Search
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
Language development is critical for children's life chances. Promoting parent-child interactions is suggested as one mechanism to support language development in the early years. However, limited evidence exists for a causal effect of parent-child interactions on children's language development.
This study sought to determine the prevalence of Developmental Language Disorder (DLD) in Australian school-aged children and associated potential risk factors for DLD at 10 years.
The majority of children acquire language effortlessly but approximately 10% of all children find it difficult especially in the early or preschool years with consequences for many aspects of their subsequent development and experience: literacy, social skills, educational qualifications, mental health and employment.
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.
The Life Course Centre is a national centre funded by the Australian Research Council Centre of Excellence Scheme and hosted through the University of Queensland with collaborating nodes at the University of Western Australia, Sydney University and University of Melbourne.