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Prenatal exposure to vitamin D is thought to be critical for optimal fetal neurodevelopment, yet vitamin D deficiency is apparent in a growing proportion of...
The current study provides preliminary evidence that machine learning algorithms provide equivalent predictive accuracy to traditional methods for language difficulties in middle childhood
Fiona Pete Stanley Azzopardi FAA FASSA MSc MD FFPHM FAFPHM FRACP FRANZCOG HonDSc HonDUniv HonFRACGP HonMD HonFRCPCH HonLLB (honoris causa) PhD, FRACP
The aim of this study was to investigate the language outcomes of 7-year-old children with and without a history of late language emergence at 24 months.
The primary objectives of this study were to determine the prevalence of late language emergence (LLE) and to investigate the predictive status of maternal...
The increasing need for speech and language therapy (SLT) services, coupled with poor employment retention rates, poses serious cost-benefit considerations.
The aim of this research note is to encourage child language researchers and clinicians to give careful consideration to the use of domain-specific tests as a proxy for language; particularly in the context of large-scale studies and for the identification of language disorder in clinical practice.
Natural Language Sampling (NLS) offers clear potential for communication and language assessment, where other data might be difficult to interpret. We leveraged existing primary data for 18-month-olds showing early signs of autism, to examine the reliability and concurrent construct validity of NLS-derived measures coded from video-of child language, parent linguistic input, and dyadic balance of communicative interaction-against standardised assessment scores. Using Systematic Analysis of Language Transcripts (SALT) software and coding conventions, masked coders achieved good-to-excellent inter-rater agreement across all measures.
CDKL5 deficiency disorder (CDD) is a genetically caused developmental epileptic encephalopathy that causes severe communication impairments. Communication of individuals with CDD is not well understood in the literature and currently available measures are not well validated in this population. Accurate and sensitive measurement of the communication of individuals with CDD is important for understanding this condition, clinical practice, and upcoming interventional trials.
Growing up in a language-rich home environment is important for children's language development in the early years. The concept of "technoference" (technology-based interference) suggests that screen time may be interfering with opportunities for talk and interactions between parent and child; however, limited longitudinal evidence exists exploring this association.