Early starts and late finishes both reduce alertness and performance among short-haul airline pilots.

Flight crews are frequently required to work irregular schedules and, as a result, can experience sleep deficiency and fatigue. This study was conducted to determine whether perceived fatigue levels and objective performance varied by time of day, time awake, and prior night's sleep duration. Ninety-five pilots (86 male, 9 female) aged 33 years (±8) volunteered for the study. Participants completed a daily sleep diary, Samn-Perelli fatigue scale, and psychomotor vigilance task that were completed before and after each flight duty period and at the top-of-descent for each flight. Pilots experienced higher self-reported fatigue (EMM = 3.92, SE = 0.09, p < 0.001) and worse performance (Response speed: EMM = 4.27, SE = 0.08, p = 0.004) for late-finishing duties compared with early-starting duties (Samn-Perelli: EMM = 3.74, SE = 0.08; Response speed: EMM = 4.37, SE = 0.08), but had shorter sleep before early-starting duties (early: EMM = 6.94, SE = 0.10; late: EMM = 8.47, SE = 0.14, p < 0.001). However, pre-duty Samn-Perelli and response speed were worse (z = 4.18, p < 0.001; z = 3.05, p = 0.03; respectively) for early starts compared with late finishes (EMM = 2.74, SE = 0.19), while post-duty Samn-Perelli was worse for late finishes (EMM = 4.74, SE = 0.19) compared with early starts (EMM = 4.05, SE = 0.12). The results confirm that duty time has a strong influence on self-reported fatigue and performance. Thus, all flights that encroach on a biological night are targets for fatigue risk management oversight.

Performance on the Robotics On-Board Trainer (ROBoT-r) Spaceflight Simulation During Acute Sleep Deprivation.

Exploration of deep space poses many challenges. Mission support personnel will not be immediately available to assist crewmembers performing complex operations on future long-duration exploration operations. Consequently, it is imperative that crewmembers have objective, reliable, and non-invasive metrics available to aid them in determining their fitness for duty prior to engaging in potentially dangerous tasks. The Robotics On-Board Trainer (ROBoT) task is NASA's platform for training astronauts to perform docking and grappling maneuvers. It is regularly used by crewmembers during spaceflight for refresher training. The operational ROBoT system, however, does not record data. Thus, a research version of ROBoT, called ROBoT-r, was developed so that operationally relevant data could be mined to provide feedback to crewmembers. We investigated whether ROBoT-r metrics would change according to sleep loss and circadian phase in a 28-h laboratory-based sleep deprivation study. Overall, participants showed improvement over time despite sleep loss, indicating continued learning. Performance on the psychomotor vigilance task (PVT) followed an expected profile, with reduced performance across the night. These findings suggest that individuals may be able to temporarily compensate for sleep loss to maintain performance on complex, novel tasks. It is possible that some ROBoT-r metrics may be sensitive to sleep loss after longer bouts of wakefulness or after individuals have habituated to the task. Studies with additional participants and extended pre-training on the ROBoT-r task should be conducted to disentangle how brain activity may change as individuals learn and habituate to complex tasks during sleep loss.

The relationship between workload, performance and fatigue in a short-haul airline.

The aim of this study was to determine the relationship between pilot workload, performance, subjective fatigue, sleep duration, number of sectors and flight duration during short-haul operations. Ninety pilots completed a NASA Task Load Index, Psychomotor Vigilance Task and a Samn-Perelli fatigue scale on top-of-descent of each flight and wore an activity monitor throughout the study. Weak, but significant, correlations were revealed between workload and all factors. Subjective fatigue, number of sectors and lapses were significant predictors of workload. Pilots reported higher workload when fatigue increased, the number of sectors were higher, and objective performance was worse.

Mitigating fatigue on the flight deck: how is controlled rest used in practice?

Controlled Rest (CR) refers to a short, unscheduled, voluntary nap opportunity taken by pilots on the flight deck as a countermeasure to unanticipated fatigue in flight. This study explores the profile of CR use in a long-haul commercial airline. Forty-four pilots wore actiwatches and filled in an application-based sleep/work diary for approximately 2 weeks resulting in complete records from 239 flights. Timing of sleep periods and flight schedules were analyzed relative to home-base time. Pearson correlations were used to assess the influence of pilot demographics on CR use. A mixed-effects logistic regression was used to analyze the impact of schedule factors on CR. CR was taken on 46% (n = 110) of flights, with 80% (n = 106/133) of all CR attempts (accounting for multiple CR attempts on 23 flights) estimated by actigraphy to have successfully achieved sleep. Average sleep duration during successful rest periods was estimated as 31.7 ± 12.2 min. CR was more frequent on 2-pilot (69%, n = 83) vs. >2-pilot flights (23%, n = 27); return (60%, n = 71) vs. outbound flights (33%, n = 39); night (55%, n = 76) vs. day flights (34%, n = 34); and <10 h (63%, n = 80) vs. >10 h duration flights (27%, n = 30) (all p ≤ 0.001). There was no significant difference for direction of travel (eastbound: 51%, n = 57; westbound: 40%, n = 44; p = .059). Of note, 22% (n = 26) of augmented flights contained both CR and bunk rest. Data from this airline show that CR is most commonly used on flights with 2-pilot crews (<10 h duration) and nighttime flights returning to base. Future studies are required to determine the generalizability of these results to other airlines.

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments.

Sleep loss and circadian misalignment contribute to a meaningful proportion of operational accidents and incidents. Countermeasures and work scheduling designs aimed at mitigating fatigue are typically evaluated in controlled laboratory environments, but the effectiveness of translating such strategies to operational environments can be challenging to assess. This manuscript summarizes an approach for collecting sleep, circadian, fatigue, and performance data in a complex operational environment. We studied 44 airline pilots over 34 days while they flew a fixed schedule, which included a baseline data collection with 5 days of mid-morning flights, four early flights, four high-workload mid-day flights, and four late flights that landed after midnight. Each work block was separated by 3-4 days of rest. To assess sleep, participants wore a wrist-worn research-validated activity monitor continuously and completed daily sleep diaries. To assess the circadian phase, pilots were asked to collect all urine produced in four or eight hourly bins during the 24 h after each duty block for the assessment of 6-sulfatoxymelatonin (aMT6s), which is a biomarker of the circadian rhythm. To assess subjective fatigue and objective performance, participants were provided with a touch-screen device used to complete the Samn-Perelli Fatigue Scale and Psychomotor Vigilance Task (PVT) during and after each flight, and at waketime, mid-day, and bedtime. Using these methods, it was found that sleep duration was reduced during early starts and late finishes relative to baseline. Circadian phase shifted according to duty schedule, but there was a wide range in the aMT6s peak between individuals on each schedule. PVT performance was worse on the early, high-workload, and late schedules relative to baseline. Overall, the combination of these methods was practical and effective for assessing the influence of sleep loss and circadian phase on fatigue and performance in a complex operational environment.

Validation of a touchscreen psychomotor vigilance task.

OBJECTIVE: The purpose of this study was to compare a psychomotor vigilance task developed for use on touchscreen devices with the original PVT-192 in conditions of acute sleep loss and circadian desynchronization. BACKGROUND: The Psychomotor Vigilance Task (PVT) is considered the gold standard fatigue detection test and is used frequently in fatigue research. With the rapid development of new technologies it is essential to develop a PVT available on different platforms such as touchscreen devices. The advantage of such PVT is that it can be implemented on small devices and can be easily used in field studies. METHODS: Ten participants completed a 5-min PVT (NASA-PVT) on a touchscreen device and a 5-min PVT on the original PVT-192. On the day of the experiment, participants arrived in the lab approximately two hours after their habitual wake time. Participants completed a constant routine protocol under dim lighting, while maintaining a constant posture. The 5-min PVT-192 and NASA-PVT were taken every two hours for at least 24h. RESULTS: The NASA-PVT and PVT-192 were sensitive to extended wakefulness in the same manner. The reaction times were slower and the lapses were higher as time progressed on both NASA-PVT and PVT-192 (p<0.001). Overall, there was a sharp decline in performance after 16h of being awake which coincided with the time the participants were usually going to bed and the worst performance occurred after 24h of wakefulness for both PVTs (p<0.001). CONCLUSIONS: Overall, our data suggest that the NASA-PVT is a valid tool for assessing fatigue in field studies.

Sleep and neurobehavioral performance vary by work start time during non-traditional day shifts.

INTRODUCTION: It is established that shiftwork causes sleep loss and circadian misalignment. Individuals who work non-traditional day shifts that encroach into typical sleep times, such as those in the service and transportation sectors, may also experience sleep and circadian disruption. We aimed to determine how neurobehavioral performance and sleep would be affected by work start time among individuals working a non-traditional daytime shift pattern. METHODS: We collected sleep diaries, wrist-worn actigraphy (CamNtech, Cambridge UK), and the psychomotor vigilance task (PVT) from 44 pilots (4F) who worked a shift rotation consisting of a five-day baseline block starting in the mid-morning (baseline), five early shifts (early), five high workload midday shifts (midday), and five days of late shifts (late), each separated by 3-4 days off. RESULTS: Mixed-model analysis revealed that individuals obtained less sleep when working the early shifts (5.70 ±â€¯0.73 h) relative to baseline (6.78 ±â€¯0.86 h; P < .01). Sleep duration declined significantly from the beginning to the end of late shifts (P = .003). All shifts were associated with decreased reaction time on the PVT relative to baseline (236 ±â€¯48; early, 257 ±â€¯70 ms; midday 261 ±â€¯62 ms; late 266 ±â€¯64 ms; P < .01 for all). CONCLUSIONS: We found that non-traditional day shifts encroach on an individual's sleep opportunity and such shifts could be a contributing factor to the high prevalence of sleep deficiency observed in modern society. Our findings suggest that it would be prudent for industries requiring such shifts to expand fatigue risk management training to individuals classified as day shift workers.

Evaluation of a Psychomotor Vigilance Task for Touch Screen Devices.

OBJECTIVE: Our goals were to compare three techniques for performing a psychomotor vigilance task (PVT) on a touch screen device (fifth-generation iPod) and to determine the device latency. BACKGROUND: The PVT is a reaction-time test that is sensitive to sleep loss and circadian misalignment. Several PVT tests have been developed for touch screen devices, but unlike the standard PVT developed for laboratory use, these tests allow for touch responses to be recorded at any location on the device, with contact from any finger. In addition, touch screen devices exhibit latency in processing time between the touch response and the time registered by the device. METHOD: Thirteen participants completed a 5-min PVT on a touch screen device held in three positions (on a table with index finger, handheld portrait with index finger, handheld landscape with thumb). We compared reaction-time outcomes in each orientation condition using paired t tests. We recorded the first session using a high-speed video camera to determine the latency between the touch response and the documented response time. RESULTS: The participants had significantly faster reaction times in the landscape-oriented position using the thumb, compared with the portrait-oriented position using the index ( M = 224.13 and M = 244.26, p = .045). Using data from 1,241 unique touch events, we found a mean device latency of 68.53 ms that varied highly between individuals. CONCLUSION: Device orientation and device latency should be considered when using a touch screen version of a PVT. APPLICATION: Our findings apply to researchers administering touch screen versions of the PVT.