Kelsey Egelhoff Alison E. Lane. Introduction

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1 J Autism Dev Disord (2013) 43: DOI /s BRIEF REPORT Brief Report: Preliminary Reliability, Construct Validity and Standardization of the Auditory Behavior Questionnaire (ABQ) for Children with Autism Spectrum Disorders Kelsey Egelhoff Alison E. Lane Published online: 14 August 2012 Ó Springer Science+Business Media, LLC 2012 Abstract The Auditory Behavior Questionnaire (ABQ) evaluates abnormal behavioral responses to auditory stimulation in children with Autism Spectrum Disorder (ASD). This study reports preliminary reliability, construct validity and standardization of the ABQ. Parents of children with ASD aged 7 21 years (n = 165) completed the ABQ on-line. Cronbach s alpha was 0.94 indicating strong internal consistency. Factor analysis revealed a four-factor structure supporting previous theoretical discussion of global sensory processing difficulties and the construct validity of the ABQ. The 4-factors, (1) Difficulty in Background Noise, (2) Aver sive Reactions, (3) Unresponsiveness, and (4) Stereotypic/ Repetitive Behaviors, are very similar to Dunning s (Devel opment of a questionnaire to assess auditory behaviors in children diagnosed with autism spectrum disorders, The Ohio State University, Columbus, 2003) hypothesized factor domains. Standard factor scores for children with ASD are reported. Keywords Autism spectrum disorder (ASD) Auditory behavior Auditory processing Questionnaire Measurement K. Egelhoff (&) Department of Clinical Therapies and Audiology, Nationwide Children s Hospital, Suite 2A, OCC, 700 Children s Drive, Columbus, OH 43205, USA kelsey.egelhoff@nationwidechildrens.org A. E. Lane Division of Occupational Therapy, School of Health and Rehabilitation Sciences, The Ohio State University, 443C Atwell Hall, 453 W 10th Avenue, Columbus, OH 43210, USA Introduction Abnormal behavioral responses to auditory stimuli are frequently reported in individuals diagnosed with Autism Spectrum Disorder (ASD) (Wetherby et al. 1981; Grandin and Scariano 1989; Egelhoff et al. 2005). Professionals report hypersensitivities to sound, difficulty functioning in the presence of background noise, under-responsiveness to sound stimulation and sensory seeking behaviors to auditory stimuli in children diagnosed with ASD (Dunning 2003). Further, parents of children with ASD report that disruptive reactions to sound can lead to behavioral disturbances that have a negative impact on day-to-day activities (Rapin 1991; Dunning 2003; Alcantara et al. 2004). Abnormal behavioral responses to sound can greatly impact how a child performs in common tasks such as going to school, being in public with his/her family and interacting with peers (Dunning 2003). Additionally, recent study has linked difficulties in processing verbal instructions with academic underachievement in children with ASD (Ashburner et al. 2008). Studies using electrophysiologic and behavioral (nonelectrophysiologic) measures have reported that children with ASD have abnormalities in auditory processing (Wetherby et al. 1981; Steinschneider and Dunn 2002). For example, children with ASD have been found to have difficulty recognizing speech in the presence of background noise (Alcantara et al. 2004) and a diminished ability to attend to particular sounds in environments with multiple complex sound sources (Teder-Salejarvi et al. 2005). Research has not yet been able to identify and describe how neurophysiological abnormalities relate to functional behavior in ASD populations. One barrier to understanding this relationship is the lack of a proven instrument to measure auditory behaviors (Dunning 2003; Egelhoff et al. 2005).

2 J Autism Dev Disord (2013) 43: ASD is a diverse disorder that presents with symptoms across many sensory modalities. Specific patterns in sensory processing deficits have been found in children with ASD and suggest the importance of investigating specific modalities/domains of sensory function (Lane et al. 2011; Lane et al. 2010). Overall understanding of sensory processing in ASD populations is important, but focusing on specific modalities and individual differences may provide additional cues regarding the diversity of behaviors seen in ASD populations. Although auditory processing deficits are not fully understood in ASD, auditory treatments and listening therapies are utilized by therapists to reduce or eliminate abnormal behavioral responses to sound in children with ASD (Rimland and Edelson 1994, 1995; Neysmith-Roy 2001; Corbett et al. 2008). These interventions have been developed in the absence of consensus in the literature about the mechanisms responsible for abnormal auditory behaviors. There is a significant need to investigate behavioral measures of auditory processing in populations diagnosed with ASD. Tools such as dichotic word recognition and speech testing in the presence of a background competitor are two examples of behavioral measures of auditory processing that could provide additional insight into the auditory processing of a child with ASD. The ability to measure auditory processing abilities and identify deficits in individuals with ASD will provide more accurate understanding of the auditory characteristics of this disorder and assist in the development of evidence-based intervention methods. Further, patterns of difficulty on behavioral measures of auditory processing need to be linked with reports of abnormal behavioral responses to sounds in everyday contexts. Currently, no dedicated tool exists to categorize individuals diagnosed with ASD based on abnormal behavioral responses to sound. The Sensory Profile (Dunn 1999) is commonly used in interdisciplinary research and clinical practice to document sensory processing patterns in children with ASD. The scope of the Sensory Profile is broad capturing behaviors associated with difficulties across multiple sensory modalities and response types. While the Sensory Profile includes specific items related to auditory behaviors and may be useful for future comparisons to other assessment tools of the auditory domain, it is not a dedicated measure of auditory processing. Development of a dedicated measure that categorizes individuals diagnosed with ASD based on behavioral responses to sound will allow for in-depth analysis of auditory behavioral patterns across such a diverse group. The Auditory Behavior Questionnaire (ABQ) was developed to provide a clinically useful tool for categorizing and assessing the abnormal behavioral response to auditory stimulation reported in children with ASD. Unlike the Sensory Profile, the ABQ was developed specifically for assessment of the auditory domain in ASD. Dunning (2003) developed the foundation and item pool for this questionnaire from the results of a survey of parents and professionals working with children diagnosed with ASD. Participants (n = 175) provided observations regarding auditory behavior in children with ASD in an open-response format. A content analysis of the participants responses was then conducted by Dunning. Themes were identified in the data based on how frequently specific responses to sounds were reported. The process required the research team to conduct several reviews of the information and coding of similar observations. This analysis led to specific groupings of auditory behavior within the information provided by participants. As a result of this study, four behavioral domains that described much of the abnormal auditory response were hypothesized. These domain groupings were: difficulty in background noise; hypersensitivity to sound; unresponsiveness; and auditory seeking. The initial stage of questionnaire development concluded with the creation of the ABQ items based on the observations provided from participants. Statistical analysis of the ABQ is required to confirm the initial development findings. The aim of the current study was to examine preliminary reliability, construct validity and standardization of the ABQ. Specifically, this study (1) assessed the internal consistency of the ABQ, (2) revised the ABQ through item reduction, (3) evaluated the factor structure of the ABQ, and (4) developed a standardized scoring mechanism for the ABQ. Methods Participants Participants in the study were parents of children diagnosed with ASD. Participants were recruited from various on-line ASD communities, including the Interactive Autism Network (IAN), Autism Society of America, and local parent support groups in the central Ohio area. Participants were included in the study if they: (1) were the parent and/or legal guardian of a child (aged 7 21 years) with a diagnosis of ASD (based on parent report), (2) reported their child had normal hearing, and (3) completed all survey items. ASD diagnoses included in this study were Asperger s Disorder, Autistic Disorder/Autism, and Pervasive Developmental Disorder Not Otherwise Specified (PDD-NOS) (APA 1994). Materials and Procedures All the test materials were compiled into an on-line survey created through Survey Monkey (SurveyMonkey.com TM ).

3 980 J Autism Dev Disord (2013) 43: Initial questions on the survey pertained to the child s demographic information including age, specific ASD diagnosis, and details about the diagnosis (i.e. practitioner who made the diagnosis and tools used in assessment process). Demographic information was not obtained for the parents completing the survey (should I say why? My main reason is bc they weren t the focus of the study). The questions from the ABQ (Dunning 2003) comprised the final portion of the survey. The ABQ contained 60 items investigating the frequency of different behavioral responses to auditory stimulation. Participants were asked to rate how frequently different behavioral responses to sound occur in their children on a 5-point Likert scale (1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Very Often). One limitation of the initial distribution of the survey was an error in the format for one of the ABQ items. Two items were listed under the same question for the first 75 respondents. These two items were excluded from analysis based on this error. As the removed items were similar to others already included, the content of the scale was not considered to be compromised. A total of 58 items were included in initial analyses. Data Analysis Descriptive statistics were used to identify errors in the data and to characterize the sample. Reliability and validity of the ABQ items was then assessed. Cronbach s alpha was used to assess internal consistency (Study Aim 1). Interitem correlations were calculated for all items on the ABQ. Item pairs with correlations of 0.7 or above were identified and subjected to further analysis for item redundancy. Items with extremely low variability (same response from all subjects) or judged to be redundant were removed from the ABQ. Clinical judgment of the researchers informed analysis of item variability and assisted in the determination of which items were removed (Study Aim 2). Second, factor analysis was used to examine construct validity (Portney and Watkins 2009) (Study Aim 3). Factor analysis was completed using Principal Axis Factoring as an extraction method with promax rotation and Kaiser normalization using SPSS Version Descriptive statistics were computed for each resulting factor and a factor score was calculated using a weighted sum score method (DiStefano et al. 2009) (Study Aim 4). Items are grouped for each factor based on the factor loadings before a weighted sum score is computed. First, multiplying the item factor loading value to each item score creates a sum score for each factor. Second, all the weighted totals per item for each factor are summed for a total sum score, a.k.a. factor score. This method was done for all the items that loaded on factor 1, factor 2, factor 3 and factor 4. One advantage of the weighted sum score method is that items with the highest loadings on the factor have the largest effect on the factor score because different weights (i.e., factor loading values) are applied to each item. Once a standardized factor score was determined, normalized histograms and performance probability (P P) plots were analyzed for each standardized factor. The sum of the scores by factor was determined for all subjects included in the study providing preliminary standardization data for the ABQ. Results Participants A total of 174 responses were received from the distribution of the survey between December 2009 and March Nine participants were excluded based on the inclusion criteria five participants were excluded for not completing the survey items, one reported their child did not have an ASD diagnosis, and three reported their child had a diagnosed sensorineural hearing loss. Data from the remaining 165 participants were included in the analysis % of the children were identified by their parents as having a diagnosis of Autism or ASD % identified their child s diagnosis as Asperger s Syndrome and 21.8 % identified PDD-NOS as the diagnosis. Per parent report, the majority of ASD diagnoses were given by a multidisciplinary team (36.2 %) and/or psychologist (41.4 %) and 79 % were completed using a combination of parent interview and practitioner observation of the child. The majority of participants had a child between 7 and 9 years of age (37.9 %) while 21.9 % were between 10 and 12 years of age, 24.7 % were between 13 and 15 years of age, 13.2 % were between 16 and 18 years of age and 2.3 % was between 19 and 21 years of age. Internal Consistency Cronbach s alpha was 0.94 for the 58 ABQ items analyzed. This value is very close to 1.0 suggesting excellent reliability and provides evidence that the items measure a common underlying construct (George and Mallery 2003). Item Reduction Inter-item correlations were then calculated for all items on the ABQ to evaluate which items were redundant in nature. Removal of items that do not provide additional information reduces the burden associated with using the tool and potentially improves its measurement properties (Murphy and Davidshofer 2005). Item pairs with correlations of 0.70

4 J Autism Dev Disord (2013) 43: or above were identified and subjected to further analysis for possible item redundancy. Mean, median, standard deviation (SD) and skewness were computed for each item. Coefficient values for each item pair ranged from to Clinical judgment was used along with statistical results to dictate which items were removed. If two items were very similar and had a high correlation value then the less specific item was kept in the ABQ for better interpretation for future use. For example, item X (Cover his/ her ears to a sound) and item Y (Cover his/her ears to a loud sound) had a correlation value of 0.86 and the text was very similar. The researchers decided to keep item X since it was not a specific type of sound (i.e., loud versus quiet). Based on these guidelines for revision, a total of 18 items were removed leaving 40 total remaining ABQ items. Factor Analysis Factor analysis was completed on the remaining 40 items. The use of a scree plot graphing eigenvalues against potential factor models supports the evaluation of multiple factor models (Cattell 1966). Based on the scree plot, 4, 5, 6 and 7 factor models were evaluated (see Fig. 1). A 4-factor model was determined to best fit the data and supported the theoretical foundation proposed by Dunning (2003). Based on the pattern of item loadings, the 4-factors were named: (1) Difficulty in Background Noise, (2) Aversive Reactions, (3) Unresponsiveness, and (4) Stereotypic/Repetitive Behaviors. Table 1 displays item loadings for each factor. Standard Factor Scores Weighted sum scores were computed for each factor scores creating standardization data (see Fig. 2). A standard factor score close to zero suggests a child exhibits behaviors in that factor domain that are consistent with the majority of children in this sample, all of whom had ASD. If a child has a negative standard factor score then the child is not displaying many behaviors associated with that factor domain. A more positive standard factor score suggests the child displays more of the observed behaviors associated with that domain than other children in this sample with ASD. The use of standard factor scores will allow for comparison of individuals auditory behaviors with those of peers with ASD and the determination of patterns of abnormal behavioral performance across the four factors. Results from this study reaffirm that the ABQ is measuring the targeted auditory behaviors that were identified in the early stages of the tool s development. Confirmation of a factor structure further strengthens confidence in the future use of this tool in clinical settings. Discussion Preliminary results suggest that the ABQ is a reliable and valid tool in assessing behavioral responses to sound in children with ASD. Specifically, the factor structure revealed in this study matched previous hypotheses regarding the likely organization of these behaviors. The 4-factors, Fig. 1 A scree plot graphs the eigenvalues against the potential factor numbers. The eigenvalues represent the amount of variance explained by each factor

5 982 J Autism Dev Disord (2013) 43: Table 1 Item loadings by factor Table 1 continued ABQ item Factor loading value ABQ item Factor loading value Factor 1: Difficulty in background noise Have difficulty responding when there is a lot of noise around him/her Have trouble focusing on a task when people are talking around him/her Have trouble paying attention to you when there is background noise Avoid playing with other children that are yelling or screaming Appears distracted in a noisy environment Avoid situations due to the sounds in that environment Appear distressed by background noise or people talking around him/her Pay attention to someone speaking to them in a noisy environment Avoid noisy situations where they have trouble focusing Get distracted by a background noise (i.e. TV or radio) when they should be focusing Have difficulty paying attention to someone speaking to them in the presence of noise Factor 2: Aversive reactions Cover his/her ears to a sound Appear overly sensitive to sounds Appear stressed or anxious about sound that bothers him/her Get upset and cry over normal everyday sounds Cry when he/she hears a loud sound Avoid the flushing of a toilet due to the sound it makes Get upset at the sight of a vacuum/other device that makes loud noises Cover his/her ears when people are talking Cover his/her ears when people are talking Have a meltdown in a noisy room Get upset after an unexpected/startling sound occurs Factor 3: Unresponsiveness Not startle/react to unexpected sounds Appear unresponsive to others speaking to him/her Only respond when his/her name is called multiple times Target his/her listening to a person or conversation Have difficulty concentrating on what someone is saying to them Act like a child with a hearing loss Not respond to a loud sound in the environment around him/her Appear to require more time for a sound to register Factor 4: Stereotypic/repetitive behaviors Hum or repeat sounds he/she hears Get focused on a sound and ignore everything around him/her React to very faint or distant sounds Seek sounds for self-stimulation behaviors Detect sounds that others have a difficult time hearing or detecting Hold a loud toy or object to his/her ear for long periods of time Appear to focus attention on sounds around him/her Enjoy sounds that you think are too loud Verbally repeat sounds that are loud or bothersome Make a verbal sound over and over again and seem to enjoy it (1) Difficulty in Background Noise, (2) Aversive Reactions, (3) Unresponsiveness, and (4) Stereotypic/Repetitive Behaviors, align almost exactly with the initial hypothesized factor domains by Dunning (2003). Dunning s hypothesized groupings were: difficulty in background noise, hypersensitivity to sound, unresponsiveness, and auditory seeking behaviors. Results of the current experiment supported this basic domain structure. Two of the domains were renamed, however, to better reflect the nature of the difficulties experienced by children with ASD. Specifically, the domain of hypersensitivity to sound was renamed as aversive reactions. The domain of aversive reactions captures ABQ items assessing hypersensitive responses to sound. Additionally, the auditory seeking domain set forth by Dunning was renamed to stereotypic/repetitive behaviors. Again, the current domain includes auditory seeking behaviors but has a more global name that includes all the stereotypic/repetitive behaviors commonly seen in ASD but in this case are specific to auditory stimulation. These factors also align with theorized patterns of global sensory processing dysfunction proposed by Miller et al. (2007). In this schema, sensory processing difficulties are conceptualized as: Sensory Over-responsivity, Sensory Under-responsivity and Sensory Seeking. The addition of Difficulty in Background Noise in this study introduces a new category that may relate more to impairments in attention and filtering of sensory input. Future studies should examine whether this a specific feature of children with autism and sensory processing difficulties or whether it is evident in other diagnostic groups (e.g. ADHD). Although the main goals of the current study were met, limitations included no measure of test retest reliability of

6 J Autism Dev Disord (2013) 43: Fig. 2 Frequency histograms of standardized scores for each factor of the ABQ the responses submitted. Follow-up testing for test retest reliability was not possible due to the methodology for recruitment and the use of an on-line survey. Another limitation was age differences of the participants children. A broad age-range was captured in this study. The participants were representative of the entire age range (7 21 years), but the number of children within each age group varies which may have influenced the results. As previously mentioned, the majority of children (38.8 %) were within 7 9 years of age while only 0.6 % represented the age range. Overall the limitations were of minimal concern at this initial stage of ABQ development. Future research will aim to further evaluate the test retest reliability of the ABQ and response differences based on age, gender, symptom, behavior and cognitive profiles. Comparisons with typical developing peers as well as other diagnoses such as ADHD, intellectual disability as well as individuals with Auditory Processing Disorder that do not have ASD will provide important insights into the validity of the ABQ in ASD populations. Additionally, the concurrent validity of the ABQ requires investigation. Comparisons of the ABQ with more established measures of sensory processing such as the Sensory Profile (Dunn 1999) may provide additional information of a child or individual s sensory processing abilities across modality. Specifically comparing the auditory processing items of the Sensory Profile and the standard factor scores for the ABQ may be beneficial for further validation of the ABQ as an assessment tool of the auditory domain. Future clinical use of the ABQ will improve the specificity of parental reports and clinician observed auditory difficulties in children with ASD. Current auditory research in individuals with ASD is lacking a formal assessment tool to identify abnormal behavioral responses to auditory stimuli. Additionally, guidelines and expectations for assessing auditory processing abilities in individuals with ASD are not currently available. Not all children with ASD will exhibit deficits in auditory processing and abnormal auditory behaviors but those that do may benefit from more specialized intervention recommendations. An assessment tool, such as the ABQ, that categorizes ASD populations based on behavioral responses to auditory stimuli will allow for assessment of patterns of behavior when auditory concerns arise for certain children with ASD. Once a child is identified as having abnormal responses to sound, the use of behavioral measures, such as dichotic listening testing and word

7 984 J Autism Dev Disord (2013) 43: recognition testing in the presence of multitalker babble, can provide clinically useful measures of behavior and assess deficits in auditory processing abilities. Similarly, in regards to the selection of treatments, the ABQ may be useful in differentiating those individuals with ASD that exhibit atypical patterns of behavioral responses to sound or auditory processing deficits and could potentially benefit from an auditory intervention. Acknowledgments Subjects were recruited with the assistance of the Interactive Autism Network (IAN) Research Database at the Kennedy Krieger Institute and Johns Hopkins Medicine Baltimore, sponsored by the Autism Speaks Foundation. This research project was supported by student research grants to the first author from the Ohio Speech Language Hearing Association (OSHLA) and the Ohio State University Nisonger/LEND program (Grant #T73MC00049). Special thanks to Susan White Ph.D. for additional statistical support during this project. This project was completed as part of a doctoral dissertation. References Alcantara, J. I., Weisblatt, E. J., Moore, B. C., & Bolton, P. F. (2004). Speech-in-noise perception in high-functioning individuals with autism or asperger s syndrome. Journal of Child Psychology and Psychiatry and Allied Disciplines, 45(6), American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association. Ashburner, J., Ziviani, J., & Rodger, S. (2008). Sensory processing and classroom emotional, behavioral, and educational outcomes in children with autism spectrum disorder. The American Journal of Occupational Therapy: Official Publication of the American Occupational Therapy Association, 62(5), Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, Corbett, B. A., Shickman, K., & 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), DiStefano, C., Zhu, M., & Mîndrilă, D. (2009). Understanding and using factor scores: Considerations for the applied researcher. Practical Assessment, Research & Evaluation, 14(20). Available online: Dunn, W. (1999). The sensory profile: User s manual. San Antonio, TX: Psychological Corporation. Dunning, K. (2003). Development of a questionnaire to assess auditory behaviors in children diagnosed with autism spectrum disorders. Unpublished master s thesis, The Ohio State University, Columbus, OH. Egelhoff, K., Whitelaw, G., & Rabidoux, P. (2005). What audiologists need to know about autism spectrum disorders (ASD). Seminars in Hearing, 26, George, D., & Mallery, P. (2003). SPSS for windows step by step: A simple guide and reference update (4th ed.). Boston: Allyn & Bacon. Grandin, T., & Scariano, M. (1989). Emergence: Labeled autistic. California: Arena Press. Lane, A., Dennis, S., & Geraghty, M. (2011). Brief report: Further evidence of sensory subtypes in Autism. Journal of Autism and Developmental Disorders, 41(6), Lane, A., Young, R., Baker, A., & Angley, M. (2010). Sensory processing subtypes in autism: Association with adaptive behavior. Journal of Autism and Developmental Disorders, 40, Miller, L. J., Anzalone, M. E., Lane, S. J., Cermak, S. A., & Osten, E. T. (2007). Concept evolution in sensory integration: A proposed nosology for diagnosis. The American Journal of Occupational Therapy, 61, Murphy, K. R., & Davidshofer, C. O. (2005). Psychological testing: Principles and applications (6th ed.). Upper Saddle River, NJ: Pearson Education, Inc. Neysmith-Roy, J. M. (2001). The tomatis method with severely autistic boys: Individual case studies of behavioral changes. South African Journal of Psychology, 31(1), Portney, L., & Watkins, M. (2009). Foundations of clinical research: Applications to practice (3rd ed.). Upper Saddle River, NJ: Pearson Education, Inc. Rapin, I. (1991). Autistic children: Diagnosis and clinical features. Pediatrics, 87(5 Pt 2), Rimland, B., & Edelson, S. M. (1994). The effects of auditory integration training on autism. American Journal of Speech- Language pathology, 5, Rimland, B., & Edelson, S. M. (1995). Brief report: A pilot study of auditory integration training in autism. Journal of Autism and Developmental Disorders, 25(1), Steinschneider, M., & Dunn, M. (2002). Electrophysiology in developmental neuropsychology. In S. Segalowitz & I. Rapin (Eds.), Handbook of neuropsychology (2nd ed., pp ). Amsterdam: Elsevier Science B. V. Teder-Salejarvi, W. A., Pierce, K. L., Courchesne, E., & Hillyard, S. A. (2005). Auditory spatial localization and attention deficits in autistic adults. Cognitive Brain Research, 23(2 3), Wetherby, A. M., Koegel, R. L., & Mendel, M. (1981). Central auditory nervous system dysfunction in echolalic autistic individuals. Journal of Speech and Hearing Research, 24(3),

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