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There is a scarcity of diagnostic assessments and screening tools for autism spectrum disorders (ASD) in Greek. In this study, we examined the psychometric properties of the recently developed Greek version of the Social Communication Questionnaire (SCQ). We used parental responses for 311 children (mean age: 7.54 years old, SD = 1.92), 122 with a diagnosis of ASD (93 boys, 29 girls) and 189 neurotypical children (104 boys, 85 girls), with 167 responses referring to the Lifetime and 144 to the Current form of the SCQ. Both forms presented adequate construct validity based on the four‐factor model, while in both forms, autistic children presented higher SCQ total and subscale scores (four factors) than typical children. The forms had excellent internal reliability. An item‐response‐theory analysis suggested that over 80% of test items fitted adequately a Rasch model, while a preliminary analysis of gender biases suggested that a small number of items (Lifetime: five; Current: six out of 39) were differentially sensitive to autistic symptomatology in boys and girls. A receiver‐operating‐characteristic analysis showed excellent diagnostic performance based on the SCQ total score (Lifetime: area‐under‐the‐curve/AUC = 0.937, Current: AUC = 0.963), and acceptable to excellent discrimination for the four subscales (AUCs between 0.737 and 0.955). Our preliminary results suggest that the Greek SCQ presents satisfactory psychometric properties and can be used for differentiating children with ASD from typical children in initial assessments within clinical and research settings. Lay Summary: Autism spectrum disorder (ASD or autism) is a lifelong neurodevelopmental condition with a prevalence of ~1.5%–2% and characterized by difficulties in social interaction and communication and repetitive and restricted behaviors. There is increasing concern that research in ASD has focused on a small number of languages and cultural settings and that this bias challenges the identification and diagnosis of the condition in other languages and cultures, which are underrepresented in autism research. One such language is Greek (spoken by ~13.5 million), for which there is a scarcity of standardized instruments for the diagnosis of autism. This study examines the psychometric properties of the recently published Greek version of the Social Communication Questionnaire (SCQ), a widely used screening tool for ASD. We conduct an in‐depth psychometric analysis of the Greek SCQ, including both forms in which the instrument is available (Lifetime and Current). This analysis shows that the Greek SCQ can be used for differentiating children with ASD from typical children in initial assessments within clinical and research settings. The findings of this study have implications for clinicians, special educators and researchers working with Greek‐speaking individuals with ASD and, more broadly, for cross‐cultural autism research. [ABSTRACT FROM AUTHOR]

Oral communication often takes place in noisy environments, which challenge spoken‐word recognition. Previous research has suggested that the presence of background noise extends the number of candidate words competing with the target word for recognition and that this extension affects the time course and accuracy of spoken‐word recognition. In this study, we further investigated the temporal dynamics of competition processes in the presence of background noise, and how these vary in listeners with different language proficiency (i.e., native and non‐native) using computational modeling. We developed ListenIN (Listen‐In‐Noise), a neural‐network model based on an autoencoder architecture, which learns to map phonological forms onto meanings in two languages and simulates native and non‐native spoken‐word comprehension. We also examined the model's activation states during online spoken‐word recognition. These analyses demonstrated that the presence of background noise increases the number of competitor words, which are engaged in phonological competition and that this happens in similar ways intra and interlinguistically and in native and non‐native listening. Taken together, our results support accounts positing a "many‐additional‐competitors scenario" for the effects of noise on spoken‐word recognition. [ABSTRACT FROM AUTHOR]