Effects of partial sleep deprivation: A comparative assessment of young non-professional and professional taxi drivers

AimThis study aims to determine the effects of partial sleep deprivation (PSD) on driving performance of professional and young non-professional drivers.MethodsThe study included fifty participants (20 professional taxi drivers and 30 young non-professional drivers) driving the simulator-cab in three conditions. The first test session (TS1) was conducted after one night of PSD followed by the second test (TS2) after two consecutive nights of PSD. The driving performance metrics in two conditions of PSD (i.e., sleep duration = 4.25 ± 0.5 h) were compared with the baseline drive with no sleep loss. Sleep restriction was monitored using Actiwatch. Drivers subjectively self-reported their alertness using Karolinska Sleepiness Scale (KSS). Driving performance metrics and reaction time to emergency events were collected during each drive.ResultsA preliminary mixed-design ANOVA showed deterioration in driving performance of all drivers in terms of speed (p < 0.1), speed variability (p = 0.06), standard deviation in lateral positions (SDLP) (p < 0.001) and delayed reaction time (p < 0.05). Separate Mixed-Effects Generalized Linear Models for professional and non-professional drivers showed that speed variability, SDLP and reaction time increased from baseline during both the PSD tests, among both the driving groups. The speed variability, SDLP and reaction time of professional drivers differed significantly from other drivers under PSD conditions. Contrary to the existing belief, the professional drivers had significant decrements in driving performance due to PSD.ConclusionA critical and comparative analysis revealed that driving experience/skill of professional drivers does not improve their resistance to deteriorating effects of sleep loss.     

Hazard perception performance and visual scanning behaviours: The effect of sleepiness

Driver sleepiness accounts for a substantial proportion of crashes in Australia and Worldwide. Young adults are overrepresented in sleep-related crashes and are more susceptible to sleepiness, resulting in impaired attention and driving performance. Visual scanning behaviour can affect the role between attention and information acquisition from the driver's environment. Thus, if attention is impaired, visual scanning behaviours are likely to show decrements as well. Overall, 32 young adults aged between 20 and 25 years completed a 60-minute hazard perception task to examine the effect of sleepiness and time-on-task on hazard perception performance, visual scanning behaviours, subjective sleepiness scores, and psychomotor vigilance test performance. The main outcomes include decrements in hazard perception performance and a restriction in horizontal and vertical eye scanning ranges across the 60-minute session, but with a more pronounced effect when sleep-restricted. These outcomes were consistent with increases in subjective sleepiness and behavioural metrics of sleepiness assessed via the PVT. Reductions in scanning range could limit opportunities to attend to hazards and other critical safety events. The current study outcomes provide an important contribution regarding the risks associated with sleepy driving performance.     

The self-reported causes of sleepiness in shift-working tram and truck drivers

Identifying the causes of sleepiness in various safety-critical work environments is necessary for implementing more efficient fatigue management strategies. In transportation, little is known about drivers’ own perceptions of these causes. Therefore, we instructed shift-working tram (n = 23) and long-haul truck drivers (n = 52) to report at the end of their shifts what made them sleepy if they felt so. These self-reports, measured on-duty sleepiness, and sleep amounts were recorded on every shift over a period of 2–3 weeks per driver. The causes of sleepiness were queried with smartphone applications and sleep logs. Sleepiness was measured with the Karolinska Sleepiness Scale (KSS) and sleep with wrist-worn actigraphs. Data were analyzed using generalized estimating equations. Sleep loss and insufficient rest breaks were commonly reported as causing sleepiness among the tram drivers, whereas time of day and sleep loss were the leading causes among the truck drivers. Other causes, such as traffic or cabin conditions, were not frequently mentioned. During morning, day, and evening shifts, the truck drivers were less likely to report insufficient rest breaks as causing sleepiness than the tram drivers. Similarly, during morning shifts, the truck drivers were less likely to attribute their sleepiness to sleep loss. In shifts with drives reporting severe sleepiness (KSS ≥ 7 at least once, 18–21% of shifts), sleep loss was significantly reported as causing sleepiness among both groups. Reporting insufficient rest breaks was associated with severe sleepiness among the tram drivers, whereas time of day showed the same among the truck drivers. The results highlight the need for addressing sleep-related fatigue in transportation and provide directions for future research with regard to secondary causes of sleepiness.     

Functional Equivalence of Sleep Loss and Time on Task Effects in Sustained Attention

Research on sleep loss and vigilance both focus on declines in cognitive performance, but theoretical accounts have developed largely in parallel in these two areas. In addition, computational instantiations of theoretical accounts are rare. The current work uses computational modeling to explore whether the same mechanisms can account for the effects of both sleep loss and time on task on performance. A classic task used in the sleep deprivation literature, the Psychomotor Vigilance Test (PVT), was extended from the typical 10‐min duration to 35 min, to make the task similar in duration to traditional vigilance tasks. A computational cognitive model demonstrated that the effects of time on task in the PVT were equivalent to those observed with sleep loss. Subsequently, the same mechanisms were applied to a more traditional vigilance task—the Mackworth Clock Task—providing a good fit to existing data. This supports the hypothesis that these different types of fatigue may produce functionally equivalent declines in performance.     

Three consecutive nights of sleep loss: Effects of morning caffeine consumption on subjective sleepiness/alertness,reaction time and simulated driving performance

Caffeinated products are often consumed as a popular countermeasure to the effects of sleep loss. However, the efficacy of caffeine to exert these effects after consecutive nights of sleep loss is poorly understood. The aim of this study was to investigate the effects of three consecutive nights of restricted sleep and morning caffeine consumption on subjective ratings of sleepiness/alertness, reaction time, and simulated driving performance. Twenty healthy, habitual caffeine consumers (11 females; age: 23.3 ± 5.7 y; BMI: 22.3 ± 3.5 kg⋅m⁻²; caffeine intake: 204 ± 89 mg⋅day⁻¹; Mean ± SD) who had normal sleeping patterns (≥8 h⋅night⁻¹) participated in this double-blind, placebo-controlled, randomised study. Following one night of normal sleep (≥8 h time in bed (TIB)), participants underwent three consecutive nights of restricted sleep (5 h TIB). Participants received caffeine (200 mg; n = 10) or placebo (n = 10) capsules each morning and all participants received caffeine (100 mg) capsules each afternoon. Subjective ratings of alertness, concentration and tiredness were measured before and 1 h after morning capsule administration. Choice Reaction Time (CRT) was examined 1 h after morning capsule administration, with response speed and accuracy as outcome variables. Driving performance was assessed using a 30 min simulated driving task, with lateral (standard deviation of lane position [SDLP]; total number of line crossings [LC]) and longitudinal (standard deviation of speed [SDSP]) measures of vehicle control as outcome variables. Alertness and concentration significantly decreased, and tiredness increased across the three days of sleep loss. Caffeine only marginally alleviated these effects. No differences were observed between treatments or across trial days for response speed and accuracy on the CRT task. Likewise, no significant differences were observed between groups or across trial days for any measures of simulated driving performance. Overall, results from this study indicate that three consecutive days of sleep loss influence subjective ratings of alertness, concentration and tiredness, but does not alter CRT or simulated driving performance. Caffeine may alleviate some of the negative subjective effects imposed by restricted sleep, but the efficacy of caffeine to attenuate performance changes in CRT and driving performance were unable to be observed.     

Fatigue risk management based on self-reported fatigue: Expanding a biomathematical model of fatigue-related performance deficits to also predict subjective sleepiness

Biomathematical models of fatigue can be used to predict neurobehavioral deficits during sleep/wake or work/rest schedules. Current models make predictions for objective performance deficits and/or subjective sleepiness, but known differences in the temporal dynamics of objective versus subjective outcomes have not been addressed. We expanded a biomathematical model of fatigue previously developed to predict objective performance deficits as measured on the Psychomotor Vigilance Test (PVT) to also predict subjective sleepiness as self-reported on the Karolinska Sleepiness Scale (KSS). Four model parameters were re-estimated to capture the distinct dynamics of the KSS and account for the scale difference between KSS and PVT. Two separate ensembles of datasets – drawn from laboratory studies of sleep deprivation, sleep restriction, simulated night work, napping, and recovery sleep – were used for calibration and subsequent validation of the model for subjective sleepiness. The expanded model was found to exhibit high prediction accuracy for subjective sleepiness, while retaining high prediction accuracy for objective performance deficits. Application of the validated model to an example scenario based on cargo aviation operations revealed divergence between predictions for objective and subjective outcomes, with subjective sleepiness substantially underestimating accumulating objective impairment, which has important real-world implications. In safety-sensitive operations such as commercial aviation, where self-ratings of sleepiness are used as part of fatigue risk management, the systematic differences in the temporal dynamics of objective versus subjective measures of functional impairment point to a potentially significant risk evaluation sensitivity gap. The expanded biomathematical model of fatigue presented here provides a useful quantitative tool to bridge this previously unrecognized gap.     

Differential effects of driver sleepiness and sleep inertia on driving behavior

ObjectivesDriver sleepiness is one of the major safety issues in conventional driving and sleep inertia emerges as a driver state in automated driving. The aim of the present study was to assess the differential impacts of sleepiness and sleep inertia on driving behavior.Method61 participants completed a 10-min manual driving task during an otherwise automated drive. They completed the task (a) under an alert state, (b) under a sleepy state, and (c) after EEG-confirmed sleep. Driving performance was assessed with the parameters lane-keeping, speed choice, and speed-keeping. The eye-blink-based sleepiness measure PERCLOS (the proportion of time with eyes closed) was compared for the three driver states.ResultsLane- and speed-keeping performance were impaired under the sleepy state and after sleep, relative to the alert state. After sleep, lane-keeping behavior recovered rapidly and speed-keeping recovered by trend. Under the sleepy state, performance deteriorated. After sleep, the mean speed was lower than in the sleepy state and in the alert state. PERCLOS was increased after sleep and under the sleepy state, relative to the alert state.ConclusionsAlthough sleep inertia had detrimental effects on driving parameters similar to sleepiness, this effect rapidly vanished. Hence, while brief naps might be suitable to restore alertness in general, the minimal time needed to regain full capacity after napping should be a focus of future research.     

The validity of psychomotor vigilance tasks of less than 10-minute duration

The 10-min psychomotor vigilance task (PVT) has often been used to assess the impact of sleep loss on performance. Due to time constraints, however, regular testing may not be practical in field studies. The aim of the present study was to examine the suitability of tests shorter than 10 min. in duration. Changes in performance across a night of sustained wakefulness were compared during a standard 10-min PVT, the first 5 min of the PVT, and the first 2 min of the PVT. Four performance metrics were assessed: (1) mean reaction time (RT), (2) fastest 10% of RT, (3) lapse percentage, and (4) slowest 10% of RT. Performance during the 10-min PVT significantly deteriorated with increasing wakefulness for all metrics. Performance during the first 5 min and the first 2 min of the PVT deteriorated in a manner similar to that observed for the whole 10-min task, with all metrics except lapse percentage displaying significant impairment across the night. However, the shorter the task sampling time, the less sensitive the test is to sleepiness. Nevertheless, the 5-min PVT may provide a viable alternative to the 10-min PVT for some performance metrics.     

The validity of psychomotor vigilance tasks of less than 10-minute duration.

The 10-min psychomotor vigilance task (PVT) has often been used to assess the impact of sleep loss on performance. Due to time constraints, however, regular testing may not be practical in field studies. The aim of the present study was to examine the suitability of tests shorter than 10 min. in duration. Changes in performance across a night of sustained wakefulness were compared during a standard 10-min PVT, the first 5 min of the PVT, and the first 2 min of the PVT. Four performance metrics were assessed: (1) mean reaction time (RT), (2) fastest 10% of RT, (3) lapse percentage, and (4) slowest 10% of RT. Performance during the 10-min PVT significantly deteriorated with increasing wakefulness for all metrics. Performance during the first 5 min and the first 2 min of the PVT deteriorated in a manner similar to that observed for the whole 10-min task, with all metrics except lapse percentage displaying significant impairment across the night. However, the shorter the task sampling time, the less sensitive the test is to sleepiness. Nevertheless, the 5-min PVT may provide a viable alternative to the 10-min PVT for some performance metrics.     

The multiple vigilance test

The multiple vigilance test is a 30-min signal detection task designed to assess performance. Sixty target and 180 nontarget stimuli are presented with random interstimulus intervals ranging from 4 to 11 sec. Subjects respond by pressing the spacebar (or microswitch in an alternate version of the program) when they see the masking pattern transformed into the target. This vigilance test is used in conjunction with measures of physiological sleepiness (Multiple Sleep Latency Test) and subjective sleepiness (Stanford Sleepiness Scale). This behavioral information concerning manifest sleepiness provides a more complete picture of a subject’s state of alertness. The assessment of vigilance during long, monotonous, nonstimulating tasks is clinically important in patients with disorders of sleep and arousal.     

The driver vigilance telemetric control system (DVTCS): Investigating sensitivity to experimentally induced sleep loss and fatigue

Vigilance technologies are used in the Australian rail industry to address the risks associated with driver sleepiness and fatigue. The aim of this study was to investigate whether a new device, designed to detect lowered states of arousal using electrodermal activity (EDA), would be sensitive to experimentally induced sleepiness and fatigue. Fifteen individuals (7 of them female, 9 male; 18–32 years of age) spent 3 consecutive days in the laboratory, which included 1 night of sustained wakefulness (28 h). The participants completed a 10-min psychomotor vigilance task (PVT) and fatigue and sleepiness ratings every 2 h, and a 30-min driving simulator every 4 h. As was expected, simulated driving, PVT, and subjective ratings indicated increasing levels of sleepiness and fatigue during sustained wakefulness. The EDA device output did not coincide with these findings. The results indicated that the EDA indicator was not sensitive to increased sleepiness and fatigue at the levels produced in the present study.     

Distracted driving caused by voice message apps: A series of experimental studies

Hand-free voice message apps are frequently used by young people while driving. Previous studies have identified voice message apps as a common source of driving distraction. To quantitatively evaluate the factors contributing to driving distractions, three simulated driving experiments were designed using a dual-task experimental paradigm. In Experiment 1, participants completed several common tasks related to voice messages in WeChat with or without manual operations (perceptual-motor distraction). Experiments 2 and 3 further took into consideration the cognitive distraction level, measured by task difficulty and task frequency. The results showed that, in comparison with undistracted driving, the perceptual-motor distraction related to voice message app use significantly (ps < 0.05) weakened young drivers’ driving performance with respect to the standard deviation of lateral position (SDLP) between two cars (0.24 m), response time (0.21 s) and error rate (0.12) to turning lights, and collision percentage (0.54%), similar to the effects induced by non-voice-based apps. There were also significant differences (ps < 0.05) between driving with secondary tasks with and without continuous manual operations in the SDLP between two cars (0.19 m) and in the response time (0.18 s) and error rate (0.10) to turning lights, which indicates that the distracting effect produced by voice-message apps comes from the related manual operations. The effects of cognitive distraction on driving performance mainly depended on task difficulty level. High-difficulty secondary tasks via a voice message app significantly (ps < 0.05) weakened the driving performance in response time (by 0.13 s and 0.13 s compared to low-difficulty and baseline conditions, respectively) and error rate (by 0.07 and 0.07 compared to low-difficulty and baseline conditions, respectively) to turning lights and collision percentage (by 0.90% and 0.80% compared to low-difficulty and baseline conditions, respectively). The findings provide a theoretical reference for analysing the distracting components of voice messages and suggest that drivers should limit the use of these kinds of apps during driving.     

A sleep physiologist's view of the drowsy driver

Drowsy driving is dangerous because of the impairment of driving skills that it causes. Unfortunately, the conceptual basis that underlies much of the multi-disciplinary research on this topic is muddled. The same poorly defined terms, such as fatigue and sleepiness, are used differently by different disciplines and researchers. Some new definitions and concepts are proposed here which may be helpful, as least as a stimulus for discussion by others. Drowsiness, sleepiness and fatigue are distinguished. A new conceptual model of sleepiness is outlined, based on a mutually inhibitory interaction between a putative sleep drive and a wake drive. Sleepiness, defined as sleep propensity, is a function of the relative strengths, not the absolute strengths, of the sleep and wake drives. The measurement of sleepiness requires some new variables such as instantaneous sleep propensity, to be distinguished from either the situational or the average sleep propensity. A subject's instantaneous sleep propensity depends on many variables including his average sleep propensity in daily life, the time of day, the duration of prior wakefulness, the subject's posture, physical and mental activity at the time, and individual differences based on psychophysiological traits. The relationship between dozing at the wheel while driving and crashing the vehicle may not be as straightforward as it appears at first.     

Absorbed in sleep: Dissociative absorption as a predictor of sleepiness following sleep deprivation in two high-functioning samples

In recent years, a labile sleep-wake cycle has been implicated as a cause for dissociative experiences, and studies show that dissociation is elevated following sleep deprivation. Dissociative individuals may find it harder to regulate sleepiness in the face of sleep disruption. Although there is significant variability in reactions to sleep deprivation, research on trait predictors is scarce. The present study examined the ability of trait dissociation to prospectively predict sleepiness following sleep loss and recovery sleep. Two high-functioning samples, namely, Remotely Piloted Aircraft officers (N = 29) and Air Force jet pilots (N = 57) completed state and trait questionnaires assessing sleep and dissociation before and after full or partial sleep loss. Dissociative absorption was a consistent predictor of an increase in sleepiness following sleep loss and following recovery sleep, controlling for baseline sleepiness levels. We discuss the findings in light of a difficulty to regulate and monitor consciousness states.     

Effects of slow-release caffeine and a nap on driving simulator performance after partial sleep deprivation

A driving simulator was used to evaluate the effectiveness of a 30-min. nap and 300-mg slow-release caffeine as countermeasures to drivers' sleepiness induced by partial sleep deprivation. 12 participants were allowed 45 hr. time in bed at the laboratory. Driving performance then was measured twice--at 9 a.m. and at 1 p.m.--by a 45-min. driving task on a simulator. Subjective sleepiness/alertness and mood were assessed four times on the Stanford Sleepiness Scale and the Profile of Mood States. Driving performance was assessed as Lane Drifting, Speed Deviation, and Accident Liability. A 30-min. nap opportunity and 300 mg of slow-release caffeine both were successful in counteracting drivers' sleepiness. The remedial effect of slow-release caffeine lasted longer than that of the nap, that is, it was also effective in the afternoon session. This suggests that slow-release caffeine represents a valuable countermeasure that, in the case of partial sleep deprivation, is preferred to a nap when sleepiness has to be counteracted for a longer time.     

Diverging diamond interchanges: A driving simulator study

This study assessed driver performance while navigating a Diverging Diamond Interchange (DDI) compared to a standard intersection in a driving simulator. A total of 201 Western Australian (WA) drivers aged 18–80 years completed the simulator drive and questionnaire. Measures of driving simulator performance assessed included time spent out of lane, number of lane excursions, compliance to the speed limit, crashes and near misses. Other driving measures, which were recorded by the researcher, included driver errors/violations such as red-light violations, wrong way violations and navigation errors. Qualitative information was also obtained in a post exit interview with each participant regarding the difficulties they experienced when driving through the DDI. A repeated-measure analysis of variance (r-ANOVA) was undertaken to examine differences in intersection type (DDI versus standard intersection) and driving performance measures from the driving simulator. The only significant result was compliance to the speed limit (F (1, 656) = 160.11, p < 0.001) on the driving simulator. A higher proportion of red-light violations were observed by the researcher as participants navigated through the DDI, compared to the standard intersection. Qualitative comments from participants also highlighted the need for better signage and road markings. Recommendations when DDIs are implemented include community education on speed limit compliance, avoidance of red-light violations and design improvements regarding signage and road markings.     

Effects of sleep deprivation on cognitive performance by United States Air Force pilots

This study examined the effects of 35 h of continuous sleep deprivation on performance in a variety of cognitive tasks as well as simulated flight. Ten United States Air Force pilots completed the Multi-Attribute Task Battery (MATB), Psychomotor Vigilance Task (PVT), and Operation Span Task (OSPAN), as well as simulated flight at 3 h intervals over a 35 h sleep deprivation period. Performance declined on all tests after about 18–20 h of continuous sleep deprivation, although the degree to which performance degraded varied. During the second half of the sleep deprivation period, performance on the simulated flight was predicted by PVT and OSPAN reasonably well but much less so by the MATB. Variance from optimal flight performance was predicted by both PVT and OSPAN but each measure added incremental validity to the prediction. The two measures together accounted for 58% of the variance in flight performance in the second half of the sleep deprivation period.     

Measured increases in steering entropy may predict when performance will degrade: A driving simulator study

We investigated the effect of time-on-task on driver’s mental workload and driving performance during a simulated driving task. The extent of mental workload was estimated from steering entropy, while driver performance was measured from the Standard Deviation of Lateral Position (SDLP) and the Standard Deviation (SD) Sterring Angle. Seventeen participants underwent a simulated highway driving task for 60 min. The results show that mental workload increased significantly after 15 min, whereas driving performance did not degrade until 30 min. These results suggest that when drivers first affected by time-on-task, they can cope with the situation by increasing mental effort investment and can manage to perform normally for a while (15 min). Since changes in steering entropy precede changes in driving performance, this measure of mental workload may have utility as a predictor of increased accident risk.     

Sleep interventions for performance,mood and sleep outcomes in athletes: A systematic review and meta-analysis

Sleep is fundamental to sports performance and other health outcomes such as mental wellbeing. This systematic review explored the effects of sleep interventions implemented among athletes on performance, sleep, and mood outcomes. Five databases were searched, returning 5996 records for screening. Of these, 27 articles met the inclusion criteria (16 controlled deigns, 11 uncontrolled; athletes n = 617; male n = 432, female n = 93, non-binary/other n = 0 or not reported n = 92). Narrative synthesis of all studies based on intervention type suggested that sleep hygiene, assisted sleep, and sleep extension interventions may be associated with improved sleep, performance, and mood outcomes. Twelve controlled trials were eligible for quantitative meta-analysis, investigating the effect of sleep interventions on athlete sleep, performance, and negative affect, compared to controls post-intervention. Utilizing random-effects meta-analyses, sleep interventions improved subjective sleep quality (g = 0.62, 95% CI [0.21, 1.02]), reduced sleepiness (g = 0.81, 95% CI [0.32, 1.30]) and decreased negative affect (g = 0.63, 95% CI [0.27, 0.98]), but did not appear to influence subjective sleep duration. No effects were identified for objective sleep measures (e.g., actigraphy), or aerobic/anaerobic performance indices. While sleep interventions may offer some benefit to athletes, caution is warranted given limitations of the extant research relating to small, non-representative studies with methodological concerns.     

Mirror,mirror - Does the fitness club industry have a body image problem?

The primary aim of the present study was to report longitudinal data on body image across the first year of gym engagement. Second, we aimed to compare body image among those who reported regular use of the fitness club (≥2 sessions/week) with those who did not (≤1exercise session/week or no exercise/dropout), as well as between genders and Body Mass Index groups (BMI<25 and BMI≥25) at membership start-up. Novice exercisers (n = 250) from 25 fitness clubs in Oslo (Norway) responded to an online questionnaire at start-up, three, six and 12-months follow-up, with a high response rate (100%, 89.6%, 85.2% and 74.8%). The questionnaire covered background/health information and exercise involvement. A modified Multidimensional Body Self Relations Questionnaire Appearance Scales (MBSRQ-AS), comprising five subscales (appearance satisfaction, appearance investment, weight-related attitude, self-classified weight and Body Areas Satisfaction Scale (BASS), was used to gather repeated measures of body image. Data were analysed separately for each subscale and as a body image total score, using a linear mixed model adjusted for baseline, gender and BMI. We found differences in body image total score reported at six months when compared with onset (0.04, 95% CI 0.005–0.078, p = 0.024), whereas the subscale appearance satisfaction was different at three (0.08, 95% CI 0.015–0.164, p = 0.018), six (0.11, 95% CI 0.039–0.197, p = 0.003) and twelve (0.10, 95% CI 0.021–0.179, p = 0.013) months when compared with onset. Also the subscale BASS was different at three (0.17, 95% CI 0.009–0.255, p < 0.001), six (0.21, 95% CI 0.127–0.301, p < 0.001) and twelve (0.26, 95% CI 0.143–0.388, p < 0.001). Participants adhering to regular exercise (≥2 times weekly) had better outcomes on total body image than those who exercised less frequently or irregularly (three: 2.94 vs. 2.83, p = 0.027 and 12-months: 2.97 vs. 2.85, p = 0.028).At membership start-up, being male (p < 0.001) and having a BMI<25 (p = 0.003), were the strongest factors associated with reporting a higher score on total body image. In conclusion, we found improved body area and appearance satisfaction in novice exercisers across the first year of fitness club membership.