Introduction
Pre-operative anxiety is among the most unpleasant experiences associated with
surgery. An unfamiliar environment, loss of control, perceived or actual physical risk,
dependence on strangers, separation from family and friends (Gillen et al., 2008), the
threat of death, and possible postoperative complications are factors that may cause
patients to feel anxious in the waiting area before surgery (Mitchell, 2003). The
waiting period is also the time during which patients are most likely to imagine any
potential danger they may face (Cooke et al., 2005; Haun et al. 2001). Preoperative
anxiety is characterized by subjective, consciously perceived feelings, of
apprehension and tension accompanied by autonomic nervous system arousal, which
cause physical and psychological changes, including changes in heart rate, blood
pressure, and respiratory rate, as well as feelings of pressure, fear, and uncertainty
(Gail, 2005).Anxiety can affectan individual’scognitiveabilitiesand cause
discomfort both mentally and physically (Vaughn et al., 2007). This, in turn, may
increase postoperative pain, prolong postoperative recovery, and increase the potential
for complications (Ozalp et al., 2003; Katz et al., 2005).
Given the potential effects of anxiety, there are strategies to limit patient anxiety
and improve comfort levels when waiting for surgical and invasive procedures. It has
patients, most still feel anxious (Duggan et al., 2002). Other research has revealed that
patients do not want excessive medication to lower their anxiety, but would rather
listen to music or read (Hyde et al., 1998). Among various non-pharmaceutical
anxiety-relieving alternatives, music intervention had been reported to have a
consistently positive and statistically significant effects on reducing pre-operative
anxiety and post-operative pain (Nilsson, 2008). The common theory regarding the
anxiety and stress-reducing effect of music is that music acts as a distracter, focusing thepatient’sattention away from negative stimuli to something pleasant and
encouraging (Mitchell, 2003; Nilsson, 2008). Music involves the patient’smind with
something familiar and soothing, which allows patient to escape into his or her own
world. Patients can focus their awareness on the music to aid relaxation. (Thorgaard et
al., 2005; White, 2000; White, 2001). Most prior studies used a compact-disk or
cassette player with headphones to listen to music (Gillen et al., 2008). However,
re-using headphones among patients raises a concern about nosocomial infection
control. Since the organisms causing most nosocomial infections can come from
contact with staff (cross-contamination), contaminated instruments and needles, and
the environment (exogenous flora),WHO (2002) suggested highly-susceptible patients
or protected areas such as operating suites need separate cleaning equipment. Though
infections (Short et al., 2010), it increased extra cost. Therefore, non-contact
alternative music delivering devices other than headphones need to be considered out
of concern for infection control. The purpose of the present research is to evaluate the
effectiveness of broadcast music versus headphone music playing to relieve
preoperative anxiety levels of patients in the waiting area of an operating theater.
Materials and Methods
Research design and settingThe present studyisa randomized controlled clinical study that took place in the
operating theater of a metropolitan teaching hospital in Taiwan.The aim of this study
is to evaluate the effectiveness of broadcasting compared with headphone in
delivering music intervention to reduce pre-operative anxiety of the patient in holding
area of an operation theatre. To contrast the effect of music intervention in our study,
control group was considered in addition to broadcasting and headphone groups. The
study hospital is JCIA (Joint Commission International Accreditation) certified. It is
required to assess patients’anxiety and pain on admission and each significantevents
such as surgery and procedure.The waiting area is independent, but not completely
isolated, from the nursing station. It is 12.6 x 3.9 m, and it can take seat eight patients
simultaneously. The temperature of the room was maintained between 19 to 21°C.
Patients who were sent to the waiting area between 07:00 and 14:00 were
recruited for enrollment. The inclusion criteria were that the patient: (1) was
conscious and aged 20~65 years, (2) had not consumed any medications for
hypertension or heart disease, or caffeine, sedatives, or operative premedication, (3)
had not been diagnosed with hearing impairment, visual impairment, arrhythmias, or
heart disease, (4) stayed at least 25 min in the waiting area, and (5) was willing to
participate in the study and signed an informed consent form.
We applied random table to divide numbers 1 to 30 to three groups to determine
each day of a month to be ‘headphoneday,’‘broadcastday’or‘controlday’.
Subjects who were sent to theoperating theaterforsurgery on ‘headphoneday’were
assigned to the headphone group. The same rulewasapplied to recruit subjects into
the broadcast and control groups.
Sample size was determined with G power software (Grant Devilly, Victoria,
Australia). We set alpha as 0.05, the effect size (f) of one-way ANOVA of VAS scores
and heart rate variability among the three groups as 0.3 (small), and the power as 0.8
for our three groups. The resulting sample size was 111 participants (37 for each
group). Considering an attrition rate of 30% due to the short stay in the waiting area,
we decided on an expected sample size of 50 for each group.
It is recommended that therapeutic music should have a slow tempo, low pitch,
regular rhythm, and pleasing harmonics, and should consist of string, flute, and piano
selections (Nilsson, 2008; Pelletier, 2004). The genre and the duration of the soothing
music did not seem to influence the effectiveness of music intervention. These results
are confirmed both by a review that explored the use of music and its effect on
anxiety during short waiting periods and a Cochrane review that explored the effects
of music on pain (Cooke et al., 2005).
Considering the short stay of patient in the waiting area and time spent for HRV
and VAS measuring, a 10-min music was prepared for intervention. The kinds of
music chosen to play in this study were light music of folk songs or pop music, played
at a tempo of 60~80 beats per minute and a volume of 50~55 db. The patients in the
headphone group listened to music via an MP3 player (Ergotech, ET-U31P, Taiwan).
The headphone was put on when the subject agreed to participate. For the subjects in
the broadcast group, they listened to music through an open speaker (Pioneer CD
player, PD-M427, Japan). The music was played from 07:00 to 15:00 on the broadcast
day. When subjects entered the waiting area, they were asked about participating by
permitting VAS and HR measurements. The control group did not listen to music,
and were asked if they would participate by having VAS and HR measurements.
which make every person in the same area can hear, we decide to use pre-selected
standard 10 pieces of music repeatedly, randomly played and not allow participants to
make choice. To prepare music for intervention, we firstly chose 40 pieces of music
which meet the recommended criteria. Then, we had 10 preoperative patients to elect
the top ten relax ones. All the 10 pieces of music were stored in a MP3 player or CD
disk and played randomly.
Measurements
We employed both subjective and objective measures for anxiety in our study.
The visual analog scale
We used a visual analog scale (VAS) instead of State-Trait Anxiety Inventory
(STAI), which is used in most studies of anxiety. This decision was made out of three
concerns. First, the 40-item STAI takes minutes to fill out. This could cause
unnecessary strain for patients waiting for surgery in the waiting area of the operating
room and make them more nervous. In contrast, the VAS takes only 5 s for the patient
to communicate his/her anxiety level. Second, a patient can remain lying down and
still respond to the VAS, while the patient might need to change his/her position to fill
out the STAI questionnaire. Third, the VAS was routinely used in this hospital for pain
and anxiety assessment. Subjects were used to responding to it.
construct a scale. The researcher gave oral instruction (in mandarin) of “Pleasepoint atthenumberlineto show how anxiousyou feelatthemoment”, and offered three examples: “A mark at the extreme left would show that you are feeling not anxiousat
allat the moment. A mark at the extreme right would show that you are feeling the
most anxious you could ever imagine. A mark near the centre would show that you
feel moderately anxious”.
To use for measuring anxiety, participants were asked to say a number or indicate
with their finger a score from 0 (calm) to 10 (very anxious). It has been reported that
the VAS was significantly correlated with hospital anxiety (r= 0.28) (Ledowski et al.,
2005) and STAI (r=0.5-0.6) (Abdul-Latif et al,. 2001; Clan, 2004).Davey et al. (2007)
showed the VAS correlation with STAI was 0.78, and claimed that VAS measures
quickly and easily assess anxiety and may be useful for research purposes when
researchers have very limited time or questionnaire.
Heart rate variability
Heart rate variability (HRV) is a well-established non-invasive tool which can
be used to study the effect of mental stress on autonomic control of the heart rate
(Acharya et al., 2006; Malik et al., 1996). Several studies have shown that analysis of
heart rate variability is gaining acceptance as a tool to measure cardiac
Benjamin, 2006). In our previous study (Lee et al., 2010) evaluating the preoperative
anxiety relieving effect of a music intervention, HR variability parameters correlated
well with VAS scores, indicating that HR variability parameters can provide reliable
evidence for measuring preoperative anxiety.
There were time-domain and frequency-domain parameters in HR variability
analysis. In the time-domain analysis, the variables included the mean of the NNIs
(mean NNI), the standard deviation of the NNIs (SDNN), and the root mean square of
successive differences in the NNIs (rMSSD). The past literature pointed out that when
an individual feels anxiety or pressure, these indicators decrease (Malik et al., 1996).
In the frequency-domain, total power represents the overall activity of the
autonomic nervous system (ANS). Low frequencies (LFs; frequencies between 0.04
and 0.15 Hz) reflect mixed sympathetic and parasympathetic activities. High
frequencies (HFs; frequencies between 0.15 and 0.4 Hz) reflect parasympathetic
activity. High values of the low-to high (LF/HF) ratio indicate a dominance of
sympathetic activity while low values indicate a dominance of parasympathetic
activity. Activation of the sympathetic nerves, as in anxiety, can cause the HR to
increase, total power and high frequencies to decrease, and low frequencies and the
low-to-high ratio to increase (Kamath and Fallen, 1993).
device (DailyCare BioMedical, Chungli, Taiwan). It is a handheld limb lead EKG
(lead I) recorder with HR variability analytical software. To measure HR, the
researchersplaced thesensoron theradialareaofthepatient’sforearm for5 min.The participants were asked not to move around to ensure the quality of the readings.
According to theuser’smanual,theCheckMyHeartisCE (CONFORMITE
EUROPEENNE) certified and has passed electromagnetic interference and
compatibility tests. Its sampling frequency is 250 samples/sec. The measurement heart
rate range is 45-186 bpm and ST segment -3 to +3 mm, and it operates stably at
temperatures of 50℉-104℉ (10℃-40℃) and humidity of 25%-95%. It has been used
in clinical studies of HR variability (Peng et al., 2009; Wen et al., 2007). Our heart
rate data were analyzed by the CheckMyHeart software, and provided parameters of
heart rate variability.
Data Collection Process
This research was approved by the Institutional Review Board of the study
setting (approved code: CRC-03-09-07). The researcher (KJL) checked the operating
schedule and met potential participants in the waiting area of the operating theater.
After an eligible participant entered the waiting room, the researcher explained the
purpose and process of the study, helped the patient fill out a consent form, let the
group listened to a 10-min session of music with an MP3 player and headphones.
Participants in the broadcast group listened to music from a CD player broadcast in
the air. Subjects of the control group were toldtorest and relax. After a 10-min
session, participants received VAS and 5-min HR measurement
Statistical Analysis
Data were first examined for completeness. Incomplete data or data with too
many noise signals were deleted for data processing. Data analysis was performed
with SPSS 15.0 (SPSS, Chicago, IL). The major statistical procedures applied were
descriptive statistics, and Chi-squared test were applied to evaluate the background
differences among the three groups. One way ANOVA test was applied to examine
the different in VAS and HR variability parameters among the three groups. If a
significant difference was identified, a Sheffe test was further applied to examine the
paired difference. A value of p<.05 was deemed statistically significant.
Results
Between May to June 2009,186 patients were contacted and 180 were enrolled
in the study. Of them, six were unable to complete the study due to being sent to the
operating suite before the 10-min of music or rest was finished, three refused
measurement, four were excluded due to poor EKG recording (incomplete or too
processing. The 167 subjects were 66 in the broadcast group, 48 in the headphone
group and 53 in the control group. The participation process is presented in Figure 1.
There were no significant differences between three groups in terms of demographics.
The average waiting time for the 167 participants was 23 min. Seventy-six percent of
patients received general anesthesia, andeighteenpercent underwent spinal anesthesia.
The majority of subjects received obstetric and gynecological surgery, followed by
orthopedic surgery. There were no significant differences between the two groups in
age, gender, waiting time, methods of anesthesia, or types of surgery (Table 1).
VASAnxiety levels
According to the VAS scores, the mean anxiety level of all participants was
5.2±1.8. The mean anxiety score of the control group was 6.2 (SD=1.2), which was
significantly higher than that of the headphone group (5.1±2.7) and the broadcast
group (4.4±1.6) (p<.05). The anxiety score of the broadcast group was lower than that
of the headphone group, but no statistically significant difference was found between
the two groups (p=0.1) (Table 2).
Heart rate variability parameters
The average heart rates of the broadcast group, headphone group and control
group were not significantly different (72.2 bpm, 76.2 bpm, and 74.6 bpm,
broadcast group were all higher than those in the headphone and control groups
(Table 2), but the differences were not significant. There was significant difference in
high frequency HR variability among the three groups (F=4.8, p<.01). The Scheffe
test showed that the significant difference was between the broadcast group and the
control group ( p<.01), while there was no difference between the broadcast group
and the headphone group. There was also significant difference in low frequency HR
variability among the three groups (F=4.9, p<.01). The Scheffe test showed that the
significant difference was between the broadcast group and the control group ( p<.01),
while there was no difference between the broadcast group and the headphone group.
No significant differences in high frequency, low frequency and low-to-high
frequency ratio of HR variability were found between the headphone group and the
control group. Furthermore, the total power of the headphone group was higher than
that of the broadcast group or the controls, though it was not statistically significant.
Correlation of VAS scores and heart rate variability parameters
The correlation between VAS scores and heart rate variability parameters were
examined by Pearson correlation and the result was shown in Table 3. The VAS
scores were significantly correlated with frequency-domain parameters of HR
variablity (p<.05) but not time-domain ones. The VAS score was positively correlated
r=.21, p<.01 respectively) and was negatively correlated with high frequency of HR
variability( r=.22, p<.01).
Discussion
There was no pretest-posttest comparison in this study. This was limited by the
intervention for our broadcast group. When patients in the broadcast group entered the
room, music might already be playing and this would make a pretest-posttest
comparison meaningless. To provide reference in absence of pre-test, we include a
control group for post intervention comparison. In our previous study on (Lee et al,
2010), we had demonstrated the effect of 10 minutes music on anxiety-relieving for
patients awaiting surgery. Current study was to compare the anxiety-relieving effect
of broadcast to headphone music playing for patients awaiting surgery. The finding of
no difference between the broadcast group and the headphone group provide reference
in considering using music broadcast system for anxiety-relieving effect.
In this study, the VAS levels of the two music listening groups were reduced
after the music intervention, while the control group did not exhibit a significant
change (p < 0.01). This finding, as expected, was consistent with previous findings
(Cooke et al., 2005; Gillen et al., 2008; Hayes et al., 2003; Lee et al., 2004; Maranets
and Kain, 1999; Padmanabhan et al., 2005; Wang et al., 2002). Similar findings have
control trial of 170 patients waiting for vascular angiography procedures using a
boom-box style music player, and the result showed statistically significant
differences in anxiety reduction between the experimental group and the control
group. In addition, Kaemph and Amodei (1989) found a significant decrease in
anxiety among outpatients awaiting arthroscopic procedures for the group exposed to
music played on an audiocassette player a foot away. Our research also showed that
anxiety in the broadcast group was significantly lower than that of the control group.
This evidence indicates that when headphones are not available or not appropriate,
speakers can be an effective substitute.
The anxiety reliving effect was also indicated by a change in part of the heart
rate variability parameters. Our frequency-domain analysis showed that LF and HF
were statistically different among the broadcast group and the control group (p <
0.01). HF in the broadcast group was markedly higher than that in the control group,
indicating a greater modulation of HF by the parasympathetic nervous system in the
broadcast group than that in the control group upon listening to music. HF in the
headphone group was also higher than that in the control group. Moreover, our
findings that LF in the broadcast group was significantly lower than the control
group indicates there was less tension of the sympathetic nervous system in the
group. Sheps and Sheffield (2001) stated that anxiety increases the activity of
sympathetic nerves and decreases the activity of parasympathetic nerves, resulting in
increased LFs and lowered HFs. Thus our findings indicated a decreased activity of
sympathetic nerves and an increased activity of parasympathetic nerves after
listening to music. Our findings are similar to those by Chiu et al. (2003) where HF
was markedly elevated and LF and LF/HF ratio significantly decreased after music
therapy.
In contrast, the HR variability parameters in the control group showed less
changes (Table 2). Comparing the HF and LF, the regulation of the sympathetic
nervous system is superior in both the headphone and the broadcast groups to that of
the control group. However, the difference was only significant between broadcast
group and control group. One possible reason is that while listening to the music,
patients in the waiting room can also monitor the progress in the environment by
listening to the staff talking, which makes them feel more at ease. In patients
listening to music with headphones, they were deprived from any information from
the environment. Such effect of sensory deprivation resulting from wearing
headphones requires further evaluation.
The HR values did not show a significant difference among the three groups. This is
terms of the time domain of HR variability parameters, thedifferences among the
three groupswere not significant(Table 2) as well as the correlations with VAS scores
(Table 3).Chiu et al. (2003) used HRV analysis to evaluate the anxiety of 68
pre-operative procedure subjects, and also found time-domain parameters, consistent
with our findings. This phenomena indicates that 10 min of music listening did not
cause significant changes in the scale of the variations, but the frequency of variation
presented a significant change(Table 2 and Table 3).Our study found VAS scores is
associated with frequency domain of HR variability parameters. The previous study
showed high-frequency parameter of HR variability was significantly correlated with
anxiety by using STAI (State–Trait Anxiety Inventory) (Shinba et al., 2008). However,
Francis et al. (2009) showed anxiety score was associated with rMSSD in implantable
cardioverter defibrillator patients. Their explanation is that time domain assessments
collected over several hours are less vulnerable to ECG artifacts and ectopy than
frequency domain.In other words, the time-domain parameters were not as sensitive
as frequency-domain parameters for indicating changes in anxiety levels of patients
preoperatively. Researchers have pointed out that temporal-domain analysis is optimal
for analyzing long-term EKG recording (Chiu et al., 2003). Therefore, it is possible
that the indicators in this short-term study were not suitable for time-domain analysis.
anxiety reduction, the retention of this effect is unclear. It has been reported that post
operation music intervention not only reduced anxiety scores, but also pain scores and
the use of analgesics (Nilsson, 2008). Therefore, future studies need to determine if
lowering the levels of anxiety in the preoperative patient has any lasting effect on
outcomes during the intraoperative and postoperative stages. With the use of objective
measurements such as HR variability used in this study, investigating the anxiety
levels of patients intraoperatively and immediately postoperatively becomes possible.
Limitations
Although the present study has yielded findings that have both theoretical and
practical implications, there are some limitations. First, there was no pretest-posttest
comparison.Primarily without a pre-test it is impossible to determine the change.To
provide reference in absence of pre-test, we include a control group for post
intervention comparison. Second, in the present research, participants were not
allowed to choose their favorite music. The waiting room in our study did not have
individual partitions, so the participants in the broadcast group could not listen to
music of their own choosing. Therefore, the participants in the headphone group
listened to same music arrangement without personal choice. In future studies, a
better research design or a more suitable testing location may provide better insight
Conclusion
Listening to music is effective for reducing the anxiety of preoperative patients.
Such patient anxiety can be indicated by a decrease in VAS scores, and a decrease in
the low- and an increase in the high-frequency parameters of HR variability. Both
headphone and broadcast music are effective for reducing thepreoperativepatient’s
anxiety in the waiting room.
Relevance to clinical practice
From an infection control perspective, broadcasting from speakers can be a
substitute for headphones when playing music to lower the anxiety level of patients
waiting for surgery.
Acknowledgements
This study was supported by Taipei Medical University Hospital, Taiwan, ROC.
Contributions of the author
Study design: YFC, KCL; data analysis: YFC, KCL, PYC; Manuscript preparation:
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