Jennifer Whipple, MM, MT-BC The Florida State University
This meta-analysis of 12 dependent variables from 9 quantitative studies comparing music to no-music conditions during treatment of children and adolescents with autism resulted in an overall effect size of d=.77 and a mean weighted correlation of r=.36 (p=.00). Since the confidence interval did not include 0, results were considered to be significant. All effects were in a positive direction, indicating benefits of the use of music in intervention. The homogeneity Q value was not significant (p=.83); therefore, results of included studies are considered to be homogeneous and explained by the overall effect size. The significant effect size combined with the homogeneity of the studies, leads to the conclusion that all music intervention, regardless of purpose or implementation, has been effective for children and adolescents with autism. Included studies are described in terms of type of dependent variables measured; theoretical approach; number of subjects in treatment sessions; participation in and use, selection, and presentation of music; researcher discipline; published or unpublished source; and subject age. Clinical implications as well as recommendations for future research are discussed.
Music in Intervention for Children and Adolescents
According to the National Center on Birth Defects and
Developmental Disabilities of the Centers for Disease Control (n.d.), the
incidence of Autism Spectrum Disorders (ASDs) in the United States is not
known. It is clear, however, that the rate of diagnosis of children has
increased in recent years to the point that more than 15,000 3- through
5-year-old children and 78,000 6- through 21-year-old students received
federally funded services during the 2000-2001 school year based on a diagnosis
of autism. This does not include students with ASDs classified by a different
category or receiving regular classroom, private school, or home school
The use of music in assessment of musical and nonmusical
skills has provided insight into individual functioning of children and
adolescents with ASDs. Based on a qualitative analysis conducted by Whipple
(2003) of 11 American assessment studies, information obtained about musical
abilities and preferences as well as other auditory discrimination skills
and responses support the use of music in treatment with this population.
In addition, 29 American studies involving music in treatment were identified,
all demonstrating treatment benefits (Whipple, 2003). Still, additional
analysis may be beneficial in more fully determining the efficacy of music
in the treatment of this population.
Meta-analysis is a set of statistical procedures in
which quantitative research data is compiled, allowing for greater confidence
in conclusions about the efficacy of treatment and making large bodies of
literature more manageable for readers (Johnson, 1989). In the field of
music therapy, meta-analysis originated with examination of music in medical
and dental treatment (Standley, 1986), with multiple updates warranted (Standley,
1992, 1996, 2000) due to the increasing literature base. In addition, music
therapy meta-analyses have been conducted regarding treatment of dementia
(Koger, Chapin, & Brotons, 1999) and premature infant (Standley, 2002),
pediatric (Standley & Whipple, 2003), and psychiatric populations (Silverman,
In an endeavor to further examine benefits of music
in intervention, the present meta-analysis will
contrast the effects of music and no-music conditions on treatment of children
and adolescents with autism.
Criteria for inclusion in this meta-analysis were studies
1) using group or individual subject experimental treatment
2) with design, procedures, and results
allowing replicated data analysis.
3) with subjects who were children or adolescents
diagnosed with autism, eliminating studies incorporating diverse special
education populations regardless of inclusion of students with ASDs;
4) utilizing music as a separate, independent
variable contrasted with a no music control condition;
5) with quantitative results reported with sufficient
information to extract an effect size; and
6) in the form of refereed papers and publications
(i.e., theses, dissertations, journal articles, and poster session presentations)
published or presented in the United States.
Based on accepted meta-analysis process (Johnson, 1989),
an exhaustive literature search was conducted to find all studies meeting
the defined criteria. Next, characteristics and qualities of the collected
studies were identified, described, and coded. Finally, each study/s results
were statistically analyzed and converted to computed effect sizes using
meta-analysis software (Johnson, 1989).
The identification of applicable literature included
searches of the Journal of Music Therapy (1964-present), Music Therapy Perspectives
(1982-1984, 1986-present), Music Therapy (1981-1996), and ProQuest, the
University of Michigan's on-line database of dissertations and theses, (1950-present),
using music and autism or autistic as keywords. Full papers from all relevant
American Music Therapy Association (AMTA) research poster session presentations
from 2002 only were obtained from AMTA. Papers from previous years were
unavailable. Reference lists of all collected published and unpublished
papers were searched, as were the music therapy focus issue of Early Childhood
Connections (Humpal, 2001) and an analysis of music research with disabled
children and youth from 1975 to 1999 (Jellison, 2000).
Of the 29 treatment studies located, 10 studies met
criteria for inclusion in the meta-analysis. An additional study met the
criteria (Wylie, 1996), but was eliminated prior to data analysis as it
was the only study involving children with the ASD of Rett's Disorder, rather
than strictly children with autism. Consequently, the resulting meta-analysis
focused exclusively on treatment for individuals with autism, not ASDs.
The studies meeting criteria are marked with an asterisk in the reference
section and are described in Table 1 in terms of type of dependent variables
measured; theoretical approach; number of subjects in treatment sessions;
participation in and use, selection, and presentation of music; researcher
discipline; published or unpublished source; and subject age. Gender is
not listed since all studies had all or mostly male subjects. This is to
be expected since the rate of autism is four to five times higher in males
than females (APA, 2000). Of the included studies, the earliest was published
in 1976 and 50% were conducted by music therapists. Regarding type of dependent
variables measured, social behaviors were considered to include those such
as self-stimulation and attention to task.
Communication variables included incidences of vocalization,
speech, sign, and eye contact. The category of cognitive skill included
academic tasks, vocabulary acquisition, and following directions for motor
tasks. Included studies are summarized below.
In the category of social behaviors, Brownell (2002) and Pasiali (2002)
explored the use of social stories set to music to reduce challenging behaviors.
Clauss (1994) examined the effect of background instrumental music on the
self-stimulatory behaviors of adolescents when engaged in a computer task.
Wood (1991) measured the frequency of out-of-seat behaviors during mealtime
of children exposed to background instrumental music.
In the communication category, Watson (1979)
explored the use of a token economy system in which tokens received for
spontaneous speech were exchanged for participation in a music therapy session.
Three studies measured overall communicative acts of children: Wood (1991),
when exposed to background instrumental music during mealtime; O'Loughlin
(2000), when exposed to language-based songs; and Wimpory, Chadwick, and
Nash (1995), when provided with several music therapy sessions incorporating
games, movement, singing, and musical accompaniment of activities.
In the category of cognitive skills, Carroll
(1983) examined the effect *of sung versus spoken instruction on the ability
of children to follow instructions to complete a gross motor task. Similarly,
Laird (1997) assessed the effect of sung versus spoken instructions on direction
following and accuracy of geometric shape identification by children and
adolescents. Clauss (1994) measured the response accuracy of adolescents
in completing a computer task when exposed to background instrumental music.
In the only included study utilizing a standardized assessment, Litchman
(1976) used the Peabody Picture Vocabulary Test to measure the vocabulary
acquisition of children and adolescents in background music and no-music
conditions. O'Loughlin (2000) measured the ability of children to accurately
look at and point to stimuli when provided with language-based songs, promoting
picture identification and direction following.
Eighteen additional articles involving music in the
treatment of children and adolescents with autism were evaluated and determined
not to meet study inclusion criteria based on the following factors:
1) studies with insufficient data points for analysis
(Bruscia, 1982; Goldstein, 1964; Griggs-Drane & Wheeler, 1997; Hadsell
& Coleman, 1988; Mahlberg, 1973; Miller & Toca, 1979; O?Connell,
1974; Saperston, 1973; Staum & Flowers,1984);
2) studies without a no-music control condition (Buday,1995;
Edgerton, 1993, 1994; Gore, 2002; Stevens & Clark, 1969);
3) studies in which the music condition could not be
separated from another intervention (Chilcote-Doner,
1982; Hairston, 1990; O?Dell, 1998);
4) a study in which the music and no-music condition
data could not be separated (Rao, 2001);
5) a study
in which music intervention was a constant factor, with different non-music
reinforcement interventions (Schmidt, Franklin, & Edwards, 1976).
In some cases, studies could have been eliminated for
more than one factor,though only the primary factor is cited. One study
(Chilcote-Doner, 1982) eliminated for inability to separate music from other
variables, also could have been eliminated since a recorded drumbeat was
the only form of auditory stimulation included in the study. For this meta-analysis,
the incorporation of both pitch and rhythm were required in order for the
auditory stimulation to be considered music. In another study (Buday, 1995),
eliminated for lack of a clear control condition, used vocabulary signed
and spoken in the rhythm of children?s songs, eliminating only the melodic
element, for the non-music condition. Consequently, this operational definition
of music may be important in future analyses.
Finally, five articles describing treatment techniques
for children and adolescents with ASDs were not included in this analysis
as they did not include quantitative data (Furman, 2001; Hollander &
Juhrs, 1974; Nelson, Anderson, & Gonzales, 1984; Thaut, 1980, 1984;
When selecting variables for analysis, the following
hierarchy was employed:
the single variable with quantitative data was
if more than one variable was
available, the primary variable based on the title of the study or otherwise
identified focus of intervention was selected;
if several variables met that criterion
and all were of the same type of data (e.g., frequency of behavioral observations)
and in the same category of variable measured (i.e., social behavior, communication,
or cognitive skill), the data were combined into one variable;
when it was not possible to select one
variable or combine multiple variables into one measure, the two most important
variables based on the already identified focus of the study were selected,
with a limit of two variables set for each study to avoid disproportional
weighting of studies.
This process resulted in selection of 13 variables from
10 studies. When multiple baseline conditions were reported and conditions
in addition to the extractable music conditions were included in the original
study, data from the baseline condition immediately prior to the music condition,
rather than a mean of the baseline conditions, was used for this meta-analysis
in order to avoid pollution from the other non-music condition. Variables
were converted to an estimated effect size, Cohen's d, using meta-analytic
statistical software (Johnson, 1989).
Listed in Table 2 are the sample size, 95% confidence
interval, and Pearson r and Cohen's d statistics with their probability
for each selected study variable. Effect sizes ranged from .09 to 3.36 with
an overall effect size of d=.83 and a mean weighted correlation of r=.38
(p=.00). Since the confidence interval did not include 0, results were considered
to be significant. All effects were in a positive direction, indicating
benefits of the use of music in intervention with this population. In addition,
the homogeneity Q value was not significant (p=.39), allowing results of
studies to be considered consistent and explained by the overall effect
However, the largest outlier was Wimpory, et al. (1995),
with an effect size (d=3.36) almost two standard deviations larger than
the next highest effect size for Litchman (1976)
(d=1.71). Since Wimpory, et al. (1995) was the only study included with
a sample size of one and was the largest outlier, it was marked for exclusion
from data analysis.
Data reanalysis without Wimpory, et al. (1995) resulted
in an overall effect size of d=.77 and a mean weighted correlation of r=.36
(p=.00). Since the confidence interval did not include 0, results were considered
to be significant. Again, all effects were in a positive direction, ranging
from d=.09 to d=1.71, indicating benefits of the use of music in intervention
with this population. The new homogeneity Q value was even less significant
(p=.83); therefore, results of included studies are considered to be homogeneous
and explained by the overall effect size.
Clinical Implications and Research Recommendations
Meta-analysis of research regarding children and adolescents
with autism reveals that all use of music in treatment with this population
has a relatively high effect. Benefits are not differentiated based on treatment
design, age of subjects, music used, source of research, treatment methodology,
or profession of the music provider.
Prizant, Wetherby, and Rydell (2000) described three
theoretical approaches to intervention with clients with ASDs: discrete
trial-traditional behavioral (DT-TB), developmental social-pragmatic (DSP),
and contemporary applied behavioral analysis (CABA). The first, DT-TB was
most prominent in the 1960s and 1970s. Intervention did not occur in natural
environments based on the theory that clients with autism were unable to
learn in a natural context due to their learning deficits and the limited
quantity of trials and reinforcement available within daily routines. Emphasis
was on teaching speech communication and motor behaviors related to activities
of daily living. All elements were taught through repetitive trials massed
in sets of approximately 100, though current practice supports sets of approximately
10 trials per session. An individual trial included
presentation of the stimulus by the therapist or teacher; client response;
consequence of verbal or primary reinforcement (e.g., food) or of verbal
or physical punishment followed by physical prompting of the correct response;
and a pause before beginning the next trial with presentation of the next
stimulus. Over time, the use of physical punishment was largely eliminated
from research and clinical practice. Research and clinical applications
of DT-TB techniques were first to indicate the ability of individuals with
autism to learn communication and appropriate social skills, but often behaviors did not generalize to other environments and were incompatible with spontaneous and initiated communication (Prizant, et al., 2000).
The DSP model is at the other end of the theoretical
approach continuum. This model developed in the late 1970s and 1980s and
focused on intervention within the context of daily routines and events.
Avoiding exclusive prompting and shaping of responses, teachers, therapists,
and family members were to respond to the child's communicative attempts
within the context of social interaction. The DSP approach emphasizes creation
of motivating contexts, routines, and activities; following the child's
lead; analyzing children's unconventional and early communicative behaviors
for meaning; assisting emotional regulation and expression; establishing
individual goals based on current communicative abilities and learning strengths;
and focusing on meaningful language and functional communication instead
of building larger repertoires of speech and language lacking context and
comprehension (Prizant, et al., 2000).
In between the DT-TB and DSP approaches is CABA, which
began in the 1990s and incorporates the behavioral concepts of reinforcement
for appropriate responses, yet structures intervention for generalization
of skills. In contrast to a DT-TB approach, CABA
allows either client-led or combined therapist- and client-led interactions
to encourage communication initiation, emphasizes activities preferred or
selected by the child, and relies on natural and minimally structured interactions.
Like DSP, the aim of CABA intervention is to facilitate spontaneous communication
and social interaction across settings and situations. Still, definite differences
are apparent between CABA and DSP methods. The CABA approach focuses less
consistently than DSP on the typical language development sequence, focuses
more on measurement of behavioral responses than holistic successful participation,
looks at isolated behaviors more frequently than targeting multiple goals
within one experience, and places less emphasis on development of relationships
and social and emotional expression (Prizant, et al., 2000).
In analysis of music intervention with this population
based on theoretical approach, Whipple (2003) found that the preponderance
of studies most closely fit the DSP approach, though most studies contained
elements of more than one theoretical approach. Still, studies were determined
to be from one approach based on a preponderance of the above defined characteristics
within each individual study. Greatest emphasis was placed on the context
in which treatment occurred, functionality of goals, and evidence of generalization.
Based on categorization determined in Whipple (2003), studies included in
this meta-analysis were spread among the three approaches, with four DT-TB,
four CABA, and four DSP. Based on the non-significant homogeneity Q value,
results of this meta-analysis showed no difference in treatment effect,
whether theoretical approach was DT-TB, CABA, or DSP. This is of importance
since current national research trends support DSP research focused on functional
and spontaneous communication, socialization, play skills, generalization
and maintenance, natural contexts, positive approaches to address problem
behaviors, and functional academic skills (National Research Council, 2001;
Prizant, et al., 2000). The most obvious need revealed by the meta-analysis
process is for studies with quantitative data and non-confounding research
designs, as evidenced by the reduction from 29 identified treatment studies
to only 9 meeting criteria for this meta-analysis. Of those eliminated,
nine were on the basis of insufficient data points for analysis. The elimination
of others without no-contact control or exclusive music conditions was necessary
for the purpose of this meta-analysis, but may not necessarily represent
a gap in the research base in the same way as do those without adequate
Additionally, studies with larger sample sizes are needed.
Several of the studies excluded on the basis of insufficient data were case
studies. Others included were in the form of case studies but with data
presented in such a way that they could be considered as a group of subjects
with a common measured variable (Brownell, 2002; Pasiali, 2002). The largest
samples were found in Litchman (1976) with a between groups design of 10
subjects per group, totaling 20 subjects, and Laird (1997) with a within
subjects design of 13 subjects, each serving as their own control. The total
sample size for the meta-analysis was 76 from the 9 studies included, resulting
in a mean sample per study of 8.44. When calculated for the 12 study variables
included, the sample size rises to 96, but the mean sample decreases to
8.00 per study variable. This is an extremely small sample size in quantitative
Many studies also appear to be in the form of post hoc
analysis of clinical work. This limits the inclusion of these studies in
meta-analysis, as they may have insufficient or no pre-treatment baseline
data. Also, music treatment data may not be able to be extracted from other
intervention variables. In addition, while not necessarily precluding their
inclusion in meta-analysis, these studies often have small sample sizes
and present difficulty in selecting primary variables to analyze due to
global assessment approaches.
The body of literature regarding music in intervention
with children and adolescents with autism reports the following benefits:
increased appropriate social behaviors and decreased
inappropriate, stereotypical, and self-stimulatory behaviors;
increased attention to task;
increased vocalizations, verbalizations,
gestures, and vocabulary comprehension;
increased echolalia, moving toward increased
communication, and decreased echolalic percentage of total utterances;
increased communicative acts and engagement
enhanced body awareness and coordination;
improved self-care skills and symbolic
However, since the meta-analytic process required that
many studies be excluded, only music uses found in Table 1 were supported
in the current study. Additionally, treatment and program descriptions without
quantitative data advocate the use of Orff-Schulwerk techniques (Hollander
& Juhrs, 1974) in addressing a multitude of non-musical therapeutic
goals. Also suggested without data support is learning to sing or play an
instrument to provide long-term benefits for quality of life, self-esteem,
and social acceptance (Nelson, et al., 1984; Toigo, 1992). Several suggestions
regarding the use of music in teaching academic material have also been
made, often based on music therapy treatment and research with broad special
education populations, but need further clarification of the efficacy of
specific techniques for this unique population (Furman, 2001; Thaut, 1980,
1984; Toigo, 1992; Nelson, et al., 1984).
The National Research Council (NRC) (2001) has stressed
the need for integration of the diverse bodies of literature related to
ASDs, encompassing differences based on experimental design, including single-subject
and group experimental, as well as differences based on focus, to include
neurological, behavioral, and developmental aspects. Only two of the 9 studies
included in final analysis, and three of the 10 originally analyzed studies,
were from published sources. Based on the NRC recommendations and to allow
for better access to information, the greatest need at this point in time
appears to be for more published studies regarding the use of music in intervention
with this population.
Most important for music therapists is to be cognizant
that all music intervention has been effective for children and adolescents
with autism. Music appears to be so powerful a tool with this population
that regardless of its purpose or how it is used for a particular client,
it achieves positive effects. However, music therapists have not differentiated
their professional role with this population. The goal of future research,
while addressing the sample size and design clarity deficits already described,
should be to assess the efficacy of specific applications of music in the
treatment of children and adolescents with autism.
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