DAILY SLEEP,WEEKLY WORKING HOURS,AND RISK OF WORK-RELATED INJURY: US NATIONAL HEALTH INTERVIEW SURVEY (2004–2008)

The impact on health and safety of the combination of chronic sleep deficits and extended working hours has received worldwide attention. Using the National Health Interview Survey (NHIS), an in-person household survey using a multistage, stratified, clustered sample design representing the US civilian, non-institutionalized population, the authors estimated the effect of total daily self-reported sleep time and weekly working hours on the risk of a work-related injury. During the survey period 2004–2008, 177,576 persons (ages 18–74) sampled within households reported that they worked at a paid job the previous week and reported their total weekly work hours. A randomly selected adult in each household (n?=?75,718) was asked to report his/her usual (average) total daily sleep hours the prior week; complete responses were obtained for 74,415 (98.3%) workers. Weighted annualized work-related injury rates were then estimated across a priori defined categories of both average total daily sleep hours and weekly working hours. To account for the complex sampling design, weighted multiple logistic regression was used to independently estimate the risk of a work-related injury for categories of usual daily sleep duration and weekly working hours, controlling for important covariates and potential confounders of age, sex, race/ethnicity, education, type of pay, industry, occupation (proxy for job risk), body mass index, and the interaction between sleep duration and work hours. Based on the inclusion criteria, there were an estimated 129,950,376 workers annually at risk and 3,634,446 work-related medically treated injury episodes (overall injury rate 2.80/100 workers). Unadjusted annualized injury rates/100 workers across weekly work hours were 2.03 (≤20 h), 3.01 (20–30 h), 2.45 (31–40 h), 3.45 (40–50 h), 3.71 (50–60 h), and 4.34 (>60 h). With regards to self-reported daily sleep time, the estimated annualized injury rates/100 workers were 7.89 (<5 h sleep), 5.21 (5–5.9 h), 3.62 (6–6.9 h), 2.27 (7–7.9 h), 2.50 (8–8.9 h), 2.22 (9–9.9 h), and 4.72 (>10 h). After controlling for weekly work hours, and aforementioned covariates, significant increases in risk/1 h decrease were observed for several sleep categories. Using 7–7.9 h sleep as reference, the adjusted injury risk (odds ratio [OR] for a worker sleeping a total of <5 h/day was 2.65 (95% confidence interval [CI]: 1.57–4.47), for 5–5.9 h 1.79 (95% CI: 1.22–2.62), and for 6–6.9 h 1.40 (95% CI: 1.10–1.79). No other usual sleep duration categories were significantly different than the reference; however, for >10 h of usual daily sleep, the OR was marginally significantly elevated, 1.82 (95% CI: 0.96–3.47). These results suggest significant increases in work-related injury risk with decreasing usual daily self-reported sleep hours and increasing weekly work hours, independent of industry, occupation, type of pay, sex, age, education, and body mass (Author correspondence: david.lombardi@libertymutual.com)     

WORK HOURS AND SLEEP/WAKE BEHAVIOR OF AUSTRALIAN HOSPITAL DOCTORS

The objective of the study was to describe the work and sleep patterns of doctors working in Australian hospitals. Specifically, the aim was to examine the influence of work-related factors, such as hospital type, seniority, and specialty on work hours and their impact on sleep. A total of 635 work periods from 78 doctors were analyzed together with associated sleep history. Work and sleep diary information was validated against an objective measure of sleep/wake activity to provide the first comprehensive database linking work and sleep for individual hospital doctors in Australia. Doctors in large and small facilities had fewer days without work than those doctors working in medium-sized facilities. There were no significant differences in the total hours worked across these three categories of seniority; however, mid-career and senior doctors worked more overnight and weekend on-call periods than junior doctors. With respect to sleep, although higher work hours were related to less sleep, short sleeps (< 5 h in the 24 h prior to starting work) were observed at all levels of prior work history (including no work). In this population of Australian hospital doctors, total hours worked do impact sleep, but the pattern of work, together with other nonwork factors are also important mediators. (Author correspondence: sally.ferguson@unisa.edu.au)     

Independent Effects of Sleep Duration and Body Mass Index on the Risk of a Work-Related Injury: Evidence From the US National Health Interview Survey (2004–2010)

Fatigue has been linked to adverse safety outcomes, and poor quality or decreased sleep has been associated with obesity (higher body mass index, BMI). Additionally, higher BMI is related to an increased risk for injury; however, it is unclear whether BMI modifies the effect of short sleep or has an independent effect on work-related injury risk. To answer this question, the authors examined the risk of a work-related injury as a function of total daily sleep time and BMI using the US National Health Interview Survey (NHIS). The NHIS is an in-person household survey using a multistage, stratified, clustered sample design representing the US civilian population. Data were pooled for the 7-yr survey period from 2004 to 2010 for 101 891 “employed” adult subjects (51.7%; 41.1?±?yrs of age [mean?±?SEM]) with data on both sleep and BMI. Weighted annualized work-related injury rates were estimated across a priori defined categories of BMI: healthy weight (BMI: <25), overweight (BMI: 25–29.99), and obese (BMI: ≥30) and also categories of usual daily sleep duration: <6, 6–6.99, 7–7.99, 8–8.99, and ≥9?h. To account for the complex sampling design, including stratification, clustering, and unequal weighting, weighted multiple logistic regression was used to estimate the risk of a work-related injury. The initial model examined the interaction among daily sleep duration and BMI, controlling for weekly working hours, age, sex, race/ethnicity, education, type of pay, industry, and occupation. No significant interaction was found between usual daily sleep duration and BMI (p?=?.72); thus, the interaction term of the final logistic model included these two variables as independent predictors of injury, along with the aforementioned covariates. Statistically significant covariates (p?≤?.05) included age, sex, weekly work hours, occupation, and if the worker was paid hourly. The lowest categories of usual sleep duration (<6 and 6–6.9?h) showed significantly (p?≤?.05) elevated injury risks than the referent category (7–8?h sleep), whereas sleeping >7–8?h did not significantly elevate risk. The adjusted injury risk odds ratio (OR) for a worker with a usual daily sleep of <6?h was 1.86 (95% confidence interval [CI]: 1.37–2.52), and for 6–6.9?h it was 1.46 (95% CI: 1.18–1.80). With regards to BMI, the adjusted injury risk OR comparing workers who were obese (BMI: ≥30) to healthy weight workers (BMI: <25) was 1.34 (95% CI: 1.09–1.66), whereas the risk in comparing overweight workers (BMI: 25–29.99) to healthy weight risk was elevated, but not statistically significant (OR?=?1.08; 95% CI: .88–1.33). These results from a large representative sample of US workers suggest increase in work-related injury risk for reduced sleep regardless of worker's body mass. However, being an overweight worker also increases work-injury risk regardless of usual daily sleep duration. The independent additive risk of these factors on work-related injury suggests a substantial, but at least partially preventable, risk. (Author correspondence: david.lombardi@libertymutual.com)     

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)     

Aircrew fatigue in trans-Atlantic morning and evening flights

The aim of the investigation was to compare sleepiness and sleep on westward morning and evening flights. Seven morning-crew pilots and seven evening-crew pilots participated. Data were collected before, during, and after outward-bound (westward) and homeward-bound (eastward) flights across six time zones. A sleep/wake diary (with repeated sleepiness and performance ratings) and wrist actigraphy were used for data collection. Maximum sleep was obtained after return and minimum sleep before the outward-bound flights. Actigraphy measures and sleep efficiency over the course of the study showed no significant differences between the morning and evening crews. There was a trend for a significant effect of morning vs. evening flight for time with heavy eyelids, with the homeward-bound flight showing more time with heavy eyelids. There were no significant differences between morning and evening crews with regard to napping during the flight. The duration of wakefulness was longer for the evening flight crew. There were significant interactions for Karolinska sleepiness scale (KSS) self-ratings on both the outward-bound and homeward-bound flights, and KSS was elevated during a considerable portion of the evening flights. Rated performance showed a significant time effect, but there was no difference in self-ratings between morning and evening crews. Evening flights involve higher levels of sleepiness than morning flights, presumably because of the close proximity in time to the circadian trough of alertness.     

Aircrew Fatigue in Trans‐Atlantic Morning and Evening Flights

The aim of the investigation was to compare sleepiness and sleep on westward morning and evening flights. Seven morning‐crew pilots and seven evening‐crew pilots participated. Data were collected before, during, and after outward‐bound (westward) and homeward‐bound (eastward) flights across six time zones. A sleep/wake diary (with repeated sleepiness and performance ratings) and wrist actigraphy were used for data collection. Maximum sleep was obtained after return and minimum sleep before the outward‐bound flights. Actigraphy measures and sleep efficiency over the course of the study showed no significant differences between the morning and evening crews. There was a trend for a significant effect of morning vs. evening flight for time with heavy eyelids, with the homeward‐bound flight showing more time with heavy eyelids. There were no significant differences between morning and evening crews with regard to napping during the flight. The duration of wakefulness was longer for the evening flight crew. There were significant interactions for Karolinska sleepiness scale (KSS) self‐ratings on both the outward‐bound and homeward‐bound flights, and KSS was elevated during a considerable portion of the evening flights. Rated performance showed a significant time effect, but there was no difference in self‐ratings between morning and evening crews. Evening flights involve higher levels of sleepiness than morning flights, presumably because of the close proximity in time to the circadian trough of alertness.     

Working on Sundays–Effects on Safety,Health, and Work-life Balance

Several attributes of the work schedule can increase the risk of occupational injuries and accidents, health impairments, and reduced social participation. Although previous studies mainly focused on the effects of shiftwork and long working hours on employee health and safety, there is little evidence of a potential negative impact of working Sundays on the incidence of occupational accidents, health impairments, and work-life balance. A representative sample of employed workers in 31 member and associated states of the European Union (n?=?23,934) served as the database for a cross-sectional analysis. The sample was collected via face-to-face interviews in the year 2005. The association of the risks of occupational accidents, health impairments, and decreases in work-life balance with working Sundays was calculated using logistic regression models, controlling for potential confounders, such as shiftwork, workload, and demographic characteristics. The results indicated that working one or more Sundays/month was associated with increase both in the risk of reporting one or more health impairments (odds ratio [OR]: 1.17, 95% confidence interval [CI]: 1.06–1.29) and poorer work-life balance (OR: 1.15, 95% CI: 1.02–1.28). These effects remained after controlling for potentially confounding factors, such as other work schedule attributes, intensity of physical and mental workload, and individual characteristics. Furthermore, working Sundays was also related to increased risk of occupational accidents within the last year (OR: 1.34, 95% CI: 1.03–1.73). Controlling again for individual, workload, and working-time characteristics, a significant association with accident risk, however, remained only in work sectors with low a priori risk of occupational accidents (OR: 1.40, 95% CI: 1.02–1.91), although the increased risk could be observed for both medium and high a priori risk sectors working Sundays (without controlling for additional confounders). The results thus indicate that the detrimental effects of working Sundays on safety, health, and social well-being should be taken into account when designing work schedules. The potential hazards to employees' safety, health, and work-life balance, in particular, should be considered in discussions concerning extending work on Sundays in certain sectors, e.g., retail. (Author correspondence: awirtz@hsph.harvard.edu)     

Incorporation of caffeine into a quantitative model of fatigue and sleep

A recent physiologically based model of human sleep is extended to incorporate the effects of caffeine on sleep-wake timing and fatigue. The model includes the sleep-active neurons of the hypothalamic ventrolateral preoptic area (VLPO), the wake-active monoaminergic brainstem populations (MA), their interactions with cholinergic/orexinergic (ACh/Orx) input to MA, and circadian and homeostatic drives. We model two effects of caffeine on the brain due to competitive antagonism of adenosine (Ad): (i) a reduction in the homestatic drive and (ii) an increase in cholinergic activity. By comparing the model output to experimental data, constraints are determined on the parameters that describe the action of caffeine on the brain. In accord with experiment, the ranges of these parameters imply significant variability in caffeine sensitivity between individuals, with caffeine's effectiveness in reducing fatigue being highly dependent on an individual's tolerance, and past caffeine and sleep history. Although there are wide individual differences in caffeine sensitivity and thus in parameter values, once the model is calibrated for an individual it can be used to make quantitative predictions for that individual. A number of applications of the model are examined, using exemplar parameter values, including: (i) quantitative estimation of the sleep loss and the delay to sleep onset after taking caffeine for various doses and times; (ii) an analysis of the system's stable states showing that the wake state during sleep deprivation is stabilized after taking caffeine; and (iii) comparing model output successfully to experimental values of subjective fatigue reported in a total sleep deprivation study examining the reduction of fatigue with caffeine. This model provides a framework for quantitatively assessing optimal strategies for using caffeine, on an individual basis, to maintain performance during sleep deprivation.     

江苏省2008年疑似预防接种异常反应监测数据的分析评价

采用描述性流行病学方法对江苏省2008年疑似预防接种异常反应(Adverse event following immunization,AEFI)监测数据及网络直报系统运转情况进行分析和评价。共收集到AEFI报告个案6197例,其中疫苗引起的反应占98.97%,偶合症占0.95%,不明原因占0.02%,待定占0.06%。临床诊断分布是以发热、局部红肿和局部硬结等一般反应为多见,其次为异常反应中的过敏性皮疹,无菌性脓肿。全省AEFI网络直报系统运行正常,各项考核指标均完成得较好。采用统一的AEFI分类与临床诊断病例定义,通过网络直报系统的三级审核,报告的数据质量有了很大的提高。监测结果显示,全省免疫规划疫苗安全性与预防接种服务质量良好。     

简述疫苗安全性管理

疫苗接种是保护公众健康最有效的措施之一,疫苗可有效降低传染病的发病率和死亡率。与疫苗的有效性评估不同,疫苗的安全性不能直接测定,只能通过有限的疫苗不良事件的相关情况来推断。对疫苗安全性监测的科学理论,全球关注的个案研究,以及注册前有关疫苗的临床试验安全性的相关事宜进行了简介。     

清远市2009—2012年疑似预防接种异常反应监测分析

目的了解广东省清远市疑似预防接种异常反应(AEFI)的发生特征,评价AEFI信息管理系统运转情况及预防接种安全性。方法采用描述流行病学方法对清远市2009—2012年报告的AEFI数据进行统计分析。结果2009—2012年清远市共报告AEFI 553例,年均发生率为7.6/10万,以一般反应为主(72.33%);AEFI监测县区覆盖率、48 h内及时报告率和调查率、个案调查表完整率等运转指标均明显提高;发生时间以3、9、11月份居多(占40.87%),人群以≤2岁婴幼儿为主(占60.58%),接种后1 d内发生AEFI占85.90%;发生率较高的疫苗主要为23价肺炎球菌多糖疫苗、甲型H1N1流感病毒裂解疫苗、b型流感嗜血杆菌结合疫苗、麻疹风疹联合减毒活疫苗、吸附白破联合疫苗、吸附百白破联合疫苗(占46.84%)。结论清远市AEFI集中在小年龄组及接种早期。疫苗的安全性和预防接种服务质量良好。AEFI监测的完整性和敏感性逐年提高。为减少预防接种后不良事件的发生,提高AEFI监测敏感性,须进一步规范预防接种工作,提高预防接种质量,加强AEFI监测。     

“知信行”模式对老年糖尿病患者睡眠质量的改善作用

目的:调查老年糖尿病患者的睡眠质量,探讨\"知信行\"管理模式对糖尿病患者睡眠障碍的改善作用。方法:选取100例糖尿病患者,随机分为管理组和对照组,每组50例。管理组患者采用\"知信行\"管理模式进行护理,对照组患者采用常规基础护理模式。采用匹兹堡睡眠质量指数量评估量表(PSQI)评价患者的睡眠质量,Piper疲劳量表(PFS)评估患者的疲劳程度。结果:护理干预前,两组患者的睡眠质量评分与疲劳程度评分无显著性差异(P0.05)。接受不同护理干预后,两组患者的睡眠质量评分与疲劳程度评分均降低,且管理组评分低于对照组,差异具有统计学意义(P0.05)。结论:\"知信行\"护理管理模式对老年糖尿病患者的睡眠障碍具有一定的改善作用,有助于降低患者的疲劳程度,值得临床护理推广。     

Explaining Sleep Duration in Adolescents: The Impact of Socio‐Demographic and Lifestyle Factors and Working Status

Previous studies found students who both work and attend school undergo a partial sleep deprivation that accumulates across the week. The aim of the present study was to obtain information using a questionnaire on a number of variables (e.g., socio‐demographics, lifestyle, work timing, and sleep‐wake habits) considered to impact on sleep duration of working (n=51) and non‐working (n=41) high‐school students aged 14–21 yrs old attending evening classes (19:00–22:30 h) at a public school in the city of São Paulo, Brazil. Data were collected for working days and days off. Multiple linear regression analyses were performed to assess the factors associated with sleep duration on weekdays and weekends. Work, sex, age, smoking, consumption of alcohol and caffeine, and physical activity were considered control variables. Significant predictors of sleep duration were: work (p < 0.01), daily work duration (8–10 h/day; p < 0.01), sex (p=0.04), age 18–21 yrs (0.01), smoking (p=0.02) and drinking habits (p=0.03), irregular physical exercise (p < 0.01), ease of falling asleep (p=0.04), and the sleep‐wake cycle variables of napping (p < 0.01), nocturnal awakenings (p < 0.01), and mid‐sleep regularity (p < 0.01). The results confirm the hypotheses that young students who work and attend school showed a reduction in night‐time sleep duration. Sleep deprivation across the week, particularly in students working 8–10 h/day, is manifested through a sleep rebound (i.e., extended sleep duration) on Saturdays. However, the different roles played by socio‐demographic and lifestyle variables have proven to be factors that intervene with nocturnal sleep duration. The variables related to the sleep‐wake cycle—naps and night awakenings—proved to be associated with a slight reduction in night‐time sleep, while regularity in sleep and wake‐up schedules was shown to be associated with more extended sleep duration, with a distinct expression along the week and the weekend. Having to attend school and work, coupled with other socio‐demographic and lifestyle factors, creates an unfavorable scenario for satisfactory sleep duration.     

糖尿病足患者睡眠质量与疲劳程度的调查研究

目的:调查糖尿病足(diabetic foot,DF)患者的睡眠质量与疲劳程度,并分析其相关性。方法:选取105例糖尿病足患者,采用人口数据统计表调查患者的一般情况,匹兹堡睡眠质量指数量(PSQI)评估患者的睡眠质量,Piper疲劳量表(PFS)评估患者的疲劳程度,并通过pearson检测分析其相关性。结果:人口统计数据显示,56%的DF患者年龄在41岁以上,64.8%女性,82.9%已婚,48.6%小学学历,39%病程3年或更长的时间。PSQI的平均总得分为(8.17±3.02),PFS量表总分为(6.38±2.18),睡眠质量与疲劳度总得分之间呈显著正相关,相关系数r=0.622(P0.05)。结论:DF患者的睡眠质量较差,大多出现中度疲劳,二者之间呈正相关,应加强对DF患者的睡眠质量与疲劳的护理。     

Flexible Working Hours,Health, and Well-Being in Europe: Some Considerations from a SALTSA Project

The project brought together researchers from 9 EU-Countries and resulted in a number of actions, in particular the following: (a) There is an urgent need of defining the concept of flexible working hours, since it has been used in many different and even counterintuitive ways; the most obvious distinction is where the influence over the working hours lies, that is between the “company-based flexibility” and the “individual-oriented flexibility”; (b) The review of the Legislation in force in the 15 European countries shows that the regulation of working times is quite extensive and covers (Council Directive 93/104/EC) almost all the various arrangements of working hours (i.e., part-time, overtime, shift, and night work), but fails to provide for flexibility; (c) According to the data of the Third EU Survey on Working Conditions, longer and “irregular” working hours are in general linked to lower levels of health and well-being; moreover, low (individual) flexibility and high variability of working hours (i.e., company-based flexibility) were consistently associated with poor health and well-being, while low variability combined with high autonomy showed positive effects; (d) Six substudies from different countries demonstrated that flexible working hours vary according to country, economic sector, social status, and gender; overtime is the most frequent form of company-based flexibility but has negative effects on stress, sleep, and social and mental health; individual flexibility alleviates the negative effects of the company-based flexibility on subjective health, safety, and social well-being; (e) The literature review was able to list more than 1,000 references, but it was striking that most of these documents were mainly argumentative with very little empirical data. Thus, one may conclude that there is a large-scale intervention ongoing in our society with almost completely unknown and uncontrolled effects. Consequently, there is a strong need for systematic research and well-controlled actions in order to examine in detail what flexible working hours are considered, what and where are their positive effects, in particular, as concerns autonomy, and what regulation seem most reasonable.     

Flexible working hours, health, and well-being in Europe: some considerations from a SALTSA project

The project brought together researchers from 9 EU-Countries and resulted in a number of actions, in particular the following: (a) There is an urgent need of defining the concept of flexible working hours, since it has been used in many different and even counterintuitive ways; the most obvious distinction is where the influence over the working hours lies, that is between the “company-based flexibility” and the “individual-oriented flexibility”; (b) The review of the Legislation in force in the 15 European countries shows that the regulation of working times is quite extensive and covers (Council Directive 93/104/EC) almost all the various arrangements of working hours (i.e., part-time, overtime, shift, and night work), but fails to provide for flexibility; (c) According to the data of the Third EU Survey on Working Conditions, longer and “irregular” working hours are in general linked to lower levels of health and well-being; moreover, low (individual) flexibility and high variability of working hours (i.e., company-based flexibility) were consistently associated with poor health and well-being, while low variability combined with high autonomy showed positive effects; (d) Six substudies from different countries demonstrated that flexible working hours vary according to country, economic sector, social status, and gender; overtime is the most frequent form of company-based flexibility but has negative effects on stress, sleep, and social and mental health; individual flexibility alleviates the negative effects of the company-based flexibility on subjective health, safety, and social well-being; (e) The literature review was able to list more than 1,000 references, but it was striking that most of these documents were mainly argumentative with very little empirical data. Thus, one may conclude that there is a large-scale intervention ongoing in our society with almost completely unknown and uncontrolled effects. Consequently, there is a strong need for systematic research and well-controlled actions in order to examine in detail what flexible working hours are considered, what and where are their positive effects, in particular, as concerns autonomy, and what regulation seem most reasonable.     

Twelve-Hour Night Shifts of Healthcare Workers: A Risk to the Patients?

We assessed the impact of 12h fixed night shift (19:00–07:00h) work, followed by 36h of off-time, on the sleep–wake cycle, sleep duration, self-perceived sleep quality, and work-time alertness on a group composed of 5 registered and 15 practical nurses. Wrist actigraphy (Ambulatory Monitoring, Inc.), with data analysis by the Cole-Kripke algorithm, was applied to determine sleep/wake episodes and their duration. The sleep episodes were divided into six categories: sleep during the night shift (x¯=208.6; SD±90.6mins), sleep after the night shift (x¯=138.7; SD±79.6min), sleep during the first night after the night work (x¯=318.5; SD±134.6min), sleep before the night work (x¯=104.3; SD±44.1min), diurnal sleep during the rest day (x¯=70.5; SD±43.0min), and nocturnal sleep during the rest day (x¯=310.4; SD±188.9mins). A significant difference (p<.0001; T-test for dependent samples) was detected between the perceived quality of sleep of the three diurnal sleep categories compared to the three nocturnal sleep categories. Even thought the nurses slept (napped) during the night shift, their self-perceived alertness systematically decreased during it. Statistically significant differences were documented by one-way ANOVA (F=40.534 p<.0001) among the alertness measurements done during the night shift. In particular, there was significant difference in the level of perceived alertness (p<.0001) between the 7^th and 10^thh of the 12h night shift. These findings of decreased alertness during the terminal hours of the night shift are of concern, since they suggest risk of comprised patient care.