Emerging Technologies, Medical Devices, Apps, Sensors, and Informatics to Help People with Diabetes.
JMIR Diabetes (JD) is a new sister journal of JMIR (the leading open-access journal in health informatics with a 2015 impact factor of 4.532) focusing on technologies, medical devices, apps, engineering, informatics and patient education for diabetes prevention, self-management, care, and cure, to help people with diabetes. As open access journal we are read by clinicians and patients alike and have (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 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.
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Latest Submissions Open for Peer-Review:View All Open Peer Review Articles
Using data cubes to construct a disease-gene-drug association network for diabetes mellitus
Date Submitted: May 16, 2017
Open Peer Review Period: May 19, 2017 - Jul 14, 2017
Background: In this post-genomic big-data era, genomic approaches are increasingly used to search for potential new drugs and treatments for diseases. Large-scale data mining of biomedical literature...
Background: In this post-genomic big-data era, genomic approaches are increasingly used to search for potential new drugs and treatments for diseases. Large-scale data mining of biomedical literature is an essential tool for investigating and predicting the relationships between causal genes and treatments of diabetes mellitus (DM). Objective: The objective of the study is to construct a disease-gene-drug association network for diabetes mellitus and predict some new associations. Methods: Based on textual data, we developed a novel, data cube–based approach for constructing a disease-gene-drug association network for DM. We used association rules to measure the associations between biological entities. Results: We obtained phenotypic, genotypic, and treatment drug data for DM from the PubMed database. After data preprocessing, we constructed the 0-D vertex cube, which we then filtered to construct three 1-D cubes consisting of 14 diseases, 23 genes, and 34 drugs. We found 194 associations between the 14 subclasses of DM and the 23 genes, 75 associations between 11 of the DM subclasses and 24 of the drugs, and 142 associations between 14 of the DM-related genes and 15 of the drugs. By applying association rules to quantify the correlation between the disease phenotypes, genes, and treatment drugs, we established three 2-D cubes and three relational networks. Finally, using the bottom-up computation algorithm, we constructed the 3-D disease-gene-drug network, which revealed 411 associations between 14 subclasses of DM, 23 genes, and 24 drugs. Based on this 3-D network, we constructed 8 optimal disease-gene-drug subnetworks of DM. Conclusions: We have implemented and validated a network-based approach to identifying and ranking the hidden associations between diseases, genes, and drugs. Our results provide new potential pathways in the search for DM treatment drugs.
Smartphone Apps for Gestational Diabetes: A Scoping Review Examining Functionality, Implementation, Impact and the Role of Health Literacy
Date Submitted: May 14, 2017
Open Peer Review Period: May 17, 2017 - Jul 12, 2017
Background: The increasing ownership of smartphones and advances in hardware and software position these devices as cost-effective personalized tools for health promotion and management among women wi...
Background: The increasing ownership of smartphones and advances in hardware and software position these devices as cost-effective personalized tools for health promotion and management among women with gestational diabetes mellitus (GDM). Numerous smartphone apps are available online; however, no review has documented how these apps are developed and evaluated in relation to gestational diabetes. Objective: To answer the following two research questions: (1) What is known from the existing literature about the availability, functionality, and effectiveness of smartphone apps on GDM prevention and management? And (2) What is the role of health literacy in these apps? Methods: Seven relevant electronic databases were searched for original research documents using terms related to smartphone apps, GDM, and health literacy. Selected articles were thematically categorized using a framework adapted from Arksey & O'Malley. Results: Twelve articles related to seven app/systems were included in the final analysis. Articles were classified around two themes: (1) description of the development, feasibility or usability of the apps/systems, and (2) trial protocols. Varying degrees of personalization exist in the apps for GDM and decision support systems (DSSs) can be used to generate time-efficient personalized feedback for both patients and healthcare providers. Health literacy was considered during the development or measured as an outcome by some apps. Conclusions: There is a limited body of research on smartphone apps in relation to GDM prevention and management. Smartphone apps can provide time- and cost-efficient personalized interventions for GDM. Several randomized controlled trials (RCT) have been launched recently to evaluate the effectiveness of the apps. Consideration of health literacy should be improved when developing features of the apps.
Digital Health for Medication Adherence in Adult Diabetes or Hypertension: An Integrative Review
Date Submitted: May 12, 2017
Open Peer Review Period: May 13, 2017 - Jul 8, 2017
Background: Optimal management of chronic diseases, such as type 2 diabetes (T2D) and hypertension (HTN) often include prescription medications. Medication adherence (MA)is one component of self-manag...
Background: Optimal management of chronic diseases, such as type 2 diabetes (T2D) and hypertension (HTN) often include prescription medications. Medication adherence (MA)is one component of self-management. Optimization through digital health (eHealth and mHealth) could enhance patient awareness and/or communication between the patient and provider. Objective: Medication Adherence (MA) is a major issue that affects 50-60% of chronically ill adults. Digital health refers to eHealth and mHealth collectively  and as these technologies become more accessible, remote health delivery is increasingly available as an adjunct to improve medication adherence, communicate with patients and providers, and provide education to patients, families and communities. The objective of this integrative review was to examine the types of digital health technologies that targeted medication adherence in the adult population with diabetes or hypertension. Methods: An integrative review was conducted using databases within EbscoHost, PubMed, and Scopus. Eligible studies available as of September 2016 had to be written in English, and contain digital health interventions to improve medication adherence to prescription medications in adults (18 years or older), and focus on diabetes or hypertension. Results: Of the 337 located studies, 12 used a digital health intervention to promote medication adherence to prescribed medications for diabetes or hypertension and were assessed according to the Chronic Care Model. Conclusions: The twelve studies included in this review found no conclusive evidence of improved medication adherence using digital health interventions such as Interactive Voice Response (IVR), Short Message Service (SMS), telemonitoring, and interactive software technology. Among those are digital health interventions that foster medication adherence via one-way communication to the patient or two-way communication between the patient and healthcare provider for adjunct medication adherence strategies. More research is needed to determine which digital health interventions are most beneficial for individuals with diabetes or hypertension.