JMIR Diabetes

Technologies evolve at a breakneck pace, and the success of mobile health (mHealth) for people with type 2 diabetes mellitus (T2DM) depends on whether health care professionals, care management, government regulators, and consumers will adopt the technology as a viable solution to enhance patient self-management.

Gestational diabetes mellitus (GDM) is an increasingly common high-risk pregnancy condition requiring intensive daily self-management, placing the burden of care directly on the patient. Understanding personal and cultural differences among patients is critical for delivering optimal support for GDM self-management, particularly in high-risk populations. Although mobile apps for GDM self-management are being used, limited research has been done on the personalized and culturally tailored features of these apps and their impact on patient self-management.

Diabetes is a significant health concern in sub-Saharan Africa, emphasising the importance of assessing the health literacy and eHealth skills of hospitalised diabetic patients. This study evaluated the health literacy and eHealth literacy of diabetic patients at Donka Hospital in Guinea and Sanou Sourou Hospital in Burkina Faso, providing insights for targeted interventions and mHealth solutions to improve self-management and treatment outcomes.

Wearable devices can simultaneously collect data on multiple items in real time and are used for disease detection, prediction, diagnosis, and treatment decision-making. Several factors, such as diet and exercise, influence blood glucose levels; however, the relationship between blood glucose and these factors has yet to be evaluated in real practice.

One in eleven people receive primary care from a federally qualified health center (FQHC) in the U.S. Text-messaging interventions (TMI) are accessible ways to deliver health information, engage patients, and improve health outcomes in the health center setting.

The management of type 2 diabetes mellitus (T2DM) includes mastery of complex care activities, self-management skills, and routine health care encounters to optimize glucose control and achieve good health. Given the lifelong course of T2DM, patients are faced with navigating complex medical and disease-specific information. This health-seeking behavior is a driver of health disparities and is associated with hospitalization and readmission. Given that health-seeking behavior is a potentially intervenable social determinant of health, a better understanding of how people navigate these complex systems is warranted.

Highly effective anti-obesity and diabetes medications such as glucagon-like peptide 1 (GLP-1) agonists and glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 (dual) receptor agonists (RAs) have ushered in a new era of treatment of these highly prevalent, morbid conditions that have increased across the globe. However, the rapidly escalating use of GLP-1/dual RA medications is poised to overwhelm an already overburdened HCP workforce and healthcare delivery system; stifling its potentially dramatic benefits. Relying on existing systems and resources to address the oncoming rise in GLP-1/dual RA use will be insufficient. Generative artificial intelligence (GenAI) has the potential to offset the clinical and administrative demands associated with the management of patients on these medication types. Early adoption of GenAI to facilitate the management of these GLP-1/dual RAs has the potential to improve health outcomes while decreasing its concomitant workload. Research and development efforts are urgently needed to develop GenAI obesity medication management tools, as well as ensure their accessibility and utility by encouraging their integration into healthcare delivery systems.

Type 1 diabetes is a demanding chronic condition that requires diligent blood glucose monitoring and timely insulin administration by patients who must integrate self-management into their daily lives.

In home remote foot temperature monitoring (RTM) holds promise as a method to reduce foot ulceration in high-risk patients with diabetes. Few studies have evaluated adherence to this method, or evaluated factors associated with non-compliance.

Importance: Type 2 diabetes mellitus (T2D) is a common health issue, with heart failure (HF) being the common and lethal long-term complication. Although insulin is widely used for the treatment of T2D, evidence regarding the efficacy of insulin compared to non-insulin therapies on incident heart failure risk is missing among randomized clinical trials. Real-world evidence on insulin’s effect on long-term heart failure may supplement existing guidelines on the management of T2D.

Mobile apps designed with cultural sensitivity have demonstrated higher user acceptability and greater effectiveness in enhancing self-care skills. However, a significant gap exists in developing such apps for specific populations, such as Portuguese Americans living in southern Massachusetts, home to the second-largest Portuguese community in the United States. This group possesses unique cultural traditions, particularly in dietary practices, including a tendency toward high carbohydrate intake. Tailoring diabetes self-care apps to address these specific cultural requirements could substantially improve diabetes management within this population.

Patients with diabetes experience worse health outcomes and greater health care expenditure. Improving diabetes outcomes requires involved self-management. Peer coaching programs can help patients engage in self-management while addressing individual and structural barriers. These peer coaching programs can be scaled with digital platforms to efficiently connect patients with peer supporters who can help with diabetes self-management.