Music Interventions for ASD Review Article The ...

Music Interventions for ASD

Review Article

The impact of music interventions on verbal communication skills for children with autism spectrum disorders: A systematic review.

SinYee Chuah Clinical and Health Psychology, University of Edinburgh, UK Joanne M Williams Clinical and Health Psychology, University of Edinburgh, UK

Corresponding Author: Joanna M. Williams, Clinical and Health Psychology, University of Edinburgh, Medical School, Teviot Place, Edinburgh, EH8 9AG, UK. Email: [email protected]


Abstract

This systematic review explores the impact of music-based intervention on verbal communication skills among children with ASD. A total of 11 studies were included. Overall, the quality of studies was rated with mean 19.7 out of 28. Majority studies showed significant impact of music on verbal communication among ASD. Verbalmusic interventions were shown to be more appropriate for enhancing expressive language, while music therapy was seem to have impact on overall verbal communication development. Only one study implemented music listening intervention, hence its impact remained inconclusive.

Keywords

Autism spectrum disorder, music intervention, verbal communication, children


Introduction This paper systematically reviews research on impact of music-based interventions on verbal communication skills for children with ASD. Autism spectrum disorder (ASD) is often used as a term to describe a continuum of pervasive developmental disorders (PDD) that include autism, Asperger’s syndrome, PDD-not otherwise specified (PDDNOS). Language communication is one of the triad of deficits among children with ASD and is often the first symptom noticed by parents of children with ASD (Kjelgaard and Tager-Flusberg, 2001; Tager-Flusberg et al., 2005). Children with ASD often experience early delays or absence in language development (Tager-Flusberg et al., 2005). Many parents reported regression of language development in their children with ASD (Kurita, 1985) and this may be specific to ASD (Lord et al., 2004).

Research shows that children with ASD demonstrate impaired in conversational and narrative skills (Tager-Flusberg and Sullivan, 1995). Mixed results have found regarding receptive and expressive language abilities among those with ASD (Allen and Rain, 1992 as cited in Rapin and Dunn, 2003; Bartak et al., 1975; Kjelgaard and TagerFlusberg, 2001; Tager-Flusberg, 1981; Tuchman et al., 1991). Other language patterns such as echolalia, reversing pronouns, and odd intonation patterns are also salient speech characteristics among autism (Tager-Flusberg et al., 2005).


Neurological evidence reveals differences in brain structure and activation that are related to language development in ASD from neurotypical children (Herbert et al., 2002; Rojas et al., 2002). The brain regions that involved in language processing are usually larger in left hemisphere (Petrides, 2013). However, Herbert et al. (2002) found that adolescents with ASD had significantly larger inferior frontal cortex (associated with Broca’s region) in the right hemisphere. Research also suggests differences in activation language areas of the cortex between high-function ASD and normal children (Just et al., 2004). High-functioning ASD children showing significantly less activation in left inferior frontal gyrus, which is related to semantic and syntactic processes. These results explained impairments in producing and processing language among ASD.

Further neurological evidence relating to ASD concerns the mirror neuron system which is proposed to be related to language development (Arbib, 2005; Oberman and Ramachandran, 2007; Rizzolatti et al., 1996). The activation of mirror neurons within the language regions of the brain were proposed to represent the neural basis of understanding motor events (articulatory gestures) and imitating them (Rizzolatti and Arbib, 1998), as well as represent the connection and prerequisite between speaker and listener for communication (Liberman and Mattingly, 1985). Abnormalities of mirror neuron system found in ASD (Hadjikhani at al., 2006) are likely to contribute to communication impairment among those with ASD.


Music and ASD Children with ASD are more responsive to classical music, compared to short sentences and environmental noises (Molnar-Szakacs and Heaton, 2012). Some children with ASD show superior pitch processing (Heaton, 2003; Heaton et al., 2001; Mottron et al., 2000), including those who are not musical savants (Heaton, 2009). These results suggest that many children with ASD possess musical potential that might be used to support language development.

Music form consists of beginning and conclusion, thus applying music within intervention can induces attention and patience in autism by stretching their ability to stay until the end (Berger, 2002). Consistent and repeating rhythmic patterns can be helpful with language development among autism. Breaking down spoken language into rhythmic patterned syllabus, words become simpler to hear and remember for children with ASD and may motivate them to imitate and learn to speak. It has been suggested that tempo relates to auditory memory and cognitive processing. Nevertheless, whether slower tempo of a song provides stronger impact on language development among children with ASD remained unknown. The use of appropriate melodic song with children with ASD may stimulate the desire for speech imitation and induce attention to the emotional content of speech (Berger, 2002).


Activation of brain regions when listening to music provides further understanding of the roles of music for children with ASD. Individuals with ASD showed activation in cortical and subcortical brain regions which were associated with emotion and reward processing, while listening to happy and sad music (Caria et al., 2011). Children with ASD are able to depict affective states and elements in music (Heaton et al., 1999, 2008). It has been suggested that such affective responses in music are mediated by the mirror neuron system (Molnar-Szakacs and Overy, 2006). According to the Shared Affective Motion Experience (SAME) model, the anterior insula formed a “connection” between limbic system and the mirror neuron system, a central network which allows musical signals to be evaluated and creates a sense of shared experience, which results in emotional response to the music (Molnar-Szakacs et al., 2012; Overy and MolnarSzakacs, 2009). Since music can be associated with mirror neuron system, there is the potential to improve language skills that involving mirror neuron system, using musicbased interventions .

Music and language: Underlying processes Both music and language comprise patterns which are governed by combinatorial rules/grammar and principles of hierarchical organization (Molnar-Szakacs and Overy, 2006). “Hierarchical organization is the process of integrating lower-level units to form


more complex higher-level units” (Molnar-Szakacs and Overy, 2006: 236). Such hierarchical organization contains more than one level (Jeannin, 2008). For music, the hierarchical organization involves combinations of units, such as notes, to form chords and scales, follows by forming rhythm, melody and harmony, and then eventually produces overall musical structures. Similarly in language system, speech structure are form from words, phrases, and sentences, which in term formed by combining phonemes, morphemes, and syllables.

Furthermore, individuals engage in similar learning mechanisms for language and music acquisition, such as rules and statistical learning mechanisms (McMullen and Saffran, 2004). According to the rules learning mechanism, individuals were able to learn novel language and music through grammatical rules and cognitive rule respectively (Chomsky, 1959; Narmour, 2000). The fundamental idea was to discover the underlying structure by abstracting away from the elements in past experiences. The statistical learning in language suggested that learners discovered structure by detecting sound patterns, words, and the beginnings of grammar (Saffran, 2003a). Listeners were able to use statistical properties of the syllable sequences to find the word boundaries (Saffran et al., 1996). Similar statistical learning mechanism was used for discovering musical tones. Listeners were able to determine boundaries of tone words by tracking the familiar absolute pitch (Saffran, 2003b).


In addition, several studies have shown overlapping neural responses to music and language stimuli (Koelsch et al., 2005; Ozdemir et al., 2006; Schön et al., 2004). Using fMRI technique, Ozdemir et al. (2006) found overlapping of activation pattern in bihemispheric regions for vocal production. There are also studies that indicated overlap of neural resources between the processing of musical and linguistic syntax (Koelsch et al., 2005), as well as pitch contour processing during sentences and melodies listening task (Maess et al., 2001).

The present study Whipple (2004) conducted a meta-analysis of 10 quantitative studies of any design to examine the efficacy of music treatment in ASD on social behaviors, communication and cognitive skills. Results indicate positive effects of the use of music in intervention for children and adolescents with ASD. However, important details such as study design and randomization were not reported in this review. Moreover, the selected studies were mainly unpublished manuscripts and the interventions used were heterogeneous, ranging from background music to music therapy.

A Cochrane systematic review was conducted to examine the effect of music therapy for children with ASD on behavioral problems, gestural and verbal communication


skills (Gold et al., 2006). The selected three studies were RCT or controlled clinical trials with four to ten participants aged 2 to 9 years old. The review suggested positive effects of music therapy on gestural communication skills (medium effect size, SMD=0.50) and verbal communication skills (smaller effect size, SMD=0.36). Compared to the previous review, the Cochrane review provided thorough and transparent information regarding search procedure, design type, outcome assessment, intervention, and results.

Unlike previous reviews, this paper focuses the effect of music-based intervention specifically on verbal communication skills on children with ASD. This review aims to investigate not only the effect of music therapy that is delivered by professionals, but also interventions that use music as speech teaching tools, as well as auditory integration therapy (filtered music listening). This paper will provide a systematic and synthetic evaluation of the qualities of the studies reviewed.

Research Questions: 1. Are there positive impacts of music-based interventions on verbal communication skills among children with ASD?


2. Which types of music-based intervention are most suitable to enhance expressive language, receptive language and decrease autism verbal symptoms among children with ASD?

Methodology The guidelines from Centre for Reviews and Dissemination (2009) and Cochrane Handbook for Reviews of Interventions (Higgins and Green, 2011) were used in present review for the literature search. The literature search was carried out between January to June 2014.

Inclusion and exclusion criteria Types of studies. The present review used only studies with primary data including: Randomized controlled trials (including repeated measures design) and single-subject study (i.e. AB design and reversal design). No publication date restriction was adopted but the review only included English language studies. Studies that were inaccessible in full text were excluded.

Types of participants. Studies with children of aged 3 to 12 years were included. This age range was selected because early intervention is important and is believed to be more beneficial for young ASD children. Studies with participants above 13 years old


were excluded because individuals above 13 years old were classified as adolescents (Erikson, 1950). Also, studies with wider age range (eg. 3 to 17 ages) were excluded if more than 50% of the participants are above 13 years old. Participants included were children with diagnostic of Autistic Disorder, Asperger syndrome and Pervasive Development Disorder Not Otherwise Specified as defined in DSM-4, ADOS-G or CARS. Children with diagnostic of Rett’s disorder or children disintegrative disorder (CDD) were excluded due to the different diagnostic’s clinical trajectories (Patterson et al., 2012).

Types of interventions. Studies that used music as an intervention tool including (a) music therapy, (b) verbal-music intervention, and (c) music listening.

Types of outcome measures. Studies with verbal communication skill as primary or secondary dependent variable were included. Verbal communication skills were defined as expressive language (e.g., novel words production, verbal imitation, verbal response to questions, or making requests); receptive language (e.g. following given instructions or identifying target words); or autism verbal symptoms (e.g. irrelevant/inappropriate speech) (Ramdoss et al., 2010). No restriction to specific measurement tools were implemented, due to a wide range of validated measurement tools available.


Information sources and search terms Thirteen databases were used for searched:

•

RILM Abstracts of music literature;

•

Social Sciences Citation Index;

•

Medline;

•

OAlster;

•

CINAHL Plus;

•

ERIC;

•

FRANCIS;

•

Academic OneFile;

•

SocINDEX;

•

Science Citation Index;

•

Science Direct;

•

Arts and Humanities Citation Index;

•

British Library document supply centre inside serials and conference proceedings.

Five main search variables were used for searching trials: music, intervention, autism, children, and communication. For each variable, synonyms and possible keywords were identified. All search terms were combined and inserted into the keywords field:


(musi* OR melodi* OR auditory OR improvisation* OR song*) AND (intervention OR therapy OR treatment OR training) AND (autis* OR asperger* OR ASD OR pervasive developmental disorder OR PDD-NOS) AND (children OR child OR young*) AND (communication OR language OR speech OR expressive OR receptive OR verbal)

Data extraction Identified studies were first assessed for inclusion or exclusion and selected studies were summarized by author based on a modified data extraction form (Centre for Reviews and Dissemination, 2009). Abstracted data included:

a) General information (e.g. author, year of publication); b) Study characteristics (e.g. aim of the study, study design, and allocation); c) Participant characteristics (e.g. sample size, age, gender, and diagnosis); d) Measurements (e.g. relevant measurement tools, measurement category, measurements validity and reliability, and inter-rater/ inter-observer reliability); e) Intervention (e.g. description of intervention and control, duration, materials used, number of participants in the each condition, and follow up); f) Results (e.g. statistical technique used, statistical results, p-value, and effect size); and


g) Conclusion reported.

Quality assessment The quality assessment was based on the guidelines of Cochrane Handbook for Reviews of Interventions (Higgins and Green, 2011), CONSORT 2010 checklist (CONSORT, 2014), and the RCT of Psychotherapy Quality Rating Scale (Kocsis et al., 2010). A domain-based evaluation from Cochrane and scoring system from the RCT of Psychotherapy Quality Rating Scale were adopted and modified to create a new scale which suitable for the present systematic review. Scoring system was applied to provide a systematic empirical method for evaluating overall quality of the selected studies (Kocsis et al., 2010). The modified scale contained 6 domains and a total of 14 items (see Table 1).

The items generated were compared with CONSORT 2010 checklist and the RCT of Psychotherapy Quality Rating Scale to ensure the quality of both reporting and implementing the intervention were being assessed. Short description and 3-level scores with requirements were provided for each item. A score of 2 indicated well-covered, well-described and well-implemented of an item. A score of 1 indicated adequately addressed or implemented an item. A score of 0 indicated poorly addressed, not addressed, or not relevant for an item (Kocsis et al., 2010). The total score of the


assessment is 28. A detailed description of the assessment scale was provided in Appendix 1.

Table 1. Assessment domains and items. Domains

Items 1. Specific and relevant aim or hypothesis

Study design 2. Adequate control group or comparison group 3. Documentation the reliability of diagnostic Description of methodology participants 4. Justification and adequate sample size 5. Relevant outcome measure Intervention

6. Intervention (including control group or comparison group) with sufficient details for replication 7. Relevant outcome measure 8. Validated measuring tools.

Outcome

9. Follow-up Assessment

measures

10. Rater or observer blinded to treatment group or aim of the research and with established reliability (e.g. inter-rater reliability, inter-observer reliability, intra


class coefficient)

11. Appropriate statistical test with p-value Data analysis 12. Effect size 13. Conclusion of study and relationship between music and verbal communication Discussion 14. Addressing limitation and recommendation for future study

Results Study selection A total of 511 studies were identified at the initial phase. After reviewing the title of 511 studies, 460 studies were excluded. The abstract of the remaining 51 studies were reviewed based on the inclusion and exclusion criteria. 25 studies were further excluded. The full text of the 26 studies were downloaded and reviewed in details. Of these, 15 studies were excluded and 11 studies (2.15% of the total initial search) met the inclusion criteria and were included for the present systematic review. The specific reasons for exclusion of the 15 excluded studies were listed as Appendix 2. The


references from the 11 selected studies were reviewed, but no other relevant papers were emerged. The flow of the selection process was shown as Figure 1.


511 studies identified through

Excluded (n=460):

database searching search. Titles

Duplication, n=254

were screened.

Theoretical/review paper/not relevant study, n=167 No music component, n=27 No relevant measurement, n=17 Not ASD, n=8 Case study, n=4 Not children, n=2 Not in English, n=1

51 abstract were reviewed. Excluded (n=25): Theoretical/review paper/not relevant study, n=12 Not music therapy, n=5 Case study, n=3 No relevant measurement, n=2 26 full text studies were

Wide age range, n=2

retrieved and assessed.

Not children, n=1

Excluded (n=15): Not music therapy/no music element, n=5 No relevant measurement, n=4 Case study, n=2 Wide age range, n=2 Not in English, n=1 11 studies included in the review.

Figure 1. Flow chart of selection process.

Review paper, n=1


Characteristics of the studies See Appendix 3 for the summary of the following characteristics of the studies.

Participant characteristics. There were notably small sample sizes ranging from 5 to 50 participants across all studies. Six studies recruited less than 12 participants. Target population was children aged from 3 to 12 years old, with only one study (Gattino et al., 2011) recruiting children up to 12 years old (Mean age=9.75 years). Seven studies reported participant gender, with predominantly male participants. All of the participants were diagnosed with autism. Only one study (Gattino et al., 2011) specifically addressed the inclusion of PDD-NOS and Asperger. Three studies conducted an independent diagnosis assessment to confirm participants’ ASD diagnostic.

Study design. The most common designs were randomized controlled trials (n=8). Among these eight studies, three studies implemented repeated measures design. The other three studies were single-subject design, with only one study (Edgerton, 1994) using reversal design (A-B-A) and two other studies (Dezfoolian et al. , 2013; Wan et al., 2011) using a simple pre-post design. Only one study (Wan et al., 2011) included follow-up measurements at week 4 and week 8. Majority studies (n=8) included at least one comparison group.


Intervention. Different types of music-based interventions were implemented across 11 studies: music therapy, verbal-music intervention, and music listening. (See Appendix 4 for details.)

“Music therapy” are music-based interventions that are primarily based on musical activities such as instruments playing, singing, movement to music, and musical games. This type of intervention was implemented in four (36.4%) of the selected studies. Although these interventions were created by different researchers or therapists with different guidelines, the fundamental principle was to improve ASD children’s behaviors through instrument playing and musical activities. Three of these studies applied non-directive and improvisation approach (Edgerton, 1994; Gattino et al., 2011; Thompson et al., 2013), whereas one study applied a music education approach (Dezfoolian et al., 2013).

“Verbal-music intervention” is verbal communication training which incorporated music in teaching target words and phrases. Six (54.5%) of the chosen studies implemented such intervention in attempt to enhance ASD children’s verbal communication skills. Five studies used selected target words or phrases as part of the lyrics of the chosen song (Buday, 1995; Lim, 2010; Lim and Draper, 2011; Sandiford et


al., 2013; Simpson et al., 2013). Wan et al. (2011) was the only study that intoned (sung) the target words in two pitches while tapping the drums, which were tuned to the same pitches.

“Music listening” is defined as a sound based therapy that incorporate forms of music therapy by providing high and low frequency filtered music for children. Only one selected study implemented this type of intervention (Corbett et al., 2008). Throughout the therapy sessions, children listened to prepared auditory stimulation recordings (e.g. Mozart music and Gregorian chants) through an “Electronic Ear” with different level of frequencies.

Targeted outcomes. Three target verbal communication skills outcomes were reviewed: expressive language, receptive language and autism verbal symptoms. Overview of key findings and measurement tools were summarized in Appendix 5.

Expressive language was defined as various types of speech productions, such as making request, answering questions, verbal imitation, novel words production, and greetings. Eight studies included expressive language as one of the targeted outcomes. Overall, mixed results were shown in these eight studies. Due to the variety of expressive languages, different types of measurement tools were used in each study.


Trained words production. Three studies (Lim and Draper, 2011; Lim, 2010; Wan et al., 2011) that showed significant results, measured verbal production according on specific criteria such as semantics, phonology, pragmatics, prosody and phoneme. Wan et al. (2011) further suggested that the improvements were maintained after 4 weeks and 8 weeks. However, Wan et al. (2011) results cannot be confidently contributed to the effects of intervention due to the lack of comparison groups and no effect sizes were reported. In contrast, Sandiford et al. (2013) reported non-significant results based on scoring correct trained word production which can be argued that children with ASD required more practice time to produce the trained words correctly. However, the same study suggested participants who experienced music-based intervention scored significantly higher in producing nonsensical and little resemblance to the target words.

Verbal initiation. Sandiford et al. (2013) showed improvement of verbal initiation in term of producing novel words in home setting, yet it was not related to treatment conditions. Thompson et al. (2013) also showed no different results with or without family-centered music therapy. Expressive language in these two studies were measured via identifying words that used in daily life by parent-rated assessments which may have biased results. On the other hand, Edgerton (1994) suggested improvement of overall communicative behaviors, yet the study only statistically analyzed positive


correlation of musical behaviors and non-musical speech production. Analysis did not investigate treatment effect on children’s speech production.

Verbal imitation. Two studies measured the effect of music-based interventions on verbal imitation (Buday, 1995; Sandiford et al., 2013). Measurement of verbal imitation was more lenient as verbal imitation was scored for any imitative attempt during the intervention. Despite the slight differences in outcome measurements, both studies suggested better verbal imitation in the experimental group compared to the control group.

Verbal production based on pictures. Corbett et al. (2008) was the only study that measured expressive language by assessing participants’ single word production to pictures. The study showed overall improvement of expressive language but there were no significant differences between experimental group and placebo. Such results might due to the inappropriate used of outcome measurement tool for children with ASD as it required higher cognitive competency to complete the task. To be able to produce correct answer to each picture, participants required not only speech production capabilities, but also previous learning experience and higher level of cognitive skills as they were required to retrieve words from memory. Without previous learning of the


words and meaning, they were not able to provide correct answers even the participants were able to speak.

Receptive language was defined as understanding languages demonstrated by following or responding to instructions. Three studies examined impact on receptive languages differently. Corbett et al. (2008) measured receptive language by requesting children to select correct pictures based on daily used vocabulary (PPVT, Dunn and Dunn, 2007) and reported an improvement of receptive language in all participants, regardless treatment or placebo condition. Simpson et al. (2013) suggested music-based intervention enhanced children engagement in completing the task, and hence increased the correct labelling pictures of spoken words. Yet the statistical analysis did not investigate differences between treatment groups, as well as the cause and effects of music on receptive language. Thompson et al. (2013) used a parent-rate measurement to identify children’s vocabulary comprehension after intervention and suggested no significant improvement between children receiving with or without family-centered music therapy, but the result was inconclusive due to the weak control group (all subjects continue attending personal intervention therapy) and possible performance bias among parents. Due to the lack of robust methodology, it is hard to make confident conclusion regarding the effects of music-based intervention on receptive language among children with ASD.


Two studies measured reduction of autism verbal symptoms to show the effects of

music-based intervention on ASD children’s verbal communication skills. Gattino et al. (2011) suggested both treatment conditions showed reduction in autism verbal symptoms, but this result did not significantly favor to music-based intervention. One possible reason for the finding might be the inappropriate assessment tool as the initially purpose of CARS was to diagnose the presence or absence of ASD and its severity. In contrast, Dezfoolian et al. (2013) suggested music-based intervention reduced autism verbal symptoms. However, the finding remained inconclusive due to the absent of control group and small sample size (n=5).

Synthesis of key findings This section focuses in exploring the relationship between the type of music-based interventions and the type of targeted outcomes (See Appendix 6 for the overview).

Five studies examined the effect of verbal-music interventions on expressive language among children with ASD. Although the interventions consisted of different concepts across studies, the findings were more inclined towards positive effect of music on expressive language. There were two studies that implemented music therapy to examine the effect of music on expressive language but showed contradictory results.


The main different was the collaboration between parents and therapists and active participation of parents within Family-centered Music Therapy (Thompson et al., 2013). Only one study examined the effect of music listening intervention on expressive language among children with ASD. Due to the lack of studies available, the effect of music therapy and music listening intervention on expressive language remained inconclusive.

For receptive language results are inconclusive. All three studies implemented different music-based interventions.. Although the studies inclined towards non-significant results, there was only one study for each intervention, different measurement tools, and methodological weaknesses.

Looking at the only two studies that examined the effect of music-based interventions on autism verbal symptoms, both studies implemented music therapy and showed contradictory results. These two interventions differed in using planned program and improvised activities respectively. Apart from that, Gattino et al. (2011) utilized comparison group and more participants (n=24) compared to Dezfoolian et al. (2013) that utilized single pre-post study design and few participants (n=5). . If investigators utilized comparison group and larger samples in replicating Dezfoolian et al. (2013), the results might be similar to Gattino et al. (2011).


Quality Assessment All papers were assessed for quality by the author of the present review. A second coder was enlisted in order to obtain inter-judge reliability scores for quality assessments. Four papers (36%) were randomly selected through generating random numbers via Microsoft Excel RANDBETWEEN function. A calculation of inter-rater reliability was made using Cohen’s Kappa via IBM SPSS Statistic 22. The result obtained was Kappa=0.587 (p=.000). Disagreements were discussed and adjustments to coding scheme made.

Papers were rated between 17 (60.7%) to 25 (89.3%), with the mean of 19.7 (70.4%) out of 28. Most studies used a small sample size and no follow up was implemented, hence showing low generalization and maintenance effect. Also, the information of diagnostic methodology, measurements, results and discussion were limited. For example, diagnostic tools, reliability and validity of the measurements, relationship between the music and communication were not reported; as well as low effect size or no effect size was implemented. In contrast, the strongest study (Lim, 2010) scored 25 out of 28, suggesting strong methodology and thorough report.


Although all selected studies scored above 60% quality score, there were some important and consensus limitations. Firstly, eight studies showed small sample size, only one study (Lim, 2010) recruited more than 50 participants. Secondly, only one study (Wan et al., 2011) implemented follow up. Without implementing follow up, the studies are unable to suggest the maintenance effects of music-based intervention. Lastly, low effect size or no effect size was reported in majority of the studies. Therefore, it is hard to make conclusive conclusions of the effect of music-based intervention on verbal communication among ASD. Appendix 7 summarized the individual item grading for each study.

Discussion The purpose of this paper was to review the effects of music-based interventions on verbal communication skills among children with ASD. Music-based interventions were categorized into three types: music therapy, verbal-music intervention; and music listening. Outcome measures were divided into three types: expressive language, receptive language; and autism verbal symptoms.

Positive impacts of music-based interventions on verbal communication skills among ASD were found, but not all studies showed statistically significant results. Verbalmusic interventions were shown to be more appropriate for enhancing expressive


language, while music therapy was seem to have impact on overall verbal communication development. Only one study implemented music listening intervention, hence its impact remained inconclusive. Overall, the quality of studies was rated with mean 19.7 out of 28. The existing studies mainly demonstrated weak methodology in term of small sample sizes and no follow-up. Although the impact of music on communication skills among ASD remained debatable and more robust studies were needed, this impact should not be overlooked.

The findings contrast with Whipple (2004) who concluded high effectiveness of music intervention for children with ASD. There are two main differences between the two reviews. First, the target outcome of the two reviews was different. Whipple (2004) focused on cognitive skills, social behaviors and communication, and only 4 out of 10 studies measured communication. Second, the type of analysis review used was different. Whipple (2004) was a meta-analysis, whereas this paper is a systematic review. The two reviews use different assessment tools to analyze the impact of musicbased interventions for children with ASD.

Gold et al. (2006) concluded significant effect of music therapy on verbal communication. However, limited data was available in the review as studies that


implemented other than RCT study designs and other music interventions were excluded. This review differs from Gold et al. (2006) within these two areas.

This review suggests that verbal-music interventions are most appropriate for enhancing expressive language in children with ASD. It also suggested that children with ASD were able to produce language by learning how to speak with the help of music. Furthermore, these results support that there are overlapping neural responses to music and language stimuli (Koelsch et al., 2005; Ozdemir et al., 2006; Schön et al., 2004), hence children with ASD are able to learn to speak much easier with combination of music and speech training. In verbal-music interventions, words are combined with rhythmic patterns and become simpler for children with ASD to learn because the words had form a chunk pattern which related to gestalt language acquisition among ASD. The results further support the argument regarding music activates the brain regions which contain mirror neuron system (Overy and Molnar-Szakacs, 2009), and hence enhance the imitation abilities (Rizzolatti and Arbib, 1998) when the children with ASD are experiencing speech training.

The studies reviewed that implemented music therapy, examined the impact of music in all three types of verbal communication among children with ASD. However, consensus is difficult to draw from the mixed findings. In music therapy, music stimulations come


from various types of activities which involve multi-sensory activation. While children with ASD experiencing music therapy, individuals involve in playing music instruments (motor), listening to music (auditory), singing (speech), music games (social) and more. Music therapy may be appropriate for overall development of children with ASD, including behavioural problems and social interactions, rather than in verbal communication only.

Lastly, only one selected study implemented music listening intervention. The study measured both expressive language and receptive language; and showed little or no impact of music in language development among ASD. Based on the similarities underpinning processes between music and language, music listening intervention should have impact on verbal communication among ASD. However, limited data is available on the impact of listening to filtered music on verbal communication. In contrast with the findings, other studies showed different benefits of listening to filtered music for children with ASD, such as decreased repetition behaviours, improved attention, and decreased irritability (Bettison, 1996; Rimland and Edelson, 1995). Therefore, more future studies are needed.

Strengths and contributions


This paper differs from other reviews in terms of the range of interventions, study designs and outcomes reviewed. The inclusion of three possible music-based interventions in current review, allows investigators to understand the effects and differences across the existing music-based interventions, as well as provides more comprehensive findings regarding the effect of music on verbal communication skills among ASD.

Only Gold et al. (2006) and this review adopt a quality assessment procedure. The findings (M=20) of this paper indicate moderate quality of studies, and raise the awareness of limited robust research and the problem of generalization and maintenance effects of the existing evidences which due to methodological shortcomings. Also, additional rater for quality assessment in current review reduces performance bias. Although the second rater only assessed four studies (38.4%), different perspectives are important to provide higher reliability of assessment.

Limitations and future studies There were few factors that influenced the selection of relevant studies for the present review. Due to the restriction in translation and resources, inclusion of only English language and full text publications might reduce the validity of the findings. Grey literature was also excluded from this review which can lead to exaggerated estimates of


intervention effectiveness because of excluding vital evidences (McAuley et al., 2000). Hence, it is important to include grey literatures in the future to minimize publication bias and inaccurate findings (Cochrane Corner, 2007). Selection bias cannot be overlooked due to only one reviewer was involved throughout the searching and screening procedure. Addition reviewer might provide reassurance for the selection studies. Furthermore, second rater only assessed four random studies for quality assessment due to time restriction, and hence results in low inter-rater reliability. If feasible, all selected studies should be assessed by second rater to enhance the reliability of the quality assessments.

One of the major limitations of the existing studies is small sample size within most of the studies. The lack of adequate sample size raises the problem of generalization and inaccurate interpretation of findings. Hence, researchers should recruit larger samples in future studies. Besides that, the existing studies are not able to provide information regarding the maintenance effects of the intervention, which due to the lack of followup within the studies. Longitudinal designs with sufficient follow-up are highly recommended in future studies. Language skills are associated with severity of ASD and IQ yet only few studies measured and reported participants’ autism severity and IQ, and they were not used as covariate for statistical analysis. In addition, language age of the participants should not be neglected, as differences in language age may influences


the effectiveness of intervention on language learning development among ASD. It is important that investigators include autism severity, IQ level and language age as covariates in future studies to evaluate true treatment effects.

Although most of the studies used validated outcome measures, these were not standardized across studies. Different types of measure tools were used to examine same outcome across studies, hence mixed findings were shown. In order to find consistent effectiveness of intervention, investigators should use standardized and validated outcome measures in future studies. Apart from that, it is important to further explore participants’ verbal attempts and the usage of novel words they learnt in different setting. Therefore, investigators should include assessments from home setting to explore the impact of interventions in different setting. Moreover, although the existing studies could be categorized into three groups), interventions with different guidelines, durations and number of sessions were used within the categories. Such differences should not be neglected and they may affect the overall findings of musicbased intervention, thus more future studies with same interventions with standards methodology should be conducted. In addition, there is a growth of music-based intervention implementation across the world, yet most of the existing studies were done in USA, UK and Australia. Future studies with samples of different nationalities


should explore the effect of music-based intervention on autism verbal communication skills across cultures.

Conclusion The findings suggested that verbal-music interventions are more appropriate for expressive language development, while music therapy is more likely to have impact on overall verbal communication development among children with ASD. The impact of music listening intervention remains inconclusive. While the studies show a significant impact of music the studies were rated low on quality with a mean score of 19.7 out of 28. More robust and rigorous studies are needed in the future.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

References

Arbib MA (2005) From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics. The Behavioral and Brain Sciences 28(2): 105–124. Bartak L, Rutter M and Cox A (1975) A Comparative Study of Infantile Autism and Specific Developmental Receptive Language Disorder: I. The Children. The British Journal of Psychiatry 126(2): 127–145.


Berger DS (2002) Music Therapy, Sensory Integratioin and the Autistic Child. London and Philadelphia: Jessica Kingsley Publishers. Bettison S (1996) The long-term effects of auditory training on children with autism. Journal of Autism and Developmental Disorders 26(3): 361–374. Buday EM (1995) The Effects of Signed and Spoken Words Taught with Music on Sign and Speech Imitation by Children with Autism. Journal of Music Therapy 32(3): 189–202. Caria A, Venuti P and De Falco S (2011) Functional and dysfunctional brain circuits underlying emotional processing of music in autism spectrum disorders. Cerebral Cortex 21(12): 2838–2849. Centre for Reviews and Dissemination (2009) Systemetic Reviews: CRD’s guidance for undertaking reviews in health care. York: CRD, University of York. Chomsky N (1959) A review of B. E. Skinner’s verbal behavior. Language 35: 26–58. Cochrane Corner (2007) Finding studies for inclusion in systematic reviews of interventions for injury prevention: The important of grey and unpublished literature. Injury Prevention 13(2): 359. CONSORT (2014) CONSORT 2010 checklist. Available at www.consortstatement.org/consort-statement/checklist (accessed 14 June 2014). Corbett BA, Shickman K and Ferrer E (2008) Brief report: The effects of Tomatis sound therapy on language in children with autism. Journal of Autism and Developmental Disorders 38(3): 562–566. Dezfoolian L, Zarei M, Ashayeri H, et al. (2013) A pilot study on the effects of OrffBased Therapeutic Music in children With autism spectrum disorder. Music and Medicine 5(3): 162–168. Dunn LM and Dunn DM (2007) Peabody Picture Vocabulary Test, Fourth Edition (PPVTTM-4). Available at www.pearsonclinical.com/language/products/100000501/peabody-picturevocabulary-test-fourth-edition-ppvt4.html?Pid=PAa30700#tab-pricing (accessed 11 June 2014).


Erikson EH (1950) Childhood and society. New York: Norton. Edgerton CL (1994) The effect of improvisational music therapy on the communicative behaviours of autistic children. Journal of Music Therapy 31: 31–62. Gattino GS, Riesgo RDS, Longo D, at el. (2011) Effects of relational music therapy on communication of children with autism: A randomized controlled study. Nordic Journal of Music Therapy 20(2): 142–154. Gold C, Wigram T and Elefant C (2006) Music therapy for autistic spectrum disorder (Review). Cochrane Database of Systemetic Review (2): 1–23. Hadjikhani N, Joseph RM, Snyder J, et al. (2006) Anatomical differences in the mirror neuron system and social cognition network in autism. Cerebral Cortex 16(9): 1276–1282. Heaton P (2003) Pitch memory, labelling and disembedding in autism. Journal of Child Psychology and Psychiatry, and Allied Disciplines 44(4): 543–551. Heaton P (2009) Assessing musical skills in autistic children who are not savants. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 364(1522): 1443–1447. Heaton P, Allen R, Williams K, et al. (2008) Do social and cognitive deficits curtail musical understanding? Evidence from autism and Down syndrome. British Journal of Developmental Psychology 26(2): 171–182. Heaton P, Hermelin B and Pring L (1999) Can children with autistic spectrum disorders perceive affect in music? An experimental investigation. Psychological Medicine 29(6): 1405–1410. Heaton P, Pring L and Hermelin B (2001) Musical processing in high functioning children with autism. Annals of the New York Academy of Sciences 930: 443–444. Herbert MR, Harris GJ, Adrien KT, et al. (2002) Abnormal asymmetry in language association cortex in autism. Annals of Neurology 52(5): 588–596. Higgins J and Green S (2011) Cochrane handbook for systematic reviews of intervention. Available at handbook.cochrane.org/ (accessed 9 June 2014).


Jeannin M (2008) Organizational structures in language and music. The World of Music 50(1): 5–16. Just MA, Cherkassky VL, Keller TA, et al. (2004) Cortical activation and synchronization during sentence comprehension in high-functioning autism: Evidence of underconnectivity. Brain : A Journal of Neurology 127: 1811–1821. Kjelgaard MM and Tager-Flusberg H (2001) An investigation of language impairment in autism: Implications for genetic subgroups. Language and Cognitive Processes 16(2-3): 287–308. Kocsis JH, Gerber AJ, Milrod B, et al. (2010) A new scale for assessing the quality of randomized clinical trials of psychotherapy. Comprehensive Psychiatry 51(3): 319–324. Koelsch S, Gunter TC, Wittfoth M, et al. (2005) Interaction between syntax processing in language and in music: An ERP Study. Journal of Cognitive Neuroscience 17(10): 1565–1577. Kurita H (1985) Infantile Autism with speech loss before the age of thirty months. Journal of the American Academy of Child Psychiatry 24(2): 191–196. Liberman AM and Mattingly IG (1985) The motor theory of speech perception revised. Cognition 21(1): 1–36. Lim HA (2010) Effect of “developmental speech and language training through music” on speech production in children with autism spectrum disorders. Journal of Music Therapy 47(1): 2–26. Lim HA and Draper E (2011) The effects of music therapy incorporated with applied behavior analysis verbal behavior approach for children with autism spectrum disorders. Journal of Music Therapy 48(4): 532–550. Lord C, Shulman C and DiLavore P (2004) Regression and word loss in autistic spectrum disorders. Journal of Child Psychology and Psychiatry, and Allied Disciplines 45(5): 936–955. Maess B, Koelsch S, Gunter TC, et al. (2001) Musical syntax is processed in Broca’s area: An MEG study. Nature Neuroscience 4(5): 540–545.


McAuley L, Pham B, Tugwell P, et al. (2000) Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses? Lancet 356: 1228–1231. McMullen E and Saffran JR (2004) Music and language: A development comparison. Music Perception: An Interdisciplinary Journal 21(3): 289–311. Molnar-Szakacs I, Assuied VG and Overy K (2012) Shared affective motion experience (SAME) and creative, interactive music therapy. In Hargreaves DJ, Miell DE and MacDonald RAR (eds.) Musical Imaginations : Multidisciplinary perspectives on creativity , performance and perception. Oxford: Oxford University Press, 313-331. Molnar-Szakacs I and Heaton P (2012) Music: A unique window into the world of autism. Annals of the New York Academy of Sciences 1252: 318–324. Molnar-Szakacs I and Overy K (2006) Music and mirror neurons: From motion to “e”motion. Social Cognitive and Affective Neuroscience 1(3): 235–241. Mottron L, Peretz I and Ménard E (2000) Local and global processing of music in highfunctioning persons with autism: Beyond central coherence? Journal of Child Psychology and Psychiatry, and Allied Disciplines 41(8): 1057–1065. Narmour E (2000) Music expectation by cognitive rule-mapping. Music Perception 17(3): 329–398. Oberman LM and Ramachandran VS (2007) The simulating social mind: The role of the mirror neuron system and simulation in the social and communicative deficits of autism spectrum disorders. Psychological Bulletin 133(2): 310–327. Overy K and Molnar-Szakacs I (2009) Being together in time: Musical experience and the mirror neuron system. Music Perception 26(5): 489–504. Ozdemir E, Norton A and Schlaug G (2006) Shared and distinct neural correlates of singing and speaking. NeuroImage 33(2): 628–635. Patterson SY, Smith V and Mirenda P (2012) A systematic review of training programs for parents of children with autism spectrum disorders: Single subject contributions. Autism 16(5): 498–522.


Petrides M (2013) Neuroanatomy of Language Regions of The Human Brain. London: Elsevier Science. Ramdoss S, Lang R, Mulloy A, et al. (2010) Use of computer-based interventions to teach communication skills to children with autism spectrum disorders: A systematic review. Journal of Behavioral Education 20(1): 55–76. Rapin I and Dunn M (2003) Update on the language disorders of individuals on the autistic spectrum. Brain and Development 25(3): 166–172. Rimland B and Edelson SM (1995) Brief report: A pilot study of auditory integration training in autism. Journal of Autism and Developmental Disorders 25(1): 61–70. Rizzolatti G and Arbib MA (1998) Language within our grasp. Trends Neuroscience 21: 188–194. Rizzolatti G, Fadiga L, Gallese V, et al. (1996) Premotor cortex and the recognition of motor actions. Brain Research. Cognitive Brain Research 3(2): 131–141. Rojas DC, Bawn SD, Benkers TL, et al. (2002) Smaller left hemisphere planum temporale in adults with autistic disorder. Neuroscience Letters 328(3): 237–240. Saffran JR (2003a) Statistical language learning: mechanisms and constraints. Current Directions in Psychological Science 12(4): 110–114. Saffran JR (2003b) Absolute pitch in infancy and adulthood: the role of tonal structure. Developmental Science 6(1): 35–43. Saffran JR, Aslin RN and Newport EL (1996) Statistical learning by 8-month-old infants. Science 274(5294): 1926–1928. Sandiford GA, Mainess KJ and Daher NS (2013) A pilot study on the efficacy of melodic based communication therapy for eliciting speech in nonverbal children with autism. Journal of Autism and Developmental Disorders 43(6): 1298–1307. Schön D, Magne C and Besson M (2004) The music of speech: music training facilitates pitch processing in both music and language. Psychophysiology 41(3): 341–349.


Simpson K, Keen D and Lamb J (2013) The use of music to engage children with autism in a receptive labelling task. Research in Autism Spectrum Disorders 7(12): 1489–1496. Tager-Flusberg H (1981) On the nature of linguistic functioning in early infantile autism. Journal of Autism and Developmental Disorders 11(1): 45–56. Tager-Flusberg H, Paul R and Lord C (2005) Language and communication in autism. In Volkmar FR, Paul R, Klin A and Cohen D (eds.) Handbook of Autism and Pervasive Developmental Disorders: Diagnosis, Development, Neurobiology, and Behavior. New York: John Wiley & Sons, Ltd, 335-364. Tager-Flusberg H and Sullivan K (1995) Attributing mental states to story characters: A comparison of narratives produced by autistic and mentally retarded individuals. Applied Psycholinguistics 16(3): 241–256. Thompson GA, McFerran KS and Gold C (2013) Family-centred music therapy to promote social engagement in young children with severe autism spectrum disorder: A randomized controlled study. Child: Care, Health and Development: 1–13. Tuchman RF, Rapin I and Shinnar S (1991) Autistic and dysphasic children. I: Clinical characteristics. Pediatrics 88(6): 1211–1218. Wan CY, Bazen L, Baars R, et al. (2011) Auditory-motor mapping training as an intervention to facilitate speech output in non-verbal children with autism: a proof of concept study. PloS One 6(9): 1–7. Whipple J (2004) Music in intervention for children and adolescents with autism : A meta-analysis. Journal of Music Therapy 41(2): 90–106.