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The New South Wales Child Development Study was established to enable a life course epidemiological approach to identifying risk and protective factors
We examined associations between developmental vulnerability profiles determined at the age of 5 years and subsequent childhood mental illness between ages 6 and 13 years in an Australian population cohort.
Patterns of early childhood developmental vulnerabilities may provide useful indicators for particular mental disorder outcomes in later life
Student bullying behaviours are a significant social issue in schools worldwide. Whilst school staff have access to quality bullying prevention interventions, schools can face significant challenges implementing the whole-school approach required to address the complexity of these behaviours.
Trans youth are at high risk of mental health difficulties and negative life events. Strong parental support is highly protective however there is little understanding of what factors facilitate the process of parental understanding and acceptance of a child’s gender identity.
This study finds that the Early Development Instrument shows moderate validity and reliability in poor communities in Indonesia
This article examines the relationship between preschool quality and children’s early development in a sample of over 7900 children enrolled in 578 preschools in rural Indonesia.
The aim of the current study was to investigate the risk factors present at 2 years for children who showed language difficulties that persisted
The Kids in Communities Study will test and investigate community-level influences on child development across Australia
The mental health and wellbeing of young people has important consequences for students and society. Schools are a logical environment for management and early intervention of wellbeing, mental health and engagement with school. Interventions aimed at improving mental health and wellbeing in education systems requires knowledge of how wellbeing is clustered at a school level. Cluster-randomised trials, and regression analyses of such data also require knowledge of clustering.