Effects of sleep deprivation on cognitive and physical performance in university students

Abstract

using paired two-tailed T tests and MANOVA. Reaction time and systolic blood pressure post-exercise were significantly increased following sleep deprivation (mean ± SD change: reaction time: 0.15 ± 0.04 s, p = 0.003; systolic BP: 6 ± 17 mmHg, p = 0.012). No significant differences were found in other variables. Reaction time and vascular response to exercise were significantly affected by sleep deprivation in university students, whilst other cognitive and cardiopulmonary measures showed no significant changes. These findings indicate that acute sleep deprivation can have an impact on physical but not cognitive ability in young healthy university students. Further research is needed to identify mechanisms of change and the impact of longer term sleep deprivation in this population.

Sixteen weeks of aerobic training influence spirometry, s-klotho, and hemodynamic responses to sub-maximal exercise testing in obese men with severe obstructive sleep apnea

“…Klotho is an enzyme that in humans is encoded by the KL gene. 1 S-klotho is a type I membrane protein first documented in 1997. 2 The protein is associated with the degenerative process, acceleration and/or deceleration of aging, bone lose, and alcohol consumption.…”

The degree of radiation-induced DNA strand breaks is altered by acute sleep deprivation and psychological stress and is associated with cognitive performance in humans

“…Furthermore, an individual's level of radiosensitivity predicted his/her subsequent cognitive performance. Given that the consequences of sleep deprivation have been investigated in diverse human cohorts, including firefighters [93], astronauts [94,95], nurses [96], students [97], and physicians [98], it is critical to identify molecular biomarkers to predict individual vulnerability to sleep deprivation and develop effective countermeasures.…”

Correlates of Cognitive Load in Surrogate Decision Makers of the Critically III

“…Also, the constructed regression models explained only 26% of the observed variance in intrinsic and extraneous cognitive load. To improve upon this limitation, more work is needed to understand the precursors of cognitive load within SDMs of the critically ill. For example, other feasible predictors that could explain cognitive load, which were not included in this study could be the SDMs’ education level or symptoms of physical fatigue—concepts that are established predictors of working memory (Patrick et al, 2017; Souza-Talarico, Caramelli, Nitrini, & Chaves, 2007).…”