ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Autism
This article is part of the Research TopicSensory Processing in Autism: Mechanisms, Impacts and InterventionsView all 13 articles
Predicting Parental Caregiving Burden Based on Sensory Processing Patterns and Social Skills in Individuals with High-Functioning Autism Spectrum Disorder
Provisionally accepted
- 1Xi'an Gaoxin Hospital, Xi'an, China
- 2Shaanxi Provincial Hospital of Traditional Chinese Medicine, Xi'an, China
- 3Xi'an Peihua University, Xi'an, China
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Objective: This study aimed to Predicting Parental Caregiving Burden Based on Sensory Processing Patterns and Social Skills in Individuals with High-Functioning Autism Spectrum Disorder. Method: This correlational study recruited a convenience sample of 60 autistic children (aged 5-12 years, IQ > 80) from rehabilitation clinics. Parents completed the Zarit Burden Interview, the Sensory Profile School Companion, and the Gresham and Elliott Social Skills Rating Scale. Data were assessed using Pearson correlation as well as multiple regression analyses. Results: Sensory processing patterns were positively correlated with parental burden (r = 0.52 to 0.58), while social skills were negatively correlated (r = -0.59). Regression analyses identified significant unique predictors. Sensory Sensitivity (β = 0.28, p = 0.03) and Sensory Avoiding (β = 0.31, p = 0.02) were significant positive predictors of burden. In a separate model, lower Social Skills (β = -0.42, p = 0.003) and higher Problem Behavior (β = 0.28, p = 0.02) significantly predicted greater burden, collectively explaining 41.4% of the variance. Conclusion: Specific sensory processing difficulties (sensitivity and avoidance) and social-behavioral factors are significant, unique predictors of parental care burden. Interventions targeting these domains may alleviate caregiver stress and improve family outcomes in autism.
Keywords: Autism Spectrum Disorder, Parental caregiving burden, Prediction model, sensory processing, Social Skills
Received: 16 Nov 2025; Accepted: 09 Feb 2026.
Copyright: © 2026 Zhang, Zhang, Li, Zhang and Su. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Li Su
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