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This large population-based study identified no consistent association across two cohorts between prenatal head growth and postnatal autistic traits
To assess the relative effectiveness of topical versus systemic antibiotics for people with chronic suppurative otitis media
Young adults' alcohol consumption appears to be impacted by liquor store density and convenience, rather than outlet size
Elevated levels of emotional difficulties among school students with T1D and variable levels of support from school staff to assist these students to manage their diabetes at school
High dose vitamin D supplementation is associated with a shift to a more inflammatory faecal microbiome and increased susceptibility to colitis
Adolescents living with type 1 diabetes (T1D) are faced with unique challenges to nutrition management. The current Perth Children's Hospital (PCH) T1D management model includes individualised education at diagnosis and annual reviews. Currently, no group education is provided to develop self-management skills for healthy meal preparation. Teaching Kitchens offers a skills-based program in food literacy and nutrition. This feasibility study explored if a Teaching Kitchens program at PCH engaged adolescents aged between 13 and 17 years, living with T1D.
The Kids Research Institute Australia is one of 20 West Australian research facilities to share in $25 million funding under the State Government’s Research Infrastructure Support (RIS) program, through the Future Health Research and Innovation (FHRI) Fund.
This chapter outlines the concept of ‘justice capital’. It commences with a discussion of the impacts of colonization on Indigenous people in Australia, with a particular focus on Indigenous children placed in state care systems.
To investigate how caregivers of children with developmental and epileptic encephalopathy and severe developmental impairments describe meaningful change for functional domains and why it is important.
Processed electroencephalography (EEG) indices used to guide anesthetic dosing in adults are not validated in young infants. Raw EEG can be processed mathematically, yielding quantitative EEG parameters (qEEG). We hypothesized that machine learning combined with qEEG can accurately classify expired sevoflurane concentrations in young infants. Knowledge from this may contribute to development of future infant-specific EEG algorithms.