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The current study provides preliminary evidence that machine learning algorithms provide equivalent predictive accuracy to traditional methods for language difficulties in middle childhood
The aim of the current study was to investigate the risk factors present at 2 years for children who showed language difficulties that persisted
Our results demonstrate a range of multiple risk profiles in a population-representative sample of Australian children and highlight the mix of risk factors faced by children
Parent–child book reading interventions alone are unlikely to meet needs of children and families for whom the absence of reading is psychosocial risk factor
This research focuses on three questions 1) What are the patterns of stability & change; 2) what are the predictors of this progression, and; 3) what is the...
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...
Children and adolescents with Intellectual Disability experience a worse Quality-of-Life (QoL) relative to typically developing peers. Thus, QoL evaluation is important for identifying support needs and improving rehabilitation effectiveness. Nevertheless, currently in Italy there are not tools with this scope. This study aims to translate and cross-culturally adapt the Quality-of-Life Inventory-Disability into Italian.
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 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.