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Music improves sleep quality in students
La
´szlo
´Harmat, Johanna Taka
´cs & Ro
´bert Bo
´dizs
Accepted for publication 20 December 2007
Correspondence to L. Harmat:
e-mail: laszloharmat@yahoo.com
La
´szlo
´Harmat MSc
Postgraduate Student
Semmelweis University, Institute of
Behavioural Sciences, Budapest, Hungary
Johanna Taka
´cs MSc
Postgraduate Student
Semmelweis University, Institute of
Behavioural Sciences, Budapest, Hungary
Ro
´bert Bo
´dizs PhD
Senior Research Fellow
Semmelweis University, Institute of
Behavioural Sciences, Budapest, Hungary
HARMAT L., TAKACS J. & BODIZS R. (2008)HARMAT L., TAKA
´CS J. & BO
´DIZS R. (2008)
Music improves sleep quality in
students. Journal of Advanced Nursing 62(3), 327–335
doi: 10.1111/j.1365-2648.2008.04602.x
Abstract
Title. Music improves sleep quality in students.
Aim. This paper is a report of a study to investigate the effects of music on sleep
quality in young participants with poor sleep.
Background. Sleep disorders may result in fatigue, tiredness, depression and
problems in daytime functioning. Music can reduce sympathetic nervous system
activity, decrease anxiety, blood pressure, heart and respiratory rate and may have
positive effects on sleep via muscle relaxation and distraction from thoughts.
Control groups have not been used in most previous studies.
Methods. We used a three-group repeated measures design. Ninety-four students
(aged between 19 and 28 years) with sleep complaints were studied in 2006. Par-
ticipants listened for 45 minutes either to relaxing classical music (Group 1) or an
audiobook (Group 2) at bedtime for 3 weeks. The control group (Group 3) received
no intervention. Sleep quality was measured using the Pittsburg Sleep Quality Index
before the study and weekly during the intervention. Depressive symptoms in
experimental group participants were measured using the Beck Depression
Inventory.
Results. Repeated measures
ANOVAANOVA
revealed a main effect of TIME (P<0Æ0001)
and an interaction between TIME and GROUPS (P<0Æ0001). Post hoc tests with
Bonferroni correction showed that music statistically significantly improved sleep
quality (P<0Æ0001). Sleep quality did not improve statistically significantly in the
audiobook and the control group. Depressive symptoms decreased statistically
significantly in the music group (P<0Æ0001), but not in the group listening to
audiobooks.
Conclusion. Relaxing classical music is an effective intervention in reducing
sleeping problems. Nurses could use this safe, cheap and easy to learn method to
treat insomnia.
Keywords: alternative therapy, depression, insomnia, psychology, sleep, stress
Introduction
Sleep quality is a very important factor in quality of life. Sleep
disorders may result in fatigue, tiredness, depression and
problems in daytime functioning. Several studies have
focused on the effects of music on sleep quality, and
researchers have found, in a variety of study settings and
populations, that music positively affects sleep.
The purpose of this research was to confirm the positive
effects of music on sleep quality that the earlier studies have
shown and investigate the specific effects of music on sleep
quality by controlling for the confounding effect of relaxation
ORIGINAL RESEARCH
JAN
2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd 327
and positive expectations. Most earlier researchers did not
take into consideration these factors that may influence
participants’ sleep quality and there remains the question
whether music per se influences sleep or whether sleep quality
is also affected by participants’ expectations of the treatment.
Background
A number of studies conducted in clinical settings have
suggested that sedative music may have positive effects on
sleep via muscle relaxation and distraction from thoughts
(Mornhigweg & Voigner 1995, Zimmermann et al. 1996,
Johnson 2003, Lai & Good 2004). Music can reduce
sympathetic nervous system activity, decrease anxiety, blood
pressure and heart and respiratory rates (Standley 1986,
Good et al. 1999, Salamon et al. 2003).
Eight studies have had a direct focus on the effects of music
on sleep. Zimmermann et al. (1996) studied the effects of
relaxing music on sleep and pain in 96 patients who had
undergone coronary artery bypass graft surgery. Levin (1998)
examined the effects of ‘Brain Music’ in the treatment of 58
patients suffering from insomnia. ‘Brain Music’ is basically
the transformation of spontaneous bioelectrical activity into
music. Gitangali (1998) examined a traditional Indian ragha,
which is similar to lullabies. Two studies have been
conducted with children (Field 1999, Tan 2004). In Field’s
study, children in the experimental group listened to music at
naptime, while in Tan’s study they also did so at bedtime.
Three researchers have investigated the effects of music on
sleep in older adults (Mornhigweg & Voigner 1995, Johnson
2003, Lai & Good 2004). All studies showed that music had
a statistically significant sleep-promoting effect, except for
that by Gitangali (1998) in which no evidence was found for
the positive effect of music on sleep.
These results indicated that music is a potential non-
pharmacological intervention for the treatment of sleep
disturbances such as insomnia. However, they were based
on self-report measures and have further limitations. For
example, in most studies a control group was not used, whilst
in theirs (Fried 1990a,b, Lai & Good 2004) music was
combined with relaxation therapy or some other interven-
tion, making it difficult to draw conclusions about the effects
of music per se.
The study
Aim
The aim of the study was to investigate the effects of music on
sleep quality in young participants with poor sleep.
Design
A randomized controlled trial was used with a three group,
repeated measures design was carried out in 2006.
Participants
Ninety-four students, 73 women and 21 men (mean
age = 22Æ6 years,
SDSD
=2Æ83, range: 19–28), with sleep com-
plaints were recruited at a university in Hungary. Participants
were randomized using a computerized randomization table
and variable block randomization. Each block was randomly
assigned to the groups and the three groups in each block
received only one ‘treatment’: listening to music (Group 1;
n= 35), listening to an audiobook (Group 2; n= 30) or no
intervention (Group 3; n= 29).
The inclusion criteria were:
•age above 19 years,
•able to understand the Hungarian language,
•poor sleep: Pittsburg Sleep Quality Index (PSQI) global
score >5 (Buysee et al. 1989),
•no daytime somnolence: Epworth Sleepiness Scale (ESS)
<16 (Johns 1991) and
•no severe depressive symptoms: Beck Depression Inven-
tory (BDI) score <19 (Eaves & Rush 1984).
The exclusion criteria were:
•current use of hypnotics, sedatives or antidepressants; and
•medical diagnosis for primary sleep disorder.
Experimental interventions
Members of the music group were given a CD containing
classical music and were asked to accept or refuse the music
collection. No participant refused it. The music was a
collection of relaxing classical music including some popular
pieces from Baroque to Romantic (The Most Relaxing
Classical, 2 CD, Edited by Virgin 1999). We did not offer a
choice of the type of music to be listened to, but all the
participants confirmed that they liked classical music. The
music was the same for all participants. The music collection
was introduced to the participants by the investigators before
the study and they were to listen to it for 45 minutes every
night at bedtime for 3 consecutive weeks. All participants in
the music group listened to 3-minute excerpts.
The members of the audiobook group were given a CD
containing 11 hours of short stories by Hungarian writers
such as Frigyes Karinthy, Gyula Kru
´dy, Ge
´za Ga
´rdonyi,
Zsigmond Mo
´ricz and Miha
´ly Babits. Similarly to those in
the music group, they were asked to listen to the audiobook
at bedtime for 45 minutes each night for 3 consecutive
L. Harmat et al.
328 2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd
weeks. They had the option to listen to new stories each
night but could also listen repeatedly to the stories they
preferred. All these participants listened to the same audio-
book collection.
The music and audiobook participants were asked to listen
to their CD before going to bed and to avoid physical
activities during and after the music or audiobook session.
They had no previous training in any relaxation technique.
Members of the control group did not receive any
intervention, but participated in the pre- and postintervention
assessment and were encouraged not to use music or an
audiobook at bedtime.
Measures
The PSQI (Buysee et al. 1989) is a commonly used question-
naire that measures self-reported sleep habits and can be
completed in a short time. It gives information about the
participant’s perceived sleep quality, sleep latency, sleep
duration, sleep efficiency, sleep disturbance, daytime dys-
functions and use of sleep medication. These seven compo-
nents form a global score that ranges between 0 and 21; the
score for each component ranges from 0 to 3. Buysee et al.
(1989) reported that score of 5 (indicating poor sleep) yielded
a diagnostic sensitivity of 89Æ6% and a specificity of 86Æ5%
and that the scale had good internal consistency, with
a=0Æ83. A global PSQI score >5 is indicative of severe
sleep difficulties in at least two areas…
In order to develop the PSQI-H, the original PSQI was
translated from English into Hungarian and then back-
translated into English by an independent translator. We
compared the original and the backtranslated PSQI ver-
sions and created a preliminary Hungarian version. The
Cronbach acoefficient in our study was a=0Æ79, indicat-
ing good internal consistency. Validation of the Hungarian
version of the questionnaire is in process. In the present
study, both the global PSQI and the component subscale
scores were analysed so that the effects of music on
individual elements of sleep could be determined. In the
intervention groups, the PSQI was administrated four
times: once before the intervention and subsequently at
the end of each week during the study period. In the
control group, the PSQI was used only twice, before and
after the study, to minimize interference with usual practice
and to avoid introducing any positive or negative expec-
tations about sleep in this group.
Mood and depression scores were measured by means of
the BDI (Beck et al. 1961). We used a shortened version that
is a modified version of the original shortened BDI (Beck &
Beck 1972). The shortened version of BDI consists of 9 items
and has been shown to have an internal consistency of
a=0Æ85 in a nationwide representative Hungarian sample
(Ro
´zsa et al. 2003). On the basis of comparison of BDI and
the shortened version, a reliable transformation of the scores
of the shortened questionnaire into the original score is
possible. (Kopp 1985, Kopp & Skrabski 1990). The items of
the shortened questionnaire assess the existence and intensity
of the following depressive symptoms: social withdrawal,
inability to make decisions, sleep problems, fatigue, exagger-
ated anxiety over somatic complaints, inability to work,
pessimism, lack of satisfaction, difficulties with feeling
pleasure and self-blame (Kopp et al. 1995). The BDI and its
shortened version are reliable methods to measure the
severity of depression. They correlate strongly with other
estimates of depressive symptoms by psychiatrists. According
to Eaves and Rush (1984), the severity of depression can be
evaluated as follows:
0–9 points Normal
10–18 points Mild depressive symptoms
19–25 points Moderately severe depressive symptoms
26 points or higher Severe depressive symptoms
The ESS was used to assess depression and daytime
somnolence. ESS is a simple, self-administrated question-
naire that measures general level of daytime sleepiness.
Based on their recent way of life, participants rated on a
scale from 0 to 3 the likelihood of dozing off or falling
asleep in eight different situations commonly encountered
in daily life. ESS values above 16 points are indicative of a
high level of daytime sleepiness (Johns 1991). We used the
ESS as a filter to exclude other sleep disturbances, such as
obstructive sleep apnoea, periodic limb movement disorder,
narcolepsy or idiopathic hypersomnia, which are associated
with excessive daytime sleepiness.
Data collection
The study protocol is show in Figure 1. At the beginning of
the study baseline data were collected using the PSQI, BDI
and ESS and participants were randomly assigned to one of
the three groups. During the following 3 weeks, the PSQI
was completed weekly by participants in the music and
audiobook groups. In the control group, we administered
PSQI only on the third week. Participants in the music and
audiobook groups also completed the BDI at the end of
the intervention; in addition, we contacted the participants
by telephone weekly during the study period to assess
compliance with the protocol and all said that they
complied.
JAN: ORIGINAL RESEARCH Music improves sleep quality
2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd 329
Ethical considerations
The study was approved by the human research ethics
committee of the study university. Participants received
both oral and written information about the study signed
an informed consent form.
Data analysis
We used parametric tests, i.e. paired samples t-tests, t-tests
for independent samples and
ANOVAANOVA
with three groups.
Independent sample t-tests were used to compare the PSQI
and BDI scores of the two experimental groups at pretest
and at weeks 1, 2 and 3. The Normality assumption was
checked. A repeated measures
ANOVAANOVA
with main factors of
GROUP (3 levels) and TIME (2 levels: pre and post) was
used to analyse sleep quality between and within the three
groups before and after the study. The assumptions of the
parametric
ANOVAANOVA
model were also checked. Paired sample
t-tests were used for within-group comparisons and Pear-
son’s correlation was used to assess any linear relationship
between PSQI and BDI scores in the experimental groups.
The Bonferroni correction was used to control for Type I
error with multiple testing, and the more conservative
statistical significance threshold of 0Æ001 was set. Statistical
analyses were performed using
SPSSSPSS
12 and
STATISTICASTATISTICA
7.0.
Results
Pretest scores
At pretest (first meeting) the global PSQI and BDI were
completed by all participants. The global PSQI scores ranged
from 6 to 13 in the music group and from 6 to 11 in the
audiobook group (Table 1). These scores indicate some sleep
difficulties. BDI scores ranged from 0 to 13 in the music
group and from 0 to 14 in the audiobook group. The
independent t-tests showed no statistically significant pretest
differences between the two experimental groups in age, BDI
and global PSQI scores (P>0Æ05).
There were no statistically significant differences between
the three groups in global PSQI scores.
PSQI and BDI outcomes in post-tests
Global sleep quality and BDI scores
A repeated measures
ANOVAANOVA
with GROUP (3 levels) and
TIME (2 levels) as main factors was used to analyse sleep
quality within and between groups before and after the study.
We did not find a statistically significant GROUP main effect.
There was a significant main effect of TIME (F=87Æ157;
P<0Æ0001) and a significant interaction between TIME and
GROUPS (F=14Æ748; P<0Æ0001). Post hoc comparison
95 participants
Pretests
Pittsburg Sleep Quality Index (PSQI) Random assign
to 3 Groups
Beck Depression Inventory (BDI)
Epworth Sleepness Scale (ESS)
Posttests for 3 Groups
Week 1
Phone lx
Tests Tests Tests
Phone lx Phone lx
Week 2 Week 3
Group 1, Listening to Music at
Group 2, Listening to Audiobook
Group 3
No intervention
PSQI PSQI PSQI
PS
Q
I
BDI
bedtime 45-minutes
at bedtime 45-minutes
(aged 19–28)
Figure 1 Study design.
Table 1 Pittsburg Sleep Quality Index and
Beck Depression Inventory mean scores by
group
Pretest
Music group
(n= 35)
Audiobook
group (n= 30)
t95% CI
Mean
SDSD
Mean
SDSD
Pittsburg Sleep
Quality Index
6Æ83 2Æ093 6Æ27 1Æ721 1Æ170 0Æ398 to +1Æ522
Beck Depression
Inventory
5Æ40 3Æ767 5Æ70 3Æ564 0Æ328 2Æ127 to +1Æ527
L. Harmat et al.
330 2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd
(Bonferroni correction) of pretest scores with the three-weeks’
post-test scores showed that music significantly improved
sleep quality (P<0Æ0001). We did not find any improvement
in sleep quality in the audio or control groups (Figure 2).
We used t-tests for independent samples to compare
weekly changes in global PSQI scores in the two intervention
groups, i.e. music (Group 1) and audiobook (Group 2). We
could not include the control group (Group 3) in these
analyses as we had data on only two TIME points for this
group. The magnitude of the difference between groups
(music vs. audiobook) was statistically significant after the
second week (week 2, P=0Æ0002 and week 3, P=0Æ0004).
Improvement continued during the following week of the
study (Table 2). Thus, listening to music has a cumulative
effect on sleep quality (Figure 3).
According to our results, music altered mood (Figure 4).
Depressive symptoms decreased in the music group
(t=6Æ124; P<0Æ0001) but did not change statistically
significantly after listening to audiobooks.
The improvement of sleep quality (PSQI pretest minus
PSQI3) correlated statistically significantly with decrease in
depressive symptoms (BDI pretest minus BDI post-test) in the
audiobook group (r=0Æ400; P=0Æ029), but this Pvalue was
not statistically significant when the Bonferroni correction
factor was taken into account.
PSQI component scores
The music group had statistically significantly better scores
on the six PSQI components during the 3 weeks. A paired
samples t-test was used to compare pretest scores and weeks
1, 2 and 3 scores within the music group. Listening to music
resulted in improved subjective sleep quality, shorter sleep
latency, longer sleep duration, better sleep efficiency, reduced
sleep disturbances and less daytime dysfunction week by
week; however, sleep duration showed a delayed effect since
a statistically significantly longer sleep duration occurred
during the second (t=4Æ098; P<0Æ0001) and third weeks
(t=4Æ828; P<0Æ0001) in the PSQI tests (Figure 5).
None of the PSQI components improved statistically
significantly in the audiobook group. We measured PSQI
components at the pretest and post-test assessment in the
control group as well, but found no statistically significant
changes in any of the component scores.
Responders vs. non-responders
Similarly to Lai’s study (Lai & Good 2004), we divided the
participants into ‘responders’ and ‘non-responders’ after the
intervention in the music and audiobook groups. Participants
were considered responders if their total PSQI post-treatment
scores dropped into the normal range (PSQI <5). By the end
of the study, 30 out of the 35 people (86%) in the music
group responded to the intervention and became ‘good
sleepers’, while five remained ‘poor sleepers’. In the audio-
book group there were nine ‘responders’ (30%), while 21
from this group (70%) remained in the ‘poor sleepers’ range
at the end of the study.
There were differences in pretest scores between ‘respond-
ers’ and ‘non-responders’ from the music group. The pretest
9
8
Music
Audiobook
Control
7
6
5
PSQI_pre
S
cores
PSQI_week3
Tim
e
4
3
2
1
Figure 2 Pretest and post-test global Pittsburg Sleep Quality Index
(PSQI) scores in the three groups: music, audiobook and control.
Vertical bars represent 95% confidence intervals.
Table 2 Weekly Pittsburg Sleep Quality Index scores by groups
Time points
Music group (n= 35)
Audiobook group
(n= 30)
t95% CI
Mean
SDSD
Mean
SDSD
Pretest 6Æ83 2Æ093 6Æ27 1Æ721 1Æ170 0Æ398 to +1Æ522
Week 1 5Æ43 2Æ417 5Æ97 2Æ059 0Æ957 1Æ166 to +0Æ585
Week 2 3Æ97 2Æ135 5Æ83 2Æ520 3Æ325 3Æ015 to 0Æ708
Week 3 3Æ27 1Æ800 5Æ17 2Æ214 3Æ892 2Æ933 to 0Æ943
JAN: ORIGINAL RESEARCH Music improves sleep quality
2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd 331
scores of the ‘responders’ were also statistically significantly
lower on three of the six components of sleep quality:
perceived sleep quality, sleep latency and sleep efficiency
(P<0Æ05). Lai and Good (2004) had the same results for
pretest scores between ‘responders’ and ‘non-responders’. In
our study, there were nine ‘responders’ in the audiobook
group at the end of the intervention, while 21 participants
remained in the ‘poor sleepers’ range. Among ‘responders’,
we did not find statistically significantly lower pretest scores
for any components of sleep quality.
Discussion
This is the first study to show that music per se improves sleep
quality by controlling for the confounding effects of relax-
ation and positive expectations. Students who listened to
sedative classical music for 45 minutes at bedtime for
3 weeks had better global sleep quality in the second and
third week than those who did not. A possible explanation
for the lack of a significant group main effect could be that
the magnitude of difference between groups (music vs.
audiobook) was statistically significant after the second week
only. The improvement continued during the third week and
more greater at the end of the study. The intervention was
based on the effects of listening to music, but we do not yet
have sufficient knowledge about the effects of music on sleep
quality. Several studies conducted in clinical settings have
suggested that sedative music may have positive effects on
sleep via muscle relaxation and distraction from thoughts.
Music can decrease sympathetic nervous system activity, as
well as anxiety, heart rate, respiratory rate and blood
pressure (Standley 1986, Good et al. 1999, Salamon et al.
2003).
Several factors may help to explain our findings. One
group of explanatory factors is related to the psychophysi-
ological effect of musical tempo and the type of music that
participants prefer. Reinhardt (1999) investigated the influ-
ence of musical rhythm on the synchronisation and coordi-
nation of heart rate. Twenty-eight patients with chronic
cancer pain in a stable phase of the disease underwent a 14-
day relaxation training designed to improve the process of
falling asleep. The therapy included 30-minute lullaby-like,
rhythmically dominated music with gradually decreasing
tempo. Reinhardt found that during the relaxation therapy
trained patients showed increasing synchronisation and
coordination of heart rate and musical beat. At a musical
tempo between 48 and 42 beats/minute, a very stable 2:3
synchronisation was observed. Trained patients who reported
the best relaxing and analgesic effects showed the highest
degree of synchronisation. Bernardi et al. (2006) also
confirmed that slow or meditative music can have a relaxing
effect as well as an arousal effect, predominantly depending
on the tempo. Sedative music with a slow tempo (42–
65 beats/minute) induces relaxation and reduces activity in
0
1
2
3
4
5
6
7
8
Pretest_PSQI PSQI1 PSQI2 PSQI3
Audiobook Music
*
*
Figure 3 Weekly global Pittsburg Sleep Quality Index (PSQI) scores
for music and audiobook groups. *Statistically significant differences
between groups (P<0Æ05).
BDI
_prestest BDI_prestest
BDI_posttest
BDI_posttest
0·00
1·00
2·00
3·00
4·00
5·00
6·00
BDI_prestest
5·70 5·40
BDI_posttest
5·13 2·66*
Audiobook
Music
Figure 4 Beck Depression Inventory (BDI) scores in pretest and post-
tests. *Significant differences between BDI pretest and post-test
within groups (P<0Æ05).
Music group
0·00
0·40
0·80
1·20
1·60
Sleep
quality
Sleep
latency
Sleep
duration
Sleep
efficiency
Sleep
disturbance
Daytime
disfunction
Pretest
Week1
Week2
Week3
Figure 5 Weekly Pittsburg Sleep Quality Index outcomes in the music
group.
L. Harmat et al.
332 2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd
the neuroendocrine system, and slow music produces a lower
heart rate and blood pressure (Standley 1986). Salamon et al.
(2003) confirmed that preferred classical music statistically
significantly decreases systolic and diastolic blood pressure as
well as anxiety levels.
In addition, studies have also shown that relaxation may be
induced with approximately 30 minutes of sedative music
(Mockel et al. 1994). Based on knowledge from previous
studies (Tan 2004, Lai & Good 2004), and to ensure that all
participants had sufficient time to fall asleep, we decided to
use a CD-recording approximately 45 minutes long. The
selection of music type was based on previous studies with
sedative music (Field 1999, Johnson 2003, Lai & Good
2004). According to Gaston (1951), the tempo should be
somewhere around 60–80 beats/minute.
It is very important to differentiate between the efficacy of
music in advancing sleep onset and its efficacy in improving
sleep quality. In some studies (Fried 1990a,b, Lai & Good
2004) music was combined with relaxation therapy or with
some other intervention, making it difficult to draw conclu-
sions about the effects of music per se. In addition, a control
group without any intervention has rarely been used,
preventing investigation of the effects of the positive expec-
tations of the experimental group. In contrast, we used a
control group (no intervention) and an audiobook group to
compare non-intervention and the effect of another interven-
tion (listening to audiobooks) to listening to music.
The auditory processes implied by listening to audiobooks
are similar to those implied by listening to music. Elements of
speech and musical sound can be characterized by the same
parameters: pitch, duration, loudness, rhythmic metrical
structure, contour, articulation and timbre. A large number
of researchers have tried to reveal the similarities and
differences between the two domains in the brain. A recent
study has provided neurophysiological data to prove the
similarity between listening to music and verbal material. In
this research, Broca’s area, known for its specialization to
syntactical processing in language, was also activated by
music perception (Koelsch et al. 2002). This suggests that the
mechanisms underlying syntactical processing are shared
between music and language (Patel 2003). In addition, there
is a similar brain response between speech and music
boundary processing, and Kno
¨sche also discovered EEG
and EMG correlates for phrase boundaries in music. Neither
music nor spoken language form uniform auditory streams;
rather, they are structured into phrases (Kno
¨sche et al. 2005).
Despite the similar cognitive and neurobiological specific-
ity of music and language, audiobooks had no effect on sleep
quality in our study. The specificity of music may concern
different processing components. Some processing compo-
nents appear to be genuinely specialized for music (Peretz &
Hyde 2003), while other components can be involved in the
processing of both music and speech (Patel et al. 1998).
Audiobooks also had no statistically significant effect on
depressive symptoms in our study, as measured by the BDI.
However, music decreased depressive symptoms scores in the
experimental group. Several researchers have examined the
therapeutic effect of music on depression (Hanser & Thomp-
son 1994, Lai 1999, Hsu & Lai 2004) and found that music
had beneficial effects on depressive symptoms. Music has
been found to increase circulating endorphin levels (Mockel
et al. 1994), which are associated with positive moods (Gerra
et al. 1998). By the end of our study, mood scores had
improved in the music group; however, our results suggest
that music-induced improvement in sleep quality is not due to
the effect of music on depressive symptoms. Nevertheless,
this might be true in the case of audiobooks.
The effect of music on sleep duration appeared later, since
significantly longer sleep duration occurred in the second and
third weeks in the PSQI tests. Sleep duration also showed a
delayed improvement in a previous study (Lai & Good
2004). Listening to music in the present study resulted in
reduction of global PSQI mean values to the normal range.
Following the 3-week intervention, 30 out of the 35
members of the music group became ‘good sleepers’, while
What is already known about this topic
•Sleep disorders may result in fatigue, tiredness,
depression and problems in daytime functioning.
•Music can reduce sympathetic nervous system activity,
decrease anxiety, blood pressure, heart and respiratory
rate and may have positive effects on sleep via muscle
relaxation and distraction from thoughts.
•Control groups have not been used in previous
research.
What this study adds
•Music had a positive effect on sleep quality and
depressive symptoms, but listening to audiobook had
no statistically significant effect on sleep quality and
depressive symptoms.
•More research is needed to confirm the effectiveness of
music on sleep quality in patients suffering from
insomnia, and objective, physiological measures such
as polysomnography should be used.
•Nurses could use this safe, cheap and easy to learn
method to treat insomnia.
JAN: ORIGINAL RESEARCH Music improves sleep quality
2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd 333
the global PSQI mean scores of the audiobook group
remained in the ‘poor sleepers’ range.
Study limitations
The first limitation of our study is that participants were
recruited as ‘poor sleepers’ (PSQI global score >5). They
were healthy people with some sleeping problems which can
return into the normal range without any intervention.
Secondly, we used self-report measures of sleep without
verifying them objectively. Thirdly, a 3-week study period
may not be sufficiently long to draw any conclusions about
the sustainability of improved sleep on longer time periods.
Fourthly, the stories to which participants in the audiobook
group listened to may have induced different emotions, while
the emotional effect of slow classical music was considerably
more balanced. Fifthly, we contacted by telephone every
participant once a week to assess their compliance with the
protocol, but we have no further information about how
frequently they listened to music or to the audiobook during
the study period. Finally, a Hawthorne effect may have
occurred in the study. The Hawthorne effect refers to a
phenomenon which is thought to occur when people
observed during a research study temporarily change their
behaviour and performance.
Future research
We recommend that researchers investigate the effects of music
and audiobooks on sleep quality for more than three weeks.
Music has a cumulative effect of sleep quality and our findings
suggest that all poor sleepers might become good sleepers with
a longer music intervention. It is also necessary to investigate
the effects of music using objective, physiological measures of
sleep such as polysomnography. Findings from the study by
Lasic and Ogilvie (2007), in which the effects of music on sleep
quality were investigated using a polisomnographic and
quantitative EEG analysis, are not in line with our results.
However, his study was conducted over a four-night period
and such a short time is probably not sufficient to observe a
positive effect of music on sleep quality. More research is
needed to confirm the effectiveness of music on sleep quality in
clinical populations such as in patients suffering from insom-
nia. However, it is difficult to find and enrol in a study patients
suffering from insomnia who are medication-free.
Conclusion
Our findings provide evidence for the usefulness of relaxing
classical music as an intervention for sleeping problems in
young adults. In line with former studies, we confirmed that
listening to relaxing classical music has a positive effect on
sleep quality. Hospitalized patients often suffer from sleeping
problems, such as insomnia, and listening to music is a simple
intervention that may reduce these problems. Nurses should
use music therapy in their practice because it is a safe and
cheap method which may be used to treat insomnia in
different populations. In addition, the intervention is quick
and easy to learn.
Acknowledgements
This work was supported by a PhD Grant from the
Hungarian Ministry of Education, the National Office for
Research and Technology (NKFP-1/B/020/04) and National
Research Found (OTKA TS-049785). The authors were also
supported by the Ferenc Faludi Academy (LH) and the Ja
´nos
Bolyai Research Fellowship of the Hungarian Academy of
Sciences (RB).
Author contributions
LH, JT and RB were responsible for the study conception and
design. LH and JT performed the data collection. LH and JT
performed the data analysis. LH was responsible drafting of
the manuscript. RB made critical revisions to the paper for
important intellectual content. JT provided statistical exper-
tise. LH and JT obtained funding. RB provided administra-
tive, technical or material support. RB supervised the study.
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