Teen at work: the burden of a double shift on daily activities

The purpose of this study was to the evaluate time spent by working and nonworking adolescents on daily activities (work, home duties, school, transportation, other activities, leisure, sleep, and naps). Twenty-seven students, 8 male workers, 8 female workers, 5 male nonworkers, and 6 female nonworkers, ages 14-18 yrs participated in the study. They attended evening classes Monday-Friday (19:00-22:30h) in a public school in the city of S?o Paulo, Brazil. The students answered a comprehensive questionnaire on the characterization of their life, work, and health conditions. Simultaneously, they wore actigraphs (Ambulatory Monitoring, Inc.) and completed a diary of their daily activities (time spent at work, on home duties, commuting, leisure, other activities) for a minimum of 10 to a maximum of 17 consecutive days. The means of the variables were tested for differences by a two-factor (work and sex) ANOVA and Student-t test applied to pair-wise samples (weekdays and weekends). The average duration during weekdays of working time was 7 h 09 min and home duties 0 h 48 min. As for commuting time, there was a work effect [F(1,23) = 4.9; p = 0.04]; mean commuting time was 2 h 22 min for workers (males and females) and 1 h 25 min for nonworkers. There was a significant difference between workers and nonworkers [F(1,23) = 4.6; p = 0.04] regarding extra-cirricular class activities; workers spent a mean of 3 min/day on them as opposed to 1 h 14 min by nonworkers. The average daily time spent on leisure activities by workers was 6h 31 min; whereas, for nonworkers it was 7h 38min. Time spent in school amounted to 2h 47min for workers in comparison to 3h 22min by nonworkers. There was a significant work effect upon sleep [F(1,23)= 10.0; p <0.01]. The work effect upon nighttime sleep duration was significant [F(1,23)= 16.7; p <0.01]. Male workers showed a mean night sleep of 6 h 57 min and female workers 07h 15min. The average nighttime sleep duration for nonworkers was 9 h 06 min. There was a significant interactive effect between work and sex [F(1,23)= 5.6; p=0.03] for naps. Female workers showed took shortest nap on average (36 min; SD = 26 min), and female nonworkers the longest naps (1 h 45min; SD= 35min). Study and employment exert significant impact on the life and activities of high school students. Work affects sleep and nap duration plus the amount of time spent in school and other extra-curricular activities.     

Sleep Patterns of Day-Working,Evening High-Schooled Adolescents of São Paulo,Brazil

Children who grow up in developing countries of the world must work to help financially support their families, and they must also attend school. We investigated the impact of work on the sleep of working vs. nonworking high school students. Twenty-seven São Paulo, Brazil, public high school students (eight male and eight female working students plus six nonworking female and five nonworking male students) 14–18 yrs of age who attended school Monday–Friday between 19:00 to 22:30 h participated. A comprehensive questionnaire about work and living conditions, health status, and diseases and their symptoms was also answered. The activity level and rest pattern (sleep at night and napping during the day) were continuously assessed by wrist actigraphy (Ambulatory Monitoring, USA). The main variables were analyzed by a two-factor ANOVA with application of the Tukey HSD test for multiple comparisons, and the length of sleep during weekdays vs. weekends was compared by Student t-test. Working students went to sleep earlier weekends [F_(1,23) = 6.1; p = 0.02] and woke up earlier work days than nonworking students [F_(1,23) = 17.3; p = 0.001]. The length of nighttime sleep during weekdays was shorter among all the working [F_(1,23) = 16.7; p < 0.001] than all the nonworking students. The sleep duration of boys was shorter than of girls during weekends [F_(1,23) = 10.8; p < 0.001]. During weekdays, the duration of napping by working and nonworking male students was shorter than nonworking female students. During weekdays, working girls took the shortest naps [F_(1,23) = 5.6; p = 0.03]. The most commonly reported sleep complaint during weekdays was difficulty waking up in the morning [F_(1,23) = 6.5; p = 0.02]. During weekdays, the self-perceived sleep quality of working students was worse than nonworking students [F_(1,23) = 6.2; p = 0.02]. The findings of this study show that work has negative effects on the sleep of adolescents, with the possible build-up of a chronic sleep debt with potential consequent impact on quality of life and school learning.     

Sleep patterns of day-working, evening high-schooled adolescents of São Paulo, Brazil

Children who grow up in developing countries of the world must work to help financially support their families, and they must also attend school. We investigated the impact of work on the sleep of working vs. nonworking high school students. Twenty-seven S?o Paulo, Brazil, public high school students (eight male and eight female working students plus six nonworking female and five nonworking male students) 14-18 yrs of age who attended school Monday-Friday between 19:00 to 22:30h participated. A comprehensive questionnaire about work and living conditions, health status, and diseases and their symptoms was also answered. The activity level and rest pattern (sleep at night and napping during the day) were continuously assessed by wrist actigraphy (Ambulatory Monitoring, USA). The main variables were analyzed by a two-factor ANOVA with application of the Tukey HSD test for multiple comparisons, and the length of sleep during weekdays vs. weekends was compared by Student t-test. Working students went to sleep earlier weekends [F(1,23)=6.1; p=0.02] and woke up earlier work days than nonworking students [F(1,23) = 17.3; p = 0.001]. The length of nighttime sleep during weekdays was shorter among all the working [F(1,23)= 16.7; p <0.001] than all the nonworking students. The sleep duration of boys was shorter than of girls during weekends [F(1,23)= 10.8; p <0.001]. During weekdays, the duration of napping by working and nonworking male students was shorter than nonworking female students. During weekdays working girls took the shortest naps [F(1,23)= 5.6; p = 0.03]. The most commonly reported sleep complaint during weekdays was difficulty waking up in the morning [F(1,23) = 6.5; p = 0.02]. During weekdays, the self-perceived sleep quality of working students was worse than nonworking students [F(1,23) = 6.2; p = 0.02]. The findings of this study show that work has negative effects on the sleep of adolescents, with the possible build-up of a chronic sleep debt with potential consequent impact on quality of life and school learning.     

Sleep on the Job Partially Compensates for Sleep Loss in Night‐Shift Nurses

Nursing personnel in Brazil are usually submitted to fixed 12 h shifts with no consecutive working days or nights. Moonlighting is common in this group, with a consequent increase in the number of working hours. The possibility of sleeping on the job during the night shift in the studied hospitals had already been described. The present study aims to analyze whether the time devoted to daily activities (sleep, rest, leisure, housework, commuting, personal needs, care of children or other people, non‐paid work, and study) is related to the number of worked hours and to nap‐taking during the night shift. The field study took place at two public hospitals in Rio de Janeiro, Brazil. Workers filled out a structured form on time devoted to the above‐mentioned activities for at least four consecutive days. The time devoted to sleep was analyzed according to its occurrence at home or on the job. Workers were classified according to the number of jobs (one job/two jobs) and the time dedicated to work according to the median of the whole series (below the median/above the median). All workers who had at least one working night were analyzed as to nap‐taking on the job. They were classified according to the sleep occurrence during the night shift—the sleep group and the non‐sleep group, both of which were compared to daytime workers. Statistical treatment of data included non‐parametrical procedures. The study group comprised 144 workers (mean age: 35.7±10.5 years old; 91% women; 78% nurse assistants, the remainder registered nurses). They recorded their daily activities for 4–11 days; 829 cumulative days were analyzed for the whole group. A total of 165 working nights were analyzed; sleep or rest occurred during 112 (68%) of them, with mean sleep/rest duration of 141±86 min. Time devoted to sleep and leisure varied according to the number of working hours, being significantly reduced in those submitted to longer work hours (p<0.001 and p=0.002, respectively). Results close to significance point to a reduction in the time dedicated to housework among workers with long work hours (p=0.053). The time spent on sleep/rest per working night did not differ according to the number of worked hours (p=0.490). A tendency was observed for those who have two jobs to devote more time to sleep/rest on the job (p=0.058). The time of personal needs was significantly lower among those who did not sleep on the job as compared to day workers (p=0.036). The total sleep time was significantly lower among those who did not sleep on the job, as compared to day workers and to those who slept on the job (p=0.004 and p=0.05, respectively). As to home sleep length, workers who slept and those who did not sleep on the job were similar and slept significantly less than exclusively daytime workers (p<0.001 and p=0.002, respectively). Sleeping on the job during the night shift seems to partially compensate for the shorter sleep at home among night workers and may play a beneficial effect in coping with two jobs.     

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.     

The Nutritional Status and Eating Habits of Shift Workers: A Chronobiological Approach

The eating habits of workers may vary according to the season of the year and corresponding work schedule. A study aiming at verifying the changes in their diet in summer and winter, as well as the nutritional status of those who work fixed shifts, was conducted. The distribution during the 24 h in the quantity of calories and macronutrients ingested and the circadian rhythm of calories consumed were also analyzed. The study was conducted on 28 workers subject to three fixed work (morning, afternoon, and night) shifts at a transport company in the city of São Paulo, Brazil. The mean age of the workers was 32.8 (SD ± 5.3) yrs. Their food intake was ascertained by the use of a 3-day dietary record, and their nutritional status was evaluated by their body mass index (BMI), both in winter and summer. Two-way ANOVA (shift and season) showed food consumption—measured in calories/24 h—was significantly higher in winter than summer (F_(1.25) = 11.7; p < 0.001). No statistically significant differences were found among shifts (F_(2.25) = 0.85; p < 0.44), and the interaction effect between shift and season was also not significant (F_(2.25) = 0.15; p < 0.86). No seasonal difference in BMI was detected (Kruskal-Wallis test). Cosinor analyses showed circadian rhythmicity in calories consumed by morning (p < 0.01) as well as afternoon shift workers (p < 0.001), both in the winter and summer. Circadian rhythmicity in calories consumed by night workers was found only in summer (p < 0.01). The changes observed in the workers’ eating habits from one season to another and during the 24 h period show the need for further studies to help develop educational programs to improve the nutrition of shift employees taking into consideration shift schedule and season of the year when work is performed.     

Effects of a sleep education program with self-help treatment on sleeping patterns and daytime sleepiness in Japanese adolescents: A cluster randomized trial

Subjective insufficient sleep and delayed sleep–wake patterns have been reported as the primary causes for daytime sleepiness, a reasonably significant and prevalent problem for adolescents worldwide. Systematic reviews have indicated that the success of sleep education programs has thus far been inconsistent, due to the lack of a tailored approach that allows for evaluation of individual differences in behavior patterns. One way to resolve this problem is to assess the individual sleep behaviors of adolescents by using a checklist containing the recommended behaviors for promoting sleep health. Such self-help education programs have already been implemented for elementary school children, school nurses and the elderly. The present study aimed to verify the effects of a sleep education program with supplementary self-help treatment, based on a checklist of sleep-promoting behaviors, in addition to evaluation of changes in sleeping patterns, sleep-promoting behaviors and daytime sleepiness in adolescents. A cluster randomized controlled trial involving 5 Japanese junior high schools was conducted, and 243 students (sleep education: n = 122; waiting list: n = 121; 50.6% female; 7th grade) were included in the final analysis. The sleep education group was provided with information on proper sleep health and sleep-promoting behaviors. The students in this group were asked to practice one sleep-promoting behavior as a goal for 2 weeks and to monitor their practice using sleep diaries. Both pre- and post-treatment questionnaires were administered to students in order to assess knowledge of sleep-promoting behaviors, sleeping patterns and daytime functioning. Students in the sleep education group showed significant improvement in their knowledge of sleep health (F_1,121 = 648.05, p < 0.001) and in their sleep-promoting behaviors (F_1,121 = 55.66, p < 0.001). Bedtime on both school nights (F_1,121 = 50.86, p < 0.001) and weekends (F_1,121 = 15.03, p < 0.001), sleep-onset latency (F_1,121 = 10.26, p = 0.002), total sleep time on school nights (F_1,121 = 12.45, p = 0.001), subjective experience of insufficient sleep (McNemar χ²(1) = 4.03, p = 0.045) and daytime sleepiness (McNemar χ²(1) = 4.23, p = 0.040) were also improved in the sleep education group. In contrast, no significant improvement in these variables was observed for students in the waiting-list group. In conclusion, the sleep education program with self-help treatment was effective not only in increasing sleep knowledge but also in improving sleep-promoting behavior and sleeping patterns/reducing daytime sleepiness for students in the sleep education group, in comparison with the waiting-list group.     

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.     

Delaying and Extending Sleep During Weekends: Sleep Recovery or Circadian Effect?

There is a well-known tendency to delay and prolong our sleep during weekends (Saturday and Sunday), with an advance and reduction of sleep during workdays (Monday to Friday). The objective of this work was to determine if the changes of sleep during weekends are produced by a partial sleep deprivation or a lack of entraining of circadian rhythms to an advanced phase, during workdays. The subjects were 52 undergraduate female students, mean age = 17.5 years, SD = 1.32. All students attended school following a regular schedule, from Monday to Friday. Two groups of students were studied: one attended school from 07:00 to 12:00 h (morning group, n = 30); the other attended school from 14:00 to 18:00 (afternoon group, n = 22). None of the students worked or was engaged in other activity with a fixed schedule. All kept a sleep-wake diary for 2 weeks, in which they recorded their bedtimes, wakeup times, and sleep-onset latencies. The morning group delayed 47.4 min [t(29) = 4.72, p < 0.0001] and prolonged their sleep 118.2 min [t(29) = 9.4, p < 0.0001] during weekends. Although the afternoon group had the opportunity to maintain a delayed phase and a long sleep time throughout the week, they delayed their bedtime by 24 min [t(21) = 2.99, p < 0.01] during weekends, without changing their sleep duration. The findings suggest that the prolonged sleep during weekends is due to reduction of sleep during workdays, whereas the delay of bedtime seems to be associated with a tendency of the human circadian system to maintain a delayed phase     

Sleep Duration,Schedule and Quality among Urban Chinese Children and Adolescents: Associations with Routine After-School Activities

Background

With rapid urbanization accompanied by lifestyle changes, children and adolescents living in metropolitan areas are faced with many time use choices that compete with sleep. This study reports on the sleep hygiene of urban Chinese school students, and investigates the relationship between habitual after-school activities and sleep duration, schedule and quality on a regular school day.

Methods

Cross-sectional, school-based survey of school children (Grades 4–8) living in Shanghai, China, conducted in 2011. Self-reported data were collected on students’ sleep duration and timing, sleep quality, habitual after-school activities (i.e. homework, leisure-time physical activity, recreational screen time and school commuting time), and potential correlates.

Results

Mean sleep duration of this sample (mean age: 11.5-years; 48.6% girls) was 9 hours. Nearly 30% of students reported daytime tiredness. On school nights, girls slept less (p<0.001) and went to bed later (p<0.001), a sex difference that was more pronounced in older students. Age by sex interactions were observed for both sleep duration (p=0.005) and bedtime (p=0.002). Prolonged time spent on homework and mobile phone playing was related to shorter sleep duration and later bedtime. Adjusting for all other factors, with each additional hour of mobile phone playing, the odds of daytime tiredness and having difficulty maintaining sleep increased by 30% and 27% among secondary students, respectively.

Conclusion

There are sex differences in sleep duration, schedule and quality. Habitual activities had small but significant associations with sleep hygiene outcomes especially among secondary school students. Intervention strategies such as limiting children’s use of electronic screen devices after school are implicated.     

Sleep Loss and Performance of Anaesthesia Trainees and Specialists

Fatigue risk associated with work schedules of hospital doctors is coming under increasing scrutiny, with much of the research and regulatory focus on trainees. However, provision of 24 h services involves both trainees and specialists, who have different but interdependent work patterns. This study examined work patterns, sleep (actigraphy, diaries) and performance (psychomotor vigilance task pre‐ and post‐duty) of 28 anaesthesia trainees and 20 specialists across a two‐week work cycle in two urban public hospitals. Trainees at one hospital worked back‐to‐back 12 h shifts, while the others usually worked 9 h day shifts but periodically worked a 14 h day (08:00–22:00 h) to maintain cover until arrival of the night shift (10 h). On 11% of day shifts and 23% of night shifts, trainees were working with ≥2 h of acute sleep loss. However, average sleep loss was not greater on night shifts, possibly because workload at night in one hospital often permitted some sleep. Post‐night shift performance was worse than post‐day shift performance for the median (t₍₁₃₁₎=3.57, p<0.001) and slowest 10% of reaction times (t₍₁₃₄₎=2.91, p<0.01). At the end of night shifts, poorer performance was associated with longer shift length, longer time since waking, greater acute sleep loss, and more total work in the past 24 h. Specialists at both hospitals had scheduled clinical duties during the day and were periodically scheduled on call to cover after‐hours services. On 8% of day shifts and 14% of day+call schedules, specialists were working with ≥2 h of acute sleep loss. They averaged 0.6 h less sleep when working day shifts (t_(23.5)=2.66, p=0.014) and 0.8 h less sleep when working day shifts+call schedules (t_(26.3)=2.65, p=0.013) than on days off. Post‐duty reaction times slowed linearly across consecutive duty days (median reaction time, t₍₁₃₁₎=?3.38, p<0.001; slowest 10%, t₍₁₆₀₎=?3.33, p<0.01; fastest 10%, t₍₁₃₈₎=?2.67, p<0.01). Poorer post‐duty performance was associated with greater acute sleep loss and longer time since waking, but better performance was associated with longer day shifts, consistent with circadian improvement in psychomotor performance across the waking day. This appears to be the first study to document sleep loss among specialist anaesthetists. Consistent with observations from experimental studies, the sleep loss of specialists across 12 consecutive working days was associated with a progressive decline in post‐duty PVT performance. However, this decline occurred with much less sleep restriction (< 1 h per day) than in laboratory studies, suggesting an exacerbating effect of extended wakefulness and/or cumulative fatigue associated with work demands. For both trainees and specialists, robust circadian variation in PVT performance was evident in this complex work setting, despite the potential confounds of variable shift durations and workloads. The relationship between PVT performance of an individual and the safe administration of anaesthesia in the operating theater is unknown. Nevertheless, the findings reinforce that any schedule changes to reduce work‐related fatigue need to consider circadian performance variation and the potential transfer of workload and fatigue risk between trainees and specialists.     

Subjective and objective sleep among air ambulance personnel

ABSTRACT

The present study aimed to investigate the effects of shift work on sleep among pilots and Helicopter Emergency Medical Service crew members (HCM) in the Norwegian Air Ambulance. Sleep was assessed by diaries and actigraphy during a workweek (24 h duty for 7 consecutive days) in the winter season and a workweek during the summer season in pilots and HCM (N = 50). Additionally, differences in sleep were studied between the week before work, the workweek, and the week after work in both seasons. Results indicated that bedtime was later (p <.001) and time spent in bed (p <.05) was shorter during the summer, compared to the winter, season. The workers delayed the sleep period in the workweek, compared to the week before (winter: p <.001, summer: p <.001) and the week after (winter: p <.05-.001, summer: p <.001). They spent more time in bed during the workweek, compared to the week before (winter: p <.001, summer: p <.01) and after (winter: p <.001, summer: p =.37). Further, the workers had longer wake after sleep onset during the workweek, compared to the week before (winter: p <.001, summer: p <.01) and the week after (winter: p <.01, summer: p <.01). Finally, the workers had lower sleep efficiency during the workweek recorded by actigraphy compared to the week before (winter: p <.01, summer: p <.001) and the week after (winter: p <.01, summer: p <.001). According to the sleep diaries the total sleep time was 7:17 h in the winter and 7:03 h in the summer season. Overall, the sleep was somewhat affected during the workweek, with delayed sleep period, longer wake after sleep onset, and lower sleep efficiency compared to when off work. However, the workers spent more time in bed during the workweek compared to the weeks off, and they obtained over 7 h of sleep in both workweeks. Our findings suggest that the pilots and the HCM sleep well during the workweek, although it affected their sleep to some extent.     

CHRONIC SLEEP DEFICIT AND PERFORMANCE OF A SUSTAINED ATTENTION TASK—AN ELECTROOCULOGRAPHY STUDY

Electrooculography (EOG) was used to explore performance differences in a sustained attention task during rested wakefulness (RW) and after 7 days of partial sleep deprivation (SD). The RW condition was based on obtaining regular sleep, and the SD condition involved sleep restriction of 3?h/night for a week resulting in a total sleep debt of 21?h. The study used a counterbalanced design with a 2-wk gap between the conditions. Participants performed a sustained attention task for 45?min on four occasions: 10:00–11:00, 14:00–15:00, 18:00–19:00, and 22:00–23:00?h. The task required moving gaze and attention as fast as possible from a fixation point to a target. In each session, 120 congruent and 34 incongruent stimuli were presented, totaling 1232 observations/participant. Correct responses plus errors of omission (lapses) and commission (false responses) were recorded, and the effect of time-of-day on sustained attention following SD was investigated. The analysis of variance (ANOVA) model showed that SD affected performance on a sustained attention task and manifested itself in a higher number of omission errors: congruent stimuli (F_(1,64)?=?13.3, p?<?.001) and incongruent stimuli (F_(1,64)?=?14.0, p?<?.001). Reaction times for saccadic eye movements did not differ significantly between experimental conditions or by time-of-day. Commission errors, however, exhibited a decreasing trend during the day. The visible prevalence of omissions in SD versus RW was observed during the mid-afternoon hours (the so-called post-lunch dip) for both congruent and incongruent stimuli (F_(1,16)?=?5.3, p?=?.04 and F_(1,16)?=?5.6, p?=?.03, respectively), and at 18:00?h for incongruent stimuli (F_(1,13)?=?5.7, p?=?.03). (Author correspondence: magda.fafrowicz@uj.edu.pl)     

Can a Shorter Psychomotor Vigilance Task Be Usedas a Reasonable Substitute for the Ten‐Minute Psychomotor Vigilance Task?

The 10 min psychomotor vigilance task (PVT) is commonly used in laboratory studies to assess the impact of sleep loss, sustained wakefulness, and/or time of day on neurobehavioral performance. In field settings, though, it may be impractical for participants to perform a test of this length. The aim of this study was to identify a performance measure that is sensitive to the effects of fatigue but less burdensome than a 10 min test. Sixteen participants (11 female, 5 male; mean age=21.7 years) slept in the sleep laboratory overnight then remained awake for 28 h from 08:00 h. During every second hour, participants completed three PVTs of differing duration (10 min, 5 min, 90 sec). For the 5 min/10 min comparison, ANOVA indicated that response time was significantly affected by test length (F_1,14=26.9, p<.001) and hours of wakefulness (F_13,182=46.1, p<.001) but not by their interaction (F_13,182=1.7, ns). There was a strong correlation between response time on the 5 and 10 min PVTs (r=.88, p<.001). For the 90 sec/10 min comparison, ANOVA indicated that response time was significantly affected by test length (F_1,14=65.9, p<.001) and hours of wakefulness (F_13,182=29.7, p<.001) as well as by their interaction (F_13,182=6.0, p<.001). There was a strong correlation between response time on the 90 sec and 10 min PVTs (r=.77, p<.001). The effects of hours of wakefulness on neurobehavioral performance were similar for the 5 min and 10 min PVTs. In contrast, performance on the 90 sec PVT was less affected by hours of wakefulness than on the 10 min PVT. In addition, performance on the 10 min PVT was more highly correlated with the 5 min PVT than the 90 sec PVT. These data indicate that the 5 min PVT may provide a reasonable substitute for the 10 min PVT in circumstances where a test shorter than 10 min is required.     

Post-Sleep Inertia Performance Benefits of Longer Naps in Simulated Nightwork and Extended Operations

Operational settings involving shiftwork or extended operations require periods of prolonged wakefulness, which in conjunction with sleep loss and circadian factors, can have a negative impact on performance, alertness, and workplace safety. Napping has been shown to improve performance and alertness after periods of prolonged wakefulness and sleep loss. Longer naps may not only result in longer-lasting benefits but also increase the risk of sleep inertia immediately upon waking. The time course of performance after naps of differing durations is thus an important consideration in weighing the benefits and risks of napping in workplace settings. The objective of this study was to evaluate the effectiveness of nap opportunities of 20, 40, or 60 min for maintaining alertness and performance 1.5–6 h post-nap in simulated nightwork (P1) or extended operations (P2). Each protocol included 12 participants in a within-subjects design in a controlled laboratory environment. After a baseline 8 h time-in-bed, healthy young males (P1 mean age 25.1 yr; P2 mean age 23.2 yr) underwent either ≈20 h (P1) or ≈30 h (P2) of sleep deprivation on four separate occasions, followed by nap opportunities of 0, 20, 40, and 60 min. Sleep on the baseline night and during the naps was recorded polysomnographically. During the nap opportunities, sleep onset latency was short and sleep efficiency was high. A greater proportion of slow-wave sleep (SWS) was obtained in nap opportunities of 40 and 60 min compared with 20 min. Rapid eye movement (REM) sleep occurred infrequently. A subjective sleepiness rating (Karolinska Sleepiness Scale, KSS), 2-Back Working Memory Task (WMT), and Psychomotor Vigilance Task (PVT) were completed 1.5, 2, 2.5, 3, 4, 5, and 6 h post-nap. The slowest 10% of PVT responses were significantly faster after 40 and 60 min naps compared with a 20 min (P1) or no (P2) nap. There were significantly fewer PVT lapses after 40 and 60 min naps compared with no nap (P2), and after 60 min naps compared with 20 min naps (P1). Participants felt significantly less sleepy and made more correct responses and fewer omissions on the WMT after 60 min naps compared with no nap (P2). Subjective sleepiness and WMT performance were not related to the amount of nap-time spent in SWS. However, PVT response speed was significantly slower when time in SWS was <10 min compared with 20–29.9 min. In conclusion, in operationally relevant scenarios, nap opportunities of 40 and 60 min show more prolonged benefits 1.5–6 h post-nap, than a 20 min or no nap opportunity. Benefits were more apparent when the homeostatic pressure for sleep was high and post-nap performance testing occurred across the afternoon (P2). For sustained improvement in cognitive performance, naps of 40–60 min are recommended. (Author correspondence: t.l.signal@massey.ac.nz)     

Individual differences in the sleep/wake cycle of Arctic flexitime workers

Daytime workers tend to have shorter sleep duration and earlier sleep onset during work days than on days off. Large individual differences in sleep onset and sleep duration may be observed on work days, but work usually synchronizes sleep offset to a similar time. The present study describes individual differences in sleep behaviour of 48 daytime workers (25 men, aged 20–58 years) from an iron ore mine in Northern Sweden. The aim of the study was to determine whether differences in sleep patterns during work days were associated with the outcomes of sleepiness and sleep complaints. Cluster analysis was used to group workers into two categories of sleep onset and sleep duration. The “Late Sleep Onset” cluster comprised workers who slept 1.30 h later than the “Early Sleep Onset” cluster (p < 0.0001 for all weekdays). The “Long Sleep Duration” cluster slept 1.10 h longer than the “Short Sleep Duration” cluster (p < 0.0002 for work nights). The “Late Sleep Onset” cluster reported less refreshing sleep (p < 0.01) and had lower sufficient sleep scores (p < 0.01) than the “Early Sleep Onset” cluster. The “Short Sleep Duration” cluster also reported lower scores for sufficient sleep (p < 0.04) than the “Long Sleep Duration” cluster. For combined characteristics (phase and duration), workers with a late phase and short sleep duration reported greater sleep debt and sleepiness than workers with an early phase and short sleep duration (p < 0.02). Work schedule and commuting time modulate both sleep phase and sleep duration independently. Workers, classified as having an intermediate sleep phase preference, can organize their sleep time in order to minimize sleep debt and sleepiness symptoms. Individual differences in sleep phase and duration should be considered when promoting well-being at work even among groups with similar sleep needs. In order to minimize sleep debt and sleepiness symptoms, successful sleep behaviour could be promoted involving extend use of flexitime arrangement (i.e. later starting times) and reduce use of alarm clocks.     

Fatigue and Mood Correlates of Sleep Length in Three Age‐Social Groups: School Children,Students, and Employees

The aim of the study was to trace the consequences of insufficient sleep, in terms of chronic sleep reduction rather than acute sleep deprivation, on fatigue, mood, cognitive performance self‐estimations, and daytime sleepiness in different age‐social groups. The age group of the subjects reflects their social situation and their working time organization: adolescents (n=191) obeyed the strict school schedules with starting times often before 08:00 h; university students (n=115) had more flexible timetables; young employees (n=126) were engaged in regular morning schedules or irregular daytime hours or day and night shifts. A questionnaire study determined the declared need of sleep, self‐reported sleep length, chronic fatigue (using a scale comprised of eight fatigue symptoms and four mood and three cognitive items), and daytime sleepiness (Epworth Sleepiness Scale). The declared need for sleep decreased in subsequent age groups from 9 h 23 min in school children to 8 h 22 min in university students and to 7 h 37 min in young employees. Consequently, the discrepancy between preferred and real sleep length (sleep deficit) was the largest in adolescents: 106 min. Females showed a greater need of sleep than males (p=.025) and significantly more fatigue, mood, and cognitive problems; they also exhibited higher level of daytime sleepiness (p<.000). The sleep index (reported sleep length related to requirements) correlated significantly with all health issues in women (p<.000), while only with fatigue symptoms in men (p=.013). Actual sleep length was unrelated to mood and fatigue issues; the declared individual need of sleep and sleep index showed significant associations, especially in the group of adolescents. The most frequent complaints of adolescents included tiredness on awakening (46%), nervousness, and general weakness; university students reported excessive drowsiness (50%), tension, and nervousness; employees suffered mostly from negative moods, such as tension (49%), nervousness, and irritability. The findings of the study indicate that chronic sleep loss seems to affect females more severely than males. The associations of fatigue and mood with sleep need and sleep index were more pronounced in younger subjects. Surprisingly, fatigue symptoms in school children and university students were as frequent as in hard‐working adults. Because the problem of insufficient sleep is already present in youngsters, their work time organization needs more attention.     

The use of Artemia biomass sampling to predict cyst yields in culture ponds

The possibility of using biomass volume (= mean biomass present in the pond.week ^–1) to predict the total amount of harvestable cysts (= kg wet weight collected. week ^–1) produced in a culture pond by an Artemia franciscana population using a mixed model regression was evaluated for two different sampling methods; horizontal transects and vertical point samples. For transects, the following equation was found: `log (0.01 + cyst yields) = –2.05 + 0.025<sup>*</sup>(biomass volume)' with F <sub>(1, 4.87)</sub> = 8.83 and p = 0.032. For the point samples, the regression was also significant with F <sub>(1, 55.2)</sub> = 13.62 and p = 0.0005 for following equation: `log (0.01 + cyst yield) = –3.613 + 0.021^*(biomass volume). As pond effect and interaction terms did not significantly explain a significant portion of the variance for either of the sampling methods (Transects: pond: F _{(3, 14.3)} = 2.48; p = 0.103; pond^*biomass volume: F _{(3, 3.61)} = 4.63; p = 0.0976; Point samples: pond: F _{(3, 44.5)} = 0.00; p = 0.999; pond^*biomass volume: F _{(3, 44.2)} = 0.11; p = 0.954 ), the variable pond (repeated measurement factor) was not included in the final calculations for the regression equations. Although a combination of factors influences the equation, the high significance levels of the regression indicate biomass volume can be safely used to predict production trends. The low investment requirements of this method make it especially attractive for on farm use, where correctly determining the point of cyst decline will help farmers to allocate resources where needed.     

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 S?o 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.     

Interaction with Shelter Dogs Reduces Negative Affect of Adolescents in Substance Use Disorder Treatment

We investigated the effectiveness of a human–animal interaction program, involving dogs from an animal shelter, in improving affect of adolescent males in inpatient treatment for substance use disorder (SUD). We hypothesized that adolescents would experience improvements in affect and attitudes toward activities when participating in human–dog interaction activities (dog-interaction condition) compared with “treatment-as-is” recreational activities (control condition). Participants were assigned to weekly 1-h-long condition activities for 8 weeks (4 weeks per condition). Due to attrition, only the participants’ first and second exposures to each condition were evaluated. Using a withinand between-subjects, repeated measures crossover design, we assessed effects of the two conditions on affective states as indexed by Positive and Negative Affect Scale-Expanded Form (PANAS-X) subscales (mixed linear model, n = 12). Attitudes toward doginteraction and control activities were assessed using a researcher-generated survey (ordered logistic regression, n = 14, mean age = 16.2 years). Condition impacted Hostility (F_(1,31) = 6.55, p < 0.05) and Sadness (F_(1,41) = 4.62, p < 0.05) subscale scores; scores were higher following the control condition and lower following the dog-interaction condition. There was a carryover effect of condition in the previous activity session on Sadness scores during the current activity session (F_(1,41) = 4.32, p < 0.05), suggesting that the prior session experience affected current expectations. In the attitudes survey, the dog-interaction condition elicited more positive responses than the control condition (X² ≥ 4.10, df = 1, p < 0.05). From this exploratory study, we conclude that the dog-interaction activities induced an improvement in affect, specifically within dimensions of negative affect, and participants had a more favorable attitude toward the dog activities than the treatment-as-is activities. Offering activities involving interaction with shelter dogs thus shows promise as a useful method for restoring responsiveness to naturally reinforcing (non-substance-related) affective stimuli in adolescents with SUD.