانان قطارهاي مسافري و اثر آن بر خستگي اين افراد مي?باشد. روش كار: پژوهش حاضر يك مطالعه توصيفي?تحليلي مي?باشد كه در ميان 100 نفر از لكوموتيورانان نيروي كشش راه?آهن كه با استفاده از نمونه?گيري تصادفي انتخاب شدند، صورت?گرفت. به منظور ارزيابي وضعيت باركاري و خستگي لكوموتيورانان به ترتيب از پرسشنامه NASA-TLX و مقياس خستگي Samn-Perelli استفاده?گرديد. تجزيه و تحليل آماري داده?ها با استفاده از تست?هاي Paired t-test و Spearman صورت گرفت. يافته ها: نتايج به‌دست?آمده نشان داد كه لكوموتيورانان، دو بعد تلاش و كوشش و بارذهني خود را به ترتيب با ميانگين?هاي 22/74 و 31/73 به‌عنوان مهم?ترين ابعاد باركاري ارزيابي كرده?اند. بين باركاري و ميزان خستگي قبل از حركت و نيم ساعت قبل از رسيدن به مقصد (مربوط به مسير رفت) ارتباط معني?داري به‌دست نيامد (05/0

Introduction: Train driving is a high responsibility job in railway industry. Train drivers need different cognitive functions such as vigilance, object detection, memory, planning, decision-making. High level of fatigue is one of the caused factor of accidents among train drivers. Numerous factors can impact train drivers’ fatigue but high level of workload is a key factor. Therefore, the aim of the present study was to investigate workload and its relationship with fatigue among train drivers in Keshesh section of Iranian Railway Company. . Material and Method: This descriptive analytical study was done among 100 train drivers in Keshesh section of Iranian Railway industry. They were selected by simple random sampling. The NASA-TLX workload scale and Samn-Perelli fatigue scale were respectively used to investigate workload and fatigue. Data were analyzed by Paired t-test and Spearman correlation coefficient. . Result: According to the NASA-TLX results, effort and mental workload with the mean score of 74/22 and 73/31 were respectively the most important attributes of workload among train drivers. No significant relationship was observed between workload and level of fatigue before departure and half an hour before reaching the destination station (P > 0.05). However, the relationship between of workload and level of fatigue half an hour before the end of shift (on the way back to the origin station) was statistically significant (P=0.048) among the sample population. . Conclusion: Effort and mental workload were the most important attributes of workload among train drivers. By focusing on these two variables and adopting fatigue management programs, fatigue and workload can be controlled and the efficiency of the whole system can be enhanced accordingly.