ThePrevalenceofSleepDisordersinCollegeStudentsImpactonAcademicPerformance
The Academic Costs of Extra Studying at The Expense of Sleep
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The
Prevalence of Sleep Disorders in College
Students: Impact on Academic Performance
Jane F. Gaultney PhD
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Students: Impact on Academic Performance, Journal of American College Health, 59:2,
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JOURNAL OF AMERICAN COLLEGE HEALTH, VOL. 59, NO. 2
The Prevalence of Sleep Disorders in College
Students: Impact on Academic Performance
Jane F. Gaultney, PhD
Abstract. Objective: To examine the prevalence of risk for sleep
disorders among college students by gender and age, and their asso-
ciations with grade point average (GPA). Participants: Participants
were 1,845 college students at a large, southeastern public univer-
sity. Methods: A validated sleep disorder questionnaire surveyed
sleep data during the 2007–2008 academic year. Students’ GPAs
were obtained from the office of the registrar. Results: Twenty-
seven percent of students were at risk for at least one sleep disorder.
African American and Asian students reported less risk for insom-
nia and fewer poor sleep practices relative to white and Latino
students. Students reported insufficient sleep and a discrepancy be-
tween weekday and weekend amount of sleep. Students at risk for
sleep disorders were overrepresented among students in academic
jeopardy (GPA < 2.0). Conclusions: Many college students are at
risk for sleep disorders, and those at risk may also be at risk for
academic failure.
Keywords: academic performance, college students, gender, GPA,
sleep disorders, sleep hygiene
College students experience a number of sleep prob-lems, which may impact academic performance,health, and mood.1 A common sleep problem among
college students is sleep deprivation and resulting excessive
daytime sleepiness (EDS). Both biological and social factors
contribute to deprivation. Many college students are older
adolescents and are still dealing with adolescent physiology
such as a biologically driven delayed sleep phase.2 Accord-
ing to the National Sleep Foundation,3 59% of adults 18 to 29
years of age describe themselves as night-owls. Unable to fall
asleep earlier in the evening, they cannot get enough sleep if
they must get up early. In addition, sleep may be voluntar-
ily sacrificed due to social factors or involuntarily curtailed
because of living in a noisy residence hall or apartment. A
typical coping technique for dealing with sleep deprivation
Dr Gaultney is with the Department of Psychology at University
of North Carolina at Charlotte in Charlotte, North Carolina.
Copyright © 2010 Taylor & Francis Group, LLC
is to attempt to make up for lost sleep by increasing sleep on
the weekends, a practice that actually worsens the problem.4
Another potential source of EDS that has been less thor-
oughly examined in this population, however, is untreated
sleep disorders, which may be underdiagnosed among col-
lege students. The International Classification of Sleep Dis-
orders5 categorizes 3 types of sleep disorders: dyssomnias
(which may produce EDS), parasomnias (which usually are
not associated with EDS), and medical/psychological disor-
ders. The first 2 categories are primary disorders of sleep,
whereas the third category includes conditions that are often
associated with disrupted sleep.
The consequences of sleep problems—whether due to in-
sufficient sleep or an untreated sleep disorder—can be se-
rious. Sleep problems have been associated with deficits
in attention and academic performance,6 drowsy driving,7
risk-taking behavior and depression,8 impaired social rela-
tionships,9 and poorer health.10 Wolfson and Carskadon4
reported that reduced sleep time, later bedtime and awak-
ening, irregular sleep/wake patterns, and poor sleep quality
negatively impacted adolescents’ school performance. The
National Sleep Foundation3 found that high school students
who reported insufficient sleep or daytime sleepiness also
reported depressed mood and lower grades, whereas 80% of
students who reported getting enough sleep made As and Bs
in school. Among college students who carried a full aca-
demic load, those who reported poorer sleep quality were
likely to perform worse on academic tests.11
The impact of sleep loss on academic performance might
be subtle. Fifty college students, deprived of sleep for 1 night,
were then asked to solve math addition problems.12 Partici-
pants selected the difficulty level of the problems. After sleep
loss, participants were more likely to choose easier problems
to solve. Extrapolating from these data, students who are
chronically sleepy may limit their future options by choos-
ing easier courses while in college.
The prevalence of sleep disorders in college students
has not been established. It is not known whether reported
91
Gaultney
sleepiness among college students is simply due to insuf-
ficient sleep or whether it might be secondary to an undi-
agnosed sleep disorder. Although reported sleep disorders in
adults tend to increase with age,13 they may also occur among
college students frequently enough to warrant screening this
population. In addition, sleep patterns or disorders among
college students may vary by gender or race/cultural affili-
ation.14 The purpose of the present study was to determine
the prevalence of sleep disorders among college students, to
examine whether race or gender associated with different pat-
terns of sleep disorders, and to determine whether students
at risk for sleep disorders were also at risk for poor academic
performance.
METHODS
Participants included 1,845 students enrolled in Introduc-
tory Psychology labs at a large state university in southeastern
United States. The students received extra credit for partic-
ipating in research; alternative assignments were available.
This project was approved by the local institutional review
board. Twenty-nine percent of the sample was male. Seventy
percent of the participants were white, 17% African Amer-
ican, 5% selected a designation of “other,” 4% were Asian,
and 4% were Latino students. The participants had an av-
erage age of 20.38 years (SD = 4.63, range = 18–71), and
an average grade point average of 2.77 (SD = .92, range =
0.00–4.00). Forty-six percent were first year students, 26%
were sophomores, 16% juniors, and 10% seniors. The ma-
jority of the students (76%) considered themselves to be
“evening” people.
The survey used, the SLEEP-50 by Spoormaker et al,15
has been validated for college students. It consists of 50
items that tap a variety of sleep characteristics. The valida-
tion sample included 377 college students, 342 patients with
sleep disorders, 32 individuals who experienced nightmares,
and 44 healthy controls. The results indicated good internal
consistency (Chronbach’s alpha = .85), and test–retest re-
liability ranged from .65 to .89. Scales and cut-off scores
for several sleep disorders were developed, and sensitivity
and specificity values identified for each scale. To each item
(eg, “I am told I snore.”) the student indicated that it was
“not at all” (1), “somewhat” (2), “rather much” (3), or “very
much” (4) true. Additional items were added to the survey
to obtain demographic information as well as additional de-
tails about sleep (eg, typical amount of sleep when there is
work/school the next day, typical amount of sleep when there
is no work/school the next day).
The SLEEP-50 provides scores for Obstructive Sleep Ap-
nea (OSA), Periodic Limb Movement Disorder/Restless Leg
Syndrome (PLMD/RLS), Insomnia, Narcolepsy, Circadian
Rhythm Disorders (CRDs), Sleepwalking, Nightmares, Af-
fective Disorder, Hypersomnia, Sleep State Misperception
(SSM), Sleep Hygiene (behaviors and environmental condi-
tions that influence sleep), and Impact on Daily Functioning
(IDF; disruptions to the ability to function well during the
day). Cut-points were identified to determine which students
were at risk for the various disorders. In order to be identified
as “at risk” for each disorder, the participant’s scores on both
the disorder’s scale and the IDF scale had to meet or exceed
a specified threshold.
Data were collected online during the 2007–2008 aca-
demic year. Current grade point average (GPA; as of the end
of the semester when the sleep survey was completed) was
provided as de-identified data by the registrar’s office.
Descriptive information about sleep scales, sleep habits,
and student characteristics are presented. Continuous vari-
ables were analyzed by analyses of variance (ANOVA), t
tests, and Fisher’s least significant difference (LSD), and
counts were compared by means of χ 2 analyses.
RESULTS
Table 1 presents descriptive information about the sleep
disorder scales and prevalence of risk for sleep disorders.
Over 500 students out of 1,845 (27%) were at risk for at least
one sleep disorder. The most commonly reported disorders
were narcolepsy and insomnia, followed by RLS/PLMD,
CRDs, affective disorder, OSA, and hypersomnia. Prevalence
rates for sleepwalking, nightmares, and SSM were low. The
rate of narcolepsy indicated by this scale is extremely high
relative to the general population. Due to questions about
the accuracy of this scale, analyses involving participants
identified as at risk for narcolepsy should be considered un-
interpretable at this time, and are not reported here.
A breakdown of specific sleep hygiene practices/
characteristics indicated fairly even rates (3% to 6%) of
keeping the bedroom too light, too noisy, nighttime alcohol
consumption, smoking, use of other substances that could
interfere with sleep, and feeling sad or feeling no pleasure.
On a scale of 1 (do not get nearly enough sleep) to 10
(get an ideal amount of sleep), students averaged 6.50. They
reported sleeping an average of 6.79 hours (SD = 1.41) on a
typical school/work night, and 9.30 hours (SD = 1.87) when
they did not have school/work the next day, producing a day-
of-the-week sleep discrepancy of 2.49 hours (SD = 1.84).
Nineteen percent reported that they worried rather much or
very much about whether they got enough sleep (42% re-
ported no worry), and 13% reported that they generally slept
badly (56% reported they never slept badly). Seventy-six per-
cent described themselves as rather or very much an evening
person.
Because of relatively small sample sizes (when compared
to the overall sample size) for students identifying as Asian,
Latino, or other, analyses of race/ethnicity effects included
just African American and Caucasian students. Chi-square
analyses indicated no significant race differences in risk for
sleep disorders, although 2 approached significance. A higher
percentage of Caucasian students were at risk for RLS/PLMD
(9% > 6%; χ 2(1) = 2.67, p = .10) and insomnia (12% >
9%; χ 2(1) = 3.05, p = .08). A Gender × Race ANOVA
examining the number of poor sleep hygiene practices (the
Factors Affecting Sleep scale) produced a significant main
effect of race/ethnicity, F(4, 1585) = 31.39, p < .01, ηp2 =
.02. African Americans students (M = 8.45, SD = 1.69) had
92 JOURNAL OF AMERICAN COLLEGE HEALTH
Prevalence of Sleep Disorders in College
TABLE 1. Mean Sleep Scale Scores and Percent at Risk for Each Disorder and Sleep Practices
Range M (SD) Cutpoint % risk (N)
OSA 8–28 11.11 (2.38) > 15 4.0 (74)
Insomnia 8–32 15.33 (4.63) ≥ 19 12.0 (226)
Narcolepsy 5–16 6.52 (1.69) ≥ 7 16.0 (296)
RLS/PLMD 3–16 6.52 (1.69) ≥ 7 8.0 (152)
CRDs 3–12 5.34 (1.82) ≥ 8 7.0 (134)
Sleepwalking 1–12 3.29 (0.83) ≥ 7 0.4 (8)
Nightmares 3–12 5.40 (2.49) ≥ 9 2.0 (40)
Affective Disorder 4–16 7.90 (2.37) ≥ 12 7.0 (131)
SSM Yes/No — — 0.4 (8)
Hypersomnia Yes/No — — 4.0 (68)
∗IDF 5–28 12.67 (4.11) ≥ 15 —
Total no. of poor sleep
practices
6–23 9.14 (2.09)
% rather much/very much
Bedroom—Too Light 1–4 1.28 (0.61) 4 (75)
Bedroom—Too Noisy 1–4 1.24 (0.53) 3 (55)
Alcohol at Night 1–4 1.42 (0.62) 5 (89)
Smoke at Night 1–4 1.25 (0.65) 6 (121)
Other Substances 1–4 1.22 (0.58) 4 (75)
Feel Sad 1–4 1.47 (0.64) 6 (100)
No Pleasure 1–4 1.29 (0.58) 4 (82)
Note. Range: 1 (not nearly enough) to 10 (ideal amount).
∗Risk for each disorder based on cutpoint for that disorder’s scale and cutpoint for the Impact on Daytime Functioning (IDF) scale.
fewer poor sleep hygiene practices than did white students
(M = 9.31, SD = 2.10).
There were no gender differences in the percentages at risk
for OSA, CRDs, or hypersomnia (Table 2). Females were at
greater risk for RLS/PLMD, insomnia, affective disorder,
nightmares, and having at least one sleep disorder.
An ANOVA examined whether having any sleep disorder
(no disorders versus at least one sleep disorder) was associ-
ated with GPA. Those who reported no sleep disorder had a
higher GPA (M = 2.82, SD = .88) than did those who re-
ported at least one sleep disorder (M = 2.65, SD = .99), F(1,
1842) = 15.17, p < .01, ηp2 = .01. Self-identified morn-
ing people had a higher GPA (M = 2.90, SD = .84) than
did evening people (M = 2.72, SD = .93), t(1842) = 3.56,
p < .01. In response to a statement “I generally sleep badly,”
those who indicated this described them “very much” had a
significantly lower GPA (M = 2.35, SD = 1.10) than those
who indicated it was “rather much” (M = 2.71, SD = .79),
“somewhat” (M = 2.75, SD = .97), or “not at all” (M = 2.82,
SD = .88) true of themselves, F(3, 1836) = 7.32, p < .01.
Grade point average was significantly but weakly corre-
lated with amount of sleep prior to school/work (r = .12, p <
.01), and with the difference score (r = −.06, p < .05), indi-
cating that students who got more sleep before school/work
and those who reported more consistent sleep schedules had
higher grades. Although significant, these correlations are
still small, and should be interpreted cautiously.
Another way to characterize the “real-world” associations
between potential sleep disorders and GPA is to examine
numbers of students at risk for a sleep disorder who are
TABLE 2. Percent Male and Female Students at Risk for Each Sleep Disorder
Male (N = 542) Female (N = 1303) χ 2(1) ϕ
OSA 3 (16) 4 (58) 2.24 .04
PLMD/RLS 6 (31) 9 (121) 6.44∗ .06
Insomnia 8 (44) 14 (182) 12.19∗∗ .08
Affective disorder 4 (21) 8 (110) 12.11∗∗ .08
CRDs 7 (37) 7 (97) 0.22 .01
Nightmares 1 (6) 3 (34) 4.07∗ .05
Hypersomnia 4 (19) 4 (49) 0.07 .01
≥1 disorder 23 (125) 29 (379) 7.00∗∗ .06
∗∗p < .01; ∗p < .05.
VOL 59, SEPTEMBER/OCTOBER 2010 93
Gaultney
TABLE 3. Percent Students at Risk for Each
Sleep Disorder Who Are Also at Academic
Risk (GPA < 2.0) and χ2 Comparisons to
Students With GPA ≥ 2.0
% at academic
risk (N) χ 2 ϕ
OSA 30 (22) 10.70∗∗ .08
PLMD/RLS 21 (32) 3.07# .04
Insomnia 22 (49) 6.24∗ .06
Affective
disorder
19 (25) 1.05 .02
CRDs 26 (35) 10.87∗∗ .08
Hypersomnia 21 (14) 1.08 .02
≥1 disorder among
Total sample 22 (110) 17.37∗∗ .10
Males 21 (26) 1.87 −.06
Females 22 (84) 16.84∗∗ −.11
African
Americans
38 (32) 6.14∗ −.14
White 18 (61) 10.20∗∗ .09
∗∗p < .01; ∗p < .05; #p < .10.
also at risk academically. At this institution, students must
maintain a 2.0 GPA. If they fall below that they are put on
academic probation and, unless the GPA improves over the
next semester, expelled. A significant number of students
at risk for OSA, insomnia, or CRDs were also in academic
peril (Table 3). Individuals at risk for at least one disorder
were significantly overrepresented in the group with a GPA
< 2.0. This disparity was most apparent among female stu-
dents. African American and white students at risk for a sleep
disorder were at equal risk academically.
COMMENT
Seventy million Americans (∼23%) are reported to have
some type of sleep disorder.16 The 27% reported by this sam-
ple is in line with that estimate. Prevalence for each sleep dis-
order in this sample was consistent with those reported in the
literature, with one glaring exception. Narcolepsy likely af-
fects <1% of adults.17 The finding that 16% of students were
at risk for narcolepsy is high. There was no reason to assume
that this sample was at any greater risk than similar ones,
although this possibility cannot be ruled out. The anomaly
could be due to some characteristic of the Narcolepsy scale
on this questionnaire. Spoormaker et al15 noted that the Nar-
colepsy scale was the most problematic, with one of its items
loading on the IDF scale, and another loading on both Nar-
colepsy and Nightmares scales. The Narcolepsy scale for this
sample may be conflated with other sleep disorders. This ar-
gument is strengthened by the fact that all 89% of students
who were at risk for narcolepsy were also at risk for at least
one other disorder. Arguing against overinclusion, however,
is the finding in the validation study of a specificity score
of .86, but a sensitivity score of just .67 for the Narcolepsy
scale, suggesting that the scale did a good job of excluding
those who did not have narcolepsy, but did less well at identi-
fying those who did have narcolepsy. If anything, narcolepsy
should have been underestimated.
Students at risk for OSA were overrepresented within stu-
dents with a GPA < 2.0, as were those at risk for insomnia,
CRDs, or at least one sleep disorder. Why female, African
American, and white students had the greatest connection be-
tween risk for a sleep disorder and lowered GPA is not clear.
Future research will need to examine group differences in
severity of sleep disorders and comorbid risk factors.
A number of mechanisms may explain the relation be-
tween sleep disorders and academic performance. An ob-
vious one is daytime sleepiness, with lowered levels of at-
tention,18 and impaired memory and decision making. 19 If
daytime sleepiness was the only culprit, however, it is not
clear why the same relation with academic performance was
not found for PLMD/RLS or hypersomnia. It is possible that
students with these disorders were less sleepy than other
groups; however, in the absence of a measure of sleepiness,
we cannot speculate on relative degrees of daytime sleepiness
associated with risk for these disorders.
Adequate, uninterrupted sleep may optimize learning and
cognitive functioning. Sleep appears to play an important, al-
though not well-understood, role in memory consolidation.20
Sleep after study promotes integration of newly acquired
material with existing memories. Untreated sleep disorders,
therefore, may hamper a student’s ability to learn new ma-
terial well. Obstructive sleep apnea has been associated with
cognitive deficits,21 and treatment of OSA may21 or may
not22 improve cognition. Less directly, poor sleep might im-
pact learning by means of reduced motivation, compromised
health, or depressed mood.
In the current sample, race/ethnicity did not produce sig-
nificant differences in risk for sleep disorders. Although
some studies have found Caucasians to be at greater risk
for RLS/PLMD, others have found no race differences.23
African Americans have been reported to be at greater risk
for OSA.24 It may be that race/ethnic differences in sleep dis-
orders were not found in the present study because college
students are not representative of adults in general. For exam-
ple, they may have more ready access to health care. Because
of the lack of consensus in the literature about race/ethnic dif-
ferences in prevalence of sleep disorders, the nonsignificant
trends reported here, and the potential benefits of identifying
those most at risk for specific sleep disorders, future research
should further explore any race- or ethnicity-related differ-
ences in sleep disorders.
Females were at greater risk for RLS/PLMD, insomnia,
affective disorder, nightmares, and more likely to be at risk
for at least one sleep disorder. Other studies have found fe-
males to be at greater risk for RLS.25 There could be several
reasons for this, such as pregnancy, low iron levels (iron is an
essential cofactor for the metabolism of dopamine),26 or ge-
netics.27 Insomnia, affective disorders, and nightmares may
represent co-occurring sleep and mood problems that are
closely intertwined and likely transactional. Nightmares and
short sleep duration are associated with suicidal behavior.28
94 JOURNAL OF AMERICAN COLLEGE HEALTH
Prevalence of Sleep Disorders in College
Distress associated with nightmares predicts greater levels
of psychological disturbance.29 Women are more likely to
report depression, anxiety, and nightmares, which are asso-
ciated with stress and psychopathology.30 Therefore, insom-
nia and nightmares might be related to depressive symptoms
among women in this sample. This will need to be tested by
future research.
Most students in this sample considered themselves to be
evening people and reported insufficient sleep during the
week, which they tried to make up on the weekends, result-
ing in a day-of-week discrepancy of almost 2.5 hours. These
self-reported amounts of sleep need to be verified by objec-
tive measures such as actigraphy. Being an evening person,
sleeping “badly,” getting less sleep, and having inconsistent
bedtimes predict a lowered GPA. These behaviors may be
modifiable (given sufficient motivation), and education about
sleep hygiene may be useful, perhaps as part of an interven-
tion package for students who are struggling academically.
Assuming an average basal sleep need of 8 hours per
night,3 the students in this sample, who reported a mean of
6.79 hours of sleep during their school/work week, lost 6.05
hours of sleep over 5 days. Even though they compensated
by getting extra sleep on the weekends, this extra sleep (2.6
hours over a 2-day period) was not enough to compensate for
the lost sleep during the week, resulting in a mounting sleep
debt. Although there are individual differences in amount of
sleep needed, the fact that 86% of the participants reported
that waking up tired was somewhat, rather much, or very
much true of them indicates that the majority of students
were not getting adequate rest.
Identification and treatment of students with sleep disor-
ders may produce benefits such as improved academic per-
formance and better quality of life. If the findings reported
here are representative, then sleep screening and treatment
among college students may be of great benefit, particularly
among individuals at risk for academic failure.
Diagnosis and treatment of sleep disorders could lead to
increased or more consolidated sleep in young adults, and
may improve cognition and mood. When 15 college students
were asked to sleep as much as possible at night during
the sleep-extension phase of one study,30 daytime sleepiness
decreased, and reaction time, mood, and fatigue improved,
despite the fact that participants had reported little daytime
sleepiness prior to the extension phase. Additional research
is needed to determine whether treating sleep disorders trans-
lates into improved academic performance and/or quality of
life.
A few universities have tried interventions intended to im-
prove sleep. Although several studies emphasize a need to
educate college students about good sleep hygiene, it is not
established that this will change sleep behavior or daytime
outcomes. Tsai and Li31 evaluated the effectiveness of a 2-
credit course on sleep management. Lectures, group discus-
sion, and self-evaluation were used to educate 241 college
students about sleep hygiene, resulting in improved sleep
quality, but not sleep patterns. The authors concluded that
the course had only a mild impact on sleep behaviors. Other
evidence, however, suggests that knowledge of sleep hygiene
does impact sleep-related behavior, with increased knowl-
edge of sleep hygiene resulting in better sleep practices,
which, in turn, was associated with better sleep quality.32 One
reason for this discrepancy may be undetected and untreated
sleep disorders. Education can highlight poor sleep practices,
but cannot overcome a physiologically based sleep disorder.
Future research can test the effectiveness of sleep education
among those with no apparent risk for a sleep disorder.
In a best-case scenario, successful treatment of sleep dis-
orders or improved sleep practices might increase GPAs,
improving students’ chances of staying in school and ulti-
mately graduating. Although it is reasonable to expect that
a successfully treated sleep disorder will contribute to aca-
demic success, a cause-and-effect relationship has not been
established. Given the potential prevalence of sleep disorders,
careful study is needed. Extrapolating from the percentages
obtained from this sample, 6,575 students in this institu-
tion might be at risk for a sleep disorder, with 1,446 of the
6,575 already in academic trouble. Obviously, there are many
other factors that could influence grades, retention, and grad-
uation rates that are unrelated to sleep. However, it seems
reasonable for colleges to consider adding sleep screening
and intervention early in students’ academic experience in
an effort to improve student health as well as retention and
graduation rates. Sleep screening is low-cost and easy to im-
plement. Follow-up plans to direct at-risk students to sleep
labs accredited by the American Academy of Sleep Medicine
would need to be developed. Large-scale screening and re-
ferral of entering college students, and any related outcomes,
need to be examined in a prospective study.
Few large-scale studies have examined patterns of risk
for sleep disorders among college students in light of gender,
race, and academic success. One strength of the current study
is the use of a survey that was validated for this population.
GPA was actual rather than self-reported and was current as
of the end of the semester in which the survey was taken.
No survey, however, can take the place of diagnosis by a
sleep physician. Although the survey results could identify
participants at risk for a sleep disorder, it was not known
whether they had a diagnosable disorder. In addition, factors
unrelated to sleep almost certainly influenced GPA. Another
limitation of the study was the inflated Narcolepsy scale.
Further validation of this scale is needed.
This report is an initial look at an understudied population.
It raises issues that require additional study, especially with
regard to the actual prevalence of sleep disorders among
college students as a group as well as among subgroups;
effective approaches to screening for sleep disorders; the
academic, social, and health outcomes of identifying and
treating sleep disorders; and effective means of promoting
sleep awareness and good sleep practices among college stu-
dents. Given cultural differences in beliefs about and patterns
of sleep,33 interventions for sleep practices may need to be
culture specific. Online surveys offer a practical approach to
screening large numbers of students, but plans must be in
place to notify students who are at risk for a sleep disorder
VOL 59, SEPTEMBER/OCTOBER 2010 95
Gaultney
and to direct them to an appropriate physician. Information
about good sleep practices could be integrated into freshmen
seminars or introductory meetings. Producing a fundamen-
tal change in sleep-related behavior and attitudes, however,
is a much more daunting task. The length and content of
effective interventions will need to be established. Identify-
ing and treating sleep disorders will likely be simpler than
convincing a student to practice good sleep hygiene.
In summary, these data indicate a substantial number of
college students may be at risk for sleep disorders or poor
sleep hygiene, and that sleep may impact academic success.
Institutions of higher learning are concerned about student
retention and graduation rates.34 Twenty-seven percent of
the present sample were at risk for at least one sleep dis-
order. Risk for a sleep disorder predicted GPA, which, in
turn, predicts students’ persistence in college.35 Identifica-
tion and successful resolution of sleep problems, therefore,
might increase retention and graduation rates. Czeisler,36 re-
ferring to businesses, stated that “[p]aying attention to sleep
is the low-hanging fruit that could dramatically raise produc-
tivity.” Perhaps the same will be true for academic produc-
tivity, although further study is needed to see the impact of
treatments. It is worth the effort to identify and treat sleep
disorders among college students in hopes of improving their
overall health as well as their academic success.
NOTE
For comments and further information, address correspon-
dence to Dr Jane F. Gaultney, PhD, Department of Psychol-
ogy, University of North Carolina at Charlotte, 9201 Uni-
versity City Boulevard, Charlotte, NC 28223, USA (e-mail:
jgaultny@uncc.edu).
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