There is growing evidence that prevalence rates of autism spectrum disorder (ASD) are increasing. A number of factors appear to contribute to this increase, including excessive screen time. Screen time seems to be linked to the severity of the symptoms of ASD. Given this, the aim of the present cross-sectional study was to investigate the association between early screen time and ASD symptoms severity in the first 36 months of life. To this end, sixty-eight Iranian toddlers (mean age: 27.09 months; 22.1% females) with ASD were recruited. Parents completed the modified checklist for autism in toddlers (M-CHAT), the Repetitive Behavior Scale-Revised (RBS-R), and a lifestyle checklist. Next, parents rated children’s daily exposure to content specifically designed (foreground media) and not specifically designed (background media) for children, along with their daily exposure to social interaction. Per day, toddlers spent 5.12 h (±3.77) with foreground media, 3.72 h (±3.57) with background media, and 2.89 h (±2.74) in interaction with other people (parents). To test the hypotheses, we performed a series of Pearson’s correlations and multiple regression analyses. Toddlers’ higher severity scores for ASD symptoms were associated with longer foreground (r = 0.234, p = 0.001) and longer background (r = 0.180, p = 0.012) media duration, and with shorter duration of interaction with others (r = 0.192, p = 0.009). Toddlers spending 1 h more in foreground screen time and background screen time have 0.38 and 0.29 more units in the ASD symptom severity scale, respectively, while toddlers spending 1 h more in social interactions have 0.42 fewer units in the ASD symptom severity scale. The screen time and interaction duration are related to ASD symptoms severity of toddlers. The cross-sectional study design precludes causal associations, although bi-directional relationships appear plausible.

Excessive exposure of young children to digital devices has increased in recent years. Much research has shown that early excessive screentime is associated with autistic-like symptoms. This study aimed to differentiate children with Post–Digital Nannying Autism Syndrome (PDNAS) from children with autism spectrum disorders (ASD) and typically developing children (TDC), both behaviorally and cognitively. This study is comparative and cross-sectional and included three groups of children. The first group consisted of 15 young children with subthreshold autism symptoms. They had not received a formal diagnosis of ASD and had been exposed to digital devices for more than half of their waking time. The second group consisted of 15 young children with ASD, and the third group consisted of 15 young TDC. A lifestyle checklist, a modified checklist for autism in toddlers (M-CHAT), a behavioral flexibility rating scale-revised (BFRS-R), the Gilliam autism rating scale (GARS-2), and a behavior rating inventory of executive functioning-preschool version (BRIEF-P) were used to compare the three groups. The results showed that executive functions and behavioral flexibility were more impaired in children with ASD than in children with PDNAS and in TDC. Also, we found that there was no significant difference in the severity of autism symptoms between the children with ASD and the children with PDNAS. Early excessive exposure to digital devices may cause autism-like symptoms in children (PDNAS). Children with PDNAS are different from children with ASD in executive functions and behavioral flexibility. Further research is needed in this area.

Childhood autism is a severe form of complex genetically heterogeneous and behaviorally defined set of neurodevelopmental diseases, collectively termed as autism spectrum disorders (ASD). Reverse transcriptase quantitative real-time PCR (RT-qPCR) is a highly sensitive technique for transcriptome analysis, and it has been frequently used in ASD gene expression studies. However, normalization to stably expressed reference gene(s) is necessary to validate any alteration reported at the mRNA level for target genes. The main goal of the present study was to find the most stable reference genes in the salivary transcriptome for RT-qPCR analysis in non-syndromic male childhood autism. Saliva samples were obtained from nine drug naïve non-syndromic male children with autism and also sex-, age-, and location-matched healthy controls using the RNA-stabilizer kit from DNA Genotek. A systematic two-phased measurement of whole saliva mRNA levels for eight common housekeeping genes (HKGs) was carried out by RT-qPCR, and the stability of expression for each candidate gene was analyzed using two specialized algorithms, geNorm and NormFinder, in parallel. Our analysis shows that while the frequently used HKG ACTB is not a suitable reference gene, the combination of GAPDH and YWHAZ could be recommended for normalization of RT-qPCR analysis of salivary transcriptome in non-syndromic autistic male children.