Comparing Type 2 Diabetes Self-Management Apps Against the Needs of Low-Income Minority Patients: Is There An Implicit Functionality Bias?

Background: Diabetes Mellitus is a chronic disease affecting 30 million in the US. It is a leading cause of death and a major risk factor for severe COVID-19. More than 90% of cases are Type 2 (T2DM), which has adult onset and has risk factors that are behavioral (e.g., smoking) or environmental (e.g., poor nutrition, decreased physical activity). Self-management is critical to long-term treatment of T2DM. It includes adherence to medication regimens, constant nutritional and physical activity management, blood glucose monitoring, and behavioral changes (e.g., smoking cessation). Many mobile computing health (mHealth) apps have been developed to support TM self-management. Problem: US T2DM rates among non-Hispanic whites and the well-educated have leveled off, but diagnoses continue to increase disproportionately among low-income populations, particularly African-American, Latino, and Native American minorities. This has created a growing health disparity associated with social and economic factors that include differential access to healthcare, healthy food, occupational opportunities and physical activity options. (termed Social Determinants of Health or SDOH [1]. Recent public health research [2,3] has begun to identify unique SDOH challenges faced by one such population, low-income African Americans. This poster examines the degree to which the existing T2DM mHealth apps are able to address the self-management needs exposed in this emerging research, versus the more widely studied needs and issues associated with more affluent and largely white population of persons with T2DM. Methods: Seventeen positively assessed T2DM apps were selected from recent review articles. Separately, two sets of functional features were compiled. First, from the T2DM literature, a set of 23 categories and sub-categories was compiled of general features that were identified as desirable to support the T2DM self-management process. Second, a set of eleven functional features and sub-features was developed from the research on the SDOH challenges of low income African American persons with T2DM. The T2DM apps were then compared in a two-stage process using the two sets of criteria. Because many of the criteria in the second set involved social support, only those apps that have some form of social functionality were included in the second stage comparison. Results. The results of the two comparisons are presented as two matrices comparing each app with each criterion and sub-criterion. None of the apps in stage one contained all the general functions suggested in the literature, though several come close. In stage two, most apps had few or none of the focused forms of social support for self-management capabilities of interest. Conclusions. Social capabilities of existing T2DM apps seemed based on the unconstrained social network models used in general social network media (e.g., Facebook, Twitter, Instagram). However, the needs expressed from the low-income communities focused on first order geospatially-local networks that could provide pragmatic help in self-management activities. Additionally, existing apps relied on Premium versions and in-app sales for revenue models, but such features are not accessible to low-income users. Such design decisions suggest an implicit design bias toward more affluent user populations, which also sociologically tend to be more White. Participatory design is recommended as a method that could help avoid such implicit design biases.