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With increasing demands for health, disability and education services, innovative approaches can help distribute limited resources according to need. Despite an increased focus on support needs within the clinical pathway and policy landscape, the body of research knowledge on this topic is at a relatively early stage. However, there appears to be a sense of unmet support needs and dissatisfaction with the provision of required support following an autism diagnosis amongst caregivers of young people on the spectrum.
A diagnosis of an autism spectrum condition (autism) provides limited information regarding an individual’s level of functioning, information key in determining support and funding needs.
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.
Our previous cross-sectional investigation (Chetcuti et al., 2020) showed that infants with autism traits could be divided into distinct subgroups based on temperament. This longitudinal study builds on this existing work by exploring the continuity of temperament subgroup classifications and their associations with behavioral/clinical phenotypic features from infancy to toddlerhood.
The past three decades have seen a major shift in our understanding of the strong links between autism and identity. These developments have called for careful consideration of the language used to describe autism.
Director of CliniKids, Professor Andrew Whitehouse, and Professor Murray Maybery, have been identified as the world’s most frequent autism research collaborators of the decade.
The CliniKids team has reimagined how allied health services for children with autism spectrum disorder or developmental delays are delivered.
To identify factors associated with quality of life (QoL) in children with intellectual disability. We aimed to identify patterns of association not observable in previous hypothesis-driven regression modelling using the same data set from a cross-sectional observational study.
Recent studies have reported that strengths-based programs, leveraging autistic adolescents' abilities and interests, could improve their skills and facilitate social engagement. However, little is known about the long-term impact of strengths-based approaches. This study aimed to explore the long-term outcomes of community strengths-based programs designed to support autistic adolescents in developing interests and skills in Science, Technology, Engineering, Arts, and Mathematics (STEAM) and the factors influencing their participation in these programs.
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.