From Clinic to Home: Validating the Social Communication Scale for Telemedicine-Supported Early Autism Screening in Chinese Toddlers

Telemedicine is reshaping how early autism detection can be delivered, particularly in resource-limited settings. Yet, most existing tele-assessment tools were developed in Western contexts, limiting their cultural applicability. To address this gap, we evaluated the Social Communication Scale (SCS), a brief video-based tool, for telemedicine-supported screening in Chinese toddlers. A total of 170 Chinese toddlers aged 16 to 30 months were recruited. Parent-child interaction videos were recorded at home and subsequently coded using the SCS scheme. Autism likelihood (Elevated vs. Low) was defined using the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) classifications. Reliability and validity were evaluated. Screening accuracy was evaluated using total-score cutoff, logistic regression, and Random Forest (RF) models. The SCS demonstrated good inter-rater reliability (intraclass correlation coefficient [ICC] = 0.87) and moderate convergent validity with ADOS-2 and parent-reported measures of socialization and communication. Both logistic regression and RF outperformed the total-score approach, with RF yielding more balanced performance across metrics. Including demographic variables further improved RF classification performance (area under the receiver operating characteristic curve [AUC] = 0.91; sensitivity = 0.91; specificity = 0.91). The SCS demonstrates potential as a telemedicine-supported screening tool for early autism identification. Further validation in independent samples and against clinical diagnoses is needed to establish its generalizability and diagnostic accuracy.Lay AbstractTelemedicine is changing how early autism detection can be delivered, particularly in areas where specialist services are difficult to access. Telemedicine refers to the use of the internet and other digital technologies to provide health care remotely. Although several telemedicine tools for autism screening and diagnosis have shown promising results, most were developed and tested in Western countries and may not work equally well in different cultural settings. In this study, we evaluated a telemedicine tool called the Social Communication Scale (SCS) in 170 Chinese toddlers aged 16 to 30 months. A short video of a parent and child playing naturally together at home or in another familiar setting was recorded. Trained coders then reviewed the videos and assessed the child's early social communication behaviors associated with autism. The SCS was able to distinguish between toddlers identified by the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) as having an elevated or low likelihood of autism. Using artificial intelligence (machine learning) alongside the SCS further improved its accuracy. These findings suggest that the SCS could become a useful addition to early autism screening, particularly in places where specialist services are limited. With further testing in larger and more diverse groups of children, this approach could help more families access earlier assessment and support.