Behavioral health risks are among the most serious and difficult to mitigate risks of confinement in space craft during long-duration space exploration missions. We report on behavioral and ...psychological reactions of a multinational crew of 6 healthy males confined in a 550 m(3) chamber for 520 days during the first Earth-based, high-fidelity simulated mission to Mars. Rest-activity of crewmembers was objectively measured throughout the mission with wrist-worn actigraphs. Once weekly throughout the mission crewmembers completed the Beck Depression Inventory-II (BDI-II), Profile of Moods State short form (POMS), conflict questionnaire, the Psychomotor Vigilance Test (PVT-B), and series of visual analogue scales on stress and fatigue. We observed substantial inter-individual differences in the behavioral responses of crewmembers to the prolonged mission confinement and isolation. The crewmember with the highest average POMS total mood disturbance score throughout the mission also reported symptoms of depression in 93% of mission weeks, which reached mild-to-moderate levels in >10% of mission weeks. Conflicts with mission control were reported five times more often than conflicts among crewmembers. Two crewmembers who had the highest ratings of stress and physical exhaustion accounted for 85% of the perceived conflicts. One of them developed a persistent sleep onset insomnia with ratings of poor sleep quality, which resulted in chronic partial sleep deprivation, elevated ratings of daytime tiredness, and frequent deficits in behavioral alertness. Sleep-wake timing was altered in two other crewmembers, beginning in the first few months of the mission and persisting throughout. Two crewmembers showed neither behavioral disturbances nor reports of psychological distress during the 17-month period of mission confinement. These results highlight the importance of identifying behavioral, psychological, and biological markers of characteristics that predispose prospective crewmembers to both effective and ineffective behavioral reactions during the confinement of prolonged spaceflight, to inform crew selection, training, and individualized countermeasures.
Abstract
Study Objectives:
Fatigue from sleep loss is a risk to physician and patient safety, but objective data on physician sleep and alertness on different duty hour schedules is scarce. This ...study objectively quantified differences in sleep duration and alertness between medical interns working extended overnight shifts and residents not or rarely working extended overnight shifts.
Methods:
Sleep–wake activity of 137 interns and 87 PGY-2/3 residents on 2-week Internal Medicine and Oncology rotations was assessed with wrist-actigraphy. Alertness was assessed daily with a brief Psychomotor Vigilance Test (PVT) and the Karolinska Sleepiness Scale.
Results:
Interns averaged 6.93 hours (95% confidence interval CI 6.84–7.03 hours) sleep per 24 hours across shifts, significantly less than residents not working overnight shifts (7.18 hours, 95% CI 7.06–7.30 hours, p = .007). Interns obtained on average 2.19 hours (95% CI 2.02–2.36 hours) sleep during on-call nights (17.5% obtained no sleep). Alertness was significantly lower on mornings after on-call nights compared to regular shifts (p < .001). Naps between 9 am and 6 pm on the first day post‐call were frequent (90.8%) and averaged 2.84 hours (95% CI 2.69–3.00 hours), but interns still slept 1.66 hours less per 24 hours (95% CI 1.56–1.76 hours) compared to regular shift days (p < .001). Sleep inertia significantly affected alertness in the 60 minutes after waking on-call.
Conclusions:
Extended overnight shifts increase the likelihood of chronic sleep restriction in interns. Reduced levels of alertness after on-call nights need to be mitigated. A systematic comparison of sleep, alertness, and safety outcomes under current and past duty hour rules is encouraged.
BACKGROUND: Sustained high-level cognitive performance is of paramount importance for the success of space missions, which involve environmental, physiological, and psychological stressors that may ...affect brain functions. Despite subjective symptom reports of cognitive fluctuations
in spaceflight, the nature of neurobehavioral functioning in space has not been clarified.METHODS: We developed a computerized cognitive test battery (Cognition) that has sensitivity to multiple cognitive domains and was specifically designed for the high-performing astronaut
population. Cognition consists of 15 unique forms of 10 neuropsychological tests that cover a range of cognitive domains, including emotion processing, spatial orientation, and risk decision making. Cognition is based on tests known to engage specific brain regions as evidenced
by functional neuroimaging. Here we describe the first normative and acute total sleep deprivation data on the Cognition test battery as well as several efforts underway to establish the validity, sensitivity, feasibility, and acceptability of Cognition.RESULTS: Practice
effects and test-retest variability differed substantially between the 10 Cognition tests, illustrating the importance of normative data that both reflect practice effects and differences in stimulus set difficulty in the population of interest. After one night without sleep, medium
to large effect sizes were observed for 3 of the 10 tests addressing vigilant attention (Cohen's d = 1.00), cognitive throughput (d = 0.68), and abstract reasoning (d = 0.65).CONCLUSIONS: In addition to providing neuroimaging-based novel information on the effects of spaceflight
on a range of cognitive functions, Cognition will facilitate comparing the effects of ground-based analogues to spaceflight, increase consistency across projects, and thus enable meta-analyses.Basner M, Savitt A, Moore TM, Port AM, McGuire S, Ecker AJ, Nasrini J, Mollicone DJ, Mott
CM, McCann T, Dinges DF, Gur RC. Development and validation of the Cognition test battery for spaceflight. Aerosp Med Hum Perform. 2015; 86(11):942-952.
Cortisol and C-reactive protein (CRP) typically change during total sleep deprivation (TSD) and psychological stress; however, it remains unknown whether these biological markers can differentiate ...robust individual differences in neurobehavioral performance and self-rated sleepiness resulting from these stressors. Additionally, little is known about cortisol and CRP recovery after TSD. In our study, 32 healthy adults (ages 27-53; mean ± SD, 35.1 ± 7.1 years; 14 females) participated in a highly controlled 5-day experiment in the Human Exploration Research Analog (HERA), a high-fidelity National Aeronautics and Space Administration (NASA) space analog isolation facility, consisting of two baseline nights, 39 h TSD, and two recovery nights. Psychological stress was induced by a modified Trier Social Stress Test (TSST) on the afternoon of TSD. Salivary cortisol and plasma CRP were obtained at six time points, before (pre-study), during baseline, the morning of TSD (TSD AM), the afternoon of TSD (TSD PM), and recovery, and after (post-study) the experiment. A neurobehavioral test battery, including measures of behavioral attention and cognitive throughput, and a self-report measure of sleepiness, was administered 11 times. Resilient and vulnerable groups were defined by a median split on the average TSD performance or sleepiness score. Low and high pre-study cortisol and CRP were defined by a median split on respective values at pre-study. Cortisol and CRP both changed significantly across the study, with cortisol, but not CRP, increasing during TSD. During recovery, cortisol levels did not return to pre-TSD levels, whereas CRP levels did not differ from baseline. When sex was added as a between-subject factor, the time × sex interaction was significant for cortisol. Resilient and vulnerable groups did not differ in cortisol and CRP, and low and high pre-study cortisol/CRP groups did not differ on performance tasks or self-reported sleepiness. Thus, both cortisol and CRP reliably changed in a normal, healthy population as a result of sleep loss; however, cortisol and CRP were not markers of neurobehavioral resilience to TSD and stress in this study.
There are substantial individual differences (resilience and vulnerability) in performance resulting from sleep loss and psychosocial stress, but predictive potential biomarkers remain elusive. ...Similarly, marked changes in the cardiovascular system from sleep loss and stress include an increased risk for cardiovascular disease. It remains unknown whether key hemodynamic markers, including left ventricular ejection time (LVET), stroke volume (SV), heart rate (HR), cardiac index (CI), blood pressure (BP), and systemic vascular resistance index (SVRI), differ in resilient vs. vulnerable individuals and predict differential performance resilience with sleep loss and stress. We investigated for the first time whether the combination of total sleep deprivation (TSD) and psychological stress affected a comprehensive set of hemodynamic measures in healthy adults, and whether these measures differentiated neurobehavioral performance in resilient and vulnerable individuals. Thirty-two healthy adults (ages 27-53; 14 females) participated in a 5-day experiment in the Human Exploration Research Analog (HERA), a high-fidelity National Aeronautics and Space Administration (NASA) space analog isolation facility, consisting of two baseline nights, 39 h TSD, and two recovery nights. A modified Trier Social Stress Test induced psychological stress during TSD. Cardiovascular measure collection SV, HR, CI, LVET, BP, and SVRI and neurobehavioral performance testing (including a behavioral attention task and a rating of subjective sleepiness) occurred at six and 11 timepoints, respectively. Individuals with longer pre-study LVET (determined by a median split on pre-study LVET) tended to have poorer performance during TSD and stress. Resilient and vulnerable groups (determined by a median split on average TSD performance) showed significantly different profiles of SV, HR, CI, and LVET. Importantly, LVET at pre-study, but not other hemodynamic measures, reliably differentiated neurobehavioral performance during TSD and stress, and therefore may be a biomarker. Future studies should investigate whether the non-invasive marker, LVET, determines risk for adverse health outcomes.
Abstract
Study Objectives
Prescription sleep aids are frequently used in the general population and even more frequently in spaceflight. To evaluate the risk to operational safety, a ground-based, ...double-blind, placebo-controlled study on the emergent awakening effects of zolpidem and zaleplon was conducted.
Methods
N = 34 participants (age M = 42.1 ± 9.7; 25 males; 9 Astronauts, 7 Astronaut candidates, and 18 Flight Controllers) were investigated for three nights separated by M = 10 days. They were randomized to ingestion of one of the following at lights out: placebo, 10 mg zaleplon, and either 5 mg (N = 20) or 10 mg (N = 14) zolpidem. They were awakened abruptly by alarm at the expected PK,max (1 hr after lights out for zaleplon; 1.5 hr for placebo/zolpidem). Participants were required to turn off the alarm and perform a cognitive test battery twice, separated by a 20–30 min reading break. They then returned to sleep and were awakened to perform the same cognitive tasks at an average of 6.7 hr after drug ingestion.
Results
Relative to placebo, the effects of 10 mg zaleplon and 5 mg zolpidem on cognitive performance were minor. In contrast, 10 mg zolpidem adversely affected cognitive throughput (p < 0.001), psychomotor vigilance (p < 0.001), working memory (p < 0.01), delayed word recall (p < 0.05), and subjective sleepiness (p < 0.01) at the first emergent awakening. At terminal awakening, neither cognitive performance nor subjective sleepiness was impaired after ingestion of zaleplon or zolpidem (5 mg and 10 mg) compared with placebo.
Conclusions
Presleep ingestion of sleep medications, especially 10 mg zolpidem, poses a risk for performance errors after emergent awakenings near the expected PK,max.
Registration
Optimize Astronaut Sleep Medication Efficacy and Individual Effects (clinicaltrials.gov ID NCT03526575).
U.S. internal-medicine residency programs were randomly assigned to standard duty-hour policies or more flexible policies, which maintained the 80-hour workweek limit but did not require limits on ...shift length. Sleep duration and morning sleepiness were similar for interns in standard programs and those in flexible programs.
Biomathematical models of fatigue capture the physiology of sleep/wake regulation and circadian rhythmicity to predict changes in neurobehavioral functioning over time. We used a biomathematical ...model of fatigue linked to the adenosinergic neuromodulator/receptor system in the brain as a framework to predict sleep inertia, that is, the transient neurobehavioral impairment experienced immediately after awakening. Based on evidence of an adenosinergic basis for sleep inertia, we expanded the biomathematical model with novel differential equations to predict the propensity for sleep inertia during sleep and its manifestation after awakening. Using datasets from large laboratory studies of sleep loss and circadian misalignment, we calibrated the model by fitting just two new parameters and then validated the model’s predictions against independent data. The expanded model was found to predict the magnitude and time course of sleep inertia with generally high accuracy. Analysis of the model’s dynamics revealed a bifurcation in the predicted manifestation of sleep inertia in sustained sleep restriction paradigms, which reflects the observed escalation of the magnitude of sleep inertia in scenarios with sleep restriction to less than ∼ 4 h per day. Another emergent property of the model involves a rapid increase in the predicted propensity for sleep inertia in the early part of sleep followed by a gradual decline in the later part of the sleep period, which matches what would be expected based on the adenosinergic regulation of non-rapid eye movement (NREM) sleep and its known influence on sleep inertia. These dynamic behaviors provide confidence in the validity of our approach and underscore the predictive potential of the model. The expanded model provides a useful tool for predicting sleep inertia and managing impairment in 24/7 settings where people may need to perform critical tasks immediately after awakening, such as on-demand operations in safety and security, emergency response, and health care.
Biomathematical models of fatigue can be used to predict neurobehavioral deficits during sleep/wake or work/rest schedules. Current models make predictions for objective performance deficits and/or ...subjective sleepiness, but known differences in the temporal dynamics of objective versus subjective outcomes have not been addressed. We expanded a biomathematical model of fatigue previously developed to predict objective performance deficits as measured on the Psychomotor Vigilance Test (PVT) to also predict subjective sleepiness as self-reported on the Karolinska Sleepiness Scale (KSS). Four model parameters were re-estimated to capture the distinct dynamics of the KSS and account for the scale difference between KSS and PVT. Two separate ensembles of datasets – drawn from laboratory studies of sleep deprivation, sleep restriction, simulated night work, napping, and recovery sleep – were used for calibration and subsequent validation of the model for subjective sleepiness. The expanded model was found to exhibit high prediction accuracy for subjective sleepiness, while retaining high prediction accuracy for objective performance deficits. Application of the validated model to an example scenario based on cargo aviation operations revealed divergence between predictions for objective and subjective outcomes, with subjective sleepiness substantially underestimating accumulating objective impairment, which has important real-world implications. In safety-sensitive operations such as commercial aviation, where self-ratings of sleepiness are used as part of fatigue risk management, the systematic differences in the temporal dynamics of objective versus subjective measures of functional impairment point to a potentially significant risk evaluation sensitivity gap. The expanded biomathematical model of fatigue presented here provides a useful quantitative tool to bridge this previously unrecognized gap.
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