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Journal of Music Therapy, 53(4), 2016, 430–477
doi:10.1093/jmt/thw012; Advance Access publication October 19, 2016
© the American Music Therapy Association 2016. All rights reserved.
For permissions, please e-mail: journals.permissions@oup.com
The Effects of Music on Pain:
AMeta-Analysis
Jin HyungLee, PhD, MT-BC
Ewha Womans University, Seoul, Korea
Background: Numerous meta-analyses have been conducted on the
topic of music and pain, with the latest comprehensive study published in
2006. Since that time, more than 70 randomized controlled trials (RCTs)
have been published, necessitating a new and comprehensive review.
Objective: The aim of this meta-analysis was to examine published RCT
studies investigating the effect of music on pain.
Methods: The present study included RCTs published between 1995
and 2014. Studies were obtained by searching 12 databases and hand-
searching related journals and reference lists. Main outcomes were pain
intensity, emotional distress from pain, vital signs, and amount of anal-
gesic intake. Study quality was evaluated according to the Cochrane
Collaboration guidelines.
Results: Analysis of the 97 included studies revealed that music inter-
ventions had statistically significant effects in decreasing pain on 0–10
pain scales (MD = –1.13), other pain scales (SMD = –0.39), emotional
distress from pain (MD = –10.83), anesthetic use (SMD = –0.56), opi-
oid intake (SMD =–0.24), non-opioid intake (SMD=–0.54), heart rate
(MD=–4.25), systolic blood pressure (MD=–3.34), diastolic blood pres-
sure (MD=–1.18), and respiration rate (MD=–1.46). Subgroup and mod-
erator analyses yielded additional clinically informative outcomes.
Conclusions: Considering all the possible benefits, music interventions
may provide an effective complementary approach for the relief of acute,
procedural, and cancer/chronic pain in the medical setting.
Keywords: music therapy; music medicine; pain; meta-analysis
Introduction
According to the International Association for the Study of
Pain (IASP, 1994), pain is “an unpleasant sensory and emotional
Address correspondence concerning this article to Jin Hyung Lee, PhD, MT-BC,
Ewhayeodae-gil 52, Graduate School #306, Ewha Womans University, Seoul, South
Korea. E-mail: mtjinlee@gmail.com.
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Vol. 53, No. 4 431
experience associated with actual or potential tissue damage, or
described in terms of such damage.” This denition implies that
how one understands and uses the word “pain” is inuenced by his
or her multilayered physical, psychological, social, and cultural expe-
riences associated with unpleasant stimuli or injuries from thepast.
Pain can be classied as procedural, acute, or chronic (Allen,
2013). Procedural pain occurs when medical procedures result in
tissue and/or nerve damage. Sharp and sudden pain not caused
by medical procedures is called acute pain, which is often associ-
ated with a single treatable event of injury or illness that can usu-
ally be managed within seven days (American Society for Pain
Management Nursing [ASPMN], 2010). Chronic pain, also known
as persistent pain, lasts longer than the anticipated duration of
healing (ASPMN, 2010), and occurs continuously or intermittently
with or without a known cause. According to the American Pain
Society (2006), cancer-related pain is classied as a type of chronic
pain with further sub-classication.
Pain plays a critical role in maintaining health and well-being.
However, many patients undergoing medical treatment suffer from
unnecessary procedural and acute pain during their course of
treatment or recovery, and even prolonged chronic pain thereafter
(Brennan, Carr, & Cousins, 2007; Groenewald, Rabbitts, Schroeder, &
Harrison, 2012). Untreated pain can lead to immunological or
neural alterations associated with chronic pain (Stephens, Laskin,
Pashos, Peña, & Wong, 2003); issues in gastrointestinal and uri-
nary tract function, and an increase in cardiac output and catabolic
hormones (Stephens et al., 2003); decreases in mobility, strength,
and immune functioning (Lipman, 2005; Lohman, Schleifer, &
Amon, 2010); and various problems in the social, behavioral, and
psychological domain (European Pain Federation, n.d.; Gureje,
Von Korff, Simon, & Gater, 1998; Kreps, 2012). Due to its negative
impact on every aspect of one’s life, pain can signicantly dimin-
ish one’s quality of life (King & Fraser, 2013; Reyes-Gibby, Aday, &
Cleeland, 2002).
Music interventions have been utilized as a way of ameliorating
pain and distress for patients with various medical issues. Generally,
two major types of music interventions have been implemented:
“music medicine” and “music therapy.” Music medicine (MM)
refers to the “pre-recorded music listening experiences adminis-
tered by medical personnel” (Dileo & Bradt, 2005, p.5). On the
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432
other hand, music therapy (MT) is an intervention “involving a rela-
tionship between client and therapist, a therapeutic process” with
a carefully planned music experience (Dileo & Bradt, 2005, p.9).
To investigate the effects of music on pain, many clinical trials
have been conducted since the early 1970s (Lee, 2015). However,
the overwhelming number of existing and newly published stud-
ies, and their vast differences in ndings, make it very challenging
for clinicians to make well-informed decisions (Sauerland & Seiler,
2005). Systematic reviews can address this issue by carefully synthe-
sizing results from multiple studies. Asystematic review is a rigorous
and comprehensive synthesis of clinical trials in order to uncover
reliable and generalizable evidence in a specic area of practice
(Durlak, Meerston, & Foster, 2003; Sauerland & Seiler, 2005).
Asubset of systematic reviews that utilizes statistical techniques to
integrate quantitative data from multiple studies is meta-analysis
(Moher, Liberati, Tetzlaff, Altman, & PRISMA Group, 2009).
Therefore, in order to integrate results from numerous clini-
cal trials investigating the effects of music interventions on pain,
systematic reviews have been conducted with patients with cancer
(Bardia, Barton, Prokop, Bauer, & Moynihan, 2006; Bradt, Dileo,
Grocke, & Magill, 2011; Tsai et al., 2014; Zhang et al., 2012),
patients undergoing surgery (Engwall & Duppils, 2009; Hartling
et al., 2009; Nilsson, Hälsoakademin, & Örebro universitet, 2008),
pediatric patients (Klassen, Liang, Tjosvold, Klassen, & Hartling,
2008; Lee, 2013; Standley & Whipple, 2003); neonatal patients
(Hartling et al., 2009; Haslbeck, 2012; Standley, 2002), patients
with heart disease (Bradt, Dileo, & Potvin, 2013), patients undergo-
ing medical procedures (Bechtold et al., 2009; Tam, 2008; Yinger &
Gooding, 2015), and all types of patients (Dileo & Bradt, 2005;
Cepeda, Carr, Lau, & Alvarez, 2006; Lee, 2015).
A critical review of these systematic reviews indicated that the sys-
tematic reviews yield inconsistent results showing varying degrees
of effect sizes and substantial heterogeneity among included stud-
ies (Lee, 2015). The methodological quality of the reviewed stud-
ies was “moderate” in general, and many studies omitted essential
information about music interventions, which is essential for high-
quality systematic reviews (Shea etal., 2007). For instance, most
studies reviewed music medicine studies only or did not differen-
tiate the type of music interventions used, making it impossible
to compare or contrast the effects between the two very different
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Vol. 53, No. 4 433
clinical applications (Lee, 2015). Furthermore, the most recent
meta-analysis solely devoted to the effects of music on pain was
conducted by Cepeda and colleagues (2006), which analyzed tri-
als published between the years 1986 and 2003. In a preliminary
search of RCTs investigating this effect, the author identied over
70 studies published in or after 2004. Therefore, a more up-to-date,
comprehensive review is needed, including all populations across
different settings and age groups.
Consequently, the aim of this study was to conduct a rigorous
and comprehensive meta-analysis of clinical trials investigating the
effect of music on pain, encompassing a wide range of medical
diagnoses, settings, age groups, and types of pain; to compare the
effects between music medicine and music therapy; and to investi-
gate potential moderator variables (e.g., pain subtypes, age groups)
that appear to affect the outcome. The study sought to answer the
following research questions: (a) How effective is music in reduc-
ing pain for patients of all ages and populations when compared
to standard care?; (b) How effective is music in reducing analgesic
use when compared to standard care?; (c) How effective is music in
alleviating pain as measured by lowered vital signs (i.e., heart rate,
respiration rate, and systolic and diastolic blood pressure) when
compared to standard care?; (d) Is there a difference between
the effectiveness of music medicine and music therapy in reduc-
ing pain, analgesic use, and vital signs when compared to standard
care?; (e) As moderator variables, how inuential are pain sub-
types (i.e., procedural/acute vs. chronic/cancer pain), patient age
groups, and methodological rigor (e.g., randomization, allocation
concealment, blinding, etc.) on the effectiveness of music in reduc-
ing pain when compared to standard care?
Methods
Inclusion Criteria
Included trials were limited to randomized controlled trials
(RCT) published between 1995 and 2014 in English, German,
Korean, and Japanese. Studies from the past two decades were cho-
sen, because clinical trials from more recent years are considered
higher quality in their methodology and reporting style (Tsai etal.,
2014). The language restriction was applied due to the limited
resources available to the author.
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434
There were no limitations in regard to age, gender, ethnicity, types
of pain, medication use, or type of medical procedure. However, stud-
ies involving musicians who sustained injuries from playing instru-
ments were excluded due to the difference in the scope of practice
and medical issues. To minimize heterogeneity caused by differences
in interventions, I excluded studies that combined two or more
approaches (e.g., music plus videos), studies that employed a non-
standard care group as a comparison group (e.g., music vs. verbal
relaxation), and music medicine studies that fell outside the usual
practice (e.g., use of live musicians or vibroacoustic equipment).
Outcome Measures
The primary outcome was participants’ self-reported level of
pain intensity on 0–10 pain scales such as visual analog scales
(VAS), faces scales, numerical rating scales (NRS), and other vali-
dated pain scales (e.g., the McGill Pain Questionnaire and Present
Pain Intensity).
Emotional distress from pain measured on 100 mm visual analog
scale was utilized as a secondary outcome, as a group of researchers
in nursing used this affective pain scale to measure the “amount of
emotional distress associated with the sensation” (Good etal., 1999,
p.165). Other secondary outcomes were physiological measures,
such as heart rate, systolic blood pressure, diastolic blood pressure
and respiration, and amount of anesthetic and opioid intake.
For this study, studies were grouped by combining four pain types
into two groups according to the duration and severity of pain: acute/
procedural and chronic/cancer pain. Due to the scarcity of studies
investigating either chronic or cancer pain alone, the classication
of pain offered by the American Pain Society (2006) was utilized, in
which cancer-related pain was included as a subtype of chronic pain.
Search Strategy
Two research librarians were consulted in developing a com-
prehensive search strategy to identify clinical trials published in
Academic OneFile, Academic Search Premier, CINAHL, Global
Health, Google Scholar, Healthstar, Medline, ProQuest Digital
Dissertations, PsycINFO, RILM Abstracts of Music Literature, RISS
International (Korean DB), and Web of Science. The keywords and
strategy used for the search were pain OR distress OR discomfort OR ache
OR headache OR bromyalgia OR migraine OR analgesic OR analgesia OR
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Vol. 53, No. 4 435
opioid OR pain relief OR pain medication, and music OR music therapy OR
lullaby OR sing OR song OR listening OR harp. To identify unindexed
articles, I hand-searched the following music therapy and related
journals: Journal of Music Therapy, Music Therapy Perspectives, Music
and Medicine, Australian Journal of Music Therapy, British Journal of
Music Therapy, Canadian Journal of Music Therapy, New Zealand Journal
of Music Therapy, Nordic Journal of Music Therapy, Voices: World Forum
for Music Therapy, Journal of Music and Human Behaviors (Korea), and
Korean Journal of Music Therapy, in addition to checking the reference
lists of all identied clinical trials, systematic reviews, and meta-analy-
ses. To locate unpublished gray literature such as unpublished or yet-
to-be published clinical trials and doctoral dissertations, Isearched
Google, Google Scholar, and conference proceedings available
online, and contacted 18 PhD music therapy programs worldwide to
inquire about articles being prepared for publication.
Study Selection
First, Iexamined titles, keywords, and abstracts of identied arti-
cles to eliminate irrelevant studies. Then, full texts were inspected
to check against the inclusion and exclusion criteria. When
Iencountered studies that were questionable as to whether they
met the inclusion criteria, Icontacted my research advisor to dis-
cuss the details and clarify issues before making a nal decision.
Data Extraction
I modied the data extraction form used by Bradt, Magee, Dileo,
Wheeler, and McGilloway (2010) and converted it into a Microsoft
Excel™ le to extract data from selected articles. The form cap-
tured: (1) general information, (2) research design, (3) participant
characteristics, (4) methodological quality, (5) outcome measures,
(6) statistical data, and (7) details about type and nature of music
interventions. Iused only the information reported originally in
the research article or dissertation extracting and analyzing data.
Idid not attempt to obtain missing data from the author(s), and
double data extraction was not done due to time limitations.
Statistical data extracted from each study included sample sizes,
and means and standard deviations for both treatment and control
groups. If only the mean and standard deviation of change scores
from pretest to posttest were available, it was noted, and data were
extracted in the same manner. For studies that used wait-list control
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436
group or crossover design, scores from the rst phase of the clinical
trial were extracted. For studies with signicant baseline differences
in the pretest outcome, Icalculated the mean change score (MCS)
and SD of MCS using the Cochrane MCS calculator to obtain the
applicable data. This was only done with outcomes that could be
combined using the mean difference analysis explained below.
Assessment of Study Quality and Risk ofBias
I evaluated the quality of each study according to the Cochrane
Handbook for Systematic Reviews of Interventions (Higgins &
Green, 2011). Specic areas assessed for quality and bias appraisal
were: (1) randomization, (2) allocation concealment, (3) blinding
of research personnel who administer the music intervention, (4)
assessment of subjective outcomes, (5) assessment of objective out-
comes, (6) intention to treat analysis, (7) selective reporting, and
(8) other sources of bias. Each area was rated as “low,” “unclear,” or
“high risk of bias.” When assessing the “intention to treat analysis,”
I rated it as “low bias” if the attrition rate was less than 20% and
reasons for dropout were similar for both groups. For a detailed
elaboration of the assessment criteria, refer to Lee (2015).
Statistical Analysis
All outcome data included in this review were continuous data,
and were analyzed using the standardized mean differences (SMD)
or mean differences (MD) with 95% condence intervals. SMD was
used when outcomes from various scales were combined, whereas
MD was calculated to present outcomes that utilize an identical
assessment tool (e.g., 0–10 numeric rating scales, vital signs). If
essential data needed for meta-analysis (i.e., means and standard
deviations) were missing, Iexcluded those studies without attempt-
ing to impute missing outcomes.
I used the Review Manager (RevMan 5.3.3) to process the statis-
tical data from all included studies. For studies that only reported
change scores from pretest to posttests, those scores derived from
identical measurement tools were pooled under the mean dif-
ference (MD) analysis, as suggested in the Cochrane Handbook
(Higgins & Green, 2011). Because heterogeneity is anticipated
from observation of previous meta-analyses, Iused the more con-
servative random-effect model to calculate the pooled estimates
(Higgins & Thompson, 2002).
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Vol. 53, No. 4 437
The study used I2 statistics to evaluate heterogeneity, which esti-
mates the percentage of total variation across trials (Higgins &
Thompson, 2002). Interpretation of the results was based on the
guidelines proposed by Higgins and Thompson, which indicate
that percentages roughly around 25%, 50%, and 75% can be con-
sidered “low,” “medium,” and “high” heterogeneity, respectively
(2002). Publication bias was examined by visually inspecting a
funnel plot generated from 0–10 pain intensity scales. The poten-
tial reporting bias was assessed using the guidelines presented by
Sauerland and Seiler (2005).
Moderator and Sensitivity Analyses
In order to investigate factors that cause variability in effect size,
Ianalyzed age groups and pain types as predetermined modera-
tors. In addition, Icompared studies that met certain methodologi-
cal criteria (e.g., randomization and allocation concealment) to
examine whether meeting the methodological standards affected
the effect size.
Results
Description of Included Studies
Figure1 illustrates the process of study selection, and a refer-
ence list for included studies appears in Supplementary Appendix
A.Atotal of 94 trials were identied. Because three articles reported
multiple trials or treatment conditions (Koch, Kain, Ayoub, &
Rosenbaum, 1998; MacDonald, Mitchell, Serpell, Davies, & Ashley,
2003; Schou, 2008), the total number of analyzed trials was 97 (87
for music medicine [MM] and 10 for music therapy [MT]), which
involved a total of 9,184 participants. The reasons for exclusion are
also provided in Figure1.
The nal sample consisted of 69 two-arm parallel, 19 three-arm
parallel, 5 four-arm parallel, and 3 randomized crossover RCTs. As
shown in Table1, the studies were conducted most frequently in
North America, Asia, and Europe. Ninety-one trials were reported
in English, whereas six were in Korean (Hyun etal., 2004; Jeon,
2004; Kim & Kim, 2009, 2010; Kim etal., 2004; Seo & Hong, 2010).
None of the retrieved articles in German or Japanese language met
the inclusion criteria. Supplementary Appendix B lists the charac-
teristics of participants in included studies.
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F1.
Flowchart of study selection process.
T1
Region and Country of Included Trials
Region MM MT Total Country
North America 30 7 37 Canada, USA
Asia 25 2 27 China & Hong Kong SAR, India,
Japan, Malaysia, South Korea,
Taiwan, Thailand, Vietnam
Europe 24 1 25 Denmark, Finland, France, Greece,
Iceland, Italy, Scotland, Sweden,
Turkey, UK
Middle East 6 6 Iran, Israel
Africa 1 1 Egypt
South America 1 1 Colombia
Total 87 10 97
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Vol. 53, No. 4 439
T2
Interventions by Types of Pain, Age Groups & Settings
Interventions / pain types
Adults Children
TotalInpatient Outpatient Inpatient Outpatient
Music medicine 48 33 1 5 87
Acute pain 37 12 49 (56%)
Procedural pain 6 19 1 5 31 (36%)
Cancer/Chronic pain 5 2 7 (8%)
Music therapy 6 2 1 1 10
Cancer/Chronic pain 4 1 5 (50%)
Acute pain 2 1 3 (30%)
Procedural pain 1 1 2 (20%)
Total 54 35 2 6 97
T3
Titles Used to Describe Music Medicine in Different Regions
Regions
Referred to “music medicine” as
Total
“Music,” “music listening,” or
“music intervention” (MI) Both MI & MT
interchangeably Music therapy (MT)
North America 23 5 2 30
Asia 10 10 5 25
Europe 14 6 4 24
Middle East 3 3 6
Africa 1 1
South America 1 1
Total 52 (58.6%) 24 (27.6%) 11 (13.8%) 87
Table 2 summarizes study and participant characteristics for
included studies, with trials ranging in sample size from 25 to 617
with a mean sample size of 95.96 (SD=79.72) and a median of
66.5. Eighty-six studies targeted acute/procedural pain, whereas
only 10 studies focused on cancer or chronic pain. Eighty-eight
studies involved adult patients, and only eight trials involved chil-
dren. Based on reported information from 81 studies, the mean
age was 48.37 (SD=9.64) for the adults and 8.78 (SD=0.81) for the
children. Atotal of 61 studies reported the gender of participants;
these included 53.8% male overall, with 49.9% male participants
for the adult group and 57.7% male for the children’s group. The
gender distribution was similar for MM and MT groups. Table 3
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440
illustrates different populations and settings according to types of
pain and music intervention. General characteristics of the stud-
ies, including pain type, age group, medical specialization, treat-
ment setting, and outcome measures, can also be found in Tables
4 and5.
Description of Outcome Measures
Outcome measures are summarized in Table 4 (MM studies)
and Table 5 (MT studies) and were grouped into three categories
including pain intensity, physiological measures (i.e., vitals), and
analgesic requirements. Overall, a total of 76 studies (78.4%) relied
upon participants’ own rating of pain intensity using 0–10 scales
such as Visual Analog Scales (VAS), Faces Scales (FS), Numeric
Rating Scales (NRS), and Verbal Rating Scales (VRS). Other sub-
jective tools included the Magill Pain Questionnaire (MPQ) (k = 8;
8.2%), a visual analog scale of emotional distress from pain (VAS-
Distress) (k= 8; 8.2%), and brief pain inventory (BPI) (k = 1; 1%).
Five studies (5.2%) employed objective assessments of pain using
validated tools, such as CAMPIS-R: Child-Adult Medical Procedure
Interaction Scale-Revised (Yinger, 2012); CHEOPS: Children’s
Hospital of Eastern Ontario Pain Scale (Yu, Liu, Li, & Ma, 2009);
FLACC: Face, Legs, Activity, Cry, Consolability Scale (Gutgsell et
al., 2013); NIPS: Neonatal Infant Pain Scale (Zhu et al., 2015);
and OSBD-R: Observational Scale of Behavioral Distress–Revised
(Hartling et al., 2013). Here, k indicates number of studies.
The secondary outcomes of pain were physiological measures,
including heart rate (k = 28; 28.9%), respiration rate (k = 10; 10.3%),
mean arterial blood pressure (k = 5; 5.2%), systolic blood pressure
(k = 21; 21.6%), and diastolic blood pressure (k = 19; 19.6%). A
number of studies also investigated analgesic requirements during
or after medical or surgical procedures. These were categorized
as anesthetics (i.e., Propofol, Isourane, & Sevourane) (k = 7;
7.2%), opioids (i.e., Alfentanil, Fentanyl, Meperidine, Morphine, &
Tramadol) (k = 23; 23.7%), non-opioids (i.e., Acetaminophen &
Diclofenac) (k = 3; 3.1%), and sedatives (Midazolam & Versed) (k
= 7; 7.2%).
Description of Intervention Characteristics
Intervention characteristics are summarized in Table 6 (MM
studies) and Table7 (MT studies).
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T4
General Characteristics—Music Medicine Studies
Authors & year Pain
Types Age
Group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Abraham & Dvory,
2014
AP Adults Neurology Out VAS (unclear)
Ajorpaz etal., 2014 AP Adults Cardiology In VAS
Allred, K., 2007 AP Adults Orthopaedic In VAS MPQ-SF HR, RR, MAP
Angioli etal., 2014 AP Adults OBGYN Out VAS HR, RR, SBP, DBP
Ayoub etal., 2005 AP Adults Urology In AN-Propofol
Bally etal., 2003 AP Adults Cardiology Out VAS
Bansal etal., 2010 AP Adults Urology In SD-Midazolam
Beaulieu-Boire etal.,
2013
AP Adults Intensive care In OP-Fentanyl &
AN-Propofol
Bechtold etal., 2006 AP Adults Gastroenterology Out VAS OP-Meperidine &
SD-Midazolam
Bellieni etal., 2013 AP Adults Physical therapy Out VAS
Binns-Turner, 2008 AP Adults Oncology In VAS HR, MAP OP-Morphine eqv.
Blankeld etal., 1995 AP Adults Cardiology In OP-Morphine
Brouscious, 1999 AP Adults Cardiology In NRS
Cepeda etal., 1998 AP Adults Urology Out VRS OP-Alfentanil
Chan, 2007 AP Adults &
seniors
Cardiology In VAS HR, RR, SBP, DBP
Chan etal., 2003 AP Adults OBGYN Out VAS
Chan etal., 2006 AP Adults &
seniors
Cardiology In VAS HR, RR, SBP, DBP
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442
Authors & year Pain
Types Age
Group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Chiang, 2012 CP Adults Hospice/
Oncology
In VAS
Chlan etal., 2000 AP Adults Gastroenterology Out NRS
Costa etal., 2010 AP Adults Gastroenterology Out VA S
Danhauer etal., 2007 AP Adults OBGYN Out VAS
Danhauer etal., 2010 AP Adults Oncology Out VAS
Ebneshahidi &
Mohseni, 2008
AP Adults OBGYN In VAS HR, SBP, DBP OP-Morphine
Good, 1995 AP Adults General surgery In NRS OP-Morphine
Good & Chin, 1998 AP Adults OBGYN In VAS
Good etal., 1999 AP Adults General surgery In VAS
Guerrero etal., 2012 AP Adults OBGYN Out VAS HR, SBP, DBP
Hartling etal., 2013 AP Children Emergency
medicine
Out OSBD-R HR
Hook etal., 2008 AP Adults OBGYN In VAS VAS-D OP-Morphine eqv.
Huang etal., 2010 CP Adults Oncology In VAS, VRS VAS-D
Hyun etal., 2004 AP Adults Orthopaedic In VAS HR, SBP, DBP
Ikonomidou etal.,
2004
AP Adults OBGYN In VAS
Jacobson, 1995 AP Adults General medicine In VAS VAS-D
Jacobson, 1999 AP Adults General medicine In VAS VAS-D
Jafari etal., 2012 AP Adults Cardiology In NRS
Jeon, 2004 AP Adults Dentistry Out VAS
T4
Continued
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Vol. 53, No. 4 443
Authors & year Pain
Types Age
Group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Jose etal., 2012 AP Adolescents &
adults
Cardiology In NRS
(unclear)
HR, SBP, DBP
Kim etal., 2004 AP Adults Orthopaedic In NRS
Kim etal., 2011 AP Adults Dentistry Out VAS (0–5) HR, RR, SBP, DBP
Koca Kutlu & Eren,
2014
AP Adults Nephrology Out VAS
Koch etal., 1998 AP Adults Urology In HR, SBP, DBP AN-Propofol
Koch etal., 1998 AP Adults Urology Out VAS HR, SBP, DBP OP-Alfentanil
Kristjánsdóttir &
Kristjánsdóttir,
2011
AP Adolescents General medicine Out VAS
Kulkarni etal., 2012 AP Adults Radiology In OP-Fentanyl &
SD-Midazolam
Kwekkeboom, 2003 AP Adults Oncology In NRS
Laurion & Fetzer,
2003
AP Adults OBGYN Out VRS OP-Morphine eqv. &
NOP-Acetaminophen
Lepage etal., 2001 AP Adults General surgery Out SD-Midazolam
Li & Dong, 2012 AP Adults OBGYN In VAS
Li etal., 2011 CP Adults Oncology In VAS MPQ
Macdonald etal.,
2003
AP Adults General surgery In VAS MPQ
Macdonald etal.,
2003
AP Adults OBGYN In VAS
T4
Continued
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444
Authors & year Pain
Types Age
Group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Masuda, Miyamoto &
Shimizu, 2005
AP Seniors Orthopaedic In VAS, FS HR, SBP, DBP
Migneault etal., 2004 AP Adults OBGYN In HR, MAP OP-Fentanyl &
AN-isourane
Nagata etal., 2014 AP Adults Gastroenterology Out VA S HR, SBP, DBP
Nguyen etal., 2010 AP Children Oncology In NRS HR, RR, SBP, DBP
Nilsson etal., 2003 AP Adults General surgery Out VAS OP-Morphine
Nilsson etal., 2003 AP Adults General surgery In VAS OP-Morphine
Nilsson etal., 2005 AP Adults General surgery In NRS HR, SBP, DBP OP-Morphine
Ottaviani etal., 2012 AP Older adults Orthopaedic Out VAS HR, SBP, DBP
Ovayolu etal., 2006 AP Adults Gastroenterology Out VAS OP-Meperidine &
SD-Midazolam
Parlar Kilic etal.,
2014
AP Adults Emergency
medicine
Out VAS
Phipps etal., 2010 AP Adults Neurology In VAS HR, RR, SBP, DBP
Phumdoung & Good,
2003
AP Adults OBGYN In VAS VAS-D
Pothoulaki etal.,
2008
AP Adults Nephrology Out VAS
Press etal., 2003 AP Children Emergency
medicine
Out FS VAS
(Observer)
Reza etal., 2007 AP Adults OBGYN In VAS OP-Morphine
Salem, 2004 AP Adults OBGYN In VA S VAS-D
T4
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Authors & year Pain
Types Age
Group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Sen etal., 2010 AP Adults OBGYN In OP-Tramadol &
NOP-Diclofenac
Sen etal., 2009 AP Adults Urology Out AN-Propofol
Sen etal., 2009 AP Adults OBGYN In OP-Tramadol
Seo & Hong, 2010 CP Adults Hospice/
Oncology
In BPI-K
Siedliecki & Good,
2006
CP Adults Pain clinic Out VAS MPQ-SF
Simavli etal., 2014 AP Adults OBGYN In VA S HR, SBP, DBP NOP-Diclofenac
Simavli etal., 2014 AP Adults OBGYN In VA S
Simcock etal., 2008 AP Adults Orthopaedic In VAS, FS
Szmuk, 2008 AP Adults General Surgery In VAS HR, MAP AN-sevourane
Vaajoki etal., 2012 AP Adults General Surgery In VAS VAS-D
Vanderboom etal.,
2012
AP Adults Neurology Out HR, SBP OP-Fentanyl &
SD-Midazolam
Voss etal., 2004 AP Adults Cardiology In VAS VAS-D
Yeo etal., 2013 AP Adults Urology Out VAS HR, SBP
Yu etal., 2009 AP Children Oriental
medicine
Out FS CHEOPS HR, RR, MAP
Zengin etal., 2013 AP Adults Oncology Out VAS HR, RR, SBP, DBP
Zhang etal., 2005 AP Adults OBGYN In AN-Propofol
T4
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Authors & year Pain
Types Age
Group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Zhang etal., 2014 AP Adults Urology Out VAS HR
Zhu etal., 2015 AP Neonates Neonatology In NIPS
Zimmerman etal.,
1996
AP Adults Cardiology In VRS MPQ
Note. AP: acute/procedural pain; CP: cancer/chronic pain; Out: outpatient; In: inpatient; VAS: visual analog scale; NRS: numeric rating
scale; MPQ-SF: Magill pain questionnaire–short form; HR: heart rate; RR: respiration rate; MAP: mean arterial pressure; SBP: systolic
blood pressure; DBP: diastolic blood pressure; AN: anesthetic; SD: sedative; OP: opioid; VRS: verbal rating scale; VAS-D: visual analog scale
of emotional distress from pain; OSBD-R: observational scale of behavioral distress–revised; SBP: systolic blood pressure; DBP: diastolic
blood pressure; NOP: none-opioid medication; eqv: equivalent; VAS: visual analog scale; NRS: numeric rating scale; FS: faces scale; MAP:
mean arterial pressure; NOP: NOP: none-opioid medication; VRS: verbal rating scale; BPI-K: Brief pain inventory–Korean; CHEOPS:
Children’s Hospital of Eastern Ontario Pain Scale; NIPS: Neonatal infant pain scale.
T4
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T5
General Characteristics—Music Therapy Studies
Authors & year Pain
types Age group Specialization Setting 0–10 scale Other
scales Physiological
measures Analgesic
requirements
Bradt, 2001 AP Children Orthopaedic In VAS
Clark etal., 2006 CP Adults Radiology Out NRS
Fredenburg &
Silverman, 2014
CP Adults Oncology In NRS
Ghetti, 2011 AP Adults General
surgery
In NRS
Ghetti, 2013 AP Adults Cardiology Out NRS HR, RR, SBP,
DBP
OP-Fentanyl &
SD-Versed
Gutgsell etal., 2013 CP Adults Hospice/
Oncology
In NRS FLACC
Kim & Kim, 2009 CP Adults Oncology In VAS
Kim & Kim, 2010 CP Adults Oncology In VAS
Yinger, 2012 AP Children Pediatric Out CAMPIS-R
Schou, 2008 AP Adults Cardiology In VAS OP-Morphine
Note. AP: acute/procedural pain; CP: cancer/chronic pain, Out: outpatient; In: inpatient; VAS: visual analog scale, NRS: numeric rating
scale, FLACC: Face, Legs, Activity, Cry, Consolability Scale; CAMPIS-R: Child-Adult Medical Procedure Interaction Scale-Revised; HR:
heart rate; RR: respiration rate; SBP: systolic blood pressure; DBP: diastolic blood pressure; OP: opioid; SD: sedative.
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T6
Intervention Characteristics of Music Medicine Studies
Authors & year Duration Selection Title of IX Equip Types / Genres / Titles of music
Abraham & Dvory,
2014
30 PP MI SPK Classical, instrumental, rock
Ajorpaz etal., 2014 30 SC IC HDP
Allred, K., 2007 20 PP MI HDP Easy listening
Angioli etal., 2014 PP MI SPK Pop, jazz, classical, rock
Ayoub etal., 2005 PC MI HDP Personal library
Bally etal., 2003 30 PP MT HDP Classical, soft rock, relaxation, country
Bansal etal., 2010 PP MT HDP Classical, folk, or religious category
Beaulieu-Boire etal.,
2013
60 SC MI HDP Classical: provided lists of titles
Bechtold etal., 2006 SC MI SPK New age: “Watermark” by Enya
Bellieni etal., 2013 PP MI ERP Classic, rock, disco
Binns-Turner, 2008 PP MI ERP Classical, easy listening, inspirational, new age
Blankeld etal., 1995 30 SC MI HDP New age: “Dream Flight II” by Herb Ernst
Brouscious, 1999 35 PP MI ERP Various: provided lists of titles
Cepeda etal., 1998 45 PP MI HDP Classical, Caribbean, soft rock, jazz
Chan etal., 2003 PP IC SPK Instrumental ballad
Chan etal., 2006 45 PP IC ERP Chinese and Western
Chan, 2007 45 PP IC ERP Chinese classical (e.g., bamboo ute), religious music (e.g.,
Buddha Bar IV–Tibet), and Western classical (e.g., Mozart
piano concerto No. 26)
Chiang, 2012 20 PP MI Choice Classical, piano, harp, religious, easy listening, Chinese, and
Taiwanese: provided lists of titles
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Authors & year Duration Selection Title of IX Equip Types / Genres / Titles of music
Chlan etal., 2000 PP MT HDP Classical, country-western, new age, easy listening, pop, rock,
religious, era-specic, motion-picture soundtracks, jazz
Costa etal., 2010 25 PP MI HDP Blues, swing, classic, country, jazz, glam rock, 50-60-70s rock,
instrumental, new age, Celtic, reggae, relaxing, Spanish
music, classic Italian pop, modern Italian pop, classic
American pop, motion picture sound, native American
Danhauer etal., 2007 10 PP IC HDP Classical, harp, general instrumental, nature sounds
Danhauer etal., 2010 20 PP MI HDP Classical, harp, general instrumental, nature sounds, country,
gospel, and jazz
Ebneshahidi &
Mohseni, 2008
30 PC IC HDP Personal library
Good & Chin, 1998 15 PP MI ERP Western music: piano, harp, synthesizer, orchestral, slow jazz
Good etal., 1999 15 PP MI ERP Synthesizer, harp, piano, orchestral, slow jazz
Good, 1995 PP MI ERP Synthesizer, harp, piano, orchestral, slow jazz music
Guerrero etal., 2012 PP MI HDP Rock, pop, hip-hop, rap, classical, jazz, Spanish, alternative,
easy listening and reggae
Hartling etal., 2013 SC MI SPK “The Planets Op.32, Jupiter, Storms in Africa, Disco Beat,
and Sunny Days”
Hook etal., 2008 30 PP MT HDP Western, Malay, Chinese
Huang etal., 2010 30 PP IC ERP Folk songs, Buddhist hymns (Taiwanese), harp, piano:
provided lists of titles
Hyun etal., 2004 60 PP IC HDP
Ikonomidou etal.,
2004
30 SC IC HDP Pan ute music
T6
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T6
Continued
Authors & year Duration Selection Title of IX Equip Types / Genres / Titles of music
Jacobson, 1995& 1999 PP MI HDP Provided lists of titles
Jafari etal., 2012 30 PP IC HDP
Jeon, 2004 PP MI HDP Classical, new age, popular, Korean popular
Jose etal., 2012 20 PP MT HDP Old Hindi, devotional songs, instrumental, Cazab.
Kim etal., 2004 120 PP IC Classical, meditative, or nature music: provided lists of titles
Kim etal., 2011 20 PP IC HDP Classical, pop, folk, hymns, and Korean-style country
Koca Kutlu & Eren,
2014
30 SC IC HDP Instrumental (violin and piano) Turkish art music
Koch etal., 1998a & b 67 PC MI HDP Personal library
Kristjánsdóttir &
Kristjánsdóttir,
2011
3 PP MI HDP vs SPK Top-10 charts music and classical
Kulkarni etal., 2012 60 PC MI HDP Personal library
Kwekkeboom, 2003 10 PP IC HDP
Laurion & Fetzer,
2003
SC IC
Lepage etal., 2001 45 PP MI HDP Pop, jazz, classical, new age
Li & Dong, 2012 30 SC MI Chinese classical
Li etal., 2011 30 PP MT HDP Chinese classical & folk, popular world music, and Chinese
relaxation music
Macdonald etal.,
2003: T1& T2
Choice PC MI Personal library
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Vol. 53, No. 4 451
Authors & year Duration Selection Title of IX Equip Types / Genres / Titles of music
Masuda etal., 2005 20 PP MI HDP Western classical, Gagaku, Noh songs, or Enka (Japanese)
Migneault etal., 2004 PP MI HDP Classical, jazz, new age, and popular piano music
Nagata etal., 2014 SC MI SPK New age: “The Best of Enya–Paint the Sky with Stars”
Nguyen etal., 2010 23 PP IC ERP Traditional Vietnamese and children’s songs
Nilsson etal., 2003 40 SC MI HDP New age
Nilsson etal., 2003 110 SC MI HDP Classical
Nilsson etal., 2005 40 SC MI HDP New age, synthesizer
Ottaviani etal., 2012 20 SC IC SPK
Ovayolu etal., 2006 30 SC IC SPK Turkish classical played on ney (reed ute)
Parlar Kilic etal., 2014 SC IC SPK Turkish classical (Acemasiran)
Phipps etal., 2010 30 PP IC SPK Light classical
Phumdoung & Good,
2003
180 PP MI ERP Synthesizer, harp, piano, orchestra, and jazz: provided lists of
titles
Pothoulaki etal., 2008 PP MI HDP Popular, Greek folk, jazz, classical, soundtracks, new age
Press etal., 2003 SC MI HDP
Reza etal., 2007 24 SC MI HDP Soft instrumental, Spanish-style guitar
Salem, 2004 50+ PP MI HDP Soft synthesizer, harp, piano, orchestra, jazz
Schou, 2008 35 PP MT SPK Easy listening, classical, Musicure, jazz: provided lists of titles
Sen etal., 2010 60 SC MT HDP
Sen etal., 2009 60 PC IC HDP Personal library
Sen etal., 2009 49 PC MI ERP Personal library
Seo & Hong, 2010 35 PP IC ERP Gospel, hymnal, Buddhist hymnal, K-pop (Ballad, Trot),
popular, Korean art song, classical, instrumental
T6
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T6
Continued
Authors & year Duration Selection Title of IX Equip Types / Genres / Titles of music
Siedliecki & Good,
2006
60 PP MI HDP Piano, jazz, orchestra, harp, synthesizer
Simavli etal., 2014 40+ PP MT HDP Classic, Turkish music (art, folk, classic), popular
Simavli etal., 2014 40+ PP MT Choice Classic, Turkish music (art, folk, classic), popular
Simcock etal., 2008 PC MI HDP Personal library
Szmuk, 2008 75 PP MI HDP Classical, pop-rock, Israeli music
Vaajoki etal., 2012 30 PP MI HDP Domestic or foreign hit songs, dance, pop, rock, soul, blues,
spiritual or classical
Vanderboom etal.,
2012
PP MI SPK Classical, jazz, new age, country, pop, rock, folk, acoustic,
meditative trance.
Voss etal., 2004 30 PP MI HDP Synthesizer, harp, piano orchestra, slow jazz, ute
Yeo etal., 2013 8 SC MI HDP Classical
Yu etal., 2009 30 PP IC HDP Popular & traditional children’s, Christmas, folk songs
Zengin etal., 2013 30 SC MT SPK Turkish classical (Acemisiran)
Zhang etal., 2005 6 PP MI HDP
Zhang etal., 2014 7 PP MI Classical, Chinese folk, popular, Western
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Authors & year Duration Selection Title of IX Equip Types / Genres / Titles of music
Zhu etal., 2015 5 SC MT SPK Easy listening: “Souvenirs D’enfance, AComme Amour, &
Ballade Pour Adeline by Richard Oayderman”
Zimmerman etal., 1996 30 PP IC HDP Country-western instrumental by Country Pops; Fresh Aire
by Mannheim Steamroller; Winter into Spring by George
Winston; Prelude and Comfort Zone, by Steven Halpern
Note. PP: participant preferred; SC: staff chosen; PC: participant chosen; EC: expert consultation; MC: musical criteria; PL: published
literature; IX: intervention; MI: referred own IX as music or music intervention; MT: referred to own IX as music therapy; IC: referred to
own IX as music, music intervention and/or music therapy interchangeably; SPK: speaker; HDP: headphone; ERP: earphones.
T6
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T7
Intervention Characteristics of Music Therapy Studies
Authors & year Age group Session
style Setting Music
format Length
(minutes) / Frequency Specic
MT approach
Bradt, 2001 Children Active Ind Live 30–45 / 1 Entrainment session
Clark etal., 2006 Adults Passive Ind Recorded 45–60 / 1+ IML
(2–4 week)
Provided 1 psycho-educational session to
develop individualized music list and teach
relaxation techniques, participants used
music & relaxation individually
Fredenburg &
Silverman,
2014
Adults Passive Ind Live 30 / 1 Receptive approach with therapist’s live
singing & playing of patient’s preferred
music
Ghetti, 2011 Adults Active Ind Live 30–40 / 1 Active music engagement (recreative)
Ghetti, 2013 Adults Active Ind Live 30–40 / 1 Emotional approach coping coupled with
active music engagement (recreative)
Gutgsell etal.,
2013
Adults Passive Ind Live 20 / 1 Receptive approach with therapist’s guided
relaxation with live harp music
Kim & Kim, 2009 Adults Active Group
3–6
Live 60 / 1 Various (recreative, compositional
Improvisational, receptive)
Kim & Kim, 2010 Adults Active vs.
Passive
Group
3–6
Live &
Recorded
50 / 1 Compared two MT conditions: receptive
group vs. recreative/singing-centered
group
Schou, 2008 Adults Passive Ind Recorded 35 / 3–5 Therapist provided guided relaxation and
imagery with music
Yinger, 2012 Children Active Ind Live Before/during/after
immunization / 1
Recreative
Note. Ind: individual; IL: individual music listening; MT: music therapy.
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Music Medicine Studies. Among the 87 music medicine studies
analyzed for this meta-analysis, 55 (63%) were identied as provid-
ing “participant-preferred” (PP) music as the researchers prepared
lists of music from which the participants chose specic songs, or
a style, instrument type, or genre of music that they preferred.
Genres of music commonly provided were classical, easy listening,
new age, slow jazz, and softrock.
Ten clinical trials (10.3%) used procedures wherein participants
were asked to bring their own music (Ayoub, Rizk, Yaacoub, Gaal, &
Kain, 2005; Ebneshahidi & Mohseni, 2008; Koch et al., 1998;
Kulkarni, Johnson, Kettles, & Kasthuri, 2012; MacDonald et al.,
2003; Simcock etal., 2008; Şen etal., 2009; Şen, Sizlan, etal., 2009);
this was classied as “participant-chosen” (PC) music in this study.
Due to vast differences in musical tastes, participants brought a wide
variety of music; however, MacDonald and colleagues reported that
about 70% of the participants in their experimental group selected
popular music (2003). Other studies did not describe the type of
music participants selected for themselves.
Twenty-two trials (25%) used researcher-chosen (RC) music in
which participants listened to particular pieces of music selected by
their researchers. Among these, six studies listed the specic pieces
of music that they used (Beaulieu-Boire et al., 2013; Bechtold, Perez,
Puli, & Marshall, 2006; Blankeld, Zyzanski, Flocke, Alemagno, &
Scheurman, 1995; Hartling et al., 2013; Nagata et al., 2014; Zhu
etal., 2015), whereas 11 studies only provided the style or genre of
music that they used.
The duration of music listening was highly variable among trials.
Based on the data from 63 studies, the mean duration of the music
intervention was 37.8 minutes (SD = 28.5), with a range from 1
minute to 180 minutes and a mode of 30 minutes.
Robb, Burns, and Carpenter (2011) recommended that
researchers provide a rationale for the selection and application
of music when reporting music-based interventions. However,
many studies analyzed in this study omitted essential informa-
tion about the music interventions. Among MM studies, 72 trials
(82.8%) did not report the specic music used, 20 studies (23%)
did not indicate the duration of the music intervention, 9 studies
left out all information about their music, and 6 studies did not
explain the equipment used to deliver music (i.e., headphones
or speakers).
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Even though the scope and nature of practice between MM and
MT interventions are very different, MM studies have used a variety
of terms to describe interventions. When Ianalyzed what MM studies
called their interventions, Ifound that 51 studies (58.6%) used terms
such as “music,” “music listening,” or “music intervention,” and 12
authors referred to their MM intervention as “music therapy.” The
latter group of authors used both terms, MM and MT, interchange-
ably. As shown in Table3, Idiscovered that music medicine was most
poorly differentiated from music therapy among studies in Asia.
Music Therapy Studies. There were 10 music therapy clinical tri-
als included in this meta-analysis. Two studies conducted by the
same researchers (Kim & Kim, 2009, 2010) investigated the effect
of a single group music therapy session on pain, whereas the oth-
ers examined the impact of individual MT sessions. In terms of
the levels of participants’ music involvement, ve studies (Bradt,
2001; Ghetti, 2011, 2013; Kim & Kim, 2009; Yinger, 2012) included
a more active style of engagement using recreative (e.g., singing
and playing pre-composed music) and creative methods (e.g.,
songwriting), whereas four trials (Clark etal., 2006; Fredenburg &
Silverman, 2014; Gutgsell etal., 2013; Schou, 2008) used sessions
involving receptive methods (e.g., listening to live music) with pas-
sive participation. One study by Kim and Kim (2010) compared the
two types of approaches by conducting two separate MT groups:
one with a receptive approach and the other with a singing-cen-
tered recreative approach.
Most studies provided one single MT session, but three studies
(Bradt, 2001; Clark etal., 2006; Schou, 2008) implemented slightly
different formats. Bradt (2001) randomized the sequence of two
MT and one standard-care session, and reported results from every
phase. Only the post-test data from the rst MT session was used
for this meta-analysis. Clark etal. (2006) offered a 45–60-minute
psycho-educational session described as an “interview” wherein the
therapist assessed the client’s musical preference, educated partici-
pants on relaxation techniques, and provided a personalized music
program. The frequency and duration of listening to music after
that was different for each individual participant. Schou (2008)
facilitated guided relaxation with music and imagery for patients
undergoing cardiac surgery once before and 2–4 times after the
surgery. For this analysis, Iextracted data from the post-test of the
rst session following heart surgery.
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Results of Risk of Bias Assessment
Randomization. Upon assessing whether the included studies
clearly described the method of random allocation, Ifound that 68
trials (70.1%) implemented a proper method, whereas 28 studies
(29%) did not.
Allocation Concealment. Group allocation was properly con-
cealed to the recruiter and participants until all informed consents
were obtained in 26 studies (27%), but not in three studies (3.2%).
The rest of the studies (69.8%) did not mention allocation con-
cealment procedures.
Blinding. Blinding the researcher was not possible and/or not
described in most studies (94.8%), but it was adequately per-
formed in ve MM studies (5.2%) (Beaulieu-Boire et al., 2013;
Ikonomidou, Rehnstrom, & Naesh, 2004; Migneault etal., 2004;
Nguyen, Nilsson, Hellström, & Bengtson, 2010; Yu etal., 2009).
Most studies could not prevent participants from knowing their
group allocation due to the nature of music interventions. However,
it was achieved among ve MM studies, as four studies (Migneault
etal., 2004; Reza, Ali, Saeed, Abul-Qasim, & Reza, 2007; Simcock
etal., 2008; Szmuk etal., 2008) provided music after participants
were sedated, and Bechtold and colleagues (2006) did not reveal
the independent variable (i.e., music) to their participants.
Risk of bias for “Assessment of Objective Outcomes” was rated as
“low” for 67 studies (69.8%), because 37 of them did not use objective
assessment tools (38.5%), and 30 trials (31.3%) used proper blinding
of their assessors. Among the rest, 16 studies did not blind the outcome
assessors, and 22 trials did not describe the process of blinding assessors.
Intention-to-Treat Analysis. Attrition rate was adequately
reported and explained in 74 trials (77.1%). On the other hand,
withdrawals were either too high or reported without reasons in
ve studies (5.2%), and were not clearly described in 17 studies
(17.7%).
Selective Reporting. All outcomes were discussed in 90 studies
(93.8%); however, there were six studies with missing or unclear
information (6.4%).
Other Sources of Bias. Sixty-two studies (64.6%) either declared
no conict of interest or disclosed their funding sources. Thirty-
three studies (35.4%) were rated as “unclear,” as the above infor-
mation was missing. Arisk of bias graph can be found in Figure2.
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F2.
Risk of bias graph: Risk of bias across all included studies.
Assessment of ReportingBiases
Publication bias was examined by visually inspecting a funnel plot
created using the Revman software based on data from the 0–10
pain intensity scales (Figure3). The funnel plot did not indicate
evidence of a publication bias, as it demonstrated a symmetrical,
inverted funnel shape (Egger, Smith, Schneider, & Minder, 1997).
Results of Main Outcomes
In this section, effect size ndings for pain intensity, emotional
distress from pain, analgesic use, and vital signs are presented.
Tables 4 and 5 provide a list of studies and their corresponding
outcome measures, and Table 8 lists the overall results of the
meta-analyses.
Effect Size for Pain Intensity. A total of 76 studies involving
6,430 participants examined the effect of music interventions on
the subjective perception of pain using 0–10 scales. The music
group showed a statistically signicant lower level of pain than
the standard care group by 1.13 units on the 0–10 scales (95% CI
–1.44, –0.82, p < .00001). However, this result was highly inconsist-
ent among the studies analyzed (I 2=95%).
Fifteen studies involving 1,278 participants used various other
types of pain scales (see “Other scales” in Tables 4 and 5). The
standardized mean difference (SMD) was –0.39, indicating a
small to medium effect according to Cohen’s guidelines (1988),
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Vol. 53, No. 4 459
in decreasing the pain level (95% CI –0.68, –0.09, p = 0.01) with
substantial heterogeneity (I 2=84%).
Effect Size for Emotional Distress from Pain. The analysis of the
eight studies involving 731 participants showed a statistically sig-
nicant lower distress score (MD=–10.83, 95% CI –17.12, –4.53,
p = .0008), but this also was highly heterogeneous (I 2=91%) (see
“VAS-D” in Table4 under “Other scales”).
Effect Size for Analgesic Use. Here, ndings for anesthetics, opi-
oids, non-opioids, and sedatives are described. For anesthetic use,
seven studies involving 382 participants revealed a statistically sig-
nicant and moderate effect on reducing total anesthetic use (e.g.,
propofol, isourane, or sevourane) (SMD = –0.56, 95% CI –0.88,
–0.25, p = .0005); this effect was moderately heterogeneous (I
2 = 54%).
For opioids intake such as morphine, fentanyl, and tramadol, 23 stud-
ies involving 1,761 participants indicated a small but statistically sig-
nicant and homogeneous effect (SMD = –0.24, 95% CI –0.34, –0.14,
p < .00001, I
2 = 8%). For non-opioid intake (i.e., acetaminophen and
diclofenac), three studies involving 258 participants yielded a moder-
ate and statistically signicant effect in reducing the use of non-opioids
F3.
Funnel plot: Music vs. standard care on 0–10 pain intensity scales.
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T8
Meta-Analysis of Music Interventions on Pain
Analysis no. & outcomes k N Effect size 95% CI p value I 2 (%)
1.1 Pain intensity: 0–10 scales 76 6,430 MD –1.13 –1.44, –0.82 < .00001 95
1.1.1 MT 9 505 “ –1.50 –2.09, –0.91 < .00001 58
1.1.2 MM 67 5,925 “ –1.08 –1.42, –0.75 < .00001 96
1.2 Pain intensity: other scales 15 1,278 SMD –0.39 –0.68, –0.09 .010 84
1.2.1 MT 2 254 “ –0.42 –1.09, 0.24 0.22 79
1.2.2 MM 13 1,024 “ –0.38 –0.72, –0.04 0.03 86
1.3 Distress: 100 mm VAS (MM) 8 731 MD –10.83 –17.12, –4.53 .0008 91
1.4 Use of anesthetics (MM) 7 382 SMD –0.56 –0.88, –0.25 .0005 54
1.5 Use of opioids 22 1,761 “ –0.24 –0.34, –0.14 < .00001 8
1.5.1 MT 2 49 “ –0.05 –0.62, 0.51 0.85 0
1.5.2 MM 21 1,712 “ –0.25 –0.35, –0.14 < .00001 15
1.6 Use of non-opioids (MM) 3 258 “ –0.54 –0.78, –0.29 < .0001 0
1.7 Use of sedatives 7 564 “ –0.4 –0.92, 0.11 0.12 88
1.7.1 MT 1 20 “–0.39 –1.28, 0.50 0.39 n/a
1.7.2 MM 6 544 “–0.41 –0.97, 0.16 0.16 90
1.8 Heart rate 28 2,195 MD –4.25 –5.92, –2.59 < .00001 70
1.8.1 MT 1 22 “–1.5 –16.92, 13.92 0.85 n/a
1.8.2 MM 27 2,173 “–4.28 –5.97, –2.60 < .00001 71
1.9 Systolic blood pressure 21 1,811 “ –3.34 –5.23, –1.45 .0005 43
1.9.1 MT 1 20 “5 –13.70, 23.70 0.60 n/a
1.9.2 MM 20 1,791 “–3.42 –5.32, –1.51 .0004 45
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Analysis no. & outcomes k N Effect size 95% CI p value I 2 (%)
1.10 Diastolic blood pressure 19 1,693 “–1.18 –2.30, –0.07 0.04 43
1.10.1 MT 1 20 “5.8 –3.05, 14.65 0.20 n/a
1.10.2 MM 18 1,673 “–1.31 –2.40, –0.21 0.02 42
1.11 Mean arterial pressure (MM) 5 216 “ –0.61 –6.91, 5.69 0.85 74
1.12 Respiration rate 10 1,028 “ –1.46 –2.58, –0.34 0.01 92
1.12.1 MT 1 19 “2.4 –0.91, 5.71 0.16 n/a
1.12.2 MM 9 1,009 “–1.71 –2.86, –0.56 .004 92
Note. k: number of studies; N: number of participants; CI: condence interval; I2: heterogeneity testing; MD: mean difference; SMD: stand-
ardized mean difference; VAS: visual analog scale.
T8
Continued
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T9
Moderator Analyses on 0–10 Pain Intensity Scale••
Intervention Moderator k N Effect size (MD) 95% CI p value I
2 (%)
Types of pain
Overall Acute/Procedural 67 5,679 –1.11 –1.45, –0.77 < .00001 96
Chronic/Cancer 9 751 –1.16 –1.54, –0.77 < .00001 66
MT Acute/Procedural 4 100 –1.53 –3.08, 0.03 0.05 73
Chronic/Cancer 5 405 –1.42 –1.99, –0.84 < .00001 48
MM Acute/Procedural 63 5,579 –1.09 –1.44, –0.74 < .00001 96
Chronic/Cancer 4 346 –0.92 –1.41, –0.43 < .001 71
Age groups
Overall Children 5 344 –1.60 –2.83, –0.38 0.01 87
Adults 71 6,086 –1.10 –1.42, –0.77 < .00001 95
MT Children 1 32 –3.45 –4.80, –2.10 < .00001 n/a
Adults 8 473 –1.26 –1.71, –0.81 < .00001 26
MM Children 4 312 –1.13 –2.17, –0.09 0.03 80
Adults 63 5,613 –1.08 –1.42, –0.73 < .00001 96
Randomization & allocation concealment
Both met 20 1,624 –0.97 –1.55, –0.39 .001 91
Not met 56 4,805 –1.18 –1.51, –0.85 <.00001 95
Blinding objective assessors
Blinded 3 300 –0.39 –0.72, –0.06 0.02 38
Not blinded 3 273 –0.72 –1.47, 0.02 0.06 88
Note. k: number of studies; N: number of participants; MD: mean difference; CI: condence interval; I2: heterogeneity testing; n/a: not
available.
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Vol. 53, No. 4 463
(SMD = –0.54, 95% CI –0.78, –0.29, p < .0001) with no signs of het-
erogeneity (I
2 = 0%). Finally, seven studies showed no statistically sig-
nicant effect on reducing sedative use (e.g., midazolam and versed)
(SMD = –0.4, 95% CI –0.92, 0.11, p = 0.12, I
2 = 88%).
Effect Size for Vital Signs. The following section describes the
effect size ndings for ve vital signs: heart rate, systolic blood pres-
sure (SBP), diastolic blood pressure (DSB), mean arterial pressure
(MAP), and respiration rate. The analysis of 28 studies involving
2,195 participants indicated that music interventions lowered heart
rate by 4.25 bpm (beats per minute) (95% CI –5.92, –2.59, p <
.00001). However, this result was highly heterogeneous (I
2 = 70%).
SBP was reported in 21 studies with 1,811 participants; the mean
difference was –3.34 mmHg (95% CI –5.23, –1.45, p = .0005), and
this effect was fairly consistent (I 2 = 43%). For DSP, the analysis of
19 studies with 1,693 participants indicated that music signicantly
decreased diastolic blood pressure by 1.18 units (mm Hg) (95% CI
–2.30, –0.07, p = 0.04); this effect was moderately consistent (I 2 =
43%). MAP was measured in ve studies, but did not show evidence
for an effect of music on MAP (MD = –0.61, 95% CI –6.91, 5.69, p
= 0.85, I
2 = 74%). Ten trials involving 1,028 participants reported
respiration rate and demonstrated that the music group took 1.46
breaths per minute fewer than the control group (95% CI –2.58,
–0.34, p = 0.01); however, these results were highly inconsistent (I
2
= 92%).
Comparative Analysis: Music Therapy vs. Music Medicine
Pain Intensity Scales. A subgroup analysis between MT and MM
studies demonstrated that participants from the nine MT trials
involving 505 participants displayed a greater reduction of –1.50
(95% CI –2.09, –0.91, p < .00001), whereas the participants in the
67 MM studies with 5,925 participants showed a reduction of –1.08
(95% CI –1.42, –0.75, p < .00001) on the 0–10 scales. The differ-
ence between the two groups was not statistically signicant. On
the other hand, the level of heterogeneity was moderate for MT
(I 2=58%) and high for MM (I 2=96%) studies.
A subgroup analysis on other pain intensity scales showed a
small to medium effect for 13 MM studies involving 1,024 par-
ticipants (SMD = –0.38, 95% CI –0.72, –0.04, p = 0.03), but no
statistically signicant effect for two MT trials of 254 participants
(SMD = –0.42, 95% CI –1.09, 0.24, p = 0.22). This is likely due
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464
to the small number of studies analyzed for the MT group. The
results, however, were inconsistent for both MM (I 2=86%) and
MT (I 2=79%) groups.
Emotional Distress from Pain. Acomparison on emotional
distress from pain measured by 0–10 VAS scale could not be
conducted because none of the MT studies investigated this
outcome.
Anesthetic Use. Subgroup analyses between MT and MM on
the amount of anesthetic use and non-opioids were not feasible,
because none of the MT studies reported these outcomes.
A comparative analysis on the use of opioids indicated a non-
signicant effect for two MT studies involving 49 participants
(SMD=–0.05, 95% CI –0.62, 0.51, p = 0.85), but a small yet statisti-
cally signicant effect for 21 MM studies with 1,712 participants
(SMD=–0.25, 95% CI –0.35, –0.14, p < .00001, I 2=15%).
The data on sedative use did not indicate an effect for the one
MT study (SMD= –0.39, 95% CI –1.28, 0.50, p = 0.39) or six MM
studies (SMD=–0.41, 95% CI –0.97, 0.16, p = 0.16).
Vital Signs. Comparative analyses on vital signs did not yield any
meaningful result, as there was only one RCT in the MT group
reporting these outcomes (Ghetti, 2013).
Moderator and Sensitivity Analyses
Types of Pain. Scores from the 0–10 pain intensity scales were
reanalyzed by comparing acute/procedural pain vs. chronic can-
cer pain. The analysis showed that the combined music interven-
tions showed a statistically signicant effect on reducing chronic/
cancer pain (k=9, N=5,679, MD = –1.16, 95% CI –1.54, –0.77,
p < .00001, I 2=66%) and acute/chronic pain (k=67, N = 751,
MD=–1.11, 95% CI –1.45, –0.77, p < .00001, I 2= 96%). Here, k
indicates the number of trials analyzed and N indicates the total
number of participants involved in the analysis.
This analysis on the subtypes of pain was conducted separately
for MT and MM studies. MT trials showed a statistically signicant
but heterogeneous effect on acute/procedural pain (k=4, N=100,
MD = –1.53, 95% CI –3.08, –0.03, p =.05, I 2 = 73%), but a sta-
tistically signicant and moderately consistent effect for chronic/
cancer pain (k=5, N=405, MD=–1.42, 95% CI –1.99, –0.84, p <
.00001, I 2=48%).
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Vol. 53, No. 4 465
The analysis of MM studies also produced a statistically signi-
cant but heterogeneous effect on both acute/procedural pain
(k=63, N =5,579, MD=–1.09, 95% CI –1.44, –0.74, p < .00001,
I 2=96%) and chronic/cancer pain (k=4, N =346, MD=–0.92,
95% CI –1.41, –0.43, p < .001, I 2=71%).
Age Groups. The moderator analyses on age groups indicated
that music decreased pain signicantly for both children (k=5,
N=344, MD=–1.60, 95% CI –2.83, –0.38, p = 0.01, I 2=87%) and
adults (k= 71, N = 6,086, MD =–1.10, 95% CI –1.42, –0.71, p <
.00001, I 2=95%) on 0–10 scales. The mean difference was greater
for children than adults, but not statisticallyso.
Additional analyses on the age groups were conducted sepa-
rately for MT and MM interventions. The results suggested that
MT had statistically signicant pain-relieving effects for both chil-
dren (k=1, N=32, MD=–3.45, 95% CI –4.80, –2.10, p < .00001)
and adults (k=8, N=473, MD=–1.26, 95% CI –1.71, –0.81, p <
.00001, I 2=26%); this result should be interpreted with caution
because there was only one MT study involving children.
The analyses of MM studies also indicated statistically signicant
effects for both children (k=4, N=312, MD=–1.13, 95% CI –2.17,
–0.09, p = 0.03, I 2=80%) and adults (k=63, N=5,613, MD=–1.08,
95% CI –1.42, –0.73, p < .00001, I 2=96%).
Randomization and Allocation Concealment. There were 20
studies with 1,624 participants that met both criteria for minimiz-
ing selection bias, whereas there were 56 studies with 4,805 par-
ticipants that did not fulll one or more criteria. The pooled esti-
mate of effects on 0–10 pain intensity scales indicated that both
groups showed a statistically signicant pain-reducing effect, but it
was slightly weaker for the group with higher methodological rigor
(MD=–0.97, 95% CI –1.55, –0.39, p=.001) than the one without
(MD=–1.18, 95% CI –1.44, –0.82, p < .00001). Both groups, how-
ever, exhibited substantial heterogeneity of over 90%.
Assessment of Objective Outcomes. The six studies that used
observational tools to measure pain intensities were divided into
three studies that hid the group allocation information from their
assessors and three that did not blind the assessors. The trials with
blinded assessors produced a small to medium, but statistically sig-
nicant and fairly consistent pain-reducing effect (N = 300, SMD
= –0.39, 95% CI –0.72, –0.06, p = 0.02, I 2 = 38%) when compared
to standard care. On the other hand, trials that did not blind
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466
their assessors showed a greater but not signicant effect (N =
273, SMD = –0.72, 95% CI –1.47, 0.02, p = 0.06), in addition to
high heterogeneity (I 2 = 80%). Table 9 reports the results of mod-
erator analyses.
Discussion
The aim of this study was to conduct a meta-analysis of clinical
trials investigating the effect of music interventions on pain regard-
less of the medical diagnosis, settings, age groups, or types of pain.
The results were reported using mean difference (MD) or stand-
ardized mean difference (SMD) along with I 2 results for estimation
of heterogeneity. For interpretation of SMD, Ifollowed Cohen’s
guideline; he indicated a small effect for 0.2, a medium effect for
0.5, and a large effect for 0.8 (1988).
Analyses of Outcome Variables
This study showed that music interventions overall decreased
pain by 1.13 units on 0–10 scales. This result is substantially greater
than the results from previous meta-analyses, which was –0.46 for
overall pain without a specic population (Cepeda etal., 2006),
and –0.54 for cancer pain (Zhang etal., 2012). This comparison
with the study by Cepeda and colleagues is especially meaningful,
as a comprehensive meta-analysis on all types of pain, in that the
current nding is based on 72 newly added studies in addition to
17 overlapping studies.
The analysis of non 0–10 pain scales indicated a small to medium
effect (SMD=–0.39, p=0.01). This nding is similar to or weaker
than the results from previous meta-analyses, which were –0.39 for
pediatric pain (Klassen etal., 2008) and –0.59 to –0.656 for cancer
pain (Bradt etal., 2011; Tsai etal., 2014). This difference between
overall pain and cancer pain can be due to the “oor effect”
(MacDonald etal., 2003), which illustrates how interventions often
show a larger effect on severe pain than minor pain (Binns-Turner,
Wilson, Pryor, Boyd, & Prickett, 2011). On the other hand, when
converted into SMD, the pain intensity measured on 0–10 scales
becomes –0.63, which is greater or similar to that effect reported
in the meta-analyses on cancer pain (Bradt etal., 2011; Tsai etal.,
2014).
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Over 20 studies included in this meta-analysis mentioned the
Gate Control theory (Melzack, 1996), which proposes that cogni-
tive understanding and emotional reaction to pain can activate the
descending control of pain inhibitors. In investigating this theory,
eight trials investigated the “amount of emotional distress asso-
ciated with the sensation” (Good etal., 1999, p.165) and found
that music listening has a medium to large effect on decreasing
emotional distress from pain. This outcome appears to support
the Gate Control theory and the need for assessing pain using
multidimensionaltools.
The evidence suggests that receptive music interventions (i.e.,
MM) have a small to moderate effect in reducing the amount of
anesthetic, opioid, and non-opioid usage during or after medi-
cal procedures. This effect was highly consistent for opioid and
non-opioid intake, but moderately heterogeneous for the use of
anesthetics. Considering the potential side effects that accompany
these analgesic agents, the overall evidence seems to support the
use of music for reducing analgesiause.
The results showed a moderate but statistically signicant effect
on lowering heart rate by 4.25 bpm, systolic blood pressure by
3.34 mm Hg, and respiration rate by 1.46 bpm. Ameta-analysis
investigating heart rate reduction in patients with heart failure
reported that every 5 bpm reduction in heart rate was associ-
ated with an 18% reduction in risk of death (McAlister, Wiebe,
Ezekowitz, Leung, & Armstrong, 2009). In terms of blood pres-
sure, every 10 mm Hg decrease in systolic and 5 mm Hg reduction
in diastolic blood pressure has been found to be associated with a
22% decrease in risk for developing coronary heart disease and a
41% reduction in risk of stroke (Law, Morris, & Wald, 2009). These
studies suggest that the clinical signicance of the outcomes on
vital signs may be greater for patients suffering from pain. However,
the effects on vital signs have been inconsistent, and these results
need to be interpreted with caution.
Comparative Analysis: Music Therapy vs. Music Medicine
Although Dileo and Bradt (2005) found a statistically more
favorable result for MT than for MM in their meta-analysis, the
present study did not nd a statistical difference between MT and
MM (p=0.23), even though MT showed a greater pain-reducing
effect (MD=–1.50) than MM (MD=–1.08). On the other hand,
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an additional interpretation can be made in terms of MM and
MT’s clinical signicance. Gallagher, Liebman, and Bijur (2001)
reported that the minimum change required for achieving a clini-
cally meaningful change is 1.3 on 0–10 VAS scales. Based on that
recommendation, MT is found to be clinically signicant, whereas
MM isnot.
The comparison on non 0–10 scales showed no statistically sig-
nicant effect for MT but a small to moderate effect for MM. The
non-signicant effect for MT was likely due to the small sample
size and highly variable data from one study (Gutgsell etal., 2013).
This study by Gutgsell etal. used two types of non 0–10 scales: Face,
Legs, Activity, Cry, Consolability (FLACC) scale and Functional
Pain Scale (FPS). The scores from FLACC, which were used for
this analysis, show an extremely large standard deviation that seems
to impact the meta-analytic results. When the FLACC data were
replaced with FPS, the analysis yielded a statistically signicant
result with a moderate effect for the MT group (SMD=–0.54, 95%
CI, –0.89, –0.19, p=0.003) with a robust consistency (I 2=34%).
This moderate effect was larger than what was found for the MM
group (SMD=–0.38); however, no rm conclusion can be drawn at
this point due to the small number of MT studies.
Results from the current analyses suggest that MT showed a clini-
cally more meaningful effect on patients’ own perception of pain
intensity, whereas MM is more effective in decreasing analgesic use
and lowering vital signs. This overview of effects found in this meta-
analysis seems to reect the fundamental differences between MT
and MM. The goal of MM is narrower in that music is generally
used to distract, alleviate tension, and/or promote relaxation, and
the important factors in MM are quality music, proper equipment,
and appropriate music selection. On the other hand, MT “always
involves a therapeutic process, a music therapist, and a relationship
that develops through the music and process” (Dileo, 1999, p.4).
Thus, music therapists do not approach a client only to reduce
stress or alleviate pain, because the therapeutic focus is “broader,
involving the whole of the patient on many levels” (Dileo, 1999,
p. 5). What makes MT different from MM is the role and pres-
ence of a therapist, extensive use of live music, utilization of various
music experiences, an individually tailored therapeutic process,
and a holistic approach. Nevertheless, the purpose of this discus-
sion is not to determine which is better; rather, it is to establish that
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Vol. 53, No. 4 469
both interventions have therapeutic value and can benet patients
in different ways.
Moderator and Sensitivity Analyses
Music interventions, as a whole, showed a slightly stronger
impact on acute/procedural pain (MD=–1.15) than on chronic/
cancer pain (MD=–0.97), but the difference was marginal. Similar
patterns were observed for both MT and MM studies. In terms of
the clinical signicance, MT showed clinically meaningful effects
for both acute/procedural pain (MD=–1.53) and chronic/cancer
pain (MD=–1.42), whereas MM did not show a clinically meaning-
ful effect on either types ofpain.
Results from 0–10 pain intensity scales indicate that music inter-
ventions are effective for both adults and children. However, a
fairly large difference exists between their effect estimates (chil-
dren: MD=–1.60; adults: MD=–1.1). This difference is not statisti-
cally signicant, but according to Gallagher etal. (2001), the mean
difference in children is clinically signicant, whereas the adults’
score is not. Thus, it can be said that children benet more from
the pain-reducing effect of music. An interesting comparison can
be made with the results from other meta-analyses (Dileo & Bradt,
2005; Tsai etal., 2014). In their analyses of moderators, Tsai etal.
found that adults beneted more than children on anxiety and
depression measures; however, children beneted more on pain
measures (SMD=–0.835 for children vs. SMD=0.579 for adults).
Likewise, Dileo and Bradt also reported discovering a greater over-
all effect size in studies conducted in the pediatric population
(r=0.39) compared to other populations (r=0.12 to r = 0.38),
although the effect was not based on pain-specic outcomes.
A closer look at the data shows that in general, children benet
more from music than adults do, and more from music therapy
than music medicine. However, these observations are made based
on a few trials, and more studies are needed to conrm these
ndings.
The sensitivity analyses of methodological factors suggest that
selection or detection bias may be present and may skew clini-
cal outcomes; however, the actual impact on effect estimates is
minimal. On the other hand, a sub-analysis indicated that studies
with the highest methodological qualities yielded the strongest
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470
evidence with zero heterogeneity. Nevertheless, it is important to
continue to conduct risk of bias assessment, and to interpret results
accordingly.
Issue of Heterogeneity
Although various efforts have been made to minimize heteroge-
neity, highly inconsistent effects still remained. For instance, the
results of I 2 were 95% for 0–10 scales and 84% for other scales.
There are many factors that could contribute to this high level of
heterogeneity, such as population, medical diagnosis, procedure,
research setting, study design, and sampling error. In addition, the
vast differences found in music interventions appear to contribute
to the high level of heterogeneity (Tsai etal., 2014). In this study,
the duration, frequency, style, genre, preparation, choice, ration-
ale, personnel, equipment, and approach in the delivery of music
interventions were largely different. When visually inspecting the
forest plots, however, it was observed that the direction of effect
is in agreement in at least 90% of the studies. The heterogene-
ity appears to be inuenced more by several studies with either
highly effective or ineffective results. Thus, a further investigation
of these studies may lead to the discovery of factors that contrib-
ute to the high variance in meta-analytic results. Nevertheless, the
meta-analytic results from this study must be interpreted with cau-
tion, and additional moderator analyses or sub-analyses need to be
conducted to identify the various sources of heterogeneity.
Limitations
Specic efforts have been made to uncover consistent pain-
reducing effects of music by conducting various moderator analy-
ses, yet a great portion of the ndings yielded highly heteroge-
neous outcomes. Moreover, a few sub-analyses, particularly some
involving MT, included only a few studies, thus weakening the
external validity of the results. Thus, it is essential to interpret the
results from this study with caution. In addition, one should be
extra careful when interpreting the meta-analytic results based on
vital signs and amount of anesthetic use, as the statistically lower
vital signs and analgesic drug use may indicate other non-pain
outcomes such as decreased level of anxiety or lower sympathetic
arousal.
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Vol. 53, No. 4 471
Because no comprehensive meta-analysis on music and pain has
been conducted on studies published in or after 2005, Iinvested
extra time searching many databases with wide search parameters
without restrictions. In addition, Ialso conducted extensive hand
and online searches and contacted experts in the eld. Thus, this
study became one of the largest meta-analyses focusing on a par-
ticular outcome in MM and MT research. However, due to the inev-
itable language restrictions, there were a good number of studies
that could not be included. In addition, because Icould not access
foreign databases in languages other than English and Korean,
there may be undiscovered clinical trials that meet the inclusion
criteria of this study in other languages.
One of the criteria for evaluating methodological quality of sys-
tematic reviews is the implementation of “double extraction.” Due
to the time constraints and timelines for completing extraction
and analysis, Iwas unable to use “double extraction” and include
studies with missing data in this study.
Conclusion
Results from the 97 trials suggest that music interventions over-
all have benecial effects on pain intensity, emotional distress
from pain, use of anesthetic, opioid and non-opioid agents, heart
rate, systolic and diastolic blood pressure, and respiration rate.
Additional analyses suggest that MM and MT show no statistically
signicant difference in lowering pain levels; MT shows a more
clinically meaningful effect in reducing self-rated pain intensity
than MM; MT shows clinically meaningful effects on both acute/
procedural pain and chronic/cancer pain; children appear to
benet more from music interventions overall than do adults.
However, these results need to be interpreted with caution due
to highly heterogeneous outcomes among the included studies.
Based on the current analysis, both MT and MM appear to be ben-
ecial and can benet patients in different ways: MT has shown a
greater clinical impact on pain intensity than MM; on the other
hand, MM produced evidence suggesting a signicant reduction
in analgesic use whereas MT did not. Considering all the possible
benets, both types of music interventions may provide an effective
complementary approach for the relief of acute, procedural, and
cancer/chronic pain in the medical setting.
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472
Supplementarydata
Supplementary data can be found at: http://www.jpepsy.oxford-
journals.org/.
Funding
The author did not receive any funding for this study.
Acknowledgments
The author would like to thank Dr. Cheryl Dileo for her guid-
ance throughout this project as this study was conducted in par-
tial fulllment of the degree of Doctor of Philosophy at Temple
University. He also thanks the Cochrane collaboration for making
the Revman software openly available to researchers.
Conicts of interest
None declared.
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