Publication:
Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness, Circadian Phase, Hours since Awakening, and Accumulated Sleep Loss

Thumbnail Image

Open/View Files

Date

2016

Journal Title

Journal ISSN

Volume Title

Publisher

Public Library of Science
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Bermudez, Eduardo B., Elizabeth B. Klerman, Charles A. Czeisler, Daniel A. Cohen, James K. Wyatt, and Andrew J. K. Phillips. 2016. “Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness, Circadian Phase, Hours since Awakening, and Accumulated Sleep Loss.” PLoS ONE 11 (3): e0151770. doi:10.1371/journal.pone.0151770. http://dx.doi.org/10.1371/journal.pone.0151770.

Research Data

Abstract

Sleep restriction causes impaired cognitive performance that can result in adverse consequences in many occupational settings. Individuals may rely on self-perceived alertness to decide if they are able to adequately perform a task. It is therefore important to determine the relationship between an individual’s self-assessed alertness and their objective performance, and how this relationship depends on circadian phase, hours since awakening, and cumulative lost hours of sleep. Healthy young adults (aged 18–34) completed an inpatient schedule that included forced desynchrony of sleep/wake and circadian rhythms with twelve 42.85-hour “days” and either a 1:2 (n = 8) or 1:3.3 (n = 9) ratio of sleep-opportunity:enforced-wakefulness. We investigated whether subjective alertness (visual analog scale), circadian phase (melatonin), hours since awakening, and cumulative sleep loss could predict objective performance on the Psychomotor Vigilance Task (PVT), an Addition/Calculation Test (ADD) and the Digit Symbol Substitution Test (DSST). Mathematical models that allowed nonlinear interactions between explanatory variables were evaluated using the Akaike Information Criterion (AIC). Subjective alertness was the single best predictor of PVT, ADD, and DSST performance. Subjective alertness alone, however, was not an accurate predictor of PVT performance. The best AIC scores for PVT and DSST were achieved when all explanatory variables were included in the model. The best AIC score for ADD was achieved with circadian phase and subjective alertness variables. We conclude that subjective alertness alone is a weak predictor of objective vigilant or cognitive performance. Predictions can, however, be improved by knowing an individual’s circadian phase, current wake duration, and cumulative sleep loss.

Description

Keywords

Biology and Life Sciences, Physiology, Physiological Processes, Sleep, Medicine and Health Sciences, Chronobiology, Neuroscience, Cognitive Science, Cognitive Neuroscience, Reaction Time, Cognitive Neurology, Cognitive Impairment, Neurology, Cognitive Psychology, Attention, Vigilance (Psychology), Psychology, Social Sciences, Mathematical and Statistical Techniques, Statistical Methods, Forecasting, Physical Sciences, Mathematics, Statistics (Mathematics), Health Care, Patients, Inpatients

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories