The effect of musical attention control training (MACT) on attention skills of adolescents with neurodevelopmental delays: a pilot study.

Journal of Music Therapy, 51(4), 2014, 333–354 doi:10.1093/jmt/thu030 © the American Music Therapy Association 2014. All rights reserved. For permissions, please e-mail: [email protected]

The Effect of Musical Attention Control Training (MACT) on Attention Skills of Adolescents with Neurodevelopmental Delays: A Pilot Study Queens University of Charlotte

A. Blythe LaGasse, PhD, MT-BC Colorado State University

Saundra L. Penn, PhD, LPC, RPT Queens University of Charlotte Background: Given the effect of musical training on the rate and accuracy of processing auditory information, therapeutic uses of music may potentially have remedial benefits for individuals with neurodevelopmental deficits. However, additional studies are needed to establish efficacy of music therapy interventions for attention skills in children/adolescents with neurodevelopmental disabilities including those with Autism Spectrum Disorders (ASD). Objective: To establish feasibility and preliminary efficacy of a group music therapy protocol to improve attention skills (sustained, selective, attentional control/switching) in adolescents diagnosed with autism and/ or developmental delays. Methods: This single group pretest/posttest study took place in a private school for high functioning adolescents with neurodevelopmental delays. Nine students (4 males, 5 females), ages 13 to 20, participated Varvara Pasiali, PhD, MT-BC, is an assistant professor of Music Therapy at Queens University of Charlotte. Blythe LaGasse, PhD, MT-BC is an associate professor of Music Therapy at Colorado State University. Saundra L. Penn, PhD, is an assistant professor in Human Services Studies at Queens University of Charlotte. Correspondence concerning this article should be addressed to Varvara Pasiali, PhD, MT-BC, Assistant Professor of Music Therapy, Queens University of Charlotte, 1900 Selwyn Ave., Charlotte NC 28274. Contact: office 704-688-2720; fax 704-3372356; e-mail [email protected] An earlier version of this manuscript was presented at the research poster session of the American Music Therapy Association national conference, Jacksonville, FL (November, 2013). The authors would like to express appreciation to the families, students, and staff at Philips Academy, Charlotte, NC.

Downloaded from http://jmt.oxfordjournals.org/ at The University of British Colombia Library on June 17, 2015

Varvara Pasiali, PhD, MT-BC

334

Journal of Music Therapy

Keywords: attention, autism spectrum disorders, music therapy, neurodevelopmental disorder

Focusing on certain aspects of the environment, integrating information gathered through sensory systems, and allowing the brain to interpret and respond to information are tasks relevant to our attention abilities, which are comprised of three distinct functional components: sustained, selective, and attention control/switching. Sustained attention (also called alerting) consists of vigilance, arousal, and the ability to sustain attention to a specific stimulus. Selective attention (also called executive control/ focused) involves the engagement of more complex operations, selection of relevant stimuli, and resolution of competing goals. Attentional control/switching (also called orienting) is the selection of and switching between specific information in the environment by disengaging, moving to new focus, and engaging attention (Fan et al., 2012; Manly, Robertson, Anderson, & Mimmo-Smith, 1999; Petersen & Posner, 2012). Individuals with neurodevelopmental delays often have difficulties with attention abilities. The Diagnostic and Statistical Manual of


in the study. Autism severity was assessed using the CARS2-HF and indicated the following distribution for study participants: severe (n = 3), mild (n = 4), or minimal/no (n = 2) symptoms. We assessed feasibility of implementing a 45-min Musical Attention Control Training (MACT) intervention delivered by a board-certified music therapist eight times over 6 weeks in a school setting. We also examined preliminary efficacy of the MACT to improve attention skills using the Test of Everyday Attention for Children (TEA-Ch). Results: Parental consent rate was 100%. All nine participants successfully completed testing measures and 6 weeks of the intervention. Average participation rate was 97%. Data analysis showed positive trends and improvements on measures of attentional control/switching and selective attention. Conclusions: The results showed that the intervention and testing measures were feasible to implement and acceptable to the participants who all completed the protocol. Data analysis demonstrated positive trends indicating that more research on the use of music therapy attention training in high-functioning adolescents with neurodevelopmental disabilities is warranted.

Vol. 51, No. 4

335


Mental Disorders (American Psychiatric Association, 2013; DSM-5) does not include attention as a core deficit of Autism Spectrum Disorders (ASD). Researchers however, have pointed out that difficulties in attention skills are an identified need of individuals with ASD (Ames & Fletcher-Watson, 2010; Ravizza, Solomon, Ivry, & Carter, 2013). Despite research indicating that children with ASD demonstrate difficulties with attention, there are few studies in which researchers have tested treatment protocols to specifically improve attentional abilities. Music can engage children with ASD and, when applied in a systematic manner, may improve attention control skills. Although results in many studies have demonstrated increased engagement with music (Carnahan, Musti-Rao, & Bailey, 2009; Finnigan & Starr, 2010; Kim, Wigram, & Gold, 2009), we found no studies specifically measuring the impact of music therapy on attention skills in persons with ASD. Persons with ASD display typical sustained attention skills (Sanders, Johnson, Garavan, Gill, & Gallagher, 2008), demonstrating the ability to attend to a preferred item for extended periods of time. However, persons with ASD demonstrate difficulty with selective attention (filtering out irrelevant stimuli) and attentional control/switching (Ravizza et al., 2013; Sanders et al., 2008). Furthermore, many children with ASD demonstrate difficulty with specific behaviors linked with attention skills such as difficulty initiating and inhibiting responses to environmental stimuli and poor impulse control (Gardiner, 2005; Schopler, Van Bourgondien, Wellman, & Love, 2010). Sanders et al. (2008) proposed that difficulties in skills such as attention might be the result of atypical brain connectivity in individuals with ASD. Brain connectivity allows for information to be transmitted and differentiated in an efficient manner, including local over connectivity (atypical intensity and regional localized activation), and long-range under connectivity (inability of neural units to activate effectively). Furthermore, Fan et al. (2012) demonstrated that persons with ASD have atypical neurological activations when completing attending tasks. These different cortical activations affect the individual’s ability to process and respond appropriately to various environmental stimuli (Belmonte, 2000; Belmonte et al., 2004). A lack of efficient processing may be observed in behavioral challenges, learning difficulties, and attention focused on meaningless or irrelevant stimuli.

336



Results from studies with a variety of populations indicate that attention can be modified or strengthened with modification in environment (Kinnealey et al., 2012; Montgomery, Storey, Post, & Lemley, 2011) or training (Gagnon & Belleville, 2012; Shalev, Tsal, & Mevorach, 2007). Furthermore, researchers have suggested that reward networks can affect attentional networks (Padmala & Pessoa, 2011). Ivanov and colleagues (2012) completed a study where adults participated in a task that provided few opportunities for reward incentives and had high attentional demands. Anticipation of punishment/loss of a reward following an incorrect response was more salient in promoting heightened activation in attentional networks than the expectation of a possible reward incentive. Moreover, with increased task difficulty the researchers found enhanced attention activation and decreased reward activation, suggesting that difficult tasks are perceived as less rewarding regardless of external reward (Ivanov et al., 2012). This research evidence suggests that the reward and motivation to participate in music experiences may impact attention. Strait and Kraus (2011) found that musical training decreased prefrontal neural variability during auditory selective attention tasks. Variability in the activation of prefrontal regions corresponds with decreased attention task performance. Moreover, musical training supported development of higher-level cognitive mechanisms leading to enhanced auditory processing (Kraus & Chandrasekaran, 2010; Strait, Kraus, Parbery-Clark, & Ashley, 2010). Given the effect of musical training on the rate and accuracy of processing auditory information, therapeutic uses of music may potentially have remedial benefits for individuals with neurodevelopmental deficits (Kraus & Chandrasekaran, 2010; Strait & Kraus, 2011; Strait et al., 2010). Musical stimuli can be motivating and may help children with attentional difficulties focus. For example, using music as background listening increased the amount of time children with autism focused on visual stimuli (Xu et al., 2010). Moreover, using background music as a form of stimulation increased the ability of children with ADHD to focus on an arithmetic task (Abikoff, Courtney, Szeibel, & Koplewicz, 1996). Geist and Geist (2008, 2012) suggested that a rhythm stimulus during chanting or singing songs that pertain to learning pre-academic concepts, such as patterning and one-on-one correspondence, can facilitate attention

Vol. 51, No. 4

337


and engagement. Lastly, Wolfe and Noguchi (2009) reported that preschool children were able to maintain attention during a developmentally appropriate musical story even when distracter sounds, such as ambulance siren, people talking, and telephone ringing, were presented. The aforementioned evidence supports music as a foundation for attentional processes. Music therapy researchers documented various ways music-based applications gain and maintain engagement (DeBedout & Worden, 2006; Robb, 2003; Standley & Hughes, 1996; Sussman, 2009). Both Robb (2003) and Standley and Hughes (1996) examined child engagement during music therapy sessions. Robb (2003) worked with six children who had visual impairment four of which had additional disabilities. Each of the four sessions lasted for 30-min. In two sessions, she used music-based applications and the remainder two she used similar play-based approaches. She measured attentive behaviors such as on task behavior, following instructions, maintaining personal space, and engaging in activities. Overall, participants who had multiple disabilities seemed more responsive to music therapy interventions than participants who only had visual impairment. Using time sampling, event recording, and content analysis, Standley and Hughes (1996) examined two videotapes of 30 min music therapy sessions with students in two inclusive preKindergarten classrooms and documented a high percentage of on task behaviors. Seventeen children (ages 5–13) with severe delays participated in DeBedout and Worden’s (2006) study, each at their respective school. Discrete trials of presenting musical and nonmusical stimuli demonstrated more positive responses to the continuous interaction with the therapist during the music condition (strumming the guitar while the therapist sang a song). Lastly, the results of a research study by Sussman (2009) showed that using musical props can help children with developmental disabilities shift attention and orient their bodies towards peers. The results of the above studies further support that children with neurodevelopmental disabilities engage and change behaviors with music therapy treatment. Moreover, research findings indicate that children with ASD find participation in music-based experiences motivational. During music therapy, children with autism experience high frequency of active engagement and comply with interpersonal demands (Kim, Wigram, & Gold, 2009). Wigram and Gold (2006) suggested that

338



the structure and predictability inherent in active music making facilitates motivation to build attention skills. Researchers also showed that participating in music-based experiences improved joint-attention skills of young children with ASD (Kalas, 2012; Kim et al., 2009; Reitman, 2006). Joint attention requires social and attentional skills, as the child must attend to cues from another person and shift attention to an item or point of reference. In conclusion, research findings support that music facilitates attentional control. An intervention specifically focused on attending skills may provide motivation and structure for the improvement of engagement, disengagement, and switching attention. Music therapists can adapt music-based experiences to provide an individualized “best fit” approach for attention training. Wigram and Elefant (2009) proposed that music therapists have skills and clinical training that enable them to present clients with many opportunities to engage in back and forth interactions during sessions. The music therapist can create developmentally appropriate music-based experiences that target specific skills that are needed in children with ASD. Although there are no known studies specifically targeting attention is persons with ASD, Thaut et al. (2009) demonstrated that music therapy treatment improved attention skills in persons with traumatic brain injury. Mueller (2013) also showed gains in executive function and attentional skills in adults with acquired brain injury, with changes only observed in active music therapy groups and not passive music listening groups. Additionally, observations in one case study demonstrated that music therapy could assist in improving attention in a child with Attention Deficit Hyperactivity Disorder, indicating the possibility for treatment-based attention changes in children with attentional difficulties (Ouellet, 2012). In the recent years, researchers developed protocols for assessing and developing attention skills of adults with neurocognitive disorders. Such protocols were effectively implemented with older adults (Ceccato et al., 2012), and with adults who have schizophrenia (Ceccato, Caneva, & Lamonaca, 2006). Lastly, researchers pilot tested a music-based Attention Assessment (MAA; Jeong & Lesiuk, 2011) for assessing attention skills of patients with Traumatic Brain Injury. Initial psychometric measures showed high internal consistency, and hierarchical progressive difficulty of test items. Even though additional psychometric investigation is needed to

Vol. 51, No. 4

339

1. What percentage of parents will consent to having their child with autism and/or cognitive disabilities participate in a study testing a music therapy group intervention? 2. What percentage of planned intervention sessions will adolescents complete? 3. What percentage of participants is able to complete evaluation sessions and what is the duration for completing study instruments? 4. What are potential barriers, if any, to delivering the intervention and assessment sessions in a private school system? Research questions related to potential benefits were: 1. Are there any changes in attention skills (sustained, selective, attentional control/switching) as measured by a standardized measure of attention? 2. Is there any identifiable impact of severity of autism on changes in attention scores?

Method Participants Participants were recruited from a private school for high-functioning adolescents with neurodevelopmental disabilities (N = 9). Ages ranged from 13 to 20; four were males and five were females. All participants were native English speakers. One participant had


establish the validity of using the scale for diagnostic evaluation the findings indicate the potential of using a melodic contour based test to assess attention. Although evidence supports the use of music for attentional skills in persons with disabilities, there are no known studies investigating the use of a music therapy attention protocol on the sustained, selective, and attentional control/switching attention in children and adolescents with neurodevelopmental disabilities including ASD. Aims for this pilot study were to: (a) determine the feasibility of the Music Attention Control Training (MACT) intervention on attention behavior in adolescents with autism and cognitive disability, and (b) to obtain preliminary evidence of intervention effects on attention outcomes. Research questions related to feasibility were:

340


Procedure The research design was single group pre and posttest. The school principle sent information about the music therapy study via a school newsletter (N = 16 families/students). The first author of this study met with the school principle and identified a total of 10 students that met inclusion criteria and had the functioning skills/cognitive abilities to complete the TEA-Ch (N = 10). The school principle contacted the students’ families/guardians to obtain informed consent. All parents contacted consented to having their child participate in the study. Students gave verbal assent to participate in music therapy. A team of teachers working directly with the students completed CARS2-HF (Schopler et al., 2010). The team sought parental feedback when clarification was needed. The researchers administered the Test of Everyday Attention for Children (TEA-Ch; Manly et al., 1999) prior to and after participating in music therapy sessions. Testing was conducted in a quiet office at the participants’ school. A total of 10 students were initially identified as potential participants in the study. During the first evaluation session, one student selected to participate in the study was unable to understand the instructions and complete the TEA-Ch during pretest due to language barriers. All remainder of students completed the pre and post evaluation sessions (N = 9). The researchers used the two parallel versions of TEA-Ch for the test/retest to avoid practice effects. The aim was to evaluate a short-term directive protocol targeting attentions skills. Thus, the researchers implemented a short-term treatment protocol of eight 45-min group music therapy sessions. Eight sessions fall within the guidelines of short-term group therapy (c.f. Brabender, Smolar, & Fallon, 2004).


a history of hearing loss and wore hearing aids. Participants were assessed using the High Functioning Version of the Childhood Autism Rating Scale (CARS2-HF; Schopler et al., 2010). Three participants had severe symptoms, four participants had mild to moderate symptoms, and two participants had minimal to no symptoms of Autism Spectrum Disorder (ASD). Although participants had co-morbid intellectual disabilities, none had co-morbid secondary major diagnoses such as Down syndrome. This study was conducted in accordance with the ethical guidelines approved by the University’s Institutional Review Board.

Vol. 51, No. 4

341

Measures


Feasibility. Data were collected pertaining to the number of students initially identified as potential participants to the study, the number of consent forms sent and returned, and ability of students to complete evaluation sessions. The researchers administering TEA-Ch (first & third author) and recorded anecdotal observations regarding student behavior during pre and post measurement on the scoring sheets. The researcher (first author) implementing the music therapy sessions maintained attendance and anecdotal notes regarding participation. Anecdotal notes also included information regarding potential barriers (e.g., planned school closings, special events, holidays). CARS2-HF. The High Functioning Version of the Childhood Autism Rating Scale, developed by Schopler et al. (2010), includes ratings of 15 functional areas including social-emotional understanding/regulation, interpersonal skills, use of body, play/interests, anxiety, response to visual and auditory stimuli, receptive/ expressive communication, and cognitive skills. Clinicians can use the scale to identify children with autism and determine symptom severity. Ratings are based on direct observations of the intensity and duration of specific behaviors. The high functioning version was developed for individuals 6 years of age and older with IQ scores above 80. The internal consistency of CARS2-HF is estimated as .96. Interrater reliability is .95. The total raw scores of CARS2-HF range from 15–60. Raw scores lead to a diagnostic hypothesis of autism-related symptoms as follows: 15–27.5 minimal or no autistic behaviors, 28–33.5 mild-to moderate level of autistic behaviors, 34–60 severe autistic behaviors. TEA-Ch. Developed by Manly et al. (1999), TEA-Ch is a measuring tool that includes nine tasks that require different types of skills such as sustained, selective, and attentional control/switching attention, as well as ability to inhibit verbal and motor responses. Heaton et al. (2001) pointed out that even though TEA-Ch consists of a total of nine subtests, administration of the tasks yields a total of 13 scoring items. There is no total raw score for attention. The estimate length of time required to complete TEA-Ch is one hour. The tool has two versions to allow for test-retest. The test-retest reliability coefficients for the subtests range from 0.57 to 0.87. A Structural Equation Model analysis using three separate factors (sustained, selective, and attentional control/switching attention)

342


• Score! The task involves silently counting the number of tones heard (ranging from 9–15) without using fingers on a 15 min audio track. The raw score is obtained by giving one point for each trial counted correctly (maximum = 10). • Score Dual Task. This is a dual task that involves completing the Score! while listening to an audiotaped news report that includes a reference to an animal. After each trial, children report number of tones and name the animal in the report. The raw score is obtained by counting the number of animals named correctly (maximum=10), and number of tones counted accurately (maximum = 10). Total maximum = 20. • Code Transmission. For this task, children listen to a string of numbers and upon hearing a pattern of two 5s, they must report the number presented prior to the pattern. This is a 12-min task with 40 double 5 patterns. Raw scores are obtained by counting the number of correct responses. • Sky Search Dual Task. Perform the subtests Score! and Sky Search at the same time. Count correct responses (maximum = 20). • Walk, Don’t Walk. Complete a scoring sheet resembling footprints on a path. For this task, children have to put a mark in each box after hearing a tone indicating they are taking a step. When two tones sound, the participants have to stop and inhibit the tendency to put a mark in the next box. The speed of the tones increases as the test progresses. Record the number of paths (maximum = 20) completed correctly. The two scoring items for selective attention skills were: Sky Search, and Map Mission. • Sky Search. For this task, children are given a large sheet filled with spaceship pairs and distractor dissimilar spaceships. They must find and circle pairs of spaceships that are the same as quickly as possible. A posttest, without the


resulted in fit index values above 0.90 (Manly et al., 1999). Similar to Heaton et al. (2001) we used the nine scoring items that fit the factor analysis model reported in the test manual. The five scoring items for sustained attention skills were: Score!, Score Dual Task, Code Transmission, Sky Search Dual Task, Walk Don’t Walk.

Vol. 51, No. 4

343

The two scoring items for attentional control/switching attention skills were: Creature Counting and Opposite Worlds. • Creature Counting. For this task, children count the number of creatures in a burrow. They follow a visual pathway and they count up when the arrow points up and count down when the arrow points down. Record accuracy and speed. A smaller number indicates a higher percentile ranking. • Opposite Worlds. A waving path with the numbers 1 and 2 is shown. When the child sees a 1 they say “2” and when the child sees a 2 they say “1”. Record time to correctly complete the task. (see Heaton et al., 2001; Manly et al., 1999). Group Music Therapy Intervention Serving a dual role as a board-certified music therapist and researcher, the first author of this study facilitated the music therapy sessions. The music therapy intervention/treatment involved participating in eight 45-min sessions over a period of 6 weeks (10/26/2012 - 11/30/2012). During the sessions, the researcher used music-based clinical techniques to target development of specific attention skills (sustained, selective, & attentional control/switching attention). The researcher used age-appropriate and/or preferred client music to maintain active engagement and focus. The technique employed was Musical Attention Control Training (MACT; Thaut, 2005). During each session, the researcher implemented a variety of music-based experiences for MACT including adapted Orff-based


distractor items, is used as a control for motor speed differences. Scoring involves counting the number of correct pairs circled and the time taken. Then, test administrators record the time-per-target by dividing the total time taken to complete the task by the number of targets found. To find the subtest score, subtract the motor control posttest score from the time-per-target score. The smaller the raw score the higher the percentile ranking. • Map Mission. Children must circle the restaurant symbols (fork and knife) on a city map with various distracters as fast as they can in one min. Count number of correct symbols circled.

344



musical tasks, structured drumming/rhythm experiences, and structured/unstructured improvisation. Adapted Orff-based musical tasks included singing songs and chants, using body percussion, improvising on pitched and non-pitched percussion, and using vocal or rhythmic ostinatos. Participants played a variety of instruments following adapted notation charts. Moreover, the researcher assigned specific instruments and taught the participants short instrumental pieces allowing them to learn and perform by ear. During structured drumming, the participants had to follow both verbal and nonverbal cuing for mirroring patterns, changing dynamics, improvising or performing specific patterns assigned by the researcher. Music therapy sessions had a predictable structure. The researcher began the session by using familiar and predictable tasks, introducing more challenging activities in the middle of the session and ending with a music-assisted relaxation exercise with either recorded or live music. The purpose of using music-assisted relaxation was to help participants calm down physically and emotionally as well as transition to their next school-related activity. Sustained attention. The intervention involved active or receptive participation requiring the students to focus their attention on a changing musical stimulus (i.e., sustained attention). Specifically, the researcher facilitated musical experiences to practice sustained attention by requiring the students to respond to changes of musical elements (e.g., changing dynamics, tempo, rhythmic patterns). Examples included the researcher modeling rhythm patterns the students had to echo, using conducting cues to change the dynamics during drumming, alternating between free improvisation and structured instrumental playing (Where the students had to match what the researcher was playing/modeling), and so forth. Selective attention. During the intervention, students had to focus on single musical cues while ignoring other stimuli (i.e., selective attention). Opportunities to practice selective attention included focusing on maintaining a rhythmic pattern while ignoring patterns playing by other students, or switching to different patterns/instruments when given a specific musical cue that was embedded in the music. For example, the researcher modeled a specific pattern that a student had to maintain on an instrument. After modeling the patterns, the researcher switched to free improvisation. The students had to remain focused on their assigned pattern, despite the distraction from the researcher. In addition, the

Vol. 51, No. 4

345

Data Analysis Feasibility. The authors of this study reviewed all anecdotal notes regarding consent rate, attendance and participation in the music therapy group intervention, and potential barriers to delivering the intervention. Consent rate was converted to a percentage by dividing the number of eligible students with the number or consent forms returned and then multiplying by 100. Participation was considered for students that attended sessions fully, without removal or refusing to engage/follow instructions. The participation rate was converted to a percentage for each session by dividing the number of students who attended the each session with the total number of participants (N = 9) and then multiplying by 100. The average participation rate across all music therapy sessions is reported in the results section.


researcher played musical examples that included contrasting sections. The students had to switch from one instrument to another with the changes in the music. Other times, specific cues (such as a discordant chord or a contrasting musical phrases) were impeded while the researcher improvised on the piano as cues for students to perform a task such as switching instruments, switching patterns, changing dynamics, switching chairs, alternate between standing/ sitting and so forth. Attentional control/switching attention. More complex musical experiences during the intervention required students to focus on two auditory sources at the same time (i.e., attentional control/switching attention). Chanting while doing body percussion, playing an instrument and singing, or playing assigned parts in a musical arrangement allowed opportunities to practice attentional control/switching attention. Often the researcher required the students to alternate monitoring two external stimuli such as following musical and non-musical cues provided by the researcher and another student. Engaging students in complex experiences often extended over multiple sessions by teaching/structuring sequential steps. For example, when the researcher taught the students chants, she would first incorporate those during musical experiences that provided opportunities to practice sustained or selective attention. She would then create instrumental arrangements incorporating body percussion, ostinatos, and patterns on pitched percussion that the students executed.


346

Results Feasibility Consent rate. Ten students were eligible to participate in the study. The parents of all eligible students consented to participating in the study and all the students verbally assented to complete the testing and participate in the sessions. The private school where the study was conducted has been a clinical practicum site for music therapy students. Parental involvement in the school is high, thus the parents/guardians were familiar with music therapy. Familiarity with music therapy likely contributed to the high consent rate. The rate of consent was 100%. Participation rate. All music therapy sessions occurred during regular school hours. The length of the session was the same as a class period. Student participants perceived participation in music therapy as part of their daily class schedule. All recruited students participated in the study and attended music therapy sessions. There were no withdrawals from the study. One participant missed the first session due to a scheduled appointment. Another participant missed part of one session due to illness. There were no further absences. During music therapy, all students in attendance participated fully without refusing to engage. The average participation rate was 97%. Evaluation. One eligible student was unable to complete the first task of the TEA-Ch during pretesting due to language barriers. He therefore did not participate in the study. All nine remaining participants completed both pre and posttesting as scheduled. Overall, one participant completed the TEA-Ch during the standard time


Preliminary Efficacy. Data were analyzed first with visual inspection of raw data for collective participants and separately according to severity of ASD on the CARS2-HF. Given the small sample size, statistical testing was only completed to examine trends in targeted outcomes. A series of paired sample t-tests were applied to the subtests of the TEA-Ch. Analysis with paired t-tests was based on the assumption that the data would be normally distributed. In order to check this, we applied the Shapiro-Wilks test to the difference scores. If the assumption of normality was not fulfilled, we planned to use a Wilcoxon Signed-Rank test to account for violation of the assumption.

Vol. 51, No. 4

347

Preliminary Outcomes Means and SDs were calculated for the TEA-Ch data before and after the intervention. Visual inspection of the TEA-Ch data indicated positive trends in several areas of the attention test. In particular, the participants showed positive directional changes on tests related to selective attention and attentional control/switching (see Table 1). Measures related to sustained attention had no observable changes in direction. The Shapiro-Wilks test indicated that the difference scores were normally distributed. Statistical analysis confirmed positive trends with significant improvements for measures of selective attention and attentional control/switching attention. There was no significant difference for measures of sustained attention (Table 1). Difference scores for the participants were visually analyzed to determine if level of ASD impacted scores on the TEA-Ch. There were no observable patterns for children who were considered “mild” by the CARS2-HF (28–33.5) or severe (above a score of 34). Difference scores for the four TEA-Ch subtests found to be significant are shown in Table 2.


reported by those creating the measure. Seven participants needed 10–20 min longer to complete than the standard time. One student became irritable and distracted during pre and posttesting and needed 30 min longer to complete the measure. Potential barriers. The study was completed in three months. All pretesting was completed within two weeks prior to beginning music therapy sessions, as was planned. The music therapy sessions spanned a period of 6 weeks. In order to complete the eight music therapy sessions prior to winter school break, the frequency of sessions varied. Music therapy sessions occurred once a week. However, two music therapy sessions were scheduled on weeks three and six. Posttesting was completed within 2 weeks following completion of the music therapy sessions, as planned. Since this study was completed at a school, breaks and holidays were observed with the school calendar. Planned events impacting implementation of this study included: one half-week break during the treatment period, a fundraiser celebration, and a parent-teacher conference day. The fact that students demonstrated some regression of attention skills after a school holiday should be considered, as this may have impacted the results.

7 (2.78) 13.67 (2.44) 34.22 (6.28) 11.44 (4.75) 44.79 (116.03) 3.72 (1.57) 33.33 (9.43) 5.78 (1.20) 37 (8.20)

7.55 (3.40) 14.33 (4.33) 33.33 (6.56) 8.89 (5.62) 9.16 (13.74) 5.11 (2.50) 23.77 (5.19) 4.11 (2.42) 43.55 (12.41)

Post

8 8

8 8

8 8 8 8 8

df

-2.774 2.467

2.666 -4.053

0.743 0.625 -0.488 -1.994 -1.034

t


0.024* 0.039*

0.029* 0.004*

0.479 0.550 0.639 0.081 0.331

p

Notes. * Significant at p < .05. Higher scores represent higher percentile ranking for the following sub-tests of the TEA-Ch: Score, Score Dual Task, Code Transmission, Walk, Don’t Walk, Map Mission, & Creature counting (accuracy). Lower scores represent higher percentile ranking for the following sub-tests of the TEA-Ch: Sky Search, Sky Search Dual Task, Same World, & Opposite World.

Sustained Score! Score Dual Task Code Transmission Walk, Don’t Walk Sky search Dual Task Selective Sky Search Map Mission Attentional Control/Switching Creature Counting Opposite Worlds

Pre

Means, (standard deviations), and Results of Paired t-Test for TEA-Ch

Table 1

348 Journal of Music Therapy

17 12 15 18 14 20 17 17 19

1 2 3 4 5 6 7 8 9 Average SD

23 26 29 29.5 32 33.5 37.5 38 42

CARS Raw Score

-1.04 0.80 -2.05 -0.26 -4.12 1.89 -0.50 -2.95 -.68 -.990 1.843

Sky Search

-8 7 1 -13 -19 -9 -7 -11 -1 -6.667 7.874

Opposite World

1 1 4 3 2 3 -1 3 21 4.111 6.509

Creature Counting


7 12 11 4 8 -1 19 5 0 7.222 6.241

Map Mission

Notes. Lower scores are considered improvements for the Sky Search and Opposite World Tasks. CARS-HF scores above 34 are an indicator of severe symptoms of ASD. Scores between 28 to 33.5 indicate mild-to-moderate symptoms of ASD. Scores between 15–27.5 indicate minimal-to-no symptoms of ASD.

Age

Participant

Difference Scores (post-pre) for Subtests Found to be Significant for Arranged by CARS2-HF Scores

Table 2

Vol. 51, No. 4 349


350

Discussion


Children with ASD often struggle with ignoring irrelevant stimuli and switching between sources of stimuli. Since the ability to control attention impacts cognitive functioning and learning, interventions that improve attention function could positively impact daily living and academic success. The researchers of this pilot study aimed to determine the feasibility of the MACT intervention on attention behavior in adolescents with autism and cognitive disability and to obtain preliminary evidence of intervention effects on attention outcomes. Feasibility data indicate that delivery of the MACT protocol was feasible; however, there were complications specific to the school setting and group nature of the protocol. In observation, it was clear that some students struggled with more demanding tasks, while others lost attention to simpler tasks. Differences in individual abilities and needs would be better studied with individualized treatment. However, individualized treatment is often not the reality of school-based music therapy where many students may be seen together for fiscal impact. For this reason, we propose that future research on the MACT intervention be tested in small group settings, based on pretest measure of attentional abilities. The setting used in this study complicated study procedures due to issues such as special events and school holidays. In particular, the study spanned over a time when students had half a week off of school for a holiday break. Observations upon their return were that they were less organized and displayed much higher arousal. Musically, many adolescents displayed an inability to entrain to rhythm tasks after the break. Although consistent with this clinical setting, future researchers using a school setting may want to avoid completing study procedures when a break or change is scheduled to occur in the school calendar. This complication may also show that a future efficacy trial of the MACT protocol may be easier (in some regards) in a non-school environment (e.g., private clinic) before testing its effectiveness in the natural school environment. However, implementing the protocol in a naturalistic setting allows for a more timely transition of learned skills in the school setting. Feasibility data indicate that the children and their families were willing to be involved in this behavioral research study. The 100% consent rate was high and indicates that participant accrual for a larger study in a similar setting would be viable. Furthermore, the 0% attrition rate coupled with 97% attendance in sessions indicates that

Vol. 51, No. 4

351


the protocol was well tolerated by the children involved in the study. This tolerance of the protocol may be due to the inclusion of the sessions in the typical school day, which prevented absences due to issues such as after school scheduling conflicts. For this reason, conducting the study in the school setting was advantageous due to convenience of not needing transportation or other arrangements. Since participants ranged in their level of autism, these data support further study of this intervention with children who have mild to severe ASD. The study procedures were all completed within the proposed timelines, with 100% cooperation from the students’ teachers. Nine participants tolerated the TEA-Ch assessment despite the measure taking longer than expected to complete. One participant showed irritability; however, was able to complete the measure. In future studies, researchers may focus on the selective and switching aspects of testing, as these are the areas of higher need in individuals with ASD. No complaints were received about the testing measures, indicating that the children, teachers, and parents tolerated these measures. Collectively, the data indicate positive trends in outcomes related to two of the targeted attention functions: selective and attentional control/switching attention. The finding that there were no trends in sustained attention tests is not surprising, as research indicates that individuals with ASD do not have sustained attention deficits (Sanders et al., 2008). The second research outcome question was focused on any identifiable impact of autism severity on changes in attention scores. Visual analysis revealed no observable differences in test scores for individuals considered to have more severe symptoms of ASD (n = 3), when compared to individuals considered to have mild symptoms (n = 6). However, there were only three participants with CARS2-HF scores that would indicate severe symptoms of ASD, which cannot be considered representative of a population of children with severe symptoms of ASD. Although positive trends in data provide initial evidence that the intervention was successful, results must be interpreted with caution due to the small sample size, lack of a control group, and potential for research bias in administration of testing measures. The fact that the sample was high-functioning adolescents attending a private school may also have influenced the results. Future research on this protocol should strive to address these limitations in order to better test efficacy of the MACT intervention with adolescents who have neurodevelopmental disabilities including ASD.


352

References Abikoff, H., Courtney, M. E., Szeibel, P. J., & Koplewicz, H. S. (1996). The effects of auditory stimulation on the arithmetic performance of children with ADHD and nondisabled children. Journal of Learning Disabilities, 3, 238–246. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing. Ames, C., & Fletcher-Watson, S. (2010). A review of methods in the study of attention in autism. Developmental Review, 30, 52–73. doi: 10.1016/j.dr.2009.1012.1003 Belmonte, M. (2000). Abnormal attention in autism shown by steady-state visual evoked potentials. Autism, 4, 269–285. doi: 210.1177/1362361300004003004 Belmonte, M. K., Allen, G., Beckel-Mitchener, A., Boulanger, L. M., Carper, R. A., & Webb, S. J. (2004). Autism and abnormal development of brain connectivity. The Journal of Neuroscience, 24, 9228–9231. doi: 10.1523/JNEUROSCI.3340-04.2004 Brabender, V. M., Smolar, A. I., & Fallon, A. E. (2004). Essentials of group therapy. Hoboken, NJ: John Wiley & Sons. Carnahan, C., Musti-Rao, S., & Bailey, J. (2009). Promoting active engagement in small group learning experiences for students with autism and significant learning needs. Education and Treatment of Children, 32, 37–61. Ceccato, E., Caneva, P., & Lamonaca, D. (2006). Music therapy and cognitive rehabilitation in schizophrenic patients: A controlled study. Nordic Jounral of Music Therapy, 15, 110–120. doi: 10.1080/08098130609478158 Ceccato, E., Vigato, G., Bonetto, C., Bevilacqua, A., Pizziolo, P., Crociani, S., . . . Barchi, E. (2012). STAM protocol in dementia: A multicenter, single-blind, randomized, and controlled trial. American Journal of Alzheimer’s Disease and Other Dementias, 27, 301–310. doi: 10.1177/1533317512452038 DeBedout, J., & Worden, M. (2006). Motivators for children with severe intellectual disabilities in the self-contained classroom: A movement analysis. Journal of Music Therapy, 43, 123–135. doi:10.1093/jmt/43.2.123 Fan, J., Bernardi, S., Dam, N. T., Anagnostou, E., Gu, X., Martin, L., . . . Hof, P. R. (2012). Functional deficits of the attentional networks in autism. Brain Behavior, 2, 647–660. doi: 10.1002/brb3.90 Finnigan, E., & Starr, E. (2010). Increasing social responsiveness in a child with autism: A comparison of music and non-music interventions. Autism, 14, 321–348. Gagnon, L. G., & Belleville, S. (2012). Training of attentional control in mild cognitive impairment with executive deficits: results from a double-blind


In summary, outcomes from this study indicate that the MACT intervention is feasible and acceptable to adolescents with neurodevelopmental disabilities including ASD. In addition, scores on the TEA-Ch moved in the desired direction, providing initial evidence that the protocol may assist in developing attention skills. These preliminary pilot data support the pursuit of a larger controlled trial to test efficacy of the MACT intervention for adolescents with neurodevelopmental disabilities including ASD.

Vol. 51, No. 4

353


randomised controlled study. Neuropsycholigal Rehabilitation, 22, 809–835. doi: 10.1080/09602011.2012.691044 Gardiner. (2005). Neurologic music therapy in cognitive rehabilitation. In M. Thaut (Ed.), Rhythm, music and the brain (pp. 179–202). New York: Routledge. Geist, K., & Geist, E. A. (2008). Do re mi, 1-2-3: That’s how easy math can be-Using music to support emergent mathematics. Young Children, 63(2), 20–25. Geist, K., & Geist, E. A. (2012). Bridging music neuroscience evidence to music therapy best practice in the early childhood classroom: Implications for using rhythm to increase attention and learning. Music Therapy Perspectives, 30, 141– 144. doi: 10.1093/mtp/30.2.141 Heaton, S.C., Reader, S.K., Preston, A.S., Fennell, E.B., Puyana, O.E., Gill, N., & Johnson, J.H. (2001). The Test of Everyday Attention for Children (TEA-Ch): Patterns of performance in children with ADHD and clinical controls. Child Neuropsychology, 7, 251–64. doi: 10.1076/chin.7.4.251.8736 Ivanov, I., Liu, X., Clerkin, S., Schulz, K., Friston, K., Newcorn, J. H., & Fan, J. (2012). Effects of motivation on reward and attentional networks: An fMRI study. Brain Behavior, 2, 741–753. doi: 10.1002/brb3.80 Jeong, E., & Lesiuk, T. L. (2011). Development and preliminary evaluation of a music-based attention assessment for patients with traumatic brain injury. Journal of Music Therapy, 48, 551–572. doi:10.1093/jmt/48.4.551 Kalas, A. (2012). Joint attention responses of children with autism spectrum disorder to simple versus complex music. Journal of Music Therapy, 49, 430–452. doi:10.1093/jmt/49.4.430 Kim, J., Wigram, T., & Gold, C. (2009). Emotional, motivational and interpersonal responsiveness of children with autism in improvisational music therapy. Autism, 13, 389–409. doi: 10.1177/1362361309105660 Kinnealey, M., Pfeiffer, B., Miller, J., Roan, C., Shoener, R., & Ellner, M. L. (2012). Effect of classroom modification on attention and engagement of students with autism or dyspraxia. American Journal of Occupational Therapy, 66, 511–519. doi: 10.5014/ajot.2012.004010 Kraus, N., & Chandrasekaran, B. (2010). Music training for the development of auditory skills. Nature Reviews Neuroscience, 11, 599–605. doi: 10.1038/nrn2882 Manly, T., Robertson, I. H., Anderson, V., & Mimmo-Smith, I. (1999). Test of every day attention for children. London, U.K.: Pearson Assessment. Montgomery, J., Storey, K., Post, M., & Lemley, J. (2011). The use of auditory prompting systems for increasing independent performance of students with autism in employment training. International Journal of Rehabilitation Research, 34, 330–335. doi: 10.1097/MRR.0b013e32834a8fa8. Mueller, C. (2013). Training endogenous task shifting using neurologic music therapy. Unpublished Master’s Thesis, Colorado, Fort Collins. Ouellet, S. (2012). Music therapy as support in the development of a child with attention deficit hyperactivity disorder (ADHD). Canadian Journal of Music Therapy, 18, 79–90. Padmala, S., & Pessoa, L. (2011). Reward reduces conflict by enhancing attentional control and biasing visual cortical processing. Journal of Cognitive Neuroscience, 23, 3419–3432. doi: 10.1162/jocn_a_00011 Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89. doi: 10.1146/ annurev-neuro-062111-150525

354



Ravizza, S. M., Solomon, M., Ivry, R. B., & Carter, C. S. (2013). Restricted and repetitive behaviors in autism spectrum disorders: The relationship of attention and motor deficits. Development and Psychopathology, 25, 773–784. doi: 10.1017/s0954579413000163 Reitman, M. (2006). Effectiveness of music therapy interventions on joint attention in children diagnosed with autism: A pilot study. Dissertation Abstracts International, 66. Robb, S. (2003). Music interventions and group participation skills of preschoolers with visual impairments: Raising questions about music, arousal, and attention. Journal of Music Therapy, 40, 266–282. doi:10.1093/jmt/40.4.266 Sanders, J., Johnson, K. A., Garavan, H., Gill, M., & Gallagher, L. (2008). A review of neuropsychological and neuroimaging research in autistic spectrum disorders: Attention, inhibition and cognitive flexibility. Research in Autism Spectrum Disorders, 2, 1–16. doi: http://dx.doi.org/10.1016/j.rasd.2007.03.005 Schopler, E., Van Bourgondien, M. E., Wellman, G. J., & Love, S. R. (2010). Childhood Autism Rating Scale (CARS). (2nd ed.). Los Angeles, CA: Western Psychological Services. Shalev, L., Tsal, Y., & Mevorach, C. (2007). Computerized progressive attentional training (CPAT) program: Effective direct intervention for children with ADHD. Child Neuropsychology, 13, 382–388. doi: 10.1080/09297040600770787 Standley, J., & Hughes, J. (1996). Documenting developmentally appropriate objectives and benefits of a music therapy program for early intervention: A behavioral analysis. Music Therapy Perspectives, 14, 87–94. doi:10.1093/mtp/14.2.87 Strait, D. L., & Kraus, N. (2011). Can you hear me now? Musical training shapes functional brain networks for selective auditory attention and hearing speech in noise. Frontiers in Psychology, 2, 113. doi: 10.3389/fpsyg.2011.00113 Strait, D. L., Kraus, N., Parbery-Clark, A., & Ashley, R. (2010). Musical experience shapes top-down auditory mechanisms: Evidence from masking and auditory attention performance. Hearing Research, 261, 22–29. doi: 10.1016/j.heares.2009.12.021 Sussman, J. E. (2009). The effect of music on peer awareness in preschool age children with developmental disabilities. Journal of Music Therapy, 46, 53–68. doi:10.1093/jmt/46.1.53 Thaut, M. H. (2005). Rhythm music and the brain. New York: Routledge. Thaut, M. H., Gardiner, J. C., Holmberg, D., Horwitz, J., Kent, L., Andrews, G., . . . McIntosh, G. R. (2009). Neurologic music therapy improves executive function and emotional adjustment in traumatic brain injury rehabilitation. Annals of the New York Academy of Sciences, 1169, 406–416. doi: 10.1111/j.1749-6632.2009.04585.x Wigram, T., & Gold, C. (2006). Music therapy in the assessment and treatment of autistic spectrum disorder: clinical application and research evidence. Child: Care, health and development, 32, 535–542. Wigram, T., & Elefant, C. (2009). Therapeutic dialogues in music: Nurturing musicality of communication in children with autistic spectrum disorder and Rett syndrome. In S. Malloch & C. Trevarthen (Eds.), Communicative musicality: Exploring the basis of human companionship (pp. 423–445). New york: Oxford University Press. Wolfe, D. E., & Noguchi, L. K. (2009). The use of music with young children to improve sustained attention during a vigilance task in the presence of auditory distractions. Journal of Music Therapy, 46, 69–82. doi:10.1093/jmt/46.1.69 Xu, M., Huang, X., Lu, Y., Xu, X., Tang, Y., & Lu, P. (2010). Explorative analysis on the effects of pictures and music on the attention and emotion in autistic children. Chinese Mental Health Journal, 24, 696–699.

Corporal artistic training influences attention: a pilot study.

Mindfulness training for adolescents: A neurodevelopmental perspective on investigating modifications in attention and emotion regulation using event-related brain potentials.

Chewing and attention: a positive effect on sustained attention.

A pilot study evaluating a one-session attention modification training to decrease overeating in obese children.

The attention training technique, self-focused attention, and anxiety: a laboratory-based component study.

Effect of Attention Training in Mild Cognitive Impairment Patients with Subcortical Vascular Changes: The RehAtt Study.

Attention demands of ball-tracking skills.

Allocation of attention, reading skills, and deafness.

Selective control of attention supports the positivity effect in aging.

hyperactivity disorder--A functional MRI study.

Computer-assisted attention training in schizophrenics. A comparative study.

Hyperactivity Disorder (ADHD): A Pilot Study.

Feasibility study of an attention training application for older adults.

Social skills training with young adolescents.

The relationship between adolescents' pain catastrophizing and attention bias to pain faces is moderated by attention control.

Effect of target separation on selective attention.

Cognitive control, attention, and the other race effect in memory.

The effect of focused attention and open monitoring meditation on attention network function in healthy volunteers.

Effects of weighted vests on attention, impulse control, and on-task behavior in children with attention deficit hyperactivity disorder.

A musical profile for sample of learning-disabled children and adolescents: a pilot study.

Impact of simulation training on Jordanian nurses' performance of basic life support skills: A pilot study.

A pilot study on feasibility, acceptance and effectiveness of metacognitive-oriented social skills training in schizophrenia.

Hyperactivity Disorder.

Neurofeedback and cognitive attention training for children with attention-deficit hyperactivity disorder in schools.