AUTHOR=Qiu Nana , Tang Chuangao , Zhai Mengyao , Huang Wanqing , Weng Jiao , Li Chunyan , Xiao Xiang , Fu Junli , Zhang Lili , Xiao Ting , Fang Hui , Ke Xiaoyan 

TITLE=Application of the Still-Face Paradigm in Early Screening for High-Risk Autism Spectrum Disorder in Infants and Toddlers

JOURNAL=Frontiers in Pediatrics

VOLUME=8

YEAR=2020

URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2020.00290

DOI=10.3389/fped.2020.00290

ISSN=2296-2360

ABSTRACT=<p><bold>Background:</bold> Although autism spectrum disorder (ASD) can currently be diagnosed at the age of 2 years, age at ASD diagnosis is still 40 months or even later. In order to early screening for ASD with more objective method, behavioral videos were used in a number of studies in recent years.</p><p><bold>Method:</bold> The still-face paradigm (SFP) was adopted to measure the frequency and duration of non-social smiling, protest behavior, eye contact, social smiling, and active social engagement in high-risk ASD group (HR) and typical development group (TD) (HR: <italic>n</italic> = 45; TD: <italic>n</italic> = 43). The HR group was follow-up until they were 2 years old to confirm final diagnosis. Machine learning methods were used to establish models for early screening of ASD.</p><p><bold>Results:</bold> During the face-to-face interaction (FF) episode of the SFP, there were statistically significant differences in the duration and frequency of eye contact, social smiling, and active social engagement between the two groups. During the still-face (SF) episode, there were statistically significant differences in the duration and frequency of eye contact and active social engagement between the two groups. The 45 children in the HR group were reclassified into two groups after follow-up: five children in the N-ASD group who were not meet the criterion of ASD and 40 children in the ASD group. The results showed that the accuracy of Support Vector Machine (SVM) classification was 83.35% for the SF episode.</p><p><bold>Conclusion:</bold> The use of the social behavior indicator of the SFP for a child with HR before 2 years old can effectively predict the clinical diagnosis of the child at the age of 2 years. The screening model constructed using SVM based on the SF episode of the SFP was the best. This also proves that the SFP has certain value in high-risk autism spectrum disorder screening. In addition, because of its convenient, it can provide a self-screening mode for use at home.</p><p><bold>Trial registration:</bold> Chinese Clinical Trial Registry, ChiCTR-OPC-17011995.</p>