Zhai Jinhe, Li Xiaoxue, Zhou Yong, Fan Lili, Xia Wei, Wang Xiaomin, Li Yutong, Hou Meiru, Wang Jia, Wu Lijie
School of Public Health, Harbin Medical University, Harbin, China.
Heilongjiang Provincial Center for Disease Control and Prevention, Harbin, China.
Front Psychiatry. 2023 Apr 6;14:1056051. doi: 10.3389/fpsyt.2023.1056051. eCollection 2023.
Individuals with autism spectrum disorder (ASD) often have different social characteristics and particular sensory processing patterns, and these sensory behaviors may affect their social functioning. The objective of our study is to investigate the sensory profiles of children with ASD and their association with social behavior. Specifically, we aim to identify the predictive role of sensory processing in social functioning.
The Short Sensory Profile (SSP) was utilized to analyze sensory differences between ASD children and their peers. The Social Responsiveness Scale (SRS) and other clinical scales were employed to assess the social functioning of children with ASD. Additionally, the predictive ability of sensory perception on social performance was discussed using random forest and support vector machine (SVM) models.
The SSP scores of ASD children were lower than those of the control group, and there was a significant negative correlation between SSP scores and clinical scale scores ( < 0.05). The random forest and SVM models, using all the features, showed higher sensitivity, while the random forest model with 7-feature factors had the highest specificity. The area under the receiver operating characteristic (ROC) curve (AUC) for all the models was higher than 0.8.
Autistic children in our study have different patterns of sensory processing than their peers, which are significantly related to their patterns of social functioning. Sensory features can serve as a good predictor of social functioning in individuals with ASD.
自闭症谱系障碍(ASD)患者通常具有不同的社交特征和特殊的感觉加工模式,这些感觉行为可能会影响他们的社交功能。我们研究的目的是调查ASD儿童的感觉特征及其与社交行为的关联。具体而言,我们旨在确定感觉加工在社交功能中的预测作用。
使用简短感觉概况量表(SSP)分析ASD儿童与其同龄人之间的感觉差异。采用社会反应量表(SRS)和其他临床量表评估ASD儿童的社交功能。此外,使用随机森林和支持向量机(SVM)模型讨论感觉知觉对社交表现的预测能力。
ASD儿童的SSP得分低于对照组,且SSP得分与临床量表得分之间存在显著负相关(<0.05)。使用所有特征的随机森林和SVM模型显示出更高的敏感性,而具有7个特征因子的随机森林模型具有最高的特异性。所有模型的受试者工作特征(ROC)曲线下面积(AUC)均高于0.8。
我们研究中的自闭症儿童与同龄人具有不同的感觉加工模式,这与他们的社交功能模式显著相关。感觉特征可以作为ASD患者社交功能的良好预测指标。