What Factors Influence the Sleep of On-call Workers?

The Influence of Emergency Call Volume on Occupational Workload and Sleep Quality in Urban Firefighters

OBJECTIVE

The aim of the study is to determine the impact of emergency call volume on exertion, autonomic activity, and sleep among urban structural firefighters.

METHODS

Thirty-four firefighters wore a wrist-based monitor to track sleep and autonomic parameters and rated their level of perceived exertion (Borg Rating of Perceived Exertion) and subjective sleepiness after a 24-hour shift. Predictive variables included total run time and total run time after 11:59 PM.

RESULTS

Total run time and sleep duration accounted for Borg Rating of Perceived Exertion and subjective sleepiness, while total run time and total run time after 11:59 PM accounted for sleep durations on-duty.

CONCLUSIONS

The current results suggest that emergency call volume is associated with indicators of exertion and sleep. As such, call volume tracking is an important consideration for departments to ensure personnel readiness and wellness and provide a method of tracking the occupational demands experienced by firefighters on-duty.

Differences in shift and work-related patterns between metropolitan and regional/rural healthcare shift workers and the occupational health and safety risks

OBJECTIVES

To explore if there are differences in shift patterns and work-related factors between metropolitan and regional/rural healthcare shift workers and their risk of poor sleep and mental health. Furthermore, explore whether these factors impact on medical errors, workplace and car/near car accidents.

DESIGN

A cross-sectional study.

SETTING

An anonymous online survey of healthcare shift workers in Australia.

PARTICIPANTS

A total of 403 nurses, midwives and paramedics completed the survey.

MAIN OUTCOME MEASURES

Sample characteristics, employment location, shift work-related features, sleep and mental health measurements, workplace accidents, medical errors and car/near car accident post shift.

RESULTS

Regional/rural healthcare shift workers were significantly older, had more years' experience, worked more nights, on-call and hours per week. Those in metropolitan areas took significantly longer (minutes) to travel to work, had higher levels of anxiety, increased risk of shift work disorder, reported significantly more workplace accidents and were more likely to have a car/near car accident when commuting home post shift. Both groups reported ~25% having a medical error in the past year. Workplace accidents were related to more on-call shifts and poor sleep quality. Medical errors were associated with fewer years' experience, more evening shifts and increased stress. Car accidents were associated with metropolitan location and increased depression.

CONCLUSION

Differences in work-related factors between metropolitan and regional/rural healthcare shift workers were observed. Some of these factors contributed to occupational health and safety risks. Further exploration is needed to understand how to reduce occupational health and safety risks, and improve employee and patient safety both in both regional/rural and metropolitan areas.

Daily variation in sleepiness among firefighters while working the 24/48 and 48/96 shift schedules

Objective

To assess the daily relationship between prior-night total sleep time (TST) and next-day, afternoon sleep propensity among firefighters operating from two popular fire department shift schedules.

Methods

Dataset included 22 firefighters (24/48 shift schedule) and 20 firefighters (48/96 shift schedule). Daily TST was assessed using actigraphy and daily sleep propensity was assessed using the Epworth Sleepiness Scale (ESS), completed every afternoon.

Results

Separate one-way repeated measures ANOVA indicated statistically significant differences among daily sleep propensity within each shift schedule. Separate Pearson product moment correlations indicated moderate relationships between prior-night TST and next-day, afternoon sleep propensity.

Conclusion

When firefighters slept less, sleep propensity the following day increased. Least TSTs occurred on nights prior to commuting suggesting firefighters likely begin shifts without sufficient sleep and drive home without sufficient sleep, then experience greatest sleep propensity.

A preliminary framework for managing sleep inertia in occupational settings

Sleep inertia, the temporary period of impairment experienced upon waking, is a safety hazard that has been implicated in serious work-related incidents resulting in injuries as well as the loss of life and assets. As such, sleep inertia warrants formal management in industries where personnel are required to undertake their role soon after waking (e.g. emergency services, engineers, and health care). At present, there is a lack of practical, evidence-based guidance on how sleep inertia could be formally managed at an organizational level. We propose a preliminary framework for managing sleep inertia based on the translation of research findings into specific work procedure modifications/control mechanisms. Within the framework, work procedure modifications/control mechanisms to manage sleep inertia are organized into three levels: (1) modifications/controls that eliminate the chance of sleep inertia, (2) modifications/controls that reduce sleep inertia severity, and (3) modifications/controls that manage the risk of errors during sleep inertia. Practical considerations, limitations, and areas of further research are highlighted for each modification/control to help determine how readily each control measure could be implemented by industries at present. A guide for organizations to use this preliminary framework of sleep inertia management is put forward, as well as the next research priorities to strengthen the utility and evidence base of the framework. This paper is part of the Sleep and Circadian Rhythms: Management of Fatigue in Occupational Settings Collection.

On-call work and depressive mood: A cross-sectional survey among rural migrant workers in China

Introduction

With the rapid development of China's "gig economy," the on-call work model has grown increasingly prevalent in China and has attracted a large number of rural migrant workers with its low employment threshold. However, this irregular employment mode may negatively impact the mental health of workers.

Methods

This paper uses an ordinal logistic regression model to study the relationship between Chinese rural migrant workers' on-call work and their depression.

Results

The results showed that after controlling for relevant variables, the odds ratio of depressive mood among rural migrant workers engaged in on-call work was 1.22 (95% CI 1.04-1.43) compared with rural migrant workers who did not need to be on call. In further heterogeneity research, we found that on-call work is more likely to aggravate the depression risk of rural migrant workers who are highly dependent on the internet and have low-wage incomes.

Discussion

This research suggests that appropriate measures should be taken to mitigate the negative impact of on-call work on the mental health of rural migrant workers, and more attention needs to be paid to the mental health of lower salaried and gig workers. This paper provides a valuable sample of Chinese rural migrant workers for theoretical research on the relationship between on-call work and mental health and confirms the relationship between the two. These results contribute new ideas to the theory and practice of psychological crisis intervention aimed at Chinese rural migrant workers.

Intra-Tour Variation of Firefighter Sleep Duration and Sleep-Wake Cycle within the 24/48 and 48/96 Shift Schedules

OBJECTIVE

The purpose of this paper is to investigate intra-tour variation in total sleep time (TST) and sleep-wake cycle among US firefighters working the 24 hours on and 48 hours off shift schedule (24/48) and the 48 hours on and 96 hours off shift schedule (48/96).

METHODS

Twenty-four firefighters were recruited for this sleep study and were evaluated over 18 days during a 24/48 shift schedule and again 6 months after firefighters transitioned to a 48/96 shift schedule. The primary outcome variables included TST, measured by actigraphy, and sleep-wake cycle (in-bed time and sleep offset) using the Emergency Services Sleep Diary.

RESULTS

Firefighters experienced intra-tour variations in TST and sleep offset. The least TST occurred at home prior to starting shift on the 24/48 and 48/96 schedules (5.80 hours and 5.66 hours, respectively). The second least TST occurred the night preceding shift end (5.84 hours and 5.81 hours, respectively). In contrast to in-bed time, sleep offset varied throughout the schedule and was found to correlate with TST. In addition, shift start/end time appears to be responsible for advanced sleep offset.

CONCLUSION

Results indicate that firefighters' sleep is complex and should not be reduced to singular averages. In both schedules, firefighters arrived at work with insufficient sleep, received insufficient sleep while on shift, and would commute home with insufficient sleep. These findings can inform future firefighter sleep research by accounting for intra-tour variations.

Comparison of adult shift and non-shift workers’ physical activity and sleep behaviours: cross-sectional analysis from the Household Income and Labour Dynamics of Australia (HILDA) cohort

Aim

This study compares the pattern of physical activity and sleep between shift and non-shift workers using a novel physical activity–sleep index. By drawing from a diverse occupational population, this research aims to reduce any occupational specific biases which are prevalent in shift-work research.

Subject and methods

Current data included 7607 workers (shift workers n = 832) from the Household Income and Labour Dynamics of Australia cohort study. The combined physical activity–sleep index comprised three physical activity components and three sleep health components: achieving moderate (1pt) or high (2pts) IPAQ classification; accruing ≥30% of physical activity as vigorous intensity (1pt); meeting sleep duration recommendations on a work night (1pt); and non-work night (1pt); and reporting no insomnia symptoms (1pt) (higher score = healthy behaviour, max. 6). Generalised linear modelling was used to compare behaviours of shift and non-shift workers.

Results

Findings showed shift workers reported significantly lower activity–sleep scores (3.59 vs 3.73, p < 0.001), lower sleep behaviour sub-score (2.01 vs. 2.22, p < 0.001) and were more likely to report insomnia symptoms (p < 0.001) compared to non-shift workers. No difference was reported for overall physical activity (shift = 1.58 vs. non-shift = 1.51, p = 0.383).

Conclusion

When viewed in conjunction using the combined activity–sleep index, shift workers displayed significantly poorer combined behaviours when compared to non-shift workers.

Does knowledge of sleep hygiene recommendations match behaviour in Australian shift workers? A cross-sectional study

OBJECTIVES

Shiftworkers routinely obtain inadequate sleep, which has major health consequences. Sleep hygiene describes a range of behaviours, lifestyle and environmental factors that can improve sleep. To date, limited research has examined sleep hygiene in shiftworkers. This study aimed to assess the sociodemographic and behavioural correlates of sleep hygiene knowledge and engagement with sleep hygiene practices in Australian shiftworkers.

STUDY DESIGN

An online, cross-sectional survey.

SETTING AND PARTICIPANTS

Australian adults from across multiple industries (n=588) who work shift work.

MEASURES

The online survey included questions regarding sleep hygiene knowledge and questions from modified versions of the Pittsburgh Sleep Quality Index and Sleep Hygiene Index.

RESULTS

Of the 588 participants, 52.9% reported having heard of 'sleep hygiene'. Of these participants, 77.5% reported understanding the term moderately, extremely or very well. Engagement with each sleep hygiene practice was varied. Common sleep hygiene practices were controlling the bedroom environment (eg, a cool, dark and quiet bedroom). Less common practices were avoiding light as bedtime approaches. Logistic regressions revealed that shiftworkers who had heard of sleep hygiene were more likely to engage in sleep hygiene practices and had better sleep quality compared with those who had not heard of sleep hygiene. Increased engagement in sleep hygiene practices did not predict the likelihood of individuals reporting better sleep quality.

CONCLUSIONS

Shiftworkers demonstrated varied knowledge, understanding and engagement with individual sleep hygiene practices. Future research should focus on the development of sleep hygiene interventions that accommodate the unique challenges of shift work to optimise sleep.

A Time to Rest, a Time to Dine: Sleep, Time-Restricted Eating, and Cardiometabolic Health

Cardiovascular disease (CVD) poses a serious health and economic burden worldwide. Modifiable lifestyle factors are a focus of research into reducing the burden of CVD, with diet as one of the most investigated factors. Specifically, the timing and regularity of food intake is an emerging research area, with approaches such as time-restricted eating (TRE) receiving much attention. TRE involves shortening the time available to eat across the day and is associated with improved CVD outcomes compared with longer eating windows. However, studies that have examined TRE have not considered the impact of sleep on CVD outcomes despite recent evidence showing that sleep duration can influence the timing and amount of food eaten. In this article, we argue that as TRE and sleep influence each other, and influence the same cardiometabolic parameters, experiencing inadequate sleep may attenuate any positive impact TRE has on CVD. We examine the relationship between TRE and CVD, with sleep as a potential mediator in this relationship, and propose a research agenda to investigate this relationship. This will provide necessary evidence to inform future interventions aimed at reducing the burden of CVD.

"I Want to Be Safe and Not Still Half Asleep": Exploring Practical Countermeasures to Manage the Risk of Sleep Inertia for Emergency Service Personnel Using a Mixed Methods Approach

PURPOSE

The aim of this exploratory cross-sectional mixed methods study was to determine 1) whether sleep inertia, the temporary state of impaired vigilance performance upon waking, is perceived to be a concern by emergency service personnel, 2) what strategies are currently used by emergency service workplaces to manage sleep inertia, 3) the barriers to implementing reactive sleep inertia countermeasures, and 4) what strategies personnel suggest to manage sleep inertia.

PARTICIPANTS AND METHODS

A sample (n = 92) of employed and volunteer Australian emergency service personnel (fire and rescue, ambulance, police, state-based rescue and recovery personnel) completed an online survey. Data collected included demographic variables and work context, experiences of sleep inertia in the emergency role, barriers to sleep inertia countermeasures, and existing workplace sleep inertia countermeasures and recommendations. Quantitative data were analysed using descriptive statistics, and qualitative data were thematically analysed.

RESULTS

Approximately 67% of participants expressed concern about sleep inertia when responding in their emergency role. Despite this, there were few strategies to manage sleep inertia in the workplace. One major barrier identified was a lack of time in being able to implement sleep inertia countermeasures. Fatigue management strategies, such as reducing on-call periods, and operational changes, such as screening calls to reduce false alarms, were suggested by participants as potential strategies to manage sleep inertia.

CONCLUSION

Sleep inertia is a concern for emergency service personnel and thus more research is required to determine effective sleep inertia management strategies to reduce the risks associated with sleep inertia and improve personnel safety and those in their care. In addition, future studies could investigate strategies to integrate reactive sleep inertia countermeasures into the emergency response procedure.

Who is 'on-call' in Australia? A new classification approach for on-call employment in future population-level studies

BACKGROUND

On-call research and guidance materials typically focus on 'traditional' on-call work (e.g., emergency services, healthcare). However, given the increasing prevalence of non-standard employment arrangements (e.g., gig work and casualisation), it is likely that a proportion of individuals who describe themselves as being on-call are not included in current on-call literature. This study therefore aimed to describe the current sociodemographic and work characteristics of Australian on-call workers.

METHODS

A survey of 2044 adults assessed sociodemographic and work arrangements. Of this population, 1057 individuals were workforce participants, who were asked to provide information regarding any on-call work they performed over the last three months, occupation type, weekly work hours, and the presence or absence of non-standard work conditions.

RESULTS

Of respondents who were working, 45.5% reported working at least one day on-call in the previous month. There was a high prevalence of on-call work in younger respondents (63.1% of participants aged 18-24 years), and those who worked multiple jobs and more weekly work hours. Additionally, high prevalence rates of on-call work were reported by machinery operators, drivers, community and personal service workers, sales workers, and high-level managers.

CONCLUSIONS

These data suggest that on-call work is more prevalent than previously recorded and is likely to refer to a broad set of employment arrangements. Current classification systems may therefore be inadequate for population-level research. A taxonomy for the classification of on-call work is proposed, incorporating traditional on-call work, gig economy work, relief, or unscheduled work, and out of hours work.

Perception versus Reality: The Relationship between Subjective and Objective Measures of Sleep When On-call under Simulated Laboratory Conditions

BACKGROUND

On-call working arrangements have been shown to negatively impact sleep. However, workers may perceive their sleep to be worse than it actually is. The aim of this study was to compare participants' pre- and post-sleep estimates of sleep duration and sleep quality with objectively measured sleep when on-call under laboratory conditions.

PARTICIPANTS

72 healthy, adult males.

METHODS

Analyses were performed on three interrelated studies, all of which consisted of four nights in a sleep laboratory. Following adaptation and baseline nights were two on-call nights (sleep opportunity 23:00 h - 07:00 h). Before and after each sleep opportunity, participants provided subjective estimates of sleep. Sleep was objectively measured using polysomnography.

RESULTS

Estimated sleep duration (6.74 ± 1.13 h) and sleep onset latency (20.55 ± 14.85 min) were significantly poorer than objectively measured sleep outcomes (sleep duration 7.21 ± 1.25 h; sleep latency 13.20 ± 10.06 min). Of the variance in post-sleep estimated sleep duration, 14% was associated with objectively measured minutes of N3 (R²Δ = 0.55) and REM (R²Δ = 0.75). Additionally, 14% of post-sleep sleep quality estimation variance was associated with minutes of N2 (R²Δ = 0.60) and N3 (R²Δ = 0.79), measured by polysomnography.

CONCLUSIONS

Some objective measures of sleep were associated with subjective estimates of sleep duration and sleep quality. However, individuals may overestimate sleep onset latency and underestimate sleep duration during on-call periods. It may be beneficial for on-call workers to actively reflect on feelings of fatigue/alertness for workplace fatigue management, rather than relying solely on estimates of sleep.

Are Individuals with Low Trait Anxiety Better Suited to On-Call Work?

Research has indicated that individuals with certain traits may be better suited to shiftwork and non-standard working arrangements. However, no research has investigated how individual differences impact on-call outcomes. As such, this study investigated the impact of trait anxiety on sleep and performance outcomes on-call. Seventy male participants (20–35 years) completed an adaptation night, a control night, and two on-call nights in a laboratory. Trait anxiety was determined using the State Trait Anxiety Inventory (STAI) X-2, and participants completed the STAI X-1 prior to bed each night to assess state anxiety. Sleep was measured using polysomnography and quantitative electroencephalographic analysis. Performance was assessed using a 10-min psychomotor vigilance task (PVT) performed each day at 0930, 1200, 1430 and 1700 h. Data pooled from three separate but inter-related studies was used for these analyses. Results indicated that the effects of trait anxiety on state anxiety, sleep and performance outcomes on-call were generally limited. These findings suggest that on-call outcomes are not negatively affected by higher levels of trait anxiety.

The effect of a short burst of exercise during the night on subsequent sleep

When on-call workers wake during the night to perform work duties, they may experience reduced alertness and impaired performance as a result of sleep inertia. After performing their duties, on-call workers may have the opportunity to return to sleep. Thus, it is important that sleep inertia countermeasures do not affect subsequent sleep. Exercise may be a suitable countermeasure; however, the impact on subsequent sleep is untested. Healthy participants (n = 15) completed three conditions in a counterbalanced order: sedentary, low-intensity exercise or high-intensity exercise, performed for 2 min upon awakening. Sleep was recorded 2 hr later using polysomnography, the Karolinska Sleepiness Scale was administered to measure subjective sleepiness, and core body temperature was measured continuously. Results indicate there was no effect of condition on most sleep variables; however, three variables had small differences, with longer total sleep time (p = .006), higher sleep efficiency (p = .006) and shorter N3 latency (p < .001) in the low-intensity exercise condition. There was no difference in subjective sleepiness (p = .124) or core body temperature (p = .216) 90 min after the exercise intervention. These results indicate that using a short burst of exercise to counteract sleep inertia when woken during the night may be a suitable countermeasure for on-call workers who not only need to be alert upon waking but also need quality sleep when returning to bed. Future research could include participants of other ages and health statuses to investigate whether the results are generalizable.