Sleep patterns in college students

Abstract

Objective: Since gender effect is inconsistent and grade effect has not been addressed in previous studies, we investigated both effects on the daily sleep patterns in a group of young college students. Methods: The sample consisted of 237 students aged 18–24 years. Each subject completed a 7-day sleep log. Results: Gender differences were found in several sleep variables and those were mostly not dependent on weekday/weekend difference. The female students went to bed and rose earlier and had longer sleep latency, more awakenings, and poorer sleep quality than the male. Gender differences were also shown in the relationship between sleep quality and other sleep variables. The correlation between sleep quality and rise time, time in bed, and sleep efficiency was stronger in men than in women. In contrast, grade differences were mostly dependent on weekday/weekend difference. The freshmen rose earlier and had shorter sleep time than did the other students on weekdays only. Sleep latency was the longest in seniors on weekdays only. Conclusion: This study showed that gender differences in sleep patterns and sleep difficulties were remarkable in the group of young college students. Alarmed by the high prevalence of sleep difficulties among general college students, it is recommended that the students should be informed of their sleep problems and the consequences.

Full text

Sleep patterns in college students
Gender and grade differences
Ling-Ling Tsai*Sheng-Ping Li
Department of Psychology, National Chung-Cheng University, 160 San-Hsing, Ming-Hsiung, Chia-Yi 621, Taiwan, ROC
Received 16 September 2002; accepted 3 July 2003
Abstract
Objective: Since gender effect is inconsistent and grade effect
has not been addressed in previous studies, we investigated both
effects on the daily sleep patterns in a group of young college
students. Methods: The sample consisted of 237 students aged
18–24 years. Each subject completed a 7-day sleep log. Results:
Gender differences were found in several sleep variables and
those were mostly not dependent on weekday/weekend differ-
ence. The female students went to bed and rose earlier and had
longer sleep latency, more awakenings, and poorer sleep quality
than the male. Gender differences were also shown in the
relationship between sleep quality and other sleep variables. The
correlation between sleep quality and rise time, time in bed,
and sleep efficiency was stronger in men than in women. In
contrast, grade differences were mostly dependent on weekday/
weekend difference. The freshmen rose earlier and had shorter
sleep time than did the other students on weekdays only. Sleep
latency was the longest in seniors on weekdays only. Conclusion:
This study showed that gender differences in sleep patterns and
sleep difficulties were remarkable in the group of young college
students. Alarmed by the high prevalence of sleep difficul-
ties among general college students, it is recommended that
the students should be informed of their sleep problems and
the consequences.
D2004 Elsevier Inc. All rights reserved.
Keywords: Gender differences; Sleep disturbances; Undergraduates; University students
Introduction
Previous studies in general adult population have shown
that sleep patterns are both quantitatively and qualitatively
related to the age and gender [1–4]. The prevalence of
insomnia is found to be more common among old people
and in women [2,5–11]. A recent study showed that the
prevalence of global dissatisfaction with sleep increased
with age and was higher in women [12]. Significant age
differences are also found in both habitual sleep patterns and
sleep disturbances in adolescents. Among both girls and
boys, bedtime [3,13 – 15] is delayed, total sleep time is
decreased [3,13 –17], and the prevalence of sleep problems
increases with age [16]. Compared to older adolescents,
young adults go to bed even later and sleep even less
[3,13,18]. Disrupted sleep, daytime sleepiness, and dissat-
isfaction with sleep are more common in young adults than
in adolescents [19].
In contrast to age difference, few gender differences in
sleep patterns and sleep disturbances have been reported in
adolescents [3,14 – 17]. Although girls go to bed later,
wake up earlier, and thus sleep less than boys, they do
not have sleep problems more frequently than boys [16].
Compared to adolescents, gender differences in young
adults seem to be more frequently reported. Women aged
between 18 and 24 years go earlier to bed and wake up
earlier than men [3] but have equivalent amounts of total
sleep time, number of awakenings, and daytime naps [3,9].
With a wider age range, a study found that women (age 17
to 30 years) were more likely to have nightmares, delayed
sleep onset, and frequent night awakenings [20]. Another
study using Pittsburgh Sleep Quality Index (PSQI) showed
that women aged 20–29 years have poorer sleep quality
than men [1]. Reyner and Horne [4], using sleep logs and
actimetry, found no significant gender differences in sleep
latency, wake up time, total sleep time, or sleep quality in
the 20–34 years group, but they found that women had
0022-3999/04/$ – see front matter D2004 Elsevier Inc. All rights reserved.
doi:10.1016/S0022-3999(03)00507-5
* Corresponding author. Tel.: +886-5-2720411x32201; fax: +886-5-
2720857.
E-mail address: psyllt@ccu.edu.tw (L.-L. Tsai).
Journal of Psychosomatic Research 56 (2004) 231 – 237

more nocturnal awakenings than men. The major cause of
awakenings in these young women is children. A home-
based electrophysiological sleep recording study in the
group of 20–34 years also failed to find significant gender
differences in total sleep time, sleep latency, wake after
sleep onset, and sleep efficiency. However, it did show that
young men had less slow wave sleep than young women
[21]. One epidemiological study found that the prevalence
of insomnia was higher but that of insufficient sleep was
lower in young women aged 20 – 39 years than in young
men [2]. Taken together, although gender differences in
sleep patterns and sleep disturbances are global and
substantial in general adult population, they are inconsis-
tent and, if any, relatively small effect size in young adults.
Furthermore, some sleep parameters, which are more
related to sleep disturbances, e.g., sleep latency, number
of nocturnal awakenings, and sleep quality, show gender
differences starting only in the age of 20s. Some biological
maturational processes may contribute to gender differ-
ences in the sleep patterns and cause sleep disturbances in
young adults. However, factors other than biological ones
such as role in family, response to stress, and life style
(eating, drinking, smoking, exercise, etc.) can also be
involved in gender differences. For example, it has been
reported that child caring and disturbances due to the bed
partner are the two major causes of nocturnal awakenings
in young women [4].
Many college students are single and at their late
adolescent and early adult ages. Their sleep patterns and
sleep disturbances could be different from those of non-
students at their ages [13]. Compared to nonstudent adults
in their 20s, college students have later bedtime and rise
time and show higher incidence of daytime sleepiness in
addition to physical and mental health complaints. Al-
though the student group has the lowest prevalence of
global sleep dissatisfaction of all occupations [12], 71% of
college students express dissatisfaction with their sleep
[22]. Previous studies in college students do not show
consistent gender differences in sleep patterns. One study
showed that gender differences were not associated with
time in bed, number of awakenings, or sleep quality [23].
Another study found no gender difference in sleep latency
[24]. In contrast, contradictory findings in gender differ-
ences have been reported. Both shorter [25] and longer
[26] sleep duration and both poorer [27] and better [26]
sleep quality have been reported in men than in women.
For sleep disturbances, both significantly lower [24] and
higher [27] incidence have been reported in men than in
women. These discrepancies cannot be simply attributed to
cultural differences of student samples since some studies
in the same country also showed inconsistent results, e.g.,
Refs. [23–25]. Age, however, could be one of the con-
founding factors since gender difference effect sizes in
most sleep parameters are small and even smaller in
younger ages. Most studies included a wide age range of
college students, e.g., Refs. [23–26].
In this study, we intended to determine gender effect on
daily sleep patterns in college students aged 18 – 24 years.
If gender differences occur in such a narrow age range, it
would be concluded that gender did play a significant role
in sleep patterns in early adulthood. Another purpose of
this study is to investigate whether grade (educational
level), related to biological as well as academic age, is
involved in sleep patterns in college students.
Methods
Subjects
The sample consisted of 237 college students enrolled
in the course of ‘‘Sleep Management’’ offered in the
spring semester in 1998 and open to all the students in
the authors’ university. The students were distributed
evenly in three classes at three different time slots
(8:10–10:00 a.m., 2:10–4:00 p.m., 4:10–6:00 p.m.) on
Wednesday. The students who took this course were
required to record 7-day sleep logs in the first month
of the class as the course assignment. However, they
were solicited to give their permission on the incorpora-
tion of their sleep log data in this study as courtesy and
were informed that no extra credit would be given for
their participation. Of the 362 students enrolled in the
class, 314 completed the consent forms. Among them,
237 students were aged 18 – 24. Students from all aca-
demic fields of the university, i.e., arts, social sciences,
science, engineering, law, and business, were included in
the study.
Materials and measures
The daily sleep patterns were recorded in sleep logs. It
has been shown that subjective estimates of sleep time
and sleep latency in the mornings after the overnight
sleep recordings are positively correlated to recorded
sleep time and sleep latency, respectively [28,29]. The
sleep log form was designed for a 7-day recording period
and tended to show the daily sleep pattern of the users.
The form included a line space at the top for filling in
subject name, major, grade, and recording period. This
was followed by the instruction translated as ‘‘Please
record the daily sleep information in 5 minutes after
getting up. Record each nap in 5 minutes after waking
up as well.’’ A grid was placed below the instructions.
The grid included dates (listed as rows in the first
column) and headings for eight self-reported question
variables and four self-calculated variables (listed as
columns in the first row). The question variables included
bedtime, time falling asleep, number of awakenings
during the sleep period, time waking up, rise time, sleep
quality evaluation (from 1 = extremely awful to 10 = ex-
tremely great), naptime, and significant events on the
L.-L. Tsai, S.-P. Li / Journal of Psychosomatic Research 56 (2004) 231–237232

previous day. The self-calculated variables included sleep
latency, time asleep, time in bed, and sleep efficiency.
Data analysis
A total of 12 variables were derived from sleep logs.
Bedtime, rise time, number of awakenings, sleep quality,
and naptime were recorded by subjects. Sleep latency (the
time difference between bedtime and time falling asleep),
time asleep (the time difference between time falling asleep
and time waking up), time in bed (the time difference between
bedtime and rise time), sleep efficiency (time asleep 100/
time in bed), total sleep (the sum of sleep time at night and
naptime during the day), bedtime regularity (standard devia-
tion of bedtime over the 7-day recording period), and rise time
regularity (standard deviation of rise time over the 7-day
recording period) were then calculated. For bedtime, rise time,
time asleep, time in bed, and total sleep, we used 2
(genders) 4 (grades: freshman, sophomore, junior, and
senior) 2 (days: weekday, weekend) analysis of variances
(ANOVAs) with repeated measures on day. The data dis-
tributions of sleep latency (skewness g1 = 1.123), number of
awakenings (g1 = 2.886), sleep efficiency (g1 = 1.433),
sleep quality (g1 = 0.893), naptime (g1 = 1.045), bedtime
standard deviation (g1 = 1.365), and rise time standard
deviation (0.797) were significantly skewed. Since signifi-
cantly skewed sample violates the assumption of normality
associated with parametric statistical methods, nonpara-
metric statistical methods were used and medians/semi-
interquartile ranges were presented for those skewed data.
Gender effect was evaluated by Mann – Whitney test with
chi-square approximation, grade effect by Kruskal – Wallis
test, and day effect by Wilcoxon signed ranks test with
normal (z) approximation.
Based on the cutoff values with significantly increased
odds ratios of global sleep dissatisfaction in [12], we define
sleep difficulties as time in bed less than 7 h or mean sleep
latency longer than 30 min. We also arbitrarily defined
sleep difficulties as the number of awakenings more than
once, sleep efficiency less than 85%, rating on sleep quality
less than 6, or naptime longer than an hour. Pearson chi-
square tests were performed for evaluating the dependency
of the distribution of each sleep difficulty on gender and on
grade, separately.
Pearson correlation was calculated between sleep qual-
ity and other sleep variables for each subject. The Fisher’s
rto ztransformation was then performed for each corre-
lation coefficient. One-group ttest was used to test whether
the means of the zscores were zero and independent ttest
was used for the gender differences. We performed post
hoc comparisons of means by using Tukey’s test for
ANOVAs and Mann–Whitney test for Kruskal–Wallis test.
All statistical analyses were performed using SYSTAT 7.0
for Windows.
Results
The demographic characteristics of the participating
college students are depicted in Table 1. No gender differ-
Table 1
Demographic characteristics of participating college students
Gender Freshman Sophomore Junior Senior
Woman Age, year (range) 18.9 F0.8 (18 – 21) 20.3 F1.05 (19 – 23) 21.1F0.8 (20 – 24) 22.2 F0.6 (21 – 23)
Subject number 29 24 31 26
Man Age, year (range) 19.1 F0.8 (18 – 21) 20.0 F0.9 (19 – 22) 21.6 F0.9 (20 – 24) 22.7F0.6 (22 – 24)
Subject number 48 19 48 12
Table 2
Sleep variables for weekdays and weekends by gender
Woman (n=110) Man (n= 127)
Sleep variable Weekday Weekend Weekday Weekend Statistical significance
Bedtime (hh:mm Fmin) 1:27 F57 1:21 F69 1:40 F55 1:45 F82 G*
Rise time (hh:mm Fmin) 8:27 F61 9:12 F79 8:39 F57 9:39 F89 G*, D***
Time asleep (min) 381 F57 428 F65 384 F52 438 F75 D***
Time in bed (min) 420 F57 471 F63 418 F51 474 F69 D***
Total sleep (min) 419 F60 466 F78 411 F60 465 F87 D***
Sleep latency (min) 17.5/6.4 15.0/5.7 14.0/5.7 12.0/6.5 G*, D**
Number of awakenings 0.8/0.5 1.0/0.5 0.6/0.4 0.5/0.5 G**
Sleep efficiency (%) 92.1/3.4 93.3/3.8 93.0/2.7 94.4/2.5 D**
Sleep quality 7.2/0.6 7.5/0.7 7.6/0.9 8.0/0.9 G*, D***
Naptime (min) 36.0/22.7 26.4/30.0 22.2/20.7 24.0/23.7 G*
Data are presented as means FS.D. or medians/semi-interquartile ranges. See the text for a detailed description. Subject numbers (n) are given in parentheses.
Gender effect is abbreviated as G and day effect as D.
* Significant difference P< .05.
** Significant difference P< .01.
*** Significant difference P< .001.
L.-L. Tsai, S.-P. Li / Journal of Psychosomatic Research 56 (2004) 231–237 233

ence was found in the mean age. The mean age consistently
increased with grade ( F= 164.24, df = 3.233, P=.0001). It
was noted that the number of males in sophomore and
senior years was less than that of freshmen and juniors.
However, we thought this would have, if any, few effect
on gender and grade interaction since interaction effect of
gender and grade was not significant on any sleep variable.
Weekday/weekend differences
As shown in Table 2, the rise time ( F= 84.36, df = 1.229,
P< .001), but not bedtime, was significantly earlier on
weekdays than on weekends. The students spent signifi-
cantly less time in bed ( F= 123.45, df = 1.229, P< .001),
slept shorter ( F= 102.22, df = 1.229, P< .001), had less total
sleep ( F= 74.40, df = 1.229, P< .001), longer sleep latency
(z= 3.274, P= .001) and lower sleep efficiency (z= 3.237,
P= .001), and gave significantly lower ratings on sleep
quality (z= 4.201, P< .001) on weekdays as compared with
those on weekends.
Gender differences
Table 2 also shows that the women had earlier bedtime
(F=5.35, df =1.229, P= .022) and rise time ( F=4.14,
df =1.229, P= .043), longer sleep latency (v
2
=6.00,
df =1, N= 237, P= .014 on weekdays; v
2
= 4.84, df =1,
N= 237, P= .028 on weekends), more awakenings during
night sleep (v
2
= 7.12, df =1, N= 237, P= .008 on week-
days; v
2
= 12.54, df =1, N= 237, P< .001 on weekends),
lower ratings on sleep quality (v
2
= 3.52, df =1, N= 237,
P= .061 on weekdays; v
2
= 9.92, df =1, N= 237, P= .002 on
weekends), and longer naptime (v
2
= 7.95, df =1, N= 237,
P= .005 on weekdays; v
2
= 5.48, df =1, N= 237, P= .019 on
weekends) than the men. Gender differences were not
significant in the bedtime regularity (median/semi-interquar-
tile range: 50/16 min in women vs. 52/18 min in men) or the
rise time regularity (66/18 in women vs. 73/22 in men).
Bedtime was more regular than rise time (Wilcoxon signed
ranks test, zapproximation = 6.13, P< .001).
We define sleep difficulties as time in bed less than
7 h, mean sleep latency longer than 30 min [12], number
of awakenings more than once, sleep efficiency less than
85%, rating on sleep quality less than 6, or naptime
longer than an hour. The percentage of difficulties in
sleep latency was significantly higher in women (11.82%
on weekdays and 15.45% on weekends) than in men
(11.81% on weekdays and 6.30% on weekends) on
weekends. Sleep difficulties in the number of awakenings
were also higher in women (40.91% on weekdays and
37.27% on weekends) than in men (25.20% on weekdays
and 18.11% on weekends). Lastly, more women (21.82%
on weekdays and 23.64% on weekends) than men
(11.02% on weekdays and 21.82% on weekends) took
mean naptime longer than an hour on weekdays. In
contrast, gender differences were not found in the per-
centage of sleep difficulties in time in bed (48.94% of all
the students on weekdays and 19.83% on weekends),
sleep efficiency (12.66% on weekdays and 15.19% on
Table 3
Correlations between sleep quality and other sleep variables
Sleep variable Woman (n= 110) Man (n= 127)
Bedtime .061 F.562 .029 F.545
Rise time* .042 F.546 .215 F.537
yyy
Time asleep .241 F.615
yyy
.370 F.571
yyy
Time in bed* .064 F.560 .258 F.586
yyy
Sleep latency (min) .304 F.575
yyy
.397 F.644
yyy
Number of awakenings .405 F.682
yyy
.396 F.925
yy
Sleep efficiency (%)* .374 F.594
yyy
.532 F.624
yyy
Naptime (min) .042 F.498 .139 F.917
Data are presented as means FS.D. The correlation coefficients of each
subject were converted to Fisher’s zscores, and the means and standard
deviations of the zscores were then converted back to correlation
coefficients. One-group ttest was performed to test whether the means of
the zscores were zero and independent ttest for gender differences.
* Significance level for gender differences, P< .05.
y
Significance level for one-group ttest, P< .05.
yy
Significance level for one-group ttest, P< .01.
yyy
Significance level for one-group ttest, P< .001.
Fig. 1. Mean and standard deviation of rise time (top), time in bed (middle),
and time asleep (bottom) across grade on weekdays and weekends.
L.-L. Tsai, S.-P. Li / Journal of Psychosomatic Research 56 (2004) 231–237234

weekends), or sleep quality (14.77% on weekdays and
10.55% on weekends).
The relationship between sleep quality and other sleep
variables is presented in Table 3. Sleep quality was posi-
tively correlated with time asleep and sleep efficiency but
negatively with sleep latency and number of awakenings in
both men and women. In contrast, sleep quality was
correlated with rise time and time in bed in men but not
in women. Furthermore, the relationships between sleep
quality and rise time, time in bed, and sleep efficiency were
stronger in men than in women.
Grade differences
Interaction effect of grade and day was found on rise time
(F=3.83, df = 3.229, P= .011), time in bed ( F= 4.19,
df = 3.229, P= .007), and time asleep ( F= 3.50, df = 3.229,
P= .016). The freshmen had a shorter sleep time at night
than other students on weekdays, which was not due to the
bedtime difference but an earlier rise time on weekdays (Fig.
1). Of all the students, the seniors had the longest sleep
latency (v
2
= 8.83, df =3, N= 237, P= .032 on weekdays;
v
2
= 5.57, df =3, N= 237, P= .134 on weekends) and nap-
time (v
2
= 18.76, df =3, N= 237, P< .001 on weekdays;
v
2
= 9.35, df =3, N= 237, P=.025 on weekends; Fig. 2).
The percentage of sleep difficulties in time in bed was the
highest in the freshmen on weekdays (v
2
= 16.84, df =3,
N= 237, P< .001). Difficulties in sleep latency were the
highest in the seniors on weekdays (v
2
=9.14, df =3,
N= 237, P= .027). Grade differences were not found in
the percentage of sleep difficulties in awakenings, sleep
efficiency, sleep quality, or naptime.
Daytime napping and nighttime sleep
To determine whether longer naptime was related to
worse sleep patterns at night [29], we compared the sleep
variables of the students whose naptime was longer than an
hour with those of the rest of the students. Indeed, students
with long naptime had more awakenings at night
(v
2
= 11.13, df =1, N=237, P= .001 on weekdays;
v
2
= 6.99, df =1,N= 237, P= .008 on weekends) and poorer
sleep quality (v
2
= 6.04, df =1, N= 237, P= .014 on week-
days; v
2
= 3.10, df =1, N= 237, P= .078 on weekends).
Discussion
This study aimed to determine gender and grade effects
on daily sleep patterns in the college students aged 18 – 24
years. Significant gender and grade differences in several
sleep variables were found in this student group. Although
the student subjects were recruited exclusively from those
enrolled in a single course, the gender and grade effect on
sleep might not be specific to this particular group of
students. First, the means of all, except for naptime, sleep
variables in this study were comparable to those of a group
of undergraduates who did not take the course (n= 49,
unpublished data). Second, though the students enrolled in
the sleep management course could be somewhat more
concerned about their sleep, they probably did not have
more sleep problems than other students. The PSQI scores
of the students who took the course were not higher but
even lower than those of the students who did not took the
course (mean global PSQI score, 5.46 F1.75, n= 279 vs.
Fig. 2. Medians and semi-interquartile range of sleep latency (top) and naptime (bottom) across grade on weekdays and weekends.
L.-L. Tsai, S.-P. Li / Journal of Psychosomatic Research 56 (2004) 231–237 235

6.52 F2.42, n= 42; unpublished data). Nonetheless, we
could not definitively exclude the possibility that female
students and/or seniors tended to select the course because
of sleep difficulties, which might thereby be related to the
gender and grade effect shown in this study.
As previous studies have shown, the college students
woke up later, had longer time in bed and sleep time, and
reported better sleep quality on weekends [17,23,24].In
contrast to the results in [24], this study showed that the
bedtime on weekends remained the same as on weekdays.
The discrepancy could be explained by much later bedtime
on weekdays shown in this study than previously shown.
The students went to bed on weekends at the time equiv-
alent to those in [24]. On the other hand, not reported
previously, the students had shorter sleep latency and better
sleep efficiency on weekends. Stress, especially the emo-
tional responses to it, is related to several sleep aspects,
including sleep latency [31]. It is possible that for some
students, less stress on weekends is one of the factors related
to shorter sleep latency on weekends. Furthermore, based on
their relationship to sleep quality (Table 2), shorter sleep
latency, longer sleep time, and higher sleep efficiency all
directed to better sleep quality on weekends.
In contrast to previous studies, which mostly failed to
find gender differences in daily sleep patterns, we did find
those in several sleep variables. Given that female college
students reported a higher level of stress than male students
[32] and, as mentioned above, that stress is related to sleep
[31], stress could be involved in the gender difference in
sleep. On the other hand, since gender differences were also
shown in the relationship between sleep quality and other
sleep variables, sleep perception and cognition difference
could be another factor. However, future studies are still
needed to clarify how biological and psychological matura-
tional processes, stress, sleep perception, and cognition, as
well as other factors, relate to gender differences in self-
reported sleep patterns in college students.
One special aspect concerning gender differences is that
the poorer sleep patterns and the higher prevalence of sleep
difficulties in the female college students persist even on
weekends. It was further noted that the number of women
with sleep latency difficulty even increased on weekends
compared to weekdays. In contrast, the number of men with
sleep latency difficulty decreased on weekends. It seemed
that weekend was of benefit to men but not to women in
terms of reduction in sleep latency difficulty. We think this
finding is very important and merits further studies. Week-
ends are thought to be more relaxed and thus more helpful
to a good night sleep than weekdays. Why women could not
take the advantage of weekends like men needs further
studies to answer the question. Another thing to be pointed
out is that unexpected gender differences were also found in
the number of awakenings at night in these young college
students. One previous study in general young adults found
that the major causes of more awakenings in young women
were children and bed partners [4]. Of the 237 students
participating in this study, 235 students answered question
10 (‘‘Do you have a bed partner or roommate?’’) in PSQI
administered in class as a course activity. Only 4 of the 235
student reported having a partner in same bed. On the other
hand, married rate was below 16% and fertility rate was
below 7% in women aged 20 – 24 years in Taiwan (MOI
Statistical Information Service http://www.moi.gov.tw/W3/
stat/, Department of Statistics, Minister of the Interior,
ROC). It is likely that most female students in this study
were single and had no children. Even if most of them had
no children and had no bed partners, the women still had
more night awakenings than the men. The relationship
between naptime and awakenings suggests longer naptime
could be attributed to more awakenings in the female
college students. Future studies are still needed to clarify
whether other factors also cause the young female college
students to wake up more frequently at night.
To the best of our knowledge, this is the first study to
show an interaction effect between grade and weekday/
weekend on sleep among college students. Grade differ-
ences in sleep patterns were shown mostly on weekdays
only. The freshmen got up earlier and slept less compared to
other students on weekdays but not on weekends. The
seniors having the longest sleep latency were shown only
on weekdays. Over twice more seniors (26.31%) than other
students (9.03%) had sleep latency difficulty on weekdays
but not on weekends. It is likely that grade differences
shown only on weekdays were due to different activity
schedules and academic demands on weekdays in different
grades instead of biological age differences. Although those
grade differences subsided on weekends, the much higher
number of short sleep time in the freshmen (67.53%) and
that of sleep latency difficulty in the seniors on weekdays
still warrant a heightened attention to the grade-related sleep
problems among college students.
In summary, this study found significant gender and
grade differences in several sleep variables among college
students. The gender difference in most sleep variables did
not depend on weekday/weekend difference, but the grade
difference depended on weekday/weekend difference. The
poorer sleep patterns of the female students on both
weekdays and weekends warrant special attention to the
progress of their sleep problems in the long run. The
freshmen need to be especially aware of the consequences
of insufficient sleep and the seniors need to deal with long
sleep latency and naptime. On the other hand, this study
found that the percentage of sleep difficulties in general
college students was amazingly high, e.g., over 48% of the
college students had short sleep time, which suggests a
probably equivalent amount of students had insufficient
sleep on weekdays. Although taking naps during daytime
may be beneficial to make up for some insufficient sleep at
night and to reduce sleepiness in class, it was limited
because naptime over an hour would be related to more
awakenings at night. Since near one fifth of the young
college students had short sleep duration on weekends,
L.-L. Tsai, S.-P. Li / Journal of Psychosomatic Research 56 (2004) 231–237236

sleep debt could be chronically accumulated in those
students. In addition to insufficient sleep, other sleep
difficulties are also common among the college students.
These findings warrant sleep education programs and
interventions for the students as previously suggested
[24,30]. It is conceivable that sleep education in college
students may help them be aware of their own sleep
problems and thereby willing to choose activity schedules
and sleep habits good for sleep.
Acknowledgments
The authors would like to thank teaching assistants Yi-
Ling Wang, Chung-Kang Shen, Chung-Shan Kao, Yu-Zhe
Tsai, and Yu-Tien Chang for helping in the administration
and collection of sleep logs. This study was supported by
National Science Council, R.O.C. College Student Grant
NSC88-2815-C194-024H.
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