Publications by authors named "Elizabeth P McKernan"

Article Synopsis
  • The study examined how autistic individuals respond to sensory stimuli, focusing on three main traits: hyperreactivity (HYPER), hyporeactivity (HYPO), and sensory seeking (SEEK).
  • Using data from 3,868 autistic youth, the researchers applied advanced statistical methods to explore the relationships between these traits across different sensory modalities.
  • Results showed that while a general pattern of HYPER responses could be validated, HYPO responses were less consistent, and SEEK had a more limited version, indicating that sensory responses in autism vary significantly and require nuanced assessment.
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The current study examined factorial invariance of the Center for Epidemiologic Studies Depression Scale-Revised (CESD-R) and the Depression Anxiety Stress Scales-21 (DASS-21) using a convenience sample of 434 adults surveyed though Amazon Mechanical Turk. Participants were sorted into two groups based on their score on the Autism-Spectrum Quotient. Results indicated that the CESD-R did not demonstrate configural invariance.

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Background Differences in responding to sensory stimuli, including sensory hyperreactivity (HYPER), hyporeactivity (HYPO), and sensory seeking (SEEK) have been observed in autistic individuals across sensory modalities, but few studies have examined the structure of these "supra-modal" traits in the autistic population. Methods Leveraging a combined sample of 3,868 autistic youth drawn from 12 distinct data sources (ages 3-18 years and representing the full range of cognitive ability), the current study used modern psychometric and meta-analytic techniques to interrogate the latent structure and correlates of caregiver-reported HYPER, HYPO, and SEEK within and across sensory modalities. Bifactor statistical indices were used to both evaluate the strength of a "general response pattern" factor for each supra-modal construct and determine the added value of "modality-specific response pattern" scores (e.

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Article Synopsis
  • - This study explores how data science can automatically measure social communication behaviors in children with autism spectrum disorder (ASD) by analyzing their interaction latency during conversations with adults.
  • - Researchers used recordings from 210 pairs of children with ASD and adult partners to calculate how quickly they responded to each other, both before and after interventions.
  • - The findings indicate that children receiving interventions showed a significant decrease in response latency, suggesting this automated measurement can effectively track treatment progress in social communication for children with ASD.
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Objective: This study compared language profiles of children with autism spectrum disorder (ASD) and typically developing (TD) children at kindergarten-entry and investigated whether kindergarten-entry language scores were predictive of concurrent and future academic achievement, peer interactions, and adaptive skills in children with ASD.

Method: Participants included 97 children (62 children with ASD; 35 TD children) assessed at kindergarten-entry and -exit. Language abilities were assessed using the Children's Communication Checklist-2 (CCC-2).

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Background: Autism spectrum disorder (ASD) is a complex neurological condition with increasing prevalence. Few tools accurately predict the developmental trajectory of children with ASD. Such tools would allow clinicians to provide accurate prognoses and track the efficacy of therapeutic interventions.

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Previous studies have suggested that sensory overresponsivity in youth with autism spectrum disorder (ASD) may be due to a failure to habituate to stimuli. We examined the relationship between performance on three tactile psychophysical tasks and the construct of sensory overresponsivity in children with and without ASD. Sensory overresponsivity predicted amplitude discrimination with an adapting stimulus, as well as the effect of adaptation, for ASD youth.

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