The effects of extended nap periods on cognitive, physiological and subjective responses under simulated night shift conditions

Effect of napping on a bean bag chair on sleep stage, muscle activity, and heart rate variability

Background

Although ample evidence has demonstrated that daytime napping is beneficial for health and cognitive performance, bedding for napping has not yet been scientifically investigated.

Objectives

To explore the effect of a bean bag chair on daytime napping and physiological parameters related to sleep.

Methods

Fourteen healthy participants were enrolled within the context of a randomized, single-blind, crossover study to evaluate the effects of a bean bag chair in comparison with those of a urethane chair manufactured to have a similar shape. Electroencephalogram, electromyogram, and heart rate variability were recorded and compared between wakefulness and napping.

Results

Electroencephalogram analyses revealed no significant differences in sleep architecture or frequency components; however, a significant decrease was found in electromyogram recordings in the trapezius muscle, which represents the neck region (p = 0.019). Additionally, a significant main effect of bedding in the low-frequency/high-frequency ratio (F[1,20] = 4.314, p = 0.037) was revealed.

Conclusions

These results suggest that napping in a bean bag chair may provide a comfortable napping environment involving muscle relaxation and proper regulation of the autonomic nervous function.

Differences in Daytime Activity Levels and Daytime Sleep Between Night and Day Duty: An Observational Study in Italian Orthopedic Nurses

Working nonstandard work schedules is often associated with increased sedentary behavior and risk of sleep disorders. Night shift workers are prone to accumulating sleep debt, which they recover by sleeping during the day. The effect on daytime activity levels is unknown. The present study aims to objectively assess whether daytime sleep could affect daytime activity levels of shift worker nurses, resulting in an accumulation of their activity debt differently between working and rest periods. The study population (N = 37; mean age 41.7 ± 9.1 years) was composed of orthopedic nurses working on a rotating schedule, including either a night shift (NS) or only day/afternoon shift (DS). Actigraph monitoring lasted both on the working and the rest period. For the NS nurses, the working period recorded higher daytime activity levels than the rest period, while daytime sleep during the working and rest periods was similar. Conversely, DS nurses showed higher daytime activity levels and shorter daytime sleep during the working period. NS nurses were less active than DS nurses during the working period, probably because NS tended to have a longer daytime sleep. During the rest period, daytime activity levels for both groups were decreased. For NS nurses, sleep recorded the better sleep parameters during the rest period, while sleep parameters did not show significant differences between the working and the rest periods in DS. During the working period, NS nurses slept worse than the DS nurses. Both groups tended to accumulate a debt in daytime activity levels during the rest period. While daytime sleep may be an excellent way to counteract sleep debt and increase sleep duration over 24 h period, on the other hand, it makes nurses less active.

Effect of shift work on fatigue and sleep in neonatal registrars

OBJECTIVE

We aimed to study fatigue and sleep in registrars working 12-hour rotating shifts in our tertiary neonatal intensive unit.

METHODS AND PARTICIPANTS

This study involved neonatal registrar's working day (08:00-21:00) and night (20:30-08:30) shifts. Participants maintained a sleep diary, answered a self-reported sleepiness questionnaire assessing subjective sleepiness, and performed a 10-minute psychomotor vigilance task (PVT) at the start and end of each shift. Primary outcomes: (1) Fatigue at the (i) "start vs end" of day and night shifts, (ii) end of the "day vs night" shifts, and (iii) end of "first vs last shift" in block of day and night shifts. (2) Duration and quality of sleep before the "day vs night" shifts. Mean reaction time (RTM), relative coefficient of variation (RTCV), and lapses (reaction time > 500ms) were used as measures of fatigue on PVT. Secondary outcome: Subjective sleepiness (self-reported sleepiness questionnaire) at the 'start vs end" of day and night shifts.

RESULTS

Fifteen registrars completed the study. Acuity was comparable for all shifts. (1) Psychomotor responses were impaired at the end vs start of day shifts [RTM (p = 0.014), lapses (p = 0.001)], end vs start of night shifts [RTM (p = 0.007), RTCV (p = 0.003), lapses (p<0.001)] and end of night vs day shifts [RTM (p = 0.007), RTCV (p = 0.046), lapses (p = 0.001)]. Only lapses were significantly increased at the end of the last (p = 0.013) vs first shift (p = 0.009) in a block of day and night shifts. (2) Duration of sleep before the night (p = 0.019) and consecutive night shifts was decreased significantly (p = 0.034). Subjective sleepiness worsened after day (p = 0.014) and night shifts (p<0.001).

CONCLUSION

Fatigue worsened after the 12-hour day and night shifts with a greater change after night shifts. Lapses increased after block of day and night shifts. Sleep was decreased before night shifts. Our findings need to be confirmed in larger studies.

Napping and cognitive performance during night shifts: a systematic review and meta-analysis

Study Objectives

To examine the benefits of napping during night shifts on cognitive performance.

Methods

Medline, Cochrane Library, Science direct, and Embase databases were searched up to July 1, 2019. Cognitive performance during night shifts, both before and following napping or under control conditions (no nap), in working-aged adults, were analyzed by time and by type of cognitive function (executive function, attention, instrumental function, and memory). Estimates were pooled using random-effects meta-analysis.

Results

A total of 18 articles (6 in real-work and 12 in laboratory) with a total of 494 participants were included. The mean nap duration was 41.6 ± 28.3 min, occurring between 12.00 am and 4.10 am, with a mean time set at 2.12 am. Cognitive performance did not differ at baseline between the groups (effect size 0.02, 95% CI −0.09 to 0.13). There was an overall improvement in performance following a nap compared to the control condition without a nap (0.25, 0.10 to 0.41). Positioning naps early in the night and activity (simulated work tasks) tended to improve cognitive performance (−0.57, −1.16 to 0.002, and 0.082, −0.04 to 0.33, respectively). The improvements were primarily seen 30 min after awakening. Only memory deteriorated immediately after awakening without an overall change in global cognitive performance.

Conclusion

Napping during night shifts seems to improve cognitive performance. Napping early in the night and activity may benefit cognitive performance over time. Considering lack of data in real work environments, further studies are warranted before preconizing napping during night shifts as a preventive strategy (safety, health, and economic outcomes).

Practice parameters for the use of actigraphy in the military operational context: the Walter Reed Army Institute of Research Operational Research Kit-Actigraphy (WORK-A)

BACKGROUND

The Walter Reed Army Institute of Research (WRAIR) Operational Research Kit-Actigraphy (WORK-A) is a set of unique practice parameters and actigraphy-derived measures for the analysis of operational military sleep patterns. The WORK-A draws on best practices from the literature and comprises 15 additional descriptive variables. Here, we demonstrate the WORK-A with a sample of United States Army Reserve Officers' Training Corps (ROTC) cadets (n = 286) during a month-long capstone pre-commissioning training exercise.

METHODS

The sleep of ROTC cadets (n = 286) was measured by Philips Actiwatch devices during the 31-day training exercise. The preliminary effectiveness of the WORK-A was tested by comparing differences in sleep measures collected by Actiwatches as calculated by Philips Actiware software against WORK-A-determined sleep measures and self-report sleep collected from a subset of ROTC cadets (n = 140).

RESULTS

Actiware sleep summary statistics were significantly different from WORK-A measures and self-report sleep (all P ≤ 0.001). Bedtimes and waketimes as determined by WORK-A major sleep intervals showed the best agreement with self-report bedtime (22:21 ± 1:30 vs. 22:13 ± 0:40, P = 0.21) and waketime (04:30 ± 2:17 vs. 04:31 ± 0:47, P = 0.68). Though still significantly different, the discrepancy was smaller between the WORK-A measure of time in bed (TIB) for major sleep intervals (352 ± 29 min) and self-report nightly sleep duration (337 ± 57 min, P = 0.006) than that between the WORK-A major TIB and Actiware TIB (177 ± 42, P ≤ 0.001).

CONCLUSIONS

Default actigraphy methods are not the most accurate methods for characterizing soldier sleep, but reliable methods for characterizing operational sleep patterns is a necessary first step in developing strategies to improve soldier readiness. The WORK-A addresses this knowledge gap by providing practice parameters and a robust variety of measures with which to profile sleep behavior in service members.