Allahyari Teimour, Saraji Gebraeil Nasl, Adl Javad, Hosseini Mostafa, Iravani Mahmood, Younesian Masood, Kass Steven J
Department of Occupational Health, School of Public Health, Medical Sciences/Tehran University, Iran.
Int J Occup Saf Ergon. 2008;14(2):149-58. doi: 10.1080/10803548.2008.11076759.
The impact of a driver's cognitive capability on traffic safety has not been adequately studied. This study examined the relationship between cognitive failures, driving errors and accident data.
Professional drivers from Iran (160 males, ages 18-65) participated in this study. The cognitive failures questionnaire (CFQ) and the driver error questionnaire were administered. The participants were also asked other questions about personal driving information. A principal component analysis with varimax rotation was performed to determine the factor structure of the CFQ. Poisson regression models were developed to predict driving errors and accidents from total CFQ scores and the extracted factors.
Total CFQ scores were associated with driving error rates, but not with accidents. However, the 2 extracted factors suggested an increased effect on accidents and were strongly associated with driving errors.
Although the CFQ was not able to predict driving accidents, it could be used to identify drivers susceptible to driving errors. Further development of a driving-oriented cognitive failure scale is recommended to help identify error prone drivers. Such a scale may be beneficial to licensing authorities or for developing driver selection and training procedures for organizations.
驾驶员的认知能力对交通安全的影响尚未得到充分研究。本研究考察了认知失误、驾驶错误与事故数据之间的关系。
来自伊朗的职业驾驶员(160名男性,年龄在18 - 65岁之间)参与了本研究。采用了认知失误问卷(CFQ)和驾驶错误问卷。还询问了参与者关于个人驾驶信息的其他问题。进行了主成分分析并采用方差最大化旋转来确定CFQ的因子结构。建立了泊松回归模型,以根据CFQ总分和提取的因子预测驾驶错误和事故。
CFQ总分与驾驶错误率相关,但与事故无关。然而,提取的两个因子表明对事故有更大影响,并且与驾驶错误密切相关。
虽然CFQ无法预测驾驶事故,但它可用于识别易发生驾驶错误的驾驶员。建议进一步开发以驾驶为导向的认知失误量表,以帮助识别易出错的驾驶员。这样的量表可能对发证机构有益,或有助于组织制定驾驶员选拔和培训程序。