Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness, Circadian Phase, Hours since Awakening, and Accumulated Sleep Loss
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...
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description | 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. |
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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><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0151770</identifier><identifier>PMID: 27019198</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Adult ; Adults ; Alertness ; Algorithms ; Analysis ; Attention (Psychology) ; Attention - physiology ; Biology and Life Sciences ; Caffeine ; Circadian rhythm ; Circadian Rhythm - physiology ; Circadian rhythms ; Cognition ; Cognition & reasoning ; Cognition - physiology ; Cognitive ability ; Cognitive tasks ; Fatigue ; Female ; Health aspects ; Hospitals ; Humans ; Male ; Mathematical models ; Medicine and Health Sciences ; Melatonin ; Models, Theoretical ; Performance prediction ; Physical Sciences ; Psychomotor performance ; Psychomotor Performance - physiology ; Research and Analysis Methods ; Self Report ; Sleep ; Sleep and wakefulness ; Sleep deprivation ; Sleep Deprivation - physiopathology ; Social Sciences ; Studies ; Urine ; Vigilance ; Wakefulness ; Wakefulness - physiology ; Womens health ; Young Adult ; Young adults</subject><ispartof>PloS one, 2016-03, Vol.11 (3), p.e0151770-e0151770</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Bermudez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2016 Bermudez et al 2016 Bermudez et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-60c352bc2e7453f17df0171cf9c081c64cb11898a92dfe7ad22a9b932e07df533</citedby><cites>FETCH-LOGICAL-c692t-60c352bc2e7453f17df0171cf9c081c64cb11898a92dfe7ad22a9b932e07df533</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4809494/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4809494/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27019198$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Vyazovskiy, Vladyslav</contributor><creatorcontrib>Bermudez, Eduardo B</creatorcontrib><creatorcontrib>Klerman, Elizabeth B</creatorcontrib><creatorcontrib>Czeisler, Charles A</creatorcontrib><creatorcontrib>Cohen, Daniel A</creatorcontrib><creatorcontrib>Wyatt, James K</creatorcontrib><creatorcontrib>Phillips, Andrew J K</creatorcontrib><title>Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness, Circadian Phase, Hours since Awakening, and Accumulated Sleep Loss</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Sleep restriction causes impaired cognitive performance that can result in adverse consequences in many occupational settings. 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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. 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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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27019198</pmid><doi>10.1371/journal.pone.0151770</doi><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Adults Alertness Algorithms Analysis Attention (Psychology) Attention - physiology Biology and Life Sciences Caffeine Circadian rhythm Circadian Rhythm - physiology Circadian rhythms Cognition Cognition & reasoning Cognition - physiology Cognitive ability Cognitive tasks Fatigue Female Health aspects Hospitals Humans Male Mathematical models Medicine and Health Sciences Melatonin Models, Theoretical Performance prediction Physical Sciences Psychomotor performance Psychomotor Performance - physiology Research and Analysis Methods Self Report Sleep Sleep and wakefulness Sleep deprivation Sleep Deprivation - physiopathology Social Sciences Studies Urine Vigilance Wakefulness Wakefulness - physiology Womens health Young Adult Young adults |
title | Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness, Circadian Phase, Hours since Awakening, and Accumulated Sleep Loss |
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