Zhang Peiwen, Zhao Wenke, Shi Lan, Wang Yu, Sun Hong, Sun Zhen
School of Economics and Management, Civil Aviation Flight University of China, Guanghan, China.
School of Statistics, Southwest University of Finance and Economics, Chengdu, China.
Front Psychol. 2022 May 11;13:865342. doi: 10.3389/fpsyg.2022.865342. eCollection 2022.
This paper uses the Multidimensional Fatigue Inventory (MFI-16) to investigate the fatigue status of pilots, and the reliability and validity of the scale are tested by Cronbach's α and exploratory factor analysis. The founding shows that mild fatigue and above accounted for 67.7%. For further quantify the impact of different flights on pilots' fatigue, research improves the fatigue coefficient model based on the results of pilot fatigue feeling questionnaire. Combined with multifactor analysis of variance and multiple linear regression, it is found that the independent variables have different and positive effects on the dependent variables, and there is no multicollinearity. Through the actual test, its accuracy is improved by 16.7% compared with the original model.
本文采用多维疲劳量表（MFI - 16）对飞行员的疲劳状况进行调查，并通过Cronbach's α系数和探索性因素分析检验量表的信效度。结果显示，轻度及以上疲劳占67.7%。为进一步量化不同飞行任务对飞行员疲劳的影响，研究基于飞行员疲劳感受问卷结果改进了疲劳系数模型。结合多因素方差分析和多元线性回归发现，自变量对因变量有不同程度的正向影响，且不存在多重共线性。通过实际测试，其准确率较原模型提高了16.7%。
