The Arts in Psychotherapy 49 (2016) 50–56
Contents lists available at ScienceDirect
The Arts in Psychotherapy
Research article
Group music therapy impacts mood states of adolescents in a
psychiatric hospital setting
Jonah Shuman b , Heather Kennedy a,b,∗ , Peter DeWitt c , Anthony Edelblute b ,
Marianne Z. Wamboldt a,b
a
University of Colorado Anschutz Medical Campus, School of Medicine, Department of Psychiatry, 13001 E. 17th Place, Campus Box C290, Room E1354,
Aurora, CO 80045, USA
b
Children’s Hospital Colorado, 13123 East 16th Avenue, Aurora, CO 80045, USA
c
University of Colorado Anschutz Medical Campus, Colorado School of Public Health, Colorado Biostatistics Consortium, 12477 E. 19th Avenue, Aurora, CO,
80045, USA
a r t i c l e
i n f o
Article history:
Received 28 May 2015
Received in revised form
30 December 2015
Accepted 14 May 2016
Available online 19 May 2016
Keywords:
Music therapy
Adolescents
Mental disorders
Retrospective study
Mood changes
a b s t r a c t
Although Music Therapy, an allied health discipline, is often included in standard care for the treatment
of children with mental health disorders, there is a lack of empirical evidence to support its contribution
for the care of children and adolescents in mental health services. The goal of this retrospective research
is to examine whether group music therapy affects mood states of adolescent inpatients in a psychiatric
hospital service based within a large children’s hospital. A secondary aim was to understand if specific
patient demographic predictors influenced the mood outcome. Participants included 352 predominately
white, non-Hispanic patients (12–21 years old, with a mean age of 15.13 ± 1.88 years) who completed
596 mood measures between August 2010 and March 2013. Participants completed the Fast Assessment
of Children’s Emotions (FACE) before and after a group music therapy session. Based on a binary outcome
model of change or no change, the probability of a change in total mood score was high (probability
of change 0.82 [95%CI 0.79, 0.85]). There were no significant associations between age, gender, or other
specific demographics that were tested, nor changes in individual or total mood scores within this sample.
This preliminary research documents the immediate impact of group music therapy sessions on mood
of adolescent patients in this setting diagnosed with a range of psychiatric disorders.
© 2016 Elsevier Ltd. All rights reserved.
1. Introduction
Music therapy is defined as “the clinical and evidence-based use
of music interventions to accomplish individualized goals within
a therapeutic relationship by a credentialed professional” (AMTA,
2015). Music therapy interventions include offering group sessions
of listening to or creating music with other clients or one-onone interactive sessions between a trained music therapist and a
client. Music therapy has been shown to be helpful in the medical
and rehabilitation fields, especially for pain and anxiety reduction
(Evans, 2002).
In a review of music therapy for surgical patients (Nilsson,
2008), 42 randomized controlled trials that examined use of music
therapy preoperatively (n = 10), intra-operatively (n = 9), postoperatively (n = 15) or at several times throughout surgical care (n = 8.)
∗ Corresponding author at: Children’s Hospital Colorado, 13123 East 16th Avenue,
B-130, Aurora, CO 80045, USA.
E-mail address: [email protected] (H. Kennedy).
http://dx.doi.org/10.1016/j.aip.2016.05.014
0197-4556/© 2016 Elsevier Ltd. All rights reserved.
Anxiety was shown to be reduced in 50% of the studies; pain in
57%; and analgesic use in 47%. The majority of these studies utilized recorded music through headphones as the intervention, with
a variety of control interventions. For example, Sendelbach, Halm,
Doran, Miller, and Gaillard (2006) randomized 86 patients undergoing cardiac surgery to either resting or music therapy twice daily,
for twenty minutes. Two days after surgery, patients in the music
therapy group reported statistically significant declines in anxiety
and opioid use for pain than those in the control group. While the
quality of studies varies, music therapy appears to reduce pain and
anxiety in the hospital setting, whether the patients undergo normal care or more intense situations, such as surgery. Evans (2002)
reviewed 19 studies on music therapy in hospital settings and suggested that, because of the low cost of music therapy interventions,
music therapy could easily be implemented in more treatment scenarios as an adjunct intervention.
Additionally, music therapy has been examined as a tool for
physical rehabilitation. Two separate reviews of the effects of music
therapy on rehabilitation (Paul & Ramsey, 2000; Weller & Baker,
2011) concluded that it increased the improvements that came
J. Shuman et al. / The Arts in Psychotherapy 49 (2016) 50–56
with regular and consistent physical therapy. In physical rehabilitation, music is used as a motivator to improve range of motion,
gross motor skills, and fine motor coordination. For cardiac rehabilitation, music is used as a distracting and calming tool for patients
dealing with high amounts of pain and discomfort. For patients
with brain injuries, music can help with speech therapy, physical
and occupational therapies; assisting with normalization of muscle
tone, development of movement patterns, and socialization. Thus
current research supports the adjunctive use of music and music
therapy in medical and rehabilitation units.
Some of the benefits of music therapy may also be useful for
patients with psychiatric disorders. Improved motivation, socialization, and ability to calm may all be useful in the treatment of
patients in psychiatric care (McCaffrey, Edwards, & Fannon, 2011).
A Cochrane review identified that four out of five randomized trials
of music therapy for adults with depression significantly reduced
depressive symptoms more than control groups (Maratos, Gold,
Wang, & Crawford, 2008). For symptoms of anxiety, group music
therapy may be an effective intervention when paired with other
types of psychotherapy (Choi, Lee, & Lim, 2008; Albornoz, 2011).
In a quasi-randomized study examining individual music therapy’s
effect on psychotic episodes in adults, participants completed the
Brief Psychiatric Rating Scale before and after individual music
therapy sessions. Ratings on all subscales were statistically different for pre to post treatment for the treatment group, supporting
the use of music therapy as adjunctive to pharmacotherapy with
this population (Morgan, Bartrop, Telfer, & Tennant, 2011).
There is a paucity of literature to support music therapy with
youth. However, the first meta-analysis on music therapy, which
included eleven studies examining music therapy’s impact on children with varied psychopathology (developmental and behavioral
problems), found that music therapy had a medium effect size
(d = 0.61) on reducing behavioral problems and improving general development. These authors recommended that several music
therapy approaches be combined to maximize outcomes (Gold,
Voracek, & Wigam, 2004). One naturalistic research study of 75
children (ages 3.5–19 years of age) with a variety of psychiatric
conditions (29% emotional disorders; 21% behavioral disorders
and 50% developmental disorders) treated by 15 master’s-level
music therapists used standardized parent and therapist assessments at the beginning and after the last music therapy or the 25th
session (whichever came first). This study found that discipline
specific techniques were more effective over non-specific techniques regardless of age or gender, and yielded a medium effect
size in change in symptoms and improvement in adaptation (Gold,
Wigram, & Voracek, 2007). Music therapy has also shown promise
for symptoms of depression and autism. In a randomized controlled study of 19 adolescents receiving individual psychotherapy
or group music therapy for 10 weeks in a school setting, depression
scores, measured by the Beck Depression Inventory, were significantly lower for the music therapy group (Hendricks, Robinson,
Bradley, & Davis, 1999). In a crossover comparison study of ten
boys (mean age 51 months, SD = 12) diagnosed with autism spectrum disorders, music therapy and play therapy were both found
to significantly improve joint attention after 12 weekly sessions
on both the Early Social Communication Scales and observational
session analysis. However, music therapy improved joint attention
significantly more (p = 0.001) than the play therapy condition and
eye contact was present more, yet did not reach significance, within
the music condition (Kim, Wigram, & Gold, 2008).
In addition to music therapy’s effectiveness for general or specific clinical profiles, it is likely to improve communication for
children and adolescents. The American Music Therapy Association
(2015) asserts that music therapy can be a powerful tool for communication. A qualitative study of 16 non-hospitalized bereaving
adolescents who participated in group music therapy found that
51
the groups helped with resilience, identity formation, competence
and connectedness, and also concluded that music therapy may be
a powerful tool for communication (McFerran, Roberts, & O’Grady,
2010).
Like the use of music therapy in medical and rehabilitation settings, music therapy in psychiatric treatment settings is often an
adjunct therapy embedded within a therapeutic milieu in which
patients may also receive traditional psychotherapies and psychopharmacologic interventions. When used as such, it is difficult
to assess the additive benefit of music therapy on such constructs
as communication, emotion regulation, socialization, behavioral
control and insight, as these outcomes are targeted by all of the
therapies. Nonetheless, given the additive benefits for including
music therapy in other health care settings, in 2005 the Department of Psychiatry within a large children’s hospital decided to
add music therapy, as well as other Complementary and Alternative Medicine (CAM) modalities of art, dance, and yoga therapy, to
the multi-disciplinary treatment of children and adolescents with
acute psychiatric symptoms. Several of the immediate goals were
to assist with acute behavioral control, to serve as a creative outlet for expressing authentic emotions, and to improve morale of
milieu staff. Physicians, nurses, therapists and milieu staff on the
unit perceived that integrating CAM into the treatment program
positively impacted patient outcomes, especially in providing positive coping skills and relaxation. Clinicians reported that seclusions
decreased after integrating CAM interventions. Additionally, milieu
staff reported positive personal and professional benefits from participating in CAM therapy sessions alongside patients, providing
evidence for improvement in morale (Kennedy, Reed, & Wamboldt,
2013).
We wished to further assess the impact of each CAM modality,
as well as assess whether one modality, e.g., music therapy, would
be better suited for certain types of patients than others. Given that
this was a clinical setting, randomization was not possible, and documenting the impact of any one intervention within a fast-paced,
multi-interventional, therapeutic milieu was difficult. We hypothesized that one of the ways in which music therapy may mediate
improvement in psychiatric symptoms would be to have an impact
on the acute mood states of the child. While many youth requiring psychiatric hospitalization have high levels of anger, sadness or
anxiety, some also suffer from being cut off from their emotions.
These youth often have psychosomatic disorders such as anorexia
nervosa, but may also suffer from psychosis or dissociative disorders. Inducing an acute change in a mood state may be helpful in
both teaching teens that music therapy could help them modulate a mood state, e.g., anger, as well as help them get in touch
with underlying emotions and start to process them. Beginning
in 2010, adolescent mood states were assessed in a standardized
manner before and after each of these sessions as part of program
evaluation.
In psychiatry and psychology, significant work has concentrated
on emotion and mood in childhood and adolescence. Regulating emotions is a critical skill for successful child development
(Eisenberg et al., 1996) and a primary goal for music therapy
(Moore, 2013). Understanding mood and its effects on learning
and quality of life is becoming increasingly important; current
literature suggests that mood impacts people differently than overall affect, as mood is shorter and more subjectively experienced
(Schwarz, 1987). Between both learning disabled and non learningdisabled middle school students (N = 66), positive moods were
shown to improve learning ability and retention (Bryan, Mathur,
& Sullivan, 1996). Students completed a standardized learning task
involving nouns, verbs, and sentence construction in a novel foreign language. The experimental group experienced self-induced
positive moods by thinking of happy things for 45 s while the control group was asked to count as high as they could in 45 s; students
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J. Shuman et al. / The Arts in Psychotherapy 49 (2016) 50–56
were scored on how well they completed the language tasks and
were re-tested two weeks later to evaluate retention. The learning disabled students showed the most striking results, with the
experimental group scoring significantly higher on both initial and
delayed testing; the non learning disabled group showed improved
test scores with self-induced positive moods on the initial test only,
with no significant difference in delayed test scores. In an article
examining the effects of negative mood on transfer and learning,
two experiments (first experiment N = 54 male students; second
experiment N = 84 students, 45 females and 39 males) were performed to investigate how an induced negative mood might affect
learning ability (Brand, Reimer, & Opwis, 2007). In both experiments, inducing a negative mood was only partially successful,
as this process was affected by the participant’s initial mood; if
the participant reported a positive mood initially, they were less
likely to successfully induce a negative mood state as opposed to a
participant with an initially negative mood. Regardless, the results
of both experiments showed a significant decrease in the transfer
learning abilities of participants with successfully induced negative
moods (p = 0.05). Conversely, in an experiment with undergraduates (N = 109) examining the effect of mood, cognitive style, and
cognitive ability on implicit learning, negative mood significantly
facilitated learning on Artificial Grammar tasks (p = 0.004) (Pretz,
Totz, & Kaufman, 2010). These findings both support and contradict other research in that negative mood did improve learning, but
only on specific tasks that are easier with bottom-up processing.
Mood also affects perception of stimuli and subsequent retention of related materials; in an experiment with college students
(N = 105), mood changed how students perceived various stimuli,
which affected what students retained at a later time (Hettena &
Ballif, 1981). Students with positive moods tended to rate all of
the sentences higher than students with depressed moods, and
students with positive moods liked the positive sentences more
than the negative sentences; this second trend was not seen in the
students with depressed moods. Students then studied the sentences and were asked to recall them at a later time; those who
had reported positive moods learned significantly more material
than those with depressed moods (p = 0.05), suggesting that positive mood states help with retention. These studies highlight the
importance of mood in learning and perception − two important
aspects of treatment goals for psychiatric patients. Therefore, mood
could be an indicator of effectiveness when assessing various forms
of treatment.
Despite the importance of music therapy as a treatment for illnesses, much of the research on music therapy with adolescents
does not evaluate mood change; this illustrates the need for both
qualitative and quantitative research on mood changes of adolescent patients who participate in music therapy.
2. Aims
The primary aim of this research was to examine changes in
mood states of adolescents who participated in music therapy
groups as a brief therapeutic intervention during a psychiatric hospitalization. The secondary aim was to examine whether particular
patients described more mood changes from the group music therapy intervention than others.
3. Methods
This study consisted of retrospective analysis of data collected
for program evaluation, and received approval from the appropriate Institutional Review Board.
3.1. Participants
Patients consist of children and adolescents, ages 12–21 years,
from three psychiatric units in a large children’s hospital who participated in at least one group music therapy session between
August 2010 and March 2013, and completed a standardized mood
assessment before and after the group. The dataset consists of 596
records from 352 patients.
3.2. Music therapy intervention
As part of standard psychiatric care in a large children’s hospital, group music therapy (60–90 min in duration) was provided to
patients on each of three units: Psychiatric Day Treatment (PDT),
Adolescent Psychiatric Inpatient Unit (APU) and Eating Disorders
Unit (EDU). As part of ongoing clinical care, patients completed the
FACE measure before and after each music therapy group, responding to the prompts: “How do you feel right now?” and “How did you
feel during group?” In a group setting, music therapy interventions
are tailored to suit the broad diagnostic categories of each unit, as
well as the day-to-day variance in cohorts within a single unit.
Adolescent Psychiatry Inpatient Unit (APU): Adolescents on the
inpatient unit have been assessed to be a risk to themselves, a
risk to others, or gravely disabled. Common presentations in this
group include, but are not limited to, recent suicide attempts and/or
self-harm, acute anxiety symptoms, active psychotic processes,
personality disorders, and social-adaptation issues that have serious psychosocial effects. This unit has an average length of stay of
about seven days, and all patients are in acute psychological distress. Teens within this program typically present with high levels
of anger, aggression, inability to connect with others, and social
withdrawal. Within this variety of presentations, and the shortterm contact with patients, music therapy directives tend to be
general in their applicability. A common intervention is simply letting patients choose a song that they’d like to listen to, and using
internet-based applications to play any song requested. This openended directive can be adapted in a number of ways. Music listening
can be developed as a coping skill, shared themes among group
members might be explored, or patients might practice making
validating statements about each other’s references.
Psychiatric Day Treatment (PDT): This unit serves a similar population to the inpatient unit, but these patients tend to be less
acute in their presentation. In this phase of treatment, a teen
patient is working to gain perspective on their life, illness, and other
challenges. The lower acuity of patients allows for more uniform
programming. A drum circle, for example, is a common intervention. In general, a drum group encourages the participation of every
individual, while compelling them to attend to others as well. The
purposeful activity involved builds social cohesion and encourages
self-expression, while rhythmic entrainment with a beat tends to
induce a state of calm attention.
Eating Disorders Unit (EDU): A patient on the eating disorder
unit might be working on a number of goals: re-feeding, increasing
parental control over meals, and patients’ intra-psychic process of
dis-identifying from their eating-disordered “voice.” Because this
population tends to display a unique combination of high intelligence with low expressivity, the music therapist’s challenge is
to create a safe space for self-expression, while also providing a
structured means for patients to articulate their perspectives. An
intervention typical to this unit is structured music improvisation.
To explore relational dynamics, the music therapist might structure patients to play together in a number of impromptu ways to
practice identifying habits of communication, nonverbal aspects
of communication, and/or new ways of interacting. The nonverbal qualities of these interventions often allow group members to
J. Shuman et al. / The Arts in Psychotherapy 49 (2016) 50–56
53
Table 1
Participant demographics by unit.
Variable
Overall
APU
PDT
EDU
N
596
%
100%
N
164
%
27.50%
N
195
%
32.70%
N
237
%
39.80%
Age (M ± SD)
Male
Female
15.13 ± 1.88
175
421
29.4
70.6
15.09 ± 1.44
67
97
40.9
59.1
15.2 ± 1.59
75
120
38.5
61.5
15.1 ± 2.31
33
204
13.9
86.1
Race
Hispanic/Latino
Non-Hispanic/Latino
70
526
11.7
88.3
23
141
14
86
20
175
10.3
89.7
27
210
11.4
88.6
Ethnicity
White
Asian
Black/African American
More Than One
Other
482
22
27
27
38
80.9
3.7
4.5
4.5
6.4
117
10
22
3
12
71.3
6.1
13.4
1.8
7.3
160
7
4
20
4
82.1
3.6
2.1
10.3
2.1
205
5
1
4
22
86.5
2.1
0.4
1.7
9.3
Insurance
Commercial
Medicaid
State/Federal
Charity
322
17
243
14
54.0
2.9
40.8
2.3
84
12
61
7
51.2
7.3
37.2
4.3
121
1
72
1
62.1
0.5
36.9
0.5
117
4
110
6
49.4
1.7
46.4
2.5
Primary Diagnosis
Anxiety Disorders
Attention and Behavior Disorders
Eating Disorder
Mood Disorder
Psychotic Disorder
Self-harm
Non-Psychological
Other Psychological
23
6
237
289
31
1
3
6
3.9
1.0
39.8
48.5
5.2
0.2
0.5
1.0
3
1
3
138
18
1
–
–
1.8
0.6
1.8
84.1
11.0
0.6
–
–
20
5
–
151
13
–
–
6
10.3
2.6
–
77.4
6.7
–
–
3.1
–
–
234
–
–
–
3
–
–
–
98.7
–
–
–
1.3
–
reflect on their own and others’ behavior in ways that are nonthreatening to this often self-conscious population.
3.3. Measures
The Fast Assessment of Child Emotions (FACE) is a pictorial measure that assesses 6 distinct mood states: angry, confused, sad,
energetic, anxious and tired. Each mood item is represented by
both words associated with that mood and a recognizable emoticon. (Kennedy, Unnithan, & Wamboldt, 2015). The FACE measure
was developed based off of the Profile of Mood States (POMS),
which has been shown to be a valid and reliable measure of fluctuations in mood of psychiatric and normal adults (McNair, Lorr, &
Droppleman, 1971). Patients are asked to record their mood state
at the beginning and end of each music therapy session. All moods
are rated on a three-point scale: (“not at all” = 0, “a little” = 1 or “a
lot” = 2); the activity item is reverse scored. The Total Mood Score
(TMS) is calculated by adding all of the six mood states. The measure
has shown good validity and reliability (Kennedy et al., 2015).
3.4. Data collection
All completed FACE surveys from the participants of group
music therapy between August 2010 and March 2013 were cleaned
and moved to a Research Electronic Data Capture (REDCap), an
electronic data capture tool hosted at the University of Colorado
Denver. REDCap is a secure, web-based application designed to support data capture for research studies, providing: (1) an intuitive
interface for validated data entry; (2) audit trails for tracking data
manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages;
and (4) procedures for importing data from external sources (Harris
et al., 2009).
From this dataset, Medical Record Numbers (MRNs) were sent to
a Clinical Information Resource Specialist who obtained informa-
tion from the Electronic Medical Record for patient characteristics
of each MRN. Patient characteristics included: age, gender, race,
ethnicity, length of psychiatric hospitalization, psychiatric diagnosis (up to three), psychiatric medications (up to three), insurance
payer type, and treatment unit (APU, ADT, or EDU). In REDCap, FACE
data was linked to the compiled patient characteristic information
by MRN. Once demographic information for a patient was linked
to the appropriate FACE survey(s), the data was de-identified for
analysis.
3.5. Data analyses
Observed data was summarized via summary statistics at both
the patient level and the session level. The primary research goal,
estimation of the probability of change in a mood scale, was
answered using the Generalized Estimating Equations (GEEs) to
fit logistic regression models. Analysis was performed on the log
odds scale and transformed to the probability scale to provide interpretable results in this manuscript. GEEs account for the multiple
FACE sheets from one patient and provided marginal inference,
i.e., population level inference. Statistical analysis was done using
R version 3.0.2 (2013-09-25) (Halekoh, Hojsgarrd, & Yan, 2006).
Statistical significance was set at the 0.05 level.
4. Results
The participants were primarily White, female, and nonHispanic, consistent with the demographics of the patient
population in the clinic. There were more females in the EDU program than the other programs, consistent with the fact that eating
disorders are more prevalent in females than males. Most common
diagnoses were mood disorders and eating disorders. Table 1 contains a summary of the participants, broken up by unit and patient
demographics.
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J. Shuman et al. / The Arts in Psychotherapy 49 (2016) 50–56
Table 2
FACE pre-scores by change or no change.
5. Discussion
FACE Score
Mood
Change
Pre Score 0
Pre Score 1
Pre Score 2
Angry
Yes
No
N
%
N
%
N
%
24
365
6.2
93.8
79
81
49.4
50.6
24
23
51.1
48.9
Confused
Yes
No
24
290
12.1
87.9
80
111
41.9
58.1
34
41
45.3
54.7
Sad
Yes
No
24
275
8.5
91.5
85
133
39
61
33
64
34.0
66
Energetic
Yes
No
91
99
47.9
52.1
86
169
33.7
66.3
49
102
32.5
67.5
Anxious
Yes
No
27
203
11.7
88.3
98
134
42.2
57.8
49
85
36.6
63.4
Tired
Yes
No
59
134
30.6
69.4
121
132
47.8
52.2
69
81
46.0
54
One of the primary aims of the study was to see if adolescents
report a change in their mood states following a group music therapy intervention. Table 2 illustrates the percentages of change or
no change for each mood state, broken up by pre scores.
As can be seen in Table 2, the majority of youth who reported
that they were “not at all” angry, confused, sad or anxious at the
start of music therapy did not change their ratings after the session.
However, almost half of the youth who reported that they had no
energy at the start of the session changed to having “a little” or “a
lot” of energy after the session. Interestingly, of those who reported
they were “not at all” tired at the beginning of the session, 30% rated
themselves as more tired after the session. Conversely, of those who
reported “a lot” of anger, confusion, sadness, and anxiety, between
one third and one half of those reported less of those mood states
after the music therapy intervention.
To test whether specific mood states changed over a music therapy session for the group as a whole, probability of change were
calculated for each mood state, as well as for the Total Mood Score
(TMS). Table 3 reports the estimated probability of a change in
mood score along with 95% confidence intervals for the estimates.
Each of the six individual mood scales have a low probability of a
change, but the probability of a change in total mood score is estimated to be 0.82. The seemingly contradictory results reflect the
nature of the mood measure; any change in any mood state contributes to a change in total mood score. These results suggest that
group music therapy cannot predictably change in a specific mood
for all the participants, but there is a very high chance that some
mood state will change for most participants. Further, participant
characteristics such as age, gender, length of stay, insurance status,
and psychiatric unit did not significantly predict change, based on
pre-session scores.
Table 3
Probabilities of a change in a mood scale by mood state. 95% confidence intervals
are presented (lcl, ucl).
Probability of change
Mood
Total Mood Score
Angry
Confused
Sad
Energetic
Anxious
Tired
Estimate
.82
.21
.26
.24
.38
.30
.41
lcl
ucl
.79
.18
.22
.21
.35
.26
.37
.85
.25
.30
.28
.42
.33
.45
The primary aim of this research was to assess whether group
music therapy sessions had an impact on adolescent mood states.
The 352 adolescents in this study were patients in inpatient or partial hospitalization settings for acute psychiatric conditions, and so
were receiving multiple therapeutic interventions concurrently. It
is difficult to evaluate the effectiveness of one therapy in the midst
of many therapeutic interventions. Thus, this preliminary study
could examine immediate changes in mood states as one measure
of the impact of music therapy.
Since music therapy may be effective in either decreasing perceived negative mood states, or increasing awareness of these
underlying emotional states, the investigators did not place a value
judgment that mood states should change from a negative to a
more positive direction. Understanding the direction of the change
in mood was not the intended outcome of this research. The goal
of music therapy is not simply symptom eradication but emotional state recognition, expression, and self-exploration (Baker,
Gleadhill, & Dingle, 2007; McCaffrey et al., 2011). Thus, the focus of
this research was to investigate overall change in mood as a result
of music therapy to assess one of the above goals.
With this population of highly acute adolescents with severe
psychopathology, most of whom had a negative mood state at time
of admission, the significant probability of a change of any mood
is to be seen as clinically meaningful. Our previous research has
already shown that CAM interventions are able to change mood significantly more than a neutral intervention (Kennedy et al., 2015).
As an intervention within a therapeutic milieu, the ability to effect
change in emotional states within a short span of time seems a
benefit in terms of helping patients identify underlying emotions,
as well as helping patients move out of, or through, problematic
mood states. The generality of the FACE measure does not indicate
which moods are reliably affected, but in diverse milieu groups,
individual patient goals can be very divergent. Group goals tend
to be more general, and the simple finding that mood tends to
be affected suggests a baseline credibility to music therapy interventions, a credibility that, in terms of this measure, may now be
further investigated.
Interestingly, of the individual mood items, fatigue and energy
changed the most. The available research on music as therapeutic
is supportive to the notion that listening to music can significantly impact both fatigue and anxiety (McCraty, Barrios-Choplin,
Atkinson, & Tomasino, 1998). Research with older adults supports
music therapy decreasing fatigue (Ferrer, 2007; Burns, Harbuz,
Hucklebridge, & Bunt, 2001; Horne-Thompson & Grocke, 2008) and
that music therapy can serve as an output for negative energy for
children and adolescents (Jackson, 2003; Montello & Coons 1998).
The secondary aim of this study was to identify any patient
demographics that were influenced more or less by music therapy,
and to assess whether or not it affects any specific mood state more
than others. Patient demographic variables of age, gender, diagnosis, length of hospital stay, psychiatric medication, insurance type,
race, ethnicity, or treatment unit did not have a statistically significant effect on the odds of change in mood state. In this large
sample of adolescents, evidence suggests that music therapy elicits changes in mood states for a diverse range of adolescents with
acute psychiatric conditions.
5.1. Limitations
This was an open observational study, without a control group.
Another consideration was that the surveys were self-report, which
means the data was limited by the self-awareness and cooperation
of the subjects. Using multi-method and multiple sources for data
J. Shuman et al. / The Arts in Psychotherapy 49 (2016) 50–56
collection may be more explanatory, but was unavailable in this
study due to logistics and funding constraints.
The study also faced a few confounding variables when assessing
patient variables that may be associated with change in mood as a
result of music therapy. Gender and primary diagnosis confounded
within the EDU because the population was predominantly female
(86.1%). Medications confounded with unit and primary diagnosis. The population was also predominantly white (81%), thus not a
representative population for all children. Finally, the patient population was acutely ill, so the results may differ in a population of
adolescents in outpatient therapy.
5.2. Future directions
To examine the overall benefit of adding music therapy to a psychiatric hospital setting, one could compare the effects of a music
therapy session to room time, in a randomized controlled fashion.
In addition to self-report measures, it may be possible to have individual therapy sessions scheduled after either the music therapy or
room time session, with the therapist blinded to what the patient
had just received. One could then gather information from the therapist as well about patients’ mood states, and willingness to engage
in therapy and process emotions and thoughts.
This research can also be replicated with adolescents from lower
levels of care, and over a longer period of time, to assess whether
changes in emotional awareness and/or mood states gained from
music therapy are helpful in reduction of psychiatric symptoms.
6. Conclusions
The strengths of this study are the large number of adolescents
who participated, and the use of a standardized assessment tool,
the FACE. Results showed that a group music therapy intervention, from 60–90 min in length, elicited change in the self-reported
mood state of the participants with varied and acute psychopathology. The probability of having a change in mood state is high
(0.82) and statistically and clinically significant. It appeared that the
intervention worked equally well for patients of different genders,
ages, diagnoses and acuity levels. These promising early results
will hopefully support further research into the benefits of music
therapy for adolescents suffering from psychiatric disorders.
Acknowledgements
Special thanks to the Undergraduate Research Opportunity Program and the University Honors and Leadership Program’s Student
Research Fellows Program at The University of Colorado Denver
for their financial support of the student researcher. The study was
also supported by NIH/NCATS Colorado CTSA Grant Number UL1
TR001082. Contents are the authors’ sole responsibility and do not
necessarily represent official NIH views.
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