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Study objectives: To investigate the effects of sleep restriction (7 nights of 5 h time in bed [TIB]) on cognitive performance, subjective sleepiness, and mood in adolescents. Methods: A parallel-group design was adopted in the Need for Sleep Study. Fifty-six healthy adolescents (25 males, age = 15-19 y) who studied in top high schools and were not habitual short sleepers were randomly assigned to Sleep Restriction (SR) or Control groups. Participants underwent a 2-w protocol consisting of 3 baseline nights (TIB = 9 h), 7 nights of sleep opportunity manipulation (TIB = 5 h for the SR and 9 h for the control groups), and 3 nights of recovery sleep (TIB = 9 h) at a boarding school. A cognitive test battery was administered three times each day. Results: During the manipulation period, the SR group demonstrated incremental deterioration in sustained attention, working memory and executive function, increase in subjective sleepiness, and decrease in positive mood. Subjective sleepiness and sustained attention did not return to baseline levels even after 2 recovery nights. In contrast, the control group maintained baseline levels of cognitive performance, subjective sleepiness, and mood throughout the study. Incremental improvement in speed of processing, as a result of repeated testing and learning, was observed in the control group but was attenuated in the sleep-restricted participants, who, despite two recovery sleep episodes, continued to perform worse than the control participants. Conclusions: A week of partial sleep deprivation impairs a wide range of cognitive functions, subjective alertness, and mood even in high-performing high school adolescents. Some measures do not recover fully even after 2 nights of recovery sleep.
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SLEEP, Vol. 39, No. 3, 2016 687 Sleep and Cognition in Adolescents—Lo et al.
Cognitive Performance, Sleepiness, and Mood in Partially Sleep Deprived
Adolescents: The Need for Sleep Study
June C. Lo, PhD; Ju Lynn Ong, PhD; Ruth L.F. Leong, BSSc; Joshua J. Gooley, PhD; Michael W.L. Chee, MBBS
Centre for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-NUS Medical School, Singapore
Study Objectives: To investigate the effects of sleep restriction (7 nights of 5 h time in bed [TIB]) on cognitive performance, subjective sleepiness, and
mood in adolescents.
Methods: A parallel-group design was adopted in the Need for Sleep Study. Fifty-six healthy adolescents (25 males, age = 15–19 y) who studied in top
high schools and were not habitual shor t sleepers were randomly assigned to Sleep Restriction (SR) or Control groups. Participants underwent a 2-w
protocol consisting of 3 baseline nights (TIB = 9 h), 7 nights of sleep opportunity manipulation (TIB = 5 h for the SR and 9 h for the control groups), and 3
nights of recovery sleep (TIB = 9 h) at a boarding school. A cognitive test battery was administered three times each day.
Results: During the manipulation period, the SR group demonstrated incremental deterioration in sustained attention, working memory and executive
function, increase in subjective sleepiness, and decrease in positive mood. Subjective sleepiness and sustained attention did not return to baseline
levels even after 2 recovery nights. In contrast, the control group maintained baseline levels of cognitive performance, subjective sleepiness, and mood
throughout the study. Incremental improvement in speed of processing, as a result of repeated testing and learning, was observed in the control group but
was attenuated in the sleep-restricted participants, who, despite two recovery sleep episodes, continued to perform worse than the control participants.
Conclusions: A week of partial sleep deprivation impairs a wide range of cognitive functions, subjective alertness, and mood even in high-performing
high school adolescents. Some measures do not recover fully even after 2 nights of recovery sleep.
Commentary: A commentary on this article appears in this issue on page 497.
Keywords: adolescents, cognitive performance, mood, partial sleep deprivation, sleepiness
Citation: Lo JC, Ong JL, Leong RL, Gooley JJ, Chee MW. Cognitive performance, sleepiness, and mood in partially sleep deprived adolescents: the
need for sleep study. SLEEP 2016;39(3):687698.
Sleep curtailment in adolescents is a serious problem in many
so c ieties, bu t in s u f c ient actio n is be i ng ta ken to stem th i s tide.
Approximately 75% of adolescents in the US1 and more than
90% in Korea2 and Japan3 sleep less than the recommended
8–10 h a night.4 Previously, the maturational delay in bed-
time combined with early morning school were the principal
reasons for shortened sleep in adolescence.5 In recent years,
increased electronic media use, higher homework load, and
reduced parental control have contributed to further sleep cur-
tailment in this age group.6 In highly competitive societies in
East Asia where voluntary sleep curtailment is most prevalent,
there is widespread belief that greater effort and more time
spent studying, perhaps at the expense of sleep, is mandatory
for acceptable academic performance.7 This viewpoint is sus-
tained by the higher scores achieved on standardized tests by
students from East Asian countries8 who, on average, sleep 1
to 2 h less than their European9,10 or Australian10 counterparts.
Although three decades of observational and experimental
studies on sleep curtailment in adolescents have provided
clear evidence for increased daytime sleepiness, the case for
objective cognitive performance degradation following par-
tial sleep deprivation has been less compelling,6 ,11 prompting
the current study.
pii: sp- 00462-15 /10.5665/sleep.5552
Some of the world’s most sleep deprived students live in East Asia where students excel in standardized academic tests. This might reinforce the notion
that ‘mind over matter’ can overcome negative effects of chronic sleep restriction. We found that in adolescents, partial sleep deprivation of comparable
duration and severity to that examined in studies on young healthy adults elicited equivalent or greater neurobehavioral decits across several cognitive
domains. Residual effects on sustained attention, speed of processing, and subjective alertness can still be observed even after 2 nights of recovery
sleep. That even students from top high schools are susceptible to neurobehavioral decits should cause policymakers and parents to reconsider if sleep
should continue to be sacriced for the sake of academic achievement.
Effects of Partial Sleep Deprivation on Subjective Sleepiness
and Mood
Sleep restricted adolescents have been consistently found to
be more sleepy. Results of observational studies have revealed
shorter sleep duration to be associated with higher levels of
subjective sleepiness.12,13 Moreover, experimental studies have
shown that just 1 night of 4- to 5-h sleep opportunity reduces
sleep latency in the Multiple Sleep Latency Test14–16 and in-
creases levels of subjective sleepiness.15 After 5 nights of 6.5 h
of time in bed (TIB), higher levels of subjective sleepiness have
been corroborated by parental assessment.17
Short sleep duration has also been associated with greater
emotional lability.18 Compared to a well-rested condition, 2
nights of sleep restriction lowered self-reported positive af-
fect.19 Elevated negative affect ratings were observed after 5
nights of restriction to 6.5 h of TIB for sleep.20
Cognitive Consequences of Partial Sleep Deprivation
In comparison to adults, the effects of shortened sleep on
objectively measured cognitive performance in children and
adolescents have been found to be relatively modest, leading
some to suggest that adolescents may be more resistant to sleep
loss.21 Although several observational studies have found that
speed of processing, sustained attention, working memory,
SLEEP, Vol. 39, No. 3, 2016 688 Sleep and Cognition in Adolescents—Lo et al.
and executive function are poorer in children and adolescents
who report shorter sleep,22–24 other studies have failed to nd
a signicant relationship between sleep duration and speed of
processing,23,25 working memory, or executive function.12,23,25
Experimental studies on the cognitive consequences of par-
tial sleep deprivation in children and adolescents have yielded
heterogeneous ndings, possibly because of differences in the
extent of partial sleep deprivation and the cognitive tasks used
across studies. In relation to partial sleep deprivation, both
the severity of sleep restriction each night and the number of
nights sleep was restricted have generally been lesser than in
adult studies. Most partial sleep deprivation studies in chil-
dren and adolescents have either reduced TIB by only 1 h for a
few nights26 or have restricted sleep opportunity to 4 to 5 h for
only 1 night.14–16 ,2 7 Although partial sleep deprivation has been
observed to impair attention,26 working memor y,26 executive
function,16 and verbal creativity16 in some studies, others have
not found any signicant decrement in attention,14,1 5,2 7 execu-
tive function,27 or speed of processing.14,16 ,2 6
Two studies investigated the cognitive effects of a longer pe-
riod of sleep restriction. In one, 5 nights of sleep restricted to 6.5
h TIB resulted in increased student and parent reports of inat-
tention, as well as problems with metacognition.17 However, in a
subset of these participants who underwent functional magnetic
resonance imaging, the investigators found no objective decit
in working memory or executive function. These adolescent
participants might have modulated task-related activation to
mitigate any potentially deleterious effects of sleep restriction.28
In a second study,21 participants restricted to 5, 6, 7, 8, or
9 h of TIB for 4 nights did not exhibit any decit in attention,
speed of processing, executive function, or working memory.
Although total sleep time (TST) was reduced in each of the
sleep-restricted groups, the duration of slow wave sleep was not
affected, leading the investigators to propose that adolescents
may be resilient to cognitive impairment following substantial
sleep re s t r ictio n becau s e of th e pres e r v atio n of slow wave sleep. 21
A recent meta-analysis29 on both observational and ex-
perimental studies found that in school-age children, the
correlation between short sleep duration and poor cognitive
performance was very modest (r = 0.08). When various cogni-
tive domains were analyzed separately, shorter sleep duration
was only modestly associated with poorer executive function,
and not at all with sustained attention a cognitive domain
highly sensitive to partial sleep deprivation in adults.30 ,31
In the current study, we evaluated the effect of 7 nights of
partial sleep deprivation on adolescents, seeking to ll gaps
left by previous studies. First, we recruited students from top
high schools – the type of students many lay persons expect to
transcend the need for sleep when motivated to attain desired
goals. Second, the modest effects of partial sleep deprivation
in prior experiments could have resulted from insufciently
severe sleep restriction compared to similar studies in adults.
In addition, these milder degrees of sleep restrtiction are not
representative of the sleep schedules encountered by students
living in highly competitive societies. To examine this possi-
bility, sleep was restricted to 5 h TIB for 7 consecutive nights.
Third, to facilitate comparison with similar studies on adults,
our test battery comprised tests commonly used in adults. An
example is the Psychomotor Vigilance Task (PVT),32 which is
widely used in sleep deprivation studies on adults33 but has not
been used in studies on children and adolescents. Fourth, to
enhance ecological validity of our ndings, the current study
was conducted in a dormitory instead of in a sleep laboratory.
Although a natural setting was used, the instrumentation, tests,
and test frequency were similar to those used in laboratory-
based studies. In particular, sleep was evaluated using both
actigraphy and polysomnography (PSG).
Sixty participants were invited to participate in the Need for
Sleep Study, a 2-w protocol aimed at characterizing changes
in cognitive performance, subjective sleepiness, and mood as-
sociated with sleep curtailment in adolescents. Participants
were between 15 and 19 y of age; had to have no history of
any chronic medical condition, psychiatric illness, or sleep
disorder; had a body mass index ≤ 30; were not habitual short
sleepers (i.e. had an average actigraphically estimated TIB
of < 6 h and no sign of sleep extension on weekends); had to
consume fewer than ve cups of caffeinated beverages a day;
and must not have traveled across more than two time zones 1
mo prior to the experiment.
Participants were randomized into the sleep restriction (SR)
and the control groups. They were not informed about their
grouping until the rst day of the 2-w protocol. Two partici-
pants withdrew several days prior to the study and one during
the study for personal reasons. One participant did not comply
with the experimental procedures and was excluded from all
the analyses.
The resulting sample consisted of 56 participants (25 males,
mean ± standard deviation of age = 16.6 ± 1.1 y). The SR
(n = 30) and the control groups (n = 26) did not differ in age,
sex distribution, body mass index, consumption of caffeinated
beverages, nonverbal intelligence, levels of anxiety and de-
pression, morningness-eveningness preference, levels of day-
time sleepiness, symptoms of chronic sleep reduction, global
score of the Pittsburgh Sleep Quality Index, and self-reported
and actigraphically assessed sleep habits (Table 1; refer to the
next section for details of screening instrumentation). Data
from actigraphy during term time indicated that on weekdays,
these participants slept less than the recommended 8–10 h,4
and TIB and TST increased by more than 2 h from weekdays
to weekends (Table 1).
Recruitment and Screening
This study was approved by the Institutional Review Board
of the National University of Singapore. Participants were re-
cruited through sleep education talks in two high-ranking high
schools (see endnote A), advertisements on the laboratory and
social networking websites, as well as by word of mouth. All
interested participants and their legal guardians were invited
to attend a brieng session. Written informed consent was ob-
tained from each participant and a legal guardian.
The Pittsburth Sleep Quality Index34 was used to assess
self-reported sleep timing, duration, and quality, whereas the
SLEEP, Vol. 39, No. 3, 2016 689 Sleep and Cognition in Adolescents—Lo et al.
Morningness-Eveningness Questionnaire35 evaluated morn-
ingness-eveningness preference. Participants completed the
C h r o n ic Sl e ep Re du ct ion Que s ti o nn ai re 36 to evalu ate symptoms
of chronic sleep restriction, the Epworth Sleepiness Scale37 to
examine levels of daytime sleepiness, and the Berlin Question-
naire38 to screen for obstructive sleep apnea. The Beck Anxiety
Inventory39 and the Beck Depression Inventory40 were used to
probe for anxiety and depression respectively. Nonverbal in-
telligence was assessed using the Raven’s Advanced Progres-
sive Matrices.41 Participants wore an actiwatch (Actiwatch 2,
Philips Respironics, Inc., Pittsburg, PA) for 1 w during term
time to evaluate sleep patterns. They also lled in a sleep diary
during that week, which provided additional information for
identifying bedtime and wake time on the actogram.
Each participant who met the inclusion criteria was inter-
viewed by JCL or RLL to ensure they would be comfortable
interacting with other participants and research staff, as well
as living away from home during the 2-w study period.
Two-Week Study Protocol
One week prior to the study, participants were required to ad-
here to a sleep-wake schedule that provided a 9-h nocturnal
sleep opportunity (23:00– 08:00). This was veried using
wrist-worn actigraphy and was intended for circadian entrain-
ment and for minimizing any effect of prior sleep restriction on
sleep and cognitive performance.
The 2-w protocol (Figure 1A) was conducted in a boarding
school after the school year had ended. In the rst 3 nights
(B1–B3), both SR and control participants had a 9 h nocturnal
sleep opportunity (23:00– 08:00) for adaptation and baseline
characterization purposes. This was followed by a 7-night ma-
nipulation period (M1–M7) in which the SR group had 5 h
(01:00– 06:00) and the control group had 9 h (23:00–08:00)
sleep opportunities. The protocol ended with 3 nights of 9-h
recovery sleep (R1–R3: 23:00–08:00) for both groups.
All participants slept in twin-share, air-conditioned rooms,
each with its own en-suite bathroom. Males and females were
Tab le 1 Characteristics for the sleep restriction and the control groups.
Sleep Restriction Group Control Group
t / χ2PMean SD Mean SD
n 30 – 26 –
Age (y) 16.43 0.94 16.81 1.17 1.33 0.19
Sex (% males) 46.70 42.30 0.11 0.74
Body mass index 20.43 2.88 20.38 2.55 0.07 0.94
Caffeinated drinks per day 0.75 0.55 0.54 0.79 1.18 0.25
Raven’s Advanced Progressive Matrices score 9.77 1.98 10.38 1.06 1.43 0.16
Beck Anxiety Inventory score 7.80 6.45 6.58 4.83 0.79 0.43
Beck Depression Inventory score 6.90 5.49 5.19 4.68 1.24 0.22
Morningness-Eveningness Questionnaire score 47.90 7.43 49.96 7.15 1.05 0.30
Epworth Sleepiness Scale score 7.77 3.59 6.19 3.57 1.64 0.11
Chronic Sleep Reduction Questionnaire
Total score 34.50 5.77 33.81 5.13 0.47 0.64
Shortness of sleep 12.37 2.39 12.50 2.30 0.21 0.83
Irritation 6.97 1.85 6.77 1.58 0.43 0.67
Loss of energy 7.43 1.94 7.00 1.65 0.89 0.38
Sleepiness 7.73 1.66 7.54 1.75 0.43 0.67
Pittsburgh Sleep Quality Index
TIB on weekdays (h) 6.12 1.03 5.94 1.14 0.63 0.54
TIB on weekends (h) 8.70 1.23 9.20 1.30 1.50 0.14
TIB on average (h) 6.86 0.87 6.87 0.87 0.07 0.95
TST on weekdays (h) 5.91 1.02 5.78 1.15 0.45 0.66
TST on weekends (h) 8.48 1.24 9.04 1.30 1.65 0.11
TST on average (h) 6.64 0.87 6.71 0.88 0.28 0.78
Global score 5.17 2.32 4.58 2.58 0.90 0.37
TIB on weekdays (h) 6.40 0.94 6.09 0.85 1.24 0.22
TIB on weekends (h) 8.46 1.08 8.45 1.25 0.99 0.99
TIB on average (h) 6.98 0.72 6.76 0.77 1.08 0.29
TST on weekdays (h) 5.61 0.86 5.37 0.73 1.11 0.27
TST on weekends (h) 7.46 1.10 7.53 1.14 0.21 0.84
TST on average (h) 6.14 0.66 5.99 0.62 0.89 0.38
Sleep efciency (%) 87.86 5.46 88.45 4.66 0.42 0.68
SD, standard deviation; TIB, time in bed; TST, total sleep time.
SLEEP, Vol. 39, No. 3, 2016 690 Sleep and Cognition in Adolescents—Lo et al.
housed in different buildings. The SR and the control groups
were housed on different oors. Windows in each bedroom
were tted with blackout panels to prevent participants from
being woken up by sunlight. Participants were provided with
earplugs and allowed to adjust room temperature according
to their own comfort. Apart from scheduled sleep periods,
meal times, and cognitive testing periods, participants spent
most of their time in a common room that received natural
as well as articial lighting. Participants were allowed to play
board games, read, study, watch movies, and play games on
their own electronic devices, in addition to interacting with
research staff and other participants. Participants were under
constant supervision of the research staff. Three main meals
were served each day, and snacks were provided upon request.
Caffeinated drinks, napping, and strenuous physical exercise
were prohibited.
Sleep-wake patterns were continuously assessed with wrist-
worn actigraphy, except for the rst night, i.e. night B1, when
all the actiwatches were charged. Each day, a computerized
cognitive performance test battery was administered at 10:00,
15:00, and 20:00 (except for the rst day [i.e. day B0]; Figure 1;
see endnote B). Polysomnographic recordings were obtained
on 7 nights: B1 and B3 for adaptation and baseline assessment,
M1, M4, and M7 to monitor sleep changes from the begin-
ning to the end of the manipulation period, and R1 and R3
for characterizing recovery sleep. Pulse oximetry was used on
the rst night to evaluate oxygen desaturations that might indi-
cate undiagnosed obstructive sleep apnea. Here, we will report
Figure 1(A) Experimental protocol. The 2-w experimental protocol is illustrated in a double raster plot. Both the sleep restriction (SR) and the control
groups had three adaptation and baseline nights (B1 to B3; time in bed [TIB] = 9 h), followed by 7 nights of sleep opportunity manipulation (M1 to M7;
TIB = 5 h for SR [black bars] and 9 h for control [gray bars]), and 3 nights of recovery sleep (R1 to R3; TIB = 9 h). On most days, a cognitive performance
test battery (purple bars) was administered at 10:00, 15:00, and 20:00. (B) Actigraphically and (C) polysomnographically assessed total sleep time (TST)
of the SR (red lines) and the control (blue lines) groups from the adaptation and baseline period to the manipulation and recovery periods. Standard errors
are illustrated. **P < 0.01; ***P < 0.001 for group contrasts.
SLEEP, Vol. 39, No. 3, 2016 691 Sleep and Cognition in Adolescents—Lo et al.
ndings regarding TST, whereas the sleep macrostructure and
microstructure ndings will be published separately.
Cognitive Performance Test Battery
A computerized cognitive performance test battery was ad-
ministered on 57 identical laptop computers (Acer Aspire E11,
Acer Inc, Taipei, Taiwan). All tests were programmed in E-
Prime 2.0 (Psychology Software Tools, Inc., Sharpsburg, PA).
Each test batter y lasted for approximately 25 min. Participants
were required to wear earphones throughout the test battery to
minimize distractions and for tone presentation during certain
tasks. The test battery comprised 7 tasks presented in the fol-
lowing order: the Karolinska Sleepiness Scale (KSS)42 the Sus-
tained Attention to Response Task (SART),43 the Symbol Digit
Modalities Test (SDMT),44 the verbal 1 and 3-back tasks,31 the
Mental Arithmetic Test (MAT),45 the Positive and Negative Af-
fect Scale (PANAS),46 and the PVT.32
In the KSS,42 participants rated their current level of subjec-
tive sleepiness using a nine-point Likert scale (1 very alert, 9
very sleepy, great effort to keep awake).
The SART43 was used to assess sustained attention. Num-
bers ranging from 0 to 9 were presented sequentially on the
screen for 250 msec, and participants were required to re-
spond by pressing the spacebar on every trial, except when the
target number ‘8’ appeared. The target to non-target ratio was
15:85, and the inter-stimulus interval was xed at 900 msec.
Two nonparametric measures of sensitivity (A’ ) and response
bias (B”D) were used to quantify performance. A’ is a mea-
sure of a participant’s ability to discriminate between targets
and non-targets, and is computed using the hit rate (number
of non-target trials responded to × 100/85) and false alarm
rate (number of target trials responded to × 100/15). A’ ranges
from 0 to 1, with 0.5 indicating performance at chance level.
B”D is a measure of a participant’s tendency toward liberal
(B”D < 0) or conservative (B”D > 0) response behavior, where
the former favors more responses and so is more likely to
lead to responses when they are not required; the latter favors
withholding responses, and as a result is less likely to result
in false alarms when responses are not required. Neutrality is
centered at 0 (B”D = 0 ).
The two measures were derived with the following
formula.47,4 8
For hit > fa, A’ = +
(hitfa) × (1 + hitfa)
4 × hit × (1 − fa)
For fa > hit, A’ = +
(fahit) × (1 + fahit)
4 × fa × (1 − hit)
B”D = (1 − hit) × (1 − fa) − (hit × fa)
(1 − hit) × (1 − fa) + (hit × fa)
The SDMT44 was used to measure speed of processing. In this
task, participants were shown a key displaying nine pairs of
digits and symbols. On every trial, a symbol appeared below
the key, and participants were required to respond by inputting
its corresponding digit (ranging from 1 to 9 on the keyboard)
as quickly as possible. If participants did not respond in 15 sec,
a beeping tone was presented until a response was recorded.
This task lasted for 2 min. The total number of correct trials
was used as the critical measure.
Verbal n-back tasks31 were used to assess working memory
and executive function. In this task, alphabets were presented
sequentially for 1,000 msec with 3,000 msec inter-stimulus in-
terval. Participants were required to decide whether the current
stimulus matched with the one shown one (1-back) or three (3-
back) items ago. The match to mismatch ratio was 8:24. We
used the formulas stated above to derive measures of sensi-
tivity (A’ ) and response bias (B”D) to quantify performance.
The MAT45 was used to measure speed of processing. This
took the form of addition problems involving pairs of two-digit
numbers that were shown on screen, and participants were re-
quired to solve them as quickly as possible. A beeping tone
was presented if participants did not respond within 15 sec.
The total number of cor rect trials in this 4-min task was used
as the critical measure.
The PA NAS46 was used to assess positive and negative af-
fect. Participants were shown 20 adjectives with 10 describing
positive mood and 10 describing negative mood. Participants
needed to respond using a ve-point Likert scale (1 very
slightly, 5 extremely).
A 10-min PVT32 was used to measure levels of sustained at-
tention. At random intervals varying from 2,000 msec to 10,000
msec, a counter on the computer screen started counting, and
participants were required to respond as quickly as possible by
pressing a key. A beeping tone was presented if no response
was detected 10,000 msec after stimulus onset. The number of
lapses (responses exceeding 500 msec) recorded during each
PVT test was used as a measure of sustained attention.
Participants wore an actiwatch (Actiwatch 2, Philips Respi-
ronics, Inc., Pittsburgh, PA) around the wrist of their non-dom-
inant hand during term time for screening purposes, during
the 1-w pre-study period for verifying their compliance with
the specied sleep schedule, as well as during the 2-w pro-
tocol. Data were collected at 2 min resolution and were scored
with the Actiware software (version 6.0.2). TST was calculated
using a medium sensitivity algorithm, with which an activity
count greater than or equal to 40 was dened as waking. Par-
ticipants also kept a sleep diary during the actigraphically
monitored periods at home.
Electroencephalography (EEG) was performed using a SOM-
NOtouch recorder (SOMNOmedics GmbH, Randersacker,
Germany) from two channels (C3 and C4 in the international
10–20 system) referenced to the contralateral mastoids. The
common ground and reference electrodes were placed at Cz
and FPz. Electrooculography (EOG) and submental elec-
tromyography (EMG) were also used. Impedance was kept
below 5 kΩ for EEG electrodes and below 10 kΩ for EOG
and EMG electrodes. Signals were sampled at 256 Hz and l-
tered between 0.2 and 35 Hz for EEG and between 0.2 and 10
Hz for EOG.
Sleep scoring analyses were performed using the FASST
toolbox (http://ww w.monte
SLEEP, Vol. 39, No. 3, 2016 692 Sleep and Cognition in Adolescents—Lo et al.
EEG signals were band-pass ltered between 0.2 and 25 Hz.
Scoring was performed visually by trained technicians following
the criteria set by the American Academy of Sleep Medicine
Manual for the Scoring of Sleep and Associated Events.49
Statistical Analyses
Statistical analyses were performed with SAS 9.3 (SAS Insti-
tute, Cary, NC). We used a general linear mixed model with
PROC MIXED to determine the effects of group, day (from
day B3 to R2), and the group × day interaction on cognitive
performance, sleepiness, and mood averaged across the three
test batteries each day. We included performance on day B2
(see endnote C) as a covariate to control for group differences
in baseline performance. To quantify the local effect size of
partial sleep deprivation on each measure, we used a similar
statistical model but excluded the recovery days to compute
Cohen f2 of the group × day interact ion.50 The cutoffs for sm all,
medium, and large effect sizes were 0.02, 0.15, and 0.35, re-
sp e c t i vel y. 51 We excluded data from the rst ve test batteries
on days B0 and B1 in all the analyses to minimize inuence of
practice effects.
To assess the efcacy of our manipulation of sleep opportu-
nities, we also used a general linear mixed model to determine
the effects of group, day (from night B2 to R3 for actigraphic
data, and from night B3 to R3 for PSG data), and group × day
interaction on TST. PSG data from night B1, i.e., the adapta-
tion night, was not included in the analysis. To ensure that
the two groups followed the 9-h sleep schedule and did not
differ in sleep duration the week prior to the 2-w protocol, we
performed independent-samples t tests on actigraphically esti-
mated TIB and TST.
Sleep Duration before and during the Protocol
One week before the 2-w protocol, both groups complied with
the 9-h sleep schedule at home (mean ± standard error of the
mean of TIB of the SR group: 8.78 ± 0.07 h versus control
group: 8.84 ± 0.04 h, t(53) = 0.68, P = 0.50). There was no
signicant group difference in actigraphically estimated TST
(SR: 6.89 ± 0.16 h versus control: 6.94 ± 0.11 h, t(53) = 0.25,
P = 0.80), suggesting that sleep history did not differ between
the two groups. The actigraphically estimated TST of 6.9 h
appears short but is readily explained by actigraphy underes-
timating TST by approximately 1 h relative to PSG (see next
section). As such, it is likely that our participants were well
rested prior to the study.
We found that (1) the SR and the control groups had similar
TST at baseline, (2) the partial sleep deprivation manipulation
resulted in a large reduction in daily TST, and (3) the SR group
had greater TST during the recovery nights. In the ensuing
material, we provide a detailed breakdown of these points.
Actigraphy during the 2-w protocol revealed a signicant
group × day interaction on TST (F(11,466) = 54.58, P < 0.001).
The two groups had similar actigraphically estimated TST on
baseline nights (e.g., on B3, SR: 6.98 ± 0.15 h versus control:
7.24 ± 0.16 h, P = 0.23). During the manipulation period, TST
was reduced to 4.01–4.41 h in the SR group and remained at
approximately 7 h for the control group (Figure 1B). On the
rst 2 recovery nights, the SR group slept for 7.61 ± 0.15 h and
7.46 ± 0.15 h respectively, both longer than the last baseline
night (P < 0.001 and P = 0.008) and signicantly longer than
the control group (R1: 7.02 ± 0.16 h, P = 0.01; R2: 6.78 ± 0.16 h,
P = 0.002). On the third recovery night, TST of the SR group
approached baseline level (P = 0.07), and the group difference
disappeared (6.62 ± 0.16 h versus 6.38 ± 0.16 h, P = 0.23).
Actigraphy underestimated sleep duration by approxi-
mately 1 h relative to PSG. This systematic bias was less
with higher sleep efciency (i.e., as TST approached TIB)
(Figure S1, supplemental material), and this was indepen-
dent of the duration of sleep opportunity (TIB). Nevertheless,
polysomnographic assessment of TST in response to sleep
curtailment was, in general, congruent with the actigraphy
ndings (Figure 1C). The group × day interaction was statisti-
cally signicant on TST (F(5,179) = 572.14, P < 0.001). TST in
the last baseline night did not signicantly differ between the
two groups (SR: 7.95 ± 0.07 h versus control: 8.09 ± 0.07 h,
P = 0.16). TST was maintained between 7.99 h and 8.18 h for
the control group. The SR group showed a signicant increase
in TST from the beginning to the middle of the manipulation
period (4.57 ± 0.07 h and 4.82 ± 0.07 h, P = 0.001). This was
then maintained until the end of the sleep opportunity manipu-
lation period (4.81 ± 0.07 h). In the rst recovery night, not only
was the SR group’s TST signicantly longer than the control
group’s (8.58 ± 0.07 h versus 8.09 ± 0.07 h, P < 0.001), it was
signicantly elevated from the baseline level (P < 0.001). On
the third recovery night, TST of the SR group remained above
baseline (P = 0.004) and signicantly longer than the control
(8.19 ± 0.07 versus 7.85 ± 0.08 h, P = 0.001).
Effects of Partial Sleep Deprivation on Subjective Sleepiness,
Cognitive Performance, and Mood
Cognitive performance, subjective sleepiness, and mood in
the SR group were affected by partial sleep deprivation, as
evidenced by a decrement in performance or reduced rate of
improvement. Two nights of recovery sleep were insufcient
to return performance to baseline levels on measures of sus-
tained attention and subjective sleepiness (Figure 2). Although
recovery sleep might have restored performance improvement
in speed of processing tasks, performance of individuals with
prior sleep restriction remained poorer than the well-rested
control group. In general, the control group showed relatively
stable cognitive performance, levels of subjective sleepiness,
and mood throughout the protocol.
In evaluating sustained attention, we found a group × day
interaction on the number of lapses in the PVT (F(9,456) = 9.09,
P < 0.001). The SR group showed a monotonic increase in
the number of lapses throughout the partial sleep deprivation
period. The number of lapses was signicantly reduced after
the rst recovery sleep episode (P < 0.001), but remained el-
evated relative to baseline after the rst two nights of recovery
sleep (P < 0.001; left panel in Figure 2A). Performance on the
SART was less affected by partial sleep deprivation. Although
the group × day interaction was also signicant for A’ in the
SART (F(9,457) = 2.02, P = 0.04), a noticeable decrease in
A’ was found only after 4 nights of partial sleep deprivation.
SLEEP, Vol. 39, No. 3, 2016 693 Sleep and Cognition in Adolescents—Lo et al.
Figure 2—Effects of partial sleep deprivation on cognitive performance, subjective sleepiness, and mood. Daily average and standard errors of the sleep
restriction (SR) (red lines) and the control (blue lines) groups from the days after the last baseline night (B3), after 1 to 7 nights of sleep manipulation (M1
to M7), and after 2 nights of recovery sleep (R1 and R2) were plotted for (A) sustained attention as indicated by the number of lapses in the Psychomotor
Vigilance Task (PVT) and the sensitivity measure (A’ ) in the Sustained Attention to Response Task (SART), (B) working memory and executive functions as
indicated by A’ in the verbal 1- and 3-back tasks, (C) speed of processing as indicated by the number of correct responses in the Mental Arithmetic Test (MAT)
and the Symbol Digit Modalities Test (SDMT), (D) subjective sleepiness level as indic ated by score on the Karolinska Sleepiness Scale (KSS), and (E) positive
and negative mood as indicated by the score on the Positive and Negative Affect Scale (PANAS). *P < 0.05; **P < 0.01; ***P < 0.001 for group contrasts.
SLEEP, Vol. 39, No. 3, 2016 694 Sleep and Cognition in Adolescents—Lo et al.
Performance returned to baseline levels after only 1 night of
recovery sleep (P = 0.17; right panel in Figure 2A). This decre-
ment in discriminability between targets and non-targets could
not be explained by changes in response bias as B”D was not
affected at all by partial sleep deprivation (group × day interac-
tion: F(9,457) = 1.30, P = 0.23; Figure S2A, supplemental mate-
rial). In terms of effect size, performance in the PVT was the
most sensitive to partial sleep deprivation of all the tests in this
study ( f2 = 1.48; Figure 3). In comparison, the A’ in SART, was
much less affected by sleep restriction ( f2 = 0.20; Figure 3).
In terms of working memory and executive function, we
observed a signicant group × day interaction on A’ in the
verbal 1-back task (F(9,456) = 2.45, P = 0.01). A’ declined after
4 nights of sleep restriction and returned to baseline levels after
one recovery sleep episode (P = 0.06; left panel of Figure 2B).
The group × day interaction on B”D in the verbal 1-back task
was not statistically signicant (F(9,457) = 1.70, P = 0.09), and
no signicant group difference in the tendency toward con-
servative response behavior was observed throughout the pro-
tocol (left panel of Figure S2A). Hence, the decrement in A’ in
the SR group could not be accounted for by response bias. In
the verbal 3-back task, there was also a signicant group ×
day interaction on A’ (F(9,457) = 3.20, P < 0.001). A’ decreased
after 4 nights of partial sleep deprivation and returned to base-
line level after 1 night of recovery sleep (P = 0.15; right panel
of Figure 2B) as observed in the verbal 1-back task. B”D in
the verbal 3-back task did not reveal a statistically signicant
group × day intera ction (F(9,457) = 1.51, P = 0.14; right panel of
Figure S2B) and hence, could not explain the decrease in A’ in-
duced by sleep loss. The size of the partial sleep deprivation ef-
fect on 1- and 3-back was similar in magnitude (f2 = 0.63 and
0.70; Figure 3), suggesting that cognitive decrement induced
by partial sleep deprivation did not change with executive load.
In both the MAT and the SDMT, which are tests of speed
of processing, performance improved with repeated testing,
but this was attenuated in the SR group relative to the control
group (group × day interaction for the MAT: F(9,456) = 4.33,
P < 0.001; for the SDMT: F(9,456) = 4.02, P < 0.001). Interest-
ingly, the largest improvement in both tasks was demonstrated
by the SR group across the rst recovery night (P < 0.001 for
both tasks; Figure 2D). Nevertheless, after 2 nights of recovery
sleep, performance of the SR group remained signicantly
poorer than the control group (P < 0.003 for both tasks). Al-
though both speed of processing tasks revealed a similar pat-
tern, performance in the MAT was a more sensitive measure of
sleep loss than the SDMT ( f2 = 1.14 and 0.72; Figure 3).
Subjective sleepiness evaluated using the KSS showed a sig-
nicant group × day interaction (F(9,457) = 9.32, P < 0.001).
KSS score was elevated after only 1 night of partial sleep de-
privation (P < 0.001), progressively increased thereafter, and
plateaued toward the end of the manipulation period. Although
KSS score in the SR group decreased after 1 night of recovery
sleep (P < 0.001), it was still higher than the baseline value
(P < 0.001) and at the level observed after 1 night of partial
sleep deprivation (P = 0.61). This remained so even after the
second recovery night (versus baseline: P < 0.001; versus M1:
P = 0.65; Figure 2D). The effect of partial sleep deprivation
on subjective sleepiness was in the medium range ( f2 = 0.50;
Figure 3).
We found a signicant group × day interaction on positive
mood (F(9,456) = 4.71, P < 0.001). Positive mood decreased
progressively during partial sleep deprivation, leveled off to-
ward the end of the manipulation period, and returned to the
baseline level after 1 night of recovery sleep (P = 0.36; left
panel of Figure 2E). In contrast, the group × day interaction on
negative mood was not statistically signicant (F(9,457) = 1.15,
P = 0.33). Negative mood appeared to stay at a low level
throughout the protocol for both the SR and the control groups
(main effect of day: F(9,457) = 0.61, P = 0.79; right panel of
Figure 2E). Effect size measures showed that partial sleep de-
privation had a medium effect on positive affect ( f2 = 0.17),
but only a small effect on negative affect ( f2 = 0.07; Figure 3).
Restricting adolescents’ sleep to 5 h TIB for 7 nights led to cu-
mulative degradation of sustained attention, working memory,
executive function, and speed of processing. In contrast, the
increase in subjective sleepiness and the reduction in positive
mood leveled off in the course of the experiment. Residual ef-
fects on sustained attention and subjective sleepiness persisted
after 2 nights of 9 h recovery sleep opportunity. Adolescents
in the control condition consistently slept approximately 8 h
each night, maintained their baseline levels of cognitive per-
formance, subjective sleepiness, and mood, and even demon-
strated improvement in speed of processing.
Partial Sleep Deprivation Affects Even Academically Strong
Perhaps the most important nding of the current work is
that even students from top schools who regularly sleep 2 to
3 h less than recommended for their age on weekday nights
Figure 3—Effect size of partial sleep deprivation on cognitive
performance, subjective sleepiness, and mood. Effect size is indicated
by the local effect size (Cohen f2) of group × day interaction on
each cognitive measure (refer to the Methods section for further
details). KSS, Karolinska Sleepiness Scale; MAT, Mental Arithmetic
Test; PANAS, Positive and Negative Affect Scale (+, score on the
positive affect subscale; −, score on the negative affect subscale);
PVT, Psychomotor Vigilance Task; SART, Sustained Attention to
Response Task; SDMT, Symbol Digit Modalities Test.
SLEEP, Vol. 39, No. 3, 2016 695 Sleep and Cognition in Adolescents—Lo et al.
experience signicant neurobehavioral decits when exposed
to partial sleep deprivation.
Prior studies on adolescents with perhaps one exception21
have used less harsh sleep restriction than that used here. Ex-
perimental studies of partial sleep deprivation in adults have
used 3 to 6 h TIB for a minimum of 7 nights.31,52,53 This con-
stitutes about 2 to 4 h less actual sleep a night, assuming a
norm of 7 to 8 h.54 For adolescents, studies using 5 h TIB are
in theory comparable to adult studies. A meta-analysis sum-
marizing sleep duration data in the past century has shown
that sleep in children and adolescents has decreased by about
75 min from the 20th century, with Asia showing one of the
fastest rates of reduction.55 This perhaps can be due to a dis-
proportionately larger amount of time spent on school work
in East Asia than in Western developed countries.56 A survey
in Korea involving a nationally representative sample of over
130,000 adolescents found that 43% reported sleeping less than
6 h each night.2 Preliminary data from students of one of the
feeder schools to the current work showed that on average, the
actigraphically estimated TST was below 5.5 h during week-
days (unpublished data). As such, the severity and duration of
sleep restriction used here has real-world relevance.
The severity of neurobehavioral decits we observed in ado-
lescents is comparable to if not greater than that observed with
adults exposed to a similar degree of partial sleep deprivation.
For example, young adults showed about 10 lapses in the PVT
af ter 7 nig ht s of 4 h TI B,53 whereas an ave r a ge of 18 lap s e s were
found after 7 nights of 5 h TIB in the current study. Although
many students seek to emulate elite performers who sleep little,
the current data show that even students from the top per-
forming country in a global test on reading, mathematics and
science8 are not spared and experience signicant neurobehav-
ioral decits when undergoing partial sleep deprivation.
Sustained Attention is the Most Affected Cognitive Domain, as
in Adults
Previous studies have suggested that executive function and
not attention is the cognitive domain most affected in par-
tially sleep deprived children and adolescents.11,16, 57 These prior
studies may not have found strong effects on attention because
of differences in tests used to measure attention. The PVT is
the most widely used test of sustained attention in adults. We
detected monotonic deterioration in vigilance over the 7 nights
of sleep restriction. The SART was less sensitive ( f2 = 0.20)
than the PVT ( f2 = 1.48; Figure 3) highlighting the differential
sensitivity to multi-night sleep restriction across tasks evalu-
ating the same cognitive domain.
In terms of effect size, decline in speed of processing was
the next most affected cognitive domain. This was slightly sur-
prising given the absence of signicant effects on this domain in
prior studies on partial sleep deprivation in children and adoles-
cents.14,16,21,26 As in the case of sustained attention, we speculate
that difference in task selection and severity of sleep restriction
could explain these discrepancies. Although 1 night of recovery
sleep might have restored the learning ability of the SR group,
their performa nce failed to catch up with that of the cont r ol group.
Whether additional nights of sufcient sleep can eliminate this
group difference in performance remains to be investigated.
Working memory and executive function evaluated with 1-
and 3-back tests were signicantly affected by sleep restric-
tion with an effect size of about half of that observed with the
PVT. Interestingly, there was no additional decline in perfor-
mance with increasing executive load (3 back versus 1 back).
The absence of an incremental effect of load is similar to that
observed with adults undergoing partial sleep deprivation31
as well as visual short term memory and total sleep depriva-
tion58 –60 and suggests that perceptual and attentional degrada-
tion61 independently or together with maintenance failure
could underlie the performance decline attributed to executive
function in the sleep deprived state.
Two Nights of Recovery Sleep may not be Enough but
Cognitive Domain Matters
Two nights of recover y sleep may not be sufcient to achieve a
complete recovery in sustained attention, speed of processing,
and alertness after 1 w of relatively severe sleep restriction in
adolescents. These ndings are reminiscent of a study where
healthy young adults were restricted to 4 h TIB for 5 nights
and the duration of recovery sleep was varied. Even 10 h of
recovery sleep for a single night was insufcient to completely
restore sustained attention to baseline levels, although speed of
processing was restored.63
Particularly relevant to hard driving students, the residual
effects of sleep deprivation may cumulate and subsequent ex-
posure to sleep restriction following incomplete recovery may
result in disproportional decline in performance (Dinges, un-
published data). Relevant to this point, the relative plateauing
of subjective sleepiness compared to monotonically declining
sustained attention and reduced improvement in speed of pro-
cessing53,64 could cause adolescents to underestimate the extent
of their objective neurobehavioral decit. Of particular concern
in societies where sacricing sleep for academic success is
prevalent is that chronic fatigue becomes a new societal norm.65
Poorer Positive Mood with Sleep Restriction
A decline in positive mood was observed after 2 nights of sleep
restriction, similar to one previous study.19 However, unlike
another study,20 we did not nd an effect on negative mood.
Although negative mood appeared to remain unaffected, many
students remarked that the test items, e.g., guilty, scared, and
afraid, were irrelevant to them. Sleep has been shown to
modulate the processing of emotional memory.66–68 Although
this may have survival value, it could have negative effects
on mental health. Indeed, a large behavioral risk factor survey
found that shorter self-reported sleep duration in adolescents
was associated with higher likelihood of reporting depressive
symptoms and suicidal ideation.2
Differences in Adolescent Sleep Assessed by Wrist Actigraphy
and PSG
The Bland-Altman plot (Figure S1) indicates that when sleep
efciency was high (i.e., when TST approached TIB), there was
overall good concordance between sleep duration measured
by both actigraphy and PSG, but when sleep efciency was
low, there was a systematic underestimation of TST for actig-
raphy. The underlying reasons for the underestimation, rather
SLEEP, Vol. 39, No. 3, 2016 696 Sleep and Cognition in Adolescents—Lo et al.
than overestimation,69 of TST by actigraphy in our sample of
adolescents and for the increased discrepancy between sleep
duration assessed by PSG and wrist actigraphy as a function
of sleep efciency are unknown and remain to be investigated.
Limitations and Future Studies
Sleep restriction was achieved by delaying bedtime and ad-
vancing wake time by 2 h so that the midpoints were aligned for
both the sleep periods and the wake periods throughout the pro-
tocol to minimize circadian phase shifting. However, because
test batteries were run at the same clock times, the duration of
preceding wakefulness was always 2 h longer for the SR group
during the manipulation period. The cognitive decrement asso-
ciated with partial sleep deprivation might thus be accentuated
by a longer duration of prior wakefulness before testing.
Our 7-night sleep restriction period was longer than the typ-
ical 5 study nights of 1 w when students curtailed their sleep.
Although this might potentially limit the generalizability of
our ndings, it is not uncommon for highly competitive stu-
dents to continue sleeping less than recommended on week-
ends in order to study. Furthermore, our nding that some
cognitive functions failed to return to baseline levels after 2
nights of recovery sleep strongly signal the need to systemati-
cally evaluate the long-term effects of repeated cycles of sleep
restriction and recovery on neurobehavioral decits. Although
we have unequivocally demonstrated neurobehavioral decits
using a standardized cognitive battery, the effect on ability
to learn, to retain information, and to creatively reorganize
learned material was not assessed. These higher-order cogni-
tive functions are of critical interest and remain to be evaluated
in future studies.
Partial sleep deprivation in adolescents of comparable dura-
tion and severity to that examined in studies on young healthy
adults elicited equivalent or greater neurobehavioral decits
across several cognitive domains. Residual effects on sus-
tained attention, speed of processing, and subjective alertness
can still be observed even after 2 nights of recovery sleep. That
even students from top high schools are susceptible to neu-
robehavioral decits following partial sleep deprivation should
cause policymakers and parents to reconsider if sleep should
continue to be sacriced for the sake of academic achievement.
A: Singapore was the top-ranked country out of 65 countries
in the 2012 PISA examinations.8 Most of our participants
came from top ranked schools. All participants stayed in the
boarding school during the 2-w protocol.
B: The label of day indicates the wake period after the corre-
sponding sleep period. For example, day B2 refers to the day
after the second baseline night, but before the third baseline
night. This highlights the effect of sleep history on subsequent
cognitive performance.
C: Performance on day B3 was not used as a covariate because
these data were included in the effect of day in the statistical
model. This model allows the evolution of cognitive perfor-
mance, subjective sleepiness, and mood from the last baseline
day (day B3) to be depicted.
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The authors are gratefu l for Hans Van Dongen for his advice on statistical
analyses, and Sher Yi Chiam and Benny Chin Seah Koh for t heir assistance
in par ticipant recruitment in their schools. We than k Amiya Patanai k and
Jasmine Siudzinski for coding the cognitive tasks, and Jesisca Tandi, Wei
Shan Cher, Pearlynne Chong, Bindiya Laksh mi Rag hunath, V Vien Lee,
SLEEP, Vol. 39, No. 3, 2016 698 Sleep and Cognition in Adolescents—Lo et al.
Shin Wee Chong, and Nicholas Ivan Chee for their effort in data collection
and processing.
Submitted for publicat ion August, 2015
Submitted in nal revised form September, 2015
Accepted for publication October, 2015
Address correspondence to: Dr. Michael W.L. Chee, Centre for Cognitive
Neuroscience, Duke-NUS Graduate Medical School, 8 College Road, Level
6, Singapore 169857; Tel: (+65) 6516 4916; Fax: (+65) 6221 8625; Email:
This was not an industry suppor ted st udy. Financial support was
provided by the National Medical Research Council, Singapore (N MRC/
STaR/0004/2008 and N MRC/STaR/015/2013) and The Far East
Organization. The authors have indicated no nancial conicts of interest.
This work was approved by the Institutional Review Board of the National
University of Singapore (13-562). All participants provided wr itten
informed consent.
... Indeed, high-quality sleep can promote memory consolidation and learning because during sleep, new memories are strengthened and become more resistant to interference [50,51]. On the other hand, in children [52] and adolescents [53,54], minimal but repeated sleep restrictions or sleep deprivation throughout the night have resulted in various cognitive deficits. More specifically, disturbed sleep may lead to slower responses and more variable performance during alertness, vigilance, and attention tasks [55,56]. ...
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Sleep disturbances may be a significant source of distress for children with neurodevelopmental disorders, and consequently also for their families. Crucially, sleep disturbances might be influenced by comorbidity. Attention deficit hyperactivity disorder (ADHD) and specific learning disorder (SLD) often co-occur, and consequently, investigating sleep disturbances in children with comorbidity of ADHD and SLD is essential. Our study aimed at detecting sleep difficulties in a group of 74 children with ADHD, 78 children with SLD, and 76 children with ADHD and SLD by using the Sleep Disturbances Scale for Children. The results showed that sleep difficulties emerge more clearly in children with comorbid ADHD and SLD compared to children with only ADHD or SLD. These sleep difficulties were not due to differences in ages and behavioral/emotional problems. In conclusion, evaluating sleep disturbances is important when assessing and managing children with ADHD, SLD, and particularly with the two comorbid conditions, to better understand their difficulties and develop tailored interventions.
... Sleep deprivation is frequent among astronauts on space missions (Barger, Flynn-Evans, et al., 2014), which results in higher sleepiness among astronauts (Lo et al., 2016). For an adult to be well-rested, the National Sleep Foundation (NSF) recommends seven to nine hours of sleep based on a study by Eugene and Masiak (2015) (Pacheco, 2021). ...
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Operations in space are anything but restful for astronauts, as there are both physical and psychological stressors. One known stressor is the lack of sufficient sleep in space which can drastically impact astronauts’ performance. Successful docking is highly important during space missions since small mistakes can lead to disastrous consequences. The docking process can be trained with the 6df task, a simulation in which six degrees of freedom must be controlled. This experimental study aimed to investigate the effect of susceptibility to sleep deprivation (SSD) on 6df docking performance impairment due to sleep deprivation (SD). A total of 62 participants (28 female; 18-39 years, Mage = 24.84; SDage = 4.69) completed a balanced-repeated-measures-cross-over-total-SD design. Test variables were calculated by subjects’ performance differences between “well-rested-“ and “SD measurements”. The dependent variable docking performance impairment due to SD was operationalised by 6df outcomes(“top-level achieved” and “mean docking accuracy”). SSD was defined as 1/reaction time (RT) from the Psychomotor Vigilance Test. A background analysis showed that participants’ RT slows significantly when SD (p < .001). Multinomial regressions (“top-level achieved”) showed no significant relations between SSD and docking performance impairment, whereas multiple regressions (“mean docking accuracy”) showed significant relations (p < .001). Post-hoc analysis showed that testing order is noteworthy because participants assessed in the order “well-rested-“ followed by “SD measurements” have lower docking performance impairment due to SD than the group with reversed order. Further, a posthoc analysis showed when participants split in “least SSD” and “most SSD”, the effect of SSD on 6df docking performance impairment due to SD was affected by testing order. The importance of testing order suggests the presence of a learning effect, meaning that docking performance impairment due to SD could be reduced by exhaustive training in well-rested conditions. In conclusion, this study can help construct guidelines for determining whether an individual can still perform the operationally relevant task safely under SD. This could also be interesting for other professions such as submarines, pilots, and surgeons, in which six degrees of freedom have to be controlled under SD.
... Implementing health promotion strategies, focused on sleep hygiene in educational centers could improve academic performance. do existe una reducción tanto en la cantidad y calidad del sueño, afectando negativamente el rendimiento académico 14,15 . Fisiológicamente, la asociación entre problemas de sueño y el rendimiento cognitivo y académico podría estar causada por una alteración en la fase de movimiento ocular rápido (REM, por su sigla en inglés) y en la fase sin movimiento ocular rápido (no REM, por su sigla en inglés). ...
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Objective: To analyze the association between sleep disorders, behaviors associated with cognition, and academic performance in elementary school students. Subjects and method: Analytical and cross-sectional research including 733 students from 5th and 8th grades from public schools par ticipating in the study "Health survey and academic performance in the Bio-Bio Province 2018". The sleep disorders were reported through a sleep self-report questionnaire, and the academic per formance was measured through the grade point average (GPA) in subjects language, mathematics, physical education, general point averages, and perception of cognitive functions in a school context. Results: 81.9% of the schoolchildren indicated problems with bedtime routines. The students with sleep disorders of both sexes presented higher memory problems, are slower in resolving math pro blems, have higher difficulties to maintain attention in classes, have more problems solving complex tasks, and more nervousness during a test than the student classified as not having sleep disorders. Additionally, the students with sleep disorders presented lower grades in their GPA and the subjects mathematics, language, and physical education than those students without sleep disorders. Con clusion: A high prevalence of bedtime routine problems was detected as well as an association bet ween sleep disorders and lower academic performance together with a worse perception of cognitive functions in schoolchildren. Implementing health promotion strategies, focused on sleep hygiene in educational centers could improve academic performance.
... Given the SART was promoted as a 4.3 min measure of sustained attention without floor or ceiling effects, the SART became extremely popular. In the 3 decades following the introduction of the SART, researchers have used the SART in a wide variety of populations and contexts (Baldwin & Lewis, 2017;Bellgrove et al, 2005;Head et al., 2017;Helton & Head, 2012;Ho et al., 2015;Johnson et al., 2013;Lo et al., 2016;Manly et al., 1999;Whyte et al., 2006). The assumption of many researchers has been that the SART measures or assesses sustained attention lapses. ...
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The sustained attention to response task (SART) is a popular measure in the psychology and neuroscience of attention. The underlying psychological cause for errors, in particular errors of commission, in the SART is actively disputed. Some researchers have suggested task-disengagement due to mind-wandering or mindlessness, and others have proposed strategic choices. In this study we explored an alternative perspective based on Signal Detection Theory, in which the high rate of commission errors in the SART reflects simply a shift in response bias (criterion) due to the high prevalence of Go-stimuli. We randomly assigned 406 participants to one of ten Go-stimuli prevalence rates (50%, 64%, 74%, 78%, 82%, 86%, 90%, 94%, 98% and 100%). As Go-stimuli prevalence increased reaction times to both Go and No–Go stimuli decreased, omission errors decreased and commission errors increased. These all were predicted from a hypothesized bias shift, but the findings were not compatible with some alternative theories of SART performance. These findings may have implications for similar tasks.
... It was likely that the cognitive tasks used in some earlier studies were not sufficiently sensitive or the sleep restriction too mild. Work using similar tasks to those used in adults found decrements in vigilance in 10-year old girls following a single night of 5h TIB of sleep (Peters et al 2009), 4 nights of 7.5h TIB sleep in 9-14 year old children (Campbell et al 2018) and any sleep duration less than 8h TIB over 24h (Lo et al 2020, Lo et al 2016b. Executive function, speed of processing, short term memory and declarative memory are also affected, albeit to a lesser degree. ...
Objectives: There is increased recognition that young people (<25 years) may occupy a carer role for family or others with health conditions or disability. This is often in addition to study and social activities. This means competing demands on time, and insufficient sleep. Our aim was to determine the contribution of caring duties to problematic sleep in young carers. Methods: A survey of Australian carers was conducted, including questions on demographics, characteristics of the carer and care recipient, and sleep quality and quantity. Participants were eligible if they reported sleep time <7 hr or dissatisfaction with their sleep, and were aged 15-24 years. Results: A total of 110 participants (71.8%_female = 79, 15-17 years = 62, 18-24 years = 48) were included in analysis; 55.5% (n= 61) reporting dissatisfaction with their sleep and 62.7% (n= 69) reporting typically less than 7 hr sleep per night. Sleep duration was significantly shorter for those who reported 1-2 or ≥3 awakenings to provide care, compared with no awakenings (p_< .05). Sleep quality, as described by scores on the Pittsburgh Sleep Quality Index (PSQI) was also significantly worse for those who were frequently awoken by their care recipient (p < .05). Worrying about the care recipient, being woken by the care recipient, and listening out for the care recipient were the most frequently identified factors impacting on sleep. Conclusion: Young carers experience reduced sleep duration and poor sleep quality. Strategies to alleviate the burden of care work on young carer's sleep would benefit the health and safety of this group.
Two adolescent mental health fields — sleep and depression — have advanced largely in parallel until about four years ago. Although sleep problems have been thought to be a symptom of adolescent depression, emerging evidence suggests that sleep difficulties arise before depression does. In this Review, we describe how the combination of adolescent sleep biology and psychology uniquely predispose adolescents to develop depression. We describe multiple pathways and contributors, including a delayed circadian rhythm, restricted sleep duration and greater opportunity for repetitive negative thinking while waiting for sleep. We match each contributor with evidence-based sleep interventions, including bright light therapy, exogenous melatonin and cognitive-behaviour therapy techniques. Such treatments improve sleep and alleviate depression symptoms, highlighting the utility of sleep treatment for comorbid disorders experienced by adolescents. Sleep problems are both a symptom and precursor of adolescent depression. In this Review, Gradisar et al. describe how the combination of adolescent sleep biology and psychology predisposes adolescents to develop depression, and describe interventions that improve sleep and depression symptoms in this population.
The effect of sleep deprivation on cognitive functions associated with the frontal lobe, such as attention, executive functions, and working memory, is not well known. This study aimed to investigate the effect of partial sleep deprivation in adolescents on the cognitive tasks of the frontal lobe, including visuospatial working memory, processing speed, sustained attention, executive functions, and short-term visual memory. Participants were recruited from voluntary students of Çukurova University. Eighteen adolescents underwent four consecutive nights of monitored sleep restriction (6–6.5 h/night) and four nights of sleep extension (10–10.5 h/night) in a counterbalanced order and separated by a washout period. Following each sleep period, the cognitive performance was assessed, at a fixed morning time, using a computerized neuropsychological test battery based on frontal lobe functions tasks, which was a timed test providing both accuracy and reaction time outcome measures. Only the spatial working memory performance of cognitive tasks was found to be statistically lower in the restricted-sleep condition than in the extended-sleep condition (p < 0.05). No significant difference was found in the performance of cognitive tasks evaluating simple attention, constant attention, executive functions, and cognitive flexibility. The findings of this study indicated that partial sleep restriction negatively affects specifically working memory and strategic thinking skills among cognitive functions based on the frontal lobe. Especially the visuospatial working memory and strategic thinking skills of adolescents might be susceptible to chronic partial sleep deprivation.
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High-altitude exposure can negatively impact one’s ability to accurately perceive time. This study focuses on Chinese migrants who have traveled to the Tibetan plateau and explores the effects of high-altitude exposure on their time interval judgment abilities based on three separate studies. In Study 1, it was found that exposure to high altitudes negatively impacted the time interval judgment functions of the migrants compared with a low-altitude control group; they exhibited a prolonged response time (540 ms: p = 0.006, 95% CI (−1.70 −0.32)) and reduced accuracy (1080 ms: p = 0.032, 95% CI (0.06 1.26)) in certain behavioral tasks. In Study 2, the results showed that high-altitude exposure and sleepiness had an interactive effect on time interval judgment (1080 ms) (p < 0.05, 95% CI (−0.83 −0.40)). To further verify our interaction hypothesis, in Study 3, we investigated the time interval judgment of interactions between acute high-altitude exposure and sleepiness level. The results revealed that the adaptation effect disappeared and sleepiness significantly exacerbated the negative effects of high-altitude exposure on time interval judgment (p < 0.001, 95% CI (−0.85 −0.34)). This study is the first to examine the effects of high-altitude exposure on time interval judgment processing functions and the effects of sleep-related factors on individual time interval judgment.
Objetivo. Determinar la asociación entre la somnolencia diurna (SD) y calidad de sueño (CS) con el rendimiento escolar (RE) de adolescentes de la Institución Educativa "Emblemática" Ventura Ccalamaqui, Barranca, 2018. Métodos. Estudio no experimental y transversal. Participaron 217 adolescentes del tercer y cuarto año de educación secundaria. Se aplicó la Escala de Somnolencia de Epworth y el Índice de Calidad de Sueño de Pittsburgh. El rendimiento escolar se determinó por la calificación en comunicación y matemática (asignaturas usadas por la comunidad internacional) y se clasificó de acuerdo al currículo nacional (AD, A, B, C). Resultados. La edad promedio de los adolescentes fue de 15,9 ± 0,6 años, donde el 51,2% fueron del sexo femenino, el 51,6% consumía café, té y/o gaseosas menos de una vez por semana. Se observó que el 49,7% presentaba somnolencia diurna, el 84,8% tenía problemas de sueño y el 52,1% presentó un rendimiento esperado. La somnolencia diurna se asoció significativamente con el rendimiento escolar (p=0,004); los estudiantes con SD presentaron RE esperado y en proceso, los estudiantes sin SD presentaron RE destacado, esperado y en proceso. La calidad de sueño de los adolescentes se asoció significativamente con su rendimiento escolar (p=0,045) y en la somnolencia diurna (p=0,015). Conclusiones. La somnolencia diurna y la calidad de sueño se asociaron con el rendimiento escolar de los adolescentes de la Institución Educativa "Emblemática" Ventura Ccalamaqui, Barranca, 2018.
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Study Objectives Various aspects of human performance were assessed in children after sleep loss. Participants Sixteen children (7 males, 9 females) between the ages of 10 and 14 years Design and Interventions Children were randomly assigned to either a control (CTRL) group, with 11 hours in bed, or an experimental sleep restriction (SR) group, with 5 hours in bed, on a single night in the sleep laboratory. Measurements Both groups were evaluated the following day with a battery of performance and sleepiness measures. Psychomotor and cognitive performance tests were given during four 1-hour testing sessions at 2-hour intervals. Results A multiple sleep latency test (MSLT) documented shorter latencies for SR children than controls. Significant treatment differences were discovered in three of four variables of verbal creativity, including fluency, flexibility, and average indices. There were also group differences found on the Wisconsin Card Sorting Test (WCST), which may be indicative of difficulty learning new abstract concepts. Measures of rote performance and less-complex cognitive functions, including measures of memory and learning and figural creativity, did not show differences between groups, perhaps because motivation could overcome sleepiness-related impairment for these tasks. Conclusions Higher cognitive functions in children, such as verbal creativity and abstract thinking, are impaired after a single night of restricted sleep, even when routine performance is relatively maintained.
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Making sense of “expert advice” is among the many challenges of parenting. With the media circulating contrasting views on the importance of sleep in adolescence, parents and practitioners would benefit from an accessible synopsis of the scientific literature. We tackled the multifaceted issue of adolescent sleep and daytime functioning, presenting the findings with their methodological limitations. Given what is known about sleep in this population, we offer guidelines that are both realistic and substantiated in empirical findings. Our aim is to put into practice the science behind adolescent sleep. (PsycINFO Database Record (c) 2015 APA, all rights reserved)
Background: Although sleep apnea is common, it often goes undiagnosed in primary care encounters. Objective: To test the Berlin Questionnaire as a means of identifying patients with sleep apnea. Design: Survey followed by portable, unattended sleep studies in a subset of patients. Setting: Five primary care sites in Cleveland, Ohio. Patients: 744 adults (of 1008 surveyed [74%]), of whom 100 underwent sleep studies. Measurements: Survey items addressed the presence and frequency of snoring behavior, waketime sleepiness or fatigue, and history of obesity or hypertension. Patients with persistent and frequent symptoms in any two of these three domains were considered to be at high risk for sleep apnea. Portable sleep monitoring was conducted to measure the number of respiratory events per hour in bed (respiratory disturbance index [RDI]). Results: Questions about symptoms demonstrated internal consistency (Cronbach correlations, 0.86 to 0.92). Of the 744 respondents, 279 (37.5%) were in a high-risk group that was defined a priori. For the 100 patients who underwent sleep studies, risk grouping was useful in prediction of the RDI. For example, being in the high-risk group predicted an RDI greater than 5 with a sensitivity of 0.86, a specificity of 0.77, a positive predictive value of 0.89, and a likelihood ratio of 3.79. Conclusion: The Berlin Questionnaire provides a means of identifying patients who are likely to have sleep apnea.
Objective: The objective was to conduct a scientifically rigorous update to the National Sleep Foundation's sleep duration recommendations. Methods: The National Sleep Foundation convened an 18-member multidisciplinary expert panel, representing 12 stakeholder organizations, to evaluate scientific literature concerning sleep duration recommendations. We determined expert recommendations for sufficient sleep durations across the lifespan using the RAND/UCLA Appropriateness Method. Results: The panel agreed that, for healthy individuals with normal sleep, the appropriate sleep duration for newborns is between 14 and 17 hours, infants between 12 and 15 hours, toddlers between 11 and 14 hours, preschoolers between 10 and 13 hours, and school-aged children between 9 and 11 hours. For teenagers, 8 to 10 hours was considered appropriate, 7 to 9 hours for young adults and adults, and 7 to 8 hours of sleep for older adults. Conclusions: Sufficient sleep duration requirements vary across the lifespan and from person to person. The recommendations reported here represent guidelines for healthy individuals and those not suffering from a sleep disorder. Sleep durations outside the recommended range may be appropriate, but deviating far from the normal range is rare. Individuals who habitually sleep outside the normal range may be exhibiting signs or symptoms of serious health problems or, if done volitionally, may be compromising their health and well-being.