The Use of Mobile Applications Among Adults with Type 1 and Type 2 Diabetes: Results from the Second MILES-Australia (MILES-2) Study

The Sukaribit Smartphone App for Better Self-Management of Type 2 Diabetes: Randomized Controlled Feasibility Study

BACKGROUND

A new app, Sukaribit, was designed to enable contact between the caregiver and the patient with the intent to improve self-care and glycemic control (hemoglobin A1c [HbA1c]).

OBJECTIVE

This study investigated the feasibility of the study methodology and the intervention in preparation for a larger effectiveness study.

METHODS

Adults with type 2 diabetes were recruited in this randomized controlled feasibility study with a mixed methods design. The intervention group (n=28) tried Sukaribit for 2 months. They were encouraged to report blood glucose levels and medications, and they received feedback from a physician. The control group (n=31) received standard care. Both groups were evaluated with pre and postmeasurements of glycemic control (HbA1c), diabetes distress, physical activity, and self-care. Feasibility was evaluated against 5 progression criteria regarding recruitment, study methods, and active participation.

RESULTS

Of the 5 progression criteria, only 2 were met or partially met. The recruitment process exceeded expectations, and data collection worked well for self-reported data but not for HbA1c measured with a home testing kit. The participants were less active than anticipated, and the effect sizes were small. Only the number of blood glucose tests per day was positively affected by the intervention, with 0.6 more tests per day in the intervention group.

CONCLUSIONS

Recruitment of participants to a future fully powered study may work with minor adjustments. The collection of HbA1c using home testing constituted a major problem, and an alternative strategy is warranted. Finally, the app was not used as intended. In order to proceed with a larger study, the app and study procedures need improvement.

Barriers and Enablers to the Adoption of a Healthier Diet Using an App: Qualitative Interview Study With Patients With Type 2 Diabetes Mellitus

BACKGROUND

Adopting a healthy diet is one of the cornerstones of type 2 diabetes (T2D) management. Apps are increasingly used in diabetes self-management, but most studies to date have focused on assessing their impact in terms of weight loss or glycemic control, with limited evidence on the behavioral factors that influence app use to change dietary habits.

OBJECTIVE

The main objectives of this study were to assess the enablers and barriers to adopting a healthier diet using the Gro Health app in 2 patient groups with T2D (patients with recently diagnosed and long-standing T2D) and to identify behavior change techniques (BCTs) to enhance enablers and overcome barriers.

METHODS

Two semistructured qualitative interview studies were conducted; the first study took place between June and July 2021, with a sample of 8 patients with recently diagnosed (<12 mo) T2D, whereas the second study was conducted between May and June 2022 and included 15 patients with long-standing (>18 mo) T2D. In both studies, topic guides were informed by the Capability, Opportunity, Motivation, and Behavior model and the Theoretical Domains Framework. Transcripts were analyzed using a combined deductive framework and inductive thematic analysis approach. The Behavior Change Wheel framework was applied to identify appropriate BCTs that could be used in future iterations of apps for patients with diabetes. Themes were compared between the patient groups.

RESULTS

This study identified similarities and differences between patient groups in terms of enablers and barriers to adopting a healthier diet using the app. The main enablers for recently diagnosed patients included the acquired knowledge about T2D diets and skills to implement these, whereas the main barriers were the difficulty in deciding which app features to use and limited cooking skills. By contrast, for patients with long-standing T2D, the main enablers included knowledge validation provided by the app, along with app elements to help self-regulate food intake; the main barriers were the limited interest paid to the content provided or limited skills engaging with apps in general. Both groups reported more enablers than barriers to performing the target behavior when using the app. Consequently, BCTs were selected to address key barriers in both groups, such as simplifying the information hierarchy in the app interface, including tutorials demonstrating how to use the app features, and redesigning the landing page of the app to guide users toward these tutorials.

CONCLUSIONS

Patients with recently diagnosed and long-standing T2D encountered similar enablers but slightly different barriers when using an app to adopting a healthier diet. Consequently, the development of app-based approaches to adopt a healthier diet should account for these similarities and differences within patient segments to reduce barriers to performing the target behavior.

Developing and Evaluating the DiabetesXcel Mobile Application for Adult Patients With Type 2 Diabetes

The authors trialed a mobile application, DiabetesXcel, which included type 2 diabetes-focused educational videos and modules, in 50 adults of Bronx, NY, a region with a high prevalence of diabetes and diabetes complications. From baseline to 4 months and from baseline to 6 months, there was significantly improved quality of life, self-management, knowledge, self-efficacy, depression, A1C, and LDL cholesterol among those who used DiabetesXcel. There was also a significant decrease in diabetes-related emergency department visits and hospital admissions from baseline to 6 months. This study demonstrates that DiabetesXcel could be beneficial for type 2 diabetes management.

Characteristics of carbohydrate counting practice associated with adequacy of glycated hemoglobin in adults with type 1 diabetes mellitus in Brazil

Background

The Carbohydrate Counting (CC) is directly associated with achieving glycemic control by people with Type 1 Diabetes Mellitus (T1DM). Therefore, this study aims to analyze characteristics of the CC practice associated with the adequacy of glycated hemoglobin (HbA1c) in adults with T1DM in Brazil.

Methods

The study was cross-sectional, carried out using an online form with questions about knowledge of CC, clinical, anthropometric, sociodemographic data, follow-up with health professionals and understanding of the concepts of CC. Pearson's chi-square test and binomial logistic regression analysis (p<0.05) were applied.

Results

173 adults participated, of which 57.2% had increased HbA1c (≥7%). Having the diabetes duration <10 years (p=0.006), performing the CC at lunch (p=0.040) and dinner (p=0.018), using specific applications to perform the CC (p=0.001), having learned to perform CC with a nutritionist (p=0.037) and knowing how to correctly define the concepts of food bolus (p=0.001), correction bolus (p<0.001) and insulin/carbohydrate ratio (p<0.001) was associated with having adequate HbA1c (<7%). Participants who were undergoing CC practice were 3.273 times more likely to have adequate HbA1c and participants with diabetes duration <10 years were 2.686 times more likely to have adequate HbA1c.

Conclusion

It was concluded that variables transversal to CC favor adequate HbA1c values in adults with T1DM and that practicing CC and having a diabetes duration of less than 10 years are predictive factors of having adequate HbA1c.

Assessing Electronic Health Literacy at an Urban Academic Hospital

BACKGROUND

Residents of the Bronx suffer marked health disparities due to socioeconomic and other factors. The coronavirus disease 2019 pandemic worsened these health outcome disparities and health care access disparities, especially with the abrupt transition to online care.

OBJECTIVES

This study classified electronic health literacy (EHL) among patients at an urban, academic hospital in the Bronx, and assessed for associations between EHL levels and various demographic characteristics.

METHODS

We designed a cross-sectional, observational study in adults 18 years or older presenting to the Montefiore Einstein Center for Cancer Care (MECCC) Department of Radiation Oncology or the Montefiore Department of Medicine in the Bronx. We assessed EHL using the eHealth Literacy Scale (eHEALS) survey, a previously validated tool, and our newly developed eHealth Literacy Objective Scale-Scenario Based (eHeLiOS-SB) tool.

RESULTS

A total of 97 patients recruited from the MECCC and Department of Medicine participated in this study. There was a statistically significant association between age and EHL as assessed by both eHEALS and eHeLiOS-SB, with older adults having lower EHL scores. Additionally, a question designed to assess general attitudes toward digital health technologies found that most participants had a positive attitude toward such applications.

CONCLUSION

Many patients, especially older adults, may require additional support to effectively navigate telehealth. Further research is warranted to optimize telemedicine strategies in this potentially-marginalized population and ultimately to create telehealth practices accessible to patients of all ages and demographics.

STYLCONNECT Study: An Assessment of Automatic Data Collection Devices by People Living with Diabetes and Using an Insulin Pen

INTRODUCTION

The use of devices to connect insulin pens could facilitate management and improve glycaemic control in people with type 1 (PwT1D) and type 2 diabetes (PwT2D). However, their acceptance seems little studied. We conducted an online survey with the main objective of assessing the level of interest among insulin-treated people with diabetes (PwD) in a device connected to a disposable pen and secondary objectives of assessing the perceived benefits and important features expected of a connected device and identifying factors associated with interest scores.

METHODS

An ad-hoc questionnaire, validated by PwD, was used. Responses from 1798 PwD (975 PwT1D and 823 PwT2D) were analysed.

RESULTS

The mean interest rating was 7.4/10 (PwT1D: 7.2 vs PwT2D: 7.7; p < 0.001). PwD perceived that the device would make it easier to record their diabetes-related information (7.7/10) and keep all insulin and diabetes data in a single location (7.7/10). It was particularly important for PwD that this type of device could integrate data from glucose-measuring devices (7.8/10) and could set an alarm when all insulin in the body had been metabolised (7.7/10).

CONCLUSION

Our study highlighted PwD's strong interest in automating the collection of their insulin therapy data, with significantly more interest among PwT2D than PwT1D, and the importance of interoperability between glucose measurement devices and interchangeability between the different brands of insulin. More generally, for the first time and on a large scale, our study provided a greater understanding of the expectations of PwD regarding these devices.

Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study

OBJECTIVES

Mobile health applications are instrumental in the self-management of chronic diseases like diabetes. Technology acceptance models such as Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) have proven essential for predicting the acceptance of information technology. However, earlier research has found that the constructs "perceived disease threat" and "trust" should be added to UTAUT2 in the mHealth acceptance context. This study aims to evaluate the extended UTAUT2 model for predicting mHealth acceptance, represented by behavioral intention, using mobile diabetes applications as an example.

METHODS

We extended UTAUT2 with the additional constructs "perceived disease threat" and "trust". We conducted a web-based survey in German-speaking countries focusing on patients with diabetes and their relatives who have been using mobile diabetes applications for at least 3 months. We analysed 413 completed questionnaires by structural equation modelling.

RESULTS

We could confirm that the newly added constructs "perceived disease threat" and "trust" indeed predict behavioural intention to use mobile diabetes applications. We could also confirm the UTAUT2 constructs "performance expectancy" and "habit" to predict behavioural intention to use mobile diabetes applications. The results show that the extended UTAUT2 model could explain 35.0% of the variance in behavioural intention.

DISCUSSION

Even if UTAUT2 is well established in the information technologies sector to predict technology acceptance, our results reveal that the original UTAUT2 should be extended by "perceived disease threat" and "trust" to better predict mHealth acceptance.

CONCLUSION

Despite the newly added constructs, UTAUT2 can only partially predict mHealth acceptance. Future research should investigate additional mHealth acceptance factors, including how patients perceive trust in mHealth applications.

Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda

BACKGROUND

Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients' self-management activities. However, they are only effective if clinicians recommend them, and patients use them.

OBJECTIVE

This study aimed to explore the determinants of DSM apps' use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care.

METHODS

We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach.

RESULTS

A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients' and HCPs' characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients' perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps.

CONCLUSIONS

Despite the potential of DSM apps to improve patients' self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal.

The Impact of Mobile Health Use on the Self-care of Patients With Type 2 Diabetes: Protocol for a Randomized Controlled Trial

Background

Chronic diseases are a substantial public health issue worldwide and affect an individual’s quality of life. Due to the alarming rise in type 2 diabetes, health care that was primarily focused on diagnosis and treatment of the disease is increasingly focused on prevention and self-care. Patients who adhere to a constant and strict treatment regimen (physical activity, diet, medication) and regularly monitor their health are more likely to maintain self-care and health, prevent the exacerbation of the disease, and avoid the complications of diabetes (retinopathy, diabetic feet, etc). In recent years, many innovative devices that have become increasingly present in inpatient health care, such as mobile apps, are available to help patients maintain consistency in monitoring their health status. Mobile apps make it easier for individuals to monitor their self-care and illness and follow instructions regarding disease control.

Objective

This study aims to determine the impact of mobile app use on self-care in patients with type 2 diabetes. We will evaluate and test the usefulness of the forDiabetes app as a tool to improve the self-care of individuals with type 2 diabetes.

Methods

We will perform a double-blind randomized controlled trial. The study will include individuals aged over 18 years diagnosed with or have regulated type 2 diabetes who are treated in family medicine practices. Additionally, the individuals included in the study should not have any acute complications due to the consequences of type 2 diabetes. They will use an Android or iOS mobile phone and a blood glucose meter during the investigation. With the help of simple randomization, individuals will be divided into the intervention and control groups. Individuals in the intervention group will use the forDiabetes mobile app to monitor their self-care for type 2 diabetes. Individuals in the control group will not receive a particular intervention. Data will be collected using the Self-care of Diabetes Inventory questionnaire and Brief Illness Perception Questionnaire. Blood sugar, blood pressure, glycated hemoglobin (HbA_1c), and weight measurements will be monitored using calibrated instruments during the study by the nurses employed at the family medicine practice. Data will be collected at the beginning of the study and after a patient visits the family medicine practice.

Results

In the first half of 2020, we have prepared a translation of the mobile app that will be used by the participants of the intervention group, as well as more detailed instructions for using the app. We have also prepared a translation of the questionnaires in Slovene. The research results will be published in 2023.

Conclusions

This research contributes to greater visibility and usability of mobile apps for the self-care of patients with type 2 diabetes and raises awareness of the possible use of innovative methods.

Trial Registration

Clinicaltrials.gov NCT04999189; https://clinicaltrials.gov/ct2/show/NCT04999189

International Registered Report Identifier (IRRID)

PRR1-10.2196/31652

Using mHealth applications for self-care - An integrative review on perceptions among adults with type 1 diabetes

BACKGROUND

Individually designed interventions delivered through mobile health applications (mHealth apps) may be able to effectively support diabetes self-care. Our aim was to review and synthesize available evidence in the literature regarding perception of adults with type 1 diabetes on the features of mHealth apps that help promote diabetes self-care, as well as facilitators and barriers to their use. An additional aim was to review literature on changes in patient reported outcome measures (PROMs) in the same population while using mHealth apps for diabetes self-care.

METHODS

Quantitative and qualitative studies focusing on adults aged 18 years and over with type 1 diabetes in any context were included. A systematic literature search using selected databases was conducted. Data was synthesised using narrative synthesis.

RESULTS

We found that features of mHealth apps designed to help promote and maintain diabetes self-care could be categorized into self-care data monitoring, app display, feedback & reminders, data entry, data sharing, and additional features. Factors affecting the use of mHealth apps reported in the literature were personal factors, app design or usability factors, privacy and safety factors, or socioeconomic factors. Quality of life and diabetes distress were the most commonly reported PROMs in the included studies.

CONCLUSION

We are unable to reach a conclusive result due to the heterogeneity of the included studies as well as the limited number of studies reporting on these areas among adults with type 1 diabetes. We therefore recommend further large-scale studies looking into these areas that can ultimately improve mHealth app use in type 1 diabetes self-care.

SYSTEMATIC REVIEW REGISTRATION

Prospero CRD42020157620 .

Physician-Authored Feedback in a Type 2 Diabetes Self-management App: Acceptability Study

Background

Type 2 diabetes (T2D) is increasingly prevalent in society, in part because of behavioral issues, with sedentary behavior, reduced exercise, and the consumption of foods with a high glycemic index being major contributors. There is evidence for the efficacy of mobile apps in promoting behavior change and lifestyle improvements in people with T2D. Many mobile phone apps help to monitor the condition of people with T2D and inform them about their health. Some of these digital interventions involve patients using apps on their own or in conjunction with health care professionals.

Objective

This study aimed to test the acceptability of receiving app-based, daily physician feedback for patients with T2D that is informed by the continuous monitoring of their activity, food choices, and glucose profiles, with the aim of encouraging healthier behavior. The GLOOK! app was designed and developed by an academic research team and pilot-tested at an Australian public hospital.

Methods

A total of 15 patients diagnosed with T2D wore a glucose monitor and an Apple Watch for 12 days. The uploaded data were integrated into the GLOOK! app on the patients’ smartphones, which also enabled the recording of activity and consumed food. A physician provided daily feedback to each individual through the app based on their data from each of the 12 days. At the beginning and end of the study, data were collected on vital signs, anthropometry, hemoglobin A_1c level, fructosamine level, and fasting lipids level. Participants were also interviewed at the beginning and end of the study to assess the acceptability of the intervention and its potential impact on promoting positive behavior change.

Results

Over the 12 days of the study, there was a significant reduction of 0.22% (P=.004) in hemoglobin A_1c level. There were favorable changes in fructosamine and lipid fractions; however, none reached significance. There was also a fall of 0.65 kg in body weight and falls in blood pressure and pulse rate that did not reach significance. Patient feedback on the GLOOK! system was positive. Of the 15 participants, 13 (87%) were enthusiastic about continuing to use the app system if some usability and reliability aspects were improved. All participants regarded the personalized physician feedback as supportive and helpful in understanding their own health behavior. Of the 15 participants, 4 (27%) felt that using the system encouraged long-term behavior changes.

Conclusions

A mobile app system that provides people with T2D daily, physician-generated, personalized feedback can produce favorable changes in glycemic and cardiovascular risk parameters—even in the short term—and encourage better self-management of their condition. Study participants found the experience of using the mobile app system acceptable and were motivated to establish longer-term lifestyle improvements through behavior changes.

Web-Based TangPlan and WeChat Combination to Support Self-management for Patients With Type 2 Diabetes: Randomized Controlled Trial

Background

China has the largest number of patients with type 2 diabetes mellitus (T2DM) in the world. However, owing to insufficient knowledge of self-management in patients with diabetes, blood glucose (BG) control is poor. Most diabetes-related self-management applications fail to bring significant benefits to patients with T2DM because of the low use rate and difficult operation.

Objective

This study aims to examine the effectiveness of the combination of the self-designed web-based T2DM management software TangPlan and WeChat on fasting BG (FBG), glycated hemoglobin (HbA_1c), body weight, blood pressure (BP), and lipid profiles in patients with T2DM over a 6-month period.

Methods

Participants were recruited and randomized into the TangPlan and WeChat or control groups. Participants in the control group received usual care, whereas the TangPlan and WeChat participants received self-management guidance with the help of TangPlan and WeChat from health care professionals, including BG self-monitoring; healthy eating; active physical exercise; increasing medication compliance; and health education during follow-ups, lectures, or web-based communication. They were also asked to record and send self-management data to the health care professionals via WeChat to obtain timely and effective guidance on diabetes self-management.

Results

In this study, 76.9% (120/156) of participants completed the 6-month follow-up visit. After the intervention, FBG (mean 6.51, SD 1.66 mmol/L; P=.048), HbA_1c (mean 6.87%, SD 1.11%; P<.001), body weight (mean 66.50, SD 9.51 kg; P=.006), systolic BP (mean 127.03, SD 8.00 mm Hg; P=.005), diastolic BP (mean 75.25, SD 5.88 mm Hg; P=.03), serum low-density lipoprotein cholesterol (mean 2.50, SD 0.61 mmol/L; P=.006), and total cholesterol (mean 4.01, SD 0.83 mmol/L; P=.02) in the TangPlan and WeChat group were all significantly lower, whereas serum high-density lipoprotein cholesterol (mean 1.20, SD 0.25 mmol/L; P=.01) was remarkably higher than in those in the control group. Compared with the baseline data, significance was found in the mean change in FBG (95% CI −0.83 to −0.20; P=.002), HbA_1c (95% CI −1.92 to −1.28; P<.001), body weight (95% CI −3.13 to −1.68; P<.001), BMI (95% CI −1.10 to −0.60; P<.001), systolic BP (95% CI −7.37 to −3.94; P<.001), diastolic BP (95% CI −4.52 to −2.33; P<.001), triglycerides (95% CI −0.16 to −0.03; P=.004), serum low-density lipoprotein cholesterol (95% CI −0.54 to −0.30; P<.001), and total cholesterol (95% CI −0.60 to −0.34; P<.001) in the TangPlan and WeChat group but not in the control group (P=.08-.88).

Conclusions

Compared with usual care for patients with T2DM, the combination of TangPlan and WeChat was effective in improving glycemic control (decrease in HbA_1c and BG levels) and serum lipid profiles as well as reducing body weight in patients with T2DM after 6 months.

Trial Registration

Chinese Clinical Trial Registry ChiCTR2000028843; https://tinyurl.com/559kuve6

Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study

Background

In recent years, the use of mobile health (mHealth) apps to manage chronic diseases has increased significantly. Although mHealth apps have many benefits, their acceptance is still low in certain areas and groups. Most mHealth acceptance studies are based on technology acceptance models. In particular, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was developed to predict technology acceptance in a consumer context. However, to date, only a few studies have used the UTAUT2 model to predict mHealth acceptance and confirm its suitability for the health sector. Thus, it is unclear whether the UTAUT2 model is suitable for predicting mHealth acceptance and whether essential variables for a health-related context are missing.

Objective

This study aims to validate the suitability of UTAUT2 for predicting mHealth acceptance.

Methods

In this study, diabetes was used as an example as mHealth apps are a significant element of diabetes self-management. In addition, diabetes is one of the most common chronic diseases affecting young and older people worldwide. An explorative literature review and guided interviews with 11 mHealth or technology acceptance experts and 8 mHealth users in Austria and Germany were triangulated to identify all relevant constructs for predicting mHealth acceptance. The interview participants were recruited by purposive sampling until theoretical saturation was reached. Data were analyzed using structured content analysis based on inductive and deductive approaches.

Results

This study was able to confirm the relevance of all exogenous UTAUT2 constructs. However, it revealed two additional constructs that may also need to be considered to better predict mHealth acceptance: trust and perceived disease threat.

Conclusions

This study showed that the UTAUT2 model is suitable for predicting mHealth acceptance. However, the model should be extended to include 2 additional constructs for use in the mHealth context.

Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study

Background

Self-monitoring of blood glucose levels, food intake, and physical activity supports self-management of patients with type 2 diabetes mellitus (T2DM). There has been an increase in the development and availability of mobile health apps for T2DM.

Objective

The aim of this study is to explore the actual use of mobile health apps for diabetes among patients with T2DM and the main barriers and drivers among app users and nonusers.

Methods

An explanatory sequential design was applied, starting with a web-based questionnaire followed by semistructured in-depth interviews. Data were collected between July and December 2020. Questionnaire data from 103 respondents were analyzed using IBM SPSS Statistics (version 25.0). Descriptive statistics were performed for the actual use of apps and items of the Unified Theory of Acceptance and Use of Technology (UTAUT). The UTAUT includes 4 key constructs: performance expectancy (the belief that an app will help improve health performance), effort expectancy (level of ease associated with using an app), social influence (social support), and facilitating conditions (infrastructural support). Differences between users and nonusers were analyzed using chi-square tests for individual items. Independent 2-tailed t tests were performed to test for differences in mean scores per the UTAUT construct. In total, 16 respondents participated in the interviews (10 users and 6 nonusers of apps for T2DM). We performed content analysis using a deductive approach on all transcripts, guided by the UTAUT.

Results

Regarding actual use, 55.3% (57/103) were nonusers and 44.7% (46/103) were users of apps for T2DM. The main driver for the use of apps was the belief that using apps for managing diabetes would result in better personal health and well-being. The time and energy required to keep track of the data and understand the app were mentioned as barriers. Mean scores were significantly higher among users compared with nonusers of apps for T2DM for the constructs performance expectancy (4.06, SD 0.64 vs 3.29, SD 0.89; P<.001), effort expectancy (4.04, SD 0.62 vs 3.50, SD 0.82; P<.001), social influence (3.59, SD 0.55 vs 3.29, SD 0.54; P=.007), and facilitating conditions (4.22, SD 0.48 vs 3.65, SD 0.70; P<.001). On the basis of 16 in-depth interviews, it was recognized that health care professionals play an important role in supporting patients with T2DM in using apps. However, respondents noticed that their health care professionals were often not supportive of the use of apps for managing diabetes, did not show interest, or did not talk about apps. Reimbursement by insurance companies was mentioned as a missing facilitator.

Conclusions

Empowering health care professionals’ engagement is of utmost importance in supporting patients with T2DM in the use of apps. Insurance companies can play a role in facilitating the use of diabetes apps by ensuring reimbursement.

Managing Diabetes Using Mobiab: Long Term Case Study of the Impact of a Mobile App on Self-Management (Preprint)

Background

This paper describes the development of a mobile app for diabetes mellitus (DM) control and self-management and presents the results of long-term usage of this system in the Czech Republic. DM is a chronic disease affecting large numbers of people worldwide, and this number is continuously increasing. There is massive potential to increase adherence to self-management of DM with the use of smartphones and digital therapeutics interventions.

Objective

This study aims to describe the process of development of a mobile app, called Mobiab, for DM management and to investigate how individual features are used and how the whole system benefits its long-term users. Using at least 1 year of daily records from users, we analyzed the impact of the app on self-management of DM.

Methods

We have developed a mobile app that serves as an alternative form to the classic paper-based protocol or diary. The development was based on cooperation with both clinicians and people with DM. The app consists of independent individual modules. Therefore, the user has the possibility to use only selected features that they find useful. Mobiab was available free of charge on Google Play Store from mid-2014 until 2019. No targeted recruitment was performed to attract users.

Results

More than 500 users from the Czech Republic downloaded and signed up for the mobile app. Approximately 80% of the users used Mobiab for less than 1 week. The rest of the users used it for a longer time and 8 of the users produced data that were suitable for long-term analysis. Additionally, one of the 8 users provided their medical records, which were compared with the gathered data, and the improvements in their glucose levels and overall metabolic stability were consistent with the way in which the mobile app was used.

Conclusions

The results of this study showed that the usability of a DM-centered self-management smartphone mobile app and server-based systems could be satisfactory and promising. Nonetheless, some better ways of motivating people with diabetes toward participation in self-management are needed. Further studies involving a larger number of participants are warranted to assess the effect on long-term diabetes management.

Glycaemic control and novel technology management strategies in pregestational diabetes mellitus

INTRODUCTION

Pregestational diabetes (PGDM) is an increasingly common and complex condition that infers risk to both mother and infant. To prevent serious morbidity, strict glycaemic control is essential. The aim of this review is to review the glucose sensing and insulin delivering technologies currently available for women with PGDM.

METHODS

We reviewed online databases for articles relating to technology use in pregnancy using a combination of keywords and MeSH headings. Relevant articles are included below.

RESULTS

A number of technological advancements have improved care and outcomes for women with PGDM. Real time continuous glucose monitoring (rtCGM) offers clear advantages in terms of infants size and neonatal intensive care unit admissions; and further benefits are seen when combined with continuous subcutaneous insulin delivery (insulin pump) and algorithms which continuously adjust insulin levels to glucose targets (hybrid closed loop). Other advancements including flash or intermittent scanning CGM (isCGM) and stand-alone insulin pumps do not confer as many advantages for women and their infants, however they are increasingly used outside of pregnancy and many women enter pregnancy already using these devices.

DISCUSSION

This article offers a discussion of the most commonly used technologies in pregnancy and evaluates their current and future roles.

Understanding digital health ecosystem from Australian citizens' perspective: A scoping review

BACKGROUND

Digital health (DH) and the benefits of related services are fairly well understood. However, it still is critical to map the digital health care landscape including the key elements that define it as an ecosystem. Particularly, knowing the perspectives of citizens on this digital transformation is an important angle to capture. In this review we aim to analyze the relevant studies to identify how DH is understood and experienced by Australian citizens and what they may require from DH platforms.

MATERIALS AND METHODS

A scoping literature review was conducted across several electronic databases (ACM Digital Library, OVID, PubMed, Scopus, IEEE, Science Direct, SAGE), as well as grey literature. Additionally, citation mining was conducted to identify further relevant studies. Identified studies were subjected to eligibility criteria and the final set of articles was independently reviewed, analyzed, discussed and interpreted by three reviewers.

RESULTS

Of 3811 articles, 98 articles met the inclusion criteria with research-based articles-as opposed to review articles or white papers- comprising the largest proportion (72%) of the selected literature. The qualitative analysis of the literature revealed five key elements that capture the essence of the digital health ecosystem interventions from the viewpoint of the Australian citizens. The identified elements were "consumer/user", "health care", "technology", "use and usability", "data and information". These elements were further found to be associated with 127 subcategories.

CONCLUSIONS

This study is the first of its kind to analyze and synthesize the relevant literature on DH ecosystems from the citizens' perspective. Through the lens of two research questions, this study defines the key components that were found crucial to understanding citizens' experiences with DH. This understanding lays a strong foundation for designing and fostering DH ecosystem. The results provide a solid ground for empirical testing.

Factors Affecting Adoption of a Technology-Based Tool for Diabetes Self-Management Education and Support Among Adult Patients with Type 2 Diabetes in South Texas

PURPOSE

The purpose of this study is to describe a novel computerized diabetes education tool and explore factors influencing self-selection and use among primarily Hispanic patients diagnosed with type 2 diabetes in south Texas.

METHODS

Study participants included 953 adult patients with type 2 diabetes enrolled in a diabetes education program between July 1, 2016, and June 30, 2017. Participants were asked to choose either a new technology-based diabetes education tool with a touch-screen device or a traditional face-to-face education method. Multivariate logistic regression analysis was applied to identify factors associated with adopting the computerized diabetes education tool among the patients.

RESULTS

When comparing technology-based tool adopters and nonadopters, several demographic and health-related factors differentiated technology use in bivariate analyses. The multivariate logistic regression model showed that Hispanic patients were less likely to choose a technology-based tool. Patients who perceived their health status as excellent/good were more likely to adopt the technologic education method than those with fair/poor perceived health status. A1C level was negatively associated with self-selection of technology.

CONCLUSIONS

Specific demographic and health-related characteristics are significant contributing factors to patients' adoption of a technology-based diabetes education tool. Health care providers can utilize these findings to target and refer specific patients to a computerized diabetes education tool for more effective diabetes care and to optimize technology adoption success.

Association Between a Low Carbohydrate Diet, Quality of Life, and Glycemic Control in Australian Adults Living With Type 1 Diabetes: Protocol for a Mixed Methods Pilot Study

BACKGROUND

Globally, the prevalence of type 1 diabetes mellitus (T1DM) is rising. In 2020, a total of 124,652 Australians had T1DM. Maintaining optimal glycemic control (hemoglobin A_1c ≤7.0%, ≤53 mmol/mol) on a standard carbohydrate diet can be a challenge for people living with T1DM. The Diabetes Complications and Control Trial established that macrovascular and microvascular complications could be reduced by improving glycemic control. Recent studies have found that a very low or low carbohydrate diet can improve glycemic control. However, the overall evidence relating to an association between a very low or low carbohydrate diet and glycemic control in people living with T1DM is both limited and mixed. In addition, research has suggested that a reduced quality of life due to anxiety and depression adversely influences glycemic control. Despite a potential link between a very low or low carbohydrate diet and optimal glycemic control, to our knowledge, no research has examined an association between a low carbohydrate diet, quality of life, and glycemic control, making this study unique in its approach.

OBJECTIVE

The study aims to develop a validated diabetes-specific quality of life questionnaire for use in Australian adults with T1DM and to determine if an association exists between a low carbohydrate diet, quality of life, and glycemic control in Australian adults living with T1DM.

METHODS

This cross-sectional study will be conducted in a tertiary hospital outpatient setting and will consist of 3 phases: phase 1, online Australian diabetes-specific quality of life questionnaire development and piloting (25-30 adults with T1DM); phase 2, questionnaire validation (364 adults with T1DM); and phase 3, a 12-week dietary intervention to determine if an association exists between a low carbohydrate diet, quality of life, and glycemic control in adults with T1DM (16-23 adults with T1DM). The validation of the study-developed Australian diabetes-specific quality of life questionnaire, and changes in hemoglobin A_1c and quality of life in adults with T1DM while undertaking a low carbohydrate diet over 12 weeks will be the primary outcomes of this study.

RESULTS

Phase 1 of the study is currently open for recruitment and has recruited 12 participants to date. It is anticipated that the first results will be submitted for publication in November 2021. Presently, no results are available.

CONCLUSIONS

This study is the first of its kind in that it will be the first to generate a new validated instrument, which could be used in evidence-based practice and research to understand the quality of life of Australian adults with T1DM. Second, the low carbohydrate dietary intervention outcomes could be used to inform clinicians about an alternative approach to assist T1DM adults in improving their quality of life and glycemic control. Finally, this study could warrant the development of an evidence-based low carbohydrate dietary guideline for adults living with T1DM with the potential to have a profound impact on this population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04213300; https://clinicaltrials.gov/ct2/show/NCT04213300.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/25085.

Identifying features of a mobile-based application for self-care of people living with T2DM

INTRODUCTION

Diabetes self-care requires support to empower patients to improve self-monitoring and maintain the necessary self-care behaviors. We aimed to identify features of a mobile-based application as a technology-based device for self-care of people living with T2DM.

METHOD

This study was conducted in two main phases in 2020. In the first phase, a literature review study was performed to identify the data elements and technical features of the T2DM self-care application. In the second phase, using the information obtained from the review of similar articles, a questionnaire was designed to validate identified requirements. The statistical population of the present study consisted of 22 endocrinologists and metabolic specialists.

RESULTS

Identification of 55 data elements and technical features for mobile-based self-care application for people with T2DM, and according to the statistical population, 15data elements for demographic requirements, 16 data elements for clinical requirements, and 17 features for the technical capability of this app were selected.

CONCLUSION

Blood sugar monitoring, exercise, nutrition, weight monitoring, and educational capabilities were the most highlighted technical features of the T2DM self-care application. Software designers can use these requirements to design a self-care app for people with type-2 diabetes that can help manage and improve patients' health status.

User Experiences With a Type 2 Diabetes Coaching App: Qualitative Study

BACKGROUND

Diabetes self-management apps have the potential to improve self-management in people with type 2 diabetes (T2D). Although efficacy trials provide evidence of health benefits, premature disengagement from apps is common. Therefore, it is important to understand the factors that influence engagement in real-world settings.

OBJECTIVE

This study aims to explore users' real-world experiences with the My Diabetes Coach (MDC) self-management app.

METHODS

We conducted telephone-based interviews with participants who had accessed the MDC self-management app via their smartphone for up to 12 months. Interviews focused on user characteristics; the context within which the app was used; barriers and facilitators of app use; and the design, content, and delivery of support within the app.

RESULTS

A total of 19 adults with T2D (8/19, 42% women; mean age 60, SD 14 years) were interviewed. Of the 19 interviewees, 8 (42%) had T2D for <5 years, 42% (n=8) had T2D for 5-10 years, and 16% (n=3) had T2D for >10 years. In total, 2 themes were constructed from interview data: (1) the moderating effect of diabetes self-management styles on needs, preferences, and expectations and (2) factors influencing users' engagement with the app: one size does not fit all.

CONCLUSIONS

User characteristics, the context of use, and features of the app interact and influence engagement. Promoting engagement is vital if diabetes self-management apps are to become a useful complement to clinical care in supporting optimal self-management.

TRIAL REGISTRATION

Australia New Zealand Clinical Trials Registry CTRN126140012296; URL https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366925&isReview=true.

Health App Use and Its Correlates Among Individuals With and Without Type 2 Diabetes: Nationwide Population-Based Survey

Background

Evidence suggests that mobile health app use is beneficial for the prevention and management of type 2 diabetes (T2D) and its associated complications; however, population-based research on specific determinants of health app use in people with and without T2D is scarce.

Objective

This cross-sectional study aimed to provide population-based evidence on rates and determinants of health app use among adults with and without T2D, thereby covering a prevention perspective and a diabetes management perspective, respectively.

Methods

The study population included 2327 adults without a known diabetes diagnosis and 1149 adults with known T2D from a nationwide telephone survey in Germany conducted in 2017. Rates of smartphone ownership and health app use were estimated based on weighted sample proportions. Among smartphone owners, determinants of health app use were identified for both groups separately in multivariable logistic regression models. Sociodemographic factors, diabetes-related factors or indicators, psychological and health-related factors, and physician-provided information were selected as potential determinants.

Results

Among participants without known diabetes, 74.72% (1690/2327) were smartphone owners. Of those, 49.27% (717/1690) used health apps, most often to improve regular physical activity. Among participants with T2D, 42.26% (481/1149) were smartphone owners. Of those, 41.1% (171/481) used health apps, most commonly to target a healthy diet. Among people without known diabetes, determinants significantly (all P values <.05) associated with an increased likelihood of health app use compared with their reference group were as follows: younger and middle age of 18 to 44 or 45 to 64 years (odds ratios [ORs] 3.89; P<.001 and 1.76; P=.004, respectively), overweight or obesity (ORs 1.58; P<.001 and 2.07; P<.001, respectively), hypertension diagnosis (OR 1.31; P=.045), former or current smoking (ORs 1.51; P=.002 and 1.58; P<.001, respectively), perceiving health as very good (OR 2.21; P<.001), other chronic diseases (OR 1.48; P=.002), and having received health advice from a physician (OR 1.48; P<.001). A slight or high perceived diabetes risk (ORs 0.78; P=.04 and 0.23; P<.001, respectively) was significantly associated with a decreased likelihood of health app use. Among people with T2D, younger and middle age (18-64 years; OR 1.84; P=.007), female gender (OR 1.61; P=.02), and using a glucose sensor in addition or instead of a glucose meter (OR 2.74; P=.04) were significantly positively associated with health app use.

Conclusions

In terms of T2D prevention, age, diabetes-related risk factors, psychological and health-related factors, and medical health advice may inform app development for specific target groups. In addition, health professionals may encourage health app use when giving advice on health behaviors. Concerning T2D management, only a few determinants seem relevant for explaining health app use among people with T2D, indicating a need for more future research on which people with T2D use health apps and why.

Impact of dietary protein on postprandial glycaemic control and insulin requirements in Type 1 diabetes: a systematic review

AIM

Postprandial hyperglycaemia is a challenge for people living with Type 1 diabetes. In addition to carbohydrate, dietary protein has been shown to contribute to postprandial glycaemic excursions with recommendations to consider protein when calculating mealtime insulin doses. The aim of this review is to identify and synthesize evidence about the glycaemic impact of dietary protein and insulin requirements for individuals with Type 1 diabetes.

METHODS

A systematic literature search of relevant biomedical databases was performed to identify research on the glycaemic impact of dietary protein when consumed alone, and in combination with other macronutrients in individuals with Type 1 diabetes.

RESULTS

The review included 14 published studies dated from 1992 to 2018, and included studies that researched the impact of protein alone (n = 2) and protein in a mixed meal (n = 12). When protein was consumed alone a glycaemic effect was not seen until ≥ 75 g. In a carbohydrate-containing meal ≥ 12.5 g of protein impacted the postprandial glucose. Inclusion of fat in a high-protein meal enhanced the glycaemic response and further increased insulin requirements. The timing of the glycaemic effect from dietary protein ranged from 90 to 240 min. Studies indicate that the postprandial glycaemic response and insulin requirements for protein are different when protein is consumed alone or with carbohydrate and/or fat.

CONCLUSIONS

This systematic review provides evidence that dietary protein contributes to postprandial glycaemic excursions and insulin requirements. These insights have important implications for the education of people with Type 1 diabetes and highlights the need for more effective insulin dosing strategies for mixed macronutrient meals.

Factors Influencing Patients' Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey

BACKGROUND

Diabetes poses heavy social and economic burdens worldwide. Diabetes management apps show great potential for diabetes self-management. However, the adoption of diabetes management apps by diabetes patients is poor. The factors influencing patients' intention to use these apps are unclear. Understanding the patients' behavioral intention is necessary to support the development and promotion of diabetes app use.

OBJECTIVE

This study aimed to identify the determinants of patients' intention to use diabetes management apps based on an integrated theoretical model.

METHODS

The hypotheses of our research model were developed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). From April 20 to May 20, 2019, adult patients with diabetes across China, who were familiar with diabetes management apps, were surveyed using the Web-based survey tool Sojump. Structural equation modeling was used to analyze the data.

RESULTS

A total of 746 participants who met the inclusion criteria completed the survey. The fitness indices suggested that the collected data fit well with the research model. The model explained 62.6% of the variance in performance expectancy and 57.1% of the variance in behavioral intention. Performance expectancy and social influence had the strongest total effects on behavioral intention (β=0.482; P=.001). Performance expectancy (β=0.482; P=.001), social influence (β=0.223; P=.003), facilitating conditions (β=0.17; P=.006), perceived disease threat (β=0.073; P=.005), and perceived privacy risk (β=-0.073; P=.012) had direct effects on behavioral intention. Additionally, social influence, effort expectancy, and facilitating conditions had indirect effects on behavioral intention that were mediated by performance expectancy. Social influence had the highest indirect effects among the three constructs (β=0.259; P=.001).

CONCLUSIONS

Performance expectancy and social influence are the most important determinants of the intention to use diabetes management apps. Health care technology companies should improve the usefulness of apps and carry out research to provide clinical evidence for the apps' effectiveness, which will benefit the promotion of these apps. Facilitating conditions and perceived privacy risk also have an impact on behavioral intention. Therefore, it is necessary to improve facilitating conditions and provide solid privacy protection. Our study supports the use of UTAUT in explaining patients' intention to use diabetes management apps. Context-related determinants should also be taken into consideration.

Community-Driven Priorities in Smartphone Application Development: Leveraging Social Networks to Self-Manage Type 2 Diabetes in a Low-Income African American Neighborhood

Social networks have the potential to enhance Type 2 Diabetes Mellitus (T2DM) self-management. We used qualitative methods to study if and how mobile application (app) functions that mobilize social resources to improve T2DM management would be desired in a low-income African American community. Data were collected through community discussions and in-depth interviews with 78 participants in 2016–2018. Participants included individuals with self-reported pre-diabetes, T2DM, close family members or friends of a T2DM patient, and healthcare providers. Open-ended questions solicited information about challenges with T2DM management and gathered ideas on features of a mobile app that could address them. Data were transcribed and thematically coded by two coders using Atlas-ti. Regarding types of app functions, main themes included: (1) the importance of having support in diabetes self-care; (2) using informal networks to help to each other; and (3) monitoring one another through an app. Suggested app features included reminders for and transportation to medical visits, sharing information and exercise companionship, and providing opportunities for monitoring by friends/family members, especially in case of emergencies. Participants viewed an app as a potential vehicle for reinforcing accomplishments in T2DM self-management. Future research should implement and test an app with these features in this or similar communities.

What Do Adults with Type 2 Diabetes Want from the "Perfect" App? Results from the Second Diabetes MILES: Australia (MILES-2) Study

Background: We investigated what Australian adults with type 2 diabetes (T2D) want from the "perfect" diabetes self-management application. Methods: Adults with T2D completed a national online survey including an open-ended question: "If you were describing the perfect app to help you manage your diabetes, what would it do?" Qualitative responses were subjected to thematic analysis. Results: Of the 339 participants who provided usable responses, 153 (45%) were women, the mean age was 58 ± 10 years, and 139 participants (41%) managed their diabetes with insulin. Two primary themes emerged. First, participants expressed a desire for assistance with practical aspects of diabetes self-management to improve, and reduce the cognitive burden of, self-management; this included tracking and visualizing multiple sources of data, using data to inform automated, personalized coaching, reminders, and alarms, and automating upload and linking of data through connected devices. Second, they desired assistance with psychological and emotional aspects of diabetes self-management; this included ongoing encouragement and motivation, help with stress management or negative emotions, and complementing existing health care by facilitating interconnectivity with health professionals. Conclusions: Our findings suggest that the clear desire of people with type 2 diabetes is for the "perfect app" to reduce not only the practical, but also the cognitive and emotional burden of diabetes self-management. They provide further evidence that understanding the desires of people living with diabetes needs to be the first step in app development to ensure that apps provide features, support, and benefits that people with diabetes value.

Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study

BACKGROUND

The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be highly valuable. However, little is known about the use of eHealth in different socioeconomic groups among people with diabetes.

OBJECTIVE

The aim of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and the association with socioeconomic status (SES) among people diagnosed with type 1 and type 2 diabetes mellitus (T1D and T2D, respectively).

METHODS

We used email survey data from 1250 members of the Norwegian Diabetes Association (aged 18-89 years), collected in 2018. Eligible for analyses were the 1063 respondents having T1D (n=523) and T2D (n=545). 5 respondents reported having both diabetes types and thus entered into both groups. Using descriptive statistics, we estimated the use of the different types of eHealth. By logistic regressions, we studied the associations between the use of these types of eHealth and SES (education and household income), adjusted for gender, age, and self-rated health.

RESULTS

We found that 87.0% (447/514) of people with T1D and 77.7% (421/542) of people with T2D had used 1 or more forms of eHealth sometimes or often during the previous year. The proportion of people using search engines was the largest in both diagnostic groups, followed by apps, social media, and video services. We found a strong association between a high level of education and the use of search engines, whereas there were no educational differences for the use of apps, social media, or video services. In both diagnostic groups, high income was associated with the use of apps. In people with T1D, lower income was associated with the use of video services.

CONCLUSIONS

This paper indicates a digital divide among people with diabetes in Norway, with consequences that may contribute to sustaining and shaping inequalities in health outcomes. The strong relationship between higher education and the use of search engines, along with the finding that the use of apps, social media, and video services was not associated with education, indicates that adequate communication strategies for audiences with varying education levels should be a focus in future efforts to reduce inequalities in health outcomes.

Associations Between the Use of eHealth and Out-of-Hours Services in People With Type 1 Diabetes: Cross-Sectional Study

BACKGROUND

Despite the increasing prevalence of diabetes and the increasing use of eHealth, little is known about the association between provider-based health services and eHealth among people with diabetes. This is the second study in a project exploring the associations between the use of eHealth and the use of provider-based health services.

OBJECTIVE

The objective of this study was to investigate which eHealth services are used among out-of-hours (OOH) visitors with type 1 diabetes (T1D), and whether the use of eHealth (eg, apps, search engines, video services, and social media) was associated with the use of OOH services. We also wanted to investigate associations between anxiety, reassurance, and change in doctor-seeking behavior because of health information acquired from the Internet, and the use of OOH services.

METHODS

We used data from a 2018 email survey of members of the Norwegian Diabetes Association (18-89 years old). Respondents with T1D were eligible for analyses. Using descriptive statistics, we estimated the use of OOH services and eHealth. Using logistic regressions, we studied the associations between the use of OOH services and the use of eHealth, as well as associations between the use of OOH services and reported consequences of using Internet-based health information.

RESULTS

In the sample of 523 people with T1D (mean age 47 years), 26.7% (129/484) visited OOH services once or more during the previous year. Among the OOH visitors, search engines were used for health purposes by 86.7% (111/128), apps (health apps in general) by 63.6% (82/129), social media by 45.3% (58/128), and video services by 28.4% (36/127). The use of OOH services was positively associated with self-reported anxiety/depression (odds ratio [OR] 4.53, 95% CI 1.43-14.32) and with the use of apps (OR 1.73, 95% CI 1.05-2.85), but not with other types of eHealth. Those who had felt anxious based on information from the Internet were more likely to visit OOH services compared with those who had not felt anxious (OR 2.38, 95% CI 1.50-3.78). People who had decided to consult a doctor based on information from the Internet were more likely to visit OOH services (OR 2.76, 95% CI 1.64-4.66), compared to those who had not made such an Internet-based decision.

CONCLUSIONS

People with T1D were frequent users of OOH services, and the OOH visitors were frequent users of eHealth. The use of OOH services was positively associated with the use of health apps, with self-reported anxiety/depression, and with feeling anxious based on information from the Internet. Likewise, deciding to consult a doctor based on information from the Internet was positively associated with OOH visits. The use of eHealth seems to have a significant impact on people with T1D.

Use, Perspectives, and Attitudes Regarding Diabetes Management Mobile Apps Among Diabetes Patients and Diabetologists in China: National Web-Based Survey

Background

The diabetes disease burden in China is heavy, and mobile apps have a great potential for diabetes management. However, there is a lack of investigation of diabetes app use among Chinese diabetes patients and diabetologists. The perspectives and attitudes of diabetes patients and diabetologists regarding diabetes apps are also unclear.

Objective

Our objectives were to investigate diabetes patients’ and diabetologists’ use, attitudes, and perspectives, as well as patients’ needs, with respect to diabetes apps to provide information regarding the optimal design of diabetes apps and the best strategies to promote their use.

Methods

Diabetes patients and diabetologists across China were surveyed on the WeChat (Tencent Corp) network using Sojump (Changsha ran Xing InfoTech Ltd) from January 23, 2018, to July 30, 2018. In total, 2 survey links were initially sent to doctors from 46 Latent Autoimmune Diabetes of Adults Study collaborative hospitals in China in 25 major cities and were spread on their WeChat contacts network. We also published the patient survey link on 3 WeChat public accounts and requested diabetes patients to fill out questionnaires. A multivariate regression analysis was used to identify associations of demographic and basic disease information with app usage among adult patients.

Results

Overall, 1276 individuals from 30 provincial regions responded to the patient survey; among them, the overall app awareness rate was 29.94% (382/1276) and usage was 15.44% (197/1276). The usage was higher among patients with type 1 diabetes (T1DM) than among patients with type 2 diabetes (T2DM; 108/473, 22.8% vs 79/733, 10.8%; P<.001). The multivariate regression analysis showed that diabetes type, age, education, family income, and location were associated with app use in adult patients (P<.05). The need for and selection of diabetes apps differed slightly between patients with T1DM and patients with T2DM. The reasons why patients discontinued the use of an app included limited time (59/197, 29.9%), complicated operations (50/197, 25.4%), ineffectiveness for glycemic control (48/197, 24.4%), and cost (38/197, 19.3%).

Of the 608 responders to the diabetologist survey, 40.5% (246/608) recommended diabetes apps to patients and 25.2% (153/608) used diabetes apps to manage patients. The greatest obstacles to the diabetologists’ use of apps to manage diabetes patients include limited time (280/608, 46.1%), legal issues (129/608, 21.2%), patients’ distrust (108/608, 17.8%), and billing issues (66/608, 10.9%).

Conclusions

The awareness and use of diabetes apps in Chinese people with diabetes and the proportion of diabetologists using diabetes apps to manage patients are low. Designing apps targeting different patient needs and conducting high-quality randomized controlled trials will improve the effectiveness of the apps, provide evidence for patients to choose suitable apps, and be conducive to the promotion of app use.

The Role of Continuous Glucose Monitoring, Diabetes Smartphone Applications, and Self-Care Behavior in Glycemic Control: Results of a Multi-National Online Survey

Background: This study investigated the determinants (with a special emphasis on the role of diabetes app use, use of continuous glucose monitoring (CGM) device, and self-care behavior) of glycemic control of type 1 and type 2 diabetes mellitus (DM). Methods: A web-based survey was conducted using diabetes Facebook groups, online patient-forums, and targeted Facebook advertisements (ads). Demographic, CGM, diabetes app use, and self-care behavior data were collected. Glycemic level data were categorized into hyperglycemia, hypoglycemia, and good control. Multinomial logistic regression stratified by diabetes type was performed. Results: The survey URL was posted in 78 Facebook groups and eight online forums, and ten targeted Facebook ads were conducted yielding 1854 responses. Of those owning smartphones (n = 1753, 95%), 1052 (62.6%) had type 1 and 630 (37.4%) had type 2 DM. More than half of the type 1 respondents (n = 549, 52.2%) and one third the respondents with type 2 DM (n = 210, 33.3%) reported using diabetes apps. Increased odds of experiencing hyperglycemia were noted in persons with type 1 DM with lower educational status (Adjusted Odds Ratio (AOR) = 1.7; 95% Confidence Interval (CI): 1.21–2.39); smokers (1.63, 95% CI: 1.15–2.32), and high diabetes self-management concern (AOR = 2.09, 95% CI: 1.15–2.32). CGM use (AOR = 0.66, 95% CI: 0.44–1.00); “general diet” (AOR = 0.86, 95% CI: 0.79–0.94); and “blood glucose monitoring” (AOR = 0.88, 95%CI: 0.80–0.97) self-care behavior reduced the odds of experiencing hyperglycemia. Hypoglycemia in type 1 DM was reduced by using CGM (AOR = 0.24, 95% CI: 0.09–0.60), while it was increased by experiencing a high diabetes self-management concern (AOR = 1.94, 95% CI: 1.04–3.61). Hyperglycemia in type 2 DM was increased by age (OR = 1.02, 95% CI: 1.00–1.04); high self-management concern (AOR = 2.59, 95% CI: 1.74–3.84); and poor confidence in self-management capacity (AOR = 3.22, 2.07–5.00). Conversely, diabetes app use (AOR = 0.63, 95% CI: 0.41–0.96) and “general diet” self-care (AOR = 0.84, 95% CI: 0.75–0.94), were significantly associated with the reduced odds of hyperglycemia. Conclusion: Diabetes apps, CGM, and educational interventions aimed at reducing self-management concerns and enhancing dietary self-care behavior and self-management confidence may help patients with diabetes to improve glycemic control.

Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: a qualitative study among app users and non-app users

BACKGROUND

Mobile phone applications (apps) have been shown to successfully facilitate the self-management of chronic disease. This study aims to evaluate firstly the experiences, barriers and facilitators to app usage among people with Type 2 Diabetes Mellitus (T2DM) and secondly determine recommendations to improve usage of diabetes apps.

METHODS

Participants were aged ≥ 18 years with a diagnosis of T2DM for ≥ 6 months. Semi-structured phone-interviews were conducted with 16 app and 14 non-app users. Interviews were based on the Technology Acceptance Model, Health Information Technology Acceptance Model (HITAM) and the Mobile Application Rating Scale. Data were analysed using deductive content analysis.

RESULTS

Most app-users found apps improved their T2DM self-management and health. The recommendation of apps by health professionals, as well as positive interactions with them, improved satisfaction; however, only a minority of patients had practitioners involved in their app use. All non-app users had never had the concept discussed with them by a health professional. Facilitators to app use included the visual representation of trends, intuitive navigation and convenience (for example, discretion and portability). Barriers to app use were participant's lack of knowledge and awareness of apps as healthcare tools, perceptions of disease severity, technological and health literacy or practical limitations such as rural connectivity. Factors contributing to app use were classified into a framework based on the Health Belief Model and HITAM. Recommendations for future app design centred on educational features, which were currently lacking (e.g. diabetes complications, including organ damage and hypoglycaemic episodes), monitoring and tracking features (e.g. blood glucose level monitoring with trends and dynamic tips and comorbidities) and nutritional features (e.g. carbohydrate counters). Medication reminders were not used by participants. Lastly, participants felt that receiving weekly text-messaging relating to their self-management would be appropriate.

CONCLUSIONS

The incorporation of user-centred features, which engage T2DM consumers in self-management tasks, can improve health outcomes. The findings may guide app developers and entrepreneurs in improving app design and usability. Given self-management is a significant factor in glycaemic control, these findings are significant for GPs, nurse practitioners and allied health professionals who may integrate apps into a holistic management plan which considers strategies outside the clinical environment.

Use of apps for physical activity in type 1 diabetes: current status and requirements for future development

Smartphone technologies, and the applications (apps) that they host, are developing rapidly mainly with regard to communication, information processing, design, features and connectivity with other devices. Technologies used in modern treatment modalities and monitoring of type 1 diabetes are also rapidly evolving and can communicate with smartphones and apps. Therefore, numerous web-based and smartphone apps aim to provide information and various patient data metrics (e.g. caloric intake, activity levels, glucose monitoring) that can be accessed and processed for decision support by smartphone apps. In this narrative review, we highlight current information about the effectiveness of interventions through smartphone apps with a focus on apps designed to give guidance to patients with type 1 diabetes on physical activity monitoring and glucose control during and after structured exercise sessions, as these patients are experiencing huge therapeutic challenges during exercise. Furthermore, we propose a number of critical elements for future apps designed for people with type 1 diabetes.

Comparing Real-Time Self-Tracking and Device-Recorded Exercise Data in Subjects with Type 1 Diabetes

BACKGROUND

Insulin therapy, medical nutrition therapy, and physical activity are required for the treatment of type 1 diabetes (T1D). There is a lack of studies in real-life environments that characterize patient-reported data from logs, activity trackers, and medical devices (e.g., glucose sensors) in the context of exercise.

OBJECTIVE

The objective of this study was to compare data from continuous glucose monitor (CGM), wristband heart rate monitor (WHRM), and self-tracking with a smartphone application (app), iDECIDE, with regards to exercise behaviors and rate of change in glucose levels.

METHODS

Participants with T1D on insulin pump therapy tracked exercise for 1 month with the smartphone app while WHRM and CGM recorded data in real time. Exercise behaviors tracked with the app were compared against WHRM. The rate of change in glucose levels, as recorded by CGM, resulting from exercise was compared between exercise events documented with the app and recorded by the WHRM.

RESULTS

Twelve participants generated 277 exercise events. Tracking with the app aligned well with WHRM with respect to frequency, 3.0 (2.1) and 2.5 (1.8) days per week, respectively (p = 0.60). Duration had very high agreement, the mean duration from the app was 65.6 (55.2) and 64.8 (54.9) minutes from WHRM (p = 0.45). Intensity had a low concordance between the data sources (Cohen's kappa = 0.2). The mean rate of change of glucose during exercise was -0.27 mg/(dL*min) and was not significantly different between data sources or intensity (p = 0.21).

CONCLUSION

We collated and analyzed data from three heterogeneous sources from free-living participants. Patients' perceived intensity of exercise can serve as a surrogate for exercise tracked by a WHRM when considering the glycemic impact of exercise on self-care regimens.