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Voice assistants (VAs) such as Siri or Amazon Alexa can benefit older adults by offering accessible and convenient information options and aiding living independently. Therefore, researchers have considered how VAs might support older adults. Yet, few studies have explored opportunities for VAs to support communities and the implications of this integration. This study investigates older adults' perceptions of VAs and the potential to extend VA capabilities to support an independent living community. We invited independent living residents to virtual community forums and interviews to discuss their experiences with VAs, expectations, and concerns for VA integration to support information exchange, wellness, and social connections in their community. We found that residents desired additional VA capabilities to address unique community needs, including building on existing community capacities to support VA adoption and use. We discuss VA design implications for independent living communities and recommendations to support VA sustainability in a community environment.
While past research has examined older adults’ voice assistant (VA) use, it is unclear whether VAs provide enough value to sustain use when compared to technologies such as smartphones. Research also suggests that barriers around structured command input may limit use. In order to investigate these gaps in adoption, we conducted interviews with ten older adults in a long-term care community who have adopted Alexa devices for at least one year. Participants learned to use Alexa through a training program that encouraged exploration. They used Alexa to complement their daily routines, improve their mood, engage in cognitively stimulating activities, and support socialization with others.We discuss our findings in the context of prior work, describe strategies to promote VA learning and adoption, and present design recommendations to support aging.
Older adults often struggle to locate a function quickly in feature-rich user interfaces (UIs). Mobile UIs not only pack a ton of features in a small screen but also get frequent updates to their visual layouts—thereby exacerbating the problem. This paper explores a design solution where users could search for a UI feature using spoken-word queries. We investigated: 1) what type of questions older users ask when facing interaction challenges in unfamiliar scenarios, 2) how those query types compare with younger users' inquiries, and 3) how older adults use a voice assistant design probe in a Wizard-of-Oz (WoZ) study. Results reveal five query types when verbally articulating interaction issues: validation, directed and undirected informational, navigational, and conceptual. In the WoZ study, older users typically asked for help following a series of non-unique or off-task feature selections (n = 13/15), and in 77% of those instances, they completed the task in the next interaction.
In this paper, we present Health Buddy, a voice agent integrated into commercially available Voice User Interfaces (VUIs) to support informal self-regulated learning (SRL) of health-related topics through multiple learning strategies and examine the efficacy of Health Buddy on learning outcomes for younger and older adults. We conducted a mixed-factorial-design experiment with 26 younger and 25 older adults, assigned to three SRL strategies (within-subjects): monologue, dialogue-based scaffolding building, and conceptual diagramming. We found that while younger adults benefit more from scaffolding building and conceptual diagramming, both younger and older adults showed equivalent learning outcomes. Furthermore, interaction fluency (operationalized by the number of conversational breakdowns) was associated with learning outcomes regardless of age. While older adults did not experience less fluent conversations, interaction fluency affected their technology acceptance toward VUIs more than younger ones. Our study discusses age-related learning differences and has implications for designing VUI-based learning programs for older adults.
This paper presents an inspirational concept for companion technology design, uncontrollability, and a corresponding artefact, the Blessing Companion. Both originated from a research through design project exploring companion technologies for blessing rituals. We established an exchange with Protestant theologians, explored believers' experiences of blessings, co-speculated on potential technologies, and refined the resulting ideas through ideation, prototyping, and testing. Inspired by believers' descriptions of blessing experiences as not plannable, predictable, controllable, or enforceable, we adopted the concept of uncontrollability, explored how it might be implemented in companion technologies, and designed the Blessing Companion. The Blessing Companion embodies uncontrollability through its ambiguous appearance and (partly) uncontrollable behaviour. It thus stands in contrast to the prevailing on-demand and user-driven interaction paradigms. We discuss how uncontrollability can be reflected in content, form, and interaction, highlight respective possibilities for companion technologies, and reflect on the Blessing Companion as an example of designing for religious rituals.
Recent years have seen a proliferation of security-focused smart home devices (SSHDs). SSHDs, such as smart locks and cameras, are designed to accomplish critical tasks, such as protecting one's home and property. However, their use by and for people with disabilities (PwD) has not been broadly investigated. To explore the state of SSHD use by PwD, we collected 114,871 amazon.com reviews for popular SSHDs and created a data set of reviews pertaining to PwD. We performed a broad analysis of the reviews in this data set and found that the presence of SSHDs empowered PwD to secure their domiciles independently. Further, caregivers used SSHDs to monitor PwD, ostensibly for the latter's safety, albeit without explicit consent. Moreover, we also found that SSHDs have several drawbacks that impose various barriers of use on PwD. We analyze the significance of these findings and suggest five future research opportunities for SSHD design.