Search

For the control group, there was a clear circadian rhythm in sleep propensity, with a peak of 98.5% at 5° (~05:20 h), a trough of 64.9% at 245° (~21:20 h), and an average of 82.3%. In contrast, sleep propensity for the sleep restriction group was relatively high at all circadian phases, with an average of 96.7%. For this group, the highest sleep propensity (99.0%) occurred at 60° (~09:00 h), and the lowest sleep propensity (91.3%) occurred at 265° (~22:40 h). As has been shown previously, these current data indicate that with a normal sleep-to-wake ratio, the effect of the circadian process on sleep propensity is pronounced, such that a forbidden zone for sleep exists at a phase equivalent to evening time for a normally entrained individual. However, these current data also indicate that when the ratio of sleep to wake is substantially lower than normal, this circadian effect is masked. In particular, sleep propensity is very high at all circadian phases, including those that coincide with the forbidden zone for sleep. This finding suggests that if the homeostatic pressure for sleep is sufficiently high, then the circadian drive for wakefulness can be overridden. In future studies, it will be important to determine whether or not this masking effect occurs with less severe sleep restriction, e.g., with a sleep-to-wake ratio of 1:3. Previous forced desynchrony studies have highlighted the close relationship between the circadian rhythms of core body temperature (CBT) and sleep propensity. In particular, these studies have shown that a "forbidden zone" for sleep exists on the rising limb of the CBT rhythm. In these previous studies, the length of the experimental day was either ultrashort (90 min), short (20 h), or long (28 h), and the ratio of sleep to wake was normal (i.e., 1:2). The aim of the current study was to examine the relative effects of the circadian and homeostatic processes on sleep propensity using a 28-h forced desynchrony protocol in which the ratio of sleep to wake was substantially lower than normal (i.e., 1:5). Twenty-seven healthy males lived in a time-isolation sleep laboratory for 11 consecutive days. Participants completed either a control (n = 13) or sleep restriction (n = 14) condition. In both conditions, the protocol consisted of 2 × 24-h baseline days followed by 8 × 28-h forced desynchrony days. On forced desynchrony days, the control group had 9.3 h in bed and 18.7 h of wake, and the sleep restriction group had 4.7 h in bed and 23.3 h of wake. For all participants, each 30-s epoch of time in bed was scored as sleep or wake based on standard polysomnography recordings, and was also assigned a circadian phase (360° = 24 h) based on a cosine equation fitted to continuously recorded CBT data. For each circadian phase (i.e., 72 × 5° bins), sleep propensity was calculated as the percentage of epochs spent in bed scored as sleep. Refereed/Peer-reviewed

Although a nonlinear time-of-day and prior wake interaction on performance has been well documented, two recent studies have aimed to incorporate the influences of sleep restriction into this paradigm. Through the use of sleeprestricted forced desynchrony protocols, both studies reported a time-of-day × sleep restriction interaction, as well as a time-of-day × prior wake × sleep dose three-way interaction. The current study aimed to investigate these interactions on simulated driving performance, a more complex task with ecological validity for the problem of fatigued driving. The driving performance of 41 male participants (mean ± SD: 22.8 ±2.2 yrs) was assessed on a 10- min simulated driving task with the standard deviation of lateral position (SDLAT) measured. Using a between-group design, participants were subjected to either a control condition of 9.33 h of sleep/18.66 h of wake, a moderate sleep-restriction (SR) condition of 7 h of sleep/21 h of wake, or a severe SR condition of 4.66 h of sleep/23.33 h of wake. In each condition, participants were tested at 2.5-h intervals after waking across 7 × 28-h d of forced desynchrony. Driving sessions occurred at nine doses of prior wake, within six divisions of the circadian cycle based on core body temperature (CBT). Mixed-models analyses of variance (ANOVAs) revealed significant main effects of time-of-day, prior wake, sleep debt, and sleep dose on SDLAT. Additionally, significant two-way interactions of timeof- day × prior wake and time-of-day × sleep debt, as well as significant three-way interactions of time-of-day × prior wake × sleep debt and time-of-day × sleep debt × sleep dose were observed. Although limitations such as the presence of practice effects and large standard errors are noted, the study concludes with three findings. The main effects demonstrate that extending wake, reducing sleep, and driving at poor times of day all significantly impair driving performance at an individual level. In addition to this, combining either extended wake or a sleep debt with the early morning hours greatly decreases driving performance. Finally, operating under the influence of a reduced sleep dose can greatly decrease performance at all times of the day. Refereed/Peer-reviewed

International commercial airline pilots may experience heightened fatigue due to irregular sleep schedules, long duty days, night flying, and multiple time zone changes. Importantly, current commercial airline flight and duty time regulations are based on work/rest factors and not sleep/wake factors. Consequently, the primary aim of the current study was to investigate pilots’ amount of sleep, subjective fatigue, and sustained attention before and after international flights. A secondary aim was to determine whether prior sleep and/or duty history predicted pilots’ subjective fatigue and sustained attention during the international flights. Nineteen pilots (ten captains, nine first officers; mean age: 47.42 + 7.52 years) participated. Pilots wore wrist activity monitors and completed sleep and duty diaries during a return pattern from Australia to Europe via Asia. The pattern included four flights: Australia-Asia, Asia-Europe, Europe-Asia, and Asia-Australia. Before and after each flight, pilots completed a 5 min PalmPilot-based psychomotor vigilance task (PVT) and self-rated their level of fatigue using the Samn-Perelli Fatigue Checklist. Separate repeatedmeasures ANOVAs were used to determine the impact of stage of flight and flight sector on the pilots’ sleep in the prior 24 h, self-rated fatigue, and PVT mean response speed. Linear mixed model regression analyses were conducted to examine the impact of sleep in the prior 24 h, prior wake, duty length, and flight sector on pilots’ self-rated fatigue and sustained attention before and after the international flights. A significant main effect of stage of flight was found for sleep in the prior 24 h, self-rated fatigue, and mean response speed (all p , 0.05). In addition, a significant main effect of flight sector on self-rated fatigue was found (p , .01). The interaction between flight sector and stage of flight was significant for sleep in the prior 24 h and self-rated fatigue (both p , .05). Linear mixed model analyses indicated that sleep in the prior 24 h was a significant predictor of self-rated fatigue and mean response speed after the international flight sectors. Flight sector was also a significant predictor of Research support: a commercial airline (cannot be identified), the Civil Aviation Safety Authority (CASA), the Australian and International Pilots’ Association (AIPA), and the Australian Research Council (ARC). This paper was presented at the 17th WTS Symposium, Hoofddorp, The Netherlands, September, 2005.

The aim of the study was to examine the adaptation of participants to a common night work schedule using urinary 6-sulphatoxymelatonin (aMT6s) concentration as the circadian phase marker. Fifteen adults (7 male, 8 female, age = 21.9 yr) spent nine consecutive nights in the laboratory, including: (i) adaptation sleep, (ii) baseline sleep, and (iii) seven simulated night shifts (23:00-07:00 h) followed by daytime sleep. During the baseline and daytime sleeps, participants collected urine samples which were subsequently assayed for aMT6s. The concentration of aMT6s in urine for the first three day sleeps was significantly lower than for the baseline sleep, but there was no difference in aMT6s concentrations between any of the last three day sleeps and the baseline sleep. The data indicate that people may adapt to a pattern of work that includes seven consecutive night shifts if they adhere to a fixed sleep schedule, if their exposure to morning sunlight is minimised, and if they are provided with an ideal sleep environment.

In the past, scientific studies have investigated the effects of shift timing and duration on sleep and alertness in the rail industry. To our knowledge no research has been conducted to determine the effects of extended break lengths (>48 h) on these factors. Hence, this study analyses the work and rest schedules of 304 Australian rail employees (mean age 41.3 yr, standard deviation 7.4 yr) to determine the effect of prior break lengths (12-169 h) on sleep and subjective alertness at work after periods of leave. Extended break periods (>48 h) were found to increase the length of the sleep prior to returning to work and reduce the total wake time to the end of the first shift, but did not influence levels of subjective alertness immediately prior to the commencement of the first shift. Research into the influence of longer break periods (>169 h) is needed in order to make definitive conclusions regarding sensible return to work policies after extended leave within the Australian rail industry.

The endogenous melatonin onset in dim light (DLMO) is a marker of circadian phase that can be used to appropriately time the administration of bright light or exogenous melatonin in order to elicit a desired phase shift. Determining an individual's circadian phase can be costly and time-consuming. We examined the relationship between the DLMO and sleep times in 16 young healthy individuals who slept at their habitual times for a week. The DLMO occurred about 2 hours before bedtime and 14 hours after wake. Wake time and midpoint of sleep were significantly associated with the DLMO (r = 0.77, r = 0.68 respectively), but bedtime was not (r = 0.36). The possibility of predicting young healthy normally entrained people's DLMOs from their sleep times is discussed.

Long-haul airline pilots often experience elevated levels of fatigue due to extended work hours and circadian misalignment of sleep and wake periods. During long-haul trips, pilots are typically given 1-3 d off between flights (i.e., layover) to recover from, and prepare for, duty. Anecdotally, some pilots prefer long layovers because it maximizes the time available for recovery and preparation, but others prefer short layovers because it minimizes both the length of the trip, and the degree to which the body clock changes from "home time" to the layover time zone. The aim of this study was to examine the impact of layover length on the sleep, subjective fatigue levels, and capacity to sustain attention of long-haul pilots. Participants were 19 male pilots (10 Captains, 9 First Officers) working for an international airline. Data were collected during an 11- or 12-d international trip. The trips involved (i) 4 d at home prior to the trip; (ii) an eastward flight of 13.5 h across seven time zones; (iii) a layover of either 39 h (i.e., short, n = 9) or 62 h (i.e., long, n = 10); (iv) a return westward flight of 14.3 h across seven time zones; and (v) 4 d off at home after the trip. Sleep was recorded using a self-report sleep diary and wrist activity monitor; subjective fatigue level was measured using the Samn-Perelli Fatigue Checklist; and sustained attention was assessed using the psychomotor vigilance task for a personal digital assistant (PalmPVT). Mixed-model regression analyses were used to determine the effects of layover length (short, long) on the amount of sleep that pilots obtained during the trip, and on the pilots' subjective fatigue levels and capacity to sustain attention. There was no main effect of layover length on ground-based sleep or in-flight sleep, but pilots who had a short layover at the midpoint of their trip had higher subjective fatigue levels and poorer sustained attention than pilots who had a long layover. The results of this study indicate that a short layover during a long-haul trip does not substantially disrupt pilots' sleep, but it may result in elevated levels of fatigue during and after the trip. If short layovers are used, pilots should have a minimum of 4 d off to recover prior to their next long-haul trip. Refereed/Peer-reviewed

The aim of this study was to examine a regular rotating 12-h shift system (2D2N4Off) at an Australian Smelter. Sleep behavior, subjective fatigue and neurobehavioral performance were investigated over a 14-day period for 20 employees. Activity monitors, sleep/wake diaries, and 5-min psychomotor vigilance tasks were used. Sleep data showed differences between day and night shifts. While sleep prior to night1 was increased relative to day shifts, a reduced sleep length carried into the period leading to night2. Total wakefulness at the end of shift, and subjective fatigue were increased for night shifts, particularly night1. Decrements in performance data supported these findings. Both prior wakefulness and prior sleep are important in a 12-h shift system. Employees may "sleep in" after day shifts, rather than taking extra sleep prior to night work. Thus, sleep between day and night shifts is based on recovery rather than preparation. Refereed/Peer-reviewed

For Australian pilots, short layovers (

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 (F1,14 = 26.9, p < .001) and hours of wakefulness (F13,182 = 46.1, p < .001) but not by their interaction (F13,182 = 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 (F1,14 = 65.9, p < .001) and hours of wakefulness (F13,182 = 29.7, p < .001) as well as by their interaction (F13,182 = 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.

Aims: To investigate factors that may contribute to performance adaptation during permanent night work. Methods: Fifteen healthy subjects participated in an adaptation and baseline night sleep, directly followed by seven simulated eight-hour night shifts (2300 to 0700 hours). At the end of each shift they were taken outside and exposed to natural light for 20 minutes. They then slept from approximately 0800 hours until they naturally awoke. Results: There was a significant increase in mean performance on a visual psychomotor vigilance task across the week. Daytime sleep quality and quantity were not negatively affected. Total sleep time (TST) for each of the daytime sleeps was reduced, resulting in an average cumulative sleep debt of 3.53 hours prior to the final night shift. TST for each of the daytime sleep periods did not significantly differ from the baseline night, nor did TST significantly vary across the week. There was a significant decrease in wake time after sleep onset and sleep onset latency across the week; sleep efficiency showed a trend towards greater efficiency across the consecutive daytime sleeps. Hours of wakefulness prior to each simulated night shift significantly varied across the week. The melatonin profile significantly shifted across the week. Conclusions: Results suggest that under optimal conditions, the sleep debt that accumulates during consecutive night shifts is relatively small and does not exacerbate decrements in night-time performance resulting from other factors. When sleep loss is minimised, adaptation of performance during consecutive night shifts can occur in conjunction with circadian adaptation.