View clinical trials related to Sleep Deprivation.
Filter by:Sleep deprivation (SD) has a powerful degrading effect on cognitive performance, particularly psychomotor vigilance (PV) and reaction time. Caffeine is well known to be an effective countermeasure to the effects of SD. However, individuals differ in both their response to SD and to the administration of caffeine. This has made it difficult to provide individualized recommendations regarding the use of caffeine to sustain alertness when needed. For the past two decades, the Army's Biotechnology HPC Institute (BHSAI), in collaboration with the Walter Reed Army Institute of Research, have been developing statistical models to predict individual performance during prolonged SD. Recently, this resulted in the publication of the 2B-Alert app, a computer algorithm based on large datasets that can learn an individual's response to SD by combining actigraphic sleep data with simultaneously acquired PV performance data. The 2B-Alert algorithm can predict an individual's sleep need and performance after ~2 weeks of training the model. Recently, the model has been extended to incorporate individualized responses to caffeine. This was recently validated in a retrospective study published by BHSAI in 2019. The present study is designed to test the predictive capacity of the 2B-Alert app in real time. During Phase 1 a total of 21 healthy participants will wear an actigraph & complete multiple daily PV tests on a personal cell phone. After 2 weeks, these individuals will attend Phase 2 involving an in-laboratory stay & SD. Participants will have an 8-hour period of sleep in the laboratory, followed by 62 hours of continuous wakefulness. During these 62 hours, participants will complete PV and mood testing every 3 hours. The 2B-Alert app will be used to predict individual caffeine need to sustain performance at near-baseline levels based on the statistical model. At 44 hours SD, participants will undergo a 6-hour "alertness window" where they may receive individualized doses of caffeine based on the recommendations of the model. After 62 hours of SD, Phase 3 begins, involving a night of monitored recovery sleep and additional sessions of PV and mood testing until release from the study at 6 pm on the final day. It is hypothesized that the 2B-Alert app will be effective at providing caffeine dosing recommendations that return PV and mood performance to normal levels during the alertness window.
Previous studies showed that insufficient sleep has a negative impact on children's physical and psychological health. Napping was found to decrease sleepiness and improve daytime functioning in adults and adolescents. The effects of napping on children, however, is unknown. The current study aims to test the effects of short daytime classroom naps on daytime functioning and behaviour in elementary school children.
The investigators proposed that pain, agitation, delirium and sleep deprivation protocol (PADS) will help improve the patients' outcomes (shortening ICU length of stay, improving ventilator free days, increasing delirium free days) in critically ill patients, a university hospital, Thailand.
This study is designed to assess neurobehavioral performance, as well as genetic and other physiological changes associated with variations in timing and quantity of sleep.
This within-subject experiment uses one night of acute sleep restriction (4h) vs normal sleep (8h) to study state-dependent changes in olfactory processing. Odor-evoked blood oxygen level dependent (BOLD) responses will be measured in olfactory brain regions using functional magnetic resonance imaging (fMRI). Food intake will be measured at a buffet.
The overall aim of Dr. Levenson's research proposal is to test the acceptability, feasibility, and preliminary outcomes of a sleep promotion program delivered to 13-15 year olds who report insufficient sleep. Dr. Levenson will examine the feasibility and acceptability of the program through a randomized pilot trial (n=40) that uses a two-period, wait-list control design. Then, Dr. Levenson will test whether the program is associated with changes in sleep, motivation, and four outcome domains: academic functioning, attention, risk behavior, and affect. Such a broadly relevant program has the potential for enormous public health impact by improving sleep and facilitating healthy development across a range of domains among typically-developing adolescents who are highly vulnerable to adverse consequences.
This study evaluates the acceptability, feasibility, and efficacy of an intervention using wearable sensors and a mHealth application, SOmNI, to promote sleep for adolescents. The investigators hypothesize that a behavioural intervention delivered through a mobile app will be a cost-effective and accessible method of engaging adolescents in the self-management of sleep behaviours. Participants will be randomized to either the SOmNI Intervention group or the Control group. Participants receiving the SOmNI app will attempt to incrementally move their school night bedtime earlier in the evening.
A quasi-experimental design where internal medicine residents in a high complexity hospital were assessed after a 24-hour shift for cognitive impairment by a trained neurologist.
Investigators will enroll up to 20 participants from 3 Children's Hospital of Philadelphia (CHOP) primary care locations. The primary objective is to determine the whether the Sleep Well! behavioral sleep intervention is feasible to be implemented in primary care offices and acceptable to families. The direction and magnitude of change in child sleep from pre-intervention to post-intervention will also be examined.
The study is a case-controlled observational trial. Forty patients will be divided into 2 groups (good or poor sleepers) depending on their first postoperative night Bispectral index data. Firstly, this study aims to characterise the lung microbiota in patients treated with thyroid surgery. Secondly, it aims to evaluate microbiota and its influence on plasma kynurenine.