SUMMAR Y The present study aimed to provide subject-specific estimates of the relation between subjective sleepiness measured with the Karolinska Sleepiness Scale (KSS) and blink duration (BLINKD) and lane drifting calculated as the standard deviation of the lateral position (SDLAT) in a high-fidelity moving base driving simulator. Five male and five female shift workers were recruited to participate in a 2-h drive (08:00-10:00 hours) after a normal night sleep and after working a night shift. Subjective sleepiness was rated on the KSS in 5-min intervals during the drive, electro-occulogram (EOG) was measured continuously to calculate BLINKD, and SDLAT was collected from the simulator. A mixed model anova showed a significant (P < 0.001) effect of the KSS for both dependent variables. A test for a quadratic trend suggests a curvilinear effect with a steeper increase at high KSS levels for both SDLAT (P < 0.001) and BLINKD (P ¼ 0.003). Large individual differences were observed for the intercept (P < 0.001), suggesting that subjects differed in their overall driving performance and blink duration independent of sleepiness levels. The results have implications for any application that needs prediction at the subject level (e.g. driver fatigue warning systems) as well as for research design and the interpretation of group average data.k e y w o r d s lane drifting, mixed models, standard deviation of lateral position
SUMMARYThe main consequence of insufficient sleep is sleepiness. While measures of sleep latency, continuous encephalographical/electro-oculographical (EEG/EOG) recording and performance tests are useful indicators of sleepiness in the laboratory and clinic, they are not easily implemented in large, real-life field studies. Subjective ratings of sleepiness, which are easily applied and unobtrusive, are an alternative, but whether they measure sleepiness sensitively, reliably and validly remains uncertain. This review brings together research relevant to these issues. It is focused on the Karolinska Sleepiness Scale (KSS), which is a nine-point Likert-type scale. The diurnal pattern of sleepiness is U-shaped, with high KSS values in the morning and late evening, and with great stability across years. KSS values increase sensitively during acute total and repeated partial sleep deprivation and night work, including night driving. The effect sizes range between 1.5 and 3. The relation to driving performance or EEG/EOG indicators of sleepiness is highly significant, strongly curvilinear and consistent across individuals. High (>6) KSS values are associated particularly with impaired driving performance and sleep intrusions in the EEG. KSS values are also increased in many clinical conditions such as sleep apnea, depression and burnout. The context has a strong influence on KSS ratings. Thus, physical activity, social interaction and light exposure will reduce KSS values by 1-2 units. In contrast, time-on-task in a monotonous context will increase KSS values by 1-2 units. In summary, subjective ratings of sleepiness as described here is as sensitive and valid an indicator of sleepiness as objective measures, and particularly suitable for field studies.
SUMMAR Y Driving in the early morning is associated with increased accident risk affecting not only professional drivers but also those who commute to work. The present study used a driving simulator to investigate the effects of driving home from a night shift. Ten shift workers participated after a normal night shift and after a normal night sleep. The results showed that driving home from the night shift was associated with an increased number of incidents (two wheels outside the lane marking, from 2.4 to 7.6 times), decreased time to first accident, increased lateral deviation (from 18 to 43 cm), increased eye closure duration (0.102 to 0.143 s), and increased subjective sleepiness.The results indicate severe postnight shift effects on sleepiness and driving performance.k e y w o r d s accidents, commute, eye closure, lateral deviation, sleepiness
SUMMARY Studies of driving and sleepiness indicators have mainly focused on prior sleep reduction. The present study sought to identify sleepiness indicators responsive to several potential regulators of sleepiness: sleep loss, time of day (TOD) and time on task (TOT) during simulator driving. Thirteen subjects drove a high-fidelity moving base simulator in six 1-h sessions across a 24-h period, after normal sleep duration (8 h) and after partial sleep deprivation (PSD; 4 h). The results showed clear main effects of TOD (night) and TOT but not for PSD, although the latter strongly interacted with TOD. The most sensitive variable was subjective sleepiness, the standard deviation of lateral position (SDLAT) and measures of eye closure [duration, speed (slow), amplitude (low)]. Measures of electroencephalography and line crossings (LCs) showed only modest responses. For most variables individual differences vastly exceeded those of the fixed effects, except for subjective sleepiness and SDLAT. In a multiple regression analysis, SDLAT, amplitude ⁄ peak eye-lid closing velocity and blink duration predicted subjective sleepiness bouts with a sensitivity and specificity of about 70%, but were mutually redundant. The prediction of LCs gave considerably weaker, but similar results. In summary, SDLAT and eye closure variables could be candidates for use in sleepiness-monitoring devices. However, individual differences are considerable and there is need for research on how to identify and predict individual differences in susceptibility to sleepiness.k e y w o r d s accidents,
SUMMARY The aim of the present national questionnaire study was to relate the use of sleepiness countermeasures among drivers to possible explanatory factors such as age, sex, education, professional driving, being a shift worker, having experience of sleepy driving, sleep-related crashes, problems with sleep and sleepiness in general and sleep length during working days. Also the attitude to countermeasures related to information or driver support system was studied. A random sample of 3041 persons was drawn from the national register of vehicle owners. The response rate was 62%.The most common countermeasures were to stop to take a walk (54%), turn on the radio ⁄ stereo (52%), open a window (47%), drink coffee (45%) and to ask passengers to engage in conversation (35%). Logistic regression analysis showed that counteracting sleepiness with a nap (a presumably efficient method) was practiced by those with experience of sleep-related crashes or of driving during severe sleepiness, as well as by professional drivers, males and drivers aged 46-64 years. The most endorsed means of information to the driver about sleepiness was in-car monitoring of driving performance providing drivers with information on bad or unsafe driving. This preference was related to experience of sleepy driving, not being a professional driver and male gender. Four clusters of behaviours were identified: alertness-enhancing activity while driving (A), stopping the car (S), taking a nap (N) and ingesting coffee or other sources of caffeine (C) (energy drinks, caffeine tablets). The participants were grouped according to their use of any of the four categories of countermeasures. The most common cluster was those who used activity, as well as stopping and drinking caffeine.k e y w o r d s countermeasures, driving, individual differences, information
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