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Digital home assistants (e.g., Amazon Echo) hold great potential to support older adults across a wide range of abilities to improve or maintain their quality of life. However, these devices and other related environmental control applications are not equipped with sufficient support for successful technology adoption among older adults. Without useful and usable information for guidance during the initial and continued use of these technologies (i.e., facilitating conditions), older adults may not sufficiently learn how to best utilize them, which is a primary barrier to technology adoption among this population. Our goal was to iteratively develop and test an instructional suite to support set up and use of an Amazon Echo Show and related connected technologies by older adults. Our human factors approach provides a roadmap to inform future instructional development for older adults to learn smart and connected technologies.

Smart technologies have increased dramatically within the last decade. Their availability has improved opportunities for productivity, health, and entertainment, and this is especially true for technologies that act as central hubs to link other devices and applications that expand their capabilities (e.g., smartphones and digital home assistants). Older adults may significantly benefit from integrating these devices into their lives to mitigate the various challenges they face with increasing age (e.g., cognitive, mobility changes). To understand the potential of these technologies for this population, we investigated use patterns, learning preferences, and other perceptions related to the adoption of these devices. Seventy older adult participants responded to an online survey regarding their use and preferences with smartphones and digital home assistants. The results informed our understanding of current adoption rates as well as provided key perspectives to inform their design for older adults.

Hypertension, or high blood pressure, is an asymptomatic cardiovascular condition common with increasing age that must be controlled with proper management behaviors, such as adherence to prescribed antihypertensive medications. Unfortunately, older adults may struggle with consistent and effective management of this medication specifically and the disease generally, which can lead to poorer health outcomes. The goal of the study was to investigate older adults’ antihypertensive medication management using the Illness Representation Model as a lens to identify potential misconceptions that may contribute to medication management. We conducted semi-structured interviews with 40 older adults regarding management routines, hypertension knowledge, perceived nonadherence contributors, and perspectives related to their illness. We identified numerous misconceptions regarding hypertension knowledge, disease severity, as well as perceived adherence performance that may contribute to challenges older adults face with maintaining antihypertensive medication adherence. Moreover, these findings inform the need for and design of effective educational tools for improving antihypertensive medication adherence.

Digital home assistants like the Amazon Echo are increasing in popularity each year among the general population and provide assistance across a wide array of daily activities. Despite their general utility, they may be most useful for supporting older adults with the various challenges of aging. However, little is known about older adults’ opinions regarding these devices, which is necessary to encourage their adoption of these devices. We conducted semi-structured interviews with 18 older adult novice users to learn about their initial opinions regarding two digital home assistants, the Amazon Echo smart speaker and Echo Show smart display. Results revealed an overall trend of positive attitudes toward them and their capabilities, with a preference toward the Echo Show. These findings provided insights into older adults’ first impressions of digital home assistants, plus the foundation for investigating their potential in supporting older adults in maintaining functional independence.

Voice-activated digital assistants have the potential to assist adults aging-in-place with a variety of everyday tasks and leisure activities. To understand this potential, semi-structured interviews were conducted to explore perceptions and attitudes from current adult users based on the models of the unified theory of acceptance and use of technology model. Several model factors were identified as influential in the initial and continued use of the digital assistants. Results indicate the need for an effective instructional protocol to promote successful interactions during the learning phase and for continued engagement with novel abilities of the digital assistants.

Many older adults are living with at least one chronic disease and must adhere to prescribed medication to mitigate and control its impact. Hypertension is one chronic disease that affects a significant portion of the world’s population, especially older adults, and is responsible for a high number of annual deaths. It is asymptomatic, meaning that there are no perceptible symptoms and, as such, older adults may struggle with adhering to their prescribed antihypertensive medications. How one internalizes the disease may influence the degree of success in managing the condition. The current study analyzed archival data from a multifaceted prospective memory intervention for older adults with hypertension who were nonadherent to their medication. We coded their responses to self-management interview questions to identify the common themes regarding the knowledge and sense of control the older adults held relevant to managing their illness. Participants’ responses revealed how they internalized hypertension and their medication, as well as the strategies and goals they reportedly used to manage the illness. The association strategy was found to be the most commonly used within participants’ routines. In addition, many participants expressed a general lack of knowledge about the disease or their medication, and their goals regarding hypertension management were general and inexplicit (e.g., “to reduce their blood pressure). This information informs the design of more effective and longer-lasting interventions geared toward significantly improving the medication adherence of older adults diagnosed with hypertension.

The aim of the current study was to understand how to integrate digital home assistant technologies and smart appliances into older adults’ homes by developing supportive user guides that facilitate adoption and continued use. We conducted a series of interviews among older adults, with and without mobility disabilities, to understand their attitudes towards digital assistants and to identify needs for instructional support and user guides. Subsequently, we developed and tested specific user guide modules for older adults aimed at addressing the identified concerns and desired instructional support. Specifically, we developed and field-tested user guides for the initial Amazon Echo device setup, basic device use (e.g., playing music and checking the weather), and separate modules for other domestic use cases (e.g., how to pair an Alexa enabled device with smart lights or appliances). Our results provide guidance for implementation of smart voice technologies to support older adults with long-term mobility disabilities.

The aim of the current study was to evaluate the feasibility, usability, safety, and efficacy of digital home assistant health applications (e.g., meditation applications, medication reminders, hydration management) for older adults with mobility disabilities. We used a multi-pronged approach. First, we compiled, categorized, and assessed a list of commercially available health applications compatible with Amazon Alexa devices. We reviewed data from the National Health and Aging Trends Study and the ACCESS study to identify challenges that older adults with mobility disabilities face within the home. We also reviewed the literature on the acceptance and use of digital home assistant health applications by older adults. Lastly, we conducted user testing in a laboratory and in a home-simulation environment to assess usability of different health applications. Our results provide guidance for the implementation of digital home assistant health applications to support older adults with long-term mobility disabilities.

Voice-activated digital assistants (e.g., Amazon Echo, Google Home) are an emerging technology that have great potential to provide support for adults aging with a long-term mobility disability. Digital assistant technologies allow the user to perform a variety of everyday tasks and activities through voice interactions. Such tasks may include environmental control (e.g., turning on/off lights, voice-activated temperature control); supporting self-health management (e.g., providing medication reminders, encouraging physical activity engagement); and fostering opportunities for social engagement (e.g., messaging/calling others, playing games remotely). This presentation will focus on the perceived facilitators and barriers to digital assistant use in the home among adults aging with mobility disabilities. The findings provide design guidelines and insight for intervention implementation for the use of these technologies for the target population.

Social engagement is a fundamental component of health and quality-of-life outcomes. Our goal in this chapter is to assess the relationship between social engagement and health outcomes for older adults, specifically with respect to the role technology can play in supporting and facilitating social engagement. Social engagement technologies include established forms of electronic communication such as email and social networking sites (e.g., Facebook), as well as emerging technologies such as telepresence, social robots, virtual reality, and augmented reality. Our review of the literature revealed that there are barriers for older adults in the adoption and use of technologies that foster social engagement. We make recommendations about how designers can overcome these barriers to better suit the needs and interests of older adults.

Recently, there has been a significant expansion in the number of smart and connected technologies for assisting individuals with a variety of tasks within the home. Examples include digital home assistants (e.g., Amazon Echo), smart lights, smart plugs, robotic vacuums, as well as a multitude of other devices. Such technologies hold the potential to support independence for older adults with long-term mobility disabilities, as they may experience challenges engaging in daily activities. The aim of the current study was to utilize a comprehensive approach with an interdisciplinary team to improve understanding of how to integrate smart technology into older adults’ homes. We focused on identifying functionality that would be useful to them, understanding their perceptions, and developing instructional support. We conducted interviews among older adults with, and without, long-term mobility disabilities to better understand their attitudes towards digital assistants, identify needs for instructional support, and test the usability of our instructional protocol. The overall goal of this research is to improve understanding of older adults’ perceptions of these technologies and identify usability challenges within the home. The instructional protocol offers support by reducing the identified barriers to initial adoption and continued use to promote aging-in-place and improving overall quality of life for older adults with long-term mobility disabilities.

The degree to which “brain training” can improve general cognition, resulting in improved performance on tasks dissimilar from the trained tasks (transfer of training), is a controversial topic. Here we tested the degree to which cognitive training, in the form of gamified training activities that have demonstrated some degree of success in the past, might result in broad transfer. Sixty older adults were randomly assigned to a gamified cognitive training intervention or to an active control condition that involved playing word and number puzzle games. Participants were provided with tablet computers and asked to engage in their assigned training for thirty 45-minute training sessions over the course of one month. Although intervention adherence was acceptable, little evidence for transfer was observed except for the performance of one task that most resembled the gamified cognitive training: There was a trend for greater improvement on a version of the corsi block tapping task for the cognitive training group relative to the control group. This task was very similar to one of the training games. Results suggest that participants were learning specific skills and strategies from game training that influenced their performance on a similar task. However, even this near-transfer effect was weak. Although the results were not positive with respect to broad transfer of training, longer duration studies with larger samples and the addition of a retention period are necessary before the benefit of this specific intervention can be ruled out.

There has been recent excitement over the potential for commercial and custom digital games to reverse age-related perceptual and cognitive decline. The effectiveness of digital game-based brain training is controversial. However, a separate issue is, should digital game-based interventions prove effective, how best to design these interventions to encourage intervention engagement and adherence by older adults (ages 65 +). This study explored older adults’ perceptions and attitudes toward game-based interventions after they were asked to play digital games (experimental or control games) for a month-long period. Clear differences in attitudes toward game-based interventions were observed, as assessed by post-intervention surveys, with older adults finding games in the control condition (word and number puzzle games) more enjoyable and less frustrating compared to a digital game that consisted of gamified brain training interventions that have demonstrated some degree of success in the literature. Interestingly, older adults perceived the control condition as more likely to boost perceptual and cognitive abilities (e.g., vision, reaction time), as assessed by a post-intervention survey of expectations. Although predicting intervention adherence was challenging, overall motivation to do well in the intervention was significantly related to perceptions of cognitive benefit. Not surprisingly, game enjoyment also predicted motivation. Finally, older adults who perceived the game they were assigned to play as more challenging were more likely to believe the game would boost cognition. These findings identify attitudes and beliefs that could be targeted to motivate older adults to adhere to digital game-based interventions found to boost cognition. To better explore factors related to intervention adherence in the future we propose studies of longer duration (e.g., 6–12 months) and studies that allow more flexibility and choice with respect to amount of gameplay (instead of gameplay being dictated by a fixed schedule determined by the experimenter, leaving less variability to be explained by individual difference factors).

Increasing evidence suggests that action digital game training can improve a variety of perceptual and cognitive abilities, including those that decline most with age. Unfortunately, previous work has found that older adults dislike these games and adherence may be poor for action game-based interventions. The focus of the current study was to better understand the types of games older adults are willing to play and explore predictors of game preference (e.g., gender, age, technology experience, personality). With this information action games might be modified or developed to maximize adherence and cognitive benefit. Older adults were administered a modified version of an existing game questionnaire and a custom game preference survey. Clear preferences were observed that were similar between participants with and without previous digital game experience (with puzzle and intellectually stimulating games being most interesting to older adults in our sample, and massively multiplayer online games and first-person shooters being least interesting). Personality, demographic, and technology experience variables were also collected. Interesting trends suggested the possibility that several demographic and personality variables might be predictive of game preference. Results have implications for future directions of research, designing games that would appeal to older adult audiences, and for how to design custom games to maximize intervention adherence based on individual difference characteristics.