JMIR Diabetes

Emerging technologies, medical devices, apps, sensors, and informatics to help people with diabetes

Editor-in-Chief:

Caroline R. Richardson, MD, Department of Family Medicine, University of Michigan Medical School, USA


JMIR Diabetes (JD, Editor-in-Chief: Caroline Richardson) is a PubMed-indexed journal of JMIR, the leading open-access journal in health informatics. JMIR Diabetes focuses on technologies, medical devices, apps, engineering, informatics and patient education for diabetes prevention, self-management, care, and cure, to help people with diabetes.

As an open access journal, JD is read by clinicians and patients alike and has (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies, as well as on diabetes prevention and epidemiology.

We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews) covering for example wearable devices and trackers, mobile apps, glucose monitoring (including emerging technologies such as Google contact lens), medical devices for insulin and metabolic peptide delivery, closed loop systems and artificial pancreas, telemedicine, web-based diabetes education and elearning, innovations for patient self-management and "quantified self," diabetes-specific EHR improvements, clinical or consumer-focused software, diabetes epidemiology and surveillance, crowdsourcing and quantified self-based research data, new sensors and actuators to be applied to diabetes.

Recent Articles

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Diabetes Health Services and System Innovations

Both primary care practices based on the chronic care model (CCM) and digital therapeutics have been shown to improve the care of patients with diabetes.

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Telemedicine for Diabetes

Diabetes is present in 10.5% of the US population and accounts for 14.3% of all office-based physician visits made by adults. Despite this established office-based approach, the disease and its adverse outcomes including glycemic control and clinical events tend to worsen over time. Available home technology now provides accurate, reliable data that can be transmitted directly to the electronic medical record.

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Apps, Mobile, Wearables for Diabetes

Type 1 diabetes (T1D) is one of the most common chronic childhood diseases, and its prevalence is rapidly increasing. The management of glucose in T1D is challenging, as youth must consider a myriad of factors when making diabetes care decisions. This task often leads to significant hyperglycemia, hypoglycemia, and glucose variability throughout the day, which have been associated with short- and long-term medical complications. At present, most of what is known about each of these complications and the health behaviors that may lead to them have been uncovered in the clinical setting or in laboratory-based research. However, the tools often used in these settings are limited in their ability to capture the dynamic behaviors, feelings, and physiological changes associated with T1D that fluctuate from moment to moment throughout the day. A better understanding of T1D in daily life could potentially aid in the development of interventions to improve diabetes care and mitigate the negative medical consequences associated with it. Therefore, there is a need to measure repeated, real-time, and real-world features of this disease in youth. This approach is known as ecological momentary assessment (EMA), and it has considerable advantages to in-lab research. Thus, this viewpoint aims to describe EMA tools that have been used to collect data in the daily lives of youth with T1D and discuss studies that explored the nuances of T1D in daily life using these methods. This viewpoint focuses on the following EMA methods: continuous glucose monitoring, actigraphy, ambulatory blood pressure monitoring, personal digital assistants, smartphones, and phone-based systems. The viewpoint also discusses the benefits of using EMA methods to collect important data that might not otherwise be collected in the laboratory and the limitations of each tool, future directions of the field, and possible clinical implications for their use.

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Diabetes Self-Management

Traditional lifestyle interventions have shown limited success in improving diabetes-related outcomes. Digital interventions with continuously available support and personalized educational content may offer unique advantages for self-management and glycemic control.

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Diabetes Self-Management

The development of evidence-based care geared towards Black and Latina women living with uncontrolled type 2 diabetes is contingent upon their active recruitment into clinical interventions. Well-documented impediments to recruitment include a historical mistrust of the research community and socioeconomic factors that limit awareness and access to research studies. Although sociocultural and socioeconomic factors deter minorities from participating in clinical research, it is equally important to consider the role of stigma in chronic disease intervention studies.

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Glucose Tracking and Self-Monitoring of Blood Glucose

Predictive alerts for impending hypoglycemic events enable persons with type 1 diabetes to take preventive actions and avoid serious consequences.

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Artificial Intelligence in Diabetes Care and Prevention

Between 2013 and 2015, the UK Biobank collected accelerometer traces from 103,712 volunteers aged between 40 and 69 years using wrist-worn triaxial accelerometers for 1 week. This data set has been used in the past to verify that individuals with chronic diseases exhibit reduced activity levels compared with healthy populations. However, the data set is likely to be noisy, as the devices were allocated to participants without a set of inclusion criteria, and the traces reflect free-living conditions.

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Telemedicine for Diabetes

The prevalence of diabetes mellitus (DM) is increasing rapidly worldwide. Simultaneously, technological advances are offering new opportunities for better management of type 1 diabetes mellitus (T1DM). Telemetry, the remote acquisition of patient data via a telecommunication system, is a promising field of application in eHealth and is rapidly gaining importance.

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Telemedicine for Diabetes

Patients with poorly controlled type 2 diabetes (T2D) experience increased morbidity, increased mortality, and higher cost of care. Self-monitoring of blood glucose (SMBG) is a critical component of diabetes self-management with established diabetes outcome benefits. Technological advancements in blood glucose meters, including cellular-connected devices that automatically upload SMBG data to secure cloud-based databases, allow for improved sharing and monitoring of SMBG data. Real-time monitoring of SMBG data presents opportunities to provide timely support to patients that is responsive to abnormal SMBG recordings. Such diabetes remote monitoring programs can provide patients with poorly controlled T2D additional support needed to improve critical outcomes.

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Diabetes Self-Management

Translation of diabetes self-management education and support (DSMES) into a digital format can improve access, but few digital programs have demonstrated outcomes using rigorous evaluation metrics.

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Apps, Mobile, Wearables for Diabetes

The use of remote data capture for monitoring blood glucose and supporting digital apps is becoming the norm in diabetes care. One common goal of such apps is to increase user awareness and engagement with their day-to-day health-related behaviors (digital engagement) in order to improve diabetes outcomes. However, we lack a deep understanding of the complicated association between digital engagement and diabetes outcomes.

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