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Research

Yarning about yarning as a legitimate method in Indigenous Research

This article demonstrates the credibility and rigor of yarning, an Indigenous cultural form of conversation, through its use as a data gathering tool

Aboriginal Health and Wellbeing

The Aboriginal Health and Wellbeing Team follows an holistic definition of Aboriginal Health which means that health is not just the physical wellbeing of an individual but includes the social, emotional and cultural wellbeing of the whole community.

People

Associate Professor Glenn Pearson

Director of First Nations Strategy and Leadership; Head, First Nations Health and Equity Research

Research

Adjusting for under-identification of Aboriginal and/or Torres Strait Islander births in time series produced from birth records

Statistical time series derived from administrative data sets form key indicators in measuring progress.

Research

Social Gradients in Indigenous Health

The pattern of association between socioeconomic factors and health outcomes has primarily depicted better health for those who are higher in the social...

Research

Ngulluk Moort, Ngulluk Boodja, Ngulluk Wirin (our family, our country, our spirit): An Aboriginal Participatory Action Research study protocol

We are working with the leadership and staff at foster care agencies and community members to provide information about cultural connection, and cultural activity and resources for Aboriginal children living in non-Aboriginal care arrangements.

News & Events

Ideas Grants to support innovative research

Two research teams, led by The Kids Research Institute Australia, have been awarded more than $2 million to fund innovative projects.

Research

The Child Mortality Research Program

Brad Carrington Fiona Farrant Shepherd Stanley BSc (Hons), PhD PhD FAA FASSA MSc MD FFPHM FAFPHM FRACP FRANZCOG HonDSc HonDUniv HonFRACGP HonMD

Research

Evidence for the use of an algorithm in resolving inconsistent and missing Indigenous status in administrative data collections

We found that algorithms reduced the amount of missing data and improved within‑individual consistency.