Parent Perspectives on Parent-Mediated Intervention for Young Children With Down Syndrome.

Background: Parent-mediated intervention (PMI) is a potentially scalable approach for tailored interventions in neurogenetic conditions like Down syndrome (DS). Because PMIs require ongoing parent engagement, they must be developed in alignment with the needs of intended users. The present study examined caregiver opinions and preferences to inform the development of syndrome-informed interventions for children with DS.

Italian normative data for the Unhelpful Thoughts and Beliefs about Stuttering (UTBAS) Scales for adults who stutter.

Purpose: This study aimed to assess the reliability and validity of the Italian translation of the Unhelpful Thoughts and Beliefs about Stuttering (UTBAS) scales for adults who stutter, as there are no assessment tools currently available in Italy. The UTBAS scales provide a comprehensive stuttering-specific measure of the unhelpful thoughts and beliefs that can be used to screen for indicators of social anxiety in adults who stutter. Additionally, the UTBAS scales also allow the identification of negative thoughts and beliefs that negatively impact speech treatment outcomes.

Cross-sectional developmental trajectories in the adaptive functioning of children and adolescents with Down syndrome.

Background: Persons with Down syndrome (DS) reveal adaptive functioning (AF) difficulties. Studies on AF in DS have focused mainly on describing the profile (i.e.

Machine learning based analysis for intellectual disability in Down syndrome.

Down syndrome (DS) or trisomy 21 is the most common genetic cause of intellectual disability (ID), but a pathogenic mechanism has not been identified yet. Studying a complex and not monogenic condition such as DS, a clear correlation between cause and effect might be difficult to find through classical analysis methods, thus different approaches need to be used. The increased availability of big data has made the use of artificial intelligence (AI) and in particular machine learning (ML) in the medical field possible.

Early developmental profiles among infants with Down syndrome.

Background: Down syndrome (DS) generally predisposes children to a pattern of relative developmental strengths and challenges, but within-syndrome heterogeneity is also commonly observed across many dimensions. The present research examines whether heterogeneity in developmental presentation can be detected during infancy in DS and whether factors associated with differing profiles can be identified.

Methods: Infants with DS (n = 75; age range: 3.