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News & Events

Urgent change needed to Close the Gap

There is an urgent need for improved cultural safety for Aboriginal and Torres Strait Islander young people in mental healthcare, new research has revealed.

News & Events

Safe use of mobile phones with T1D

The advancement of technology to assist the daily routine of diabetes is extremely helpful. However, it is important to create clear boundaries in the use of technology. Our social work team have some great tips to set up healthy routines.

News & Events

Leading researchers to explore online abuse in regions

Researchers at The Kids Research Institute Australia are working with boys and young men in regional areas to help stamp out technology-based abuse of girls and young women.

Research

Pre-service teachers: Knowledge, attitudes and their perceived skills in addressing student bullying

The lack of skills in managing future bullying and particularly cyberbullying incidents reported by pre-service teachers has social and emotional implications for young people

Research

Seventh Annual Conference of inVIVO Planetary Health on Transforming Life: Unify Personal, Public, and Planetary Health

Here we present the collection of abstracts of invited lectures and oral communications presented during the 7th inVIVO Planetary Health Conference

Research

Prevalence of allergic sensitization, hay fever, eczema, and asthma in a longitudinal birth cohort

The aim of this study was to longitudinally assess the prevalence of allergic sensitization, asthma, eczema and hay fever from infancy to adulthood

Research

Atopy-dependent and independent immune responses in the heightened severity of atopics to respiratory viral infections: Rat model studies

The co-exposure responses in the Th2high BN incorporated type I interferon/Th1, alternative macrophage activation/Th2 and Th17 signatures

Research

Predicting language difficulties in middle childhood from early developmental milestones: A comparison of traditional regression and machine learning techniques

The current study provides preliminary evidence that machine learning algorithms provide equivalent predictive accuracy to traditional methods for language difficulties in middle childhood