High risk of near-crash driving events following night-shift work

Retaining doctors in emergency medicine: an ethnographic study of emergency departments in England

OBJECTIVES

To gain a deep understanding of factors driving retention in emergency medicine. To understand in detail the day-to-day lived experience of emergency medicine doctors, to identify and explore factors influencing retention, to situate these descriptions within the current educational and health policy contexts and to advance the debate and make policy and practice recommendations.

DESIGN

Ethnography and semistructured interviews.

SETTING

Two purposively sampled emergency departments in England, with additional interview participants recruited via social media and relevant stakeholder organisations.

PARTICIPANTS

41 interview participants comprising 21 emergency physicians across 2 sites, 10 former emergency physicians and 10 stakeholders, with 132 hours of observation over 11 weeks in one emergency department in England.

RESULTS

Three key themes were developed as relevant to the day-to-day lived experience of work in the emergency department, presenting challenges to retention and opportunities for change. First, emergency physicians needed to develop workarounds to mitigate the sensory and material challenges of working in a difficult environment.Second, education influences retention through valuing, fostering competence and entrustment and supporting interdependence. These were primarily observable in the workplace through senior staff prioritising the education of more junior staff.Third, community was important for retention. Linked to education through communities of practice, it was built by brief interpersonal interactions between emergency department workers.Situating these descriptions in current policy contexts identified less than full-time working, portfolio careers and mentorship as retention strategies. Self-rostering and annualisation facilitated these retention strategies.

CONCLUSIONS

The emergency department represents a difficult environment with many challenges, yet by focusing on how doctors navigate these difficulties, we can see the way in which retention occurs in everyday practices, and that valuing staff is critical for retention.

Sleep Behavior in Royal Australian Navy Shift Workers by Shift and Exposure to the SleepTank App

INTRODUCTION

Rotating shiftwork schedules are known to disrupt sleep in a manner that can negatively impact safety. Consumer sleep technologies (CSTs) may be a useful tool for sleep tracking, but the standard feedback provided by CSTs may not be salient to shift-working populations. SleepTank is an app that uses the total sleep time data scored by a CST to compute a percentage that equates hours of sleep to the fuel in a car and warns the user to sleep when the "tank" is low. Royal Australian Navy aircraft maintenance workers operating on a novel rotational shift schedule were given Fitbit Versa 2s to assess sleep timing, duration, and efficiency across a 10-week period. Half of the participants had access to just the Fitbit app while the other half had access to Fitbit and the SleepTank app. The goal of this study was to evaluate differences in sleep behavior between shifts using an off-the-shelf CST and to investigate the potential of the SleepTank app to increase sleep duration during the 10-week rotational shift work schedule.

MATERIALS AND METHODS

Royal Australian Navy volunteers agreed to wear a Fitbit Versa 2 with the SleepTank app (SleepTank condition), or without the SleepTank app (Controls), for up to 10 weeks from May to July 2023 during the trial of a novel shift rotation schedule. Participants from across 6 units worked a combination of early (6:00 AM to 2:00 PM), day (7:30 AM to 4:30 PM), late (4:00 PM to 12:00 AM), and night shifts (12:00 AM to 6:00 AM) or stable day shifts (6:00 AM to 4:00 PM). Differences in sleep behavior (time in bed, total sleep time, bedtime, wake time, sleep efficiency [SE]) between conditions and shift types were tested using Analysis of Variance. This study was approved by the Australian Departments of Defence and Veterans' Affairs Human Research Ethics Committee.

RESULTS

Thirty-four participants completed the full study (n = 17 Controls; n = 17 SleepTank). There was a significant effect of shift type on 24-hour time in bed (TIB24; F(4,9) = 8.15, P < .001, η2 = 0.15) and total sleep time (TST24; F(4,9) = 8.54, P < .001, η2 = 0.18); both were shorter in early shifts and night shifts compared to other shift types. TIB24 and TST24 were not significantly different between conditions, but there was a trend for greater SE in the SleepTank condition relative to Controls (F(1,9) = 2.99, P = .08, η2 = 0.11).

CONCLUSIONS

Sleep data collected by Fitbit Versa 2s indicated shorter sleep duration (TIB24, TST24) for Royal Australian Navy workers during early and late shifts relative to stable day shifts. Access to the SleepTank app did not greatly influence measures of sleep duration but may be protective against fatigue by affecting SE. Further research is needed to evaluate the utility of the SleepTank app as a means of improving sleep hygiene in real-world, shift-working environments.

Sleepless on the road: Are mothers of infants with insomnia at risk for impaired driving?

Infant sleep problems have been associated with a myriad of adverse child and parent outcomes, yet whether these problems may pose a risk for parents on the road has received little research attention. This study sought to test whether mothers of infants with insomnia are at an elevated risk for vehicular crashes, by comparing their objectively measured driving performance with that of mothers of well-sleeping infants and with that of women without children. Fifty-four women from these three groups completed a simulated driving task. Outcome measures included standard deviation of lateral position, number of lane crossings, standard deviation of speed, average speed and maximum speed. Women additionally reported on their driving behaviour using the Driving Behaviour Questionnaire, and on sleep, sleepiness and insomnia symptoms using 7-day sleep diaries and questionnaires. Mothers of infants with insomnia demonstrated greater lane deviation (Wald = 9.53, p = 0.009), higher maximum speed (Wald = 6.10, p = 0.04) and poorer self-rated driving behaviour (Wald = 7.44, p = 0.02) compared with control groups. Analyses also indicated that driving performance in mothers of infants with insomnia tended to be poorer relative to control groups with the progression of time on task. While further research is needed to assess the scope of these effects, our findings suggest that parents, healthcare providers and policymakers should be aware of the potential consequences of infant sleep problems on road safety, and collaborate to establish strategies to mitigate these risks.

Research on Active Safety Situation of Road Passenger Transportation Enterprises: Evaluation, Prediction, and Analysis

The road passenger transportation enterprise is a complex system, requiring a clear understanding of their active safety situation (ASS), trends, and influencing factors. This facilitates transportation authorities to promptly receive signals and take effective measures. Through exploratory factor analysis and confirmatory factor analysis, we delved into potential factors for evaluating ASS and extracted an ASS index. To predict obtaining a higher ASS information rate, we compared multiple time series models, including GRU (gated recurrent unit), LSTM (long short-term memory), ARIMA, Prophet, Conv_LSTM, and TCN (temporal convolutional network). This paper proposed the WDA-DBN (water drop algorithm-Deep Belief Network) model and employed DEEPSHAP to identify factors with higher ASS information content. TCN and GRU performed well in the prediction. Compared to the other models, WDA-DBN exhibited the best performance in terms of MSE and MAE. Overall, deep learning models outperform econometric models in terms of information processing. The total time spent processing alarms positively influences ASS, while variables such as fatigue driving occurrences, abnormal driving occurrences, and nighttime driving alarm occurrences have a negative impact on ASS.

Awareness of errors is reduced by sleep loss

The ability to detect and subsequently correct errors is important in preventing the detrimental consequences of sleep loss. The Error Related Negativity (ERN), and the error positivity (Pe) are established neural correlates of error processing. Previous work has shown sleep loss reduces ERN and Pe, indicating sleep loss impairs error-monitoring processes. However, no previous work has examined behavioral error awareness, in conjunction with EEG measures, under sleep loss conditions, and studies of sleep restriction are lacking. Using combined behavioral and EEG measures, we report two studies investigating the impact of total sleep deprivation (TSD) and sleep restriction (SR) on error awareness. Fourteen healthy participants completed the Error Awareness Task under conditions of TSD and 27 completed the same task under conditions of SR. It was found that TSD did not influence behavioral error awareness or ERN or Pe amplitude, however, SR reduced behavioral error awareness, increased the time taken to detect errors, and reduced Pe amplitude. Findings indicate individuals who are chronically sleep restricted are at risk for reduced recognition of errors. Reduced error awareness may be one factor contributing to the increased accidents and injuries seen in contexts where sleep loss is prevalent.

High-risk event prone driver identification considering driving behavior temporal covariate shift

Drivers who perform frequent high-risk events (e.g., hard braking maneuvers) pose a significant threat to traffic safety. Existing studies commonly estimated high-risk event occurrence probabilities based upon the assumption that data collected from different time periods are independent and identically distributed (referred to as i.i.d. assumption). Such approach ignored the issue of driving behavior temporal covariate shift, where the distributions of driving behavior factors vary over time. To fill the gap, this study targets at obtaining time-invariant driving behavior features and establishing their relationships with high-risk event occurrence probability. Specifically, a generalized modeling framework consisting of distribution characterization (DC) and distribution matching (DM) modules was proposed. The DC module split the whole dataset into several segments with the largest distribution gaps, while the DM module identified time-invariant driving behavior features through learning common knowledge among different segments. Then, gated recurrent unit (GRU) was employed to conduct time-invariant driving behavior feature mining for high-risk event occurrence probability estimation. Moreover, modified loss functions were introduced for imbalanced data learning caused by the rarity of high-risk events. The empirical analyses were conducted utilizing online ride-hailing services data. Experiment results showed that the proposed generalized modeling framework provided a 7.2% higher average precision compared to the traditional i.i.d. assumption based approach. The modified loss functions further improved the model performance by 3.8%. Finally, benefits for the driver management program improvement have been explored by a case study, demonstrating a 33.34% enhancement in the identification precision of high-risk event prone drivers.

Considering the impact of shift working on health

Shift work is necessary for the provision of health services, especially in hospitals as it is the only way to provide continuous care to patients. Working at night is inconsistent with the body's biological clock and night shift working hugely disrupts the circadian and sleep wake cycles. In 2020, the World Health Organization classified night shift working as being a 'probable' class 2A carcinogen and a number of independent cohort studies of both night workers and shift workers have observed increased incidence of certain cancers. Altered sleep timing, food timing and light exposure typical for shift workers leads to an acute circadian disruption and misalignment of regulatory hormones. This straying from synchronisation has been shown to result in individuals being more vulnerable to a number of chronic health conditions. Night shift work disrupts the normal sleep-wake cycle, often leading to shortened sleep duration and excessive fatigue and the results of this are far reaching. This article will explore the full impact of shift working, questioning if current practices employed within the NHS should continue.

Spontaneous attentional failures reflect multiplicative interactions of chronic sleep loss with acute sleep loss and circadian misalignment

OBJECTIVES

Acute and chronic sleep loss and circadian timing interact such that, depending on their combination, small or very large performance decrements are observed in tasks of attention. Here, we tested whether such nonlinear interactions extend to a physiological measure of spontaneous visual attentional failures, indicating a fundamental principle of sleep-wake regulation.

METHODS

Nine healthy volunteers completed an in-laboratory 3-week forced desynchrony protocol consisting of 12 consecutive 42.85-hour cycles with a sleep-wake ratio of 1:3.3. The protocol induced increasing chronic sleep loss, while extended wake (32.85 hours) and sleep episodes (10 hours) occurred at multiple circadian phases. Attentional failure rate was quantified from continuous electrooculograms (number of 30-second epochs with slow eye movements/h of wakefulness) as a function of time since scheduled wake (acute sleep loss), week of study (chronic sleep loss), and circadian (melatonin) phase.

RESULTS

During the first ∼8 hours awake, attentional failure rate was low, irrespective of the week. During the following wake hours, attentional failure rate increased steadily but at a faster rate in weeks 2 and 3 compared to week 1. The effects of acute and chronic sleep loss on attentional failure rate were magnified during the biological night compared to the biological day.

CONCLUSIONS

A single extended sleep episode can only temporarily reverse attentional impairment associated with chronic sleep loss. Multiplicative effects of acute and chronic sleep loss-further amplified during the biological night-substantiate the interaction of 2 homeostatic response mechanisms and caution against underestimating their disproportionate combined impact on performance, health, and safety.

Subjective awareness of sleepiness while driving in younger and older adults

Understanding whether drivers can accurately assess sleepiness is essential for educational campaigns advising drivers to stop driving when feeling sleepy. However, few studies have examined this in real-world driving environments, particularly among older drivers who comprise a large proportion of all road users. To examine the accuracy of subjective sleepiness ratings in predicting subsequent driving impairment and physiological drowsiness, 16 younger (21-33 years) and 17 older (50-65 years) adults drove an instrumented vehicle for 2 h on closed loop under two conditions: well-rested and 29 h sleep deprivation. Sleepiness ratings (Karolinska Sleepiness Scale, Likelihood of Falling Asleep scale, Sleepiness Symptoms Questionnaire) were obtained every 15min, alongside lane deviations, near crash events, and ocular indices of drowsiness. All subjective sleepiness measures increased with sleep deprivation for both age groups (p < 0.013). While most subjective sleepiness ratings significantly predicted driving impairment and drowsiness in younger adults (OR: 1.7-15.6, p < 0.02), this was only apparent for KSS, likelihood of falling asleep, and "difficulty staying in the lane for the older adults" (OR: 2.76-2.86, p = 0.02). This may be due to an altered perception of sleepiness in older adults, or due to lowered objective signs of impairment in the older group. Our data suggest that (i) younger and older drivers are aware of sleepiness; (ii) the best subjective scale may differ across age groups; and (iii) future research should expand on the best subjective measures to inform of crash risk in older adults to inform tailored educational road safety campaigns on signs of sleepiness.

Predicting neurobehavioral performance of resident physicians in a Randomized Order Safety Trial Evaluating Resident-Physician Schedules (ROSTERS)

OBJECTIVES

Mathematical models of human neurobehavioral performance that include the effects of acute and chronic sleep restriction can be key tools in assessment and comparison of work schedules, allowing quantitative predictions of performance when empirical assessment is impractical.

METHODS

Using such a model, we tested the hypothesis that resident physicians working an extended duration work roster, including 24-28 hours of continuous duty and up to 88 hours per week averaged over 4weeks, would have worse predicted performance than resident physicians working a rapidly cycling work roster intervention designed to reduce the duration of extended shifts. The performance metric used was attentional failures (ie, Psychomotor Vigilance Task lapses). Model input was 169 actual work and sleep schedules. Outcomes were predicted hours per week during work hours spent at moderate (equivalent to 16-20 hours of continuous wakefulness) or high (equivalent to ≥20 hours of continuous wakefulness) performance impairment.

RESULTS

The model predicted that resident physicians working an extended duration work roster would spend significantly more time at moderate impairment (p = .02, effect size=0.2) than those working a rapidly cycling work roster; this difference was most pronounced during the circadian night (p < .001). On both schedules, performance was predicted to decline from weeks 1 + 2 to weeks 3 + 4 (p < .001), but the rate of decline was significantly greater on extended duration work roster (p < .01). Predicted performance impairment was inversely related to prior sleep duration (p < .001).

CONCLUSIONS

These findings demonstrate the utility of a mathematical model to evaluate the predicted performance profile of schedules for resident physicians and others who experience chronic sleep restriction and circadian misalignment.

Development and evaluation of a scale to measure nurses' unsafe driving behaviour while commuting

Driving is the most prevalent form of commuting for most workers but is also perhaps the most hazardous mode of travel with unsafe driving contributing significantly to road traffic accidents. Despite nurses having been reported as being at higher risk of commuter-related accidents over the last three decades, little is known about unsafe driving behaviours among nurses while commuting, which is unique from other driving routines. Additionally, the lack of appropriate tools to measure such behaviours is apparent. This study aims i) to identify unsafe driving behaviours among nurses while commuting and ii) to develop a scale to assess nurses' unsafe commuting driving behaviours. The study employed a multiphase and multimethod approach to develop the scale, which was subject to stringent validation and evaluation. Themes were specified via the Nominal Group Technique (NGT). Six themes were identified namely: i) violations and reckless driving, ii) negative emotions, iii) drowsy driving iv) mind wandering, v) error and vi) carelessness. Content and face validity were sought through expert review. A total of 442 nurses' data were collected across multisite hospitals for evaluation. Exploratory factor analysis (EFA) resulted in recovered structure and was confirmed through Confirmatory Factor Analysis (CFA) with structural equation analyses being conducted to test predictive validity. All constructs met adequate validity and reliability. Nurses' unsafe driving behaviours while commuting were identified with a novel scale to assess them being both developed and validated. The resulting MyUDWC scale is a suitable tool for measuring nurses' unsafe driving behaviours while commuting.

Road safety: The influence of vibration frequency on driver drowsiness, reaction time, and driving performance

Driver drowsiness is a factor in at least 20% of serious motor vehicle accidents. Although research has shown that Whole-Body Vibration (WBV) can induce drowsiness in drivers, it is unknown whether particular frequencies are more problematic. The present study systematically investigated the influence of WBV frequency on driver drowsiness. Fifteen participants each undertook six 1-h sessions of simulated driving while being subjected to WBV of either 0 Hz (no vibration), 1-4 Hz, 4-8 Hz, 8-16 Hz, 16-32 Hz or 32-64 Hz. Subjective sleepiness, as measured by the Karolinska Sleepiness Scale (KSS), confirmed that drivers felt drowsier when exposed to the two lowest frequency ranges (1-4 Hz and 4-8 Hz). Reaction time, which measures attention and alertness, was significantly impaired by the two lowest frequency ranges. Objective driving performance measures (Standard Deviation of Lane Position (SDLP), Standard Deviation of (SD) Steering Angle, Time in Unsafe Zone) also showed significant degradation due to exposure to the two lowest frequency ranges. Exposure to 1-4 Hz or 4-8 Hz vibration caused attention to become significantly impaired within 15-20 min and driving performance to be significantly impaired by 30-35 min. The other frequency ranges had little or no effect. These findings point to a need to develop equivalent vibration-induced drowsiness contours that can be adopted as transportation safety standards.

Diagnosis and management of sleep disorders in shift workers, with patient informed solutions to improve health services research and practice

BACKGROUND

The combination of shift work and an unmanaged sleep disorder carries health and safety risks. Yet, diagnosis rates for sleep disorders are low in shift workers. The aim of this study was to understand the experience of sleep disorder diagnosis and treatment in shift workers, and consider patient informed solutions to improve access to health services.

METHODS

Semi-structured interviews were conducted with 16 Australian shift workers with a diagnosed sleep disorder. Patient journey mapping and reflexive thematic analysis were used to understand diagnosis and management experiences.

RESULTS

There were highly variable experiences with diagnosis and management, often taking >5 years to seek help from a health care provider (HCP) after noticing symptoms of a sleep disorder. Three themes were constructed, including 'the cause of the problem', 'prioritising work', and '(dis)satisfaction and (dis)connection'. Extent of patient and HCP awareness of sleep disorders, and a prevailing attitude of shift work being 'the problem' impacted diagnosis, as did organisational needs (including rostering, which had both positive and negative influences on help seeking). Relationships with HCPs were important, and living on non-standard time was both a barrier and an enabler to sleep disorder care. Participants identified the need for education and awareness, prompts and easy access to screening and referral pathways, and tailored models of care.

CONCLUSION

Education and awareness initiatives for shift workers, their employers and HCPs, together with development of a model of care for shift workers with sleep disorders may address some of the unique barriers to diagnosis and management.

Truck collisions attributed to falling asleep at the wheel in two commercial drivers prescribed oral appliance therapy for obstructive sleep apnea

Falling asleep at the wheel is attributed to sleepiness, and obstructive sleep apnea is a significant cause of sleepiness that increases the risk of motor vehicle collisions due to falling asleep at the wheel. Although continuous positive airway pressure therapy for obstructive sleep apnea reduces the risk of motor vehicle collisions, similar evidence for alternatives such as oral appliance therapy is lacking. We discuss two truck collisions attributed to microsleep confirmed with dashcam video footage of commercial drivers with obstructive sleep apnea. Our results highlight the current situation where there is insufficient evidence for the prevention and reduction of the risk of motor vehicle collisions by oral appliance therapy, objective adherence monitoring of oral appliance therapy, and effectiveness confirmation tests. Therefore, it is suggested that for commercial truck drivers who require a high level of driving safety, careful selection for oral appliance therapy, systematic follow-up, and monitoring of the driver and truck status with dashcam video footage are crucial.

CITATION

Kumagai H, Tsuda H, Kawaguchi K, et al. Truck collisions attributed to falling asleep at the wheel in two commercial drivers prescribed oral appliance therapy for obstructive sleep apnea. J Clin Sleep Med. 2023;19(12):2117-2122.

Macronutrient intake and alertness during night shifts - the time interval matters

Background

Working night shifts is associated with higher safety risks due to shift work-related fatigue. Nutrition, especially certain (macro) nutrient compositions, has been suggested to reduce fatigue, however, results of studies are contradictory. This could be explained by differences in the time interval investigated between the consumption of a meal and measurement of cognitive performance. Therefore, this observational study investigated the association between macronutrient intake and objective alertness at different time intervals during the night shift in nurses.

Methods

128 nurses, aged 20-61 years, completed an alertness test (Psychomotor Vigilance Task) during the night shift and a 24-h dietary recall after the night shift. This was repeated three times, always on the first night shift in a night shift series. The associations between macronutrient intake 0 to 1, 1 to 2, and 2 to 3 h before the PVT with alertness during the night shift were analyzed through Linear Mixed Models. The basic model was adjusted for age and gender and the adjusted model additionally for BMI, start time of PVT and energy and caffeine intake during the relevant time interval.

Results

Protein intake was not associated with objective alertness levels, while fat and carbohydrates intake had opposite associations with objective alertness levels over similar time intervals. Fat intake up to 1 h prior to the PVT was borderline associated with a longer median reaction time (RT) (ß = 9.00 ms/10 g fat, 95% CI: -0.21, 18.20), while a higher carbohydrate intake up to 1 h prior to the PVT was borderline associated with shorter median RTs (ß = -3.89, 95% CI: -7.85, 0.06). A higher fat intake 2 to 3 h prior to the PVT was associated with less lapses (log transformed ß = -0.16; 95% CI: -0.31, -0.02), while a higher carbohydrate intake 2 to 3 h prior to the PVT was associated with more lapses (ß = 0.06, 95% CI: 0.01, 0.12).

Conclusion

Our results contribute to understanding the association between macronutrient intake, as part of a mixed meal, and alertness levels. Conflicting results from previous studies may probably be due to time differences between macronutrient intake and alertness testing.

Feeling sleepy? stop driving-awareness of fall asleep crashes

STUDY OBJECTIVES

To examine whether drivers are aware of sleepiness and associated symptoms, and how subjective reports predict driving impairment and physiological drowsiness.

METHODS

Sixteen shift workers (19-65 years; 9 women) drove an instrumented vehicle for 2 hours on a closed-loop track after a night of sleep and a night of work. Subjective sleepiness/symptoms were rated every 15 minutes. Severe and moderate driving impairment was defined by emergency brake maneuvers and lane deviations, respectively. Physiological drowsiness was defined by eye closures (Johns drowsiness scores) and EEG-based microsleep events.

RESULTS

All subjective ratings increased post night-shift (p < 0.001). No severe drive events occurred without noticeable symptoms beforehand. All subjective sleepiness ratings, and specific symptoms, predicted a severe (emergency brake) driving event occurring in the next 15 minutes (OR: 1.76-2.4, AUC > 0.81, p < 0.009), except "head dropping down". Karolinska Sleepiness Scale (KSS), ocular symptoms, difficulty keeping to center of the road, and nodding off to sleep, were associated with a lane deviation in the next 15 minutes (OR: 1.17-1.24, p<0.029), although accuracy was only "fair" (AUC 0.59-0.65). All sleepiness ratings predicted severe ocular-based drowsiness (OR: 1.30-2.81, p < 0.001), with very good-to-excellent accuracy (AUC > 0.8), while moderate ocular-based drowsiness was predicted with fair-to-good accuracy (AUC > 0.62). KSS, likelihood of falling asleep, ocular symptoms, and "nodding off" predicted microsleep events, with fair-to-good accuracy (AUC 0.65-0.73).

CONCLUSIONS

Drivers are aware of sleepiness, and many self-reported sleepiness symptoms predicted subsequent driving impairment/physiological drowsiness. Drivers should self-assess a wide range of sleepiness symptoms and stop driving when these occur to reduce the escalating risk of road crashes due to drowsiness.

Applying a Health Equity Lens to Work-Related Motor Vehicle Safety in the United States

Motor vehicle crashes (MVCs) are the leading cause of fatal work-related injuries in the United States. Research assessing sociodemographic risk disparities for work-related MVCs is limited, yet structural and systemic inequities at work and during commutes likely contribute to disproportionate MVC risk. This paper summarizes the literature on risk disparities for work-related MVCs by sociodemographic and employment characteristics and identifies worker populations that have been largely excluded from previous research. The social-ecological model is used as a framework to identify potential causes of disparities at five levels-individual, interpersonal, organizational, community, and public policy. Expanded data collection and analyses of work-related MVCs are needed to understand and reduce disparities for pedestrian workers, workers from historically marginalized communities, workers with overlapping vulnerabilities, and workers not adequately covered by employer policies and safety regulations. In addition, there is a need for more data on commuting-related MVCs in the United States. Inadequate access to transportation, which disproportionately affects marginalized populations, may make travel to and from work less safe and limit individuals' access to employment. Identifying and remedying inequities in work-related MVCs, whether during the day or while commuting, will require the efforts of industry and multiple public sectors, including public health, transportation, and labor.

Work-Related Sleep Disorders: Causes and Impacts

Insufficient sleep syndrome, shift work disorder, and obstructive sleep apnea (OSA) not only significantly impact the health of affected individuals, but also pose a threat to public safety. This article describes the clinical manifestations and impact of these sleep disorders, particularly as they pertain to workers' health and those with safety-sensitive positions. Sleep deprivation, circadian rhythm disruptions, and excessive daytime sleepiness-hallmarks of insufficient sleep, shift work disorder, and OSA, respectively-all lead to a series of cognitive deficits and impaired concentration that affect workers in a wide variety of fields. We describe the health consequences of these disorders along with treatment strategies, with a focus on current regulatory standards and the under-recognition of OSA in commercial drivers. Given its large scale, there is a need for improved guidelines and regulations for the screening, diagnosis, treatment, and long-term follow-up of OSA in commercial motor vehicle drivers. Increased recognition of the ways in which these sleep disorders impact workers will pave the way for significant improvements in occupational health and safety.

The Impact of 12 h Night Shifts on Nurses’ Driving Safety

Aim: The purpose of this study was to determine the impact of 12 h day vs. 12 h night shift-accumulated fatigue on nurses’ driving safety. Background: Evidence across industries links work-related fatigue with errors, accidents, and adverse long-term health outcomes. Shifts of 12 h or longer are particularly problematic, and the potential risks to shift-worker driving safety during their post-shift commute home have yet to be fully explored. Methods: This study used a between-groups, repeated-measures non-randomized control trial. Forty-four nurses working 12 h day shifts and 49 nurses working 12 h night shifts were tested in a driving simulator on two separate occasions—once immediately following their third consecutive 12 h hospital shift and once on their third consecutive day (72 h) off work. Results: We found that night shift nurses had significantly greater lane deviation during the post-shift drive home compared to day shift nurses, which is a key indicator of collision risk, demonstrating impaired driving safety. Conclusions: Consecutive 12 h night shifts are an extremely popular shift for nurses working in the hospital setting, however they pose a significant driving safety risk to nurses assigned to night shifts. This study provides objective evidence of the impact of shift work-related fatigue on 12 h night shift nurse safety, allowing us to make recommendations that may help prevent injury or death from motor vehicle collisions.

Transcutaneous auricular vagus stimulation (taVNS) improves human working memory performance under sleep deprivation stress

Many human activities require high cognitive performance over long periods, while impairments induced by sleep deprivation influence various aspects of cognitive abilities, including working memory (WM), attention, and processing speed. Based on previous research, vagal nerve stimulation can modulate cognitive abilities, attention, and arousal. Two experiments were conducted to assess the efficacy of transcutaneous auricular vagus nerve stimulation (taVNS) to relieve the deleterious effects of sleep deprivation. In the first experiment, 35 participants completed N-back tasks at 8:00 a.m. for two consecutive days in a within-subject study. Then, the participants received either taVNS or earlobe stimulation (active control) intervention in two sessions at random orders after 24 h of sustained wakefulness. Then, they completed the N-back tasks again. In the second experiment, 30 participants completed the psychomotor vigilance task (PVT), and 32 completed the N-back tasks at 8:00 a.m. on the first and second days. Then, they received either taVNS or earlobe stimulation at random orders and finished the N-back and PVT tasks immediately after one hour. In Experiment 1, taVNS could significantly improve the accuracy rate of participants in spatial 3-back tasks compared to active control, which was consistent with experiment 2. However, taVNS did not specifically enhance PVT performance. Therefore, taVNS could be a powerful intervention for acute sleep deprivation as it can improve performance on high cognitive load tasks and is easy to administer.

Understanding the drowsy driving crash patterns from correspondence regression analysis

Drowsy driving-related crashes have been a key concern in transportation safety. In Louisiana, 14% (1,758 out of 12,512) of police-reported drowsy driving-related crashes during 2015-2019 resulted in injury (fatal, severe, or moderate). Amid the calls for action against drowsy driving by national agencies, it is of paramount importance to explore the key reportable attributes of drowsy driving behaviors and their potential association with crash severity.

METHOD

This study used 5-years (2015-2019) of crash data and utilized the correspondence regression analysis method to identify the key collective associations of attributes in drowsy driving-related crashes and interpretable patterns based on injury levels.

RESULTS

Several drowsy driving-related crash patterns were identified through crash clusters - afternoon fatigue crashes by middle-aged female drivers on urban multilane curves, crossover crashes by young drivers on low-speed roadways, crashes by male drivers during dark rainy conditions, pickup truck crashes in manufacturing/industrial areas, late-night crashes in business and residential districts, and heavy truck crashes on elevated curves. Several attributes - scattered residential areas indicating rural areas, multiple passengers, and older drivers (aged more than 65 years) - showed a strong association with fatal and severe injury crashes.

PRACTICAL APPLICATIONS

The findings of this study are expected to help researchers, planners, and policymakers in understanding and developing strategic mitigation measures to prevent drowsy driving.

PERCLOS-based technologies for detecting drowsiness: current evidence and future directions

Drowsiness associated with sleep loss and circadian misalignment is a risk factor for accidents and human error. The percentage of time that the eyes are more than 80% closed (PERCLOS) is one of the most validated indices used for the passive detection of drowsiness, which is increased with sleep deprivation, after partial sleep restriction, at nighttime, and by other drowsiness manipulations during vigilance tests, simulated driving, and on-road driving. However, some cases have been reported wherein PERCLOS was not affected by drowsiness manipulations, such as in moderate drowsiness conditions, in older adults, and during aviation-related tasks. Additionally, although PERCLOS is one of the most sensitive indices for detecting drowsiness-related performance impairments during the psychomotor vigilance test or behavioral maintenance of wakefulness test, no single index is currently available as an optimal marker for detecting drowsiness during driving or other real-world situations. Based on the current published evidence, this narrative review suggests that future studies should focus on: (1) standardization to minimize differences in the definition of PERCLOS between studies; (2) extensive validation using a single device that utilizes PERCLOS-based technology; (3) development and validation of technologies that integrate PERCLOS with other behavioral and/or physiological indices, because PERCLOS alone may not be sufficiently sensitive for detecting drowsiness caused by factors other than falling asleep, such as inattention or distraction; and (4) further validation studies and field trials targeting sleep disorders and trials in real-world environments. Through such studies, PERCLOS-based technology may contribute to preventing drowsiness-related accidents and human error.

A brief assessment of eye blink drowsiness immediately prior to or following driving detects drowsiness related driving impairment

Drowsy driving is a major cause of fatal and serious injury motor vehicle accidents. The inability objectively to assess drowsiness has hindered the assessment of fitness to drive and the development of drowsy driving regulations. This study evaluated whether spontaneous eye blink parameters measured briefly pre- and post-drive could be used to detect drowsy driving impairment. Twelve healthy participants (6 female) drove an instrumented vehicle for 2 h on a closed-loop track during a rested (8-10 h awake) and an extended wake condition (32-34 h awake). Pre- and post-drive, the participants completed a 5 min eye blink task, a psychomotor vigilance task (PVT), and the Karolinska sleepiness scale (KSS). Whole drive impairment was defined as >3.5 lane departures per hour. Severe end of drive impairment was defined as ≥2 lane departures in the last 15 min. The pre-drive % of time with eyes closed best predicted the whole drive impairment (area under the curve [AUC] 0.87). KSS had similar prediction ability (AUC 0.85), while PVT reaction time (AUC 0.72) was less accurate. The composite eye blink parameter, the Johns drowsiness scale was the best retrospective detector of severe end of drive impairment (AUC 0.99). The PVT reaction time (AUC 0.92) and the KSS (AUC 0.93) were less accurate. Eye blink parameters detected drowsy driving impairment with an accuracy that was similar to, or marginally better than, PVT and KSS. As eye blink measures are simple to measure, are objective and have high accuracy, they present an ideal option for the assessment of fitness for duty and roadside drowsiness.

Research priorities to reduce risks from work hours and fatigue in the healthcare and social assistance sector

BACKGROUND

The services of Healthcare and Social Assistance (HCSA) workers are needed by society around the clock. As a result, these workers are exposed to shift work and long work hours. The combination of demanding work schedules and other hazards in the HCSA work environment increases the health and safety risks to these workers, as well as to their patients/clients and the public.

METHODS

This paper has three aims: (1) provide an overview of the burden of shift work, long hours, and related sleep and fatigue problems in this sector; (2) suggest research priorities that would improve these; and (3) discuss potential positive impacts of addressing these research priorities for the health and safety of workers and the public. The authors used a modified Delphi approach to anonymously rank-order priorities for improving HCSA worker health and safety and public safety. Input was also obtained from attendees at the 2019 National Institute for Occupational Safety and Health (NIOSH) Work Hours, Sleep, and Fatigue Forum.

RESULTS

The highest rated research priorities were developing better designs for work schedules, and improving the HCSA culture and leadership approaches to shift work and long work hours. Additional priorities are identified.

CONCLUSION

Research in these priority areas has the potential to benefit HCSA workers as well as their patients/clients, employers, and society.

On the road again: A cross-sectional survey examining work schedules, commuting time, and driving-related outcomes among U.S. oil and gas extraction workers

BACKGROUND

Oil and gas extraction (OGE) workers in the United States experience high fatality rates, with motor vehicle crashes the leading cause of death. Land-based OGE workers drive frequently to remote and temporary worksites. Limited information is available on factors that may influence crash risk for this workforce.

METHODS

A cross-sectional survey of 500 land-based OGE workers examined work schedules and hours, commuting, sleep, employer policies, and their relationship to potentially harmful events while driving.

RESULTS

Over 60% of participants worked 12 or more hours per day. The mean daily roundtrip commuting time was 1.82 h. Longer daily commutes, nonstandard work schedules, less sleep on workdays, and lack of employer policies were associated with one or more risky driving-related outcomes.

CONCLUSIONS

Implementation and evaluation of OGE employer policies and programs to limit long work hours, reduce long daily commutes, promote sufficient sleep, and reduce drowsy driving among U.S. OGE workers are needed.

Shift work and insulin resistance (HOMA-IR) among professional drivers

BACKGROUND: Shift work may be associated with insulin resistance. OBJECTIVE: This study aimed to investigate the potential association between shift work and the homeostatic model assessment of insulin resistance (HOMA-IR) index in professional drivers. METHOD: A total of four hundred fifty-three professional drivers were invited to participate in the study within a periodic medical examination in the occupational setting. One hundred seventy-seven daytime workers were compared with 175 night shifts and 101 early morning shift drivers. Demographic, occupational, and medical examination including blood pressure, anthropometric data was assessed. Measurement of serum insulin, fasting blood glucose and lipid profile were done for all drivers. RESULTS: Compared with day workers, night shift and early morning shift drivers displayed higher levels of HOMA-IR. Metabolic syndrome was found to be significantly increased in night workers. In linear regression analysis, insulin resistance was correlated with shift work independently of demographic and occupational characteristics. CONCLUSION: The study revealed that shift work could be a risk factor in developing the risk of metabolic syndrome and insulin resistance. Suggestively, health strategies such as structured lifestyle counseling in occupational health settings are warranted to improve and modify cardiometabolic risk factors.

The effect of evening light on circadian-related outcomes: A systematic review

Bright light exposure at night can help workers adapt to their shift schedules, but there has been relatively little research on evening light. We conducted a systematic review of studies that manipulated light exposure in the evening (broadly defined as 16:00-22:00) before real or simulated night shifts. Across the five eligible studies, evening light produced phase delays in melatonin, body temperature, and sleep propensity; it also improved sleep quality, sleep duration, memory, and work performance. There were mixed effects for mood, no changes in sleepiness, and no negative effects. The confidence in these results ranged from moderate for physiological markers of circadian phase delays to very low for mood. Future studies should compare the relative effectiveness and safety of evening versus night-time light exposure. Overall, the benefits of evening light for shift workers are tentative yet promising.

Effects of whole-body vibration on driver drowsiness: A review

INTRODUCTION

Whole-body vibration has direct impacts on driver vigilance by increasing physical and cognitive stress on the driver, which leads to drowsiness, fatigue and road traffic accidents. Although sleep deprivation, sleep apnoea and alcohol consumption can also lead to driver drowsiness, exposure to steady vibration is the factor most readily controlled by changes to vehicle design, yet it has received comparatively less attention.

METHODS

This review investigated interrelationships between the various components of whole-body vibration and the physiological and cognitive parameters that lead to driver drowsiness, as well as the effects of vibration parameters (frequency, amplitude, waveform and duration). Vibrations transmitted to the driver body from the vehicle floor and/or seat have been considered for this review, whereas hand-arm vibration, shocks, acute or transient vibration were excluded from consideration.

RESULTS

Drowsiness is affected by interactions between the frequency, amplitude, waveform and duration of the vibration. Under optimal conditions, whole-body vibration can induce significant drowsiness within 30 min. Low frequency whole-body vibrations, particularly vibrations of 4-10 Hz, are most effective at inducing drowsiness. This review notes some limitations of current studies and suggests directions for future research.

CONCLUSIONS

This review demonstrated a strong causal link exists between whole-body vibration and driver drowsiness. Since driver drowsiness has been established to be a significant contributor to motor vehicle accidents, research is needed to identify ways to minimise the components of whole-body vibration that contribute to drowsiness, as well as devising more effective ways to counteract drowsiness.

PRACTICAL APPLICATIONS

By raising awareness of the vibrational factors that contribute to drowsiness, manufacturers will be prompted to design vehicles that reduce the influence of these factors.

Fatigue in NTSB-investigations 2013-2019: evidence of accidents and injuries

ABSTRACTThis study updates the prevalence of operator fatigue as a causative factor in accidents investigated by the National Transportation Safety Board (NTSB) and the associated injury severity in fatigue-related accidents. 394 investigations were analyzed and 12% of them were identified fatigue. The prevalence of fatigue varied among the transportation modes, ranging from 28% of aviation to 7% of marine. Most fatigue-related accidents (48%) occurred during late night or morning. Compared to non-fatigued operators, fatigued operators were more involved in severe or fatal injuries (odds ratio (OR)  =  2.30; 95% confidence interval (CI) [1.66, 2.95]) and to injure non-operators (OR = 3.32; 95% CI [2.70, 3.95]). Obstructive sleep apnea (OSA) was identified as a probable cause, contributing cause, or finding in 15% of fatigued-related accidents, and 85.7% of these accidents, the operator met OSA screening criteria. Thus, opportunities remain for preventing fatigue-related accidents, including through more systematic operator screening for OSA.

Efficacy of Dietary Supplements on Sleep Quality and Daytime Function of Shift Workers: A Systematic Review and Meta-Analysis

Background

Dietary supplements (DSs) may be useful for managing shift work disorder. But the efficiency of outcomes in clinical trials using simulated shift work populations as subjects is controversial. This review explores the potential role of DSs for improving sleep quality, daily functioning, and mood among shift workers in the real world.

Methods

A related literature search was conducted in PubMed, Web of Science, Embase, and Cochrane Library databases from their inception to July 2021. Information was collected on “shift work,” “irregular working hours,” “night shift,” “dietary supplements,” and “nutraceutical research data.” Sleep quality-related scales were the primary outcome measures. The meta-analysis was conducted using RevMan 5.4 (Cochrane Collaboration, London, England) and Stata 15.0 (StataCorp, LLC, College Station, TX, USA). Heterogeneity was examined by using I2 statistics, and publication bias was assessed via Egger's regression test.

Results

Twelve studies, which involved 917 participants, met the inclusion criteria. The DS groups had significant improvement in sleep quality scores (8 randomized controlled trials [RCTs]: p = 0.04; standard mean difference (SMD), −0.45 [−0.88 to −0.03]) and daytime function (7 RCTs: p = 0.02; SMD, −0.50 [−0.92 to −0.08]). The DS groups did not have a significant improvement in psychomotor vigilance (4 RCTs: p = 0.25; SMD, 0.52 [−0.36 to 1.41]), depression (5 RCTs: p = 0.14; SMD, −0.19 [−0.45 to 0.06]), or anxiety (4 RCTs: p = 0.27; SMD, −0.23 [−0.65 to 0.18]). All RCTs suggested a positive safety profile for DSs.

Conclusions

The findings of this meta-analysis indicated DSs may be beneficial for improving sleep quality and daytime function in shift workers. Although there is a wide range of DSs, the small amount of literature included for each type does not allow for subgroup analysis to be used to eliminate high heterogeneity. We have not yet included literatures on other languages either. Given these limitations of the study, there is still a need for more well-designed randomized controlled trials so that our review can be updated in the future to make the results more conclusive.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=273558, PROSPERO: CRD42021273558.

Comparison of Work-Related Stress in Cluster of Workers' Suicides in Korea: Analysis of Industrial Accident Compensation Insurance, 2010-2017

Background: There is limited research on the heterogeneity of worker suicides. We compared differences in workers’ suicides by clustering suicide deaths. Methods: From 2010 to 2017, 353 suicide deaths were claimed in the Industrial Accident Compensation Insurance; variables were coded using a standardized methodology. A two-step cluster analysis classified the clusters based on demographic and employment conditions. Details of the suicide, clinical variables, personal stresses, and work-related stresses were compared using the chi-square test and one-way analysis of variance. Results: We identified five clusters and they differed particularly in work-related stress. “Responsibility-burdened type” experienced excessive responsibility as managers; “role-changed type” experienced a sudden and unpredictable role change as clerks or sales workers; “risk-exposed type” experienced physical risk factors at work (working alone, outdoors, and in shifts) as machine operating and assembling workers, or craft and related trades workers; “job-insecurity type” experienced unstable employment (irregular, nonpermanent) as elementary or service workers; “workplace-violence type” was mainly unmarried women who lived alone, and experienced interpersonal conflict and violence as professionals and related workers. There were no differences between clusters in clinical variables (except problem drinking) and personal stresses. Conclusion: Interventions to alleviate work-related stress in worker clusters are needed to prevent suicide in workers.

Digging for data: How sleep is losing out to roster design, sleep disorders, and lifestyle factors

Shift workers employed at a remote mining operation may experience sleep loss, impaired alertness, and consequently negative health and safety outcomes. This study determined the sleep behaviors and prevalence of risk for sleep disorders among shift workers; and quantified alertness for a roster cycle. Sleep duration was significantly less following; night shift by 77 ± 7 min and day shift by 30 ± 7 min. The wake after sleep onset was less by 23 ± 3 min for night shifts and 22 ± 3 min for day shifts (p < 0.05 for all). The prevalence of risk for sleep apnea was 31%, insomnia was 8%, and shiftwork disorder was 44%. Average alertness for all working hours was 75%. Shiftwork in remote mining operations is a significant factor that leads to sleep loss and reduced alertness, which is exacerbated by the high prevalence of risk for sleep disorders.

Disturbance of the Circadian System in Shift Work and Its Health Impact

The various non-standard schedules required of shift workers force abrupt changes in the timing of sleep and light-dark exposure. These changes result in disturbances of the endogenous circadian system and its misalignment with the environment. Simulated night-shift experiments and field-based studies with shift workers both indicate that the circadian system is resistant to adaptation from a day- to a night-oriented schedule, as determined by a lack of substantial phase shifts over multiple days in centrally controlled rhythms, such as those of melatonin and cortisol. There is evidence that disruption of the circadian system caused by night-shift work results not only in a misalignment between the circadian system and the external light-dark cycle, but also in a state of internal desynchronization between various levels of the circadian system. This is the case between rhythms controlled by the central circadian pacemaker and clock genes expression in tissues such as peripheral blood mononuclear cells, hair follicle cells, and oral mucosa cells. The disruptive effects of atypical work schedules extend beyond the expression profile of canonical circadian clock genes and affects other transcripts of the human genome. In general, after several days of living at night, most rhythmic transcripts in the human genome remain adjusted to a day-oriented schedule, with dampened group amplitudes. In contrast to circadian clock genes and rhythmic transcripts, metabolomics studies revealed that most metabolites shift by several hours when working nights, thus leading to their misalignment with the circadian system. Altogether, these circadian and sleep-wake disturbances emphasize the all-encompassing impact of night-shift work, and can contribute to the increased risk of various medical conditions. Here, we review the latest scientific evidence regarding the effects of atypical work schedules on the circadian system, sleep and alertness of shift-working populations, and discuss their potential clinical impacts.

CE: Nurses Are More Exhausted Than Ever: What Should We Do About It?

ABSTRACT

For nurses, the challenges posed by demanding work environments and schedules often lead to fatigue, and this can be exacerbated during crises like the COVID-19 pandemic. In this article, the authors discuss causes and challenges of nurse fatigue and consider several evidence-based strategies and solutions for individual nurses and organizations. Barriers to implementation, including a negative workplace culture and inadequate staffing, are also described, and several resources are presented.

European NCAP Program Developments to Address Driver Distraction, Drowsiness and Sudden Sickness

Driver distraction and drowsiness remain significant contributors to death and serious injury on our roads and are long standing issues in road safety strategies around the world. With developments in automotive technology, including driver monitoring, there are now more options available for automotive manufactures to mitigate risks associated with driver state. Such developments in Occupant Status Monitoring (OSM) are being incorporated into the European New Car Assessment Programme (Euro NCAP) Safety Assist protocols. The requirements for OSM technologies are discussed along two dimensions: detection difficulty and behavioral complexity. More capable solutions will be able to provide higher levels of system availability, being the proportion of time a system could provide protection to the driver, and will be able to capture a greater proportion of complex real-word driver behavior. The testing approach could initially propose testing using both a dossier of evidence provided by the Original Equipment Manufacturer (OEM) alongside selected use of track testing. More capable systems will not rely only on warning strategies but will also include intervention strategies when a driver is not attentive. The roadmap for future OSM protocol development could consider a range of known and emerging safety risks including driving while intoxicated by alcohol or drugs, cognitive distraction, and the driver engagement requirements for supervision and take-over performance with assisted and automated driving features.

On-road driving impairment following sleep deprivation differs according to age

Impaired driving performance due to sleep loss is a major contributor to motor-vehicle crashes, fatalities, and serious injuries. As on-road, fully-instrumented studies of drowsy driving have largely focused on young drivers, we examined the impact of sleep loss on driving performance and physiological drowsiness in both younger and older drivers of working age. Sixteen ‘younger’ adults (M = 24.3 ± 3.1 years [21–33 years], 9 males) and seventeen ‘older’ adults (M = 57.3 ± 5.2, [50–65 years], 9 males) undertook two 2 h drives on a closed-loop track in an instrumented vehicle with a qualified instructor following (i) 8 h sleep opportunity the night prior (well-rested), and (ii) after 29-h of total sleep deprivation (TSD). Following TSD, both age groups displayed increased subjective sleepiness and lane departures (p < 0.05), with younger drivers exhibiting 7.37 × more lane departures, and 11 × greater risk of near crash events following sleep loss. While older drivers exhibited a 3.5 × more lane departures following sleep loss (p = 0.008), they did not have a significant increase in near-crash events (3/34 drives). Compared to older adults, younger adults had 3.1 × more lane departures (p = < 0.001), and more near crash events (79% versus 21%, p = 0.007). Ocular measures of drowsiness, including blink duration, number of long eye closures and PERCLOS increased following sleep loss for younger adults only (p < 0.05). These results suggest that for older working-aged adults, driving impairments observed following sleep loss may not be due to falling asleep. Future work should examine whether this is attributed to other consequences of sleep loss, such as inattention or distraction from the road.

Sleepiness and safety at work among night shift NHS nurses

BACKGROUND

Sleepiness associated with night shift working (NSW) is known to adversely affect workers' health and well-being. It has been associated with adverse safety outcomes and is a recognized workplace hazard among healthcare workers.

AIMS

This study was aimed to assess the prevalence of self-reported sleepiness in NSW nurses and midwives. This study also explored the consequences of sleepiness on safety at work and driving.

METHODS

A cross-sectional study of NSW nurses and midwives was conducted at an National Health Service (NHS) hospital trust from 16 March 2020 to 1 June 2020. Data were collected by online questionnaire and included information on demographics, shift work and safety aspects. Sleepiness was assessed with the Epworth Sleepiness Scale (ESS).

RESULTS

Data collection coincided with the first coronavirus pandemic peak in England. Out of 1985 eligible NSW nurses and midwives, 229 participated in the study, with a response rate of 12%. The prevalence of sleepiness was 28%. Following a night shift, 49% of nurses reported nodding off at the wheel and 44% reported a near-miss car accident in past 12 months. An abnormal ESS score was significantly associated with near-miss car accidents (odds ratio [OR] 2.75, 95% confidence interval [CI] 1.31-5.77) and with low confidence in undertaking complex tasks at night (OR 2.64, 95% CI 1.20-5.84).

CONCLUSIONS

More than a quarter of NSW nurses and midwives reported excessive daytime sleepiness although, due to the low response rate, this may not be representative. Adverse driving events were common. Elevated ESS scores correlated well with safety issues relating to work and driving.

Winter Weather-Related Crashes during the Commute to Work: An Opportunity for Total Worker Health®

Background: The ways workers interface with their workplace and work are changing. These changes provide challenges and opportunities for health and safety professionals attempting to improve worker wellbeing for the future of work. For many workers, the morning commute, an activity typically outside the scope of workplace policies, is the most hazardous portion of the day. The hazard increases if workers are required to drive during winter weather or in other hazardous conditions in order to adhere to strict workplace start times. This research describes the role winter weather plays during the morning commute, demonstrating the need for organizational design and work arrangements that improve safety during the commute to work. Methods: Crash data from the Iowa Department of Transportation for the years 2013–2017 was linked to county level characteristics from the American Community Survey. Crashes were characterized by 30-min time intervals. The likelihood of the crash involving winter weather as a contributing circumstance was compared across time-intervals. Results: Winter weather was more likely to contribute to crashes during the commuting hours compared to 11:00 to 11:59 am. Winter weather was most frequently a contributing circumstance during 8:00–8:29 a.m. (OR = 2.21 95% CI: 1.93–2.52). Conclusions: Winter weather plays a role in crashes during commuting hours. Workplaces can adopt policies for flexible work start times or for telecommuting to empower workers to avoid hazardous driving conditions.

The pupillary light reflex (PLR) as a marker for the ability to work or drive - a feasibility study

Background

The PLR (pupillary light reflex) can be a marker for pathological medical conditions, such as neurodegenerative or mental health disorders and diseases as well as marker for physiological alterations, such as age, sex or iris color. PLR alterations have been described in people after alcohol consumption, as well. However, the effect of sleep deprivation on PLR parameters is still under debate.

Methods

The aim of this study was to investigate the feasibility of PLR measurements in sleep-deprived and alcohol-exposed participants. In addition, we wanted to identify PLR parameters that were altered by sleep deprivation and alcohol exposure.

Results

Altogether n = 50 participants have been included in this study. Differences in the PLR parameters initial diameter (d_init), latency (∆t_lat), acceleration (∆t_a), contraction velocity (ϑ_con), quarter dilatation velocity (ϑ_1/4dil), half dilatation time (∆t_1/2), and the line integral (L(0.3500)) have been evaluated between baseline, sleep deprivation, as well as alcohol exposure. In a generalized linear mixed models design, we could observe statistically significant associations between the type of exposure and the PLR parameters half dilatation time and half dilatation time after the first light pulse (all p < 0.05). The participants’ latency showed a significant association in dependence of the type of exposure after the second light pulse (p < 0.05).

Conclusion

Our study delivers first promising results to further develop devices that may identify conditions that impair the ability to work or drive.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12995-021-00330-2.

The impact of 7-hour and 11-hour rest breaks between shifts on heavy vehicle truck drivers' sleep, alertness and naturalistic driving performance

BACKGROUND

An inadequate rest break between shifts may contribute to driver sleepiness. This study assessed whether extending the major rest break between shifts from 7-hours (Australian industry standard) to 11-hours, improved drivers' sleep, alertness and naturalistic driving performance.

METHODS

17 heavy vehicle drivers (16 male) were recruited to complete two conditions. Each condition comprised two 13-hour shifts, separated by either a 7- or 11-hour rest break. The initial 13-hour shift was the drivers' regular work. The rest break and following 13-hour shift were simulated. The simulated shift included 5-hours of naturalistic driving with measures of subjective sleepiness, physiological alertness (ocular and electroencephalogram) and performance (steering and lane departures).

RESULTS

13 drivers provided useable data. Total sleep during the rest break was greater in the 11-hour than the 7-hour condition (median hours [25^th to 75^th percentile] 6.59 [6.23, 7.23] vs. 5.07 [4.46, 5.38], p = 0.008). During the simulated shift subjective sleepiness was marginally better for the 11-hour condition (mean Karolinska Sleepiness Scale [95^th CI] = 4.52 [3.98, 5.07] vs. 5.12 [4.56, 5.68], p = 0.009). During the drive, ocular and vehicle metrics were improved for the 11-hour condition (p<0.05). Contrary to expectations, mean lane departures p/hour were increased during the 11-hour condition (1.34 [-0.38,3.07] vs. 0.63 [-0.2,1.47], p = 0.027).

CONCLUSIONS

Extending the major rest between shifts substantially increases sleep duration and has a modest positive impact on driver alertness and performance. Future work should replicate the study in a larger sample size to improve generalisability and assess the impact of consecutive 7-hour major rest breaks.

I think I'm sleepy, therefore I am - Awareness of sleepiness while driving: A systematic review

Driver drowsiness contributes to 10-20% of motor vehicle crashes. To reduce crash risk, ideally drivers would be aware of the drowsy state and cease driving. The extent to which drivers can accurately identify sleepiness remains under much debate. We systematically examined whether individuals are aware of sleepiness while driving, and whether this accurately reflects driving impairment, using meta-analyses and narrative review. Within this scope, there is high variability in measures of subjective sleepiness, driving performance and physiologically-derived drowsiness, and statistical analyses. Thirty-four simulated/naturalistic driving studies were reviewed. To summarise, drivers were aware of sleepiness, and this was associated to physiological drowsiness and driving impairment, such that high levels of sleepiness significantly predicted crash events and lane deviations. Subjective sleepiness was more strongly correlated (i) with physiological drowsiness compared to driving outcomes; (ii) under simulated driving conditions compared to naturalistic drives; and (iii) when examined using the Karolinska sleepiness scale (KSS) compared to other measures. Gaps remain in relation to how age, sex, and varying degrees of sleep loss may influence this association. This review provides evidence that drivers are aware of drowsiness while driving, and stopping driving when feeling 'sleepy' may significantly reduce crash risk.

An evaluation and comparison of commercial driver sleepiness detection technology: a rapid review

Objective. Sleepiness-related motor vehicle crashes, caused by lack of sleep or driving during night-time hours, often result in serious injury or fatality. Sleepiness detection technology is rapidly emerging as a sleepiness risk mitigation strategy for drivers. Continuous monitoring technologies assess and alert to driver sleepiness in real-time, while fit for duty technologies provide a single assessment of sleepiness state. The aim of this rapid review was to evaluate and compare sleepiness detection technologies in relation to specifications, cost, target consumer group and validity.Approach. We evaluated a range of sleepiness detection technologies suitable for consumer groups ranging from regular drivers in private vehicles through to work-related drivers within large businesses.Main results. Continuous monitoring technologies typically ranged between $100 and $3000 AUD and had ongoing monthly costs for telematics functionality and manager alerts. Fit for duty technologies had either a one-off purchase cost or a monthly subscription cost. Of concern, the majority of commercial continuous monitoring technologies lacked scientific validation. While some technologies had promising findings in terms of their ability to detect and reduce driver sleepiness, further validation work is required. Field studies that evaluate the sensitivity and specificity of technology alerts under conditions that are regularly experienced by drivers are necessary. Additionally, there is a need for longitudinal naturalistic driving studies to determine whether sleepiness detection technologies actually reduce sleepiness-related crashes or near-crashes.Significance. There is an abundance of sleepiness detection technologies on the market, but a majority lacked validation. There is a need for these technologies and their validation to be regulated by a driver safety body. Otherwise, consumers will base their technology choices on cost and features, rather than the ability to save lives.

Microneedle Array Electrode-Based Wearable EMG System for Detection of Driver Drowsiness through Steering Wheel Grip

Driver drowsiness is a major cause of fatal accidents throughout the world. Recently, some studies have investigated steering wheel grip force-based alternative methods for detecting driver drowsiness. In this study, a driver drowsiness detection system was developed by investigating the electromyography (EMG) signal of the muscles involved in steering wheel grip during driving. The EMG signal was measured from the forearm position of the driver during a one-hour interactive driving task. Additionally, the participant’s drowsiness level was also measured to investigate the relationship between muscle activity and driver’s drowsiness level. Frequency domain analysis was performed using the short-time Fourier transform (STFT) and spectrogram to assess the frequency response of the resultant signal. An EMG signal magnitude-based driver drowsiness detection and alertness algorithm is also proposed. The algorithm detects weak muscle activity by detecting the fall in EMG signal magnitude due to an increase in driver drowsiness. The previously presented microneedle electrode (MNE) was used to acquire the EMG signal and compared with the signal obtained using silver-silver chloride (Ag/AgCl) wet electrodes. The results indicated that during the driving task, participants’ drowsiness level increased while the activity of the muscles involved in steering wheel grip decreased concurrently over time. Frequency domain analysis showed that the frequency components shifted from the high to low-frequency spectrum during the one-hour driving task. The proposed algorithm showed good performance for the detection of low muscle activity in real time. MNE showed highly comparable results with dry Ag/AgCl electrodes, which confirm its use for EMG signal monitoring. The overall results indicate that the presented method has good potential to be used as a driver’s drowsiness detection and alertness system.

Relations between Stress and Depressive Symptoms in Psychiatric Nurses: The Mediating Effects of Sleep Quality and Occupational Burnout

This study examines the parallel multiple mediators of quality of sleep and occupational burnout between perceived stress and depressive symptoms in psychiatric nurses. Nurses are more likely to experience depression, anxiety, decreased job satisfaction, and reduced organizational loyalty as a result of the stressful work environment and heavy workload. A total of 248 psychiatric ward (PW) nurses participated in this cross-sectional survey study. Structural equation modelling was used for data analysis. In the model of parallel multiple mediators for depressive symptoms, quality of sleep and occupational burnout played mediating roles, and these two mediators strengthened the effect of stress on depressive symptoms, with the final model showing a good fit. Stress, occupational burnout, and quality of sleep explained 46.0% of the variance in psychiatric nurses’ depressive symptoms. Stress had no significantly direct effect on psychiatric nurses’ depressive symptoms, but it had a completed mediation effect on their depressive symptoms through occupational burnout and quality of sleep. This study showed that reduction of occupational burnout and improvement of quality of sleep play important roles against depressive symptoms among PW nurses. Healthcare managers should provide PW nurses with a better environment for improving quality of sleep and reducing occupational burnout.

The Impact of Commutes, Work Schedules, and Sleep on Near-Crashes during Nurses' Post Shift-Work Commutes: A Naturalistic Driving Study

OCCUPATIONAL APPLICATIONSDriving and survey data were collected from nurses following the night-shift and analyzed with logistic regression and frequency analysis. The analyses showed that prior near-crashes and drive length contributed significantly to near-crashes. The frequency analysis showed that most near-crashes occurred on major roadways, including principal arterials, major collectors, and interstates, within the first 15 minutes of the drive. These results highlight the urgent need for countermeasures to prevent drowsy driving incidents among night-shift nurses. Specifically, nurses and hospital systems should focus on countermeasures that encourage taking a break on the post work commute and those that can intervene during the drive. This may include the use of educational programs to teach nurses the importance of adequate rest or taking a break to sleep during their drive home, or technology that can recognize drowsiness and alert nurses of their drowsiness levels, prompting them to take a break.

The Analysis of Occurrences Associated with Air Traffic Volume and Air Traffic Controllers' Alertness for Fatigue Risk Management

Fatigue is an inevitable hazard in the provision of air traffic services and it has the potential to degrade human performance leading to occurrences. The International Civil Aviation Organization (ICAO) requires air navigation services which providers establish fatigue risk management systems (FRMS) based on scientific principles for the purpose of managing fatigue. To develop effective FRMSs, it is important to investigate the relationship between traffic volume, air traffic management occurrences, and fatigue. Fifty-seven qualified ATCOs from a European Air Navigation Services provider participated in this research by providing data indicating their alertness levels over the course of a 24-hour period. ATCOs' fatigue data were compared against the total of 153 occurrences and 962,328 air traffic volumes from the Eurocontrol TOKAI incident database in 2019. The result demonstrated that ATCO fatigue levels are not the main contributory factor associated with air traffic management occurrences, although fatigue did impact ATCOs' performance. High traffic volume increases ATCO cognitive task load that can surpass available attention resources leading to occurrences. Furthermore, human resilience drives ATCOs to maintain operational safety though they suffer from circadian fatigue. Consequently, FRMS appropriately implemented can be used to mitigate the effects of fatigue. First-line countermeasure strategies should focus on enough rest breaks and roster schedule optimization; secondary strategies should focus on monitoring ATCOs' task loads that may induce fatigue. It is vital to consider traffic volume and ATCOs' alertness levels when implementing effective fatigue risk management protocols.

Awareness of sleepiness: Temporal dynamics of subjective and objective sleepiness

We systematically examined the temporal relationships between subjective sleepiness and both physiological drowsiness and performance impairment in a controlled laboratory setting. Eighteen healthy young adults (8 women; M_AGE  = 21.44 ± 3.24 years) underwent 40 hr of extended wakefulness, completing a bihourly Karolinska Sleepiness Scale (KSS) and 10-min Psychomotor Vigilance Task (PVT). Microsleeps and slow eye movements (SEMs) were scored during the PVT. KSS scores increased 3 hr prior to performance impairment (p < .001) and 4-6 hr prior to physiological sleepiness (p < .001). There were strong within-subject correlations between KSS and PVT lapses (r = 0.75, p < .001) and physiological drowsiness (r > 0.60, p < .001). Between-subjects product-moment correlations were more modest but showed a significant positive increase across time awake, suggesting that subjective sleepiness and objective outcomes were more tightly correlated after sleep loss. Cross-correlations showed significant positive correlations at 0-lag (p < .034); however, a high proportion of participants showed maximal correlations at positive lags, suggesting KSS was associated with future objective impairment. Within individuals, subjective sleepiness was highly correlated with objective impairment, between-subject correlations were more modest, possibly due to interindividual vulnerability to sleep loss. These results suggest that subjective sleepiness represents an inbuilt early warning system for subsequent drowsiness and performance impairment.