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 (Impact Factor 2016: 5.175), 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.
Jun 7, 2017
Jun 6, 2017
May 3, 2017
Apr 4, 2017
Mar 7, 2017
Feb 15, 2017
Feb 6, 2017
Jan 23, 2017
Jan 17, 2017
Dec 14, 2016
Dec 13, 2016
Nov 7, 2016
Citing this Article
Right click to copy or hit: ctrl+c (cmd+c on mac)
Latest Submissions Open for Peer-Review:View All Open Peer Review Articles
Behavioral and medical mechanisms that link diabetes to disability depend on the intersection of place and gender
Date Submitted: Jun 23, 2017
Open Peer Review Period: Jun 25, 2017 - Aug 20, 2017
Background: The mechanisms that link diabetes to disability may vary across populations. Objective: This study investigated gender by place differences in the behavioral and medical mechanisms behind...
Background: The mechanisms that link diabetes to disability may vary across populations. Objective: This study investigated gender by place differences in the behavioral and medical mechanisms behind the link between diabetes (DM) and disability in eight countries. Methods: We borrowed data from Research on Early Life and Aging Trends and Effects (RELATE). This analysis included adults from eight countries including Barbados, Brazil, Costa Rica, Chile, Cuba, Puerto Rico, Mexico, and Uruguay. Diabetes was the independent variable, disability (activities of daily living) was the dependent variable, socioeconomics, obesity, health behaviors, and comorbidities were covariates, and gender was the moderator. We used country by gender specific- logistic regressions to test the effect of DM on disability after adjusting for socioeconomics (Model 1), socioeconomics, health behaviors, and obesity (Model 2), and socioeconomics, obesity, health behaviors, and medical comorbid conditions (Model 3). Results: Gender by country specific patterns of association between DM and disability were observed in Puerto Rico, Mexico, Brazil, Chile, and Cuba. In Puerto Rico, in men, DM – ADL could be explained by health behaviors and obesity, for women, however, the impact of DM on ADL was above all confounders for women. In Mexico, for men, DM was not associated with disability, however, for women, there was a link which could be explained by health behaviors and obesity. In Brazil, for men, DM – ADL limitation link could be fully explained by health behaviors and obesity, for women, however, DM was not associated with ADL at all. In Chile, for men, DM was not associated with ADL limitation, for women, however, there was an association between DM and ADL limitation which could not be explained by health behaviors, obesity, or comorbid medical conditions. In Cuba, for men, health behaviors and obesity fully mediated the effect of DM on ADL, for women, however, this link was mediated by comorbid medical conditions. Conclusions: Gender by place differences exist in the link between DM and disability, as well as behavioral and medical mechanisms behind such link. These findings advocate for the intersectionality approach in studying burden of illnesses such as DM.
User Participation and Engagement with the See Me Smoke-Free mHealth App: Results of a Prospective Feasibility Trial
Date Submitted: Apr 21, 2017
Open Peer Review Period: May 31, 2017 - Jul 14, 2017
Background: The See Me Smoke-Free (SMSF) mobile health (mHealth) application (app) was developed to help women quit smoking by targeting concerns about body weight, body image, and self-efficacy throu...
Background: The See Me Smoke-Free (SMSF) mobile health (mHealth) application (app) was developed to help women quit smoking by targeting concerns about body weight, body image, and self-efficacy through cognitive behavioral techniques and guided imagery audio files addressing smoking, diet, and physical activity. A feasibility trial found associations between SMSF usage and positive treatment outcomes. This paper reports a detailed exploration of program use among those who downloaded the app, and the relationship between program use and treatment outcomes. Objective: To determine whether: 1) participants were more likely to set quit dates, be current smokers, and report higher levels of smoking at baseline than non-participants; 2) participants opened the app and listened to audio files more frequently than non-participants; and 3) participants with more app usage had a higher likelihood of smoking abstinence at follow-up. Methods: The SMSF feasibility trial was a single arm, within-subjects, prospective cohort study with assessments at baseline, 30- and 90-days post-enrollment. The SMSF app was deployed on the Google Play store for download, and basic profile characteristics were obtained for all app installers. Additional variables were assessed for study participants. Participants were prompted to use the app daily during study participation. Crude differences in baseline characteristics between trial participants and non-participants were evaluated using t-tests (continuous variables) and Fisher’s exact tests (categorical variables). Exact Poisson tests were used to assess group-level differences in mean usage rates over the full study period, using aggregate Google Analytics data on participation and usage. Negative binomial regression models were used to estimate associations of app usage with participant baseline characteristics, after adjustment for putative confounders. Associations between app usage and smoking abstinence were assessed using separate logistic regression models for each outcome measure. Results: Participants (n=151) were more likely than non-participants (n=96) to report female gender (P < 0.02) and smoking in the 30 days prior to enrollment (P < 0.0001). Participants and non-participants opened the app and updated quit dates at the same average rate (Rate ratio (RR) 0.98; 95% CI: 0.92, 1.04; P = 0.43), but participants started audio files (RR 1.07; 95% CI: 1.00, 1.13; P < 0.04) and completed audio files (RR 1.11; 95% CI: 1.03, 1.18; P < 0.003) at significantly higher rates than non-participants. Higher app usage among participants was generally associated with increased smoking cessation, and most effect sizes suggested strong associations, though generally without statistical significance. Conclusions: The current study suggests potential efficacy of the SMSF app, as increased usage was generally associated with higher smoking abstinence. A planned randomized controlled trial will assess the SMSF app’s efficacy as an intervention tool to help women quit smoking. Clinical Trial: ClinicalTrials.gov NCT02972515
Low- and No-Cost Strategies to Recruit Women to a Mobile Health Smoking Cessation Trial
Date Submitted: Jan 19, 2017
Open Peer Review Period: May 31, 2017 - Jul 14, 2017
Background: Successful recruitment and retention of adequate numbers of participants to mobile health (mHealth) studies remains a challenge. Given that researchers must decide how to invest limited re...
Background: Successful recruitment and retention of adequate numbers of participants to mobile health (mHealth) studies remains a challenge. Given that researchers must decide how to invest limited recruitment resources, it is important to identify the most effective recruitment strategies, defined as those that incur low costs relative to participant yield. Objective: The objective of this manuscript is to describe the development and implementation process for the recruitment phase of an mHealth intervention designed to increase smoking cessation among weight-concerned women smokers. These recruitment methods could be applicable across a range of mHealth studies. Methods: Study information was released to the media in multiple phases. First, local city and state media were contacted, followed by national women’s health media, and finally outlets in states with high smoking rates. Stories and mentions resulting from the press releases (earned media) were disseminated via existing department and new study-specific social media accounts. Strategic hashtags were used in Facebook and Twitter posts to connect with broader smoking cessation campaigns. Posts were also made to third-party Facebook smoking cessation communities and Internet classifieds sites. Results: Media coverage was documented across 75 publications and radio/television broadcasts, 35 of which were local, 39 national, and 1 international. Between March 30th and July 31st, 2015, 151 participants were successfully recruited to the study. Conclusions: Leveraging social media, and coordinating with university public affairs offices were effective and low-cost strategies to earn media coverage, and reach potential participants. Clinical Trial: Not Applicable
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.