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Despite the volume of accumulating knowledge from prospective Aboriginal cohort studies, longitudinal data describing developmental trajectories in health and well-being is limited.
Globally, nearly 9 million people are living with type 1 diabetes (T1D). Although the incidence of T1D is not affected by socioeconomic status, the development of complications and limited access to modern therapy is overrepresented in vulnerable populations. Diabetes technology, specifically continuous glucose monitoring and automated insulin delivery systems, are considered the gold standard for management of T1D, yet access to these technologies varies widely across countries and regions, and varies widely even within high-income countries.
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.
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.
Blood glucose management around exercise is challenging for youth with type 1 diabetes (T1D). Previous research has indicated interventions including decision-support aids to better support youth to effectively contextualize blood glucose results and take appropriate action to optimize glucose levels during and after exercise. Mobile health (mHealth) apps help deliver health behavior interventions to youth with T1D, given the use of technology for glucose monitoring, insulin dosing, and carbohydrate counting.
Advanced hybrid closed-loop (AHCL) therapy improves glycemia. However, it is not known if there is an improvement in overall outcomes with AHCL for youth with type 1 diabetes (T1D) at high risk of diabetes-related complications. The study aimed to capture the experiences of youth with suboptimal glycemic control when commencing AHCL therapy in a clinical trial setting.
A type 1 diabetes (T1D) transition clinic in Sydney, Australia, provides age specific care for young adults (aged 16-25 years) and for adults (aged 21 years and above), and has reported improved clinical outcomes post transition to adult care over a 21-year period. This study investigated the contribution of digital technology to long-term resilient capacity of the clinic.
Continuous glucose monitoring (CGM) can detect early dysglycemia in older children and adults with presymptomatic type 1 diabetes and predict risk of progression to clinical onset. However, CGM data for very young children at greatest risk of disease progression are lacking.
Humans are commonly exposed to plastic through their dietary intake and food consumption patterns. Plastic-associated chemicals (PAC), such as bisphenols and phthalates, are recognized as endocrine-disrupting and are associated with increased risk of cardiovascular disease and metabolic syndrome. However, accurate methods to assess dietary exposure to plastic products and PAC are inadequate, limiting interrogation of health impacts.
Behavior change techniques (BCTs) have been extensively used in physical activity interventions for children, however, no systematic reviews have synthesized their effects.