Diabetes Autoimmune

The goal of this randomized controlled trial is to compare the efficacy and safety of the iLet Bionic Pancreas (BP) System in adults with insulin-treated diabetes (type 1 diabetes or type 2 diabetes) compared to standard of care when ordered by primary care providers. The main question it aims to answer is: Can the iLet BP by deployed in primary care settings to adults with insulin-treated diabetes (type 1 diabetes or type 2 diabetes)? Researchers will compare 13-weeks of iLet BP use to routine care to see if iLet BP use has a greater reduction in HbA1c compared to13-weeks of routine care. Participants will: Use the iLet BP for 13-weeks or continue their routine care Be trained to use the study devices or continue their routine care Complete a virtual screening visit, mid-period follow up calls and a final visit Complete baseline CGM collection Complete surveys and fingerstick a1c blood tests Routine care participants will have the option to complete an observational extension phase where they will wear the iLet BP for 13-weeks

This study is designed to compare two behavioral approaches to reduce diabetes distress ("the expected burdens, concerns, fears, and threats that arise from the challenges of living with diabetes") in adults with type 1 diabetes. At the study baseline, participants will be randomized to take part in one of two virtual, group-based interventions (the "Primary" intervention) utilizing either an emotions-focused or a problem-solving approach to reduce diabetes distress. After the initial intervention, participants will complete surveys to assess their response to the material. Participants who are determined to be "non-responders" (i.e., the Primary intervention was not effective) will be re-randomized to one of two "Supplementary" interventions, which will include individualized sessions to learn and/or practice strategies related to either the psychological or problem-solving approach.

The goal of this observational study is to validate medico-administrative algorithms that classify diabetes phenotypes (Type 1, Type 2, and Latent Autoimmune Diabetes in Adults - LADA) in a population-based cohort in Quebec, including children, adolescents, and young adults up to 40 years old with diagnosed diabetes. The main questions it aims to answer are: Can these algorithms accurately distinguish between Type 1, Type 2, and LADA across different age groups? What is the prevalence and incidence of each diabetes phenotype in Quebec? Participants will have their medical and administrative data analyzed, including data on medication usage and healthcare visits, to validate the accuracy of the algorithms. The study will involve comparing these algorithm-based classifications with clinical diagnoses or self-reported data to ensure reliability.