Understanding Barriers and Design Opportunities to Improve Healthcare and QOL for Older Adults through Voice Assistants
Chen Chen, Janet G. Johnson, Kemeberly Charles, Alice Lee, Ella T. Lifset, Michael Hogarth, Alison A. Moore, Emilia Farcas, Nadir Weibel · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3441852.3471218
Summary
This paper investigates the barriers older adults face when managing their healthcare and daily routines, and explores how voice-based Intelligent Virtual Assistants (IVAs) might address those challenges. The researchers employed a user-centered design approach, conducting semi-structured interviews with 16 older adults (aged 68-90, mean age 75.56) recruited through UC San Diego Health, along with 5 healthcare providers including geriatricians and nurses. Interviews were conducted remotely during the COVID-19 pandemic, which itself amplified many of the barriers identified. The study is distinctive in framing care delivery and quality of life enhancement as a collaborative task between patients and providers, gathering perspectives from both sides rather than focusing solely on patient experience. Participants had varying levels of familiarity with IVAs — some had used devices like Amazon Echo or Google Home, while others had no prior knowledge of voice assistants. Through inductive and deductive coding grounded in grounded theory methodology, the researchers identified 12 specific barriers organized across four categories: medication management, daily life and routines, patient-provider communication, and use of voice-based technologies. The paper goes beyond simply cataloging problems by connecting each barrier to concrete design opportunities for voice-first interfaces.
Key findings
The study identified 12 barriers across four categories. In medication management, older adults struggled to track complex prescription regimens and lacked reliable guidance for over-the-counter medication selection. For daily life, loneliness and social isolation were pervasive — exacerbated by COVID-19 lockdowns — and providers lacked efficient ways to monitor patients remotely. Patient-provider communication suffered from inefficient GUI-based patient portals that older adults found difficult to use, leading many to revert to paper-based methods or phone calls. Regarding voice technology itself, older adults encountered frustration with technical complexity and setup processes, speech recognition failures related to hearing impairment and age-related vocal changes, a significant gap between available and desired IVA features, and persistent concerns about data security and privacy. Notably, none of the older adults with IVA experience had used voice assistants for healthcare purposes despite the existence of health-related voice applications. The researchers mapped their findings onto ability-based design principles, adding a Privacy and Trust category to account for the invasive nature of always-listening devices. They advocate for voice-first (not voice-only) interfaces that provide multimodal input and output, and emphasize the need for personalization that accounts for the wide variation in abilities across different stages of aging.
Relevance
This research is directly relevant to accessibility practitioners working on voice interfaces, healthcare technology, or products for aging populations. The 12 barriers provide a practical framework for understanding where current technology fails older adults, while the ability-based design mapping offers actionable design strategies. The emphasis on voice-first rather than voice-only design reinforces the importance of multimodal accessibility — providing alternative input and output channels alongside voice. The finding that older adults rely heavily on providers and caregivers as technology intermediaries highlights the need to design for ecosystems of users, not just individual end users. For organizations building voice-enabled healthcare tools, the privacy and trust concerns raised by participants underscore the importance of transparent data practices and clear communication about how voice data is used. The study's limitations include a relatively homogeneous sample skewed toward higher socioeconomic status, and the exclusion of older adults living dependently.
Tags: voice assistants · older adults · healthcare · intelligent virtual assistants · gerontechnology · user experience design · ability-based design · patient portals · qualitative research