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The EU LifeCycle Project was launched in 2017 to combine, harmonise, and analyse data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview over the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project.
The optimal time to bolus insulin for meals is challenging for children and adolescents with type 1 diabetes (T1D). Current guidelines to control glucose excursions do not account for individual differences in glycaemic responses to meals.
Current strategies to reduce cardiovascular disease (CVD) risk in young adults are largely limited to those at extremes of risk. In cohort studies we have shown cluster analysis identified a large sub-group of adolescents with multiple risk factors.
Empowering young people with type 1 diabetes (T1D) to manage their blood glucose levels during exercise is a complex challenge faced by health care professionals due to the unpredictable nature of exercise and its effect on blood glucose levels. Mobile health (mHealth) apps would be useful as a decision-support aid to effectively contextualize a blood glucose result and take appropriate action to optimize glucose levels during and after exercise.
To determine the clinical outcomes and evaluate the perspectives of children with Type 1 diabetes (T1D) and their parents managing their child on hybrid closed-loop (HCL) therapy.
The aims of the present study were to (i) examine the relationship between children's degree of adiposity and psychosocial functioning; and (ii) compare patterns of clustering of psychosocial measures between healthy weight and overweight/obese children.
To investigate perinatal risk factors for childhood Type 1 diabetes in Western Australia, using a complete population-based cohort.
Diabetes is the name for a number of different metabolic disorders in which the body's healthy levels of blood sugar (glucose) can't be maintained.Diabetes can have a significant impact on quality of life should complications develop. Diabetes can affect the individual's entire body.
To map and systematise existing research on the use of artificial intelligence (AI) in mental health-based diabetes care contexts, identify trends and potential gaps in the literature, examine methodological limitations and highlight future research directions.
Type 1 Diabetes (T1D) is a 'family illness'; diagnoses and management can be perceived as invasive or traumatic. Caregivers bear the brunt of the diagnostic shock, influencing their child's experience. Children and adolescents may grapple with the psychological effects of past/ongoing medical trauma. Additionally, adolescents may struggle with their mental health as they navigate tensions between caregiver involvement and their developmental need for autonomy.