Design of an mHealth app for the self-management of adolescent type 1 diabetes: a pilot study

Abstract

Background: The use of mHealth apps has shown improved health outcomes in adult populations with type 2 diabetes mellitus. However, this has not been shown in the adolescent type 1 population, despite their predisposition to the use of technology. We hypothesized that a more tailored approach and a strong adherence mechanism is needed for this group.

Objective: To design, develop, and pilot an mHealth intervention for the management of type 1 diabetes in adolescents.

Methods: We interviewed adolescents with type 1 diabetes and their family caregivers. Design principles were derived from a thematic analysis of the interviews. User-centered design was then used to develop the mobile app bant. In the 12-week evaluation phase, a pilot group of 20 adolescents aged 12-16 years, with a glycated hemoglobin (HbA(1c)) of between 8% and 10% was sampled. Each participant was supplied with the bant app running on an iPhone or iPod Touch and a LifeScan glucometer with a Bluetooth adapter for automated transfers to the app. The outcome measure was the average daily frequency of blood glucose measurement during the pilot compared with the preceding 12 weeks.

Results: Thematic analysis findings were the role of data collecting rather than decision making; the need for fast, discrete transactions; overcoming decision inertia; and the need for ad hoc information sharing. Design aspects of the resultant app emerged through the user-centered design process, including simple, automated transfer of glucometer readings; the use of a social community; and the concept of gamification, whereby routine behaviors and actions are rewarded in the form of iTunes music and apps. Blood glucose trend analysis was provided with immediate prompting of the participant to suggest both the cause and remedy of the adverse trend. The pilot evaluation showed that the daily average frequency of blood glucose measurement increased 50% (from 2.4 to 3.6 per day, P = .006, n = 12). A total of 161 rewards (average of 8 rewards each) were distributed to participants. Satisfaction was high, with 88% (14/16 participants) stating that they would continue to use the system. Demonstrating improvements in HbA(1c) will require a properly powered study of sufficient duration.

Conclusions: This mHealth diabetes app with the use of gamification incentives showed an improvement in the frequency of blood glucose monitoring in adolescents with type 1 diabetes. Extending this to improved health outcomes will require the incentives to be tied not only to frequency of blood glucose monitoring but also to patient actions and decision making based on those readings such that glycemic control can be improved.

Figure 1

The bluglu adapter for wireless transfer of blood glucose readings via Bluetooth. This avoids the need for manual data entry by the user.

Figure 2

The bant Readings screen, indicating the reading through colored circles that represent both value and context.

Figure 3

Trends allows at-a-glance review of readings over 7-day, 14-day, 21-day, and 90-day periods. The percentages of readings under, within, and above target range are noted for quick review.

Figure 4

Trend Alert automatically identifies 3-day trends and prompts users to identify what they believe is the cause (left) and their intended action (right).

Figure 5

The bant Rewards screen (left) indicating experience points (XP) awarded and redeemed for applications and music. The right-hand screen shows the private microblogging community within bant, allowing users to communicate with one another.