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Review
. 2018 Nov 21;6(11):e12237.
doi: 10.2196/12237.

App Features for Type 1 Diabetes Support and Patient Empowerment: Systematic Literature Review and Benchmark Comparison

Antonio Martinez-Millana #  1 , Elena Jarones #  1 , Carlos Fernandez-Llatas #  1 , Gunnar Hartvigsen #  2 , Vicente Traver #  1
Affiliations
Review

App Features for Type 1 Diabetes Support and Patient Empowerment: Systematic Literature Review and Benchmark Comparison

Antonio Martinez-Millana et al. JMIR Mhealth Uhealth. .

Abstract

Background: Research in type 1 diabetes management has increased exponentially since the irruption of mobile health apps for its remote and self-management. Despite this fact, the features affect in the disease management and patient empowerment are adopted by app makers and provided to the general population remain unexplored.

Objective: To study the gap between literature and available apps for type 1 diabetes self-management and patient empowerment and to discover the features that an ideal app should provide to people with diabetes.

Methods: The methodology comprises systematic reviews in the scientific literature and app marketplaces. We included articles describing interventions that demonstrated an effect on diabetes management with particular clinical endpoints through the use of mobile technologies. The features of these apps were gathered in a taxonomy of what an ideal app should look like to then assess which of these features are available in the market.

Results: The literature search resulted in 231 matches. Of these, 55 met the inclusion criteria. A taxonomy featuring 3 levels of characteristics was designed based on 5 papers which were selected for the synthesis. Level 1 includes 10 general features (Personalization, Family support, Agenda, Data record, Insulin bolus calculator, Data management, Interaction, Tips and support, Reminders, and Rewards) Level 2 and Level 3 included features providing a descriptive detail of Level 1 features. Eighty apps matching the inclusion criteria were analyzed. None of the assessed apps fulfilled the features of the taxonomy of an ideal app. Personalization (70/80, 87.5%) and Data record (64/80, 80.0%) were the 2 top prevalent features, whereas Agenda (5/80, 6.3%) and Rewards (3/80, 3.8%) where the less predominant. The operating system was not associated with the number of features (P=.42, F=.81) nor the type of feature (P=.20, χ2=11.7). Apps were classified according to the number of level 1 features and sorted into quartiles. First quartile apps had a regular distribution of the ten features in the taxonomy whereas the other 3 quartiles had an irregular distribution.

Conclusions: There are significant gaps between research and the market in mobile health for type 1 diabetes management. While the literature focuses on aspects related to gamification, rewarding, and social communities, the available apps are focused on disease management aspects such as data record and appointments. Personalized and tailored empowerment features should be included in commercial apps for large-scale assessment of potential in the self-management of the disease.

Keywords: apps; diabetes self-management; mHealth; patient empowerment; type 1 diabetes mellitus.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Selection of the literature for evidence-based features of mobile apps for type 1 diabetes management and empowerment.
Figure 2
Figure 2
Taxonomy of the features of an ideal app according to the evidence-based effectiveness of mobile health in diabetes support and empowerment.
Figure 3
Figure 3
Selection of the available apps for type 1 diabetes management and empowerment.
Figure 4
Figure 4
Apps included in the analysis. From top-down left-right: Balansio, Bant, BeatO, Beyond type 1 diabetes, Blood glucose tracker, BlueLoop, Brook, Carbs & Cals, Center health, Checkmate diabetes, Chron, Contour diabetes, Dario, Diabetes a la carta, Diabetes & Me, Diabetes connect, Diabetes diary, Diabetes diet and management, Diabetes digest, Diabetes evaluation, Diabetes experience day, Diabetes ID, Diabetes insight, Diabetes kit blood, Diabetes metrics, Diabetes PA, Diabetes pal, Diabetes parent, Diabetes passport, Diabetes pilot pro, Diabetes plus, Diabetes treatment, Diabetes vue, Diabetika, Diaguard, Diario de sangre, Diasend, DMI from zero to hero, Dnurse, Dottli, Dr. Diabetes, Easy diabetes, Glooko, Glucool diabetes, Glucosa compañero, Glucose buddy, Glucose wiz, Uright, Glucosio, GluQUO, Health2sync, Helparound, iFora, Inrange, Insulclock, Kids and teens diabetes, Kingfit, La diabetes M, Life in control, MedM diabetes, Meet me, Mi glucemia, Monitor de glucosa, Mumoactive, My diabetic alert, Nagbot, Neptun, One drop, Ontrack diabetes, PredictBGL, Social diabetes, SOS diabetes, Sugar sense, Sugarmate, Track3lite.
Figure 5
Figure 5
The relationship among the number of level 1 features and the Feature Factor.
Figure 6
Figure 6
Distribution of level 1 features classified according to the number of level 1 features in the apps divided into quartiles.
See this image and copyright information in PMC

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