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. Author manuscript; available in PMC: 2024 Dec 6.
Published in final edited form as: Autism Res. 2023 Jun 28;16(7):1413–1424. doi: 10.1002/aur.2961

The prevalence and developmental course of auditory processing differences in autistic children

Bonnie K Lau 1, Katherine A Emmons 2, Adrian K C Lee 3,4, Jeff Munson 5, Stephen R Dager 6, Annette M Estes 2,3
PMCID: PMC11620991  NIHMSID: NIHMS2034746  PMID: 37376987

Abstract

Auditory processing differences, including hyper- or hyposensitivity to sound, aversions to sound, and difficulty listening under noisy, real-world conditions, are commonly reported in autistic individuals. However, the developmental course and functional impact of these auditory processing differences are unclear. In this study, we investigate the prevalence, developmental trajectory, and functional impact of auditory processing differences in autistic children throughout childhood using a longitudinal study design. Auditory processing differences were measured using the Short Sensory Profile, a caregiver questionnaire, in addition to adaptive behaviors and disruptive/concerning behaviors at 3, 6, and 9 years of age. Our results showed that auditory processing differences were reported in greater than 70% of the autistic children in our sample at all three timepoints, maintained a high prevalence through 9 years of age, and were associated with increased disruptive/concerning behaviors and difficulty with adaptive behaviors. Furthermore, in our sample of children, auditory processing differences at age 3 years predicted disruptive/concerning behaviors and difficulty with adaptive behaviors at age 9 years. These findings warrant further investigations of the potential benefit of incorporating measures of auditory processing during routine clinical evaluations as well as interventions targeting auditory processing differences in autistic children.

Keywords: auditory processing, autism, development, sensory processing

Lay Summary

We followed a cohort of autistic children longitudinally at 3, 6, and 9 years of age and found that more than 70% of the children had caregiver-reported difficulty listening in noisy environments at all three ages. These auditory processing differences were associated with increased hyperactivity and agitation as well as difficulty with daily living skills, suggesting that auditory processing differences should be considered during routine clinical evaluations.

INTRODUCTION

Autism spectrum disorder (ASD) is a neurodevelopmental disability characterized by difficulties with social communication and interaction, as well as restricted interests and repetitive behaviors, according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (American Psychiatric Association, 2013). Characteristics of ASD present early in development and affect a range of behaviors including reduced eye contact, differences in verbal and nonverbal communication, repetitive motor movements, and heightened or reduced sensitivity to sensory input. In the United States, 1 in 36 children are estimated to have ASD, with boys 3.8 times more likely to be diagnosed than girls (Maenner et al., 2023). Early behavioral intervention has been shown effective in improving cognitive and behavioral outcomes in autistic children, highlighting the importance of early screening and detection (Dawson et al., 2010; Klintwall et al., 2015; Vietze & Lax, 2020).

Differences in sensory processing have long been reported in autistic adults and children. Specific differences may include seeking out or avoiding visual stimulation, increased sensitivity to loud noises, and avoidance of certain sounds and textures (e.g., Leekam et al., 2007; O’Connor, 2012; Thye et al., 2018). Under the current diagnostic criteria, sensory processing differences are a core feature of ASD, related to restrictive and repetitive behaviors. Atypical responses to sensory stimuli are common, with estimates of prevalence ranging from 70%–90% (Baranek et al., 2006; Kirby et al., 2022; Klintwall et al., 2011; Leekam et al., 2007; Tomchek & Dunn, 2007), and occur across all ages, levels of symptom severity, and sensory modalities (Ben-Sasson et al., 2009; Kern., 2006; O’Donnell et al., 2012; Tomchek & Dunn, 2007; Tomchek et al., 2014). While the prevalence of sensory processing differences in autism is well established, the developmental trajectory of sensory processing differences is less clear. Research on the topic has varied; some studies show decreases in sensory symptoms across childhood (Cheung & Siu, 2009), while others show no changes in symptoms (Green et al., 2012; McCormick et al., 2016; Perez Repetto et al., 2017). The present study aims to elucidate the development of sensory processing differences in individual autistic children between the ages of 3 and 9 years.

Successful integration of sensory input is crucial for daily functioning. In autistic adults and children, sensory processing challenges contribute to differences in social interaction and communication and affect daily functioning and academic performance (Dellapiazza et al., 2018; Howe & Stagg, 2016; Kojovic et al., 2019; Suarez, 2012; Thye et al., 2018). Sensory processing differences are also associated with increased behavioral and emotional difficulties (Baker et al., 2008), lower adaptive functioning (Kojovic et al., 2019), increased social impairments (Hilton et al., 2010; Kern et al., 2007), and parental stress (Ben-Sasson et al., 2013). In young autistic children, early sensory dysregulation may hinder the development of joint attention, language, and social play (Baranek et al., 2013; Miller Kuhaneck & Britner, 2013). A growing body of research suggests atypical responses to sensory input may precede differences in social interaction and communication, wherein early neural dysfunction produces cascading effects on social development (Baranek et al., 2018; Damiano-Goodwin et al., 2018). Infants who go on to develop autism show increased sensory seeking compared to those who do not, leading to reduced social orienting and increased social symptom severity (Baranek et al., 2018). Thus, early screening for sensory processing differences may play a role in early detection of autism.

As with other sensory modalities such as visual sensitivity, auditory processing differences are frequently reported in autistic adults and children. Commonly reported auditory symptoms include hyper- or hyposensitivity to sound, aversions or unusual interest in specific sounds, and difficulty listening in noisy environments (see O’Connor, 2012 for review). Furthermore, some evidence suggests behavioral differences are more closely linked to auditory processing differences compared to other sensory domains (Germani et al., 2014).

Prior behavioral and neurophysiological research suggests alterations in auditory processing may be an early marker for autism (Germani et al., 2014; Miron et al., 2021; Riva et al., 2018). In a recent study, parent reports of auditory processing differences at 24 months of age were associated with subsequent ASD diagnoses at age 3 years in infants with familial likelihood for autism (Germani et al., 2014). Similarly, differences in auditory event-related potentials recorded by electroencephalography (EEG) at age 12 months were associated with expressive vocabulary and critical M-CHAT items at age 20 months in infants at high likelihood of developing autism because they have an autistic sibling (Riva et al., 2018). Based on the retrospective analysis of newborn hearing screening data, infants who were later diagnosed with autism had longer auditory brainstem response latencies compared to infants who did not go on to develop autism, suggesting neurophysiological variation may be present at birth in infants who go on to develop autism (Miron et al., 2021).

Here, we aim to investigate the prevalence, developmental trajectory, and functional impacts of reported auditory processing differences in autistic children using a longitudinal study design. The Short Sensory Profile (SSP; McIntosh et al., 1999), a widely used caregiver questionnaire, was chosen as a measure of sensory processing differences in our sample. Functional behaviors were assessed using the Vineland Adaptive Behavior Scales (VABS; Sparrow & Cicchetti, 1989) and the Aberrant Behavior Checklist (ABC; Aman & Singh, 1986). The research questions under investigation were:

  1. What is the prevalence of reported auditory processing differences in this longitudinal sample?

  2. What is the developmental course of auditory processing differences across childhood, from age 3 years to 9 years?

  3. What are the functional consequences of auditoryprocessing differences in autistic children?

METHODS

Participants

Data from a larger longitudinal study on the neurobiology and developmental course of autism conducted at an autism center at a major university, was retrospectively analyzed. The full study sample consisted of 74 children who were diagnosed with ASD at age 3, with data obtained between 1990s and 2000s for this initial time point. This cohort of participants were then followed at 6 and 9 years of age. Children who had a history of sensory or motor impairment including hearing loss, traumatic brain injury, major physical anomalies, genetic disorders associated with ASD such as Fragile X, or other neurological impairments were excluded (see Dawson et al., 2004 for further details). An initial research diagnosis according to the DSM-IV (American Psychiatric Association, 2000) criteria was established at 3 years of age by a licensed clinical psychologist or a qualified graduate student in clinical psychology using: (1) the Autism Diagnostic Interview-Revised (ADI-R; Rutter et al., 2003), a standardized parent interview; (2) the Autism Diagnostic Observation Schedule-Generic (ADOS-G; Lord et al., 2003), a standardized semi-structured play observation, scored with the revised algorithm to increase comparability across modules 1–3 (Gotham et al., 2007); (3) medical and family history; (4) cognitive test scores; and (5) clinical observation and judgment. This diagnostic battery was repeated at 6 years and 9 years of age. Mothers in this sample were highly educated on average; 85% had a graduate degree, bachelor’s degree or some college education while 15% of mothers had a high school degree or less. There were 14 female participants in the sample and ethnicities represented include: White (68%), Asian (2%), African American (5%), More than one race (16%), and Unknown (9%).

All children with data on the SSP at one or more time points were included in this analysis: SSP data was obtained from 49 children at 3 years, 29 at 6 years, and 52 at 9 years of age. As parents were given the option to opt out of completing the SSP at each time point, the SSP was obtained at only one time point for 20 children and at two time points for 34 children. For 14 children, SSP data was obtained at all three time points. Written informed consent was obtained from a parent or legal representative prior to participation in this study.

Procedure

Reported sensory processing differences, adaptive behaviors, disruptive/concerning behaviors, cognition, and vocabulary were measured at 3, 6 and 9 years of age. Descriptive data for the study sample are provided in Table 1.

TABLE 1.

Descriptive data for study sample – Mean (SD), range italicized below

3 years
 6 years
 9 years
36–59 months 68–91 months 109–124 years
Sensory processing N = 49 N = 29 N = 52
 SSP total score 159.67(23.17) 153.58 (29.36) 155.98(25.32)
97–199 59–189 90–206
 Auditory filtering 19.23(4.32) 20.06(3.75) 19.00(4.12)
7–26 13–30 6–28
Symptom severity N = 49 N = 29 N = 52
 ADOS severity score 6.59(1.67) 7.28(1.87) 7.50(2.11)
2–10 3–10 1–10
Adaptive behavior N = 49 N = 52
 VABS-C 60.32(9.40) 54.10(20.17)
48–84 21–108
Disruptive/concerning behavior N = 49 N = 27 N = 52
 ABC-AG 10.92(7.93) 10.26(7.36) 9.50(9.52)
1–35 0–31 0–38
 ABC-HYP 15.45(9.82) 13.81(8.11) 12.96(10.08)
1–41 0–27 0–42
Cognition N = 47 N = 29 N = 50
 MSEL-C 58.83(15.31)
49–106
 DAS-GCA 65.52(21.08) 79.30(24.68)
44–105 45–134
Expressive vocabulary N = 45 N = 23 N = 31
 CDI – Produced 10.76(9.84)
0–48
 EVT 72.04(24.41) 88.74(15.08)
40–115 55–128
Receptive vocabulary N = 45 N = 24 N = 46
 CDI – Understood 36.78(51.93) 71.63(23.92) 80.28(28.76)
 PPVT-III 2–205 40–108 40–148
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Measures

Sensory processing

Sensory processing was assessed using the SSP, a standardized 38-item caregiver questionnaire developed to identify children with sensory processing difficulties and associated behaviors (McIntosh et al., 1999). Each item on the SSP is rated on a Likert scale ranging from 1 to 5 with a score of 1 assigned to behaviors that are “always” occurring and a score of 5 assigned to behaviors that are “never” occurring. Thus, a lower score indicates a higher occurrence of sensory processing difficulties. The item raw scores are aggregated into 7 subscale scores: Tactile Sensitivity, Taste/Smell Sensitivity, Movement Sensitivity, Underresponsive/Seeks Sensation, Auditory Filtering, Low Energy/Weak, and Visual/Auditory Sensitivity. For each subscale score as well as the SSP Total score, cutoff points based on the normative sample are provided for classification into the categories of Typical Performance, Probable Difference (−1 to −2 SDs below the mean) and Definite Difference (>2 SDs below the mean). For the Auditory Filtering subscale, this equates to a subscale score of 30–23 for Typical Performance, 22–20 for Probable Difference, and 19–6 for Definite Difference. For the SSP Total score, this equates to a total score of 190–155 for Typical Performance, 154–142 for Probable Difference, and 141–38 for Definite Difference. The normative scores were established from the full-length Sensory Profile (Dunn, 1999), which was standardized on 1037 typically developing children.

To determine the prevalence of auditory processing differences in the study sample, the percentage of children with Auditory Filtering Subscale Scores in the Probable Difference and Definite Difference range was quantified. The prevalence of Auditory Filtering differences relative to other domains was determined by comparing across the 7 subscale scores. The six items in the Auditory Filtering subscale capture hyposensitivity to sound and difficulty attending to or tuning out sound in a noisy environment (items shown in Table 2).

TABLE 2.

SSP auditory filtering items

Item Subscale
22. Is distracted or has trouble functioning if there is a lot of noise around Auditory filtering
23. Appears to not hear what you say (e.g., does not ‘tune in’ to what you say, appears to ignore you) Auditory filtering
24. Cannot work with background noise (e.g., fan, refrigerator) Auditory filtering
25. Has trouble completing tasks when the radio is on Auditory filtering
26. Does not respond when name is called but you know the child’s hearing is OK Auditory filtering
27. Has difficulty paying attention Auditory filtering
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For participants with missing data on the SSP, the average of the remaining scores in the subscale was calculated, and this value replaced the missing score(s) in that subscale. This approach was selected to control for bias while still maintaining representation of the participant’s sensory profile. One SSP at 9 years was excluded because more than 20% of the items were incomplete.

Symptom severity

The ADOS-G, a semi-structured standardized measure that assesses social interaction, communication, play, and repetitive behaviors was administered to all participants as part of the initial diagnostic confirmation process at 3 years of age and repeated at age 6 and 9. The ADOS-G module administered was selected based on language level of the participant, sometimes resulting in different modules administered for a specific child at different timepoints, depending on their language level at the time of testing. The revised algorithm was used to score the ADOS-G (Gotham et al., 2007), which was designed to improve comparison across modules 1 to 3. To examine symptom severity, the calibrated severity metric from Gotham et al., 2009 was used. This severity metric provides a method for quantifying ASD symptom severity on a 10-point scale with relative independence from effects of age and verbal IQ. These calibrated severity scores were found to have more uniform distributions across age and language ability compared to raw scores (Gotham et al., 2009). This metric was chosen as the autism severity measure in this study because it enables the comparison of scores across time, age, and ADOS module and is less influenced by verbal IQ than the raw scores. It is important to note that this severity score provides an estimate of severity of autism symptoms relative to age and language level but does not measure functional impairment.

Assessment of functional behaviors

Personal and social functioning was assessed with the Vineland Adaptive Behavior Scales (VABS; Sparrow & Cicchetti, 1989), a standardized 297-item parent interview. The VABS assesses adaptive behaviors in four domains: communication, daily living skills, socialization, and motor, with norms derived from a sample of 4800 individuals with and without disabilities. The VABS Adaptive Behavior Composite (VABS-C) is calculated from the four domain scores. As only two of the four VABS domains were administered at age 6, the VABS-C was obtained only at 3 years and 9 years of age. Thus, analyses involving the VABS-C were not conducted at the 6-year time point.

Disruptive and concerning behaviors were measured with the Aberrant Behavior Checklist (ABC; Aman & Singh, 1986), a 58-item parent report measure. The items belong to five subscales: (1) Irritability, agitation, crying; (2) lethargy, social withdrawal; (3) stereotypic behavior, (4) hyperactivity, non-compliance; and (5) inappropriate speech. Each item is scored on a scale of 0–3 with 0 indicating “not at all a problem” and 3 indicating “the problem is severe in degree”. Thus, a higher score indicates a higher occurrence of disruptive/concerning behaviors. To investigate the effect of sensory processing on mood and behavior, the analyses in this study focus on the Agitation (ABC-AG; irritability, agitation, crying) and Hyperactivity (ABC-HYP; hyperactivity, noncompliance) subscales.

Intellectual ability was assessed with the Mullen Scales of Early Learning (MSEL; Mullen, 1995) at age 3. The Early Learning Composite (MSEL-C) is calculated from the Visual Reception, Receptive Language, Expressive Language and Fine Motor subscale T scores. At ages 6 and 9, cognition was assessed with the Differential Abilities Scale (DAS; Elliott, 1990), a battery of tests used to measure verbal, reasoning, perceptual, and memory skills. The School Age Level administered included six core subtests, yielding the General Conceptual Ability standard score (DAS-GCA).

Expressive and receptive vocabulary at age 3 was assessed with the MacArthur-Bates Communicate Development Inventories-Words and Gestures (CDI-WG), a parent report measure. At age 6 and 9, the Expressive Vocabulary Test (EVT; Williams, 1997) and the Peabody Picture Vocabulary Test – 3rd Edition (PPVT-III; Dunn,, & Dunn., 1997) was administered with each child. The standard score for each measure is reported in Table 1.

Statistical analysis

To address the prevalence of auditory processing differences in this longitudinal sample, we quantified the number of participants that reported a “probable or definite difference” on the auditory filtering subtest of the SSP. We further assessed whether the percentage of participants with reported differences on the Auditory Filtering Subscale Score was statistically different than other subscales using Fisher exact tests. Next, to characterize the developmental course of auditory processing differences from 3 to 9 years of age, a general linear mixed effects model (GLMM) was used. As secondary analyses, two additional GLMMs were run to control for intellectual ability and symptom severity. To compare the developmental course of auditory processing to overall sensory processing differences, change in the SSP Total score over time was also assessed using a GLMM. To investigate the functional consequences of auditory processing difference, the association between the Auditory Filtering Subscale Score and disruptive/concerning behavior, adaptive behavior, symptom severity, cognition, and vocabulary scores at 3 and 9 years of age was assessed using Pearson Correlation coefficients. Finally, the predictive relationship of reported auditory processing differences at 3 years with agitation, hyperactivity, adaptive behaviors, and symptom severity at 9 years was further assessed using linear regression. As secondary analysis, two additional linear regressions for each significant predictor variable to control for intellectual ability and symptom severity was conducted. To provide additional context to interpret the predictive ability of the Auditory Filtering Subscale Score at age 3, two additional linear regressions were conducted to investigate whether the Auditory Filtering Subscale Score at age 3 predicted the same subscale score at age 9 and whether the ABC-HYP score at 3 years predicted the ABC-HYP score at 9 years. All tests were evaluated against at two-tailed p < 0.05 level of significance.

RESULTS

Prevalence of reported auditory filtering differences across time

SSP scores were first analyzed to determine the prevalence of reported auditory processing differences in the study sample. Figure 1 shows the percentage of children with scores in the Definite or Probable Difference range across SSP subscales at each time point. A large proportion of children reported sensory processing differences, especially in the auditory domain. More than 70% of children scored within the Definite or Probable Difference range on the Auditory Filtering subscale at each time point; and the prevalence increased over time. These numbers were consistent with the overall high percentage of children in the sample that were rated as having some degree of sensory processing difference based on the SSP Total score: 76% at 3 and 6 years and 81% at 9 years. Auditory Filtering had the highest percentage of reported difference of any subscale at all three time points. However, at 3 years, the difference between the percentage of children with reported sensory processing differences in the Auditory Filtering subscale reached statistical significance only in comparison to the Low Energy/Weakness (p < 0.001, fisher exact test) and the Movement Sensitivity subscale (p < 0.001, fisher exact test; p > 0.05 for all other subscales). At 6 years, the difference reached statistical significance in comparison to the Movement Sensitivity subscale only (p < 0.001, fisher exact test; p > 0.05 for all other subscales). By 9 years of age, the number of children with a reported difference in Auditory Filtering (80%) surpassed all other subscales (<60% for all others). This difference was statistically significant for the the Low Energy/Weakness (p < 0.001, fisher exact test), Movement Sensitivity (p < 0.001, fisher exact test), and the Visual/Auditory Sensitivity subscale (p = 0.03, fisher exact test; p > 0.05 for all other subscales).

FIGURE 1.

FIGURE 1

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Percentage of children with reported sensory processing differences in the Definite Difference, Probable Difference, and Typical Performance range in each subscale of the SSP at 3 (n = 49), 6 (n = 29), and 9 (n = 52) years of age.

Developmental course of reported auditory processing differences

To investigate the developmental course of reported auditory processing differences, change in the Auditory Filtering Subscale Score over time was assessed. For most subjects, the Auditory Filtering Subscale Score appeared to remain stable across the three time points (Figure 2). A general linear mixed model with the SSP Auditory Filtering Subscale Score as the dependent variable, timepoint as a fixed effect, and a random intercept and a random slope for timepoint was fit according to the equation as follows (Equation (1)):

AuditoryFilteringSubscaleScoreij=β0+β1timepointij+ϕi,0+ϕi,1timepointij+ϵij (1)

where β1 is the fixed effect of time point (3, 6, or 9 years), the primary effect of interest, and ϵij is an error term (Table 3). This model was selected for its ability to handle children with missing data from one or more time points and its ability to capture individual variability across subjects: the random intercept accounts for variability in the Auditory Filtering Subscale Score while the random slope captures variability in how the score changes over time for each subject. The random effects were modeled with an autoregressive covariance structure, which considers correlation to be highest for adjacent time points. Results of the model revealed no significant fixed effect of time point (p = 0.70) confirming that SSP Auditory Filtering Subscale Score remained stable from 3 to 9 years of age.

FIGURE 2.

FIGURE 2

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SSP Auditory Filtering Subscale Score as a function of time point (n = 49 at 3 years, n = 29 at 6 years, and n = 52 at 9 years of age). Individual participant trajectories are color-coded with red indicating definite difference, green indicating probable difference, and blue indicating typical performance. Large gray circle showing mean at each time point.

Table 3.

Linear mixed effect model output for change in SSP auditory filtering subscale score over time

Fixed effects β estimate 95% confidence intervals p-value
Base Model – Fixed effect of time point, random slope and intercept
Intercept 19.55 17.98, 21.12 <0.001
Time point −0.14 −0.88, 0.59 0.70
Model controlling for cognition
Intercept 19.24 16.68, 21.80 <0.001
Time point −0.08 −0.93, 0.77 0.84
Intellectual ability 0.002 −0.04, 0.04 0.89
Model controlling for ADOS severity score
Intercept 21.85 19.03, 24.67 <0.001
Time point 0.03 −0.72, 0.78 0.93
ADOS severity −0.37 −0.76, 0.01 0.056
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During secondary analyses, two additional models were run to control for intellectual ability and symptom severity. In the first model, standard scores for the cognitive assessments administered at each time point were entered into the base model as a covariate. The model results revealed that intellectual ability was not a significant covariate (p = 0.89). After adjusting for intellectual ability, the fixed effect of time point remained non-significant (p = 0.84). In the second model, the symptom severity score from the ADOS obtained at each time point was entered as a covariate. Model results revealed that the ADOS Severity Score was a not a significant covariate (p = 0.06). Again, after controlling ADOS Severity Score the fixed effect of time point did not reach significance (p = 0.94). Results of these additional models provide further evidence that even after controlling for intellectual ability and symptom severity, the Auditory Filtering Subscale Score is comparable at all three time points.

Finally, to compare the developmental course of auditory processing to overall sensory processing differences, change in the SSP Total score over time was assessed using a general linear mixed model with the SSP Total score as the dependent variable, timepoint as a fixed effect, and a random intercept and a random slope for timepoint. Results of the model revealed no significant fixed effect of time point (p = 0.38) showing that SSP Total score also remained stable from 3 to 9 years of age.

Relationship between auditory processing and functional behaviors

The association between the Auditory Filtering Subscale Score and disruptive/concerning behavior, adaptive behavior, symptom severity, cognition, and vocabulary scores at 3 and 9 years of age was assessed using Pearson Correlation coefficients (Table 4). This analysis was not conducted at age 6 due to missing data; SSP data was obtained from only 29 children and the VABS-C was not obtained at this time point.

TABLE 4.

Correlations between SSP auditory filtering score and functional behaviors

3 years
 9 years
r (N) r (N)
Adaptive behavior
 VABS-C 0.35 (44)** 0.35 (50)**
Disruptive/concerning behaviors
 ABC-AG −0.56 (49)** −0.40 (52)**
 ABC-HYP −0.68 (49)** −0.51 (52)**
Symptom severity
 ADOS severity score −0.33 (49)** −0.13 (52)
 Intellectual ability 0.16 (47) 0.001 (50)
Vocabulary
 Expressive 0.16 (47) −0.11 (31)
 Receptive −0.10 (45) −0.10 (46)
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Note: Pearson correlations,

*

p < 0.05,

**

p < 0.01 level (2-tailed).

At age 3, there was a highly significant correlation between the Auditory Filtering Subscale Score and the ABC-HYP, the ABC-AG, the VABS-C and the ADOS severity score (Figure 3a, p < 0.02 in all cases). There was a strong association between the Auditory Filtering Subscale Score and the two ABC scores, with more reported auditory processing differences correlated to increased agitation and hyperactivity. There was also a moderate association between the Auditory Filtering Subscale Score and symptom severity as well as adaptive behaviors, with more reported auditory processing differences correlated to higher symptom severity and increased difficulty with adaptive behaviors.

FIGURE 3.

FIGURE 3

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(a) Relationship between SSP Auditory Filtering Subscale Score and ABC-HYP, ABC-AG, VABS-C, and ADOS Severity Score at age 3 years. (b) Relationship between SSP Auditory Filtering Subscale Score and ABC-HYP, ABC-AG, VABS-C, and ADOS Severity Score at age 9 years.

By age 9, similar patterns of association were observed with a highly significant correlation between the ABC-HYP, the ABC-AG, and the VABC-C (Figure 3b, p < 0.01 in all cases). Thus, at both time points, reported auditory processing differences were associated with increases in disruptive/concerning behaviors and difficulty with adaptive behaviors. However, the association with symptom severity by 9 years of age was no longer significant (Figure 3b, p = 0.256). At both time points, no correlation between reported auditory processing differences, intellectual ability, or vocabulary scores was observed (p > 0.05 in all cases).

The predictive relationship of reported auditory processing differences at 3 years with agitation, hyperactivity, adaptive behaviors, and symptom severity at 9 years was further assessed using linear regression. Only the subset of children with data on all of these measures at both 3 and 9 years of age were included in this analysis (n = 36). Four separate linear regression models were run with the Auditory Filtering Subscale Score as the predictor variable (Figure 4). The model results indicated that the Auditory Filtering Subscale Score at age 3 was a significant predictor for agitation, hyperactivity, and adaptive behaviors but not symptom severity at age 9 (see model results in Table 5). For disruptive/concerning behaviors, the Auditory Filtering Subscale Score at age 3 explained 19% of the variance in the ABC-AG scores and 17% of the variance in the ABC-HYP scores at age 9. A one-point increase in the Auditory Filtering Subscale Score resulted in a 0.96 decrease in ABC-AG and a 0.95 decrease in the ABC-HYP scores. For adaptive behaviors, the Auditory Filtering Subscale Score at age 3 explained 12% of the variance of the VABS-C score at age 9 and a one-point increase in the Auditory Filtering Subscale Score resulted in a 1.48 improvement in VABS-C score. For symptom severity, the relationship between the Auditory Filtering Subscale Score at age 3 and the ADOS severity score at age 9, was not significant (p = 0.17).

FIGURE 4.

FIGURE 4

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Relationship between SSP Auditory Filtering Subscale Score at 3 years and ABC-HYP, ABC-AC, VABS-C and ADOS Severity Score at 9 years.

TABLE 5.

SSP auditory filtering subscale score at 3 years predicts functional behaviors at 9 years (n = 36)

Coefficient 95% Confidence intervals p-value Adjusted R2
ABC-AG −0.96 −1.60 – −0.32 0.005 0.19
ABC-HYP −0.96 −1.64 – −0.28 0.007 0.17
VABS-C 1.48 0.17–2.80 0.03 0.12
ADOS severity −0.11 −0.26 – 0.05 0.17 0.03
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During secondary analyses, two additional linear regressions were conducted for each significant predictor variable (agitation, hyperactivity, and adaptive behaviors) to control for intellectual ability and symptom severity. In the first set of models controlling for intellectual ability, standard scores for the cognitive assessments administered at age 9 were entered into the base model as a covariate. The results revealed that intellectual ability was not a significant covariate (p > 0.05) for the ABCAG and the ABC-HYP, and that the Auditory Filtering Subscale Score at age 3 remained a significant predictor of both measures at age 9 (ABC-AG: p = 0.009; ABC-HYP: p = 0.01). For the VABS-C, intellectual ability was a significant covariate (p < 0.001) and the Auditory Filtering Subscale Score at age 3 also remained a significant predictor (p = 0.005). In the second set of models controlling for symptom severity, the ADOS Severity Score obtained at age 9 was entered as a covariate. Model results revealed that the ADOS Severity Score was a not a significant covariate (p > 0.05) for the ABC-AG, ABC-HYP, and VABS-C models although the Auditory Filtering Subscale Score at age 3 remained a significant predictor for the ABC-AG (p = 0.007) and the ABC-HYP (p = 0.01) at age 9 and is emerging significance for the VABS-C (p = 0.05). Results of these additional models provide further evidence that even after controlling for intellectual ability and symptom severity, the Auditory Filtering Subscale Score at age 3 is predictive of agitation, hyperactivity, and adaptive behaviors at 9 years.

To provide additional context to interpret the predictive ability of the Auditory Filtering Subscale Score at age 3, two additional linear regression models were conducted to investigate (1) whether the Auditory Filtering Subscale Score at age 3 predicted the same subscale score at age 9 and (2) whether the ABC-HYP score at 3 years predicted the ABC-HYP score at 9 years. The results of the first model revealed that the SSP Auditory Filtering Subscale Score at 3 years did significantly predict the SSP Auditory Filtering Subscale Score at 9 years (β =0.45, p = 0.001) and accounted for 25% of the variance in the age 9 scores, which is greater than for agitation (19%), hyperactivity (17%), and adaptive behavior (12%). The results of the second model revealed that the ABC-HYP score at 3 years also significantly predicted the ABC-HYP score at 9 years (β =0.53, p = 0.0004) and accounted for 29% of the variance in the age 9 scores, which is greater than the amount of variance accounted for by the Auditory Filtering Subscale score at 3 years (17%).

DISCUSSION

Results from this study reveal four main findings. First, a large proportion (>70%) of children had auditory processing differences across childhood (age 3, 6, and 9 years). Second, the proportion of participants with reported auditory processing differences was stable across these ages. Third, auditory processing differences at ages 3 and 9 years were associated with increased disruptive/concerning behaviors and difficulty with adaptive behaviors. Finally, reported auditory processing differences at age 3 years predicted disruptive/concerning behaviors and difficulty with adaptive behaviors at 9 years. These auditory processing challenges may have significant implications for functioning in the school environment, where children must cope with high levels of noise and distractions. Thus, these findings suggest that caregivers, educators, and service providers should consider implementing environmental modifications to support learning and participation of autistic school-age children.

These findings are consistent with prior literature. Tomchek and Dunn (2007) observed differences in the Auditory Filtering subscale of the SSP in over 75% of their sample of autistic children aged 3 to 6 years. McCormick et al. (2016) demonstrated no significant change in SSP total scores or subscale scores in autistic children between ages 2 and 8 years. Associations between sensory processing differences and increased disruptive/concerning behaviors and difficulty with adaptive behaviors in autistic adults and children have been reported in prior studies (Baker et al., 2008, 2008; Hilton et al., 2010; Kern et al., 2007; O’Donnell et al., 2012). In other words, parents reported auditory processing differences more than any of the other domain of the SSP at age 9 years. In a cross-sectional study of young autistic children and adults aged 32 months to 38 years, Leekam et al. (2007) found that auditory symptoms were consistent between age groups, while symptoms in other domains (e.g., oral) were less common in older participants. Our findings expand on the current literature by demonstrating that auditory processing differences are stable and elevated not just across age groups, but within the same individual across childhood (age 3–9).

Also significant was the finding that auditory processing differences at age 3 years predicted disruptive/concerning behaviors and difficulty with adaptive behaviors, at age 9 years. That is, auditory processing differences in early childhood were correlated with poorer outcomes in later childhood. This finding underscores the importance of comprehensive clinical evaluations that include measures of auditory processing function in autistic children. Moreover, it suggests interventions targeting auditory processing differences in early childhood may be particularly beneficial for future adaptive functioning. Future studies should evaluate whether auditory processing interventions improve outcomes for young autistic children.

The linear mixed model investigating the developmental course of auditory processing differences revealed that symptom severity, as measured by the ADOS severity score, was close to reaching statistical significance (p = 0.06). It remains possible that with a different measure of severity or a different participant sample that autism symptom severity may be a significant covariate to auditory processing differences.

There are several limitations to the present study. First, this study focused on caregiver-reported differences rather than physiological or behavioral measure of auditory alterations. Direct measure of sensory processing may provide more objective data and could help reveal mechanisms related to sensory alterations. While many aspects of the underlying neurophysiology of sensory processing alterations in autism is not well understood, there is some emerging evidence to suggest a common neurophysiological basis for restrictive and repetitive behaviors and structural properties of cerebellar and corpus collosum white matter in infants who go on to develop ASD (Wolff et al., 2017). Recent research has also begun to identify associations between basic auditory processing and severity of autism symptoms (Brandwein et al., 2014). Future research should aim to elucidate the neurophysiological underpinnings of sensory processing differences and how they may relate to early brain changes associated with ASD. Second, the focus of this study was on the items in the Auditory Filter Subscale of the SSP (see Table 2 for list of items). However, there are additional auditory perceptual differences, including hyper- or hypo-sensitivity to sound as well as sound aversions or attractions that are often reported by autistic individuals not included in this subscale. Although the proportion of participants with reported auditory perceptual differences are high (>70%) at all timepoints, Figure 2 suggests that there are potentially 3 developmental trajectories observed: those for whom auditory processing difficulties remain stable, those who improve, and those for who symptoms worsen. Future studies with a larger sample size are needed to better identify these three subtypes and to better understand what might lead to these different trajectories. It is possible that some children in this study may have received community-based intervention that targeted the items on the Auditory Filtering subtest, which may have affected whether auditory perceptual differences changed over time. Future randomized clinical trials should be conducted to determine the impact of interventions to improve auditory processing.

In conclusion, results from this study demonstrate (1) auditory processing differences are common in autistic children aged 3 to 9 years, (2) the prevalence of auditory processing differences high from 3 to 9 years of age, greater than 70% in this sample, (3) reported auditory processing differences at ages 3 and 9 years are associated with increased disruptive/concerning behaviors and difficulty with adaptive functioning and (4) auditory processing differences at age 3 years predict disruptive/concerning behaviors and difficulty with adaptive behaviors at age 9 years. These findings suggest the potential benefit of incorporating measures of auditory processing during clinical evaluations conducted in autistic children and developing interventions targeting auditory processing differences in early childhood.

ACKNOWLEDGMENTS

We thank the participants and their families for their participation in this research.

Footnotes

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

REFERENCES

  1. Aman MG, & Singh NN (1986). Aberrant behavior checklist. Slosson. [Google Scholar]
  2. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders, fourth edition, text revision (DSM-IV-TR) (Vol. 1, 4th ed.). American Psychiatric Association. 10.1176/appi.books.9780890423349 [DOI] [Google Scholar]
  3. American Psychiatric Association (Ed.). (2013). Diagnostic and statistical manual of mental disorders: DSM-5. American Psychiatric Association. [Google Scholar]
  4. Baker AEZ, Lane A, Angley MT, & Young RL (2008). The relationship between sensory processing patterns and behavioural responsiveness in autistic disorder: A pilot study. Journal of Autism and Developmental Disorders, 38(5), 867–875. 10.1007/s10803-007-0459-0 [DOI] [PubMed] [Google Scholar]
  5. Baranek GT, David FJ, Poe MD, Stone WL, & Watson LR (2006). Sensory experiences questionnaire: Discriminating sensory features in young children with autism, developmental delays, and typical development. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 47(6), 591–601. 10.1111/j.1469-7610.2005.01546.x [DOI] [PubMed] [Google Scholar]
  6. Baranek GT, Watson LR, Boyd BA, Poe MD, David FJ, & McGuire L (2013). Hyporesponsiveness to social and nonsocial sensory stimuli in children with autism, children with developmental delays, and typically developing children. Development and Psychopathology, 25(2), 307–320. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Baranek GT, Woynaroski TG, Nowell S, Turner-Brown L, DuBay M, Crais ER, & Watson LR (2018). Cascading effects of attention disengagement and sensory seeking on social symptoms in a community sample of infants at-risk for a future diagnosis of autism spectrum disorder. Developmental Cognitive Neuroscience, 29, 30–40. 10.1016/j.dcn.2017.08.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Ben-Sasson A, Soto TW, Martínez-Pedraza F, & Carter AS (2013). Early sensory over-responsivity in toddlers with autism spectrum disorders as a predictor of family impairment and parenting stress. Journal of Child Psychology and Psychiatry, 54(8), 846–853. 10.1111/jcpp.12035 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Ben-Sasson A, Hen L, Fluss R, Cermak SA, Engel-Yeger B, & Gal E (2009). A meta-analysis of sensory modulation symptoms in individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 39(1), 1–11. 10.1007/s10803-008-0593-3 [DOI] [PubMed] [Google Scholar]
  10. Brandwein AB, Foxe JJ, Butler JS, Frey H-P, Bates JC, Shulman LH, & Molholm S (2014). Neurophysiological indices of atypical auditory processing and multisensory integration are associated with symptom severity in autism. Journal of Autism and Developmental Disorders, 45(1), 230–244. 10.1007/s10803-014-2212-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Cheung PPP, & Siu AMH (2009). A comparison of patterns of sensory processing in children with and without developmental disabilities. Research in Developmental Disabilities, 30(6), 1468–1480. 10.1016/j.ridd.2009.07.009 [DOI] [PubMed] [Google Scholar]
  12. Damiano-Goodwin CR, Woynaroski TG, Simon DM, Ibañez LV, Murias M, Kirby A, Newsom CR, Wallace MT, Stone WL, Cascio CJ (2018). Developmental sequelae and neurophysiologic substrates of sensory seeking in infant siblings of children with autism spectrum disorder. Developmental Cognitive Neuroscience, 29, 41–53. 10.1016/j.dcn.2017.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Dawson G, Rogers S, Munson J, Smith M, Winter J, Greenson J, Donaldson A, Varley J (2010). Randomized, controlled trial of an intervention for toddlers with autism: The early start Denver model. Pediatrics, 125(1), e17–e23. 10.1542/peds.2009-0958 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dawson G, Toth K, Abbott R, Osterling J, Munson J, Estes A, & Liaw J (2004). Early social attention impairments in autism: Social orienting, joint attention, and attention to distress. Developmental Psychology, 40(2), 271–283. 10.1037/0012-1649.40.2.271 [DOI] [PubMed] [Google Scholar]
  15. Dellapiazza F, Vernhet C, Blanc N, Miot S, Schmidt R, & Baghdadli A (2018). Links between sensory processing, adaptive behaviours, and attention in children with autism spectrum disorder: A systematic review. Psychiatry Research, 270, 78–88. 10.1016/j.psychres.2018.09.023 [DOI] [PubMed] [Google Scholar]
  16. Dunn LM, & Dunn LM (1997). PPVT-III: Peabody picture vocabulary test (3rd ed.). American Guidance Service. [Google Scholar]
  17. Dunn W (1999). The sensory profile User’s manual. Psychological Corporation. [Google Scholar]
  18. Germani T, Zwaigenbaum L, Bryson S, Brian J, Smith I, Roberts W, Szatmari P, Roncadin C, Sacrey LAR, Garon N, Vaillancourt T (2014). Brief report: Assessment of early sensory processing in infants at high-risk of autism spectrum disorder. Journal of Autism and Developmental Disorders, 44(12), 3264–3270. 10.1007/s10803-014-2175-x [DOI] [PubMed] [Google Scholar]
  19. Gotham K, Pickles A, & Lord C (2009). Standardizing ados scores for a measure of severity in autism spectrum disorders. Journal of Autism and Developmental Disorders, 39(5), 693–705. 10.1007/s10803-008-0674-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Gotham K, Risi S, Pickles A, & Lord C (2007). The autism diagnostic observation schedule: Revised algorithms for improved diagnostic validity. Journal of Autism and Developmental Disorders, 37(4), 613–627. 10.1007/s10803-006-0280-1 [DOI] [PubMed] [Google Scholar]
  21. Green SA, Ben-Sasson A, Soto TW, & Carter AS (2012). Anxiety and sensory over-responsivity in toddlers with autism spectrum disorders: Bidirectional effects across time. Journal of Autism and Developmental Disorders, 42(6), 1112–1119. 10.1007/s10803-011-1361-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Hilton CL, Harper JD, Kueker RH, Lang AR, Abbacchi AM, Todorov A, & LaVesser PD (2010). Sensory responsiveness as a predictor of social severity in children with high functioning autism spectrum disorders. Journal of Autism and Developmental Disorders, 40(8), 937–945. 10.1007/s10803-010-0944-8 [DOI] [PubMed] [Google Scholar]
  23. Howe FEJ, & Stagg SD (2016). How sensory experiences affect adolescents with an autistic spectrum condition within the classroom. Journal of Autism and Developmental Disorders, 46(5), 1656–1668. 10.1007/s10803-015-2693-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kern JK (2006). The pattern of sensory processing abnormalities in autism. Autism, 10(5), 480–494. 10.1177/1362361306066564 [DOI] [PubMed] [Google Scholar]
  25. Kern JK, Trivedi MH, Grannemann BD, Garver CR, Johnson DG, Andrews AA, Savla JS, Mehta JA, Schroeder JL (2007). Sensory correlations in autism. Autism: The International Journal of Research and Practice, 11(2), 123–134. 10.1177/1362361307075702 [DOI] [PubMed] [Google Scholar]
  26. Kirby AV, Bilder DA, Wiggins LD, Hughes MM, Davis J, Hall-Lande JA, Lee L-C, McMahon WM Bakian AV (2022). Sensory features in autism: Findings from a large population-based surveillance system. Autism Research: Official Journal of the International Society for Autism Research, 15(4), 751–760. 10.1002/aur.2670 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Klintwall L, Eldevik S, & Eikeseth S (2015). Narrowing the gap: Effects of intervention on developmental trajectories in autism. Autism, 19(1), 53–63. 10.1177/1362361313510067 [DOI] [PubMed] [Google Scholar]
  28. Klintwall L, Holm A, Eriksson M, Carlsson LH, Olsson MB, Hedvall A, Gillberg C, Fernell E (2011). Sensory abnormalities in autism. A brief report. Research in Developmental Disabilities, 32(2), 795–800. 10.1016/j.ridd.2010.10.021 [DOI] [PubMed] [Google Scholar]
  29. Kojovic N, Ben Hadid L, Franchini M, & Schaer M (2019). Sensory processing issues and their association with social difficulties in children with autism spectrum disorders. Journal of Clinical Medicine, 8(10), E1508. 10.3390/jcm8101508 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Leekam SR, Nieto C, Libby SJ, Wing L, & Gould J (2007). Describing the sensory abnormalities of children and adults with autism. Journal of Autism and Developmental Disorders, 37(5), 894–910. 10.1007/s10803-006-0218-7 [DOI] [PubMed] [Google Scholar]
  31. Lord C, Rutter M, DiLavore PC, & Risi S (2003). Autism diagnostic observation schedule manual. Western Psychological Services. [Google Scholar]
  32. Maenner MJ, Warren Z, Williams AR, Amoakohene E, Bakian AV, Bilder DA, Durkin MS, Fitzgerald RT, Furnier SM, Hughes MM, Ladd-Acosta CM, McArthur D, Pas ET, Salinas A, Vehorn A, Williams S, Esler A, Grzybowski A, Hall-Lande J, … Shaw KA (2023). Prevalence and characteristics of autism spectrum disorder among children aged 8 years—Autism and developmental disabilities monitoring network, 11 sites, United States, 2020. MMWR. Surveillance Summaries, 72(2);1–14. 10.15585/mmwr.ss7202a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. McCormick C, Hepburn S, Young GS, & Rogers SJ (2016). Sensory symptoms in children with autism spectrum disorder, other developmental disorders and typical development: A longitudinal study. Autism: The International Journal of Research and Practice, 20(5), 572–579. 10.1177/1362361315599755 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. McIntosh DN, Miller LJ, Shyu V, & Dunn W (1999). Development and validation of the short sensory profile. In Sensory profile manual (pp. 59–73). Psychological Corporation. [Google Scholar]
  35. Miller Kuhaneck H, & Britner PA (2013). A preliminary investigation of the relationship between sensory processing and social play in autism spectrum disorder. OTJR: Occupation, Participation and Health, 33(3), 159–167. 10.3928/15394492-20130614-04 [DOI] [PubMed] [Google Scholar]
  36. Miron O, Delgado RE, Delgado CF, Simpson EA, Yu K-H, Gutierrez A, Guangyu Z, Gerstenberger JN, & Kohane IS (2021). Prolonged auditory brainstem response in universal hearing screening of newborns with autism spectrum disorder. Autism Research, 14(1), 46–52. 10.1002/aur.2422 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. O’Connor K (2012). Auditory processing in autism spectrum disorder: A review. Neuroscience and Biobehavioral Reviews, 36(2), 836–854. 10.1016/j.neubiorev.2011.11.008 [DOI] [PubMed] [Google Scholar]
  38. O’Donnell S, Deitz J, Kartin D, Nalty T, & Dawson G (2012). Sensory processing, problem behavior, adaptive behavior, and cognition in preschool children with autism spectrum disorders. American Journal of Occupational Therapy, 66(5), 586–594. 10.5014/ajot.2012.004168 [DOI] [PubMed] [Google Scholar]
  39. Perez Repetto L, Jasmin E, Fombonne E, Gisel E, & Couture M (2017). Longitudinal study of sensory features in children with autism spectrum disorder. Autism Research and Treatment, 2017, 1–8. 10.1155/2017/1934701 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Riva V, Cantiani C, Mornati G, Gallo M, Villa L, Mani E, Saviozzi I, Marino C & Molteni M (2018). Distinct ERP profiles for auditory processing in infants at-risk for autism and language impairment. Scientific Reports, 8(1), 715. 10.1038/s41598-017-19009-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Rutter M, LeCouteur A, & Lord C (2003). Autism diagnostic interview revised: WPS edition manual. Western Psychological Services. [Google Scholar]
  42. Sparrow SS, & Cicchetti DV (1989). The Vineland adaptive behavior scales. In Major psychological assessment instruments (Vol. 2, pp. 199–231). Allyn & Bacon. [Google Scholar]
  43. Suarez MA (2012). Sensory processing in children with autism spectrum disorders and impact on functioning. Pediatric Clinics, 59(1), 203–214. 10.1016/j.pcl.2011.10.012 [DOI] [PubMed] [Google Scholar]
  44. Thye MD, Bednarz HM, Herringshaw AJ, Sartin EB, & Kana RK (2018). The impact of atypical sensory processing on social impairments in autism spectrum disorder. Developmental Cognitive Neuroscience, 29, 151–167. 10.1016/j.dcn.2017.04.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Tomchek SD, & Dunn W (2007). Sensory processing in children with and without autism: A comparative study using the short sensory profile. American Journal of Occupational Therapy, 61(2), 190–200. 10.5014/ajot.61.2.190 [DOI] [PubMed] [Google Scholar]
  46. Tomchek SD, Huebner RA, & Dunn W (2014). Patterns of sensory processing in children with an autism spectrum disorder. Research in Autism Spectrum Disorders, 8(9), 1214–1224. 10.1016/j.rasd.2014.06.006 [DOI] [Google Scholar]
  47. Vietze P, & Lax LE (2020). Early intervention aba for toddlers with asd: Effect of age and amount. Current Psychology, 39(4), 1234–1244. 10.1007/s12144-018-9812-z [DOI] [Google Scholar]
  48. Williams KT (1997). Expressive vocabulary test second edition (EVT™ 2). Journal of the American Academy of Child and Adolescent Psychiatry, 42, 864–872. [Google Scholar]
  49. Wolff JJ, Swanson MR, Elison JT, Gerig G, Pruett JR, Styner MA, Vachet C, Botteron KN, Dager SR, Estes AM, Hazlett HC, Schultz RT, Shen MD, Zwaigenbaum L, Piven J & The IBIS Network (2017). Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism. Molecular Autism, 8, 8. 10.1186/s13229-017-0126-z [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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