JMIR Publications

JMIR Diabetes

Emerging Technologies, Medical Devices, Apps, Sensors, and Informatics to Help People with Diabetes.

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Journal Description

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. 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, crowdsourcing and quantified self-based research data, new sensors and actuators to be applied to diabetes.

 

Recent Articles:

  • Image Source: Copyright sturti, via iStockPhoto. License purchased by author.
Stock file ID:516185934.

    A Novel Intervention Including Individualized Nutritional Recommendations Reduces Hemoglobin A1c Level, Medication Use, and Weight in Type 2 Diabetes

    Abstract:

    Background: Type 2 diabetes (T2D) is typically managed with a reduced fat diet plus glucose-lowering medications, the latter often promoting weight gain. Objective: We evaluated whether individuals with T2D could be taught by either on-site group or remote means to sustain adequate carbohydrate restriction to achieve nutritional ketosis as part of a comprehensive intervention, thereby improving glycemic control, decreasing medication use, and allowing clinically relevant weight loss. Methods: This study was a nonrandomized, parallel arm, outpatient intervention. Adults with T2D (N=262; mean age 54, SD 8, years; mean body mass index 41, SD 8, kg·m−2; 66.8% (175/262) women) were enrolled in an outpatient protocol providing intensive nutrition and behavioral counseling, digital coaching and education platform, and physician-guided medication management. A total of 238 participants completed the first 10 weeks. Body weight, capillary blood glucose, and beta-hydroxybutyrate (BOHB) levels were recorded daily using a mobile interface. Hemoglobin A1c (HbA1c) and related biomarkers of T2D were evaluated at baseline and 10-week follow-up. Results: Baseline HbA1c level was 7.6% (SD 1.5%) and only 52/262 (19.8%) participants had an HbA1c level of <6.5%. After 10 weeks, HbA1c level was reduced by 1.0% (SD 1.1%; 95% CI 0.9% to 1.1%, P<.001), and the percentage of individuals with an HbA1c level of <6.5% increased to 56.1% (147/262). The majority of participants (234/262, 89.3%) were taking at least one diabetes medication at baseline. By 10 weeks, 133/234 (56.8%) individuals had one or more diabetes medications reduced or eliminated. At follow-up, 47.7% of participants (125/262) achieved an HbA1c level of <6.5% while taking metformin only (n=86) or no diabetes medications (n=39). Mean body mass reduction was 7.2% (SD 3.7%; 95% CI 5.8% to 7.7%, P<.001) from baseline (117, SD 26, kg). Mean BOHB over 10 weeks was 0.6 (SD 0.6) mmol·L−1 indicating consistent carbohydrate restriction. Post hoc comparison of the remote versus on-site means of education revealed no effect of delivery method on change in HbA1c (F1,260=1.503, P=.22). Conclusions: These initial results indicate that an individualized program delivered and supported remotely that incorporates nutritional ketosis can be highly effective in improving glycemic control and weight loss in adults with T2D while significantly decreasing medication use.

  • Image Source: http://www.diabetespa.com/ (fair use).

    The Use of Mobile Health to Deliver Self-Management Support to Young People With Type 1 Diabetes: A Cross-Sectional Survey

    Abstract:

    Background: Young people living with type 1 diabetes face not only the challenges typical of adolescence, but also the challenges of daily management of their health and evolving understanding of the impact of their diagnosis on their future. Adolescence is a critical time for diabetes self-management, with a typical decline in glycemic control increasing risk for microvascular diabetes complications. To improve glycemic control, there is a need for evidence-based self-management support interventions that address the issues pertinent to this population, utilizing platforms that engage them. Increasingly, mobile health (mHealth) interventions are being developed and evaluated for this purpose with some evidence supporting improved glycemic control. A necessary step to enhance effectiveness of such approaches is to understand young people’s preferences for this mode of delivery. Objective: A cross-sectional survey was conducted to investigate the current and perceived roles of mHealth in supporting young people to manage their diabetes. Methods: Young adults (16-24 years) with type 1 diabetes in Auckland, New Zealand, were invited to take part in a survey via letter from their diabetes specialist. Results: A total of 115 young adults completed the survey (mean age 19.5 years; male 52/115, 45%; European 89/115, 77%), with all reporting they owned a mobile phone and 96% (110/115) of those were smartphones. However, smartphone apps for diabetes management had been used by only 33% (38/115) of respondents. The most commonly reported reason for not using apps was a lack of awareness that they existed. Although the majority felt they managed their diabetes well, 63% (72/115) reported wanting to learn more about diabetes and how to manage it. A total of 64% (74/115) respondents reported that they would be interested in receiving diabetes self-management support via text message (short message service, SMS). Conclusions: Current engagement with mHealth in this population appears low, although the findings from this study provide support for the use of mHealth in this group because of the ubiquity and convenience of mobile devices. mHealth has potential to provide information and support to this population, utilizing mediums commonplace for this group and with greater reach than traditional methods.

  • Diabetes Management via Mobile Health Technologies. Image source: https://pixabay.com/en/ui-mobile-app-apple-iphone-771829/. Copyright: CC0 Public Domain.

    Mixed-Methods Research in Diabetes Management via Mobile Health Technologies: A Scoping Review

    Abstract:

    Background: Considering the increasing incidence and prevalence of diabetes worldwide and the high level of patient involvement it requires, diabetes self-management is a serious issue. The use of mobile health (mHealth) in diabetes self-management has increased, but so far research has not provided sufficient information about the uses and effectiveness of mHealth-based interventions. Alternative study designs and more rigorous methodologies are needed. Mixed-methods designs may be particularly useful because both diabetes self-management and mHealth studies require integrating theoretical and methodological approaches. Objective: This scoping review aimed to examine the extent of the use of mixed-methods research in mHealth-based diabetes management studies. The methodological approaches used to conduct mixed-methods studies were analyzed, and implications for future research are provided. Methods: Guided by Arksey and O’Malley’s framework, this scoping review implemented a comprehensive search strategy including reviewing electronic databases, key journal searches, Web-based research and knowledge centers, websites, and handsearching reference lists of the studies. The studies focusing on mHealth technologies and diabetes management were included in the review if they were primary research papers published in academic journals and reported using a combination of qualitative and quantitative methods. The key data extracted from the reviewed studies include purpose of mixing, design type, stage of integration, methods of legitimation, and data collection techniques. Results: The final sample (N=14) included studies focused on the feasibility and usability of mHealth diabetes apps (n=7), behavioral measures related to the mHealth apps (n=6), and challenges of intervention delivery in the mHealth context (n=1). Reviewed studies used advanced forms of mixed-methods designs where integration occurred at multiple points and data were collected using multiple techniques. However, the majority of studies did not identify a specific mixed-methods design or use accepted terminology; nor did they justify using this approach. Conclusions: This review provided important insights into the use of mixed methods in studies focused on diabetes management via mHealth technologies. The prominent role of qualitative methods and tailored measures in diabetes self-management studies was confirmed, and the importance of using multiple techniques and approaches in this field was emphasized. This review suggests defining specific mixed-methods questions, using specific legitimation methods, and developing research designs that overcome sampling and other methodological problems in future studies.

  • Smartphone app for diabetes management. Image source: https://stock.adobe.com/ca/stock-photo/close-up-of-woman-with-smartphone-doing-blood-test/105110393. Image purchased by authors.

    Smartphone App Use for Diabetes Management: Evaluating Patient Perspectives

    Abstract:

    Background: Finding novel ways to engage patients in chronic disease management has led to increased interest in the potential of mobile health technologies for the management of diabetes. There is currently a wealth of smartphone apps for diabetes management that are available for free download or purchase. However, the usability and desirability of these apps has not been extensively studied. These are important considerations, as these apps must be accepted by the patient population at a practical level if they are to be utilized. Objective: The purpose of this study was to gain insight into patient experiences related to the use of smartphone apps for the management of type 1 diabetes. Methods: Adults with type 1 diabetes who had previously (or currently) used apps to manage their diabetes were eligible to participate. Participants (n=12) completed a questionnaire in which they were required to list the names of preferred apps and indicate which app functions they had used. Participants were given the opportunity to comment on app functions that they perceived to be missing from the current technology. Participants were also asked whether they had previously paid for an app and whether they would be willing to do so. Results: MyFitnessPal and iBGStar were the apps most commonly listed as the best available on the market. Blood glucose tracking, carbohydrate counting, and activity tracking were the most commonly used features. Ten participants fulfilled all eligibility criteria, and indicated that they had not encountered any one app that included all of the functions that they had used. The ability to synchronize an app with a glucometer or insulin pump was the most common function that participants stated was missing from current app technology. One participant had previously paid for a diabetes-related app and the other 9 participants indicated that they would be willing to pay. Conclusions: Despite dissatisfaction with the currently available apps, there is interest in using these tools for diabetes management. Adapting existing technology to better meet the needs of this patient population may allow these apps to become more widely utilized.

  • Depression. Image source: https://pixabay.com/en/lonely-hiding-sad-young-alone-1822414/. Author: Wokandapix. Copyright: CCO License.

    The Case for Jointly Targeting Diabetes and Depression Among Vulnerable Patients Using Digital Technology

    Abstract:

    It is well publicized that mobile and digital technologies hold great promise to improve health outcomes among patients with chronic illnesses such as diabetes. However, there is growing concern that digital health investments (both from federal research dollars and private venture investments) have not yet resulted in tangible health improvements. We see three major reasons for this limited real-world impact on health outcomes: (1) lack of solutions relevant for patients with multiple comorbidities or conditions, (2) lack of diverse patient populations involved in the design and early testing of products, and (3) inability to leverage existing clinical workflows to improve both patient enrollment and engagement in technology use. We discuss each of these in depth, followed by new research directions to increase effectiveness in this field.

  • An eye care professional prepares for laser surgery for diabetic retinopathy (leaking blood vessels). Image source: https://www.flickr.com/photos/nationaleyeinstitute/7543921240. Author: National Eye Institute, National Institutes of Health. Copyright: https://creativecommons.org/licenses/by/2.0/.

    Widely Viewed English Language YouTube Videos Relating to Diabetic Retinopathy: A Cross-Sectional Study

    Abstract:

    Background: An emergent source of information on health issues is the Internet. One such platform with 1 billion users is YouTube, the global video-sharing service. Objective: The purpose of this study was to describe the content and characteristics of the most widely viewed YouTube videos related to diabetic retinopathy. Methods: Videos were sorted according to number of views using the key words “diabetic retinopathy.” For each video, general descriptive information was collected. This information included date and source of upload (news, professional, or consumer), length, and total number of views as of July 18, 2016. Content categories were largely informed by a National Eye Institute fact sheet. Each video was viewed to determine which, if any, of the given content categories were present. Results: Of the 98 most widely viewed videos related to diabetic retinopathy, 42 were generated by consumers, 40 were generated by professionals, and 16 were generated from news-based sources. The largest number of views were generated from professionals (624,770/994,494, 63.82%). Compared with professional videos, consumer videos were viewed less frequently (W=622, P=.04). The main purpose of the majority of videos was to provide information (59/98, 60%), and most of the videos showed or mentioned retinopathy in general (75/98, 77%). Smaller numbers offered information about specific types of retinopathy, namely proliferative (26/98, 27%) and nonproliferative (17/98, 17%). Compared with consumer-generated videos, professional videos were 5.57 times more likely to mention that diabetic retinopathy can go unnoticed (95% CI 1.59-26.15). More than 80% (80/98) of the most widely viewed videos did not address the asymptomatic nature of the disease, only about one-third (33/98) mentioned prevention, and only 58 of the 98 videos (59%) mentioned screening. Conclusion: Future research is needed to identify aspects of YouTube videos that attract viewer attention and best practices for using this medium to increase diabetic retinopathy screening among people with diabetes.

  • iPhone user. Image source: https://pixabay.com/en/iphone-4s-technology-mobile-app-830480/. Author: MariusMB. Copyright: CC0 Public Domain.

    DiaFit: The Development of a Smart App for Patients with Type 2 Diabetes and Obesity

    Abstract:

    Background: Optimal management of chronic diseases, such as type 2 diabetes (T2D) and obesity, requires patient-provider communication and proactive self-management from the patient. Mobile apps could be an effective strategy for improving patient-provider communication and provide resources for self-management to patients themselves. Objective: The objective of this paper is to describe the development of a mobile tool for patients with T2D and obesity that utilizes an integrative approach to facilitate patient-centered app development, with patient and physician interfaces. Our implementation strategy focused on the building of a multidisciplinary team to create a user-friendly and evidence-based app, to be used by patients in a home setting or at the point-of-care. Methods: We present the iterative design, development, and testing of DiaFit, an app designed to improve the self-management of T2D and obesity, using an adapted Agile approach to software implementation. The production team consisted of experts in mobile health, nutrition sciences, and obesity; software engineers; and clinicians. Additionally, the team included citizen scientists and clinicians who acted as the de facto software clients for DiaFit and therefore interacted with the production team throughout the entire app creation, from design to testing. Results: DiaFit (version 1.0) is an open-source, inclusive iOS app that incorporates nutrition data, physical activity data, and medication and glucose values, as well as patient-reported outcomes. DiaFit supports the uploading of data from sensory devices via Bluetooth for physical activity (iOS step counts, FitBit, Apple watch) and glucose monitoring (iHealth glucose meter). The app provides summary statistics and graphics for step counts, dietary information, and glucose values that can be used by patients and their providers to make informed health decisions. The DiaFit iOS app was developed in Swift (version 2.2) with a Web back-end deployed on the Health Insurance Portability and Accountability Act compliant-ready Amazon Web Services cloud computing platform. DiaFit is publicly available on GitHub to the diabetes community at large, under the GNU General Public License agreement. Conclusions: Given the proliferation of health-related apps available to health consumers, it is essential to ensure that apps are evidence-based and user-oriented, with specific health conditions in mind. To this end, we have used a software development approach focusing on community and clinical engagement to create DiaFit, an app that assists patients with T2D and obesity to better manage their health through active communication with their providers and proactive self-management of their diseases.

  • Heatmap of diabetes-related tweets with geolocation. Image sourced and copyright owned by authors.

    Use of Social Media in the Diabetes Community: An Exploratory Analysis of Diabetes-Related Tweets

    Abstract:

    Background: Use of social media is becoming ubiquitous, and disease-related communities are forming online, including communities of interest around diabetes. Objective: Our objective was to examine diabetes-related participation on Twitter by describing the frequency and timing of diabetes-related tweets, the geography of tweets, and the types of participants over a 2-year sample of 10% of all tweets. Methods: We identified tweets with diabetes-related search terms and hashtags in a dataset of 29.6 billion tweets for the years 2013 and 2014 and extracted the text, time, location, retweet, and user information. We assessed the frequencies of tweets used across different search terms and hashtags by month and day of week and, for tweets that provided location information, by country. We also performed these analyses for a subset of tweets that used the hashtag #dsma, a social media advocacy community focused on diabetes. Random samples of user profiles in the 2 groups were also drawn and reviewed to understand the types of stakeholders participating online. Results: We found 1,368,575 diabetes-related tweets based on diabetes-related terms and hashtags. There was a seasonality to tweets; a higher proportion occurred during the month of November, which is when World Diabetes Day occurs. The subset of tweets with the #dsma were most frequent on Thursdays (coordinated universal time), which is consistent with the timing of a weekly chat organized by this online community. Approximately 2% of tweets carried geolocation information and were most prominent in the United States (on the east and west coasts), followed by Indonesia and the United Kingdom. For the user profiles randomly selected among overall tweets, we could not identify a relationship to diabetes for the majority of users; for the profiles using the #dsma hashtag, we found that patients with type 1 diabetes and their caregivers represented the largest proportion of individuals. Conclusions: Twitter is increasingly becoming a space for online conversations about diabetes. Further qualitative and quantitative content analysis is needed to understand the nature and purpose of these conversations.

  • image for table of contents.

    Evaluating the Accuracy of Google Translate for Diabetes Education Material

    Abstract:

    Background: Approximately 21% of the US population speaks a language other than English at home; many of these individuals cannot effectively communicate in English. Hispanic and Chinese Americans, in particular, are the two largest minority groups having low health literacy in the United States. Fortunately, machine-generated translations represent a novel tool that non-English speakers can use to receive and relay health education information when human interpreters are not available. Objective: The purpose of this study was to evaluate the accuracy of the Google Translate website when translating health information from English to Spanish and English to Chinese. Methods: The pamphlet, “You are the heart of your family…take care of it,” is a health education sheet for diabetes patients that outlines six tips for behavior change. Two professional translators translated the original English sentences into Spanish and Chinese. We recruited 6 certified translators (3 Spanish and 3 Chinese) to conduct blinded evaluations of the following versions: (1) sentences translated by Google Translate, and (2) sentences translated by a professional human translator. Evaluators rated the sentences on four scales: fluency, adequacy, meaning, and severity. We performed descriptive analysis to examine differences between these two versions. Results: Cronbach's alpha values exhibited high degrees of agreement on the rating outcome of both evaluator groups: .919 for the Spanish evaluators and .972 for the Chinese evaluators. The readability of the sentences in this study ranged from 2.8 to 9.0 (mean 5.4, SD 2.7). The correlation coefficients between the grade level and translation accuracy for all sentences translated by Google were negative (eg, rMeaning=-.660), which indicates that Google provided accurate translation for simple sentences. However, the likelihood of incorrect translation increased when the original English sentences required higher grade levels to comprehend. The Chinese human translator provided more accurate translation compared to Google. The Spanish human translator, on the other hand, did not provide a significantly better translation compared to Google. Conclusion: Google produced a more accurate translation from English to Spanish than English to Chinese. Some sentences translated by Google from English to Chinese exhibit the potential to result in delayed patient care. We recommend continuous training and credential practice standards for professional medical translators to enhance patient safety as well as providing health education information in multiple languages.

  • Blood glucose testing.
Image By: David-i98
License: CC BY-SA 3.0 
Source URL: https://en.wikipedia.org/wiki/File:Blood_Glucose_Testing.JPG.

    Information and Communication Technology-Powered Diabetes Self-Management Systems in China: A Study Evaluating the Features and Requirements of Apps and Patents

    Abstract:

    Background: For patients with diabetes, the self-monitoring of blood glucose (SMBG) is a recommended way of controlling the blood glucose level. By leveraging the modern information and communication technology (ICT) and the corresponding infrastructure, engineers nowadays are able to merge the SMBG activities into daily life and to dramatically reduce patient’s burden. Such type of ICT-powered SMBG had already been marketed in the United States and the European Union for a decade, but was introduced into the Chinese market only in recent years. Although there is no doubt about the general need for such type of SMBG in the Chinese market, how it could be adapted to the local technical and operational environment is still an open question. Objective: Our overall goal is to understand the local requirements and the current status of deploying ICT-powered SMBG to the Chinese market. In particular, we aim to analyze existing domestic SMBG mobile apps and relevant domestic patents to identify their various aspects, including the common functionalities, innovative feature, defects, conformance to standards, prospects, etc. In the long run, we hope the outcome of this study could help the decision making on how to properly adapt ICT-powered SMBG to the Chinese market. Methods: We identified 289 apps. After exclusion of irrelevant apps, 78 apps remained. These were downloaded and analyzed. A total of 8070 patents related to glucose were identified from patent database. Irrelevant materials and duplicates were excluded, following which 39 patents were parsed to extract the important features. These apps and patents were further compared with the corresponding requirements derived from relevant clinical guidelines and data standards. Results: The most common features of studied apps were blood health data recording, notification, and decision supporting. The most common features of studied patents included mobile terminal, server, and decision supporting. The main difference between patents and apps is that the patents had 2 specific features, namely, interface to the hospital information system and recording personal information, which were not mentioned in the app. The other major finding is that, in general, in terms of the components of the features, although the features identified in both apps and patents conform to the requirements of the relevant clinical guidelines and data standards, upon looking into the details, gaps exist between the features of the identified apps and patents and the relevant clinical guidelines and data standards. In addition, the social media feature that the apps and patents have is not included in the standard requirements list. Conclusions: The development of Chinese SMBG mobile apps and relevant patents is still in the primitive stage. Although the functionalities of most apps and patents can meet the basic requirements of SMBG, gaps have been identified when comparing the functionalities provided by apps and patents with the requirements necessitated by the standards. One of the most important gaps is that only a small portion of the studied apps provides the automatic data transmission and exchange feature, which may hamper the overall performance. The clinical guidelines can thus be further developed to leverage new features provided by ICT-powered SMBG apps (eg, the social media feature, which may help to improve the social intervention of patients with diabetes).

  • Food tracker. Source: Figure 3 from https://diabetes.jmir.org/2016/1/e1; Copyright: the authors; License: Creative Commons Attribution (CC-BY).

    Data Mining of a Remote Behavioral Tracking System for Type 2 Diabetes Patients: A Prospective Cohort Study

    Abstract:

    Background: Complications from type 2 diabetes mellitus can be prevented when patients perform health behaviors such as vigorous exercise and glucose-regulated diet. The use of smartphones for tracking such behaviors has demonstrated success in type 2 diabetes management while generating repositories of analyzable digital data, which, when better understood, may help improve care. Data mining methods were used in this study to better understand self-monitoring patterns using smartphone tracking software. Objective: Associations were evaluated between the smartphone monitoring of health behaviors and HbA1c reductions in a patient subsample with type 2 diabetes who demonstrated clinically significant benefits after participation in a randomized controlled trial. Methods: A priori association-rule algorithms, implemented in the C language, were applied to app-discretized use data involving three primary health behavior trackers (exercise, diet, and glucose monitoring) from 29 participants who achieved clinically significant HbA1c reductions. Use was evaluated in relation to improved HbA1c outcomes. Results: Analyses indicated that nearly a third (9/29, 31%) of participants used a single tracker, half (14/29, 48%) used two primary trackers, and the remainder (6/29, 21%) of the participants used three primary trackers. Decreases in HbA1c were observed across all groups (0.97-1.95%), but clinically significant reductions were more likely with use of one or two trackers rather than use of three trackers (OR 0.18, P=.04). Conclusions: Data mining techniques can reveal relevant coherent behavior patterns useful in guiding future intervention structure. It appears that focusing on using one or two trackers, in a symbolic function, was more effective (in this sample) than regular use of all three trackers.

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  • Mutual Involvement in Families with Type 2-Diabetes through Internet-based Healthcare Solutions.

    Date Submitted: Feb 6, 2017

    Open Peer Review Period: Feb 19, 2017 - Apr 16, 2017

    Background: Type 2-diabetes (T2D) is a prevalent chronic disease that affects not just the patient but the entire family. Both the patient and the rest of the family may benefit from gaining knowledge...

    Background: Type 2-diabetes (T2D) is a prevalent chronic disease that affects not just the patient but the entire family. Both the patient and the rest of the family may benefit from gaining knowledge about the disease and from supportive interfamilial interaction. Since the Internet is becoming a widely-used resource for health information, an Internet-based solution could potentially promote awareness and knowledge on how to manage T2D as a family, while also providing support for the family. Objective: To assess patients’ with T2D and their relatives’ usage of online information on diabetes and explore the families’ needs and preferences in regards to online information on diabetes. Objective: To assess patients’ with T2D and their relatives’ usage of online information on diabetes and explore the families’ needs and preferences in regards to online information on diabetes. Methods: A quantitative questionnaire survey was performed with families where at least one family member was diagnosed with T2D. The survey consisted of 36 closed questions on demographics, usage of the Internet, preferences in the source of information, interest in online information on six problem domains within family life related to T2D, preferences towards the delivery format of online information and peer-to-peer communication. Two open-ended questions were also included to elicit any additional comments or suggestions on improving online information on T2D regarding family life. Results: 50 participants corresponding to 22 families with T2D answered the questionnaire individually. 89% of the relatives and 100% of the patients indicated that information on T2D is relevant for them and 89-95% indicated that the Internet is the first or second preferred source when in need of information on T2D. Still, only 32-46% indicated to have searched the Internet to gain knowledge on T2D regarding family life. In regards to the six problem domains, 73-95% of the participants indicated interest in the domains Support, Knowledge and Everyday Life while 46-73% were interested in the domains ‘Communication, Worries and Roles. 72-84% of the participants indicated a preference for watching videos or reading about experiences derived from health care professionals (HCPs) or other families, while 20-32% were interested in peer-to-peer communication. Conclusions: Despite an interest for online information on T2D, there appears to be an unsatisfied need for more supportive online information on T2D aimed at Danish families with T2D. Based on family preferences, online information should focus on the six problem domains and be presented through text and videos by HCPs and peers. Peer-to-peer communication elements may be beneficial but are only expected to be used by a very limited number of families.

  • Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material

    Date Submitted: Feb 3, 2017

    Open Peer Review Period: Feb 6, 2017 - Apr 3, 2017

    Background: Diabetes is a major health crisis for Hispanics and Asian Americans. Moreover, Spanish and Chinese speakers, in particular, are more likely to have limited English proficiency in the U.S....

    Background: Diabetes is a major health crisis for Hispanics and Asian Americans. Moreover, Spanish and Chinese speakers, in particular, are more likely to have limited English proficiency in the U.S. One potential tool for facilitating language communication between diabetes patients and providers is technology, specifically smartphones. Objective: With regard to the machine translation quality, previous studies only assessed the translation product using writing inputs. To bridge such research gap, we conducted a pilot study to evaluate the quality of a mobile language translation app (iTranslate) with the voice recognition feature when translating diabetes patient education material. Methods: The pamphlet, “You are the heart of your family…take care of it,” is a health education sheet for diabetes patients that outlines three recommended questions for patients to ask their clinicians. Two professional translators interpreted the original English sentences into Spanish and Chinese. We recruited six certified medical translators (three Spanish and three Chinese) to conduct blinded evaluations of the following versions: (1) sentences interpreted by iTranslate, and (2) sentences interpreted by a professional human translator. Evaluators rated the sentences provided on four scales: Fluency, Adequacy, Meaning, and Severity ranged from 1 to 5. We performed descriptive analyses to examine differences between these two versions. Results: Cronbach’s alpha values exhibited high degrees of agreement on the rating outcome of both evaluator groups: 0.920 for the Spanish raters and 0.971 for the Chinese raters. The readability scores generated using Microsoft Word’s Flesch-Kincaid Grade Level for these sentences were 0.0, 1.0, and 7.1. We found that iTranslate generally provided comparable translation accuracy as human translators on simple sentences. However, iTranslate made more errors when translating difficult sentences, which might cause delayed patient care. Conclusions: iTranslate could supplement, but not supplant, human translators. Mobile translation apps should be used with precaution.

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