McCartt A T, Rohrbaugh J W, Hammer M C, Fuller S Z
Institute for Traffic Safety Management and Research, University at Albany, State University of New York, 12205-2604, USA.
Accid Anal Prev. 2000 Jul;32(4):493-504. doi: 10.1016/s0001-4575(99)00067-6.
Data on the prevalence and hypothesized predictors of falling asleep while driving were gathered through face-to-face interviews with 593 long-distance truck drivers randomly selected at public and private rest areas and routine roadside truck safety inspections. Hypothesized predictor variables related to drivers' typical work and rest patterns, extent of daytime and night-time drowsiness, symptoms of sleep disorder, measures of driving exposure, and demographic characteristics. A sizeable proportion of long-distance truck drivers reported falling asleep at the wheel of the truck: 47.1% of the survey respondents had ever fallen asleep at the wheel of a truck, and 25.4% had fallen asleep at the wheel in the past year. Factor analysis reduced the large set of predictors to six underlying, independent factors: greater daytime sleepiness; more arduous schedules, with more hours of work and fewer hours off-duty; older, more experienced drivers; shorter, poorer sleep on road; symptoms of sleep disorder; and greater tendency to night-time drowsy driving. Based on multivariate logistic regression, all six factors were predictive of self-reported falling asleep at the wheel. Falling asleep was also associated with not having been alerted by driving over shoulder rumble strips. The results suggest that countermeasures that limit drivers' work hours and enable drivers to get adequate rest and that identify drivers with sleep disorders are appropriate methods to reduce sleepiness-related driving by truck drivers.
通过在公共和私人休息区对593名随机挑选的长途卡车司机进行面对面访谈，以及在路边进行常规卡车安全检查，收集了有关驾车时入睡的患病率及假设预测因素的数据。假设的预测变量涉及司机的典型工作和休息模式、白天和夜间嗜睡程度、睡眠障碍症状、驾驶时长测量以及人口统计学特征。相当大比例的长途卡车司机报告称曾在驾驶卡车时睡着：47.1%的受访者曾在驾驶卡车时睡着，25.4%在过去一年中曾在驾驶时睡着。因子分析将大量预测因素归纳为六个潜在的独立因素：白天嗜睡程度更高；日程安排更繁重，工作时间更长，休息时间更少；年龄较大、经验更丰富的司机；在路上睡眠时间更短、质量更差；睡眠障碍症状；以及夜间困倦驾驶倾向更大。基于多变量逻辑回归分析，所有这六个因素都能预测自我报告的驾车时睡着情况。驾车时睡着还与未因驶过路肩隆隆带而被唤醒有关。结果表明，限制司机工作时间、使司机能够获得充足休息以及识别患有睡眠障碍的司机的应对措施，是减少卡车司机因嗜睡而导致的驾车问题的合适方法。
