6h-off) on neurobehavioural performance, sleep and sleepiness

Applied Ergonomics 54 (2016) 72e82

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Applied Ergonomics journal homepage: www.elsevier.com/locate/apergo

The effect of split sleep schedules (6h-on/6h-off) on neurobehavioural performance, sleep and sleepiness Michelle A. Short a, b, c, *, Stephanie Centofanti a, Cassie Hilditch a, Siobhan Banks a, Kurt Lushington a, Jillian Dorrian a a b c

Centre for Sleep Research, University of South Australia, Adelaide, Australia Bushfire Cooperative Research Centre, East Melbourne, Australia School of Psychology, Flinders University, Bedford Park, Australia

a r t i c l e i n f o

a b s t r a c t

Article history: Received 27 October 2014 Received in revised form 20 October 2015 Accepted 9 December 2015 Available online

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, 26.13y ± 4.46) participated in a 9-day laboratory study that included two baseline nights (BL, 10h time in bed (TIB), 2200h-0800h), 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 0300h-0800h and 1500h-20000h, or 6-h late: TIB 0900h-1400h and 2100h-0200h), and two recovery nights (10h TIB per night, 2200h0800h). 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 1e4), schedule (6h early, 6h late) and trial (numbers 1e6) 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 (0730h) 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 (0930h) than in trials 3 (1330h) or 4 (2130h). 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. Crown Copyright © 2015 Published by Elsevier Ltd. All rights reserved.

Keywords: Split sleep Shiftwork Sustained operations Continuous operations Attention Performance

1. Introduction

* Corresponding author. Centre for Sleep Research, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia. E-mail address: [email protected] (M.A. Short). http://dx.doi.org/10.1016/j.apergo.2015.12.004 0003-6870/Crown Copyright © 2015 Published by Elsevier Ltd. All rights reserved.

Shift work is problematic because it frequently entails both prolonged wakefulness and circadian misalignment (Folkard et al., 2005). Resultantly, shift work is associated with impaired alertness and heightened risk of fatigue, workplace accidents, performance

M.A. Short et al. / Applied Ergonomics 54 (2016) 72e82

deficits, insufficient and low quality sleep, and poor health (Dembe et al., 2006; Dinges, 1995; Driscoll et al., 2007; Pilcher et al., 2000; Rajaratnam and Arendt, 2001; Tilley et al., 1982). To manage the need for 24-h work coverage, many industries have implemented 12-h or 8-h shift work rosters (Barnes et al., 1998; Bjorvatn et al., 2006; Driscoll et al., 2007; Parkes, 2012). The most common ones include 12-h day and night shift rosters, where 2 panels of employees work 12-h shifts (day, night) with 12-h breaks, and 8-h rosters where 3 panels of employees work 8-h shifts (early, late, night) with 16-h breaks. These schedules frequently combine risk from both circadian misalignment and extended wakefulness for those workers who work the evening and night shifts: two of the largest risk factors predictive of workplace accidents and injuries (Folkard et al., 2005). As an alternative, some industries have implemented shorter, more frequent shifts (such as 6h-on/6h-off, 4h-on/8h-off and 8h-on/8h-off) to address the dual risk of homeostatic and circadian factors (Arendt et al., 2006; Colquhoun et al., 1968; Condon et al., 1984; Darwent et al., 2008; Harma et al., 2008; van Leeuwen et al., 2013). In these rosters, the buildup of homeostatic sleep drive may be reduced by limiting continuous work time with shorter shifts, which also allow more frequent sleep opportunities. Therefore, while circadian factors still operate, they are not coupled with heightened homeostatic sleep pressure and associated impairment (Mollicone et al., 2010). Additionally, these shorter and more frequent shifts typically allow at least some opportunity for sleep across the biological night for all workers. Split sleep work schedules such as the ones described above, have been most frequently implemented in maritime operations, for example 6h-on/6h-off (involving two crews of workers) or 4hon/8h-off (involving three crews) watch-keeping schedules (Eriksen et al., 2006; Hansen and Holmen, 2011; Harma et al., 2008; Howarth et al., 1999; Lutzhoft et al., 2010; Rutenfranz et al., 1988; Sanquist et al., 1997). Research into these split sleep rosters has found that those with a lower ratio of work to sleep, and schedules that begin and end at the same clock time every 24 h are associated with better sleep, performance and daytime functioning (Short et al., 2015). This would therefore indicate that the 6h-on/6h-off schedules, with a 1:1 work: rest ratio and starting at the same fixed times each day may be associated with less impairment than 8hon/8h-off schedules, which have moving shift times each 24h period (Darwent et al., 2008). Further, not all work environments can accommodate the three teams of workers required to maintain a 1:2 work: sleep ratio, such as would be required by 4h-on/8h-off schedules. The 6h-on/6h-off schedules may therefore have particular operational promise. However, previous research in this area is limited to a relatively small number of studies in specific industry populations (Colquhoun et al., 1987; Condon et al., 1988; Darwent et al., 2008; Eriksen et al., 2006; Jay et al., 2006). Most research has involved field studies, which are high in ecological validity, but are vulnerable to potential confounds such as differences in the individual characteristics of workers within that industry, light exposure, and unrestricted use of caffeine, medications and drugs (Howarth et al., 1999; Lamond et al., 2005). One study surveyed 577 shipping workers, 377 of whom worked a 6h-on/6h-off schedule and 182 of whom worked a 12h-on/12h-off schedule (Hansen and Holmen, 2011). While individuals working the 6h-on/6h-off schedule reported more sleep disturbances, the groups did not report different work capability or safety. In a study of bridge officers, those on a 6h-on/6h-off schedule (N ¼ 45) reported less sleep, a higher prevalence of excessive sleepiness, and greater frequency of nodding off while on duty than those on a 4hon/8h-off schedule (N ¼ 68) (Harma et al., 2008). Lutzhoft and colleagues (Lutzhoft et al., 2010) also compared watch keepers working a 6h-on/6h-off schedule (n ¼ 15) with those working a 4hon/8h-off schedule (N ¼ 15). Similar to Harma's group, Lutzhoft and

73

colleagues found greater sleepiness at night for workers on the 6hon/6h-off schedule. However, there was no significant difference in overall sleepiness between the two schedules, nor were there any significant differences in actigraphically-defined total sleep time, sleep efficiency, reaction time or blink duration. One confounding factor discussed by the authors is that actual shift length was routinely longer than what was rostered, particularly for individuals working the 6h-on/6h-off shifts. As such, the ratio of work to rest was likely much higher than 1:1 and the opportunity to obtain sleep was truncated. These maritime studies included predominantly male samples, and relied largely on subjective reports of sleep and performance. In addition, as these studies were conducted in the workplace, it may be difficult to collect baseline measures, where individuals were not at work, and not affected by previous shifts. Further, the effect of the schedules on sleep architecture was not measured. Laboratory simulation studies provide a research environment where these imperatives (as well as control of potential confounds) are more achievable. In their laboratory simulation, Eriksen and colleagues (Eriksen et al., 2006) investigated a 6h-on/6h-off schedule with 12 male merchant marines and navy navigators. The simulation lasted for 66 h, in which the first 30 h was spent working one of the two possible 6h-on/6h-off schedules (0000h-0600h and 1200h-1800h, or 0600h-1200h and 1800h-2400h), then a 3h-on/3h-off “dog watch” occurred to rotate individuals across to the other schedule, followed by 30 h of the second, inverse 6h-on/6h-off schedule. Participants rated their subjective sleepiness every 30 min on the Karolinska Sleepiness scale (KSS) and completed a sleep diary after every break period in which they attempted to sleep. Subjective sleepiness and reported sleep duration were similar for both watch rotations. Across individual watches, subjective sleepiness was higher on the night watch (2400h-0600h) than either the day (1200h-1800h) or the evening (1800h-2400h) watches, and increased from beginning to end of each watch (1200h-1800h, 1800h-2400h & 2400h-0600h), except for the morning watch (0600h-1200h). Sleep duration was longer on the morning (0600h1200h) than the day (1200h-1800h) off-duty periods and longer on the night (0000h-0600h) than both the day (1200h-1800h) and evening (1800h-2400h) off-duty watches. This study provides more fine-grained information on subjective sleepiness across a 6h-on/6h-off split sleep schedule, by comparing the two watch systems and comparing each watch and off-duty period with those occurring at different times, all of which are strengths of this study. Study limitations included a lack of objective measurement of sleep and performance, no baseline comparisons, and caffeine was limited but not excluded (participants were able to consume up to 2 cups of coffee per 24 h). The present study has dual aims. Firstly, it aims to compare individuals’ performance, sleepiness and objective sleep during one of two complementary 6h-on/6h-off rosters with their performance during a daytime baseline, equivalent to a 12h dayshift. The second aims is to compare objective sleep per 5h sleep opportunity during the simulated 6h-on/6h-off shift schedules. This extends upon the previous work in this field by employing a laboratorybased study to examine two 6h-on/6h-off split sleep schedules in a controlled laboratory environment. This study utilises polysomnographic measurement of sleep (the gold-standard), and includes both male and female participants. 2. Materials and methods 2.1. Participants Participants were 16 healthy adults (6 male, aged 26.13years ± 4.46). Eight participants were randomised to each 6h

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condition: 6h-early schedule (4 male, 4 female) or 6h-late schedule (2 male, 6 female). There were no significant differences in age between groups. Participants were in good health physically and psychologically. They were non-smokers and were not taking illicit or prescription drugs (with the exception of the birth control pill), as determined by urine drug screen, blood chemistry analysis, selfreported history and screening questionnaires. Individuals who participated in the study had a body mass index (BMI) between 19 and 30. They had no history of shift work or trans-meridian travel in the 3 months prior to participating. Participants had normal or corrected-to-normal vision and were fluent in written and spoken English. They were good sleepers, averaging 6e10 h sleep per night, with bedtime occurring before 12 midnight and wake time occurring between 0600h and 0900h. Participants were free of sleep and circadian rhythm disorders, as verified by sleep diaries and actigraphy for one week prior to study participation, as well as baseline polysomnography (PSG), history and questionnaires. Participants were neither extreme morning or evening types, as determined by questionnaire (Smith et al., 1989). They regularly consumed no more than two caffeinated beverages per day or two standard alcoholic drinks, and refrained from consuming caffeine and alcohol for 1 week prior to the laboratory study. This study was approved by the University of South Australia Human Research Ethics Committee. Participants gave informed written consent to participate and received an honorarium for any inconvenience associated with participation. 2.2. Study design This study was conducted in the sleep laboratory of the Centre for Sleep Research at the University of South Australia. The laboratory is a temperature and light controlled, sound attenuated environment. Lights were kept below 50 lux during wake periods (to avoid the alerting and circadian phase shifting effect of bright light) and below 1 lux during sleep opportunities. Temperature was controlled to 22  C (±1  C). Participants were allocated a bedroom for their exclusive use for sleep and neurobehavioural testing. In between sleep and performance testing, participants could spend time in a communal living space inside the laboratory, interacting with laboratory staff and other participants, watching DVDs, reading, and completing jigsaws and board games. Continuous behavioural monitoring ensured that participants remained awake during all designated wake periods. Meals were served in the communal living area at designated times. Four participants were studied simultaneously in the laboratory. Participants completed the 9-day live-in laboratory study in one of two 6h-on/6h-off conditions (see Fig. 1). The 6h early condition included 4 days of a simulated shift work schedule of work between 0830h to 1430h and 2030 to 0230h, starting at 0830h on Day 3 and ending at 0230h on Day 7. The 6h late condition included 4 days of simulated shift work between 1430h to 2030h and 0230he0830h. This schedule began at 1430h on Day 3 and finished at 0830h on Day 7. In both conditions, participants entered the sleep laboratory at 1300h on Day 1 for practice testing, which was followed by a 10h sleep opportunity between 2200h and 0800h. On Day 2, baseline neurobehavioral testing was carried out every 2 h during wake, beginning at 0930h to avoid any possible effects of sleep inertia (to be reported in another paper), followed by a second baseline 10h sleep opportunity between 2200h and 0800h. Between Days 3 and 7, participants were on their simulated shift work schedule. Each schedule allowed for 10 h' time in bed per 24 h. Two recovery nights (data not presented here) of 10 h’ time in bed was given on Days 7 and 8, during which time, two hourly neurobehavioural testing continued in wake periods. Participants exited the laboratory at 2100h on Day 9.

2.3. Measures Each neurobehavioural test battery consisted of a 3-min psychomotor vigilance task (Brief PVT), a 3-min digit symbol substitution task (DSST) (Wechsler, 1981), Positive and Negative Affect Scale (Watson et al., 1988), Karolinska Sleepiness Scale (KSS) (Akerstedt and Gillberg, 1990), a 10-min PVT (Dorrian et al., 2005) and the Samn-Perelli fatigue scale (Samn and Perelli, 1982). For the purpose of the present study, the 10-min PVT (lapses and fastest 10% of response times), and the KSS will be examined. A 10-min PVT was used to measure sustained attention and response speed. The PVT is a reaction time task that requires participants to attend to a small square on a computer screen and to respond as quickly as possible by pressing a button with their dominant hand as soon as the stimulus appears. Inter-stimulus intervals varied from 2 to 10 s. PVT lapses were used to measure sustained attention. Lapses were defined as the number of reaction times per 10 min test that were greater than 500 ms. PVT total lapse time (TLT) was the average length of PVT lapses. The 10% of fastest reaction times was used to measure response speed as, unlike mean response speed, it is not skewed by the occurrence of lapses. The KSS (Akerstedt and Gillberg, 1990) is a 9-point scale with 5 statement anchors on each odd number. Participants are asked to select the statement that most accurately reflects their subjective sleepiness at the time. Scores could range from 1 to 9, with higher scores indicating greater subjective sleepiness. All sleep periods were recorded using polysomnography (PSG). The PSG montage included frontal (F3, F4), central (C3, C4), and occipital (O1) placements referenced against contralateral A1/A2; bilateral electrooculogram and electromyogram; and electrocardiogram. Sleep periods were scored by a senior medical scientist who was independent of the study and blinded to the study aims. The standard criteria proposed by the American Academy of Sleep Medicine were used to score sleep (Silber et al., 2007). From these data, total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL) and sleep architecture were estimated.

2.4. Statistical analyses Mixed effects Analysis of Variance (ANOVA) models were used to test differences in performance, sleepiness and sleep across days in the schedule and times of day, appropriately accounting for both within and between participant variance (Van Dongen et al., 2004). All models specified a random effect of participant ID. Models for performance and sleepiness specified number of PVT lapses, PVT total lapse time and KSS as dependent variables, with fully saturated models (all main and interaction effects) for day (baseline/ experimental days 1e4), condition (6h early/6h late), and trial (1e6). Models for sleep specified TST, WASO, SOL, Stage 1 sleep (S1), Stage 2 sleep (S2), Stage 3 sleep (S3) and rapid eye movement sleep (REM) as dependent variables. Two sets of models were tested for sleep parameters. First, since the protocol was designed to allow equivalent sleep opportunities (10h) per 24 h at baseline and throughout the experimental period, one set of models tested total sleep per 24h. These specified main and interaction effects for day (baseline/experimental days 1e4) and condition (6h early/6h late). Second, in order to investigate differences in sleep in equivalent opportunities (5h TIB) across different times of day, a final set of fully saturated models, which excluded the baseline day, specified effects of day (experimental days 1e4), condition (6h Early/6h Late) and sleep period (6h Early 1500h/6h Early 0300h/6h Late 2100h/6h Late 0900h). Pairwise post-hoc analyses with least significant differences (LSD) were conducted to further investigate significant main and interaction effects.

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Fig. 1. Protocol schematics of the 6h-early (top) and 6-h late (bottom) schedules. Time (24h) is on the horizontal axis, and the vertical axis displays the nine days of the study. Sleep opportunities (time in bed (TIB)) are in black and wake times are in yellow. Pink crosses (X) indicate the timing of practice test batteries, red crosses indicate neurobehavioural test bouts.

3. Results 3.1. Performance and sleepiness There were no significant main effects of day on PVT lapses, total lapse time or fastest 10% of reaction times, indicating that, overall, individuals’ were able to sustain attention and respond as quickly on shift days as they did at baseline. There was, however, a significant condition*trial interaction for number of PVT lapses, total lapse time, and response speed (as shown in Table 1), indicating that there were differences in performance that varied between the two shift conditions as well as according to trial number. Post hoc comparisons (LSD) revealedthat participants in the 6h-late condition performed was significantly worse on trial 6 (0730h) compared to all other trials (p < 0.05, see Fig. 2) in terms of performance outcomes. In the 6h-early condition, only response speed significantly differed across trials, with slower response speeds occurring at trial 1 (0930h) than in trials 3 (1330h) or 4 (2130h), thus indicative of time-of-day effects on performance. Lastly, there was a significant condition*day interaction for response speed. While response speed did not significantly differ across days for individuals in the 6h-early condition, those in the 6h-late condition

responded significantly faster at baseline than on the first experimental day, potentially indicating an initial adjustment effect to the first day of split shifts. Individuals in the 6h-early conition were also significantly faster on the third experimental day than the remaining experimental days. There was a significant main effect of day, and day*condition interaction for sleepiness (p < 0.05, as detailed in Table 1). Post hoc comparisons (LSD) revealed that participants in the 6h-late condition were significantly sleepier on experimental days compared to baseline (p < 0.05, see Fig. 2). There was also a significant condition*trial interaction (p < 0.01, as detailed in Table 1). Overall, these results were consistent with a circadian variation of sleepiness. Specifically, participants in the 6h-early condition were significantly sleepier during trial 6 (0130h) when compared to trials 1e5 (occurring at 0930h, 1130h, 1330h, 2130 and 2330h). For participants in the 6h-late condition, sleepiness was significantly higher during the evening and nighttime trials (trials 2e6, occurring at 1730h, 1930h, 0330h, 0530h and 0730h) than on the afternoon trial (trial1, occurring at 1530h). In addition, sleepiness was also higher during the nighttime trials (trials 4e6, occurring at 0330h, 0530h and 0730h) than in the late afternoon (trial 2, occurring at 1730h, p < 0.05; as shown in Fig. 2).

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M.A. Short et al. / Applied Ergonomics 54 (2016) 72e82

Table 1 Main effects and interactions of day, condition and trial on psychomotor vigilance task (PVT) lapses, PVT total lapse time and subjective sleepiness. Final column displays significant post-hoc comparisons (p < 0.05).

PVT lapses day condition day*condition day*trial condition*trial condition*day*trial PVT total lapse time day condition day*condition day*trial condition*trial condition*day*trial Fastest 10% RT day condition day*condition day*trial condition*trial condition*day*trial Sleepiness day condition day*condition day*trial condition*trial condition*day*trial

F-value

df

p

Post-hoc^

0.15 0.01 0.45 1.21 5.87 0.93

4, 406 1, 14 4, 406 20, 406 5, 406 20, 406

0.96 0.91 0.77 0.24 <0.001* 0.55

0.08 0.06 0.64 1.31 6.56 0.98

4, 406 1, 14 4, 406 20, 406 5, 406 20, 406

0.99 0.81 0.64 0.17 <0.001* 0.48

1.32 0.05 3.19 0.87 3.82 0.72

4, 406 1, 14 4, 406 20, 406 5, 406 20, 406

0.26 0.83 0.01* 0.63 0.002* 0.80

6.27 1.23 2.81 1.39 4.35 1.05

4, 406 1, 14 4, 406 20, 406 5, 406 20, 406

<0.001* 0.29 0.03* 0.12 0.001* 0.40

6L:T6>T1-5

6L:T6>T1-5

6L: BL < E1; E3 T3-4; 6L:T6 > T1-5, T1-2 < T4-5

6L: BL < E1-4 6E: T6 > T1-5; 6L: T1
*p < 0.05; ^6E ¼ 6h Early, 6L ¼ 6h Late, BL¼Baseline, E1-4 ¼ Experimental days 1e4, T1-6 ¼ Trials 1e6.

Changes in Sleep per 24h Period Compared to Baseline (10h sleep opportunities)Table 2 and Fig. 3 provide the inferential and descriptive results of the analyses regarding sleep per 24h period. There were significant main effects of day and condition, and a significant day*condition interaction for TST (p < 0.001, Table 2). Overall, these results indicated that sleep duration was reduced during experimental days when compared to baseline sleep duration. Specifically, in the 6h-early condition, sleep duration was significantly longer at baseline than on experimental days 1, 2 and 4 (also E1
significantly greaterat baseline compared to the experimental days (also E1
M.A. Short et al. / Applied Ergonomics 54 (2016) 72e82

6 Early

6 Late

77

grand mean baseline

8 7 6

PVT Lapses

5 4 3 2 1

0330h

0730h

0330h

0730h

1930h

1530h

1130h

0730h

0330h

2330h

1930h

1530h

1130h

0730h

grand gran mean baseline E3

2330h

6 Late E2

0330h

2330h

1930h

1530h

1130h

0730h

0330h

2330h

6 Early

E1

2330h

BL

1930h

1530h

1130h

1730h

1330h

0930h

0

E4

8

Karolisnska Sleepiness Scale (KSS)

7 6 5 4 3 2 1

BL

E1

E2

1930h

1530h

1130h

0730h

0330h

1930h

E3

2330h

1530h

1130h

0730h

0330h

2330h

1930h

1130h

1530h

0730h

0330h

2330h

1930h

1530h

1130h

1730h

1330h

0930h

0

E4

Fig. 2. Psychomotor vigilance task (PVT) Lapses (Upper Panel) and Karolinska Sleepiness Scale (KSS) results (Lower Panel) presented by time of day. Open diamonds and dashed lines indicate the 6 Early and filled squares with solid lines the 6 Late Conditions. The black vertical line delineates the beginning of the experimental days (E1-E4) along the x-axis, compared to baseline (BL). Grey shading highlights time points during points during the circadian cycle where impairment may be considered more likely (0130e0730h).

Stage 2 sleep occurring in the 6h-early condition than in the 6h-late condition (Fig. 3). There was a significant main effect of day and significant condition*sleep period and day*condition*sleep period interactions for Stage 3 (p < 0.05, Table 3). For participants in the 6h-late condition who were initiating sleep at 2100h, significantly more Stage 3 sleep occurred during experimental day 1 than the other days (Fig. 4), however, it did not differ across other sleep

opportunities. There was also a significant main effect of sleep period and a condition*sleep period interaction for REM (p < 0.01, Individuals in the 6h-early condition had significantly less REM sleep during the sleep opportunity beginning at 1500h than during that beginning at 0300h, while those in the 6h-late condition had significantly less REM sleep in the sleep opportunity at 2100h compared to 0900h (Fig. 4).

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Table 2 Main effects and interaction of day (Baseline, Experimental day 1, Experimental day 2, Experimental day 3, Experimental day 4) and condition (6h-early and 6h-late) on sleep variables total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), sleep stages 1, 2 and 3 (S1, S2, S3) and rapid eye movement sleep (REM). Final column displays significant post-hoc comparisons (p < 0.05).

TST day condition day*condition WASO day condition day*condition SOL day condition day*condition S1 day condition day*condition S2 day condition day*condition S3 day condition day*condition REM day condition day*condition

F-value

df

p

Post-hoc^

10.85 5.70 6.45

4, 56 1, 14 4, 56

<0.001* 0.03* <0.001*

6E: BL > E1,E2,E4; E1 E1-4

4.81 0.99 0.45

4, 56 1, 14 4, 56

0.002* 0.34 0.77

BL < E2,E3,E4; E1
5.09 4.08 1.87

4, 56 1, 14 4, 56

0.001* 0.06 0.13

BL < E1-4; E1
1.96 0.01 2.11

4, 56 1, 14 4, 56

0.11 0.92 0.09

8.48 9.93 5.59

4, 56 1, 14 4, 56

<0.001* 0.007* 0.001*

1.68 0.40 4.10

4, 56 1, 14 4, 56

0.17 0.54 0.006*

9.37 0.52 3.46

4, 56 1, 14 4, 56

<0.001* 0.49 0.02*

6E: BL > E1,E2,E4; E1
6L: E1>BL,E2-4

6E: BL > E1-4; E1
*p < 0.05; ^6E ¼ 6h Early, 6L ¼ 6h Late, BL¼Baseline, E1-4 ¼ Experimental days 1e4, T1-6 ¼ Trials 1e6.

4. Discussion The present study examined the effects of split sleep schedules on neurobehavioural performance, sleepiness and sleep in a controlled laboratory environment using objective measures of sleep and performance. This extends previous work by comparing performance and sleep during split sleep schedules to baseline, comparing results between two complementary split sleep conditions, and also comparing each sleep period within each condition. Overall, these results suggest that there was little cumulative cost across days of split sleep. Sleepiness did not increase, nor did performance impairment, across days on these schedules. Participants got sleepier across trials within a shift, but their sleepiness did not accumulate across days on shift. This suggests that individuals were able to maintain performance across days of split sleep. While sleepiness was greater on shift days relative to baseline in the 6hlate condition, this plateaued across shift days and average sleepiness remained relatively low, with mean scores on shift days of 4, equating to “rather alert”. While the shorter period of cumulative wake may confer some benefit in terms of limiting the accumulation of homeostatic sleep pressure and performance deficits, this did not ameliorate the impact of the circadian system. Tests near the circadian nadir showed greater sleepiness and increased performance deficits for assays of sustained attention, such as lapses, total lapse time and fastest 10% of reaction times, all of which peaked during the 0730h test bout. This is consistent with the findings of Mollicone and colleagues (Mollicone et al., 2010), who found that cumulative impairment during sleep restriction was greatest around 0800h and least in the early afternoon and early evening. However, circadian effects may still be blunted by the shorter period of prior wake. This is consistent with the recent findings from split shift schedules (Jackson et al., 2014; Kosmadopoulos et al., 2014).

When examining daily sleep parameters between baseline and shift days, there was a cost of splitting sleep in terms of sleep quantity, the time needed to initiate sleep and sleep consolidation, while slow wave sleep and REM were relatively conserved. Despite the same total sleep opportunity, splitting the sleep opportunity across two periods was associated with an average loss of just under 1 h of sleep per day when compared to baseline. This loss predominantly arose from the additional time needed to initiate sleep twice per 24 h, as opposed to once (SOL at baseline M ¼ 14 min vs SOL on shift days M ¼ 30 min), and the increased wake after sleep onset occurring during split sleep (M ¼ 31 min v M ¼ 76 min), which is likely due to the effect of maintaining sleep at times outside of the biological night. When examining sleep architecture between baseline and shift days, the effect of splitting sleep varied according to split sleep condition. The 6h-early shift was associated with a greater reduction in sleep duration (relative to baseline) than the 6h-late shift. As a result, the 6h-early shift was associated with reductions in quantity of both S2 and REM sleep, while SWS and S1 were unchanged. This is consistent with previous findings showing conservation of SWS during daytime sleep schedules (Van Dongen et al., 2011). When examining the pattern of sleep in the different sleep opportunities within the schedule it can be seen that, overall, sleep occurring across the biological night was initiated faster and was more consolidated than sleep opportunities occurring during the day. Nonetheless, participants in the 6h-early condition were able to initiate sleep relatively quickly during the sleep period occurring between 1500h and 2000h, possibly because the sleep period started around the time of the afternoon dip in alertness (Lack and Lushington, 1996). However, participants had greater difficulty maintaining sleep during this sleep period, likely because this period transects the wake maintenance zone (approximately 1e3 h before habitual bedtime), when circadian alertness peaks (Strogatz

M.A. Short et al. / Applied Ergonomics 54 (2016) 72e82

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Fig. 3. Total Sleep Time (TST: Upper Panels), Wake After Sleep Onset (WASO: Middle Panels) and Sleep Onset Latency (SOL: Lower Panels) presented as totals per day in the study by condition (6h early (6E) and 6h late (6L)) on the left panel, and further broken down by timing of sleep opportunity within each condition on the right panel.

et al., 1987). Conversely, participants in the 6h-late condition took more time to initiate sleep during the sleep period spanning 2100he0200h but they were able to maintain sleep once it had begun. This is consistent with current literature showing circadian variations in sleep parameters (Åkerstedt, 2003; Czeisler et al., 1982; Lack and Lushington, 1996). Irrespective of the contributors to sleep truncation, when it occurred, S2 and REM were also truncated, while quantity of SWS was relatively spared. Splitting sleep may offer promise in operational contexts requiring 24-h work coverage with only 2 crews of workers. This promise occurs by minimising cumulative wake and ensuring that all individuals have some sleep every 24 h that occurs during the biological night. It is important to note, however, the limitations of the present study that provide important caveats to these conclusions. First, this study occurred in a highly controlled laboratory

environment, which offers the ideal sleeping environment with no distractors. Factors known to deleteriously affect sleep in shift workers, such as exposure to light and noise, family commitments and domestic responsibilities are absent in the laboratory environment. As such, it is uncertain the degree to which these results may be generalised to other non-laboratory settings. Secondly, participants were highly screened, healthy, young adults. Older adults, individuals with medical conditions or those taking medications might adjust to these schedules differently to the current participants. Thirdly, the daily sleep opportunity provided in this study is in excess of the normative time in bed of most adults (Bin et al., 2012). Future research would profit from evaluating the effect of splitting sleep under conditions of shorter sleep opportunities, which more closely approximate the sleep opportunities individuals’ would get under typical operational conditions. Lastly, a

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Table 3 Main effects and interactions of day (Shift day 1, Shift day 2, Shift day 3, Shift day 4), condition (6h-early and 6h-late) and sleep period (first sleep period, second sleep period) on sleep variables total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), sleep stages 1, 2 and 3 (S1, S2, S3) and rapid eye movement sleep (REM). Final column displays significant post-hoc comparisons (p < 0.05).

TST day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period WASO day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period SOL day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period S1 day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period S2 day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period S3 day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period REM day condition sleep period day*condition day*sleep period condition*sleep period day*condition*sleep period

F-value

df

p

Post-hoc^

0.75 1.41 33.58 1.64 0.42 46.29 1.98

3, 1, 1, 3, 3, 1, 3,

92.90 14.71 92.62 92.90 93.14 92.63 93.14

0.52 0.25 <0.001* 0.19 0.74 <0.001* 0.12

0.34 4.03 20.93 1.35 0.40 46.14 1.07

3, 1, 1, 3, 3, 1, 3,

93.20 14.55 92.80 93.20 93.51 92.83 93.51

0.80 0.06 <0.001* 0.26 0.76 <0.001* 0.37

0.66 4.11 13.70 0.18 0.67 34.74 1.38

3, 1, 1, 3, 3, 1, 3,

93.15 14.77 92.89 93.15 93.38 92.89 93.38

0.58 0.06 <0.001* 0.91 0.57 <0.001* 0.26

1.22 0.02 18.22 1.18 0.11 0.23 1.07

3, 1, 1, 3, 3, 1, 3,

92.38 14.22 92.26 92.38 92.49 92.26 92.49

0.31 0.88 <0.001* 0.32 0.95 0.63 0.37

0.85 8.10 1.69 1.58 0.12 0.96 1.14

3, 1, 1, 3, 3, 1, 3,

93.03 14.36 92.66 93.03 93.35 92.66 93.35

0.47 0.01* 0.20 0.20 0.95 0.33 0.34

3.49 0.04 2.57 1.30 1.47 32.65 2.72

3, 1, 1, 3, 3, 1, 3,

92.16 13.92 91.99 92.16 92.32 92.00 92.32

0.02* 0.85 0.11 0.28 0.23 <0.001* 0.049*

0.42 0.13 70.20 1.76 0.92 18.19 1.92

3, 1, 1, 3, 3, 1, 3,

92.44 14.08 92.20 92.44 92.65 92.21 92.65

0.74 0.73 <0.001* 0.16 0.44 <0.001* 0.13

6E: 1500h < 0300h

6E: 1500h > 0300h

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6E < 6L

6L 2100h: E1>E2-4

6E: 1500h < 0300h; 6L: 2100h < 0900h

*p < 0.05; ^6E ¼ 6h Early, 6L ¼ 6h Late, BL¼Baseline, E1-4 ¼ Experimental days 1e4, T1-6 ¼ Trials 1e6.

direct comparison to equivalent periods of traditional shifts, such as 12h-on/12h-off, would allow the discernment of any effect due to split sleep versus effects of repeated testing and other non-shift related factors. Logistic constraints of these schedules must be considered within the specific context of each work environment. For example, these watchstanding or relay type schedules are typically implemented where sleeping accommodation is very nearby (e.g. on the boat or train). Under these conditions, laboratory results may be more applicable, since they typically share the isolation from competing social factors, and therefore time off is frequently used primarily for sleep and rest. In contrast, operational

environments where long commutes are required could dramatically reduce possible sleep time during off-duty periods and substantially alter the efficacy of such shifts. 5. Concluding remarks In conclusion, while results suggest that splitting sleep lead to reduced sleep time when compared to baseline, this did not cause significant or cumulative costs in terms of neurobehavioural performance, however, sleepiness was higher across shift days. Overall, participants were able to maintain a level of performance across

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Fig. 4. Stage 1,2,3,4 and rapid eye movement (REM) sleep (Upper to Lower Panels) presented as totals per day in the study by condition (6h early (6E) or 6h late (6L) in the left panel, and further broken down by timing of sleep opportunity within each condition in the right panel.

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