118 Relationships Between Perceptions of Subjective States Differ by Sleep Loss and During Recovery in Healthy Adults

Abstract Introduction The Karolinska Sleepiness Scale (KSS) and the Profile of Mood States Fatigue and Vigor subscales (POMS-F and POMS-V) are commonly used to assess subjective sleepiness, fatigue and vigor in response to sleep loss. However, the detailed time course of relationships between these measures across sleep loss and recovery remains unknown yet is critical for assessing varying changes in perception of subjective states. Repeated measures correlation (rmcorr) examined within-individual association between the measures throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (ages 21-49; mean±SD, 33.9±8.9y; 18 females) participated in a 13-night experiment consisting of two baseline nights (10h-12h time-in-bed, TIB) followed by 5 sleep restriction (SR) nights (4h TIB), 4 recovery nights (12h TIB), and 36h total sleep deprivation (TSD). A neurobehavioral test battery, including the KSS, POMS-F, and POMS-V, was administered every 2h during wakefulness. Rmcorr compared KSS, POMS-F, and POMS-V scores by examining correlations by study day (e.g., Baseline day 2) and by time point (e.g., 1000h-2000h). Rmcorr cutoffs were as follows: r=0.1:small, 0.3:moderate, 0.5:large. Results KSS and POMS-F maintained positive correlations throughout the study, whereas POMS-F and POMS-V and KSS and POMS-V were inversely correlated. All correlations were significant except those for POMS-F and POMS-V across recovery day 1 and KSS and POMS-F across recovery day 4. All measure pairs showed moderate to large correlations across baseline and SR1-5, but only small to moderate correlations across recovery. KSS and POMS-F and KSS and POMS-V showed moderate to large correlations across TSD; however, POMS-F and POMS-V only showed a small correlation. All three pairs showed consistent moderate (POMS-F and POMS-V) or large (KSS and POMS-F, KSS and POMS-V [moderate at 2000h]) correlations when analyzed by time point across the study. Conclusion Overall, the strength of relationships between KSS, POMS-F, and POMS-V scores varied as a function of type of sleep loss (SR or TSD) and by fully rested states, but not by time of day. This demonstrates the importance of determining perceptions of sleepiness, fatigue, and vigor in relation to each other, especially during recovery for all three constructs. Support (if any) ONR Award No. N00014-11-1-0361; NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488

Download Full-text

119 Behavioral Attention and Sleepiness Display Robust Stable Relationships Across Sleep Loss but not Across Recovery

SLEEP ◽

10.1093/sleep/zsab072.118 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A48-A49

Author(s):

Namni Goel ◽

Courtney Casale ◽

Tess Brieva ◽

Caroline Antler ◽

Erika Yamazaki

Keyword(s):

Sleep Deprivation ◽

Repeated Measures ◽

Time Course ◽

Response Speed ◽

Sleep Loss ◽

Psychomotor Vigilance Test ◽

Stable Relationship ◽

Time In Bed ◽

Subjective Sleepiness ◽

Time Point

Abstract Introduction The 10-minute and 3-minute versions of the Psychomotor Vigilance Test (PVT10 and PVT3) and the Karolinska Sleepiness Scale (KSS) are commonly used to assess objective behavioral attention deficits and subjective sleepiness in response to sleep loss, respectively. However, the precise time course of relationships between behavioral attention and subjective sleepiness across sleep loss and recovery remains unknown but is critical for determining whether objective and subjective measures track each other. Repeated measures correlation (rmcorr) examined within-individual association between these measures throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (ages 21-49;mean±SD, 33.9±8.9y;18 females) participated in a 13-night experiment consisting of two baseline nights (10h-12h time-in-bed, TIB) followed by 5 sleep restriction (SR) nights (4h TIB), 4 recovery nights (12h TIB), and 36h total sleep deprivation (TSD). A neurobehavioral test battery, including the PVT10, PVT3, and KSS, was administered every 2h during wakefulness. Rmcorr compared PVT10 [lapses (reaction time [RT] >500ms) and 1/RT (response speed)], PVT3 (lapses [RT>355ms], 1/RT), and KSS scores by examining correlations by day (e.g., Baseline day 2) and time point (e.g., 1000h-2000h). Rmcorr ranges: r=0.1:small; r=0.3:moderate; r=0.5:large. Results Generally, the correlations between the PVT10 and KSS and the PVT3 and KSS showed a similar pattern for lapses and 1/RT. PVT lapses and KSS scores showed small or non-significant correlations during baseline and recovery, whereas SR and TSD showed moderate correlations. PVT 1/RT and KSS scores showed moderate correlations during baseline, moderate to large correlations during SR and TSD, but small correlations during recovery. PVT10 and PVT3 1/RT showed stronger correlations with KSS scores than lapses. Additionally, all relationships showed moderate to large correlations by time point across the study. Conclusion Overall, the relationship between behavioral attention and sleepiness was stronger across sleep loss (SR or TSD) relative to fully rested states while it was consistently relatively strong at specific times of day throughout the study. In contrast to published literature, there is a remarkably stable relationship between an individual’s objective behavioral attention performance and perceptions of sleepiness during sleep loss, which is not evident during recovery or at baseline. Support (if any) ONR Award No. N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488

Download Full-text

127 Cognitive Throughput, Behavioral Attention, and Sleepiness Show Robust Relationships During Sleep Loss but Not During Recovery

SLEEP ◽

10.1093/sleep/zsab072.126 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A52-A52

Author(s):

Tess Brieva ◽

Caroline Antler ◽

Erika Yamazaki ◽

Courtney Casale ◽

Namni Goel

Keyword(s):

Sleep Deprivation ◽

Repeated Measures ◽

Time Course ◽

Response Speed ◽

Sleep Loss ◽

Entire Study ◽

Psychomotor Vigilance Test ◽

Time In Bed ◽

Symbol Substitution ◽

Time Point

Abstract Introduction The Digit Symbol Substitution Task (DSST) is a frequently used measure to determine cognitive throughput responses to sleep loss. However, the specific time course of relationships between cognitive throughput and behavioral attention [using the 10-minute Psychomotor Vigilance Test (PVT10)] and subjective sleepiness [using the Karolinska Sleepiness Scale (KSS)] across sleep loss and recovery remains unknown yet is critical for assessing whether tasks involving learning and those without learning track each other. Repeated measures correlation (rmcorr) examined within-individual associations between measures of these tests throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (ages 21-49;mean ± SD, 33.9 ± 8.9y;18 females) participated in a 13-night experiment consisting of two baseline nights (10h-12h time in bed, TIB) followed by 5 sleep restriction (SR) nights (4h TIB), 4 recovery nights (12h TIB), and 36h total sleep deprivation (TSD). A neurobehavioral test battery, including the DSST, the KSS, and the PVT10, was administered every 2h during wakefulness. Rmcorr analyses compared DSST [number correct], KSS score, and PVT10 performance [lapses (reaction time [RT] >500ms) and 1/RT (response speed)] by examining correlations by day (e.g., Baseline day 2) and by time point (e.g., 1000h-2000h). Rmcorr ranges were as follows: r=0.1: small; r=0.3: moderate; r=0.5: large. Results During SR and TSD, correlations were significant, ranging from moderate to large, with the strongest correlation occurring during TSD. By contrast, baseline and recovery correlations were not significant or were small for DSST relative to PVT10 lapses, PVT10 response speed, or KSS scores. Additionally, all three pairs showed moderate to large correlations by time point across the entire study. Conclusion The various test measure relationships were consistently strong at specific times of day throughout the study. In addition, the associations between cognitive throughput and behavioral attention and sleepiness were strongest during sleep loss, particularly during TSD, suggesting that these measures are most acutely attuned to neurobehavioral changes resulting from sleep loss. The lack of a significant relationship at baseline and at recovery may be due to the learning effect reported for the DSST that is not present for the PVT10 or KSS. Support (if any) ONR Award No. N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488

Download Full-text

122 Different Duration Psychomotor Vigilance Tests Show Robust Stable Relationships Across Sleep Loss That Deteriorate in Recovery

SLEEP ◽

10.1093/sleep/zsab072.121 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A50-A50

Author(s):

Caroline Antler ◽

Erika Yamazaki ◽

Courtney Casale ◽

Tess Brieva ◽

Namni Goel

Keyword(s):

Sleep Deprivation ◽

Repeated Measures ◽

Response Speed ◽

Sleep Loss ◽

Sleep Restriction ◽

Psychomotor Vigilance Test ◽

Time In Bed ◽

Psychomotor Vigilance ◽

The Relationship ◽

Time Point

Abstract Introduction The Psychomotor Vigilance Test (PVT), a behavioral attention measure widely used to capture sleep loss deficits, is available in 10-minute (PVT10) and 3-minute (PVT3) versions. The PVT3 is a briefer and presumably comparable assessment to the more commonly used PVT10 yet the relationship between the measures from the two versions across specific time points and in recovery after sleep loss has not been investigated. Repeated measures correlation (rmcorr) evaluated within-individual associations between measures on the PVT10 and PVT3 throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (ages 21-49; mean±SD, 33.9±8.9y; 18 females) participated in a 13-night experiment consisting of 2 baseline nights (10h-12h time in bed, TIB) followed by 5 sleep restriction (SR1-5) nights (4h TIB), 4 recovery nights (R1-R4; 12h TIB), and 36h total sleep deprivation (TSD). A neurobehavioral test battery, including the PVT10 and PVT3 was completed every 2h during wakefulness. Rmcorr compared PVT10 and PVT3 lapses (reaction time [RT] >355ms [PVT3] or >500ms [PVT10]) and response speed (1/RT) by examining correlations by day (e.g., baseline day 2) and by time point (e.g., 1000h-2000h). Rmcorr ranges were as follows: 0.1-0.3, small; 0.3-0.5, moderate; 0.5-0.7, large; 0.7-0.9, very large. Results All time point correlations (1000h-2000h) were significant (moderate to large for lapses; large to very large for 1/RT). Lapses demonstrated large correlations during R1, moderate correlations during SR1-SR5 and TSD, and small correlations during R2 and R4, and showed no significant correlations during baseline or R3. 1/RT correlations were large for SR1-SR4 and TSD, moderate for SR5 and R1-R4, and small for baseline. Conclusion The various PVT relationships were consistently strong at specific times of day throughout the study. In addition, higher correlations observed for 1/RT relative to lapses and during SR and TSD relative to baseline and recovery suggest that the PVT10 and PVT3 are most similar and best follow performance when most individuals are experiencing behavioral attention deficits during sleep loss. Both measures track SR and TSD performance well, with 1/RT presenting as more comparable between the PVT10 and PVT3. Support (if any) ONR Award N00014-11-1-0361; NIH UL1TR000003; NASA NNX14AN49G and 80NSSC20K0243; NIHR01DK117488

Download Full-text

121 Behavioral Attention Relationships Vary Between Demographic Groups Across Sleep Loss and Recovery

SLEEP ◽

10.1093/sleep/zsab072.120 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A49-A50

Author(s):

Caroline Antler ◽

Erika Yamazaki ◽

Tess Brieva ◽

Courtney Casale ◽

Namni Goel

Keyword(s):

Sleep Deprivation ◽

Repeated Measures ◽

Age Groups ◽

Response Speed ◽

Sleep Loss ◽

Demographic Groups ◽

Time In Bed ◽

Median Split ◽

The Relationship ◽

High Bmi

Abstract Introduction The Psychomotor Vigilance Test (PVT) is a behavioral attention measure widely used to describe sleep loss deficits. Although there are reported differences in PVT performance for various demographic groups, no study has examined the relationship between measures on the 10-minute PVT (PVT10) and the 3-minute PVT (PVT3) within sex, age, and body mass index (BMI) groups throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (mean±SD ages, 33.9±8.9y) participated in a 13-night experiment [2 baseline nights (10h-12h time in bed, TIB) followed by 5 sleep restriction (SR1-5) nights (4h TIB), 4 recovery nights (R1-R4; 12h TIB), and 36h total sleep deprivation (TSD)]. A neurobehavioral test battery, including the PVT10 and PVT3 was completed every 2h during wakefulness. Repeated measures correlation (rmcorr) compared PVT10 and PVT3 lapses (reaction time [RT] >355ms [PVT3] and >500ms [PVT10]) and response speed (1/RT) by examining correlations by day (e.g., baseline day 2) and time point (e.g., 1000h-2000h) within sex groups (18 females), within age groups defined by a median split (median=32, range=21-49y), and within BMI groups defined by a median split (median=25, range=17-31). Results PVT10 and PVT3 1/RT was significantly correlated at all study days and time points excluding at baseline for the younger group and at R2 for the higher BMI group. PVT10 and PVT3 lapses showed overall lower correlations across the study relative to 1/RT. Lapses were not significantly correlated at baseline for any group, for males across recovery (R1-R4), for the high BMI group at R2-R4, for the older group at R2-R3, or for the younger group at SR5 or R3. Conclusion Differentiating participants based on age, sex, or BMI revealed important variation in the relationship between PVT10 and PVT3 measures across the study. Surprisingly, lapses were not significantly correlated at baseline for any demographic group or across recovery for males or the high BMI or older group. Thus, PVT10 and PVT3 lapses may be less comparable in certain populations when well-rested. These findings add to a growing literature suggesting demographic factors may be important factors to consider when evaluating the effects of sleep loss. Support (if any) ONR Award N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243; NIHR01DK117488

Download Full-text

Residual, differential neurobehavioral deficits linger after multiple recovery nights following chronic sleep restriction or acute total sleep deprivation

SLEEP ◽

10.1093/sleep/zsaa224 ◽

2020 ◽

Author(s):

Erika M Yamazaki ◽

Caroline A Antler ◽

Charlotte R Lasek ◽

Namni Goel

Keyword(s):

Sleep Deprivation ◽

Response Speed ◽

Sleep Loss ◽

Sleep Restriction ◽

Total Sleep Deprivation ◽

Psychomotor Vigilance Test ◽

Recovery Sleep ◽

Time In Bed ◽

Neurobehavioral Deficits ◽

Chronic Sleep

Abstract Study Objectives The amount of recovery sleep needed to fully restore well-established neurobehavioral deficits from sleep loss remains unknown, as does whether the recovery pattern differs across measures after total sleep deprivation (TSD) and chronic sleep restriction (SR). Methods In total, 83 adults received two baseline nights (10–12-hour time in bed [TIB]) followed by five 4-hour TIB SR nights or 36-hour TSD and four recovery nights (R1–R4; 12-hour TIB). Neurobehavioral tests were completed every 2 hours during wakefulness and a Maintenance of Wakefulness Test measured physiological sleepiness. Polysomnography was collected on B2, R1, and R4 nights. Results TSD and SR produced significant deficits in cognitive performance, increases in self-reported sleepiness and fatigue, decreases in vigor, and increases in physiological sleepiness. Neurobehavioral recovery from SR occurred after R1 and was maintained for all measures except Psychomotor Vigilance Test (PVT) lapses and response speed, which failed to completely recover. Neurobehavioral recovery from TSD occurred after R1 and was maintained for all cognitive and self-reported measures, except for vigor. After TSD and SR, R1 recovery sleep was longer and of higher efficiency and better quality than R4 recovery sleep. Conclusions PVT impairments from SR failed to reverse completely; by contrast, vigor did not recover after TSD; all other deficits were reversed after sleep loss. These results suggest that TSD and SR induce sustained, differential biological, physiological, and/or neural changes, which remarkably are not reversed with chronic, long-duration recovery sleep. Our findings have critical implications for the population at large and for military and health professionals.

Download Full-text

0312 Performance on a Cognitive Interference Task in Children After One-Night of Sleep Restriction

SLEEP ◽

10.1093/sleep/zsaa056.309 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A117-A118

Author(s):

G de Queiroz Campos ◽

D P Dickstein ◽

M A Carskadon ◽

J M Saletin

Keyword(s):

Repeated Measures ◽

Sleep Loss ◽

Sleep Restriction ◽

Adhd Symptoms ◽

Cognitive Interference ◽

Interference Task ◽

Attentional Processes ◽

Short Sleep ◽

Time In Bed ◽

Fmri Session

Abstract Introduction Short sleep contributes to attention failure in conditions such as ADHD. Whether sleep loss affects attentional processes as a task varies in cognitive interference is unclear. We used a multi-source interference task (MSIT) in a sleep restriction paradigm in children with a range of ADHD symptoms to examine how short sleep disrupts attention in these youth. Methods Thirteen children (7F, 11.7±1.28 years) with a range of ADHD symptom severity completed a repeated-measures experiment on two consecutive nights in the laboratory: baseline (BSLN; 9.5h time-in-bed) and sleep restriction (SR; 4h time-in-bed). Each morning they took part in an fMRI session including the MSIT, in which participants respond to a series of 3-digit numbers by indicating which digit is different on no-interference (e.g., 003; correct=3) or interference (e.g., 311, correct=3) trials. Performance measures were inverse reaction time (1/RT) and accuracy. A two-way within-subject ANOVA assessed performance across interference and sleep conditions respectively. Results 1/RT showed main-effects of sleep loss (BSLN vs. SR; F(1,148)=4.01;p<0.05;η 2=0.026) and trial type (no-interference vs. interference; F(1,148)=24.7;p<0.001;η 2=0.143). Responses were slower for interference (BSLN RT: 799.3ms, SR RT: 895.8ms) than no-interference (BSLN RT: 653.2ms, SR RT: 697.4ms) trials. No interaction between interference and sleep loss was found (F(1,148)=0.11;p>0.05;η 2=0.001). Likewise, accuracy was lower (F(1,148) = 31.1, p<.001;η 2=0.174) in interference trials (73.5%) than in no-interference trials (92.2%), however with no effect of sleep loss, nor an interaction of interference and sleep loss (all p’s > .05). Conclusion These data provide evidence that partial sleep loss disrupts attention processes in children, yet these differences do not appear to depend on cognitive interference in our sample. Future analyses will examine whether ADHD symptoms distinguish individual differences, as well as analyze fMRI data to probe neural processes underlying attention control. Support K01MH09854 (to JMS); Brown University UTRA (to GDQC).

Download Full-text

115 Age and Sex Differences in Behavioral Attention Across Baseline, Sleep Loss, and Recovery

SLEEP ◽

10.1093/sleep/zsab072.114 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A47-A47

Author(s):

Erika Yamazaki ◽

Courtney Casale ◽

Tess Brieva ◽

Caroline Antler ◽

Namni Goel

Keyword(s):

Individual Differences ◽

Repeated Measures ◽

Response Speed ◽

Sleep Loss ◽

Group Differences ◽

Significant Time ◽

Psychomotor Vigilance Test ◽

Time In Bed ◽

Performance Differences ◽

Age And Sex

Abstract Introduction There are established individual differences in performance resulting from sleep loss. However, differences in behavioral attention performance between demographic subgroups remain unclear, especially during recovery after sleep loss. Thus, we examined demographic subgroup performance differences during baseline, sleep loss (sleep restriction [SR] and total sleep deprivation [TSD]), and recovery (R). Methods Forty-one healthy adults participated in a 13-night experiment (2 baseline nights [10h-12h time-in-bed, TIB], 5 SR nights [4h TIB], 4 recovery nights [12h TIB], and 36h TSD). The 10-minute Psychomotor Vigilance Test (PVT), measuring behavioral attention, was administered every 2h during wakefulness. PVT lapses (reaction time [RT]>500ms) and 1/RT (response speed) were measured. PVT performance differences were investigated by sex (18 females) and by median split on age (range: 21-49y; median: 32y). Repeated measures ANOVAs on each study day examined PVT performance with demographic groups as the between-subject factor. Results SR1-2 and R1-2 showed significant between-subject effects by age: the older group had faster mean 1/RT than the younger group. SR2 showed a significant time*age group interaction: the older group had faster 1/RT from 0800h-1400h. B2, SR1, and R1 showed significant between-subject effects by sex: males had faster mean 1/RT than females. SR3 showed a significant time*sex interaction: males had faster 1/RT at 0800h and 1200h. PVT lapses (log transformed) analyses by age and by sex revealed significant between-subject effects at SR1 and R1. The direction of effects for lapses paralleled those for 1/RT: the younger group and females had more lapses than the older group and males, respectively. No other study days showed significant between-subjects or interaction effects. Conclusion For both age and sex, significant between-subject effects and/or interactions were revealed only in the beginning half of SR or recovery and not during TSD. These findings suggest that group differences exist when the effects of sleep loss are mild (i.e., SR1-3) or when the post-effects of sleep loss have diminished (i.e., R3-4); however, when the effects of sleep loss become more severe (i.e., SR4-5 or after a night of TSD), the well-established individual differences in response to sleep loss may overwhelm group differences. Support (if any) ONR Award No.N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488

Download Full-text

0302 One Week of Recovery Sleep is Insufficient to Restore Sustained Attention Performance Following Three Weeks of Chronic Sleep Restriction

SLEEP ◽

10.1093/sleep/zsaa056.299 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A114-A114

Author(s):

R K Yuan ◽

K Zitting ◽

N Vujovic ◽

W Wang ◽

O Buxton ◽

...

Keyword(s):

Sustained Attention ◽

Time Course ◽

Reaction Times ◽

Healthy Adults ◽

Sleep Restriction ◽

Science Center ◽

Neurobehavioral Performance ◽

Recovery Sleep ◽

Time In Bed ◽

Chronic Sleep

Abstract Introduction Sleep loss negatively impacts many aspects of neurobehavioral performance, including sustained attention and reaction times. However, the time course of recovery from chronic sleep restriction (CSR) is not well understood. To explore this, we assessed the effects of 3 weeks of CSR followed by 1 week of recovery on psychomotor vigilance task (PVT) performance in healthy adults. Methods 8 healthy adults (27–71; 4f) participated in a 37-day inpatient study. The study consisted of 6 baseline (BL) days with 8–16 h time-in-bed, followed by 3 weeks of CSR (5-5.6h time-in-bed at night), and 1 week of recovery (RC; 8-10h time-in-bed). Sustained attention was assessed by 10-minute visual PVTs administered every 2h starting ~5h after wake (~4/day). Linear and generalized linear mixed models were used to compare average reaction times (RT) and number of lapses, respectively, from the last 3 days of baseline, CSR, and recovery. Results Average RT was almost twice as long at the end of CSR compared to baseline (p<0.0001). Moreover, it remained significantly slower than baseline by roughly 173ms, even after 1 week of recovery (p<0.0001). Similarly, there was a threefold increase in the number of lapses at the end of CSR compared to baseline (p<0.0001) which remained elevated after one week of recovery (p<0.0001). Conclusion One week of recovery sleep of 8-10 h/night following 3 weeks of chronic sleep restriction was insufficient for full recovery of sustained attention as assessed by PVT reaction time and number of lapses. This suggests that chronic sleep restriction has consequences on neurobehavioral performance that do not fully dissipate within one week. Support Study supported by P01AG009975 and conducted in the Brigham and Women’s Hospital Center for Clinical Investigation, part of Harvard Clinical and Translational Science Center supported by UL1TR001102. KMZ supported by a fellowship from the Finnish Cultural Foundation. RKY supported by T32HL007901 and F32HL143893. NV supported by T32HL007901 and F32AG051325.

Download Full-text

O039 Differential effects of sleep deprivation and sleep restriction on error awareness

SLEEP Advances ◽

10.1093/sleepadvances/zpab014.038 ◽

2021 ◽

Vol 2 (Supplement_1) ◽

pp. A17-A17

Author(s):

J Boardman ◽

M Bravo ◽

T Andrillon ◽

C Anderson ◽

S Drummond

Keyword(s):

Sleep Deprivation ◽

Real Time ◽

Error Rate ◽

Sleep Loss ◽

Healthy Adults ◽

Sleep Restriction ◽

Button Press ◽

Safety Critical ◽

Error Awareness ◽

Occupational Settings

Abstract Introduction The ability to detect and subsequently correct errors is important in preventing the detrimental consequences of sleep loss. We report the first study to compare the effects of total sleep deprivation (TSD) and sleep restriction (SR) on error awareness. Methods Thirteen healthy adults (11F, age=26.8±3.4y) underwent a 34h TSD protocol, completing the Error Awareness Task (EAT: a combined Stroop/1-back/GoNogo task) at 4h and 27h post-wake. Twenty healthy adults (11F, age=27.4±5.3y) were studied both well-rested (WR: 9h sleep) and following SR (3 nights of 3h sleep), completing the EAT once/day (8-9h post-habitual wake). The EAT required participants to withhold responding to “nogo” stimuli and signal, via a button press, whenever they realised they made an error on these nogo trials. Results TSD did not significantly affect error rate (p=.712) or error awareness rate (p=.517), however, participants were slower to recognise errors after TSD (p=.004). In contrast, SR increased error rate (p<.001), decreased error awareness (p<.001), and slowed recognition of errors (p<.01). Discussion Three nights SR impaired the ability to recognise errors in real-time, despite a greater number of errors being made. Thus, impaired error awareness may be one mechanism underlying increased sleep loss-related accidents and errors in occupational settings, as well as at home. Interestingly, 1-night TSD did not lead to more, or impaired recognition of errors. TSD participants were slower to recognise errors, which may be problematic in safety critical settings. Technological and/or operational solutions may be needed to reduce the risk of errors going unrecognised.

Download Full-text

Robust stability of trait-like vulnerability or resilience to common types of sleep deprivation in a large sample of adults

SLEEP ◽

10.1093/sleep/zsz292 ◽

2019 ◽

Vol 43 (6) ◽

Cited By ~ 2

Author(s):

Erika M Yamazaki ◽

Namni Goel

Keyword(s):

Sleep Deprivation ◽

Intraclass Correlation ◽

Correlation Coefficients ◽

Sleep Loss ◽

Demographic Variables ◽

Large Individual ◽

Intraclass Correlation Coefficients ◽

Time In Bed ◽

First Time ◽

Chronic Sleep

Abstract Study Objectives Sleep loss produces large individual differences in neurobehavioral responses, with marked vulnerability or resilience among individuals. Such differences are stable with repeated exposures to acute total sleep deprivation (TSD) or chronic sleep restriction (SR) within short (weeks) and long (years) intervals. Whether trait-like responses are observed to commonly experienced types of sleep loss and across various demographically defined groups remains unknown. Methods Eighty-three adults completed two baseline nights (10 h–12 h time-in-bed, TIB) followed by five 4 h TIB SR nights or 36 h TSD. Participants then received four 12-h TIB recovery nights followed by five SR nights or 36 h TSD, in counterbalanced order to the first sleep loss sequence. Neurobehavioral tests were completed every 2 h during wakefulness. Results Participants who displayed neurobehavioral vulnerability to TSD displayed vulnerability to SR, evidenced by substantial to near perfect intraclass correlation coefficients (ICCs; 78%–91% across measures). Sex, race, age, body mass index (BMI), season, and sleep loss order did not impact ICCs significantly. Individuals exhibited significant consistency of responses within, but not between, performance and self-reported domains. Conclusions Using the largest, most diverse sample to date, we demonstrate for the first time the remarkable stability of phenotypic neurobehavioral responses to commonly experienced sleep loss types, across demographic variables and different performance and self-reported measures. Since sex, race, age, BMI, and season did not affect ICCs, these variables are not useful for determining stability of responses to sleep loss, underscoring the criticality of biological predictors. Our findings inform mathematical models and are relevant for the general population and military and health professions.

Download Full-text