Abstract
Abstract
Background: Sensory processing differences are highly prevalent in Autism Spectrum Disorder (ASD) and are increasingly recognised as clinically relevant determinants of daily functioning. However, the relationship between sensory integration profiles, autism severity, and real-life participation remains insufficiently characterised in many clinical settings. This study aimed to describe sensory processing patterns in children with ASD and examine their associations with symptom severity and participation outcomes. Methods: A cross-sectional observational clinical study was conducted in 78 children with ASD aged 6–12 years. Sensory processing was assessed using the Short Sensory Profile (SSP). Autism symptom severity was evaluated using ADOS-2 calibrated severity scores. Functional participation across home, school, and community contexts was measured with the Participation and Environment Measure–Children and Youth (PEM-CY). Pearson correlations and multiple linear regression analyses were performed. Results: Most participants (65.4%) showed “definite difference” sensory profiles. SSP total scores were significantly associated with ADOS-2 severity (r = −0.44, p < 0.001). Higher SSP scores were correlated with greater participation involvement, particularly in school (r = 0.38, p < 0.001) and community settings (r = 0.33, p = 0.004). In adjusted regression models, SSP remained an independent predictor of school and community involvement after controlling for age and ADOS-2 severity. Conclusions: Sensory integration differences are common in ASD and are meaningfully associated with symptom severity and participation restrictions. Systematic sensory assessment may support individualised interventions aimed at improving functional participation in everyday environments.
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@article{Costescu2026Sensory,
title = {Sensory Integration in Autism Spectrum Disorder: Profiles, Functional Impact, and Clinical Implications},
author = {Elena Costescu and Oana Georgiana Oprea and Vasile Burlui and Alin Ciobica and Daniela Ivona Tomita and Diana Gheban},
journal = {BRAIN BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE},
year = {2026},
doi = {10.70594/brain/17.2/16},
url = {https://doi.org/10.70594/brain/17.2/16}
}
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