Usability of Commercially Available Mobile Applications for Diverse Patients
Open accessAbstract
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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In a study of 11 commercially available mobile applications, participants could complete only 43% of the tasks without assistance.
“The results showed that participants could complete only 43% of the tasks without assistance.”
From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [130]
The Results report that participants completed 79 of 185 (43%) data-retrieval tasks across 11 apps without assistance. The claim omits that restriction and implies the figure covers all tasks; the Results separately report 51% for data-entry tasks. (LLM, conf=0.88)
Experimental — accuracy not yet measuredParticipants had interest in having technology to support self-management, but reported a lack of confidence with technology, as well as frustration with design features and navigation.
“Although participants had interest in having technology to support self-management, they reported a lack of confidence with technology, as well as frustration with design features and navigation.130”
From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [130]
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- Authors
- Sarkar, U., Gourley, G. I., Lyles, C. R., Tieu, L., Clarity, C., Newmark, L., Singh, K., & Bates, D. W.
- Affiliations
- San Francisco General Hospital (US)
- University of Michigan (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Sarkar, Urmimala
- ORCID
- Venue
- Journal of General Internal Medicine
- Published
- 2016-07-14
- Volume
- 31
- Issue
- 12
- Pages
- 1417-1426
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC5130945
- OpenAlex
- W2474131044
- Cited by
- 257
- References
- 32
- Citations by year
- 2026: 13 · 2025: 16 · 2024: 26 · 2023: 25 · 2022: 32 · 2021: 37 · 2020: 36 · 2019: 29 · 2018: 20 · 2017: 17 · 2016: 6
- FWCI
- 44.71
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of General Internal Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Commonwealth Fund
- Agency for Healthcare Research and Quality (R00 HS022408)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Social Sciences › Demography › Technology Use by Older Adults
- Keywords
- mobile health apps, usability, health technology access, racial and ethnic diversity, low-income populations, diabetes mellitus, depression, caregiving, self-management, participatory design, technology acceptance, African Americans, Hispanic Americans, chronic disease
- MeSH terms
- Adult, Depression, Diabetes Mellitus, Female, Health Services Needs and Demand, Humans, Male, Middle Aged, Self Care, User-Computer Interface, Caregivers, Telemedicine, Vulnerable Populations, Cell Phone, Mobile Applications
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