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Usability of Commercially Available Mobile Applications for Diverse Patients.

Abstract

Background

Mobile applications or 'apps' intended to help people manage their health and chronic conditions are widespread and gaining in popularity. However, little is known about their acceptability and usability for low-income, racially/ethnically diverse populations who experience a disproportionate burden of chronic disease and its complications.

Objective

The objective of this study was to investigate the usability of existing mobile health applications ("apps") for diabetes, depression, and caregiving, in order to facilitate development and tailoring of patient-facing apps for diverse populations.

Design

Usability testing, a mixed-methods approach that includes interviewing and direct observation of participant technology use, was conducted with participants (n = 9 caregivers; n = 10 patients with depression; and n = 10 patients with diabetes) on a total of 11 of the most popular health apps (four diabetes apps, four depression apps, and three caregiver apps) on both iPad and Android tablets.

Participants

The participants were diverse: 15 (58 %) African Americans, seven (27 %) Whites, two (8 %) Asians, two (8 %) Latinos with either diabetes, depression, or who were caregivers.

Main measures

Participants were given condition-specific tasks, such as entering a blood glucose value into a diabetes app. Participant interviews were video recorded and were coded using standard methods to evaluate attempts and completions of tasks. We performed inductive coding of participant comments to identify emergent themes.

Key results

Participants completed 79 of 185 (43 %) tasks across 11 apps without assistance. Three themes emerged from participant comments: lack of confidence with technology, frustration with design features and navigation, and interest in having technology to support their self-management.

Conclusions

App developers should employ participatory design strategies in order to have an impact on chronic conditions such as diabetes and depression that disproportionately affect vulnerable populations. While patients express interest in using technologies for self-management, current tools are not consistently usable for diverse patients.

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