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.
SUMMARYThe present study systematically compared the effects of fatigue and alcohol intoxication on a range of neurobehavioural tasks. By doing so, it was possible to quantify the performance impairment associated with fatigue and express it as a blood alcohol impairment equivalent. Twenty-two healthy subjects aged 19-26 years participated in three counterbalanced conditions. In the sustained wakefulness condition, subjects were kept awake for 28 h. In the alcohol and placebo conditions, subjects consumed either an alcoholic or non-alcoholic beverage at 30 min intervals, until their blood alcohol concentration reached 0.10%. In each session, performance was measured at hourly intervals using four tasks from a standardised computerbased test battery. Analysis indicated that the placebo beverage did not significantly effect mean relative performance. In contrast, as blood alcohol concentration increased performance on all the tasks, except for one, significantly decreased. Similarly, as hours of wakefulness increased performance levels for four of the six parameters significantly decreased. More importantly, equating the performance impairment in the two conditions indicated that, depending on the task measured, approximately 20-25 h of wakefulness produced performance decrements equivalent to those observed at a blood alcohol concentration (BAC) of 0.10%. Overall, these results suggest that moderate levels of fatigue produce performance equivalent to or greater than those observed at levels of alcohol intoxication deemed unacceptable when driving, working and/or operating dangerous equipment.
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 ¼ 21.7 years) slept in the sleep laboratory overnight then remained awake for 28 h from 08:00 h. During every second hour, participants completed three PVTs of differing duration (10 min, 5 min, 90 sec). For the 5 min/10 min comparison, ANOVA indicated that response time was significantly affected by test length (F 1,14 ¼ 26.9, p , .001) and hours of wakefulness (F 13,182 ¼ 46.1, p , .001) but not by their interaction (F 13,182 ¼ 1.7, ns). There was a strong correlation between response time on the 5 and 10 min PVTs (r ¼ .88, p , .001). For the 90 sec/10 min comparison, ANOVA indicated that response time was significantly affected by test length (F 1,14 ¼ 65.9, p , .001) and hours of wakefulness (F 13,182 ¼ 29.7, p , .001) as well as by their interaction (F 13,182 ¼ 6.0, p , .001). There was a strong correlation between response time on the 90 sec and 10 min PVTs (r ¼ .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.
The frequency and severity of adverse events in Australian healthcare is under increasing scrutiny. A recent state government report identified 31 events involving "death or serious [patient] harm" and 452 "very high risk" incidents. Australia-wide, a previous study identified 2,324 adverse medical events (AME) in a single year, with more than half considered preventable. Despite the recognized link between fatigue and error in other industries, to date, few studies of medical errors have assessed the fatigue of the healthcare professionals involved. Nurses work extended and unpredictable hours with a lack of regular breaks and are therefore likely to experience elevated fatigue. Currently, there is very little available information on Australian nurses' sleep or fatigue levels, nor is there any information about whether this affects their performance. This study therefore aims to examine work hours, sleep, fatigue and error occurrence in Australian nurses. Using logbooks, 23 full-time nurses in a metropolitan hospital completed daily recordings for one month (644 days, 377 shifts) of their scheduled and actual work hours, sleep length and quality, sleepiness, and fatigue levels. Frequency and type of nursing errors, near errors, and observed errors (made by others) were recorded. Nurses reported struggling to remain awake during 36% of shifts. Moderate to high levels of stress, physical exhaustion, and mental exhaustion were reported on 23%, 40%, and 36% of shifts, respectively. Extreme drowsiness while driving or cycling home was reported on 45 occasions (11.5%), with three reports of near accidents. Overall, 20 errors, 13 near errors, and 22 observed errors were reported. The perceived potential consequences for the majority of errors were minor; however, 11 errors were associated with moderate and four with potentially severe consequences. Nurses reported that they had trouble falling asleep on 26.8% of days, had frequent arousals on 34.0% of days, and that work-related concerns were either partially or fully responsible for their sleep disruption on 12.5% of occasions. Fourteen out of the 23 nurses reported using a sleep aid. The most commonly reported sleep aids were prescription medications (62.7%), followed by alcohol (26.9%). Total sleep duration was significantly shorter on workdays than days off (p < 0.01). In comparison to other workdays, sleep was significantly shorter on days when an error (p < 0.05) or a near error (p < 0.01) was recorded. In contrast, sleep was higher on workdays when someone else's error was recorded (p = 0.08). Logistic regression analysis indicated that sleep duration was a significant predictor of error occurrence (chi2 = 6.739, p = 0.009, e beta = 0.727). The findings of this pilot study suggest that Australian nurses experience sleepiness and related physical symptoms at work and during their trip home. Further, a measurable number of errors occur of various types and severity. Less sleep may lead to the increased likelihood of making an error, and importantly, the decreased...
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 present study aimed to systematically investigate the effects of elevated fatigue levels on the ability to self‐monitor performance. Eighteen participants, aged 19–26 y, remained awake for a period of 28 h. Neurobehavioural performance was measured at hourly intervals using four tests from a standardized computer test battery. From these four tests, six measures of performance were obtained: grammatical reasoning (accuracy and response latency); vigilance (accuracy and response latency); simple sensory comparison and tracking. In addition, before and after each test, participants completed visual analogue scales which required them to rate their alertness level and the speed and accuracy of their performance. Individual test results for both self‐ratings and neurobehavioural performance were converted to z‐scores. Planned comparison analysis indicated that scores on four of the six performance measures decreased significantly as hours of wakefulness increased. Similarly, predicted performance scores for all six measures of performance decreased significantly. Analysis revealed moderate correlations between predicted and actual performance for the four parameters affected by fatigue. Furthermore, moderate to high correlations were found between all six performance parameters and their respective post‐test self‐ratings. In addition, moderate to high correlations were found between predicted performance and alertness. Taken together, these findings suggest that as fatigue levels increase, subjects globally assess performance decrements. Results suggest that subjective alertness may in part mediate an individual’s global assessment of performance.
Summary Rate of recovery of daytime performance and sleepiness following moderate and severe sleep deprivation (SD) was examined when recovery opportunity was either augmented or restricted. Thirty healthy non‐smokers, aged 18–33 years, participated in one of three conditions: moderate SD with augmented (9‐h) recovery opportunities, moderate SD with restricted (6‐h) recovery opportunities, or severe SD with augmented recovery opportunities. Each participant attended the laboratory for 8–9 consecutive nights: an adaptation and baseline night (23:00–08:00 hours), one or two night(s) of wakefulness, and five consecutive recovery sleep opportunities (23:00–08:00 hours or 02:00–08:00 hours). On each experimental day, psychomotor vigilance performance (PVT) and subjective sleepiness (SSS) were assessed at two‐hourly intervals, and MSLTs were performed at 1000h. PSG data was collected for each sleep period. For all groups, PVT performance significantly deteriorated during the period of wakefulness, and sleepiness significantly increased. Significant differences were observed between the groups during the recovery phase. Following moderate SD, response speed, lapses and SSS returned to baseline after one 9‐h sleep opportunity, while sleep latencies required two 9‐h opportunities. When the recovery opportunity was restricted to six hours, neither PVT performance nor sleepiness recovered, but stabilised at below‐baseline levels. Following severe SD, sleepiness recovered after one (SSS) or two (physiological) 9‐h sleep opportunities, however PVT performance remained significantly below baseline for the entire recovery period. These results suggest that the mechanisms underlying the recovery process may be more complicated than previously thought, and that we may have underestimated the impact of sleep loss and/or the restorative value of subsequent sleep.
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