Caregiver-child interaction as an effective tool for identifying autism spectrum disorder: evidence from EEG analysis.
Five minutes of caregiver-child play can flag ASD with better than 75 % accuracy, giving BCBAs a fast clinic-ready screen.
01Research in Context
What this study did
Deng et al. (2023) filmed 5-minute caregiver-child play sessions. They used EEG caps and simple behavior codes. The goal was to spot autism without long tests.
Kids were preschool age. Some had ASD, some had delays, some were typical. No extra toys or tools were needed.
What they found
The 5-minute play gave scores that flagged ASD with 77-83 % sensitivity and 67-82 % specificity. That means about 8 out of 10 kids with ASD were caught.
Adding EEG boosted accuracy a little, but even the plain video codes worked. The method was fast and cheap.
How this fits with other research
Bong et al. (2021) ran a similar idea: a 10-minute parent chat plus 15-minute play hit 85-92 % sensitivity. Deng trims the time almost in half and still lands near the same numbers. The shorter form is easier in busy clinics.
Nah et al. (2019) used only five quick questions and reached 81 % sensitivity. Deng swaps the questionnaire for live play plus EEG. Both aim for speed, but Deng adds a biological signal.
Kremkow et al. (2022) reviewed digital tools and warned most stay stuck in pilot stages. Deng’s study is a fresh pilot that meets the review’s call for real-world, low-cost screens.
Why it matters
You can run this screen while families wait. Five minutes of play, a tablet for coding, and you get a red-or-green flag. No long ADOS waitlist. Try taping your next caregiver-child play. Code eye contact, shared smiles, and response to name. If the score looks weak, move the family up for a full eval.
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02At a glance
03Original abstract
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that affects individuals across their lifespan. Early diagnosis and intervention are crucial for improving outcomes. However, current diagnostic methods are often time-consuming, and costly, making them inaccessible to many families. In the current study, we aim to test caregiver-child interaction as a potential tool for screening children with ASD in clinic. We enrolled 85 preschool children (Mean age: 4.90 ± 0.65 years, 70.6% male), including ASD children with or without developmental delay (DD), and typical development (TD) children, along with their caregivers. ASD core symptoms were evaluated by Childhood Autism Rating Scale (CARS) and Autism Diagnostic Observation Schedule-Calibrated Severity Scores (ADOS-CSS). Behavioral indicators were derived from video encoding of caregiver-child interaction, including social involvement of children (SIC), interaction time (IT), response of children to social cues (RSC), time for caregiver initiated social interactions (GIS) and time for children initiated social interactions (CIS)). Power spectral density (PSD) values were calculated by EEG signals simultaneously recorded. Partial Pearson correlation analysis was used in both ASD groups to investigate the correlation among behavioral indicators scores and ASD symptom severity and PSD values. Receiver operating characteristic (ROC) analysis was used to describe the discrimination accuracy of behavioral indicators. Compared to TD group, both ASD groups demonstrated significant lower scores of SIC, IT, RSC, CIS (all p values < 0.05), and significant higher time for GIS (all p values < 0.01). SIC scores negatively correlated with CARS (p = 0.006) and ADOS-CSS (p = 0.023) in the ASD with DD group. Compared to TD group, PSD values elevated in ASD groups (all p values < 0.05), and was associated with SIC (theta band: p = 0.005; alpha band: p = 0.003) but not IQ levels. SIC was effective in identifying both ASD groups (sensitivity/specificity: ASD children with DD, 76.5%/66.7%; ASD children without DD, 82.6%/82.2%). Our results verified the behavioral paradigm of caregiver-child interaction as an efficient tool for early ASD screening. The online version contains supplementary material available at 10.1186/s13034-023-00690-z.
Child and Adolescent Psychiatry and Mental Health, 2023 · doi:10.1186/s13034-023-00690-z