Gregory D. Roach

The validity of psychomotor vigilance tasks of less than 10-minute duration.

The 10-min psychomotor vigilance task (PVT) has often been used to assess the impact of sleep loss on performance. Due to time constraints, however, regular testing may not be practical in field studies. The aim of the present study was to examine the suitability of tests shorter than 10 min. in duration. Changes in performance across a night of sustained wakefulness were compared during a standard 10-min PVT, the first 5 min of the PVT, and the first 2 min of the PVT. Four performance metrics were assessed: (1) mean reaction time (RT), (2) fastest 10% of RT, (3) lapse percentage, and (4) slowest 10% of RT. Performance during the 10-min PVT significantly deteriorated with increasing wakefulness for all metrics. Performance during the first 5 min and the first 2 min of the PVT deteriorated in a manner similar to that observed for the whole 10-min task, with all metrics except lapse percentage displaying significant impairment across the night. However, the shorter the task sampling time, the less sensitive the test is to sleepiness. Nevertheless, the 5-min PVT may provide a viable alternative to the 10-min PVT for some performance metrics.

CAN A SHORTER PSYCHOMOTOR VIGILANCE TASK BE USED AS 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 (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.

Sleep or swim? Early-morning training severely restricts the amount of sleep obtained by elite swimmers

Abstract Good sleep is essential for optimal performance, yet few studies have examined the sleep/wake behaviour of elite athletes. The aim of this study was to assess the impact of early-morning training on the amount of sleep obtained by world-class swimmers. A squad of seven swimmers from the Australian Institute of Sport participated in this study during 14 days of high-intensity training in preparation for the 2008 Olympic Games. During these 14 days, participants had 12 training days, each starting with a session at 06:00 h, and 2 rest days. For each day, the amount of sleep obtained by participants was determined using self-report sleep diaries and wrist-worn activity monitors. On nights that preceded training days, participants went to bed at 22:05 h (s=00:52), arose at 05:48 h (s=00:24) and obtained 5.4 h (s=1.3) of sleep. On nights that preceded rest days, participants went to bed at 00:32 h (s=01:29), arose at 09:47 h (s=01:47) and obtained 7.1 h (s=1.2) of sleep. Mixed model analyses revealed that on nights prior to training days, bedtimes and get-up times were significantly earlier (p<0.001), time spent in bed was significantly shorter (p<0.001) and the amount of sleep obtained was significantly less (p<0.001), than on nights prior to rest days. These results indicate that early-morning training sessions severely restrict the amount of sleep obtained by elite athletes. Given that chronic sleep restriction of <6 h per night can impair psychological and physiological functioning, it is possible that early-morning schedules actually limit the effectiveness of training.

The impact of a week of simulated night work on sleep, circadian phase, and performance

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.

The Relationship Between the Dim Light Melatonin Onset and Sleep on a Regular Schedule in Young Healthy Adults

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 individuals 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 peoples DLMOs from their sleep times is discussed.

The impact of training schedules on the sleep and fatigue of elite athletes

In any sport, successful performance requires a planned approach to training and recovery. While sleep is recognized as an essential component of this approach, the amount and quality of sleep routinely obtained by elite athletes has not been systematically evaluated. Data were collected from 70 nationally ranked athletes from seven different sports. Athletes wore wrist activity monitors and completed self-report sleep/training diaries for 2 weeks during normal training. The athletes also recorded their fatigue level prior to each training session using a 7-point scale. On average, the athletes spent 08:18 ± 01:12 h in bed, fell asleep at 23:06 ± 01:12 h, woke at 6:48 ± 01:30 h and obtained 06:30 ± 01:24 h of sleep per night. There was a marked difference in the athletes’ sleep/wake behaviour on training days and rest days. Linear mixed model analyses revealed that on nights prior to training days, time spent in bed was significantly shorter (p = 0.001), sleep onset and offset times were significantly earlier (p < 0.001) and the amount of sleep obtained was significantly less (p = 0.001), than on nights prior to rest days. Moreover, there was a significant effect of sleep duration on pre-training fatigue levels (p ≤ 0.01). Specifically, shorter sleep durations were associated with higher levels of pre-training fatigue. Taken together, these findings suggest that the amount of sleep an elite athlete obtains is dictated by their training schedule. In particular, early morning starts reduce sleep duration and increase pre-training fatigue levels. When designing schedules, coaches should be aware of the implications of the timing of training sessions for sleep and fatigue. In cases where early morning starts are unavoidable, countermeasures for minimizing sleep loss – such as strategic napping during the day and correct sleep hygiene practices at night – should be considered.

Sleep, Wake and Phase Dependent Changes in Neurobehavioral Function under Forced Desynchrony

STUDY OBJECTIVES The homeostatic-circadian regulation of neurobehavioral functioning is not well understood in that the role of sleep dose in relation to prior wake and circadian phase remains largely unexplored. The aim of the present study was to examine the neurobehavioral impact of sleep dose at different combinations of prior wake and circadian phase. DESIGN A between-participant design involving 2 forced desynchrony protocols varying in sleep dose. Both protocols comprised 7 repetitions of a 28-h sleep/wake cycle. The sleep dose in a standard protocol was 9.33 h per 28-h day and 4.67 h in a sleep-restricted protocol. SETTING A time-isolation laboratory at the Centre for Sleep Research, the University of South Australia. PARTICIPANTS A total of 27 young healthy males participated in the study with 13 in the standard protocol (age 22.5 ± 2.2 y) and 14 in the sleep-restricted protocol (age 21.8 ± 3.8 y). INTERVENTIONS Wake periods during both protocols were approximately 4 h delayed each 28-h day relative to the circadian system, allowing performance testing at different combinations of prior wake and circadian phase. The manipulation in sleep dose between the 2 protocols, therefore, allowed the impact of sleep dose on neurobehavioral performance to be examined at various combinations of prior wake and circadian phase. MEASUREMENTS AND RESULTS Neurobehavioral function was assessed using the psychomotor vigilance task (PVT). There was a sleep dose × circadian phase interaction effect on PVT performance such that sleep restriction resulted in slower and more variable response times, predominantly during the biological night. This interaction was not altered by prior wakefulness, as indicated by a nonsignificant sleep dose × circadian phase × prior wake interaction. CONCLUSIONS The performance consequence of sleep restriction in our study was prominent during the biological night, even when the prior wake duration was short, and this performance consequence was in forms of waking state instability. This result is likely due to acute homeostatic sleep pressure remaining high despite the sleep episode.

Mismatch between subjective alertness and objective performance under sleep restriction is greatest during the biological night

Subjective alertness may provide some insight into reduced performance capacity under conditions suboptimal to neurobehavioural functioning, yet the accuracy of this insight remains unclear. We therefore investigated whether subjective alertness reflects the full extent of neurobehavioural impairment during the biological night when sleep is restricted. Twenty‐seven young healthy males were assigned to a standard forced desynchrony (FD) protocol (n = 13; 9.33 h in bed/28 h day) or a sleep‐restricted FD protocol (n = 14; 4.67 h in bed/28 h day). For both protocols, subjective alertness and neurobehavioural performance were measured using a visual analogue scale (VAS) and the psychomotor vigilance task (PVT), respectively; both measures were given at various combinations of prior wake and circadian phase (biological night versus biological day). Scores on both measures were standardized within individuals against their respective baseline average and standard deviation. We found that PVT performance and VAS rating deviated from their respective baseline to a similar extent during the standard protocol, yet a greater deviation was observed for PVT performance than VAS rating during the sleep‐restricted protocol. The discrepancy between the two measures during the sleep‐restricted protocol was particularly prominent during the biological night compared with the biological day. Thus, subjective alertness did not reflect the full extent of performance impairment when sleep was restricted, particularly during the biological night. Given that subjective alertness is often the only available information upon which performance capacity is assessed, our results suggest that sleep‐restricted individuals are likely to under‐estimate neurobehavioural impairment, particularly during the biological night.

The sensitivity of a palm-based psychomotor vigilance task to severe sleep loss

In this study, we evaluated the sensitivity of a 5-min personal digital assistant—psychomotor vigilance test (PDA-PVT) to severe sleep loss. Twenty-one participants completed a 10-min PVT-192 and a 5-min PDA—PVT at two hourly intervals during 62 h of sustained wakefulness. For both tasks, response speed and number of lapses (RTs > 500) per minute significantly increased with increasing hours of wakefulness. Overall, standardized response speed scores on the 5-min PDA—PVT closely tracked those of the PVT-192; however, the PDA—PVT was generally associated with more lapses/minute. Closer inspection of the data indicated that when the level of sleep loss and fatigue became more severe (i.e., Day 3), the 5-min PDA—PVT was not quite as sensitive as the 10-min PVT-192 when 2- to 10-sec foreperiods were used for both. It is likely, however, that the observed differences between the two devices was due to differences in task length. Thus, the findings provide further evidence of the validity of the 5-min PDA—PVT as a substitute for the 10-min PVT-192, particularly in circumstances in which a shorter test is required and/or the PVT-192 is not as practical.

The amount of sleep obtained by locomotive engineers: effects of break duration and time of break onset

Aims: To determine the effects of break duration and time of break onset on the amount of sleep that locomotive engineers obtain between consecutive work periods. Methods: A total of 253 locomotive engineers (249 male, 4 female, mean age 39.7 years) participated. Data were collected at 14 rail depots, where participants drove electric or diesel locomotives; worked with another engineer or drove alone; carried passengers, freight, or coal; and operated in rural or urban areas. Participants completed sleep diaries and work diaries for a two week period while working their normal roster patterns. Results: For breaks that began at similar times of day, total sleep time (TST) increased with break duration. For breaks of similar duration, TST was greater for those that occurred during the night-time than for those that occurred during the daytime. An average of 3.1–7.9 hours sleep was obtained in 12 hour breaks (minimum break requirement in the Australian rail industry), depending on when the break began. Conclusions: The duration and timing of breaks are both important factors in determining the amount of sleep that locomotive engineers obtain between consecutive work periods. Consequently, minimum length break requirements that do not include a time of day component may not provide locomotive engineers with the opportunity to obtain a sufficient amount of sleep prior to resuming work.