Occupational fatigue, underlying sleep and circadian mechanisms, and approaches to fatigue risk management

The Relationship between Occupational Fatigue and Well-Being: The Moderating Effect of Unhealthy Eating Behaviour

Tech giants are large, well-known internet and technology companies. Employees of such companies are generally expected to work fast and for long periods of time, causing them to experience high occupational fatigue. The relationship between occupational fatigue and well-being is complex. Furthermore, in the context of the workplace, unhealthy eating behaviour may be used as a mechanism to cope with fatigue and stress. This study explored the relationship between occupational fatigue, well-being and unhealthy eating behaviour within this specific professional population. Study 1 used qualitative research methods, in which in-depth interviews were conducted with staff working at 13 tech giants in Shenzhen, China (N = 50). The findings revealed that work-related stress and occupational fatigue are common among employees working for tech giants. Additionally, factors such as unhealthy eating behaviour, workload, working hours and workplace interpersonal relationships were found to influence occupational well-being. Study 2 involved a cross-sessional survey of 237 employees of tech giants. The results indicated that occupational fatigue negatively impacts occupational well-being and that unhealthy eating behaviours play a moderating role between occupational fatigue and occupational well-being. These findings highlight the significance of adopting appropriate measures to improve the situation and cope with the effects of occupational fatigue by managing unhealthy eating behaviours.

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.

The effects of shift-work schedules on the sleep, health, safety, and quality of life of police employees during the COVID-19 pandemic

Introduction

The negative health and safety consequences of police fatigue are increasingly recognized as a critical problem. This study's objective was to measure the effects of different shift schedules on police employee health, safety, and quality of life.

Methods

A cross sectional research design surveyed employees (N = 319) from a large, U.S. west coast municipal police service during the fall of 2020. The survey was made up of a battery of validated instruments designed to assess dimensions of health and wellness (e.g., sleep, health, safety, and quality of life).

Results

We found 77.4% of police employees had poor sleep quality, 25.7% had excessive daytime sleepiness, 50.2% had PTSD symptoms, 51.9% had depressive symptoms, and 40.8% had anxiety symptoms. Working night shifts significantly decreased sleep quality and increased excessive sleepiness. Furthermore, employees working night shifts were significantly more likely to report falling asleep at the wheel while driving home than employees working other shifts.

Discussion

Our findings have implications for interventions designed to promote police employee sleep health, quality of life, and worker safety. We urge researchers and practitioners alike to target night shift workers, to help mitigate these risks.

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.

Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society

CITATION

Risks associated with fatigue that accumulates during work shifts have historically been managed through working time arrangements that specify fixed maximum durations of work shifts and minimum durations of time off. By themselves, such arrangements are not sufficient to curb risks to performance, safety, and health caused by misalignment between work schedules and the biological regulation of waking alertness and sleep. Science-based approaches for determining shift duration and mitigating associated risks, while addressing operational needs, require: (1) a recognition of the factors contributing to fatigue and fatigue-related risks; (2) an understanding of evidence-based countermeasures that may reduce fatigue and/or fatigue-related risks; and (3) an informed approach to selecting workplace-specific strategies for managing work hours. We propose a series of guiding principles to assist stakeholders with designing a shift duration decision-making process that effectively balances the need to meet operational demands with the need to manage fatigue-related risks.

The effects of three consecutive 12-hour shifts on cognition, sleepiness, and domains of nursing performance in day and night shift nurses: A quasi-experimental study

BACKGROUND

Healthcare systems have widely adopted consecutive 12 h day and night shifts for nurses, but the effects of these shifts on cognition, sleepiness, and nursing performance remains understudied.

OBJECTIVE

To determine the extent of changes in cognition and sleepiness in nurses working three consecutive 12 h shifts, quantify the respective impacts of these changes on different aspects of nursing performance, and investigate individual differences in all measures.

DESIGN

A quasi-experimental, between-within design collected data from nurses between November 2018 and March 2020. The between-groups component was comprised of day shift nurses vs. night shift nurses, while the within-groups component was comprised of two separate test sessions for each nurse: one immediately following a third consecutive shift (fatigued) and one after three consecutive days off work (rested).

SETTING

Participants were tested in a northwestern US university's nursing simulation laboratory.

PARTICIPANTS

A volunteer sample of 94 registered nurses involved in direct patient care working 12 h shifts were recruited from two local hospitals.

METHODS

Simulated nursing performance was measured in seven separate domains and an aggregate score from the Creighton Competence and Evaluation Inventory, covering both lower- and higher-level constructs like procedural skills, assessment, decision-making, etc. Cognition and sleepiness were assessed through measures of sustained attention, predicted cognitive effectiveness, and subjective sleepiness.

RESULTS

In our 94 nurses, individual differences in all our measures varied from trivial to extensive. For six domains of performance and the aggregate score there were no significant differences in means across groups or conditions. For the seventh, Communication skills were lower for night nurses than day nurses, but this effect was small. After three consecutive shifts, sustained attention and predicted cognitive effectiveness decreased, and subjective sleepiness increased. Predicted cognitive effectiveness was particularly low for fatigued night nurses relative to other conditions and was positively correlated with Communication while controlling for other predictors.

CONCLUSIONS AND RELEVANCE

Nurses maintained their levels of performance for all domains after three consecutive shifts. Individual differences in predicted cognitive effectiveness could account for variation in performance by shift type for Communication skills but for no other domain of performance. Communication skills and predicted cognitive effectiveness may interest researchers in the development of fatigue-mitigation strategies for night nurses, but our findings also suggest that more sensitive measures of performance may be necessary to capture other meaningful effects of long, consecutive shifts-if any-on patient care. Tweetable abstract: The effects of three consecutive 12 h shifts on cognition, sleepiness, and domains of nursing performance in day and night shift nurses: A quasi-experimental study.

Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society

Risks associated with fatigue that accumulates during work shifts have historically been managed through working time arrangements that specify fixed maximum durations of work shifts and minimum durations of time off. By themselves, such arrangements are not sufficient to curb risks to performance, safety, and health caused by misalignment between work schedules and the biological regulation of waking alertness and sleep. Science-based approaches for determining shift duration and mitigating associated risks, while addressing operational needs, require: (1) a recognition of the factors contributing to fatigue and fatigue-related risks; (2) an understanding of evidence-based countermeasures that may reduce fatigue and/or fatigue-related risks; and (3) an informed approach to selecting workplace-specific strategies for managing work hours. We propose a series of guiding principles to assist stakeholders with designing a shift duration decision-making process that effectively balances the need to meet operational demands with the need to manage fatigue-related risks.

How much sleep do you need? A comprehensive review of fatigue related impairment and the capacity to work or drive safely

In developed countries, deaths attributable to driving or working while intoxicated have steadily declined over recent decades. In part, this has been due to (a) public education programs about the risks and (b) the deterrence value associated with penalties and prosecutions based on an individual being 'deemed impaired' if they exceed a proscribed level of blood alcohol or drug concentration while driving/working. In contrast, the relative proportion of fatigue-related accidents have remained stubbornly high despite significant public and workplace education. As such, it may be useful to introduce the legal principle of 'deemed impaired' with respect to fatigue and/or sleep loss. A comprehensive review of the impairment and accident literature was performed, including 44 relevant publications. Findings from this review suggests that a driver or worker might reasonably be 'deemed impaired' once the amount of sleep falls below five hours in the prior 24. Building on the legal principles first outlined in recent New Jersey legislation (Maggie's Law), this review argues that an individual can reasonably be 'deemed impaired' based on prior sleep wake behaviour. In Maggie's Law, a driver can be indirectly 'deemed impaired' if they have not slept in the prior 24 h. Based on the extant literature, we argue that, relative to drug and alcohol intoxication, this may be overly conservative. While roadside measurement of fatigue and prior sleep-wake behavior is not yet possible, we suggest that public education programs should provide specific guidance on the amount of sleep required and that post-accident forensic examination of prior sleep wake behaviours may help the community to determine unsafe behaviours and liability more objectively than is currently the case.

Fatigue and sleep patterns among Canadian wildland firefighters during a 17-day fire line deployment

The purpose of this investigation was to enhance our understanding of the effects the current British Columbia Wildfire Service (BCWS) firefighting schedule have on the development of fatigue and sleep deprivation. This was a cohort study that objectively and subjectively measured sleep quantity, sleep quality, and fatigue throughout a 17-day British Columbia wildland firefighting deployment. Wildland firefighters (n = 30) conducted daily testing of sleep and fatigue measures during 14 days of activity on the fire line and three days immediately post deployment during their three-day rest period, for a total of 17 days of data collection. Sleep was assessed using wrist-worn actigraphy (ActiGraph LLC, Pensacola, FL) and subjective sleep questionnaires. Fatigue was assessed using subjective fatigue questionnaires and cognitive performance through the psychomotor vigilance test. Total sleep time was less on fire days (M = 6.6 h ± 49.2 min) compared to non-fire days (M = 6.8 h ± 92.2 min). Participants performed poorer on cognitive performance tests, (p = 0.288), and reported being significantly sleepier, (p = 0.038), toward the end of their 17-day deployment compared to day 1. Participants continued to report high levels of sleepiness, fatigue, and poor quality of sleep on their rest days compared to their fire line days. Working 14 consecutive days was associated with increased levels of objective fatigue and suboptimal sleep in wildland firefighters. Wildland firefighters reported significantly higher levels of fatigue and decreased alertness with increasing days on deployment and these levels did not improve following a three-day rest period.

Nursing Students' Sleep Patterns and Perceptions of Safe Practice During Their Entrée to Shift Work

Background: The transition into shift work represents a critical and challenging time point in a nurse's career. The purpose of this study was to describe nursing students' sleep patterns and perceptions of safe practice during their first semester of clinical rotations. Method: Repeated measures pertaining to the sleep patterns of 19 full-time junior undergraduate nursing students were measured before, during, and after their first clinical rotations. Sleep was measured using wrist activity monitors and sleep diaries for seven consecutive days at each time period. Students' "self-efficacy" or belief in their ability to provide safe practice was measured for (a) patient care (preventing adverse events to patients) and (b) occupational health (preventing occupational injuries to themselves) using Bandura's self-efficacy scales. Associations between students' sleep, sleepiness, and their perceptions of safe practice were explored. Results: Nursing students' self-efficacy scores regarding patient care (preventing adverse events) improved across the three time periods (from 80% before clinical rotation, to 84% during clinical rotation, to 87% after clinical rotation). Although lower overall, students' self-efficacy scores regarding occupational health (preventing occupational injuries to themselves) also improved across the three time periods (from 71% before clinical rotation, to 76% during clinical rotation, to 77% after clinical rotation). Furthermore, increased sleepiness significantly predicted lower self-efficacy scores for both patient care and occupational health. Conclusion/Application to Practice: Sleepiness can impair nursing students' confidence in their ability to practice safely.

An oculometrics-based biofeedback system to impede fatigue development during computer work: A proof-of-concept study

A biofeedback system may objectively identify fatigue and provide an individualized timing plan for micro-breaks. We developed and implemented a biofeedback system based on oculometrics using continuous recordings of eye movements and pupil dilations to moderate fatigue development in its early stages. Twenty healthy young participants (10 males and 10 females) performed a cyclic computer task for 31–35 min over two sessions: 1) self-triggered micro-breaks (manual sessions), and 2) biofeedback-triggered micro-breaks (automatic sessions). The sessions were held with one-week inter-session interval and in a counterbalanced order across participants. Each session involved 180 cycles of the computer task and after each 20 cycles (a segment), the task paused for 5-s to acquire perceived fatigue using Karolinska Sleepiness Scale (KSS). Following the pause, a 25-s micro-break involving seated exercises was carried out whether it was triggered by the biofeedback system following the detection of fatigue (KSS≥5) in the automatic sessions or by the participants in the manual sessions. National Aeronautics and Space Administration Task Load Index (NASA-TLX) was administered after sessions. The functioning core of the biofeedback system was based on a Decision Tree Ensemble model for fatigue classification, which was developed using an oculometrics dataset previously collected during the same computer task. The biofeedback system identified fatigue with a mean accuracy of approx. 70%. Perceived workload obtained from NASA-TLX was significantly lower in the automatic sessions compared with the manual sessions, p = 0.01 Cohen’s d_z = 0.89. The results give support to the effectiveness of integrating oculometrics-based biofeedback in timing plan of micro-breaks to impede fatigue development during computer work.

Drowsiness measures for commercial motor vehicle operations

Timely detection of drowsiness in Commercial Motor Vehicle (C MV) operations is necessary to reduce drowsiness-related CMV crashes. This is relevant for manual driving and, paradoxically, even more so with increasing levels of driving automation. Measures available for drowsiness detection vary in reliability, validity, usability, and effectiveness. Passively recorded physiologic measures such as electroencephalography (EEG) and a variety of ocular parameters tend to accurately identify states of considerable drowsiness, but are limited in their potential to detect lower levels of drowsiness. They also do not correlate well with measures of driver performance. Objective measures of vigilant attention performance capture drowsiness reliably, but they require active driver involvement in a performance task and are prone to confounds from distraction and (lack of) motivation. Embedded performance measures of actual driving, such as lane deviation, have been found to correlate with physiologic and vigilance performance measures, yet to what extent drowsiness levels can be derived from them reliably remains a topic of investigation. Transient effects from external circumstances and behaviors - such as task load, light exposure, physical activity, and caffeine intake - may mask a driver's underlying state of drowsiness. Also, drivers differ in the degree to which drowsiness affects their driving performance, based on trait vulnerability as well as age. This paper provides a broad overview of the current science pertinent to a range of drowsiness measures, with an emphasis on those that may be most relevant for CMV operations. There is a need for smart technologies that in a transparent manner combine different measurement modalities with mathematical representations of the neurobiological processes driving drowsiness, that account for various mediators and confounds, and that are appropriately adapted to the individual driver. The research for and development of such technologies requires a multi-disciplinary approach and significant resources, but is technically within reach.

Cognitive flexibility: A distinct element of performance impairment due to sleep deprivation

In around-the-clock operations, reduced alertness due to circadian misalignment and sleep loss causes performance impairment, which can lead to catastrophic errors and accidents. There is mounting evidence that performance on different tasks is differentially affected, but the general principles underlying this differentiation are not well understood. One factor that may be particularly relevant is the degree to which tasks require executive control, that is, control over the initiation, monitoring, and termination of actions in order to achieve goals. A key aspect of this is cognitive flexibility, i.e., the deployment of cognitive control resources to adapt to changes in events. Loss of cognitive flexibility due to sleep deprivation has been attributed to "feedback blunting," meaning that feedback on behavioral outcomes has reduced salience - and that feedback is therefore less effective at driving behavior modification under changing circumstances. The cognitive mechanisms underlying feedback blunting are as yet unknown. Here we present data from an experiment that investigated the effects of sleep deprivation on performance after an unexpected reversal of stimulus-response mappings, requiring cognitive flexibility to maintain good performance. Nineteen healthy young adults completed a 4-day in-laboratory study. Subjects were randomized to either a total sleep deprivation condition (n = 11) or a control condition (n = 8). Athree-phase reversal learning decision task was administered at baseline, and again after 30.5 h of sleep deprivation, or matching well-rested control. The task was based on a go/no go task paradigm, in which stimuli were assigned to either a go (response) set or a no go (no response) set. Each phase of the task included four stimuli (two in the go set and two in the no go set). After each stimulus presentation, subjects could make a response within 750 ms or withhold their response. They were then shown feedback on the accuracy of their response. In phase 1 of the task, subjects were explicitly told which stimuli were assigned to the go and no go sets. In phases 2 and 3, new stimuli were used that were different from those used in phase 1. Subjects were not explicitly told the go/no go mappings and were instead required to use accuracy feedback to learn which stimuli were in the go and nogo sets. Phase 3 continued directly from phase 2 and retained the same stimuli as in phase 2, but there was an unannounced reversal of the stimulus-response mappings. Task results confirmed that sleep deprivation resulted in loss of cognitive flexibility through feedback blunting, and that this effect was not produced solely by (1) general performance impairment because of overwhelming sleep drive; (2) reduced working memory resources available to perform the task; (3) incomplete learning of stimulus-response mappings before the unannounced reversal; or (4) interference with stimulus identification through lapses in vigilant attention. Overall, the results suggest that sleep deprivation causes a fundamental problem with dynamic attentional control. This element of performance impairment due to sleep deprivation appears to be distinct from vigilant attention deficits, and represents a particularly significant challenge for fatigue risk management.

Sleep inertia during a simulated 6-h on/6-h off fixed split duty schedule

Sleep inertia is a safety concern for shift workers returning to work soon after waking up. Split duty schedules offer an alternative to longer shift periods, but introduce additional wake-ups and may therefore increase risk of sleep inertia. This study investigated sleep inertia across a split duty schedule. Sixteen participants (age range 21-36 years; 10 females) participated in a 9-day laboratory study with two baseline nights (10 h time in bed, [TIB]), four 24-h periods of a 6-h on/6-h off split duty schedule (5-h TIB in off period; 10-h TIB per 24 h) and two recovery nights. Two complementary rosters were evaluated, with the timing of sleep and wake alternating between the two rosters (2 am/2 pm wake-up roster versus 8 am/8 pm wake-up roster). At 2, 17, 32 and 47 min after scheduled awakening, participants completed an 8-min inertia test bout, which included a 3-min psychomotor vigilance test (PVT-B), a 3-min Digit-Symbol Substitution Task (DSST), the Karolinska Sleepiness Scale (KSS), and the Samn-Perelli Fatigue Scale (SP-Fatigue). Further testing occurred every 2 h during scheduled wakefulness. Performance was consistently degraded and subjective sleepiness/fatigue was consistently increased during the inertia testing period as compared to other testing times. Morning wake-ups (2 am and 8 am) were associated with higher levels of sleep inertia than later wake-ups (2 pm and 8 pm). These results suggest that split duty workers should recognise the potential for sleep inertia after waking, especially during the morning hours.

Fatiguing effect of multiple take-offs and landings in regional airline operations

Fatigue is a risk factor for flight performance and safety in commercial aviation. In US commercial aviation, to help to curb fatigue, the maximum duration of flight duty periods is regulated based on the scheduled start time and the number of flight segments to be flown. There is scientific support for regulating maximum duty duration based on scheduled start time; fatigue is well established to be modulated by circadian rhythms. However, it has not been established scientifically whether the number of flight segments, per se, affects fatigue. To address this science gap, we conducted a randomized, counterbalanced, cross-over study with 24 active-duty regional airline pilots. Objective and subjective fatigue was compared between a 9-hour duty day with multiple take-offs and landings versus a duty day of equal duration with a single take-off and landing. To standardize experimental conditions and isolate the fatiguing effect of the number of segments flown, the entire duty schedules were carried out in a high-fidelity, moving-base, full-flight, regional jet flight simulator. Steps were taken to maintain operational realism, including simulated airplane inspections and acceptance checks, use of realistic dispatch releases and airport charts, real-world air traffic control interactions, etc. During each of the two duty days, 10 fatigue test bouts were administered, which included a 10-minute Psychomotor Vigilance Test (PVT) assessment of objective fatigue and Samn-Perelli (SP) and Karolinska Sleepiness Scale (KSS) assessments of subjective sleepiness/fatigue. Results showed a greater build-up of objective and subjective fatigue in the multi-segment duty day than in the single-segment duty day. With duty start time and duration and other variables that could impact fatigue levels held constant, the greater build-up of fatigue in the multi-segment duty day was attributable specifically to the difference in the number of flight segments flown. Compared to findings in previously published laboratory studies of simulated night shifts and nighttime sleep deprivation, the magnitude of the fatiguing effect of the multiple take-offs and landings was modest. Ratings of flight performance were not significantly reduced for the simulated multi-segment duty day. The US duty and flight time regulations for commercial aviation shorten the maximum duty duration in multi-segment operations by up to 25% depending on the duty start time. The present results represent an important first step in understanding fatigue in multi-segment operations, and provide support for the number of flight segments as a relevant factor in regulating maximum duty duration. Nonetheless, based on our fatigue results, a more moderate reduction in maximum duty duration as a function of the number of flight segments might be considered. However, further research is needed to include investigation of flight safety, and to extend our findings to nighttime operations.

Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback

STUDY OBJECTIVES

To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback.

DESIGN

Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered.

SETTING

Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring.

SUBJECTS

Twenty-six subjects (22-40 y of age; 10 women).

INTERVENTIONS

Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls.

MEASUREMENTS AND RESULTS

Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making.

CONCLUSIONS

Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information.