Sensory features as predictors of adaptive behaviors: A comparative longitudinal study of children with autism spectrum disorder and other developmental disabilities

Williams, Kathryn L.; Kirby, Anne V.; Watson, Linda R.; Sideris, John; Bulluck, John; Baranek, Grace T.

doi:10.1016/j.ridd.2018.07.002

Cited by 67 publications

(73 citation statements)

References 53 publications

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“…Although the exploratory nature of this study makes it difficult to generate predictions regarding how participants' scores on still further measured variables might differ across clusters defined on the basis of auditory electrophysiological responses, a considerable number of measures were collected as part of the APP. Given that anxiety [16][17][18][19], adaptive functioning [12][13][14][15], and cognitive ability [65,66] have all been associated with autistic sensory processing in previous studies, and in light of the extensive literature documenting relationships between chronological age and electrophysiological responses in TD, the variables of anxiety, adaptive behaviour, cognitive ability, and chronological age were explored in this study.…”

Section: Present Studymentioning

confidence: 99%

“…Unfortunately, existing environments have largely been designed with the sensory features of Typical Development (TD) in mind. Thus, differential sensory processing in ASD is associated with participation in activities [10,11], adaptive functioning [12][13][14][15], anxiety and other affective symptoms [16][17][18][19], and even quality of life [20].…”

Section: Introductionmentioning

confidence: 99%

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Defining Clusters of Young Autistic and Typically-Developing Children Based on Loudness-Dependent Auditory Electrophysiological Responses

Dwyer

Wang

Meo-Monteil

et al. 2020

Preprint

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Background: Autistic individuals exhibit atypical patterns of sensory processing that are known to be related to quality of life, but which are also highly heterogeneous. Previous investigations of this heterogeneity have ordinarily used questionnaires and have rarely investigated sensory processing in Typical Development (TD) alongside Autism Spectrum Development (ASD). Methods: The present study used hierarchical clustering in a large sample to identify subgroups of young autistic and typically-developing children based the normalized global field power (GFP) of their event-related potentials (ERPs) to auditory stimuli of four different loudness intensities (50, 60, 70, 80 dB SPL): that is, based on an index of the relative strengths of their neural responses across these loudness conditions. Results: Four clusters of participants were defined. Normalized GFP responses to sounds of different intensities differed strongly across clusters. There was considerable overlap in cluster assignments of autistic and typically-developing participants, but autistic participants were more likely to display a pattern of relatively linear increases in response strength accompanied by a disproportionately strong response to 70 dB stimuli. Autistic participants displaying this pattern trended towards obtaining higher scores on assessments of cognitive abilities. There was also a trend for typically-developing participants to disproportionately fall into a cluster characterized by disproportionately/nonlinearly strong 60 dB responses. Greater auditory distractibility was reported among autistic participants in a cluster characterized by disproportionately strong responses to the loudest (80 dB) sounds, and furthermore, relatively strong responses to loud sounds were correlated with both auditory distractibility and noise distress. This appears to provide evidence of coinciding behavioural and neural sensory atypicalities. Limitations : Replication may be needed to verify exploratory results. This analysis may ignore some variability related to classical ERP latencies and topographies. The sensory questionnaire employed was not specifically designed for use in autism. Variability in sensory responses unrelated to loudness is ignored, leaving much room for additional research. Conclusions: Taken together, these data demonstrate the broader benefits of using electrophysiology to explore individual differences. They illuminate different neural response patterns and suggest relationships between sensory neural responses and sensory behaviours, cognitive abilities, and autism diagnostic status.

show abstract

Section: Present Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Defining Clusters of Young Autistic and Typically-Developing Children Based on Loudness-Dependent Auditory Electrophysiological Responses

Dwyer

Wang

Meo-Monteil

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Although the exploratory nature of this study makes it difficult to generate predictions regarding how participants' scores on still further measured variables might differ across clusters defined on the basis of auditory electrophysiological responses, a considerable number of measures were collected as part of the APP. Given that anxiety [19][20][21][22], adaptive functioning [15][16][17][18], and cognitive ability [71,72] have all been associated with autistic sensory processing in previous studies, and in light of the extensive literature documenting relationships between chronological age and electrophysiological responses in TD, the variables of anxiety, adaptive behaviour, cognitive ability, and chronological age were explored in this study.…”

Section: Present Studymentioning

confidence: 99%

“…Unfortunately, existing environments have largely been designed with the sensory features of Typical Development (TD) in mind. Thus, differential sensory processing in ASD is associated with participation in activities [13,14], adaptive functioning [15][16][17][18], anxiety and other affective symptoms [19][20][21][22], and even quality of life [23].…”

Section: Introductionmentioning

confidence: 99%

Defining Clusters of Young Autistic and Typically-Developing Children Based on Loudness-Dependent Auditory Electrophysiological Responses

Dwyer

Wang

Meo-Monteil

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Autistic individuals exhibit atypical patterns of sensory processing that are known to be related to quality of life, but which are also highly heterogeneous. Previous investigations of this heterogeneity have ordinarily used questionnaires and have rarely investigated sensory processing in Typical Development (TD) alongside Autism Spectrum Development (ASD). Methods:The present study used hierarchical clustering in a large sample to identify subgroups of young autistic and typically-developing children based the normalized global field power (GFP) of their event-related potentials (ERPs) to auditory stimuli of four different loudness intensities (50, 60, 70, 80 dB SPL): that is, based on an index of the relative strengths of their neural responses across these loudness conditions.Results: Four clusters of participants were defined. Normalized GFP responses to sounds of different intensities differed strongly across clusters. There was considerable overlap in cluster assignments of autistic and typically-developing participants, but autistic participants were more likely to display a pattern of relatively linear increases in response strength accompanied by a disproportionately strong response to 70 dB stimuli. Autistic participants displaying this pattern trended towards obtaining higher scores on assessments of cognitive abilities. There was also a trend for typically-developing participants to disproportionately fall into a cluster characterized by disproportionately/nonlinearly strong 60 dB responses. Greater auditory distractibility was reported among autistic participants in a cluster characterized by disproportionately strong responses to the loudest (80 dB) sounds, and furthermore, relatively strong responses to loud sounds were correlated with both auditory distractibility and noise distress. This appears to provide evidence of coinciding behavioural and neural sensory atypicalities. CLUSTERING LOUDNESS-DEPENDENT AUDITORY ERPS 3Limitations: Replication may be needed to verify exploratory results. This analysis may ignore some variability related to classical ERP latencies and topographies. The sensory questionnaire employed was not specifically designed for use in autism. Variability in sensory responses unrelated to loudness is ignored, leaving much room for additional research. Conclusions:Taken together, these data demonstrate the broader benefits of using electrophysiology to explore individual differences. They illuminate different neural response patterns and suggest relationships between sensory neural responses and sensory behaviours, cognitive abilities, and autism diagnostic status.

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“…The term 'sensory features' is used here to describe the diverse range of sensory symptoms in individuals with ASD that can encompass hyper-reactivity, hypo-reactivity, and unusual sensory interests (6). Indeed, a range of studies have linked atypical sensory features with restricted and repetitive behaviours (7,8), socio-communicative impairments (9,10), anxiety (11,12), behavioural and sleep problems (13,14), and adaptive functioning (15). Further, several studies have identi ed the existence of potentially informative sensory-based subgroups among individuals with ASD (12,(16)(17)(18)(19).…”

Section: Introductionmentioning

confidence: 99%

Dissecting the phenotypic heterogeneity in sensory features in Autism Spectrum Disorder: a factor mixture modelling approach

Tillmann

Uljarević

Crawley

et al. 2020

Preprint

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Background: Heterogeneity in the phenotypic presentation of Autism Spectrum Disorder (ASD) is apparent in the profile and the severity of sensory features. Here we applied Factor Mixture Modelling (FMM) to test a multidimensional factor model of sensory processing in ASD. We aimed to identify homogeneous sensory subgroups in ASD that differ intrinsically in their severity along continuous factor scores. We also investigated sensory subgroups in relation to clinical variables: sex, age, IQ, social communication symptoms, restricted and repetitive behaviours, adaptive functioning and symptoms of anxiety and Attention-Deficit/Hyperactivity Disorder.Methods: 332 children and adults with ASD between the ages of 6 and 30 years with IQs varying between 40 and 148 were included. First, three different confirmatory factor models were fit to the 38 items of the Short Sensory Profile (SSP). Then, latent class models (with two-to-six subgroups) were evaluated. The best performing factor model, the 7-factor structure, was subsequently used in two FMMs that varied in the number of subgroups: a two-subgroup, seven-factor model and a three-subgroup, seven-factor model.Results: The ‘three-subgroup/seven-factor’ FMM was superior to all other models based on different fit criteria. Identified subgroups differed in sensory severity from severe, moderate to low. Accounting for the potential confounding effects of age and IQ, participants in these sensory subgroups had different levels of social-communicative symptoms, restricted and repetitive behaviours, adaptive functioning skills and symptoms of inattention and anxiety.Limitations: Results were derived using a single parent-report measure of sensory features, the SSP, which limits the generalisability of findings.Conclusion: Sensory features can be best described by three homogeneous sensory subgroups that differ in sensory severity gradients along seven continuous factor scores. Identified sensory subgroups were further differentiated by the severity of core and co-occurring symptoms, and level of adaptive functioning, providing novel evidence on the associated clinical correlates of sensory subgroups. These sensory subgroups provide a platform to further interrogate the neurobiological and genetic correlates of altered sensory processing in ASD.

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Sensory features as predictors of adaptive behaviors: A comparative longitudinal study of children with autism spectrum disorder and other developmental disabilities

Abstract: Sensory features may interfere with development of adaptive behaviors, suggesting a need for effective interventions addressing sensory features early in development.

Cited by 67 publications

References 53 publications

Defining Clusters of Young Autistic and Typically-Developing Children Based on Loudness-Dependent Auditory Electrophysiological Responses

Defining Clusters of Young Autistic and Typically-Developing Children Based on Loudness-Dependent Auditory Electrophysiological Responses

Defining Clusters of Young Autistic and Typically-Developing Children Based on Loudness-Dependent Auditory Electrophysiological Responses

Dissecting the phenotypic heterogeneity in sensory features in Autism Spectrum Disorder: a factor mixture modelling approach

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