Sleep,Sleepiness, Fatigue,and Performance of 12-Hour-Shift Nurses

Nurses working 12-h shifts complain of fatigue and insufficient/poor-quality sleep. Objectively measured sleep times have not been often reported. This study describes sleep, sleepiness, fatigue, and neurobehavioral performance over three consecutive 12-h (day and night) shifts for hospital registered nurses. Sleep (actigraphy), sleepiness (Karolinska Sleepiness Scale [KSS]), and vigilance (Performance Vigilance Task [PVT]), were measured serially in 80 registered nurses (RNs). Occupational fatigue (Occupational Fatigue Exhaustion Recovery Scale [OFER]) was assessed at baseline. Sleep was short (mean 5.5?h) between shifts, with little difference between day shift (5.7?h) and night shift (5.4?h). Sleepiness scores were low overall (3 on a 1–9 scale, with higher score indicating greater sleepiness), with 45% of nurses having high level of sleepiness (score ?>?7) on at least one shift. Nurses were progressively sleepier each shift, and night nurses were sleepier toward the end of the shift compared to the beginning. There was extensive caffeine use, presumably to preserve or improve alertness. Fatigue was high in one-third of nurses, with intershift fatigue (not feeling recovered from previous shift at the start of the next shift) being most prominent. There were no statistically significant differences in mean reaction time between day/night shift, consecutive work shift, and time into shift. Lapsing was traitlike, with rare (39% of sample), moderate (53%), and frequent (8%) lapsers. Nurses accrue a considerable sleep debt while working successive 12-h shifts with accompanying fatigue and sleepiness. Certain nurses appear more vulnerable to sleep loss than others, as measured by attention lapses. (Author correspondence: jgeiger@son.umaryland.edu)     

Sleep, sleepiness, fatigue, and performance of 12-hour-shift nurses

Nurses working 12-h shifts complain of fatigue and insufficient/poor-quality sleep. Objectively measured sleep times have not been often reported. This study describes sleep, sleepiness, fatigue, and neurobehavioral performance over three consecutive 12-h (day and night) shifts for hospital registered nurses. Sleep (actigraphy), sleepiness (Karolinska Sleepiness Scale [KSS]), and vigilance (Performance Vigilance Task [PVT]), were measured serially in 80 registered nurses (RNs). Occupational fatigue (Occupational Fatigue Exhaustion Recovery Scale [OFER]) was assessed at baseline. Sleep was short (mean 5.5?h) between shifts, with little difference between day shift (5.7?h) and night shift (5.4?h). Sleepiness scores were low overall (3 on a 1-9 scale, with higher score indicating greater sleepiness), with 45% of nurses having high level of sleepiness (score >?7) on at least one shift. Nurses were progressively sleepier each shift, and night nurses were sleepier toward the end of the shift compared to the beginning. There was extensive caffeine use, presumably to preserve or improve alertness. Fatigue was high in one-third of nurses, with intershift fatigue (not feeling recovered from previous shift at the start of the next shift) being most prominent. There were no statistically significant differences in mean reaction time between day/night shift, consecutive work shift, and time into shift. Lapsing was traitlike, with rare (39% of sample), moderate (53%), and frequent (8%) lapsers. Nurses accrue a considerable sleep debt while working successive 12-h shifts with accompanying fatigue and sleepiness. Certain nurses appear more vulnerable to sleep loss than others, as measured by attention lapses.     

The effect of consecutive transmeridian flights on alertness,sleep–wake cycles and sleepiness: A case study

ABSTRACT

Travel across time zones disrupts circadian rhythms causing increased daytime sleepiness, impaired alertness and sleep disturbance. However, the effect of repeated consecutive transmeridian travel on sleep–wake cycles and circadian dynamics is unknown. The aim of this study was to investigate changes in alertness, sleep–wake schedule and sleepiness and predict circadian and sleep dynamics of an individual undergoing demanding transmeridian travel. A 47-year-old healthy male flew 16 international flights over 12 consecutive days. He maintained a sleep–wake schedule based on Sydney, Australia time (GMT + 10?h). The participant completed a sleep diary and wore an Actiwatch before, during and after the flights. Subjective alertness, fatigue and sleepiness were rated 4 hourly (08:00–00:00), if awake during the flights. A validated physiologically based mathematical model of arousal dynamics was used to further explore the dynamics and compare sleep time predictions with observational data and to estimate circadian phase changes. The participant completed 191?h and 159 736?km of flying and traversed a total of 144 time-zones. Total sleep time during the flights decreased (357.5?min actigraphy; 292.4?min diary) compared to baseline (430.8?min actigraphy; 472.1?min diary), predominately due to restricted sleep opportunities. The daily range of alertness, sleepiness and fatigue increased compared to baseline, with heightened fatigue towards the end of the flight schedule. The arousal dynamics model predicted sleep/wake states during and post travel with 88% and 95% agreement with sleep diary data. The circadian phase predicted a delay of only 34?min over the 16 transmeridian flights. Despite repeated changes in transmeridian travel direction and flight duration, the participant was able to maintain a stable sleep schedule aligned with the Sydney night. Modelling revealed only minor circadian misalignment during the flying period. This was likely due to the transitory time spent in the overseas airports that did not allow for resynchronisation to the new time zone. The robustness of the arousal model in the real-world was demonstrated for the first time using unique transmeridian travel.     

Time to wake up: No impact of COMT Val158Met gene variation on circadian preferences,arousal regulation and sleep

Dopamine has been implicated in the regulation of sleep–wake states and the circadian rhythm. However, there is no consensus on the impact of two established dopaminergic gene variants: the catechol-O-methyltransferase Val158Met (COMT Val158Met; rs4680) and the dopamine D4 receptor Exon III variable-number-of-tandem-repeat polymorphism (DRD4 VNTR). Pursuing a multi-method approach, we examined their potential effects on circadian preferences, arousal regulation and sleep. Subjects underwent a 7-day actigraphy assessment (SenseWear Pro3), a 20-minute resting EEG (analyzed using VIGALL 2.0) and a body mass index (BMI) assessment. Further, they completed the Morningness–Eveningness Questionnaire (MEQ), the Epworth Sleepiness Scale (ESS) and the Pittsburgh Sleep Quality Index (PSQI). The sample comprised 4625 subjects (19–82 years) genotyped for COMT Val158Met, and 689 elderly subjects (64–82 years) genotyped for DRD4 VNTR. The number of subjects varied across phenotypes. Power calculations revealed a minimum required phenotypic variance explained by genotype ranging between 0.5% and 1.5% for COMT Val158Met and between 3.3% and 6.0% for DRD4 VNTR. Analyses did not reveal significant genotype effects on MEQ, ESS, PSQI, BMI, actigraphy and EEG variables. Additionally, we found no compelling evidence in sex- and age-stratified subsamples. Few associations surpassed the threshold of nominal significance (p < .05), providing some indication for a link between DRD4 VNTR and daytime sleepiness. Taken together, in light of the statistical power obtained in the present study, our data particularly suggest no impact of the COMT Val158Met polymorphism on circadian preferences, arousal regulation and sleep. The suggestive link between DRD4 VNTR and daytime sleepiness, on the other hand, might be worth investigation in a sample enriched with younger adults.     

Examining courses of sleep quality and sleepiness in full 2 weeks on/2 weeks off offshore day shift rotations

ABSTRACT

To better understand sleep quality and sleepiness problems offshore, we examined courses of sleep quality and sleepiness in full 2-weeks on/2-weeks off offshore day shift rotations by comparing pre-offshore (1 week), offshore (2 weeks) and post-offshore (1 week) work periods. A longitudinal observational study was conducted among N=42 offshore workers. Sleep quality was measured subjectively with two daily questions and objectively with actigraphy, measuring: time in bed (TIB), total sleep time (TST), sleep latency (SL) and sleep efficiency percentage (SE%). Sleepiness was measured twice a day (morning and evening) with the Karolinska Sleepiness Scale. Changes in sleep and sleepiness parameters during the pre/post and offshore work periods were investigated using (generalized) linear mixed models. In the pre-offshore work period, courses of SE% significantly decreased (p=.038). During offshore work periods, the courses of evening sleepiness scores significantly increased (p<.001) and significantly decreased during post-offshore work periods (p=.004). During offshore work periods, TIB (p<.001) and TST (p<.001) were significantly shorter, SE% was significantly higher (p=.002), perceived sleep quality was significantly lower (p<.001) and level of rest after wake was significantly worse (p<.001) than during the pre- and post-offshore work periods. Morning sleepiness was significantly higher during offshore work periods (p=.015) and evening sleepiness was significantly higher in the post-offshore work period (p=.005) compared to the other periods. No significant changes in SL were observed. Courses of sleep quality and sleepiness parameters significantly changed during full 2-weeks on/2-weeks off offshore day shift rotation periods. These changes should be considered in offshore fatigue risk management programmes.     

A novel machine learning unsupervised algorithm for sleep/wake identification using actigraphy

ABSTRACT

Actigraphy is widely used in sleep studies but lacks a universal unsupervised algorithm for sleep/wake identification. An unsupervised algorithm is useful in large-scale population studies and in cases where polysomnography (PSG) is unavailable, as it does not require sleep outcome labels to train the model but utilizes information solely contained in actigraphy to learn sleep and wake characteristics and separate the two states. In this study, we proposed a machine learning unsupervised algorithm based on the Hidden Markov Model (HMM) for sleep/wake identification. The proposed algorithm is also an individualized approach that takes into account individual variabilities and analyzes each individual actigraphy profile separately to infer sleep and wake states. We used Actiwatch and PSG data from 43 individuals in the Multi-Ethnic Study of Atherosclerosis study to evaluate the method performance. Epoch-by-epoch comparisons and sleep variable comparisons were made between our algorithm, the unsupervised algorithm embedded in the Actiwatch software (AS), and the pre-trained supervised UCSD algorithm. Using PSG as the reference, the accuracy was 85.7% for HMM, 84.7% for AS, and 85.0% for UCSD. The sensitivity was 99.3%, 99.7%, and 98.9% for HMM, AS, and UCSD, respectively, and the specificity was 36.4%, 30.0%, and 31.7%, respectively. The Kappa statistic was 0.446 for HMM, 0.399 for AS, and 0.311 for UCSD, suggesting fair to moderate agreement between PSG and actigraphy. The Bland–Altman plots further show that the total sleep time, sleep latency, and sleep efficiency estimates by HMM were closer to PSG with narrower 95% limits of agreement than AS and UCSD. All three methods tend to overestimate sleep and underestimate wake compared to PSG. Our HMM approach is also able to differentiate relatively active and sedentary individuals by quantifying variabilities in activity counts: individuals with higher estimated activity variabilities tend to show more frequent sedentary behaviors. Our unsupervised data-driven HMM algorithm achieved better performance than the commonly used Actiwatch software algorithm and the pre-trained UCSD algorithm. HMM can help expand the application of actigraphy in cases where PSG is hard to acquire and supervised methods cannot be trained. In addition, the estimated HMM parameters can characterize individual activity patterns and sedentary tendencies that can be further utilized in downstream analysis.     

Cognitive functioning of female nurses during the night shift: The impact of age,clock time,time awake and subjective sleepiness

ABSTRACT

Decline in cognitive functioning in the workplace is a major concern for health care systems. Understanding factors associated with nighttime functioning is imperative for instituting organizational risk management policies and developing personalized countermeasures. The present study aims to identify individual factors associated with cognitive functioning during the night shift of hospital nurses working on irregular rotating-shift schedules. Ninety-two female nurses were recruited from 17 wards in two general hospitals, using convenience sampling by clusters. Inclusion criteria were working at least 28 h a week (75% of full time) and one night shift per week. Exclusion criteria were pregnancy, diagnosed sleep disorders or medical conditions that may affect sleep and/or function. Cognitive performance was measured during the middle (03:00 h) and at the end (07:00 h) of the night shift using the Digit Symbol Substitution Task (DSST) and the Letter Cancellation Task (LCT) over two night shifts. Subjective sleepiness was assessed by the Karolinska Sleepiness Scale (KSS) at the same time points. All participants completed a sociodemographic questionnaire, the Munich ChronoType Questionnaire for Shift-Workers (MCTQShift) and the Pittsburgh Sleep Quality Index (PSQI). Sleep duration 24 h before the night shift and time awake since last sleep opportunity were monitored by actigraphy. Univariate repeated measures ANOVA found main effects for clock time (p<0.001), age (p<0.05), time awake (p<0.05) and sleepiness (p<0.01) for DSST correct responses; main effects for clock time (p<0.001) and sleepiness (p<0.001) for LCT capacity; and main effects for clock time (p<0.001) and age (p<0.01) for LCT omission errors. All factors remained significant in a mixed-model analysis for DSST. Cognitive performance among hospital nurses is low during the middle of the night shift and increases at the end of the shift; decreased functioning is associated with increased subjective sleepiness, older age and prolonged time awake. Identifying factors contributing to performance during the night shift may provide a basis for the development of risk management policies and preventative interventions.     

Sleep and Sleepiness among Working and Non‐Working High School Evening Students

The aim of this study was to evaluate patterns of sleepiness, comparing working and non‐working students. The study was conducted on high school students attending evening classes (19:00–22:30 h) at a public school in São Paulo, Brazil. The study group consisted of working (n=51) and non‐working (n=41) students, aged 14–21 yrs. The students answered a questionnaire about working and living conditions and reported health symptoms and diseases. For seven consecutive days, actigraphy measurements were recorded, and the students also filled in a sleep diary. Sleepiness ratings were given six times per day, including upon waking and at bedtime, using the Karolinska Sleepiness Scale. Statistical analyses included three‐way ANOVA and t‐test. The mean sleep duration during weekdays was shorter among workers (7.2 h) than non‐workers (8.8 h) (t=4.34; p<.01). The mean duration of night awakenings was longer among workers on Tuesdays and Wednesdays (28.2 min) and shorter on Mondays (24.2 min) (t=2.57; p=.03). Among workers, mean napping duration was longer on Mondays and Tuesdays (89.9 min) (t=2.27; p=.03) but shorter on Fridays and Sundays (31.4 min) (t=3.13; p=.03). Sleep efficiency was lower on Fridays among non‐workers. Working students were moderately sleepier than non‐workers during the week and also during class on specific days: Mondays (13:00–15:00 h), Wednesdays (19:00–22:00 h), and Fridays (22:00–00:59 h). The study found that daytime sleepiness of workers is moderately higher in the evening. This might be due to a work effect, reducing the available time for sleep and shortening the sleep duration. Sleepiness and shorter sleep duration can have a negative impact on the quality of life and school development of high school students.     

Effects of 6/6 and 4/8 Watch Systems on Sleepiness among Bridge Officers

During the last ten years, severe sleepiness or falling asleep by watch keeping officers has been a direct or a contributing factor in a number of maritime accidents. This study examined the relationship between two watch systems and its impact on fatigue and sleepiness in bridge officers. A questionnaire and a sleep/work diary were sent to a representative sample of the Finnish Maritime Officer Association. In all, 185 bridge officers answered the questionnaire on sleep, work hours, and safety, including the Skogby Excessive Daytime Sleepiness index (SEDS); 42% of the bridge officers worked two 4 h watches (4/8) per day, while 26% worked two 6 h watches per day (6/6). Ninety‐five of the participants completed a sleep diary for seven consecutive days while at sea. The timing of the watch duties and sleep was recorded, as was subjective sleepiness every 2 h using the Karolinska Sleepiness Scale (KSS). 17.6% of the participants had fallen asleep at least once while on duty during their career. Compared to the 4/8 watch system, the officers working the 6/6 watch system reported shorter sleep durations, more frequent nodding‐off on duty (7.3% vs. 1.5%), and excessive sleepiness (32% vs. 16% with SEDS>14). Based on a logistic regression analysis, high SEDS was significantly related with probable obstructive sleep apnea (OR 5.7), the 6/6 watch system (OR 4.0), and morningness‐eveningness while controlling simultaneously several individual and sleep‐related factors. Subjective sleepiness (KSS) was highest at 04:00 and 06:00 h. In a multivariate analysis, the KSS was significantly related to time of day, time after awaking, sleep length, and interactions of the watch systems with age, morningness‐eveningness, and Epworth sleepiness scale (ESS) score. Severe sleepiness at 04:00–06:00 h was especially problematic in the 6/6 watch system among evening types and among the bridge officers with high ESS. The results suggest the 6/6 watch system is related to a higher risk of severe sleepiness during the early morning hours compared to the 4/8 and the other watch systems assessed.     

Sleepiness and Performance in Response to Repeated Sleep Restriction and Subsequent Recovery during Semi‐Laboratory Conditions

There is an ongoing debate of how best to measure the effects of sleep loss in a reliable and feasible way, partly because well controlled laboratory studies and field studies have come to different conclusions. The aims of the present study were to investigate both sleepiness and performance in response to long‐term sleep restriction and recovery in a semi‐laboratory environment, investigate order effects (i.e., whether levels return to baseline) in a study with seven days of recovery, and characterize individual differences in tolerance to restricted sleep. Nine healthy men (age 23–28 yrs) participated in the protocol, which included one habituation day (sleep 23:00–07:00 h), two baseline days (23:00–07:00 h), five days with restricted sleep (03:00–07:00 h), and seven recovery days (23:00–07:00 h). Participants went outdoors at least twice each day. Reaction‐time tests were performed at 08:00, 14:00, and 20:00 h each day in the laboratory. Sleepiness was self‐rated by the Karolinska Sleepiness Scale (KSS) after each test. The mixed‐effect regression models showed that each day of restricted sleep resulted in an increase of sleepiness by 0.64±.05 KSS units (a nine‐step scale, p<.001), increase of median reaction times of 6.6±1.6 ms (p=.003), and increase of lapses/test of 0.69±.16 ms (p<.001). Seven days of recovery allowed participants to return to the baseline for sleepiness and median reaction time, but not for lapses. The individual differences were larger for performance measures than for sleepiness; the between‐subject standard deviation for the random intercept was in the magnitude of the effects of 1.1 days of restricted sleep for sleepiness, 6.6 days of restricted sleep for median reaction time, and 3.2 days for lapses. In conclusion, the present study shows that sleepiness is closely related to sleep pressure, while performance measures, to a larger extent, appear determined by specific individual traits. Moreover, it is suggested to measure sleepiness in a standardized situation so as to minimize the influences of contextual factors.     

Social jetlag affects subjective daytime sleepiness in school-aged children and adolescents: A study using the Japanese version of the Pediatric Daytime Sleepiness Scale (PDSS-J)

The aim of this study was to elucidate the level of daytime sleepiness in Japanese school-aged children and adolescents, and to examine associated factors including sleep loss and social jetlag using the Japanese version of the Pediatric Daytime Sleepiness Scale (PDSS-J). After the linguistic validation of the PDSS-J with a multi-step translation methodology, consisting of forward translation, back translation, expert review and cognitive debriefing interviews, we conducted a psychometric validation for 492 students aged 11–16 years (46.7% boys) of public elementary school, junior high school and high school, using the PDSS-J, the Karolinska Sleepiness Scale (KSS), and bedtimes and wake-up times on school days and free days. Internal consistency (Cronbach’s alpha) of the PDSS-J was 0.77, and the test–retest reliability demonstrated by the intraclass coefficient was 0.88. Multivariate logistic regression analysis revealed that both short sleep duration and social jetlag were identified as factors associated with daytime sleepiness, after adjustment for age and sex. PDSS-J scores were significantly higher in the group with large social jetlag with or without sufficient sleep duration than in the group with sufficient sleep duration and small social jetlag. The PDSS-J is an important tool for assessing daytime sleepiness, given its ease of administration and robust psychometric properties. The impact of not only sleep loss but also social jetlag on daytime sleepiness among school-aged children and adolescents must be fully taken into account.     

Delayed Sleep Timing and Symptoms in Adults With Attention-Deficit/Hyperactivity Disorder: A Controlled Actigraphy Study

Patients with attention-deficit/hyperactivity disorder (ADHD) often exhibit disrupted sleep and circadian rhythms. Determination of whether sleep disturbance and/or circadian disruption are differentially associated with symptom severity is necessary to guide development of future treatment strategies. Therefore, we measured sleep and ADHD symptoms in participants aged 19–65 who met the DSM-IV-TR (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision) criteria for ADHD and insomnia without psychiatric comorbidities by monitoring actigraphy and daily sleep logs for 2 wks, as well as the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), the ADHD Rating Scale (ADHD-RS), and a clinic-designed sleep behavior questionnaire. Principal components analysis identified correlated circadian- and sleep-related variables in all participants with ADHD who completed the study (n?=?24). The identified components were entered into a backwards stepwise linear regression analysis, which indicated that delayed sleep timing and increased sleepiness (ESS) (but not sleep duration or sleep efficiency) significantly predicted greater severity of both hyperactive-impulsive and inattentive ADHD symptoms (p <?.05 for partial regression coefficients). In addition, combined subtypes had the most impaired age-adjusted sleep quality (PSQI scores; p?<?.05 compared with healthy controls; n?=?13), and 91.7% of them reported going to bed late due to being “not tired/too keyed up to sleep” compared with 57.2% and 50% of inattentive and symptom-controlled participants, respectively (p?<?.05). In conclusion, the results of this study suggest that ADHD symptom severity correlates with delayed sleep timing and daytime sleepiness, suggesting that treatment interventions aimed at advancing circadian phase may improve daytime sleepiness. In addition, ADHD adults with combined hyperactive-impulsive and inattentive symptoms have decreased sleep quality as well as the delayed sleep timing of predominately inattentive subtypes. (Author correspondence: rfargason@uab.edu)     

Caffeine or melatonin effects on sleep and sleepiness after rapid eastward transmeridian travel.

We measured the effects of slow-release caffeine (SRC) and melatonin (Mlt) on sleep and daytime sleepiness after a seven-time zone eastbound flight. In a double-blind, randomized, placebo-controlled study, each of three groups of nine subjects was given either 300 mg SRC on recovery day 1 (D1) to D5 (0800) or 5 mg Mlt on preflight D-1 (1700), flight day D0 (1600), and from D1 to D3 (2300), or placebo (Pbo) at the same times. Nighttime sleep was evaluated by polysomnography and daytime sleepiness from measurements of sleep latencies and continuous wrist actigraphy. Compared with baseline, we found a significant rebound of slow-wave sleep on night 1 (N1) to N2 under Pbo and Mlt and a significant decrease in rapid eye movement sleep on N1 (Pbo) and N1-N3 (Mlt). Sleepiness was objectively increased under Pbo (D1-D6) and Mlt (D1-D3). SRC reduced sleepiness but also tended to affect sleep quality until the last drug day. In conclusion, both drugs have positive effects on some jet lag symptoms after an eastbound flight: SRC on daytime sleepiness, and Mlt on sleep.     

Objective Measurement of Daytime Napping,Cognitive Dysfunction and Subjective Sleepiness in Parkinson’s Disease

Introduction

Sleep-wake disturbances and concomitant cognitive dysfunction in Parkinson’s disease (PD) contribute significantly to morbidity in patients and their carers. Subjectively reported daytime sleep disturbance is observed in over half of all patients with PD and has been linked to executive cognitive dysfunction. The current study used daytime actigraphy, a novel objective measure of napping and related this to neuropsychological performance in a sample of PD patients and healthy, age and gender-matched controls. Furthermore this study aimed to identify patients with PD who may benefit from pharmacologic and behavioural intervention to improve these symptoms.

Methods

Eighty-five PD patients and 21 healthy, age-matched controls completed 14 days of wrist actigraphy within two weeks of neuropsychological testing. Objective napping measures were derived from actigraphy using a standardised protocol and subjective daytime sleepiness was recorded by the previously validated Epworth Sleepiness Scale.

Results

Patients with PD had a 225% increase in the mean nap time per day (minutes) as recorded by actigraphy compared to age matched controls (39.2 ± 35.2 vs. 11.5 ± 11.0 minutes respectively, p < 0.001). Significantly, differences in napping duration between patients, as recorded by actigraphy were not distinguished by their ratings on the subjective measurement of excessive daytime sleepiness. Finally, those patients with excessive daytime napping showed greater cognitive deficits in the domains of attention, semantic verbal fluency and processing speed.

Conclusion

This study confirms increased levels of napping in PD, a finding that is concordant with subjective reports. However, subjective self-report measures of excessive daytime sleepiness do not robustly identify excessive napping in PD. Fronto-subcortical cognitive dysfunction was observed in those patients who napped excessively. Furthermore, this study suggests that daytime actigraphy, a non-invasive and inexpensive objective measure of daytime sleep, can identify patients with PD who may benefit from pharmacologic and behavioural interventions to improve these symptoms.     

Longitudinal Change in Sleep and Daytime Sleepiness in Postpartum Women

Sleep disruption strongly influences daytime functioning; resultant sleepiness is recognised as a contributing risk-factor for individuals performing critical and dangerous tasks. While the relationship between sleep and sleepiness has been heavily investigated in the vulnerable sub-populations of shift workers and patients with sleep disorders, postpartum women have been comparatively overlooked. Thirty-three healthy, postpartum women recorded every episode of sleep and wake each day during postpartum weeks 6, 12 and 18. Although repeated measures analysis revealed there was no significant difference in the amount of nocturnal sleep and frequency of night-time wakings, there was a significant reduction in sleep disruption, due to fewer minutes of wake after sleep onset. Subjective sleepiness was measured each day using the Karolinska Sleepiness Scale; at the two earlier time points this was significantly correlated with sleep quality but not to sleep quantity. Epworth Sleepiness Scores significantly reduced over time; however, during week 18 over 50% of participants were still experiencing excessive daytime sleepiness (Epworth Sleepiness Score ≥12). Results have implications for health care providers and policy makers. Health care providers designing interventions to address sleepiness in new mothers should take into account the dynamic changes to sleep and sleepiness during this initial postpartum period. Policy makers developing regulations for parental leave entitlements should take into consideration the high prevalence of excessive daytime sleepiness experienced by new mothers, ensuring enough opportunity for daytime sleepiness to diminish to a manageable level prior to reengagement in the workforce.     

Prevalence and correlates of poor sleep quality and daytime sleepiness in Belgian truck drivers

Sleepiness and sleep complaints are common among professional drivers. Sleepiness is a considerable problem not only because it affects the drivers' well-being, but also because of the consequences for performance and safety. Assessment of the (self-reported) prevalence and research into the risk factors are thus an important health issue and are also indispensable to prevent productivity loss and work-related accidents and injuries. Therefore, the aim of this study was to describe sleeping, driving, and health characteristics of Belgian truck drivers and to determine occupational and individual factors associated with poor sleep quality and daytime sleepiness. Cross-sectional data were collected using a self-administered questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and Berlin Questionnaire (BQ). The mean (SD) age of the 476 studied truck drivers was 42.7 (10.2) yrs and the mean (SD) body mass index was 27.3 (5.1) kg/m(2). Approximately 47% declared that they drove >50 h/wk and found their work schedule unrealistic. The mean (SD) PSQI score was 4.45 (2.7); poor quality of sleep (PSQI >5) was found in 27.2%. The mean (SD) ESS score was 6.79 (4.17); 18% had a score >10. The BQ indicated that 21.5% had a higher risk on obstructive sleep apnea. In multiple logistic regression analysis, low educational level (odds ratio [OR] 1.86), current smoking (OR 1.75), unrealistic work schedule (OR 1.75), and risk for obstructive sleep apnea (OR 2.97) were found to be independent correlates of daytime sleepiness. Poor sleep quality was significantly associated with poor self-perceived health (OR 1.95), unrealistic work schedule (OR 2.85), low job satisfaction (OR 1.91), and less driving experience (OR 1.73). These results show that poor sleep quality and daytime sleepiness were prevalent in Belgian truck drivers. Taking into account that several significant correlates with respect to these sleep problems were identified both at the individual and the occupational level, comprehensive countermeasures to improve working conditions and organization are needed, as well as health promotion interventions, to ensure the safety and well-being of truck drivers.     

Stress and sleep in nurses employed in “3 × 8” and “2 × 12” fast rotating shift schedules

We compared two “3?×?8” shift rotas with backward rotation and quick return (morning and night shift in the same day) in a 5- or 6-day shift cycle, and a “2?×?12” shift rota with forward rotation in a 5-d shift cycle. A total of 294 nurses (72.6% women, mean age 33.8) were examined in a survey on work-related stress, including the Standard Shiftwork Index. Ten nurses per each shift roster recorded their activity and rest periods by actigraphy, rated sleepiness and sleep quality, and collected salivary cortisol throughout the whole shift cycle. Nurses engaged in the “2?×?12” rota showed lower levels of sleep disturbances and, according to actigraphy, sleep duration was more balanced and less fragmented than in the “3?×?8” rosters. The counter-clockwise shift rotation and quick return of “3?×?8” schedules reduce possibility of sleep and recovery. The insertion of a morning shift before the day with quick return increases night sleep by about 1?h. Nurses who take a nap during the night shift require 40% less sleep in the morning after. The “2?×?12” clockwise roster, in spite of 50% increased length of shift, allows a better recovery and more satisfying leisure times, thanks to longer intervals between work periods. Sleepiness increased more during the night than day shifts in all rosters, but without significant difference between 8-h and 12-h rosters. However, the significantly higher level at the start of the night shift in the “3?×?8” rotas points out that the fast backward rotation with quick return puts the subjects in less efficient operational conditions. Some personal characteristics, such as morningness, lability to overcome drowsiness, flexibility of sleeping habits and age were significantly associated to sleep disturbances in nurses engaged in the “3?×?8” rotas, but not in the “2?×?12” schedule.     

Effects of Context on Sleepiness Self‐Ratings during Repeated Partial Sleep Deprivation

Ratings of subjective sleepiness are often used in laboratory and field studies of sleep loss and shifted sleep hours. Some studies suggest that such ratings might fail to reflect sleepiness as shown in physiology or performance. One reason for this may be the influence of the context of the rating. Social interaction or physical activity may mask latent sleepiness. The present study attempted to approach this question. Nine subjects participated in a partial sleep‐deprivation experiment (five days of 4 h of time in bed [TIB]), preceded by two baseline days (8 h TIB) and followed by three recovery days (8 h TIB). Sleepiness was self‐rated on the Karolinska Sleepiness Scale (KSS; scores of 1–9) after a period of relaxation, after a reaction‐time test, and after 30 min of free activities. The results showed a strong increase in subjective sleepiness during sleep restriction and a significant difference between conditions. Free activity reduced the self‐rated subjective sleepiness by 1.1 KSS units compared to the level of sleepiness self‐rated at the end of the reaction‐time test. Thus, the results of this study indicate that the context of a sleepiness rating affects the outcome of the rating.     

Insomnia,Excessive Sleepiness,Excessive Fatigue,Anxiety, Depression and Shift Work Disorder in Nurses Having Less than 11 Hours in-Between Shifts

Study objective

To assess if less than 11 hours off work between work shifts (quick returns) was related to insomnia, sleepiness, fatigue, anxiety, depression and shift work disorder among nurses.

Methods

A questionnaire including established instruments measuring insomnia (Bergen Insomnia Scale), sleepiness (Epworth Sleepiness Scale), fatigue (Fatigue Questionnaire), anxiety/depression (Hospital Anxiety and Depression Scale) and shift work disorder was administered. Among the 1990 Norwegian nurses who participated in the study; 264 nurses had no quick returns, 724 had 1–30 quick returns and 892 had more than 30 quick returns during the past year. 110 nurses did not report the number of quick returns during the past year. The prevalence of insomnia, excessive sleepiness, excessive fatigue, anxiety, depression and shift work disorder was calculated within the three groups of nurses. Crude and adjusted logistic regression analyses were performed to assess the relation between quick returns and such complaints.

Results

We found a significant positive association between quick returns and insomnia, excessive sleepiness, excessive fatigue and shift work disorder. Anxiety and depression were not related to working quick returns.

Conclusions

There is a health hazard associated with quick returns. Further research should aim to investigate if workplace strategies aimed at reducing the number of quick returns may reduce complaints among workers.     

Prevalence and Correlates of Poor Sleep Quality and Daytime Sleepiness in Belgian Truck Drivers

Sleepiness and sleep complaints are common among professional drivers. Sleepiness is a considerable problem not only because it affects the drivers' well-being, but also because of the consequences for performance and safety. Assessment of the (self-reported) prevalence and research into the risk factors are thus an important health issue and are also indispensable to prevent productivity loss and work-related accidents and injuries. Therefore, the aim of this study was to describe sleeping, driving, and health characteristics of Belgian truck drivers and to determine occupational and individual factors associated with poor sleep quality and daytime sleepiness. Cross-sectional data were collected using a self-administered questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and Berlin Questionnaire (BQ). The mean (SD) age of the 476 studied truck drivers was 42.7 (10.2) yrs and the mean (SD) body mass index was 27.3 (5.1) kg/m². Approximately 47% declared that they drove >50 h/wk and found their work schedule unrealistic. The mean (SD) PSQI score was 4.45 (2.7); poor quality of sleep (PSQI >5) was found in 27.2%. The mean (SD) ESS score was 6.79 (4.17); 18% had a score >10. The BQ indicated that 21.5% had a higher risk on obstructive sleep apnea. In multiple logistic regression analysis, low educational level (odds ratio [OR] 1.86), current smoking (OR 1.75), unrealistic work schedule (OR 1.75), and risk for obstructive sleep apnea (OR 2.97) were found to be independent correlates of daytime sleepiness. Poor sleep quality was significantly associated with poor self-perceived health (OR 1.95), unrealistic work schedule (OR 2.85), low job satisfaction (OR 1.91), and less driving experience (OR 1.73). These results show that poor sleep quality and daytime sleepiness were prevalent in Belgian truck drivers. Taking into account that several significant correlates with respect to these sleep problems were identified both at the individual and the occupational level, comprehensive countermeasures to improve working conditions and organization are needed, as well as health promotion interventions, to ensure the safety and well-being of truck drivers. (Author correspondence: lutgart.braeckman@ugent.be)