Normal Sleep in Children and Adolescence.

Adequate sleep is essential for healthy development in childhood and adolescence. Healthy sleep contributes to good physical health, immune function, mental health, and academic performance. The regulation and architecture of sleep change greatly across childhood and adolescence, and the ability to obtain sufficient sleep is impacted by a range of factors that change with maturation. This article describes normal sleep across childhood and adolescence and discusses some of the most common barriers to adequate sleep, including early school start times, technology use, and changes to circadian rhythms, and sleep homeostasis across puberty.

Effectiveness of H5P in improving student learning outcomes in an online tertiary education setting.

Innovative, pedagogically informed instructional design is instrumental in increasing student engagement and improving learning outcomes in online learning environments. Interactive learning resources provide students with the opportunity to engage with content in a more personalised manner. H5P (HTML 5 Package) is a collaborative platform that allows developers to create interactive content and has been regularly used in education settings. Some evidence suggests using interactive H5P resources in online education courses could lead to greater student engagement. However, to date, there has been little investigation into whether H5P resources can improve student learning outcomes. The current study aimed to assess whether using interactive H5P resources improved assessed learning outcomes in an online undergraduate psychology course. A randomized cross-over design was utilized to test whether students exposed to H5P interactive videos had improved assessment results when compared to a control group. This study found no meaningful differences in assessment scores between students exposed to H5P versus those that were not. There was low overall engagement with the interactive content. However, students who did engage with the resources reported a positive experience and indicated a preference for more interactive elements in future courses. Future research should extend on the instructional design obstacles identified in this study, for example, by examining whether improved accessibility and education on the benefits of interactive resources would increase engagement and grades.

The effect of mobile phone use at night on the sleep of pre-adolescent (8-11 year), early adolescent (12-14 year) and late adolescent (15-18 year) children: A study of 252,195 Australian children.

OBJECTIVES: To examine whether the association previously reported between mobile phone use at night and poor sleep in adolescents also generalizes to pre-adolescent children. DESIGN: Cross sectional. SETTING: Database provided by Resilient Youth Australia Pty Ltd. PARTICIPANTS: Survey completed by 84,915 pre-adolescent (8-11 years), 99,680 early adolescent (12-14 years) and 67,600 late adolescent Australian children (15-18 years). MEASUREMENT: Children were asked how frequently they obtained 8 hours of sleep on most nights and if they used their mobile phone at night to send and receive messages between 10 PM and 6 AM. Binary logistic regression analyses were used to examine the association between mobile phone use at night and sleeping 8h or more on most nights with gender, socioeconomic status and year of study (2014-2018) as covariates. RESULTS: For all age cohorts including pre-adolescent children, mobile phone use at night was associated with lower odds of obtaining 8 hours of sleep on most nights. CONCLUSION: The present findings confirm that the association between mobile phone use at night and poor sleep previously reported in adolescent children also generalises to pre-adolescent children. Given the increased uptake of smartphone devices in ever younger children the findings point to the need to provide parents, schools and communities with resources to promote child sleep hygiene and media use at bedtime.

The relationships between coping styles and food intake in shiftworking nurses and midwives: a pilot study.

Shiftworkers are more likely to suffer from gastrointestinal disease and Type 2 Diabetes than the general population, likely due to their altered dietary intakes. Previous research has suggested that coping strategies and health behaviours may be linked, however, questions remain regarding these relationships in shiftworking populations. The Standard Shiftwork Index and Food Frequency Questionnaire were completed by nurses/midwives working forward rotating shifts (N=27, female=24, age=38.4 ± 13.1 y). Greater engaged coping strategy usage was associated with lower total energy, fat, carbohydrate and sugar intake (ρs>-0.1). Greater disengaged coping strategy usage was associated with greater intake of these nutrients (ρs>0.1). Results suggest that engaged coping strategies may contribute to healthier dietary choices. A greater focus on coping styles, particularly during nursing education, may improve shiftworkers' health.

The impact of a meal, snack, or not eating during the night shift on simulated driving performance post-shift.

Objective The commute home following a night shift is associated with an increased risk for accidents. This study investigated the relationship between food intake during the night shift and simulated driving performance post-shift. Methods Healthy non-shift working males (N=23) and females (N=16), aged 18-39 years (mean 24.5, standard deviation 5.0, years) participated in a seven-day laboratory study and underwent four simulated night shifts. Participants were randomly allocated to one of three conditions: meal at night (N=12; 7 males), snack at night (N=13; 7 males) or no eating at night (N=14; 9 males). During the night shift at 00:30 hours, participants either ate a large meal (meal at night condition), a snack (snack at night condition), or did not eat during the night shift (no eating at night condition). During the second simulated night shift, participants performed a 40-minute York driving simulation at 20:00, 22:30, 01:30, 04:00, and 07:30 hours (similar time to a commute from work). Results The effects of eating condition, drive time, and time-on-task, on driving performance were examined using mixed model analyses. Significant condition×time interactions were found, where at 07:30 hours, those in the meal at night condition displayed significant increases in time spent outside of the safe zone (percentage of time spent outside 10 km/hour of the speed limit and 0.8 meters of the lane center; P<0.05), and greater lane and speed variability (both P<0.01) compared to the snack and no eating conditions. There were no differences between the snack and no eating conditions. Conclusion Driver safety during the simulated commute home is greater following the night shift if a snack, rather than a meal, is consumed during the shift.

Normal Sleep in Children and Adolescence.

Adequate sleep is essential for healthy development in childhood and adolescence. Healthy sleep contributes to good physical health, immune function, mental health, and academic performance. The regulation and architecture of sleep change greatly across childhood and adolescence, and the ability to obtain sufficient sleep is impacted by a range of factors that change with maturation. This article describes normal sleep across childhood and adolescence and discusses some of the most common barriers to adequate sleep, including early school start times, technology use, and changes to circadian rhythms, and sleep homeostasis across puberty.

A pilot study investigating the impact of a caffeine-nap on alertness during a simulated night shift.

Consuming coffee immediately prior to a nap, known as a caffeine-nap, has been shown to improve alertness during the day, but it is unknown whether a caffeine-nap is effective at reducing sleep inertia during the night. A simulated shiftwork cross-over laboratory study was conducted whereby participants (N = 6, 4 F, 21-36y) consumed 200 mg of caffeine, or decaffeinated coffee (placebo), immediately prior to a 30 min nap opportunity at 03:30 h. Compared to placebo, the caffeine-nap resulted in improved vigilant attention and subjective fatigue in the 45 min post-nap opportunity. The caffeine-nap may be useful in reducing sleep inertia in shift workers who nap on nightshift.

Altering meal timing to improve cognitive performance during simulated nightshifts.

Altering meal timing could improve cognition, alertness, and thus safety during the nightshift. This study investigated the differential impact of consuming a meal, snack, or not eating during the nightshift on cognitive performance (ANZCTR12615001107516). 39 healthy participants (59% male, age mean±SD: 24.5 ± 5.0y) completed a 7-day laboratory study and underwent four simulated nightshifts. Participants were randomly allocated to: Meal at Night (MN; n= 12), Snack at Night (SN; n = 13) or No Eating at Night (NE; n = 14). At 00:30 h, MN consumed a meal and SN consumed a snack (30% and 10% of 24 h energy intake respectively). NE did not eat during the nightshift. Macronutrient intake was constant across conditions. At 20:00 h, 22:30 h, 01:30 h, and 04:00 h, participants completed the 3-min Psychomotor Vigilance Task (PVT-B), 40-min driving simulator, post-drive PVT-B, subjective sleepiness scale, 2-choice Reaction Time task, and Running Memory task. Objective sleep was recorded for each of the day sleeps using Actigraphy and for the third day sleep, Polysomnography was used. Performance was compared between conditions using mixed model analyses. Significant two-way interactions were found. At 04:00 h, SN displayed increased time spent in the safe zone (p < .001; percentage of time spent within 10 km/h of the speed limit and 0.8 m of lane center), and decreases in speed variability (p < .001), lane variability (p < .001), post-drive PVT-B lapses (defined as RT > 355 ms; p < .001), and reaction time on the 2-choice reaction time task (p < .001) and running memory task (p < .001) compared to MN and NE. MN reported greater subjective sleepiness at 04:00 h (p < .001) compared to SN and NE. There was no difference in objective sleep between eating conditions. Eating a large meal during the nightshift impairs cognitive performance and sleepiness above the effects of time of night alone. For improved performance, shiftworkers should opt for a snack at night.

Effects of fatigue on teams and their role in 24/7 operations.

In 24/7 operations, fatigue from extended work hours and shift work is ubiquitous. Fatigue is a significant threat to performance, productivity, safety, and well-being, and strategies for managing fatigue are an important area of research. At the level of individuals, the effects of fatigue on performance are relatively well understood, and countermeasures are widely available. At the level of organizations, the effects of fatigue are also relatively well understood, and organizational approaches to fatigue risk management are increasingly well documented. However, in most organizational settings, individuals work in teams, and teams are the building blocks of the organizational enterprise. Yet, little is known about the effects of fatigue on team functioning. Here we discuss the effects of fatigue at the levels of individuals, teams, and organizations, and how the consequences of fatigue cross these levels to impact overall productivity and safety. Furthermore, we describe the pivotal role of teams in understanding the adverse organizational effects of fatigue in 24/7 operations and argue that teams may be leveraged to mitigate these effects. Systematic investigation of the effects of fatigue on teams is a promising avenue toward advances in fatigue risk management and provide some ideas for how this may be approached.

Subjective Hunger, Gastric Upset, and Sleepiness in Response to Altered Meal Timing during Simulated Shiftwork.

Shiftworkers report eating during the night when the body is primed to sleep. This study investigated the impact of altering food timing on subjective responses. Healthy participants (n = 44, 26 male, age Mean ± SD = 25.0 ± 2.9 years, BMI = 23.82 ± 2.59kg/m2) participated in a 7-day simulated shiftwork protocol. Participants were randomly allocated to one of three eating conditions. At 00:30, participants consumed a meal comprising 30% of 24 h energy intake (Meal condition; n = 14, 8 males), a snack comprising 10% of 24 h energy intake (Snack condition; n = 14; 8 males) or did not eat during the night (No Eating condition; n = 16, 10 males). Total 24 h individual energy intake and macronutrient content was constant across conditions. During the night, participants reported hunger, gut reaction, and sleepiness levels at 21:00, 23:30, 2:30, and 5:00. Mixed model analyses revealed that the snack condition reported significantly more hunger than the meal group (p < 0.001) with the no eating at night group reporting the greatest hunger (p < 0.001). There was no difference in desire to eat between meal and snack groups. Participants reported less sleepiness after the snack compared to after the meal (p < 0.001) or when not eating during the night (p < 0.001). Gastric upset did not differ between conditions. A snack during the nightshift could alleviate hunger during the nightshift without causing fullness or increased sleepiness.

Self-regulation and social behavior during sleep deprivation.

An emerging literature is specifically focusing on the effects of sleep deprivation on aspects of social functioning and underlying neural changes. Two critical facets of social behavior emerge that are negatively impacted by sleep deprivation-self-regulation, which includes behavioral and emotional regulation, and social monitoring, which includes perceiving and interpreting cues relating to self and others. Sleep deprived individuals performing tasks with social components show altered brain activity in areas of the prefrontal cortex implicated in self-control, inhibition, evaluation, and decision-making, in proximity to mesocorticolimbic pathways to reward and emotional processing areas. These cognitive changes lead to increased reward seeking and behaviors that promote negative health outcomes (such as increased consumption of indulgence foods). These changes also lead to emotional disinhibition and increased responses to negative stimuli, leading to reductions in trust, empathy, and humor. Concomitant attentional instability leads to impaired social information processing, impairing individual and team performance and increasing likelihood of error, incident, and injury. Together, changes to reward seeking, the foundational components of social interaction, and interpretation of social cues, can result in unpleasant or deviant behavior. These behaviors are perceived and negatively responded to by others, leading to a cycle of conflict and withdrawal. Further studies are necessary and timely. Educational and behavioral interventions are required to reduce health-damaging behaviors, and to reduce emotionally-laden negative interpretation of sleep-deprived exchanges. This may assist with health, and with team cohesion (and improved performance and safety) in the workplace and the home.

Impact of high-frequency email and instant messaging (E/IM) interactions during the hour before bed on self-reported sleep duration and sufficiency in female Australian children and adolescents.

INTRODUCTION: Social media interactions via email and instant messaging (E/IM) are common in children and adolescents and may lead to insufficient sleep. This study investigated associations between high-frequency E/IM use to interact with peers, perceived insufficient sleep, and reduced time in bed (TIB) in female children and adolescents. METHODS: The Children's Report of Sleep Patterns was completed by 189 female primary and secondary school students (8-16 years old). Responses were categorized as binary variables (high-frequency use vs not high-frequency use; right amount of sleep vs too little sleep), and TIB was calculated from bed and wake times for the previous 24 hours. RESULTS: High-frequency social media interactions using E/IM during the hour before bed were significantly associated with perceived insufficient sleep (odds ratio [confidence interval]: 2.68 [1.39-5.17]) but not with reduced TIB (-19.07 [-40.02 to 1.89]). CONCLUSIONS: High-frequency social media interactions using E/IM in the hour before bed are a potentially modifiable risk factor for insufficient sleep in female students. Strategies to reduce nighttime usage may improve sleep in children and adolescents.

Timing of Australian flight attendant food and beverage while crewing: a preliminary investigation.

Flight attendants experience circadian misalignment and disrupted sleep and eating patterns. This survey study examined working time, sleep, and eating frequency in a sample (n=21, 4 males, 17 females) of Australian flight attendants (mean age=41.8 yr, SD=12.0 yr, mean BMI=23.8 kg/m2, SD=4.1 kg/m2). Respondents indicated frequencies of snack, meal, and caffeine consumption during their last shift. Reported sleep duration on workdays (mean=4.6 h, SD=1.9 h) was significantly lower than on days off (M=7.2 h, SD=1.2 h, p<0.001), and significantly lower than perceived sleep need (M=8.1 h, SD=0.8 h, p<0.001). Food intake was distributed throughout shifts and across the 24 h period, with eating patterns incongruent with biological eating periods. Time available, food available, and work breaks were the most endorsed reasons for food consumption. Caffeine use and reports of gastrointestinal disturbance were common. Working time disrupts sleep and temporal eating patterns in flight attendants and further research into nutritional and dietary-related countermeasures may be beneficial to improving worker health and reducing circadian disruption.

Coping with shift work-related circadian disruption: A mixed-methods case study on napping and caffeine use in Australian nurses and midwives.

INTRODUCTION: Two of the most ubiquitous fatigue countermeasures used by shift-working nurses are napping and caffeine. This mixed-methods case study investigated the ways nurses and midwives utilised napping and caffeine countermeasures to cope with shift work, and associated sleep, physical health and psychological health outcomes. MATERIALS AND METHODS: N = 130 Australian shift-working nurses and midwives (mean age = 44 years, range = 21-67, 115F, 15M) completed the Standard Shiftwork Index. A sub-set of 22 nurses and midwives completed an in-depth interview. RESULTS: Nearly 70% of participants reported napping. Those who napped during night shifts had significantly less total sleep time before (F2,75 = 5.5, p < 0.01) and between days off (F2,82 = 3.9, p < 0.05). By the end of the night shift, average hours of time awake were significantly less for prophylactic and on-shift nappers compared to non-nappers (F2,85 = 97.2, p < 0.001). Since starting shift work, the percentage of high caffeine consumers (>400 mg/day) increased from 15% to 33% of the sample and an average of 4 (SD = 2) caffeinated beverages per day was reported. Increased caffeine consumption was associated with greater sleep disturbance (r = 0.26, p < 0.05), psychological distress (r = 0.37, p < 0.001), abdomen pain (r = 0.27, p < 0.05) and weight gain since starting shift work (r = 0.25, p < 0.05). Interviews confirmed these relationships and revealed that caffeine consumption on night shift was common, whereas napping on night shift was dependent on a number of factors including ability to sleep during the day. CONCLUSION: This study identified reasons shift workers chose to engage in or abstain from napping and consuming caffeine, and how these strategies related to poor sleep and health outcomes. Further research is required to help develop recommendations for shift workers regarding napping and caffeine consumption as fatigue countermeasures, whilst taking into account the associated hazards of each strategy.

Eating on nightshift: A big vs small snack impairs glucose response to breakfast.

Shift work is a risk factor for chronic diseases such as Type 2 diabetes. Food choice may play a role, however simply eating at night when the body is primed for sleep may have implications for health. This study examined the impact of consuming a big versus small snack at night on glucose metabolism. N = 31 healthy subjects (21-35 y; 18 F) participated in a simulated nightshift laboratory study that included one baseline night of sleep (22:00 h-07:00 h) and one night awake with allocation to either a big snack (2100 kJ) or small snack (840 kJ) group. The snack was consumed between 00:00-00:30 h and consisted of low fat milk, a sandwich, chips and fruit (big snack) or half sandwich and fruit (small snack). Subjects ate an identical mixed meal breakfast (2100 kJ) at 08:30 h after one full night of sleep and a simulated nightshift. Interstitial glucose was measured continuously during the entire study using Medtronic Continual Glucose Monitors. Only subjects with identical breakfast consumption and complete datasets were analysed (N = 20). Glucose data were averaged into 5-minute bins and area under the curve (AUC) was calculated for 90 min post-breakfast. Pre-breakfast, glucose levels were not significantly different between Day1 and Day2, nor were they different between snack groups (p > 0.05). A snack group by day interaction effect was found (F1,16 = 5.36, p = 0.034) and post-hocs revealed that in the big snack group, AUC response to breakfast was significantly higher following nightshift (Day2) compared to Day1 (p = 0.001). This translated to a 20.8% (SEM 5.6) increase. AUC was not significantly different between days in the small snack group. Consuming a big snack at 00:00 h impaired the glucose response to breakfast at 08:30 h, compared to a smaller snack. Further research in this area will inform dietary advice for shift workers, which could include recommendations on how much to eat as well as content.

Sleep inertia associated with a 10-min nap before the commute home following a night shift: A laboratory simulation study.

Night shift workers are at risk of road accidents due to sleepiness on the commute home. A brief nap at the end of the night shift, before the commute, may serve as a sleepiness countermeasure. However, there is potential for sleep inertia, i.e. transient impairment immediately after awakening from the nap. We investigated whether sleep inertia diminishes the effectiveness of napping as a sleepiness countermeasure before a simulated commute after a simulated night shift. N=21 healthy subjects (aged 21-35 y; 12 females) participated in a 3-day laboratory study. After a baseline night, subjects were kept awake for 27h for a simulated night shift. They were randomised to either receive a 10-min nap ending at 04:00 plus a 10-min pre-drive nap ending at 07:10 (10-NAP) or total sleep deprivation (NO-NAP). A 40-min York highway driving task was performed at 07:15 to simulate the commute. A 3-min psychomotor vigilance test (PVT-B) and the Samn-Perelli Fatigue Scale (SP-Fatigue) were administered at 06:30 (pre-nap), 07:12 (post-nap), and 07:55 (post-drive). In the 10-NAP condition, total pre-drive nap sleep time was 9.1±1.2min (mean±SD), with 1.3±1.9min spent in slow wave sleep, as determined polysomnographically. There was no difference between conditions in PVT-B performance at 06:30 (before the nap). In the 10-NAP condition, PVT-B performance was worse after the nap (07:12) compared to before the nap (06:30); no change across time was found in the NO-NAP condition. There was no significant difference between conditions in PVT-B performance after the drive. SP-Fatigue and driving performance did not differ significantly between conditions. In conclusion, the pre-drive nap showed objective, but not subjective, evidence of sleep inertia immediately after awakening. The 10-min nap did not affect driving performance during the simulated commute home, and was not effective as a sleepiness countermeasure.

Do night naps impact driving performance and daytime recovery sleep?

Short, nighttime naps are used as a fatigue countermeasure in night shift work, and may offer protective benefits on the morning commute. However, there is a concern that nighttime napping may impact upon the quality of daytime sleep. The aim of the current project was to investigate the influence of short nighttime naps (<30min) on simulated driving performance and subsequent daytime recovery sleep. Thirty-one healthy subjects (aged 21-35 y; 18 females) participated in a 3-day laboratory study. After a 9-h baseline sleep opportunity (22:00h-07:00h), subjects were kept awake the following night with random assignment to: a 10-min nap ending at 04:00h plus a 10-min nap at 07:00h; a 30-min nap ending at 04:00h; or a no-nap control. A 40-min driving simulator task was administered at 07:00h and 18:30h post-recovery sleep. All conditions had a 6-h daytime recovery sleep opportunity (10:00h-16:00h) the next day. All sleep periods were recorded polysomnographically. Compared to control, the napping conditions did not significantly impact upon simulated driving lane variability, percentage of time in a safe zone, or time to first crash on morning or evening drives (p>0.05). Short nighttime naps did not significantly affect daytime recovery total sleep time (p>0.05). Slow wave sleep (SWS) obtained during the 30-min nighttime nap resulted in a significant reduction in SWS during subsequent daytime recovery sleep (p<0.05), such that the total amount of SWS in 24-h was preserved. Therefore, short naps did not protect against performance decrements during a simulated morning commute, but they also did not adversely affect daytime recovery sleep following a night shift. Further investigation is needed to examine the optimal timing, length or combination of naps for reducing performance decrements on the morning commute, whilst still preserving daytime sleep quality.

The impact of short night-time naps on performance, sleepiness and mood during a simulated night shift.

Short naps on night shift are recommended in some industries. There is a paucity of evidence to verify the sustained recovery benefits of short naps in the last few hours of the night shift. Therefore, the current study aimed to investigate the sustained recovery benefits of 30 and 10-min nap opportunities during a simulated night shift. Thirty-one healthy participants (18F, 21-35 y) completed a 3-day, between-groups laboratory study with one baseline night (22:00-07:00 h time in bed), followed by one night awake (time awake from 07:00 h on day two through 10:00 h day three) with random allocation to: a 10-min nap opportunity ending at 04:00 h, a 30-min nap opportunity ending at 04:00 h or no nap (control). A neurobehavioral test bout was administered approximately every 2 h during wake periods. There were no significant differences between nap conditions for post-nap psychomotor vigilance performance after controlling for pre-nap scores (p > 0.05). The 30-min nap significantly improved subjective sleepiness compared to the 10-min nap and no-nap control (p < 0.05). The 10-min nap significantly worsened negative mood compared to the 30-min nap and no-nap control (p < 0.01). Contrary to some evidence suggesting "power naps" can help to alleviate performance decrements, a 30-min nap opportunity at approximately 04:00 h was found to improve subjective, but not objective sleepiness. A 10-min nap may lead to increased negative mood in the hours following the nap due to a "short nap aversion" effect.

Sleep inertia during a simulated 6-h on/6-h off fixed split duty schedule.

Sleep inertia is a safety concern for shift workers returning to work soon after waking up. Split duty schedules offer an alternative to longer shift periods, but introduce additional wake-ups and may therefore increase risk of sleep inertia. This study investigated sleep inertia across a split duty schedule. Sixteen participants (age range 21-36 years; 10 females) participated in a 9-day laboratory study with two baseline nights (10 h time in bed, [TIB]), four 24-h periods of a 6-h on/6-h off split duty schedule (5-h TIB in off period; 10-h TIB per 24 h) and two recovery nights. Two complementary rosters were evaluated, with the timing of sleep and wake alternating between the two rosters (2 am/2 pm wake-up roster versus 8 am/8 pm wake-up roster). At 2, 17, 32 and 47 min after scheduled awakening, participants completed an 8-min inertia test bout, which included a 3-min psychomotor vigilance test (PVT-B), a 3-min Digit-Symbol Substitution Task (DSST), the Karolinska Sleepiness Scale (KSS), and the Samn-Perelli Fatigue Scale (SP-Fatigue). Further testing occurred every 2 h during scheduled wakefulness. Performance was consistently degraded and subjective sleepiness/fatigue was consistently increased during the inertia testing period as compared to other testing times. Morning wake-ups (2 am and 8 am) were associated with higher levels of sleep inertia than later wake-ups (2 pm and 8 pm). These results suggest that split duty workers should recognise the potential for sleep inertia after waking, especially during the morning hours.

The effect of split sleep schedules (6h-on/6h-off) on neurobehavioural performance, sleep and sleepiness.

Shorter, more frequent rosters, such as 6h-on/6h-off split shifts, may offer promise to sleep, subjective sleepiness and performance by limiting shift length and by offering opportunities for all workers to obtain some sleep across the biological night. However, there exists a paucity of studies that have examined these shifts using objective measures of sleep and performance. The present study examined neurobehavioural performance, sleepiness and sleep during 6h-on/6h-off split sleep schedules. Sixteen healthy adults (6 males, 26.13 y ± 4.46) participated in a 9-day laboratory study that included two baseline nights (BL, 10h time in bed (TIB), 2200 h-0800 h), 4 days on one of two types of 6h-on/6h-off split sleep schedules with 5h TIB during each 'off' period (6h early: TIB 0300 h-0800 h and 1500 h-20000 h, or 6-h late: TIB 0900 h-1400 h and 2100 h-0200 h), and two recovery nights (10h TIB per night, 2200 h-0800 h). Participants received 10h TIB per 24h in total across both shift schedules. A neurobehavioural test bout was completed every 2 h during wake, which included the Psychomotor Vigilance Task (PVT) and the Karolinska Sleepiness Scale (KSS). Linear mixed effects models were used to assess the effect of day (BL, shift days 1-4), schedule (6h early, 6h late) and trial (numbers 1-6) on PVT lapses (operationalised as the number of reaction times >500 ms), PVT total lapse time, PVT fastest 10% of reaction times and KSS. Analyses were also conducted examining the effect of day and schedule on sleep variables. Overall, PVT lapses and total lapse time did not differ significantly between baseline and shift days, however, peak response speeds were significantly slower on the first shift day when compared to baseline, but only for those in the 6h-late condition. Circadian variations were apparent in performance outcomes, with individuals in the 6h-late condition demonstrated significantly more and longer lapses and slower peak reaction times at the end of their night shift (0730 h) than at any other time during their shifts. In the 6h-early condition, only response speed significantly differed across trials, with slower response speeds occurring at trial 1 (0930 h) than in trials 3 (1330 h) or 4 (2130 h). While subjective sleepiness was higher on shift days than at baseline, sleepiness did not accumulate across days. Total sleep was reduced across split sleep schedules compared to baseline. Overall, these results show that while there was not a cumulative cost to performance across days of splitting sleep, participants obtained less sleep and reported lowered alertness on shift days. Tests near the circadian nadir showed higher sleepiness and increased performance deficits. While this schedule did not produce cumulative impairment, the performance deficits witnessed during the biological night are still of operational concern for industry and workers alike.