Evaluating a Glucose-Sensor-Based Tool to Help Clinicians and Adults With Type 1 Diabetes Improve Self-Management Skills

Design and Testing of a Smartphone Application for Real-Time Tracking of CSII and CGM Site Rotation Compliance in Patients With Type 1 Diabetes

INTRODUCTION

Glycemic control in patients with type 1 diabetes can be difficult to achieve. One critical aspect of insulin delivery is site rotation, which is necessary to reduce dermatologic complications of repeated insulin infusion. No current application is designed to help patients track sites and instruct on overused sites.

OBJECTIVE

The objectives of this study were to (1) design a smartphone app, Insulin Site Guide, to gather real-time information on continuous subcutaneous insulin infusion (CSII) and continuous glucose monitor (CGM) site location and rotation compliance and instruct subjects on the use of an overused site; (2) conduct a usability study to measure site rotation compliance; and (3) report subject satisfaction with the app.

DESIGN

The app is installed on the subject's smartphone. Subjects use the app to record CSII and CGM placement in real-time. Data are sent to the study team at the end of the study. Subjects complete a questionnaire concerning the app.

RESULTS

We report site rotation compliance data for eight subjects and survey responses for 10 subjects. Initial data from eight subjects indicate a high site rotation compliance of 84% for insulin pumps. In general, the majority of users indicate high satisfaction with the app.

CONCLUSIONS

Insulin Site Guide is a mobile app that uses a novel algorithm to better guide site rotation. Use of the app has the potential to improve site rotation and decrease dermatologic complications of diabetes with long-term use.

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 .

Systematic review of context-aware digital behavior change interventions to improve health

Health risk behaviors are leading contributors to morbidity, premature mortality associated with chronic diseases, and escalating health costs. However, traditional interventions to change health behaviors often have modest effects, and limited applicability and scale. To better support health improvement goals across the care continuum, new approaches incorporating various smart technologies are being utilized to create more individualized digital behavior change interventions (DBCIs). The purpose of this study is to identify context-aware DBCIs that provide individualized interventions to improve health. A systematic review of published literature (2013-2020) was conducted from multiple databases and manual searches. All included DBCIs were context-aware, automated digital health technologies, whereby user input, activity, or location influenced the intervention. Included studies addressed explicit health behaviors and reported data of behavior change outcomes. Data extracted from studies included study design, type of intervention, including its functions and technologies used, behavior change techniques, and target health behavior and outcomes data. Thirty-three articles were included, comprising mobile health (mHealth) applications, Internet of Things wearables/sensors, and internet-based web applications. The most frequently adopted behavior change techniques were in the groupings of feedback and monitoring, shaping knowledge, associations, and goals and planning. Technologies used to apply these in a context-aware, automated fashion included analytic and artificial intelligence (e.g., machine learning and symbolic reasoning) methods requiring various degrees of access to data. Studies demonstrated improvements in physical activity, dietary behaviors, medication adherence, and sun protection practices. Context-aware DBCIs effectively supported behavior change to improve users' health behaviors.

Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study

BACKGROUND

Attempts to utilize eHealth in diabetes mellitus (DM) management have shown promising outcomes, mostly targeted at patients; however, few solutions have been designed for health care providers.

OBJECTIVE

The purpose of this study was to conduct a feasibility project developing and evaluating a mobile clinical decision support system (CDSS) tool exclusively for health care providers to manage chronic kidney disease (CKD) in patients with DM.

METHODS

The design process was based on the 3 key stages of the user-centered design framework. First, an exploratory qualitative study collected the experiences and views of DM specialist nurses regarding the use of mobile apps in clinical practice. Second, a CDSS tool was developed for the management of patients with DM and CKD. Finally, a randomized controlled trial examined the acceptability and impact of the tool.

RESULTS

We interviewed 15 DM specialist nurses. DM specialist nurses were not currently using eHealth solutions in their clinical practice, while most nurses were not even aware of existing medical apps. However, they appreciated the potential benefits that apps may bring to their clinical practice. Taking into consideration the needs and preferences of end users, a new mobile CDSS app, "Diabetes & CKD," was developed based on guidelines. We recruited 39 junior foundation year 1 doctors (44% male) to evaluate the app. Of them, 44% (17/39) were allocated to the intervention group, and 56% (22/39) were allocated to the control group. There was no significant difference in scores (maximum score=13) assessing the management decisions between the app and paper-based version of the app's algorithm (intervention group: mean 7.24 points, SD 2.46 points; control group: mean 7.39, SD 2.56; t₃₇=-0.19, P=.85). However, 82% (14/17) of the participants were satisfied with using the app.

CONCLUSIONS

The findings will guide the design of future CDSS apps for the management of DM, aiming to help health care providers with a personalized approach depending on patients' comorbidities, specifically CKD, in accordance with guidelines.

Experiences of Adults With Type 1 Diabetes Using Glucose Sensor-Based Mobile Technology for Glycemic Variability: Qualitative Study

Background

Adults with type 1 diabetes (PWDs) face challenging self-management regimens including monitoring their glucose values multiple times a day to assist with achieving glycemic targets and reduce the risk of long-term diabetes complications. Recent advances in diabetes technology have reportedly improved glycemia, but little is known about how PWDs utilize mobile technology to make positive changes in their diabetes self-management.

Objective

The aim of this qualitative study was to explore PWDs’ experiences using Sugar Sleuth, a glucose sensor–based mobile app and Web-based reporting system, integrated with the FreeStyle Libre glucose monitor that provides feedback about glycemic variability.

Methods

We used a qualitative descriptive research design and conducted semistructured interviews with 10 PWDs (baseline mean glycated hemoglobin, HbA_1c) 8.0%, (SD 0.45); 6 males and 4 females, aged 52 years (SD 15), type 1 diabetes (T1D) duration 31 years (SD 13), 40% (4/10, insulin pump) following a 14-week intervention during which they received clinical support and used Sugar Sleuth to evaluate and understand their glucose data. Audio-recorded interviews were transcribed, coded, and analyzed using thematic analysis and NVivo 11 (QSR International Pty Ltd).

Results

A total of 4 main themes emerged from the data. Participants perceived Sugar Sleuth as an Empowering Tool that served to inform lifestyle choices and diabetes self-management tasks, promoted preemptive self-care actions, and improved discussions with clinicians. They also described Sugar Sleuth as providing a Source of Psychosocial Support and offering relief from worry, reducing glycemic uncertainty, and supporting positive feelings about everyday life with diabetes. Participants varied in their Approaches to Glycemic Data: 40% (4/10) described using Sugar Sleuth to review data, understand glycemic cause and effect, and plan for future self-care. On the contrary, 60% (6/10) were reluctant to review past data; they described receiving benefits from the immediate numbers and trend arrows, but the app still prompted them to enter in the suspected causes of glucose excursions within hours of their occurrence. Finally, only 2 participants voiced Concerns About Use of Sugar Sleuth; they perceived the app as sometimes too demanding of information or as not attuned to the socioeconomic backgrounds of PWDs from diverse populations.

Conclusions

Results suggest that Sugar Sleuth can be an effective educational tool to enhance both patient-clinician collaboration and diabetes self-management. Findings also highlight the importance of exploring psychosocial and socioeconomic factors that may advance the understanding of PWDs’ individual differences when using glycemic technology and may promote the development of customized mobile tools to improve diabetes self-management.