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The Effects of Sleep Restriction and Extension on School-Age Children: What a Difference an Hour Makes

  • Tel Aviv University, and The College of Law & Business, Ramat Gan

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This study assessed the effects of modest sleep restriction and extension on children's neurobehavioral functioning (NBF). The sleep of 77 children (age: M = 10.6 years; range = 9.1-12.2 years) was monitored for 5 nights with activity monitors. These children (39 boys and 38 girls) were all attending regular 4th- and 6th-grade classes. Their NBF was assessed using computerized tests on the 2nd day of their normal sleep schedule. On the 3rd evening, the children were asked to extend or restrict their sleep by an hour on the following 3 nights. Their NBF was reassessed on the 6th day following the experimental sleep manipulation. Sleep restriction led to improved sleep quality and to reduced reported alertness. The sleep manipulation led to significant differential effects on NBF measures. These effects may have significant developmental and clinical implications.
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The Effects of Sleep Restriction and Extension on School-Age Children:
What a Difference an Hour Makes
Avi Sadeh, Reut Gruber, and Amiram Raviv
This study assessed the effects of modest sleep restriction and extension on children’s neurobehavioral
functioning (NBF). The sleep of 77 children (age: M510.6 years; range 59.1–12.2 years) was monitored for 5
nights with activity monitors. These children (39 boys and 38 girls) were all attending regular 4th- and 6th-
grade classes. Their NBF was assessed using computerized tests on the 2nd day of their normal sleep schedule.
On the 3rd evening, the children were asked to extend or restrict their sleep by an hour on the following 3
nights. Their NBF was reassessed on the 6th day following the experimental sleep manipulation. Sleep
restriction led to improved sleep quality and to reduced reported alertness. The sleep manipulation led to
significant differential effects on NBF measures. These effects may have significant developmental and clinical
The role of sleep in learning, memory, and other
neurobehavioral functions has been extensively
studied. It has been demonstrated that experimental
manipulations of sleep can influence learning
and memory function and that intensified
learning and training can influence sleep or have
correlates in brain functioning during sleep (Maquet,
2001; Pilcher & Huffcutt, 1996). However, limited
experimental research has been focused on the role
of sleep restriction and extension in child develop-
In a recent study we identified a significant
relationship between sleep fragmentation and neu-
robehavioral functioning (NBF) in school-age chil-
dren (Sadeh, Gruber, & Raviv, 2002). We found that
an increased number of night wakings and lower
sleep efficiency were associated with compromised
NBF. Sleep duration was not correlated with NBF in
this correlative naturalistic study. The goal of the
present study was to assess the effects of moderate
experimental changes in sleep duration on NBF in
school-age children.
Sleep and NBF in Children
Many studies have demonstrated that sleep
problems and sleep fragmentation are associated
with learning difficulties or with compromised NBF
(Blunden, Lushington, & Kennedy, 2001; Gozal,
1998; Sadeh et al., 2002). However, the correlative
nature of these studies precludes any causal inter-
Most naturalistic studies have failed to document
relationships between sleep duration per se and
school performance or NBF. In some studies, an
inconsistent or a phase-shifted sleep schedule was
correlated with poorer functioning (Bates, Viken,
Alexander, Beyers, & Stockton, 2002; Epstein,
Chillag, & Lavie, 1998; Meijer, Habekothe, & van
den Wittenboer, 2000; Wolfson & Carskadon, 1998).
The most direct information on the effects of sleep
duration on NBF comes from studies that have used
sleep deprivation or sleep restriction and extension
The effects of sleep deprivation and sleep restric-
tion on NBF have been studied extensively in adults
(Bonnet, 1994; Pilcher & Huffcutt, 1996). The most
profound effects of sleep deprivation have been
documented in the area of cognitive or NBF (Bonnet,
1994; Peigneux, Laureys, Delbeuck, & Maquet, 2001;
Pilcher & Huffcutt, 1996). Pilcher and Huffcutt
(1996) performed a meta-analysis of 56 sleep-
deprivation studies and concluded that sleep depri-
vation leads to a significant impairment to human
performance. Recent studies have suggested that
executive control, located in the prefrontal cortex, is
the system that is most sensitive to sleep depriva-
tion, sleep disorders, or reduced alertness (Dahl,
1996; Drummond & Brown, 2001; Horne, 1993; Jones
& Harrison, 2001).
r2003 by the Society for Research in Child Development, Inc.
All rights reserved. 0009-3920/2003/7402-0008
Avi Sadeh, Reut Gruber, and Amiram Raviv, Department of
Psychology, Tel Aviv University, Israel.
This study was supported by the Israel Ministry of Education
and by Helene and Woolf Marmot. The authors are thankful to
Alona Raviv, Ornit Arbel, and Jeri Hahn-Markowitz for their help
in preparing this manuscript.
Correspondence concerning this article should be sent to Avi
Sadeh, Department of Psychology, Tel-Aviv University, Ramat
Aviv 69978, Israel. Electronic mail may be sent to sadeh@post.-
Child Development, March/April 2003, Volume 74, Number 2, Pages 444–455
Only a small number of sleep-deprivation studies
have been performed with children, and their
conclusions were not consistent (Carskadon, Harvey,
& Dement, 1981a, 1981b; Fallone, Acebo, Arnedt,
Seifer, & Carskadon, 2001; Randazzo, Muehlbach,
Schweitzer, & Walsh, 1998). In studying the effects of
full-night sleep deprivation (Carskadon et al., 1981b)
and 4-hr sleep restriction (Carskadon et al., 1981a),
Carskadon and colleagues reported compromised
functioning only following the full-night depriva-
tion, suggesting the sleep restriction may not lead to
significant consequences. Recent research challenges
these findings and suggests that sleep restriction
does lead to detectable deficits in NBF and that
tracking these consequences may depend on the
level of complexity of NBF that is tested. For
example, Randazzo et al. (1998) compared the
performance of children following sleep restriction
to 5 hr in bed with the performance of a control
group with 11 hr in bed. Compared with the control
group, performance after 5 hr in bed was poorer on
measures of verbal creativity and on the Wisconsin
Card Sorting Test. No differences were found on less
complex memory tasks (Randazzo et al., 1998). In a
similar study, Fallone et al. (2001) compared children
and adolescents (8 to 15 years of age) following a
night of optimized sleep (based on their normal
sleep habits) with children following sleep restric-
tion to 4 hr of sleep. Following sleep restriction, the
children were more sleepy and inattentive. How-
ever, tests of response inhibition and sustained
attention revealed no significant differences in
performance. The results of these sleep-restriction
studies suggest that the effects of modest sleep
deprivation could be detected by exploring specific
areas of NBF that are most sensitive to variations in
sleep and alertness (i.e., complex tasks that require
executive control).
From a slightly different angle, early school start
time could also be considered as a sleep-restricted
schedule (Carskadon, Wolfson, Acebo, Tzischinsky,
& Seifer, 1998; Epstein et al., 1998). Using ques-
tionnaire-based methods, these studies indicated
that early school start time is associated with shorter
sleep, increased daytime sleepiness, poorer concen-
tration, and attention problems (Epstein et al., 1998).
Sleep debt and the associated reduced alertness
could result from an acute event of extreme sleep
deprivation (e.g., a single sleepless night) or by
gradual accumulated sleep loss (e.g., a few succes-
sive nights of modest or moderate sleep restriction).
This topic of acute versus accumulated sleep loss
relates to whether people can adjust to a gradual
‘‘sleep diet’’ and learn to compensate physiologically
by improving sleep quality or to adapt to function-
ing with less sleep. Studies on cumulative sleep
restriction have shown cumulative negative effects
on NBF, daytime and nocturnal EEG, mood, and
sense of well-being (Dinges et al., 1997; Drake et al.,
2001). In an interesting study, Drake et al. (2001)
compared rapid versus cumulative sleep loss of 8 hr
and found more significant impairments on tests of
alertness, memory, and performance following rapid
sleep loss compared with the slow accumulation of a
comparable amount of sleep loss. The authors
concluded that some compensatory adaptive me-
chanisms are involved in cumulative sleep loss and
thus mitigate its effects. This topic of the accumu-
lative effects of modest sleep loss has never been
studied in children. The purpose of our study was to
examine the effects of 3 nights of modest (71 hr)
sleep restriction or extension on children’s NBF.
Goals of the Present Study
Our review of the literature detected only a small
number of studies that have experimentally tested
the effects of sleep restriction and extension in
children. All these studies were conducted in the
laboratory and were based on a single night of
drastic curtailment of sleep.
The daily struggles between children and their
parents usually occur at home and are often limited
to modest changes in sleep. Persistent battles on
topics such as ‘‘just one more TV show’’ raise the
scientific question ‘‘What difference does an hour
make?’’ The goal of the present study was to
investigate the effects of 1 hr of sleep restriction or
extension, maintained on 3 successive nights at
home, on NBF in children. To increase sensitivity
of the design, our protocol was based on repeated
(baseline-manipulation) testing design.
We designed our research to test the following
three hypotheses: (a) most children would be able to
restrict or extend their sleep on demand in their
natural home environment, (b) sleep restriction
would lead to improved sleep quality compared
with sleep extension, and (c) sleep restriction would
lead to an increase in reported fatigue and to
compromised NBF compared with sleep extension.
Seventy-seven children, 39 boys and 38 girls,
participated in the study. These children participated
in an earlier study (Sadeh et al., 2002) and they all
Sleep Restriction and Extension 445
agreed to participate in this second study when
approached 2 years later (100% consent from
available children and their parents). The study
was approved and supported by the Israel Ministry
of Education. Participating children and their par-
ents signed informed consent forms.
The children were recruited from regular classes
in two distinct age groups: fourth grade (N542, M
age 59.80 years, SD 5.64) and sixth grade (N535;
age: M511.58 years, SD 5.50). Two classes for each
grade level were included in this sample. An early
attempt to include second-grade students indicated
that younger children and their parents found it
more difficult to comply with the sleep restriction
and extension requirements of the study; therefore,
second-grade students were not included.
Most of the children were living with both parents
(90.9%), and slightly less than half (42.1%) were first
born. Parents’ ages ranged from 32 to 55 (age of
fathers: M543.57 years, SD 54.53; age of mothers:
M540.43 years; SD 54.28). Number of children in
the family ranged from one to seven (M52.96,
SD 51.03). Most fathers (97.2%) and about half of
the mothers (50.7%) held a full-time job.
Exclusion criteria included the following: (a)
acute or chronic physical illness, (b) use of medica-
tion, or (c) reported developmental or psychiatric
Each child completed the study according to a 6-
day protocol, which overlapped with the Israeli 6-
day school week (Sunday to Friday). On Day 1, each
child received a package that included the actigraph
and daily reports that were used to assess sleep and
related parameters over the 6-day period. During
Days 1 and 2, the child was instructed to sleep as he
or she regularly sleeps. In the morning of Day 1 or 2
(between 8:00 a.m. and 10:00 a.m.) the child’s
baseline NBF was tested using the Neuropsycholo-
gical Evaluation System (NES; Arcia, Ornstein, &
Otto, 1991; Sadeh et al., 2002).
In the afternoon of Day 3, the children and their
parents received a phone call indicating to them how
to modify the child’s sleep schedule for the follow-
ing 3 days. According to a random assignment, 40
children were asked to go to sleep 1 hr earlier and 37
were asked to go to sleep 1 hr later than their regular
bedtime (see Figure 1 for examples of responsive
and nonresponsive children). Previous research
showed that the morning rise time is robust (around
7:00 a.m.) during school days (Sadeh, Raviv, &
Gruber, 2000). On the morning of Day 6, after 3
consecutive nights of required alteration of sleep
schedule, the children were retested with the NES at
the same time they had been tested in the morning of
their first test administration (between 8:00 a.m. and
10:00 a.m.). This schedule was stricly adhered to in
order to control for time-of-day effects on NBF
(Sadeh et al., 2002). The study was performed during
the school year between November and May.
The main instruments used in this study for
assessing sleep and NBF have been used and
validated in developmental research (Sadeh et al.,
2002; Sadeh et al., 2000).
Actigraphy. Activity monitoring and daily sleep
logs were used to assess sleep–wake patterns. The
actigraph is a wristwatch-like device that uses a
piezo-electric beam to detect movement. The de-
tected movements are translated into digital counts
accumulated across predesigned epoch intervals
(e.g., 1 min) and stored in the internal memory. The
actigraph can collect data continuously over an
extended period (1 week or longer). Data are
downloaded to the computer using special interface
Actigraphy has been established as a reliable and
valid method for the naturalistic study of sleep in
infants, children, and adults (Sadeh & Acebo, 2002;
Sadeh, Hauri, Kripke, & Lavie, 1995). Recent studies
have also demonstrated good reliability of these
actigraphic measures (Acebo et al., 1999; Sadeh et al.,
2002; Sadeh et al., 2000).
The children were asked to attach the miniature
actigraph (a wristwatch-like device, Mini Motion-
logger, Ambulatory Monitoring Inc.) to their non-
dominant wrist in the evening when preparing for
sleep and to remove it in the morning (see Figure 1).
Sleep assessment was performed for 5 continuous
nights during school days. The actigraphs collected
data in 1-min epochs and in amplifier setting 18,
which is the standard mode for sleep–wake
scoring. Actigraphic files were analyzed with the
Actigraphic Scoring Analysis program (ASA) for an
IBM-compatible PC that provides validated sleep–
wake measures (Sadeh, Sharkey, & Carskadon,
Actigraphic sleep measures included: (a) sleep
onset time, (b) morning rise time, (c) sleep period-
Ftotal time from sleep onset time to morning
awakening time, (d) true sleep timeFsleep time
excluding all periods of wakefulness, (e) sleep
percentFpercentage of true sleep time (Measure 4)
from total sleep period (Measure 3), (f) number of
446 Sadeh, Gruber, and Raviv
night wakings, and (g) quiet sleepFpercentage of
motionless sleep.
Daily sleep–wake diaries. The subjective daily in-
formation reported by the children included the
following measures: (a) lights-off time, (b) morning
rise time, (c) number of night wakings, (d) sleep
qualityFa 4-point scale ranging from 0 (very good)to
3(bad), (e) duration to fall asleepFa 4-point scale
ranging from 0 (less than 5 min)to3(more than 30
min), (f) evening fatigueFa 3-point scale ranging
from 0 (very alert)to2(very sleepy), and (g) morning
fatigueFa 3-point scale ranging from 0 (very alert)to
2(very sleepy). These measures have been used and
validated in previous research (Sadeh et al., 2000).
NES. The NES was originally developed for
adults but it has been successfully used with
school-age children (Arcia et al., 1991; Sadeh et al.,
2002). In a recent study, the NES measures demon-
strated good test–retest reliability and were sensitive
to sleep and time-of-day variations (Sadeh et al.,
The tests were presented to the children by a
research assistant who also monitored their perfor-
mance on the practice trials and provided further
guidance when needed. Once the practice trials were
completed on each test, the children continued to the
test trials.
The children were tested twice (baseline and
postintervention) with the NES installed on a
Compaq notebook computer (Contura model). Six
age-appropriate tests were administered:
1. Finger tapping test. Task: to tap as fast as
possible with one finger on a single button.
Tested domain: motor speed. Variable: max-
imum number of taps.
2. Simple reaction-time test. Task: to press a
button as quickly as possible when a large
square appears on the screen. Tested domains:
vigilance and motor reaction. Variable: average
reaction time.
3. Continuous performance test (CPT). Task: to
respond as fast as possible to a specific animal
presented and to avoid responding to any
other animal. Tested domains: sustained visual
attention, response inhibition, and motor
20 22 00 02 04 06 08
Day 1
Day 2
Day 3
Day 4
Day 5
Day 1
Day 2
Day 3
Day 4
Day 5
Time of Day (Hour) Time of Day (Hour)
Child A Child B
Child C Child D
20 22 00 02 04 06 08
Figure 1. Examples of children’s responses to the sleep restriction and extension protocol: Raw nocturnal activity data of 4 children (A, B,
C, and D). Each panel represents the raw activity data of 1 child for 5 consecutive nights. Dark areas represent increased activity level
associated with wakefulness (before sleep onset, after morning awakening time, and during night wakings). Child A responded to the
sleep restriction protocol and fell asleep significantly later on the 3 manipulation nights (starting on the third night). Child B responded to
the sleep extension protocol and fell asleep significantly earlier on the 3 manipulation nights. Children C and D did not respond to the
experimental manipulation.
Sleep Restriction and Extension 447
speed. Variables: average reaction time, omis-
sion errors (not responding to target stimulus),
and commission errors (responding to non-
target stimulus).
4. Symbol–digit substitution (SDS). Task: Nine
symbols and nine digits are paired at the top of
the screen and the child is requested to press
the digits on the keyboard corresponding to a
test set of the nine symbols presented in a
mixed order. Six sets of nine symbol–digit pairs
were presented in succession. Tested domains:
visual memory, visual scanning, visual-motor
speed. Variable: average response latency for
completing each set.
5. Visual digit span test. Task: to recall presented
sequences of digits and to repeat the sequence
on the computer keyboard (forward) or to
repeat the digits in reversed order (backward).
Longer spans are increasingly presented until
the child makes two errors in a span length.
Tested domains: working memory, attention.
Variables: lengths of the longest span answered
correctly forward and backward.
6. Serial digit learning test. Task: to recall a long
sequence of single digits presented in succes-
sion. The same sequence of digits is repeated
until either the child recalls the entire sequence
correctly or the maximum of eight trials is
reached. Tested domain: working memory,
learning strategies. Variable: an error score that
is the sum of the errors over all trials
The Effects of the Experimental Manipulation on Sleep
To assess the effects of the experimental manip-
ulation on the actigraphic sleep measures and
the subjective reports, we used ANOVAs with
gender, age (fourth and sixth grades), and group
(sleep-restriction or sleep-extension group) as the
between-subject variables, and period (baseline vs.
intervention) as the within-subject independent
variable. Actigraphic and subjective sleep measures
were used as the dependent variables (see Table 1).
Significant Group Period interaction effects
were found for the following actigraphic sleep meas-
ures (see Figure 2): sleep onset time, sleep period,
sleep percent, true sleep time, quiet sleep, and
The Effects of Sleep Manipulation on Sleep Measures: Means (7SDs) and F Values
Sleep measure Sleep restricted Sleep extended F(1, 69) Time
Sleep onset time (hr) 139.17
Baseline 22.237.52 22.207.73
Intervention 23.017.68 21.567.59
Morning rise time (hr) 2.47
Baseline 6.967.36 6.817.30
Intervention 7.047.43 6.747.29
Sleep period (min) 88.66
Baseline 523.7729.7 516.3743.5
Intervention 482.1736.2 551.0734.7
True sleep time (min) 69.44
Baseline 488.6729.3 487.7743.0
Intervention 457.1738.3 516.9740.2
Sleep percent (%) 8.50
Baseline 93.3373.54 94.5073.74
Intervention 94.7873.02 93.7773.48
Night wakings (N) 10.46
Baseline 1.6471.18 1.3471.22
Intervention 1.2070.89 1.8171.25
Quiet sleep (%) 6.03
Baseline 70.0079.08 71.7079.97
Intervention 71.5579.68 70.0078.68
448 Sadeh, Gruber, and Raviv
number of night wakings. These interactions re-
flected the fact that sleep was significantly extended
from baseline to intervention period in the sleep-
extension group (by an average of 35 min) and that
sleep was significantly shortened in the sleep-
restriction group (41 min). These effects resulted
from the significant changes in sleep onset, whereas
morning rise time was not affected. In addition, the
results reflect changes in sleep quality in response to
the manipulation. Sleep quality was significantly
improved in the sleep-restriction group as mani-
fested in increased sleep percent and quiet sleep and
reduced number of night wakings following inter-
vention, whereas the opposite changes occurred in
the sleep-extension group.
Significant Group Period interactions were also
found on the following subjective measures (see
Figure 2): reported evening fatigue, F(4, 61) 58.61,
po.001; predicted sleep latency, F(4, 61) 52.80,
po.05; and reported sleep latency, F(4, 61) 53.40,
po.01. No significant interactions were found for
reported sleep quality and reported morning alert-
ness. The significant interactions (see Figure 2)
indicated that compared with advancing sleep onset,
delaying sleep onset resulted in increased evening
fatigue and predicted and reported shorter sleep
The analyses revealed significant age differences.
Compared with the younger age group (fourth
grade), older children (sixth grade) had delayed
sleep onset time, F(1, 69) 541.25, po.001; shorter
sleep period, F(1, 69) 535.65, po.001; shorter true
sleep time, F(1, 69) 523.03, po.001; and increased
percent of quiet sleep, F(1, 69) 56.7, po.05. Signifi-
cant gender differences were also found. Compared
with boys, girls had higher sleep percent, F(1, 69) 5
7.42, po.01, and higher quiet sleep percent,
F(1, 69) 514.83, po.001.
Figure 2. Effects of the experimental manipulation on actigraphic and reported sleep measures.
po.05 in post hoc comparisons (extension
vs. restriction). Arrows indicate point of experimental intervention.
Sleep Restriction and Extension 449
To examine individual compliance with our
experimental manipulation of sleep, we set a
criterion that compliance would be defined as
restriction or extension (according to the assign-
ment) of sleep period by an average of at least 30
min. Sixty-five percent of the children in the sleep-
restriction group and 62% of the children in the
sleep-extension group met the compliance criteria.
Thirty-six percent of the children failed to extend or
restrict their sleep by an average of 30 min or longer
(14 children from each manipulation group, simi-
larly distributed in the two age groups). No other
behavioral or background variables distinguished
between the compliant and noncompliant partici-
The Effects of the Experimental Manipulation on NBF
To analyze the effects of the experimental manip-
ulation on NBF, we divided the participants into
three groups according to the participants’ success in
meeting the demands of the sleep manipulation.
Children who extended their sleep by an average of
30 min or more during the intervention days were
defined as the sleep-extension group (SEG). Chil-
dren who shortened their sleep by an average of 30
min or more were defined as the sleep-restriction
group (SRG). Children who failed to extend or
shorten their sleep by at least 30 min were defined as
the no-change group (NCG). Because of technical
failures in one of the two administrations of the NES
in 5 children, only 72 children were included in the
final analyses (SEG: N521; SRG: N528; NCG:
The analyses were based on ANOVAs with
gender, age (fourth and sixth grades), and Group
(SRG, SEG, and NCG) as the between-subject
independent variables, and period (baseline vs.
intervention) as the within-subject repeated inde-
pendent variable. The NES measures were used as
the dependent variables (see Table 2).
Significant Group Period interactions were
found on three NES measures (see Figure 3): simple
reaction time, digit forward, and the reaction time on
the CPT. These interactions and the post hoc tests
indicated that children who extended their sleep
significantly improved their performance (from
baseline to postintervention period) on the digit
forward memory test, whereas the performance of
the other groups did not change. On the CPT,
children in the SEG significantly improved their
reaction time, whereas the performance of children
in the other groups (SRG and NCG) did not change
significantly. On the simple reaction time test,
performance of the children from the SRG
and the NCG significantly deteriorated whereas
performance of the children from the SEG remained
Additional Findings
The NES measures were found to be sensitive to
age differences. Compared with the younger chil-
dren, older children had higher numbers of finger
tappings, F(1, 60) 58.22, po.01; shorter simple reac-
tion times, F(1, 60) 56.82, po.05; shorter reaction
time on symbol–digit test, F(1, 60) 525.21, po.001;
higher scores on digit forward test, F(1, 60) 516.90,
po.001; higher scores on digit backward test,
F(1, 60) 516.86, po.001; shorter reaction times on
the CPT, F(1, 60) 512.79, po.001; and better scores
on the digit learning test, F(1, 60) 514.84, po.001.
Gender differences were found on one NES measure.
Compared with girls, boys had higher numbers of
finger tappings, F(1, 60) 58.04, po.01.
Significant main period (practice) effects were
also found, reflecting the repeated testing effects.
Compared with the first administration, perfor-
mance on the second administration was character-
ized by longer reaction times on the simple reaction
time test, F(1, 60) 516.18, po.001; shorter latencies
on the symbol–digit substitution test, F(1, 60) 5
18.67, po.001; higher scores on the digit backward
memory test, F(1, 60) 54.83, po.05; and better
performance on the digit learning test,
F(1, 60) 510.01, po.005.
Our study was aimed at exploring the effects of
manipulating sleep time on NBF of normal children.
Whereas most of the existing literature is based on
drastic experimental manipulation of sleep, we
tested the effects of a modest manipulation that we
consider more similar to everyday life experiences of
children and their parents. The use of actigraphy
enabled this intervention study in the natural
environment of the children. However, it should be
noted that actigraphic sleep assessment is based on
activity measurement and some errors are likely to
occur compared with polysomnographic sleep mea-
sures. Our results show that most children were
motivated enough and were able to comply and
extend or restrict their sleep according to their
random assignment.
The manipulation of sleep time resulted in an
average reduction of 41 min from the sleep period in
the SRG on 3 consecutive nights. Children in the SEG
450 Sadeh, Gruber, and Raviv
extended their sleep period by an average of 35 min.
These results indicate that most children can extend
or restrict their sleep period on demand with a small
incentive. Furthermore, most of the children who
went to sleep earlier managed to fall asleep earlier
than their regular bedtime. These findings are
consistent with earlier reports, based on laboratory
studies, that children and adults can extend their
sleep given the opportunity of extended bedtime
period (Carskadon, Keenan, & Dement, 1987; Webb,
The manipulation of sleep time resulted in
significant changes in sleep quality measures.
Sleep extension led to a significant increase in the
number of night wakings and to a reduction of
sleep percent. The opposite was true for sleep
restriction. These effects are in accord with earlier
findings of increased slow-wave sleep and
sleep efficiency on subsequent nights following
experimental sleep restriction (Devoto, Lucidi, Vio-
lani, & Bertini, 1999; Webb & Agnew, 1975). These
results have been attributed to the work of physio-
logical compensatory mechanisms that regulate
sleep physiology in response to variations in sleep
The operation of these compensatory mechanisms
that lead to improvement of sleep quality in
response to sleep restriction strengthens the question
of whether these small variations in sleep duration
could lead to any detectable effects on alertness and
NBF. Our results suggest that in spite of the
operation of these compensatory mechanisms, the
subjective reports and the NBF of the children
echoed the changes in sleep duration.
The Effects of Sleep Manipulation (Group) on Neurobehavioral Functioning: Means (7SDs) and F Values
NES measure Sleep restricted No change Sleep extended F(1, 61) Time F(2, 61) Time
Tapping 0.00 0.28
Baseline 149.8715.0 152.8720.4 151.2717.8
Intervention 149.7714.9 152.2719.3 151.5718.6
Simple RT 16.2
Baseline 431.4782.5 412.2773.1 414.2750.2
Intervention 458.2777.1 461.7774.6 418.7758.4
Symbol–Digit RL 18.7
Baseline 24297399 25307504 24057411
Intervention 23377415 23357421 22757390
CPT–RT 0.98 6.74
Baseline 641.0755.7 633.3745.4 615.8773.5
Intervention 639.9761.1 650.1760.9 587.8767.8
CPT–Om Err 0.02 0.28
Baseline 1.5771.17 1.4371.56 1.0070.63
Intervention 1.3271.09 1.4870.90 1.0071.04
CPT–Com Err 0.18 0.75
Baseline 0.8971.42 0.5771.04 0.4871.33
Intervention 1.0371.29 0.8371.03 0.2970.46
Digit span FW 0.05 3.25
Baseline 5.6170.69 5.1770.83 5.4370.98
Intervention 5.2570.89 5.2271.09 5.7170.90
Digit span BW 4.83
Baseline 4.1470.89 4.3571.07 4.4371.29
Intervention 4.3671.16 4.5271.04 5.0571.32
Digit learning ES 10.00
Baseline 2.7972.69 3.4373.64 2.6772.13
Intervention 2.0471.57 2.3072.30 1.7172.45
Note. Intervention groups: neurobehavioral (NES) measures: tapping 5number of finger tappings, RL 5response latency, Om
Err 5omissions errors, Com Err 5commissions errors, FW 5forward, BW 5backward, ES 5error score.
Sleep Restriction and Extension 451
The subjective daily reports reflected significant
effects of the experimental manipulation on the
children’s perceived fatigue and sleepiness. These
changes included significantly higher ratings of
fatigue in the evening, and reported predicted and
estimated shorter sleep latency following sleep
restriction compared with sleep extension. These
results are consistent with earlier findings, based on
the Multiple Sleep Latency Test, showing reduced
sleep latencies in children following sleep restriction
(Carskadon et al., 1981b).
Before addressing the effects of the experimental
manipulation on NBF we should note that signifi-
cant repeated measurement effects were found from
Figure 3. Effects of the experimental manipulation on neurobehavioral functioning. SRG 5sleep-restricted group; SEG 5sleep-extended
group; NCG 5no-change group.
po.05 in post hoc comparisons (intervention vs. baseline).
452 Sadeh, Gruber, and Raviv
baseline to intervention assessment on some of the
NBF measures. For instance, on the simple reaction
time, overall the children’s performance on the
second administration was worse (slower reaction
time) than on the first administration. This could be
attributed to the children’s loss of interest because of
the repetitive and ‘‘boring’’ nature of the task.
However, because there is no reason to assume
distinct practice effects (other then those attributed
to the manipulation itself), the interaction between
the manipulation group and administration (base-
line vs. intervention) could be attributed only to the
effect of the manipulation.
In addition, the experimental manipulation of
sleep duration led to distinct effects on performance
patterns on a number of neurobehavioral tests. The
significant Group Period interaction on the digit
forward memory test indicated that extension of
sleep lead to improved memory function as com-
pared with sleep restriction or no change in sleep
duration. Furthermore, sleep extension led to im-
proved performance on the CPT. Sleep extension
maintained performance on a simple reaction time
test, whereas performance was significantly when
sleep was restricted or when there was no change in
sleep duration. These findings suggest that moder-
ate changes in sleep duration have detectable
significant effects on children’s neuropsychological
The effects on NBF on the CPT, reaction time, and
memory tests have significant implications for
learning and school performance. These measures
have been found to be significantly correlated with
classroom behaviors and achievement tests (Arcia et
al., 1991). For instance, digit span scores were highly
correlated with reading (r5.56) and mathematics
(r5.58) scores on the California Achievement Test.
For better appreciation of the size of the manipula-
tion effects, it should be noted that the size of the
differential effect of the extension–restriction manip-
ulation on the NES measures was larger than or
similar to the highly significant age differences
between the fourth- and sixth-grade students on
these measures. It could be interpreted that the
manipulation effects on these neurobehavioral func-
tions are similar to those gained by 2 years of
It is also important to emphasize that the CPT,
which was found to be sensitive to sleep extension
and restriction in this study, was also found to be
sensitive to sleep fragmentation in our earlier study
(Sadeh et al., 2002). The CPT is a task that has been
associated with sustained attention and behavioral
inhibition (Corkum & Siegel, 1993). Behavioral
inhibition has become a key construct in under-
standing developmental psychopathology (Barkley,
1997; Gray, 1990; Nigg, 2000). Therefore, our findings
suggest that the consequences of variations in sleep
duration could be widespread, with developmental
and clinical implications.
Our findings that modest modifications of sleep
time have significant effects on NBF may appear in
conflict with our earlier findings that under normal
sleep conditions, sleep time was not correlated with
NBF (Sadeh et al., 2002). However, the absence of
significant correlations does not imply that the
children in our naturalistic study were getting
sufficient sleep or that the two phenomena are not
related. Theoretically, similar results could have
been obtained if the children were all sleep deprived
or were getting excessive sleep. Earlier research has
demonstrated that alertness and NBF could be
compromised by either fragmented sleep (Jones &
Harrison, 2001; Wesensten, Balkin, & Belenky, 1999)
or by insufficient sleep (Drummond & Brown, 2001;
Pilcher & Huffcutt, 1996). Our studies suggest that
these effects are highly relevant during childhood
and that children are sensitive to modest alteration
of their natural sleep duration.
Our results have significant clinical and educa-
tional implications. They highlight the need for
parents and professionals to be aware of the
consequences of insufficient sleep in children and
the potential benefits of sleep extension. The results
suggest that most children can extend their sleep
and gain demonstrable benefits from even modest
sleep extension. From a clinical perspective, it has
been suggested that the consequences of insufficient
sleep could also affect behavioral regulation and
lead to or exacerbate developmental psychopathol-
ogy (Dahl, 1996). Professionals should consider
whether children who present with clinical problems
associated with insufficient sleep could benefit from
better management of their sleep schedule.
We regret that the results of our study, as well as
many other studies in the field, do not provide a
clear answer to the question of how much sleep is
needed for children at different ages. Our results
emphasize, however, that for the individual child,
variations in sleep duration could have a clear
impact on his or her NBF. Parents and child care
professionals can explore the appropriate sleep
needs of a specific child by experimenting with
extending or restricting sleep, tracking the changes
in the child’s behavior and well-being, and finding
the child’s optimal sleep needs. We believe that this
is done intuitively, if not systematically, by many
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Sleep Restriction and Extension 455
... As suggested by the improved sleep efficiency found in the experiment, the impact of air quality on cognitive performance, could perhaps, at least partly be explained by improved sleep quality. It is well-established that sleep deprivation has a negative effect on various aspects of cognitive performance, e.g., impaired executive functions, working memory, and reaction time [9], with even minor restrictions in sleep leading to poorer performance [10]. On this background, the present study investigated whether CO 2 levels alone or in combination with other bioeffluents, both considered major sources of pollution during the night, influence sleep quality and next-morning cognitive performance in schoolchildren. ...
... One plausible explanation for this result is that poor indoor air quality during sleep does not disturb sleep to a degree that will affect next-morning cognitive performance. However, other studies have shown an effect of poor air quality on several cognitive functions both when performing schoolwork or office work [1][2][3]10,17,18]. ...
Full-text available
Objectives: To investigate the effect of CO2 during sleep on next-morning cognitive performance in young schoolchildren, the authors performed a double-blind fully balanced crossover placebo-controlled study. Material and methods: The authors included 36 children aged 10-12 years in the climate chamber. The children slept at 21°C in 6 groups each at 3 different conditions separated by 7 days in a random order. Conditions were as follows: high ventilation with CO2 at 700 ppm, high ventilation with added pure CO2 at 2000-3000 ppm, and reduced ventilation with CO2 at 2-3000 ppm and bioeffluents. Children were subjected to a digital cognitive test battery (CANTAB) in the evening prior to sleep and on the next morning after breakfast. Sleep quality was monitored with wrist actigraphs. Results: There were no significant exposure effects on cognitive performance. Sleep efficiency was significantly lower at high ventilation with CO2 at 700 ppm which is considered to be a chance effect. No other effects were seen, and no relation between air quality during sleep and next-morning cognitive performance was observed in the children emitting an estimated 10 lCO2/h per child. Conclusions: No effect of CO2 during sleep was found on next day cognition. The children were awakened in the morning, and spent from 45-70 min in well-ventilated rooms before they were tested. Hence, it cannot be precluded that the children have benefitted from the good indoor air quality conditions before and during the testing period. The slightly better sleep efficiency during high CO2 concentrations might be a chance finding. Hence, replication is needed in actual bedrooms controlling for other external factors before any generalizations can be made.
... 31 Experimental manipulations significantly restricting or fragmenting sleep in youth are scarce, partly due to ethical constraints. Still, such studies have demonstrated compromised neurobehavioral and affective functioning following restricted sleep in infants, 34 children, 35,36 and adolescents. 37,38 It is important to note that pediatric insomnia may be detrimental not only for the young person but also for their family members. ...
Insomnia is the most prevalent sleep disorder in youth, tends to persist over time, and is associated with a myriad of adverse outcomes. This paper synthesizes the current evidence regarding the phenomenology, prevalence, assessment, consequences, etiology, and treatment of pediatric insomnia, highlighting areas that warrant further research, and addressing the unique characteristics of this disorder in infants, children, and adolescents.
... Given that aspects of adolescent sleep are complex and may interact (El-Sheikh et al., 2019), it is important to consider multiple sleep variables and potential subgroups of adolescent sleepers that may exist. For instance, youth who exhibit sleep problems in one domain (e.g., sleep deprivation) may compensate for this loss by improving other components of sleep (e.g., quality; Sadeh et al., 2003), which may or may not protect against mental health difficulties. On the other hand, adolescents who exhibit problematic sleep in multiple areas (e.g., shorter sleep and poor sleep quality) may be at increased risk for mental health problems (El-Sheikh et al., 2019). ...
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Adolescent sleep and mental health are closely linked; however, less is known regarding how unique patterns of sleep influence youth mental health. This study aimed to identify subgroups of adolescent sleepers, demographic predictors of subgroup membership, and their prospective links with mental health outcomes. Youth from the National Longitudinal Study of Adolescent to Adult Health (N = 5411; 51.8% female) self-reported sleep (duration, sufficiency, problems, bedtime), depressive symptoms, alcohol use, cannabis use, and demographics at baseline (W1; 1994–1995; Mage = 15.06) and 1 year later (W2; 1996). Latent profile analysis revealed three sleep profiles: Optimal (highest quantity/quality, earliest bedtime), Low-Quantity/Later Bedtime (lowest duration/sufficiency, latest bedtime), and Low-Quality (highest problems). Several demographic covariates were associated with profiles. Less-optimal profiles were associated with greater W2 depressive symptoms and substance use, controlling for W1 levels. Youth with low-quantity/later bedtimes were especially at-risk for cannabis use. Results may inform interventions seeking to improve adolescent mental health by targeting multiple aspects of sleep.
... at 12-18 months was proportionately related to strong impulse control at ages 2 and 4 [49,50], others have not observed any longitudinal association with measurements taken at 4-7 and 9-16 years [51]. However, experimental research has demonstrated extending sleep by just half an hour a night enhances attention and inhibition in children, at least in the short term [52]. Overall, it would seem that sufficient levels of sleep, independent of sedentary time and physical activity, are advantageous for the development of appropriate inhibitory control in Table 3 Cross-sectional and longitudinal associations between time-use and inhibitory control, self-regulation, and mental wellbeing at 5 years of age All analyses adjusted for sex, deprivation, snoring, BMI z-score, and randomised group and analysed using compositional analysis that takes into account all time-use variables. ...
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Background Good quality sleep, regular physical activity, and limited time spent sedentary are all considered individually important in promoting good mental health in children. However, few studies have examined the influence of each behaviour simultaneously, using compositional analysis which accounts for the closed nature of the 24-h day. Our aim was to determine how compositional time use in early childhood is prospectively related to mental and psychosocial health at 5 years of age. Methods A total of 392 children wore Actical accelerometers 24-h a day for one week at 2, 3.5 and 5 years of age to examine time in sleep, physical activity, and sedentary behaviour. Psychosocial and mental health were assessed at age 5 using both laboratory based (researcher-assessed) and questionnaire (parental-report) measures. Associations were estimated using regression models with isometric log-ratios of time-use components as predictors. Results Cross-sectionally, 5-year old children who spent 10% (64 min) more time asleep than average had better inhibitory control (standardised mean difference [ d ]; 0.19; 95% confidence interal [CI]: 0.02, 0.36 for Statue test and d = 0.16; 95% CI: − 0.01, 0.33 for Heads–Toes–Knees–Shoulders task). A greater proportion of time spent active (10%, 31 min) was associated with poorer inhibitory control ( d = − 0.07; 95% CI: − 0.13, − 0.02 for Statue test, d = − 0.06; 95% CI: − 0.11, − 0.01 for Heads–Toes–Knees–Shoulders task). By contrast, differences in time-use were not found to be significantly associated with any measure of self-regulation or mental health at 5 years of age, nor were any significant longitudinal relationships apparent. Conclusions We did not find a significant association between 24-h time use in the preschool years and any measure of psychosocial or mental health at 5 years of age, although some relationships with inhibitory control were observed cross-sectionally. Trial registration : number NCT00892983, registered 5th May 2009.
... Sleep duration is associated with better cognitive functioning across the lifespan and this association starts early in life. Studies have showed that night sleep duration has been associated with better cognitive outcomes in school-aged children [1][2][3][4] as well as in adolescents [5,6] and adults [7,8]. For example, shorter habitual sleep duration and poor sleep quality have been associated with poorer intelligence quotient (IQ) scores [1] and poorer performance in standardized battery of cognitive tasks [2] in children between 7 and 11 year-olds. ...
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Study Objectives Examine how different trajectories of reported sleep duration associate with early childhood cognition. Methods Caregiver-reported sleep duration data (n=330) were collected using the Brief Infant Sleep Questionnaire at 3, 6, 9, 12, 18 and 24 months and Children’s Sleep Habits Questionnaire at 54 months. Multiple group-based day-, night- and/or total sleep trajectories were derived – each differing in duration and variability. Bayley Scales of Infant and Toddler Development-III (Bayley-III) and the Kaufman Brief Intelligence Test- 2 (KBIT-2) were used to assess cognition at 24 and 54 months respectively. Results Compared to short variable night sleep trajectory, long consistent night sleep trajectory was associated with higher scores on Bayley-III (cognition and language), while moderate/long consistent night sleep trajectories were associated with higher KBIT-2 (verbal and composite) scores. Children with a long consistent total sleep trajectory had higher Bayley-III (cognition and expressive language) and KBIT-2 (verbal and composite) scores compared to children with a short variable total sleep trajectory. Moderate consistent total sleep trajectory was associated with higher Bayley-III language and KBIT-2 verbal scores relative to the short variable total trajectory. Children with a long variable day sleep had lower Bayley-III (cognition and fine motor) and KBIT-2 (verbal and composite) scores compared to children with a short consistent day sleep trajectory. Conclusions Longer and more consistent night- and total sleep trajectories, and a short day sleep trajectory in early childhood were associated with better cognition at 2 and 4.5 years.
Importance: Little is known regarding the effect of poor sleep on health-related quality of life (HRQOL) in healthy children. Objective: To determine the effect of induced mild sleep deprivation on HRQOL in children without major sleep issues. Design, setting, and participants: This prespecified secondary analysis focused on HRQOL, a secondary outcome of the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized crossover trial of children who underwent alternating weeks of sleep restriction and sleep extension and a 1-week washout in between. The DREAM trial intervention was administered at participants' homes between October 2018 and March 2020. Participants were 100 children aged 8 to 12 years who lived in Dunedin, New Zealand; had no underlying medical conditions; and had parent- or guardian-reported normal sleep (8-11 hours/night). Data were analyzed between July 4 and September 1, 2022. Interventions: Bedtimes were manipulated to be 1 hour later (sleep restriction) and 1 hour earlier (sleep extension) than usual for 1 week each. Wake times were unchanged. Main outcomes and measures: All outcome measures were assessed during both intervention weeks. Sleep timing and duration were assessed using 7-night actigraphy. Children and parents rated the child's sleep disturbances (night) and impairment (day) using the 8-item Pediatric Sleep Disturbance and 8-item Sleep-Related Impairment scales of the Patient-Reported Outcomes Measurement Information System questionnaire. Child-reported HRQOL was assessed using the 27-item KIDSCREEN questionnaire with 5 subscale scores and a total score. Both questionnaires assessed the past 7 days at the end of each intervention week. Data were presented as mean differences and 95% CIs between the sleep restriction and extension weeks and were analyzed using intention to treat and an a priori difference in sleep of at least 30 minutes per night. Results: The final sample comprised 100 children (52 girls [52%]; mean [SD] age, 10.3 [1.4] years). During the sleep restriction week, children went to sleep 64 (95% CI, 58-70) minutes later, and sleep offset (wake time) was 18 (95% CI, 13-24) minutes later, meaning that children received 39 (95% CI, 32-46) minutes less of total sleep per night compared with the sleep extension week in which the total sleep time was 71 (95% CI, 64-78) minutes less in the per-protocol sample analysis. Both parents and children reported significantly less sleep disturbance at night but greater sleep impairment during the day with sleep restriction. Significant standardized reductions in physical well-being (standardized mean difference [SMD], -0.28; 95% CI, -0.49 to -0.08), coping in a school environment (SMD, -0.26; 95% CI, -0.42 to -0.09), and total HRQOL score (SMD, -0.21; 95% CI, -0.34 to -0.08) were reported by children during sleep restriction, with an additional reduction in social and peer support (SMD, -0.24; 95% CI, -0.47 to -0.01) in the per-protocol sample analysis. Conclusions and relevance: Results of this secondary analysis of the DREAM trial indicated that even 39 minutes less of sleep per night for 1 week significantly reduced several facets of HRQOL in children. This finding shows that ensuring children receive sufficient good-quality sleep is an important child health issue. Trial registration: Australian New Zealand Clinical Trials Registry: ACTRN12618001671257.
Background: Insufficient sleep duration increases obesity risk in children, but the mechanisms remain unclear. Objectives: This study seeks to determine how changes in sleep influence energy intake and eating behavior. Methods: Sleep was experimentally manipulated in a randomized, crossover study in 105 children (8-12 y) who met current sleep guidelines (8-11 h/night). Participants went to bed 1 h earlier (sleep extension condition) and 1 h later (sleep restriction condition) than their usual bedtime for 7 consecutive nights, separated by a 1-wk washout. Sleep was measured via waist-worn actigraphy. Dietary intake (2 24-h recalls/wk), eating behaviors (Child Eating Behavior Questionnaire), and the desire to eat different foods (questionnaire) were measured during or at the end of both sleep conditions. The type of food was classified by the level of processing (NOVA) and as core or noncore (typically energy-dense foods) foods. Data were analyzed according to 'intention to treat' and 'per protocol,' an a priori difference in sleep duration between intervention conditions of ≥30 min. Results: The intention to treat analysis (n = 100) showed a mean difference (95% CI) in daily energy intake of 233 kJ (-42, 509), with significantly more energy from noncore foods (416 kJ; 6.5, 826) during sleep restriction. Differences were magnified in the per-protocol analysis, with differences in daily energy of 361 kJ (20, 702), noncore foods of 504 kJ (25, 984), and ultraprocessed foods of 523 kJ (93, 952). Differences in eating behaviors were also observed, with greater emotional overeating (0.12; 0.01, 0.24) and undereating (0.15; 0.03, 0.27), but not satiety responsiveness (-0.06; -0.17, 0.04) with sleep restriction. Conclusions: Mild sleep deprivation may play a role in pediatric obesity by increasing caloric intake, particularly from noncore and ultraprocessed foods. Eating in response to emotions rather than perceived hunger may partly explain why children engage in unhealthy dietary behaviors when tired. This trial was registered at Australian New Zealand Clinical Trials Registry; ANZCTR as CTRN12618001671257.
Objective: This study aimed to describe how mild sleep deprivation in children changes time spent physically active and sedentary. Methods: In 2018 through 2020, children (n = 105) with normal sleep were randomized to go to bed 1 hour earlier (extension) or 1 hour later (restriction) than their usual bedtime for 1 week, each separated by a 1-week washout. Twenty-four-hour movement behaviors were measured with waist-worn actigraphy and expressed in minutes and proportions (percentages). Mixed-effects regression models determined mean differences in time use (95% CI) between conditions. Time gained from sleep lost that was reallocated to other movement behaviors in the 24-hour day was modeled using regression. Results: Children (n = 96) gained ~49 minutes of awake time when sleep was restricted compared with extended. This time was mostly reallocated to sedentary behavior (28 minutes; 95% CI: 19-37), followed by physical activity (22 minutes; 95% CI: 14-30). When time was expressed as a percentage, the overall composition of movement behavior remained similar across both sleep conditions. Conclusions: Children were not less physically active when mildly sleep deprived. Time gained from sleeping less was proportionally, rather than preferentially, reallocated to sedentary time and physical activity. These findings suggest that decreased physical activity seems unlikely to explain the association between short sleep and obesity in children.
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Objectives: To explore environmental and individual factors that are associated with child development and to investigate whether the strength of these associations differs according to the age of the children. Design: Cross-sectional study. Setting: This study was part of the LIFE Child study, a large cohort study conducted in Leipzig, Germany. Participants: 778 children aged between 0.5 and 6 years (48.6% girls, mean age=2.67 years). Outcome measures: The outcomes were cognitive development, language development, body and hand motor skills, social-emotional development, and tracing skills, measured with a standardised development test. We analysed the associations between development and gestational age, socioeconomic status (SES), sex, behavioural difficulties, siblings, sleep duration, breastfeeding duration and overweight/obesity. We also tested for interactions between these variables and child age or sex. Results: Higher gestational age (b ranging between 0.12 and 0.26) and higher SES (b ranging between 0.08 and 0.21) were associated with better outcomes in almost all developmental domains (all p<0.019). Children with older siblings had improved body and hand motor skills compared with children without older siblings (both b=0.55, all p<0.029). Boys had poorer scores than girls in body and hand motor skills and tracing (b=-0.45, -0.68 and -1.5, all p<0.019). Children with behavioural difficulties had significantly poorer outcomes in most developmental domains. Some of the associations with SES and sex were stronger in older than in younger children. Associations between gestational age and motor development were weaker in older children. We did not find significant associations between child development and sleep duration, breastfeeding duration or overweight/obesity. Conclusion: Some factors had a protective, others an adverse effect on development of children under 6 years of age. The effect of SES and sex increased, while the effect of gestational age decreased with age. Trial registration number: NCT02550236.
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This paper, which has been reviewed and approved by the Board of Directors of the American Sleep Disorders Association, provides the background for the Standards of Practice Committee's parameters for the practice of sleep medicine in North America. The growing use of activity-based monitoring (actigraphy) in sleep medicine and sleep research has enriched and challenged traditional sleep-monitoring techniques. This review summarizes the empirical data on the validity of actigraphy in assessing sleep-wake patterns and assessing clinical and control groups ranging in age from infancy to elderly. An overview of sleep-related actigraphic studies is also included. Actigraphy provides useful measures of sleep-wake schedule and sleep quality. The data also suggest that actigraphy, despite its limitations, may be a useful, cost-effective method for assessing specific sleep disorders, such as insomnia and schedule disorders, and for monitoring their treatment process. Methodological issues such as the proper use of actigraphy and possible artifacts have not been systematically addressed in clinical research and practice.
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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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Neurobiological research with animals strongly suggests that the brain systems which mediate emotion overlap with those that mediate cognition to such a degree that it is difficult, if not impossible, to maintain any clear distinction between them. Possible reasons for this overlap are discussed; and a model of brain systems that simultaneously subserve emotion and cognition is presented. The model postulates the existence of three fundamental systems of this kind in the mammalian brain: a behavioural approach system, a fight/flight system, and a behavioural inhibition system. The neuropsychology of each of these systems is briefly presented.
To determine whether a cumulative sleep debt (in a range commonly experienced) would result in cumulative changes in measures of waking neurobehavioral alertness, 16 healthy young adults had their sleep restricted to an average 4.98 hrs per night for 7 consecutive nights. Ss slept in the laboratory, and sleep and waking were monitored. Three times each day, Ss were assessed for subjective sleepiness and mood and were evaluated on a brief performance battery that included psychomotor vigilance (PVT), probed memory (PRM), and serial-addition testing. Once each day they completed a series of visual analog scales (VASs) and reported sleepiness and somatic and cognitive/emotional problems. Sleep restriction resulted in statistically robust cumulative effects on waking functions. Subjective sleepiness ratings, subscale scores for fatigue, confusion, tension, and total mood disturbance from the mood and VAS ratings of mental exhaustion and stress were elevated across days of restricted sleep. PVT performance parameters were also significantly increased by restriction. Significant time-of-day effects were evident in subjective sleepiness and PVT data. Findings suggest that cumulative nocturnal sleep debt had a dynamic and escalating analog in cumulative daytime sleepiness and that asymptotic or steady-state sleepiness was not achieved in response to sleep restriction. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Evaluated sleep, performance, and sleepiness in 9 11–13 yr olds to investigate whether children are more sensitive to sleep restriction than adults. In this 3-day study (immediately preceded by 3 adaptive days), sleep was permitted for 10 hrs on the baseline and recovery night, and for 4 hrs on a single restricted night. Effects of sleep restriction and subsequent recovery on nocturnal sleep parameters were comparable to results seen in adult Ss. No significant effects of the procedure were seen in performance on an addition test, a word memory test, or a listening attention task. Multiple sleep latency tests showed a significant increase in daytime sleepiness following sleep restriction, which persisted into the morning following recovery sleep. Children appear to be able to tolerate a single night of restricted sleep, although they do not recover as rapidly as adults. (20 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Throughout early development, a child spends more time asleep than in any waking activity. Yet, the specific role of sleep in brain maturation is a complete mystery. In this article, the developmental psychobiology of sleep regulation is conceptualized within the context of close links to the control of arousal, affect, and attention. The interactions among these systems are considered from an ontogenetic and evolutionary biological perspective. A model is proposed for the development of sleep and arousal regulation with the following major tenets: 1. Sleep and vigilance represent opponent processes in a larger system of arousal regulation. 2. The regulation of sleep, arousal, affect, and attention overlap in physiological, neuroanatomical, clinical, and developmental domains. 3. Complex interactions among these regulatory systems are modulated and integrated in regions of the prefrontal cortex (PFC). 4. Changes at the level of PFC underlie maturational shifts in the relative balance across these regulatory systems (such as decreases in the depth/length of sleep and increased capacity for vigilance and attention), which occur with normal development. 5. The effects of sleep deprivation (including alterations in attention, emotions, and goal-directed behaviors) also involve changes at the level of PFC integration across regulatory systems. This model is then discussed in the context of developmental pathology in the control of affect and attention, with an emphasis on sleep changes in depression.
The aims of this study were to explore the validity of a set of computerized tests, and to explore the validity of reaction time variability as an index of sustained attention. In Phase 1, 105 children 7–10 years old were presented with five tests from the Neurobehavioral Evaluation System (NES). The children were able to complete four of the tests: the Continuous Performance, Simple Reaction Time, Symbol-Digit Substitution, and Digit Span tests. In Phase 2, a follow-up of 88 children, performance on these tests was significantly associated with teachers' ratings of attention and with standardized academic achievement measures. Moreover, variability on the Simple Reaction Time and performance on the Digit Span and Symbol-Digit tests significantly predicted reading achievement. Similarly, performance on the Digit Span and Symbol-Digit tests significantly predicted mathematics achievement. In addition, variability on the Simple Reaction Time and Digit Span test performance were significant predictors of reading achievement above and beyond the prediction provided by teachers' ratings.
This experiment was designed to test the effects on subsequent sleep of a restriction in sleep length on the previous night. Eight male subjects were studied. After baseline recordings were made, sleep was restricted to either a period between 4-8 am or to a period between 6–8 am. On the night following the restriction of sleep the subjects retired at 11 pm and they were permitted to sleep ad lib in the morning. The restricted sleep periods resulted in differential sleep deprivation. Stages REM and 2 were markedly reduced whereas stages 3 and 4 showed little or no reduction in amount. There were significant reductions in sleep latencies and in the amount of lime spent in stages 0 and 1. The first 8 hrs of ad lib sleep following the 2 restricted sleep periods did not differ in any significant way from the 8 hrs of baseline sleep. When sleep was permitted to continue until the subjects awakened spontaneously, the sleep after the restriction of sleep to‘i hrs was significantly longer and displayed significantly more of stages REM and 2 when compared with the baseline ad lib sleep condition. The ad lib sleep period following the 4 hr condition showed similar changes although the differences were not statistically significant. The significant reductions in stages KEM and 2 during the restricted sleep periods were attributed to the effects of reduced steep length per se. The increases in sleep length and specifically the increases in stages REM and 2 during the ad lib sleep periods were attributed to a differential sleep “debt” accruing from restricted sleep length.