Sleep, 19(4):318-326
© 1996 American Sleep Disorders Association and Sleep Research Society
Effects of Sleep Deprivation on Performance:
A Meta-Analysis
June J. Pilcher and Allen 1. Huffcutt
Department of Psychology, Bradley University, Peoria, Illinois. US.A.
Results of sleep research have traditionally been
summarized through narrative reviews. In a narrative
review, a prominent researcher examines the studies in
a given area and subjectively arrives at various conclusions. For example, Krueger (1) reviewed the effects of sleep deprivation on performance and concluded that sleep deprivation results in decreased reaction times, less vigilance, an increase in perceptual
and cognitive distortions and changes in affect.
An alternative approach to summarizing primary research has emerged over the last couple of decades.
Denoted as "meta-analysis," it is based on a mathematical rather than a subjective combination of studies
(see 2,3). Like narrative reviews, meta-analytic reviews can contribute meaningful information and conclusions. Specifically, a meta-analysis can provide details regarding the strength and consistency of an experimental effect and the conditions or factors which
moderate the effect.
Each approach to summarizing research has its own
unique strengths. Narrative reviews are typically done
by someone who has considerable experience and expertise in that area, someone who is in a very good
position to understand the details and intricacies of
each study. Thus, more subjective factors, such as the
quality of each study, can easily be taken into consideration when forming conclusions.
Accepted for publication January 1996.
Address correspondence and reprint requests to June J. Pilcher,
Ph.D., Department of Psychology, Bradley University, Peoria, IL
61625, U.S.A.
Meta-analytic reviews, because of their mathematical nature, tend to be fairly objective and consistent.
Tn addition, meta-analysis has several statistical advantages. Since each individual study represents a sample
taken from a larger popUlation, sample results may not
always match those of the population (i.e. a sampling
error). Mathematically averaging across studies minimizes the influence of sampling error since the high
and low random deviations tend to balance out. Moreover, since some studies may be based on a relatively
small sample, problems with low power are avoided
since no formal significance testing is done at the individual study level. (Effectually, all individual samples are combined into one large sample which should
be largely representative of the general population.)
While meta-analysis has been gaining popularity in
other fields, such as personnel management, clinical
psychology and education (e.g. 4-6), it has yet to gain
widespread acceptance in the sleep research community. To date, only four articles have reported metaanalyses of primary sleep studies. Benca et al. (7) reviewed sleep patterns in psychiatric disorders. Hudson
et al. (8) looked at polysomnographic measures in
good and bad sleep. Knowles and MacLean (9) assessed age-related changes in sleep. Lastly, Koslowsky
and Babkoff (10) examined the effect of total sleep
deprivation on work-paced and self-paced task performance.
Moreover, consistent with the pattern observed in
other fields, some of the first meta-analyses to appear
have been somewhat limited in scope. In regard to
318
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Summary: To quantitatively describe the effects of sleep loss, we used meta-analysis, a technique relatively new
to the sleep research field, to mathematically summarize data from 19 original research studies. Results of our
analysis of 143 study coefficients and a total sample size of 1,932 suggest that overall sleep deprivation strongly
impairs human functioning. Moreover, we found that mood is more affected by sleep deprivation than either cognitive or motor performance and that partial sleep deprivation has a more profound effect on functioning than either
long-term or short-term sleep deprivation. In general, these results indicate that the effects of sleep deprivation may
be underestimated in some narrative reviews, particularly those concerning the effects of partial sleep deprivation.
Key Words: Sleep deprivation-Partial sleep deprivation-Cognitive performance-Motor performance-MoodMeta-analysis.
319
SLEEP DEPRIVATION
addition, our analysis utilizes data from both partial
and total sleep deprivation studies.
METHOD
Location of study data
The data for our meta-analyses were located by extensive literature searches on the computerized databases PsychLit (1987-1993) and Med On-Line (19861993) and in the extensive Sleep Research bibliography (1986-1993). These searches resulted in references for studies published between 1984 and 1992.
We then extended our search by locating sleep deprivation studies that were referenced in these studies. A
total of 56 primary articles were located which investigated the effects of sleep deprivation on performance.
Decision rules
We established the following criteria for inclusiOll
in our analysis. First, enough information had to be
provided to allow computation of an effect size statistic (explained in the next section) for each dependent
measure. In most cases this meant direct reporting of
the means (or a clear enough graph such that the
means could be estimated) and standard deviations for
the sleep-deprived and non-sleep-deprived groups. In
cases where results were expressed only as a t or a 1
df, an effect size statistic was computed through a statistical transformation (see 2).
Second, the study had to involve short-term total
sleep deprivation (:::;45 hours), long-term total sleep
deprivation (>45 hours), or partial sleep deprivation
(sleep period of <5 hours in a 24-hour period). The
determination of short-term and long-term sleep deprivation followed the criteria set by Koslowsky and
Babkoff (10). The decision to use a sleep duration of
<5 hours as the criteria for partial sleep deprivation
was made after reviewing a number of studies which
allowed the subjects to sleep for short periods of time
in a 24-hour period and then selecting a number that
reflected a natural cutoff point.
Third, the study had to use either a cognitive performance task, a motor performance task or a mood
scale as the dependent measure. In particular, cognitive
performance tasks (e.g. logical reasoning tasks, mental
addition tasks, Torrance tests) had to be either :::;6 minutes in duration or :=:: 10 minutes in duration. Motor
performance tasks (e.g. serial reaction time, treadmill
walking, manual dexterity tasks) had to be either 53
minutes in duration or :=::8 minutes in duration. The
above times for cognitive and motor tasks were based
on our review of a large number of studies and apSleep, Vol. 19, No.4, 1996
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sleep deprivation, there are a number of potentially
important moderator variables which could be taken
into account. For example, there are three types of
measures commonly used to assess the effects of sleep
deprivation: cognitive performance, motor performance and mood. And, there may be additional variables operating within each of these measures which
may further change the effects of deprivation on functioning.
Some evidence does, in fact, suggest that performance varies on different types of cognitive tasks. In
a comprehensive survey of the sleep deprivation literature, Johnson (11) concluded that the results from
studies using accuracy as the performance variable depended on the type of cognitive measure (e.g. logical
reasoning, mental addition, visual search tasks, word
memory tasks). In addition, other narrative reviewers
(e.g. 12) have suggested that the length and pacing of
cognitive tasks may affect performance.
Similarly, with motor performance measures, the
use of different tasks could affect results. In a review
of the effect of sleep loss on exercise, Martin (l3)
concluded that the effect of sleep deprivation depends
on the type and length of the motor task. For example,
while several studies suggest that exercise is not adversely affected by sleep deprivation (e.g. 14-17), others report that performance on certain endurance tasks
is decremented (e.g. 18). In an extensive review of the
sleep deprivation and exercise performance literature,
VanHelder and Radomski (19) concluded that sleep
deprivation up to 72 hours does not affect muscle
strength or reaction but does decrease time to exhaustion.
One factor that may affect all three measures is the
length of sleep deprivation. Naitoh (20), for example,
found that sleep deprivation of less than 46 hours is
usually too short to have a substantial effect on either
cognitive or motor tasks. Other researchers, however,
have reported performance decrements at sleep loss
durations of less than 45 hours (e.g. 21). While mood
appears to be decremented by sleep deprivation (e.g.
12,22-24), it is unclear whether different types of deprivation differentially impact mood.
The purpose of this study is to use the meta-analytic
technique to provide a comprehensive, quantitative
analysis of the effects of sleep deprivation on functioning. Our work extends that of Koslowsky and Babkoff (10) in that we evaluate a number of additional
moderator variables. Specifically, we categorize and
separately analyze the measures as being either mood
assessment, motor task performance or cognitive task
performance. Then, we further differentiate both the
motor and cognitive task performance categories according to the length and complexity of the tasks. In
1. J. PILCHER AND A. /. HUFFCUTT
320
TABLE 1.
Coding characteristics
Type of sleep deprivation
A. Short-term sleep deprivation (:545 hours)
.
B. Long-term sleep deprivation (>45 hours) .
C. Partial sleep deprivation «5 hours sleep III a 24-hour penod
Type of dependent measure
A. Cognitive task performance
B. Motor task performance
C. Mood assessment
Type of task
A. Simple task
B. Complex task
peared to represent natural separations that could differentiate short from long durations.
Finally, if subjects performed multiple tasks of the
same type, all data had to be reported. If a study reported results only for positive or statistically significant effects and not for negative or nonsignificant effects, then it was dropped.
Of the 56 primary studies located, 37 were rejected
because they did not meet the above criteria (a complete bibliography of the studies not used in this metaanalysis is available on request). Of these 37 articles,
29 did not present data in a fashion that would allow
us to compute an effect size (e.g. 21,25-28), seven did
not use a design that met our qualifications for type of
task or type of deprivation (e.g. 29-31) and one presented only positive results (32). We attempted to directly contact the authors of these articles for more
information, but a majority either could not be contacted or could not locate the data in question.
Coding of study information
The final data set was formed from the remaining
19 primary journal articles (33-51). A special coding
sheet was developed to capture information from these
studies. The information coded is listed in Table 1.
Effect size statistics, which indicate how many standard deviation units the experimental group was different from the control group, were computed using
the methodology outlined by Hunter and Schmidt (2).
The formula for the effect size statistic, d, is shown
below, where XE is the mean of the experimental
group, Xc is the mean of the control group and Sw is
the standard deviation pooled across both groups.
(1)
The formula for computing the pooled standard deviation in the effect size formula is shown below, where
NE and SE are the sample size and standard deviation,
Sleep, Vol. 19, No.4, 1996
Sw
=
(NE)SE2
NE
+ (Nd Sc 2
+ Nc
(2)
Careful attention was paid to the sign of the effect
size during coding, since d values mathematically can
be positive or negative. Studies were uniformly coded
such that a negative d represented situations where the
experimental (i.e. sleep-deprived) group did worse on
the dependent measure than the control group, while
a positive d represented situations where the experimental group did better than the control group.
In total we were able to code 143 d values representing 1:932 subjects from the 19 primary studies.
(Since most sleep deprivation studies used more than
one measure of performance, these data are not totally
independent of each other. Such a situation is common
in meta-analysis.) This subject pool represents a broad
range of subjects including both genders and a wide
age range. The 19 primary studies were divided approximately equally between the three sleep deprivation categories: four in short-term sleep deprivation
(37,42,43,45), six in long-term sleep deprivation
(33,35,46,47,50,51), three in both short-term and longterm sleep deprivation (34,36,38) and six in partial
sleep deprivation (39-41,44,48,49). Such a data set is
large and provides the opportunity to do meaningful
analyses.
The reliability of the coding process was assessed
by having two independent researchers code all 19
studies. The correlation between the raters was 0.60
for type of sleep deprivation, 1.00 for type of dependent measure, 0.94 for type of task, 0.78 for task duration, 0.93 for sample size and 0.98 for effect size.
The lowest interrater reliability was seen for type of
sleep deprivation. This was due to the initial analysis
not clearly distinguishing between short-term and partial sleep deprivation. With the second coding, this distinction was clarified, which changed some of the previously coded short-term deprivations to partial sleep
deprivations. All disagreements across all coding criteria were investigated by the two researchers and resolved. These results indicate that information could
be coded reliably from the studies.
Meta-analytic computations
The actual computations for the meta-analyses were
performed using a SAS (SAS Institute, 1990) PROC
MEANS program developed by Huffcutt et al. (52)
that takes the d values from the various studies and
combines them mathematically. The result is an estimate of the average effect size across the studies (i.e.
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Duration of task
A. Short (motor, :53 minutes; cognitive, :56 minutes)
B. Long (motor, >8 minutes; cognitive, 210 minutes)
respectively, for the experimental group and Nc and Sc
are the sample size and standard deviation for the control group.
321
SLEEP DEPRIVATION
Analyses
Our first goal was to assess the overall effect of
sleep deprivation. More specifically, we attempted to
answer two questions. First, at a general level, how
well do experimental subjects do, on average, relative
to control subjects in a sleep deprivatiori study? And
second, how constant (i.e. stable) are the effects of
sleep deprivation across different study designs?
To answer these questions we conducted a metaanalysis of all 143 effect sizes collectively. The mean
d score from this analysis indicated the average number of standard deviations that the sleep-deprived
group was different from the non-sleep-deprived
group, collapsing across all the different study design
characteristics. The standard deviation in d scores was
a reflection of the extent to which design characteristics affected the magnitude of the difference between
deprived and nondeprived subjects.
A second goal was to investigate specifically how
the effects of sleep deprivation vary according to the
two most prominent study design characteristics, the
type of deprivation and the type of measure. Our attempt here was to assess quantitatively how much difference each of these two characteristics makes in
terms of the effects of sleep deprivation. To assess the
influence of type of deprivation, we separated the studies into the three main categories (short-term, longterm and partial sleep deprivation) and conducted a
separate meta-analysis for each category. We then
looked to see if there was a difference in the mean d
scores across the three categories. [As Hunter and
Schmidt (2) noted, the more different the individual
means are from the overall mean, the more influence
that characteristic has on the strength of the experimental effect.]
Similarly, we separated the studies into the three
categories of dependent measure (cognitive task performance, motor task performance and mood scales)
and conducted a separate meta-analysis for each category. Finally, we conducted a meta-analysis in which
we combined across the two prominent design characteristics to assess whether the effects of deprivation
for a particular dependent measure changed depending
on the type of sleep deprivation (i.e. an interaction
effect).
A third goal was to do a supplemental assessment
of whether performance on cognitive tasks changed
according to either the type of task (simple vs. complex) and/or the task length (short vs. long). Thus, we
took the cognitive task studies which were already
sorted according to the type of deprivation, further
sorted them into simple and complex task categories
and conducted a separate meta-analysis for each resulting combination. Then, within each type of deprivation, we re-sorted the studies into short and long
duration categories and conducted separate meta-analyses for each resulting combination. These procedures
allowed us to assess whether, for a particular type of
deprivation, performance on a cognitive task depended
on the type and/or length of the task.
Lastly, a fourth and similar goal was to assess
whether performance on motor tasks varied according
to either the type of task (simple vs. complex) or the
length of the task (short vs. long). As described in the
preceding paragraph, studies already separated by type
of deprivation were then further separated by type of
task and length of task.
In closing, the above analyses were designed to folIowa "hierarchical" strategy, as is typically done in
a meta-analytic investigation (2). In particular, we
started at an overall summary level and then progressively made the analyses more and more specific. Two
comments should be noted in regard to this strategy.
First, unlike cognitive and motor task performance, we
did not break mood measures down by additional features such as length and complexity. Conceptually,
such features were not as meaningful with mood measures as they were with cognitive and motor tasks. And
second, the number of studies being analyzed at any
one time progressively decreased as the data set was
split into more and more subcategories. Naturally, the
smaller the number of studies in a given category, the
more tentative the results become.
RESULTS
Results of the overall analysis of all 143 coefficients
combined are presented in the top portion of Table 2.
Sleep. Vol. 19. No.4. 1996
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the average number of standard deviations the experimental distributions was offset from the control distribution) and the variability observed around this average. All computations are done weighting by sample
size, since studies based on a larger sample are more
stable than those based on a smaller sample (2,3).
It should be noted that Huffcutt et al.'s program
does not provide any tests of statistical significance.
Formal significance testing is typically not done in a
meta-analysis, as the meta-analytic procedures were
developed to avoid the problems and limitations associated with significance testing (2,3). Moreover,
since sampling errors tend to be averaged out when
combining across studies, results of a meta-analysis
are thought to represent direct estimates of the strength
of a relationship iQ the population. The average effect
size represents the overall strength of a relationship,
while the variability around the average reflects the
degree to which other variables moderate the relationship. (Therefore, high variability does not imply a lack
of an effect but rather that the strength of the effect
depends strongly on other variables.)
1. 1. PILCHER AND A. I. HUFFCUTT
322
TABLE 2.
Deprived
Group
Meta-analyses of sleep deprivation overall and
by study design characteristic
aa
SD(d)"
N,
TSS
Overall
-1.37
2.08
143
1,932
Deprivation
Short-term
Long-term
Partial
-1.21
-1.27
-2.04
1.40
2.10
2.55
34
79
30
683
799
450
Type of measure
Motor
Cognitive
Mood
-0.87
-1.55
-3.16
1.96
1.75
2.53
58
65
20
790
949
193
Analysis
Nondeprived
Group
\ \.
('
;'
Scores on Dependent Measures
FIG. 1. Illustration of the overall difference between sleep-deprived and non-sleep-deprived subjects.
As shown, the mean effect size collapsing across all
study characteristics was -1.37, indicating that the
sleep-deprived subjects performed at a level 1.37 standard deviations lower than the performance level of
the non-sleep-deprived subjects. The difference of 1.37
standard deviations between the two distributions is
graphically illustrated in Fig. 1. In more pragmatic
terms, such a finding suggests that a person at the 50th
percentile in the deprived group (shown as the dark
dot in Fig. 1) performs roughly equivalent to a person
at the 9th percentile in the nondeprived group. [This
is based on the assumption that both the deprived and
nondeprived groups roughly approximate a z distribution. Percentiles were obtained from Minium et al.
(53).] The relatively large standard deviation across
the effect sizes (2.08) suggests that study design characteristics do make a considerable difference in terms
of how deprived subjects perform relative to nondeprived subjects.
Results of the meta-analyses for the two most prominent study design characteristics, the type of deprivation and the type of measure, are also presented in
Table 2. As shown, the type of deprivation does appear
to make a difference; partial sleep deprivation appeared to have a considerably greater overall impact
on subjects than either short-term or long-term depriTABLE 3.
vation. In terms of type of measure, sleep deprivation
in general appeared to have the least effect on motor
tasks, a greater effect on cognitive tasks, and an even
greater effect on mood. [However, the average effect
size for motor tasks is still considered to be a large
experimental effect. For reference, an average effect
size of 0.20 is considered to be a small experimental
effect, 0.50 is considered medium, and 0.80 or greater
is considered to be large (54).]
Results for type of dependent measure crossed with
type of deprivation are shown in Table 3. These results
in general suggest an interaction between these two
design characteristics. For motor performance tasks,
the means were fairly close across all three types of
deprivation, suggesting that performance on motor
tasks is relatively unaffected by the type of deprivation. For cognitive performance tasks, the means were
dissimilar, with performance being considerably more
decremented with partial sleep deprivation than either
short-term or long-term deprivation. Similarly, mood
appeared to be much more affected by partial deprivation than by long-term deprivation. (There were no
studies of the effect of short-term deprivation on mood
in the final data set.)
Results of the supplemental analyses of cognitive
performance tasks are presented in Table 4. For shortterm deprivation, performance on complex and long
tasks was considerably more decremented than on simple and short tasks, respectively. For long-term deprivation, opposite results were found, with performance
Meta-analyses for type of measure and type of deprivation crossed
Type of sleep deprivation
Type of
measure
Motor
Cognitive
Mood
Short-term
Long-term
Partial
aa
SD(d)a
N,
TSS
aa
SD(d)a
N,
TSS
aa
SD(d)"
N,
TSS
-0.77
-1.36
1.31
1.39
10
24
173
510
-0.92
-1.04
-2.75
2.46
0.71
2.25
35
31
13
386
278
135
-0.85
-3.01
-4.10
1.33
2.88
2.88
13
10
7
231
161
58
Abbreviations used: a, average effect size; SD(d), standard deviation of effect sizes; N" number of study coefficients in the analysis;
TSS, total sample size from those coefficients.
a Averages and standard deviations were computed using sample size weighting.
Sleep, Vol. 19, No.4, 1996
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Abbreviations used: a, average effect size; SD(d), standard deviation of effect sizes; N" number of study coefficients in the analysis;
TSS, total sample size from those coefficients.
" Averages and standard deviations were computed using sample
size weighting.
323
SLEEP DEPRIVATION
TABLE 4.
Supplemental meta-analyses for cognitive measures
Type of sleep deprivation
Partial
Long-term
Short-term
da
SD(d)a
Nc
Overall b
-1.36
1.39
24
Type of task
Simple
Complex
-0.37
-1.53
0.41
1.43
Duration of task
Short
Long
-0.36
-1.90
0.78
1.35
TSS
da
SD(d)a
Nc
TSS
278
-3.01
2.88
10
161
14
17
134
144
-3.48
-1.49
3.01
1.69
7
3
123
38
3
28
32
246
1.18
-3.71
0.00
2.50
1
9
23
138
TSS
da
SD(d)a
Nc
510
-1.04
0.71
31
4
20
76
434
-1.17
-0.91
0.78
0.62
9
15
178
332
-1.64
-0.96
0.85
0.66
being considerably worse on short tasks than on long
tasks and slightly worse on simple tasks than on complex tasks. For partial deprivation, subjects did worse
on tasks that were simple than those that were complex
and worse on tasks that were longer. However, the relatively small samples involved makes these findings
much more tentative.
Results of the supplemental analyses of motor performance tasks are presented in Table 5. As shown,
there were no studies involving complex motor tasks
in the final data set. For length of task, performance
was worse on long tasks for all three types of deprivation. Once again, the relatively small samples involved makes these findings tentative.
DISCUSSION
Our results confirm that sleep deprivation has a significant effect on human functioning. By quantitatively
combining across primary studies, we found that the
mean level of functioning of sleep-deprived subjects
was comparable to, that of only the 9th percentile of
TABLE S.
non-sleep-deprived subjects (i.e. a 1.37 standard deviation difference between the distributions). Although
most of the sleep research community may concur
with these results, there are a surprising number of
scientists outside the sleep research field who have
concluded that sleep deprivation has no profound effect on performance and only a marginal effect on
mood. For example, many widely known professionals
outside the sleep research field writing introductory
texts in psychology and physiological psychology
have stated that the effects of sleep deprivation on human functioning are minimal (55-59).
Another major finding of our investigation was that
the effects of sleep deprivation vary according to two
key moderator variables. First, we found a substantial
difference across the three dependent measures. Specifically, we found that cognitive performance was
more affected by sleep deprivation than motor performance and that mood was much more affected than
either cognitive or motor performance. It is important
to note, however, that even on motor tasks the sleepdeprived subjects performed considerably worse than
Supplemental meta-analyses for motor measures
Type of sleep deprivation
Long-term
Short-term
Overall
b
Type of task
Simple
Complex
Duration of task
Short
Long
Partial
d
SD(d)a
Nc
TSS
da
SD(d)a
Nc
TSS
da
SD(d)a
Nc
TSS
-0.77
1.31
10
173
-0.92
2.46
35
386
-0.85
1.33
13
231
-0.77
1.31
10
173
-0.92
2.46
35
386
-0.85
1.33
13
231
-0.52
-1.22
1.04
1.58
6
4
110
63
0.02
-3.26
0.62
3.51
26
9
275
III
-0.27
-2.20
1.18
0.24
10
3
162
69
a
Abbreviations used: d, average effect size; SD(d), standard deviation of effect sizes; N c' number of study coefficients in the analysis;
TSS, total sample size from those coefficients.
a Averages and standard deviations were computed using sample size weighting.
b Data for "Overall" are from Table 3.
Sleep, Vol. 19, No.4, 1996
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Abbreviations used: d, average effect size; SD(d), standard deviation of effect sizes; N c' number of study coefficients in the analysis;
TSS, total sample size from those coefficients.
a Averages and standard deviations were computed using sample size weighting.
b Data for "Overall" are from Table 3.
324
J. J. PILCHER AND A. I. HUFFCUTT
Sleep, Vol. 19, No.4, 1996
ological concerns could account for all of the decrement found in cognitive tasks and mood.
One clear direction for future research is to address
why partial sleep deprivation may have such a pronounced effect on mood and cognitive performance.
For example, partial sleep deprivation may alter certain circadian rhythm effects on performance and
mood. While total sleep deprivation has been found to
interact with circadian rhythms (61,62), few studies
have investigated the effects of partial sleep deprivation on circadian rhythms. In addition, partial sleep
deprivation may be similar to fragmented sleep in that
subjects in both cases obtain at least some sleep. Since
sleep fragmentation has been shown to significantly
decrease performance and mood (63,64), it is possible
that the effects of partial sleep deprivation more closely resemble those of sleep fragmentation than those of
total sleep deprivation. Furthermore, partial sleep deprivation could have a unique effect on certain psychological variables. Decreased interest and attention,
for example, are thought to be two prominent variables
related to total sleep deprivation (65) and could be
investigated with partial sleep deprivation. Similarly,
partial sleep deprivation could have certain physiological effects that are either different or more pronounced than those of total sleep deprivation. Although numerous studies have been conducted on
physiological changes following total sleep deprivation (e.g. 66,67), few studies have specifically investigated physiological changes following partial sleep
deprivation. In sum, the effects of partial sleep deprivation need to be more thoroughly investigated, particularly since partial sleep loss is a relatively common
condition in our society.
There are several limitations that should be noted
about our investigation. First, we could not use a number of the primary studies that we found because they
did not meet our established criteria. Although the
meta-analytic technique does not require that all possible literature be utilized, it is important that coverage
of the literature not be systematically biased. In our
case, there is no a priori reason to assume that the
articles we rejected were different in any systematic
way from the articles that we used. Second, a general
concern about the meta-analytic technique is that it
combines across data that may be inherently positive.
This same point, however, can be made concerning
narrative reviews. In both cases, the reviewers are simply evaluating published data. Also, this concern may
not be as valid in this particular meta-analysis since a
number of the studies that we used actually included
nonsignificant data. Third, we were not able to draw
robust conclusions from our final level of analysis,
which examined the influence of task length and complexity on performance. Such analyses may become
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the non-sleep-deprived subjects. This pattern of differences among the three types of dependent measures
is not surprising and is consistent with the viewpoints
of many sleep researchers (1,11,19,24).
That mood was more influenced than the objective
performance measures is not surprising. Since mood
is usually assessed using self-reporting methodology,
it is possible that the subjects could be overestimating
the effect of sleep deprivation on their mood. However, it is important to note that on average, the sleepdeprived subjects reported mood ratings that were over
3 standard deviations worse than those of non-sleepdeprived subjects. While part of these differences
could be attributable to self-reporting error, it is likely
that sleep deprivation has a negative effect on mood.
Second, we found a substantial difference across the
three types of sleep deprivation. Unexpectedly, partial
sleep deprivation had a much stronger overall effect
on the dependent measures than either short-term or
long-term sleep deprivation. On average, partially
sleep-deprived subjects performed at a level 2 standard
deviations below that of the non-sleep-deprived subjects, compared to about a 1 standard deviation difference for both long-term and short-term deprivation.
In addition, we found an interaction between the
two key moderator variables, length of sleep deprivation and type of dependent mcasure. We found that
detriments on motor task performance were relatively
constant across the three types of sleep deprivation. In
contrast, cognitive performance and mood were considerably more decremented under partial sleep deprivation than under long-term or short-term deprivation.
Narrative reviews clearly do not indicate such an
overwhelming decrement in performance due to partial
sleep deprivation. For example, two reviews of the effects of sleep deprivation reported mixed findings from
a variety of partial sleep deprivation studies (1,60).
Similarly, more recent reviews concluded that the effects of partial sleep loss on medical residents' performance were inconclusive (12,24).
It is possible that the difference in methodology between the narrative reviews and our quantitative analysis could account for the disagreement on the effects
of partial sleep deprivation. Alternatively, the disagreement could be attributable to differences in the studies
reviewed. For example, four of the six partial sleep
deprivation studies in our meta-analysis used medical
residents as subjects, and three of these studies specifically used medical-related tasks as dependent measu~es. It is possible that these tasks were more easily
affected by sleep deprivation than more traditional
cognitive and motor tasks. However, given the magnitude of the differences between partially deprived
and control subjects, it is unlikely that these method-
SLEEP DEPRIVATION
Acknowledgements: We thank Cristin B. Dooley for
her assistance with the initial organization and analysis of
the data.
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