Pilot In-Flight Sleep During Long-Range and Ultra-Long Range Commercial Airline Flights.

INTRODUCTION: In commercial aviation, pilot fatigue is a major threat to safety. One key fatigue mitigation strategy on long-range (LR; 8-16 h) and ultra-long range (ULR; 16+ h on at least 10% of trips) routes is allotting in-flight rest breaks for the pilots. Since sleep is a strong predictor of performance, it is important to quantify total in-flight sleep (TIFS) and determine rest scheme schedules that optimize sleep opportunity and subsequent performance. Here we quantify in-flight sleep and characterize rest schemes by type and efficiency.METHODS: Between 2015 and 2019, we collected data on in-flight sleep on 3 LR and 5 ULR routes totaling 231 pilots flying over 1200 flight duty periods. Data were collected using a combination of actigraphy and logbooks.RESULTS: Over all combinations of flight direction, crew and LR vs. ULR, average TIFS ranged from 3.4 h to 5.2 h with some ULR pilots getting over 8 h. Most crews made use of simple two- or three-break rest schemes and the complex four-break rest schemes were used almost exclusively on the three longest ULR routes. The complex schemes were less efficient than simple schemes, although this effect was small. Complex schemes resulted in no more TIFS compared to simple schemes on the same routes.DISCUSSION: Overall, we find that crews are getting more sleep on these routes than previously reported on similar routes. Most crews use simple rest schemes and these simple schemes are more efficient than complex schemes.Rempe MJ, Basiarz E, Rasmussen I, Belenky G, Lamp A. Pilot in-flight sleep during long-range and ultra-long range commercial airline flights. Aerosp Med Hum Perform. 2022; 93(4):368-375.

Flight Crew Alertness and Sleep Relative to Timing of In-Flight Rest Periods in Long-Haul Flights.

BACKGROUND: In-flight breaks are used during augmented long-haul flight operations, allowing pilots a sleep opportunity. The U.S. Federal Aviation Administration duty and rest regulations restrict the pilot flying the landing to using the third rest break. It is unclear how effective these restrictions are on pilots ability to obtain sleep. We hypothesized there would be no difference in self-reported sleep, alertness, and fatigue between pilots taking the second vs. third rest breaks.METHODS: Pilots flying augmented operations in two U.S.-based commercial airlines were eligible for the study. Volunteers completed a survey at top-of-descent (TOD), including self-reported in-flight sleep duration, and Samn-Perelli fatigue and Karolinska Sleepiness Scale ratings. We compared the second to third rest break using noninferiority analysis. The influence of time of day (home-base time; HBT) was evaluated in 4-h blocks using repeated measures ANOVA.RESULTS: From 787 flights 500 pilots provided complete data. The second rest break was noninferior to the third break for self-reported sleep duration (1.5 0.7 h vs. 1.4 0.7 h), fatigue (2.0 1.0 vs. 2.9 1.3), and sleepiness (2.6 1.4 vs. 3.8 1.8) at TOD for landing pilots. Measures of sleep duration, fatigue, and sleepiness were influenced by HBT circadian time of day.DISCUSSION: We conclude that self-reported in-flight sleep, fatigue, and sleepiness from landing pilots taking the second in-flight rest break are equivalent to or better than pilots taking the third break. Our findings support providing pilots with choice in taking the second or third in-flight rest break during augmented operations.Gregory KB, Soriano-Smith RN, Lamp ACM, Hilditch CJ, Rempe MJ, Flynn-Evans EE, Belenky GL. Flight crew alertness and sleep relative to timing of in-flight rest periods in long-haul flights. Aerosp Med Hum Perform. 2021; 92(2):8391.

Delta: The Value That Matters in Fatigue Risk Management.

INTRODUCTION: Noninferiority or equivalence testing are often used when comparing a novel pharmaceutical, operation, or procedure to the current standard designated as safe. Noninferiority and equivalence testing require estimates of a metric called delta: the margin of meaningful difference. Inappropriate delta margins can lead to invalid conclusions, thereby creating uncertainty about a studys scientific credibility. We recommend that a working group be convened with the following goals: 1) to evaluate delta values currently in use in aviation; 2) to determine if it is possible to develop a systematic, evidence-based, and replicable process to derive delta values based on statistical properties from population data, rather than a mixture of evidence- and opinion-based processes; and 3) based on the findings of the second goal, update the current delta values in use in aviation. This working group should include, at a minimum, government agencies and other key stakeholders using these values within operational settings.Lamp ACM, Rempe MJ, Belenky GL. Delta: the value that matters in fatigue risk management. Aerosp Med Hum Perform. 2021; 92(2):127128.

Pilot Sleep in Long-Range and Ultra-Long-Range Commercial Flights.

INTRODUCTION: Despite the clear need for understanding how pilot sleep affects performance during long-range (LR; 12-16h) and ultra-long-range (ULR; 16+h) flights, the scientific literature on the effects of sleep loss and circadian desynchronization on pilots' sleep in commercial aviation is sparse.METHODS: We assessed pilots' sleep timing, duration, and post-trip recovery on two LR and two ULR nonstop California to Australasia routes. Pilot's sleep/wake history was measured with actigraphy and verified by logbook across 8-9 d.RESULTS: Pilots averaged 8.210 ± 1.687 SD hours of sleep per 24 h across the study period. A logistic model of the circadian timing of sleep indicated that time of day and phase of trip are significant predictors of pilots being asleep. Significant two- and three-way interactions were found between time of day, phase of trip, and route. A significant difference in average sleep time was observed between baseline and recovery day 1 for one route. All other recovery days and routes were not significantly different from baseline.DISCUSSION: For the four routes, the average amount of sleep per 24-h period during the study period was within the normal range with the circadian rhythm aligned to home-base time pre- and post-trip. Flight segments and layover conditions were associated with a misalignment of sleep relative to circadian rhythm, with layover sleep appearing to shift toward the local night. Full post-trip sleep duration recovery appears to occur for all routes within 1-2 d.Lamp A, McCullough D, Chen JMC, Brown RE, Belenky G. Pilot sleep in long-range and ultra-long-range commercial flights. Aerosp Med Hum Perform. 2019; 90(2):109-115.

Equal to or better than: The application of statistical non-inferiority to fatigue risk management.

In December 2014, the Federal Aviation Administration (FAA) completed a major revision of the rules and regulations governing flight and duty time in commercial aviation (Federal Aviation Regulation (FAR) Part 117). Scientists were included in the revision process and provided insights into sleep, sleep loss, the circadian rhythm, and their effects on performance that were incorporated into the new rule. If a planned flight was non-compliant with the regulation, for example if it exceeded flight and duty time limits, it could only be flown under an FAA-approved Fatigue Risk Management System (FRMS) as meeting an Alternative Method of Compliance (AMOC). One method that a flight could qualify as an AMOC is if it could be demonstrated empirically that it was as safe as or safer than a similar flight, designated the Safety Standard Operation (SSO), that was compliant with the regulation. In the present paper, we demonstrate the FRMS process using a comparison between a non-compliant AMOC flight from the US west coast to Australia and a compliant SSO flight from the US west coast to Taiwan. The AMOC was non-compliant because it exceeded the flight time limits in the prescriptive rule. Once a data collection exemption was granted by the FAA, both the outbound and inbound AMOC and SSO routes were studied on four Safety Performance Indicators (SPIs). The SPIs studied were inflight sleep, cognitive performance, self-reported fatigue, and self-reported sleepiness. These measures were made at top of descent (TOD), a critical phase of flight. The study was designed as a paired comparison. Forty volunteer pilots studied flew both the AMOC and the SSO flights for a total of 80 studied flights. Using statistical non-inferiority applied to the AMOC and SSO SPIs, we demonstrated, as required by the new rule, that the US-Australia AMOC flight was "as safe as, or safer than" the US-Taiwan SSO flight. In the context of FRMS, statistical non-inferiority is a concept and technique of great utility, straightforward in application, producing clear visual representations of the findings, and providing a direct answer to the question posed by the regulation - is the AMOC flight "as safe as, or safer than" the SSO.

Examining Longitudinal Stimulant Use and Treatment Attendance as Parallel Outcomes in Two Contingency Management Randomized Clinical Trials.

The primary aim of this study was to examine stimulant use and longitudinal treatment attendance in one 'parallel outcomes' model in order to determine how these two outcomes are related to one another during treatment, and to quantify how the intervention impacts these two on- and off-target outcomes differently. Data came from two multi-site randomized clinical trials (RCTs) of contingency management (CM) that targeted stimulant use. We used parallel multilevel modeling to examine the impact of multiple pre-specified covariates, including selected Addiction Severity Index (ASI) scores, age and sex, in addition to CM on concurrent attendance and stimulant use in two separate analyses, i.e., one per trial. In one trial, CM was positively associated with attending treatment throughout the trial (ß=0.060, p<0.05). In the second trial, CM predicted negative urinalysis ((-)UA) over the 12-week treatment period (ß=0.069, p<0.05). In both trials, there was a significant, positive relationship between attendance and (-)UA submission, but in the first trial a (-)UA at both baseline and over time was related to attendance over time (r=0.117; r=0.013, respectively) and in the second trial, a (-)UA submission at baseline was associated with increased attendance over time (r=0.055). These findings indicate that stimulant use and treatment attendance over time are related but distinct outcomes that, when analyzed simultaneously, portray a more informative picture of their predictors and the separate trajectories of each. This 'indirect reinforcement' between two clinically meaningful on-target (directly reinforced behavior) and off-target (indirectly reinforced behavior) outcomes is in need of further examination in order to fully exploit the potential clinical benefits that could be realized in substance use disorder treatment trials.

Napping on the Night Shift: A Study of Sleep, Performance, and Learning in Physicians-in-Training.

BACKGROUND: Physicians in training experience fatigue from sleep loss, high workload, and working at an adverse phase of the circadian rhythm, which collectively degrades task performance and the ability to learn and remember. To minimize fatigue and sustain performance, learning, and memory, humans generally need 7 to 8 hours of sleep in every 24-hour period. METHODS: In a naturalistic, within-subjects design, we studied 17 first- and second-year internal medicine residents working in a tertiary care medical center, rotating between day shift and night float every 4 weeks. We studied each resident for 2 weeks while he/she worked the day shift and for 2 weeks while he/she worked the night float, objectively measuring sleep by wrist actigraphy, vigilance by the Psychomotor Vigilance Task test, and visual-spatial and verbal learning and memory by the Brief Visuospatial Memory Test-Revised and the Rey Auditory-Verbal Learning Test. RESULTS: Residents, whether working day shift or night float, slept approximately 7 hours in every 24-hour period. Residents, when working day shift, consolidated their sleep into 1 main sleep period at night. Residents working night float split their sleep, supplementing their truncated daytime sleep with nighttime on-duty naps. There was no difference in vigilance or learning and memory, whether residents worked day shift or night float. CONCLUSIONS: Off-duty sleep supplemented with naps while on duty appears to be an effective strategy for sustaining vigilance, learning, and memory when working night float.