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

Diabetes Technol Ther. 2019 Jul;21(7):393-399. doi: 10.1089/dia.2019.0086. Epub 2019 Jun 5.

Abstract

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.

Keywords: Apps; Self-management; Smartphone; Type 2 diabetes; mHealth.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Cost of Illness
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / psychology*
  • Female
  • Follow-Up Studies
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Mobile Applications*
  • Patient Preference / psychology*
  • Qualitative Research
  • Self-Management / psychology*