Search
Tools that can be used to collect behavioural data during pandemics are needed to inform policy and practice. The objective of this project was to develop the Your COVID-19 Risk tool in response to the global spread of COVID-19, aiming to promote health behaviour change. We developed an online resource based on key behavioural evidence-based risk factors related to contracting and spreading COVID-19. This tool allows for assessing risk and provides instant support to protect individuals from infection.
The evidence about the acceptability and effectiveness of innovative paediatric models of care for Type 1 diabetes is limited. To address this gap, we synthesised literature on implemented models of care, model components, outcomes, and determinants of implementation and sustainability.
One third of Australian children diagnosed with type 1 diabetes present with life-threatening diabetic ketoacidosis (DKA) at diagnosis. Screening for early-stage, presymptomatic type 1 diabetes, with ongoing follow-up, can substantially reduce this risk (<5% risk). Several screening models are being trialled internationally, without consensus on the optimal approach. This pilot study aims to assess three models for a routine, population-wide screening programme in Australia.
The ESCALATION system is a novel paediatric Early Warning System that incorporates family involvement and sepsis recognition. This study aimed to assess the feasibility and iteratively refine the ESCALATION system in a variety of hospital settings in preparation for full-service implementation.
Dietary patterns characterised by high intakes of vegetables may lower the risk of pre-eclampsia and premature birth in the general population. The effect of dietary patterns in women with type 1 diabetes, who have an increased risk of complications in pregnancy, is not known.
To explore parents' experiences of using continuous glucose monitoring in their young children with early-stage type 1 diabetes, being followed in the Australian Environmental Determinants of Islet Autoimmunity (ENDIA) study.
Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.
This study aims to describe the risk factors and trends in birth prevalence of septo-optic dysplasia (SOD) and gastroschisis between 1980 and 2023. This descriptive, population-based study of SOD and gastroschisis used Western Australian Register of Developmental Anomalies data from 1980 to 2023. Birth prevalence was calculated using Midwives Notification System data for all births after 20 weeks gestation.
The relationship between diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes and long-term glycemic control varies between studies. We aimed, firstly, to characterize the association of DKA and its severity with long-term HbA1c in a large contemporary cohort, and secondly, to identify other independent determinants of long-term HbA1c.
Tim Jones MBBS DCH FRACP MD Co-head, Diabetes and Obesity Research Co-head, Diabetes and Obesity Research Areas of research expertise: Diabetes