Exploring older adults’ perception and use of smart speaker-based voice assistants: A longitudinal study

Assessing the Feasibility and Acceptability of Smart Speakers in Behavioral Intervention Research With Older Adults: Mixed Methods Study

BACKGROUND

Smart speakers, such as Amazon's Echo and Google's Nest Home, combine natural language processing with a conversational interface to carry out everyday tasks, like playing music and finding information. Easy to use, they are embraced by older adults, including those with limited physical function, vision, or computer literacy. While smart speakers are increasingly used for research purposes (eg, implementing interventions and automatically recording selected research data), information on the advantages and disadvantages of using these devices for studies related to health promotion programs is limited.

OBJECTIVE

This study evaluates the feasibility and acceptability of using smart speakers to deliver a physical activity (PA) program designed to help older adults enhance their physical well-being.

METHODS

Community-dwelling older adults (n=18) were asked to use a custom smart speaker app to participate in an evidence-based, low-impact PA program for 10 weeks. Collected data, including measures of technology acceptance, interviews, field notes, and device logs, were analyzed using a concurrent mixed analysis approach. Technology acceptance measures were evaluated using time series ANOVAs to examine acceptability, appropriateness, feasibility, and intention to adopt smart speaker technology. Device logs provided evidence of interaction with and adoption of the device and the intervention. Interviews and field notes were thematically coded to triangulate the quantitative measures and further expand on factors relating to intervention fidelity.

RESULTS

Smart speakers were found to be acceptable for administering a PA program, as participants reported that the devices were highly usable (mean 5.02, SE 0.38) and had strong intentions to continue their use (mean 5.90, SE 0.39). Factors such as the voice-user interface and engagement with the device on everyday tasks were identified as meaningful to acceptability. The feasibility of the devices for research activity, however, was mixed. Despite the participants rating the smart speakers as easy to use (mean 5.55, SE 1.16), functional and technical factors, such as Wi-Fi connectivity and appropriate command phrasing, required the provision of additional support resources to participants and potentially impaired intervention fidelity.

CONCLUSIONS

Smart speakers present an acceptable and appropriate behavioral intervention technology for PA programs directed at older adults but entail additional requirements for resource planning, technical support, and troubleshooting to ensure their feasibility for the research context and for fidelity of the intervention.

Longitudinal Coadaptation of Older Adults With Wearables and Voice-Activated Virtual Assistants: Scoping Review

BACKGROUND

The integration of smart technologies, including wearables and voice-activated devices, is increasingly recognized for enhancing the independence and well-being of older adults. However, the long-term dynamics of their use and the coadaptation process with older adults remain poorly understood. This scoping review explores how interactions between older adults and smart technologies evolve over time to improve both user experience and technology utility.

OBJECTIVE

This review synthesizes existing research on the coadaptation between older adults and smart technologies, focusing on longitudinal changes in use patterns, the effectiveness of technological adaptations, and the implications for future technology development and deployment to improve user experiences.

METHODS

Following the Joanna Briggs Institute Reviewer's Manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, this scoping review examined peer-reviewed papers from databases including Ovid MEDLINE, Ovid Embase, PEDro, Ovid PsycINFO, and EBSCO CINAHL from the year 2000 to August 28, 2023, and included forward and backward searches. The search was updated on March 1, 2024. Empirical studies were included if they involved (1) individuals aged 55 years or older living independently and (2) focused on interactions and adaptations between older adults and wearables and voice-activated virtual assistants in interventions for a minimum period of 8 weeks. Data extraction was informed by the selection and optimization with compensation framework and the sex- and gender-based analysis plus theoretical framework and used a directed content analysis approach.

RESULTS

The search yielded 16,143 papers. Following title and abstract screening and a full-text review, 5 papers met the inclusion criteria. Study populations were mostly female participants and aged 73-83 years from the United States and engaged with voice-activated virtual assistants accessed through smart speakers and wearables. Users frequently used simple commands related to music and weather, integrating devices into daily routines. However, communication barriers often led to frustration due to devices' inability to recognize cues or provide personalized responses. The findings suggest that while older adults can integrate smart technologies into their lives, a lack of customization and user-friendly interfaces hinder long-term adoption and satisfaction. The studies highlight the need for technology to be further developed so they can better meet this demographic's evolving needs and call for research addressing small sample sizes and limited diversity.

CONCLUSIONS

Our findings highlight a critical need for continued research into the dynamic and reciprocal relationship between smart technologies and older adults over time. Future studies should focus on more diverse populations and extend monitoring periods to provide deeper insights into the coadaptation process. Insights gained from this review are vital for informing the development of more intuitive, user-centric smart technology solutions to better support the aging population in maintaining independence and enhancing their quality of life.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/51129.

A non-randomized feasibility study of a voice assistant for parents to support their children's mental health

Background

Mental disorders affect one in seven Australian children and although effective, evidenced based treatments exist, there is a critical shortage of mental health clinicians which has created a "treatment gap." Artificial intelligence has the potential to address the high prevalence rates of mental disorders within overburdened mental health systems.

Methods

This was a non-randomized feasibility study to evaluate the novel application of voice technology to an evidence-based parenting intervention designed to support children's mental health. We deployed an Amazon Alexa app to parents recruited from the community (N = 55) and to parents with children receiving psychological treatment (N = 4). Parents from the community used the app independently whereas parents from the clinical group used the app in conjunction with attending a six-week parenting program. The primary outcome measure, feasibility was assessed in terms of acceptability, via recruitment and retention rates, quantitative surveys and qualitative interviews.

Results

In the community group, the recruitment rate was 23.8% and the retention rate 49.1%. In the clinical group, all 6 families approached for recruitment agreed to participate and 4 out of 6 completed the trial. Parents attending the parenting program spent on average, three times longer using the app than parents from the community. Overall, parents reported that the app contained easy-to-understand information on parenting, and that they could see the potential of voice technology to learn and practice parenting skills. Parents also faced several challenges, including difficulties with installation and interactions with the app and expressed privacy concerns related to voice technology. Further, parents reported that the voices used within the app sounded monotone and robotic.

Conclusion

We offer specific recommendations that could foster a better voice assistant user experience for parents to support their children's mental health. The app is highly scalable and has the potential to addresses many of the barriers faced by parents who attempt to access traditional parenting interventions.

Voice Assistants for Mental Health Services: Designing Dialogues with Homebound Older Adults

The number of older adults who are homebound with depressive symptoms is increasing. Due to their homebound status, they have limited access to trained mental healthcare support, which leaves this support often to untrained family caregivers. To increase access, a growing interest is placed on using technology-mediated solutions, such as voice-assisted intelligent personal assistants (VIPAs), to deliver mental health services to older adults. To better understand how older adults and family caregivers intend to interact with a VIPA for mental health interventions, we conducted a participatory design study during which 6 older adults and 7 caregivers designed VIPA-human dialogues for various scenarios. Using conversation style preferences as a starting point, we present aspects of human-likeness older adults and family caregivers perceived as helpful or uncanny, specifically in the context of the delivery of mental health interventions, which helps inform potential roles VIPAs can play in mental healthcare for older adults.

Smart Speakers as an Environmental Control Unit for Severe Motor Dependence: The Case of a Young Adult with Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a disease that primarily affects males and causes a gradual loss of muscle strength. This results in a deterioration of motor skills and functional mobility, which can impact the performance of various occupations. Individuals with DMD often rely heavily on caregivers to assist with daily activities, which can lead to caregiver burden. A case study was conducted to explore and describe potential variations in the performance of a young adult diagnosed with DMD and his caregivers resulting from the integration of smart speakers (SS)-controlled Internet of Things (IoT) devices in the home environment. The study also examined the potential of SS as an environment control unit (ECU) and analysed variations in caregiver burden. Smart devices and SS were installed in the most frequently used spaces, namely, the bedroom and living room. The study employed WebQDA software to perform content analysis and Microsoft Excel to calculate the scores of the structured instruments. The implementation of the IoT-assisted environment compensated for previously physical tasks, resulting in a slight increase in independent performance and reduced demands on caregivers.

Recommendations for designing conversational companion robots with older adults through foundation models

Companion robots are aimed to mitigate loneliness and social isolation among older adults by providing social and emotional support in their everyday lives. However, older adults' expectations of conversational companionship might substantially differ from what current technologies can achieve, as well as from other age groups like young adults. Thus, it is crucial to involve older adults in the development of conversational companion robots to ensure that these devices align with their unique expectations and experiences. The recent advancement in foundation models, such as large language models, has taken a significant stride toward fulfilling those expectations, in contrast to the prior literature that relied on humans controlling robots (i.e., Wizard of Oz) or limited rule-based architectures that are not feasible to apply in the daily lives of older adults. Consequently, we conducted a participatory design (co-design) study with 28 older adults, demonstrating a companion robot using a large language model (LLM), and design scenarios that represent situations from everyday life. The thematic analysis of the discussions around these scenarios shows that older adults expect a conversational companion robot to engage in conversation actively in isolation and passively in social settings, remember previous conversations and personalize, protect privacy and provide control over learned data, give information and daily reminders, foster social skills and connections, and express empathy and emotions. Based on these findings, this article provides actionable recommendations for designing conversational companion robots for older adults with foundation models, such as LLMs and vision-language models, which can also be applied to conversational robots in other domains.

Understanding older people's voice interactions with smart voice assistants: a new modified rule-based natural language processing model with human input

The COVID-19 pandemic has expedited the integration of Smart Voice Assistants (SVA) among older people. The qualitative data derived from user commands on SVA is pivotal for elucidating the engagement patterns of older individuals with such systems. However, the sheer volume of user-generated voice interaction data presents a formidable challenge for manual coding. Compounding this issue, age-related cognitive decline and alterations in speech patterns further complicate the interpretation of older users' SVA voice interactions. Conventional dictionary-based textual analysis tools, which count word frequencies, are inadequate in capturing the evolving and communicative essence of these interactions that unfold over a series of dialogues and modify with time. To address these challenges, our study introduces a novel, modified rule-based Natural Language Processing (MR-NLP) model augmented with human input. This reproducible approach capitalizes on human-derived insights to establish a lexicon of critical keywords and to formulate rules for the iterative refinement of the NLP model. English speakers, aged 50 or older and residing alone, were enlisted to engage with Amazon Alexa™ via predefined daily routines for a minimum of 30 min daily spanning three months (N = 35, mean age = 77). We amassed time-stamped, textual data comprising participants' user commands and responses from Alexa™. Initially, a subset constituting 20% of the data (1,020 instances) underwent manual coding by human coder, predicated on keywords and commands. Separately, a rule-based Natural Language Processing (NLP) methodology was employed to code the identical subset. Discrepancies arising between human coder and the NLP model programmer were deliberated upon and reconciled to refine the rule-based NLP coding framework for the entire dataset. The modified rule-based NLP approach demonstrated notable enhancements in efficiency and scalability and reduced susceptibility to inadvertent errors in comparison to manual coding. Furthermore, human input was instrumental in augmenting the NLP model, yielding insights germane to the aging adult demographic, such as recurring speech patterns or ambiguities. By disseminating this innovative software solution to the scientific community, we endeavor to advance research and innovation in NLP model formulation, subsequently contributing to the understanding of older people's interactions with SVA and other AI-powered systems.

"Like another human being in the room": a community case study of smart speakers to reduce loneliness in the oldest-old

This community case study examined the potential benefits of smart speakers to tackle loneliness in the oldest old adults living in supported accommodation. The program was established as a collaboration between the supported accommodation provider and a technology company to explore the feasibility of smart speakers to alleviate resident loneliness. Loneliness in later life often accompanies a shrinking social circle, loss of a spouse or increased disability. People aged 85 years of age and over are increasingly likely to experience these life events, leading to an increased risk of social isolation and loneliness. Five older people, mean age 90 years of age, who resided in supported accommodation, were given a smart speaker for 8 weeks to examine their experience with the voice assistant. The experiences of the five older adults are explored as case studies, with each person interviewed both before and after receiving the smart speaker. All five valued their smart speaker, recognised its potential for tackling loneliness, and wanted to keep it. The three most lonely individuals reported that their smart speaker made them feel less lonely and isolated through two mechanisms: (i) creating a presence and (ii) having some control over their situation. Although only a small study, these experiences suggest providing smart speakers for lonely and isolated oldest-old people, could be one way to help combat loneliness in community settings.

Assimilation of socially assistive robots by older adults: an interplay of uses, constraints and outcomes

By supporting autonomy, aging in place, and wellbeing in later life, Socially Assistive Robots are expected to help humanity face the challenges posed by the rapid aging of the world's population. For the successful acceptance and assimilation of SARs by older adults, it is necessary to understand the factors affecting their Quality Evaluations Previous studies examining Human-Robot Interaction in later life indicated that three aspects shape older adults' overall QEs of robots: uses, constraints, and outcomes. However, studies were usually limited in duration, focused on acceptance rather than assimilation, and typically explored only one aspect of the interaction. In the present study, we examined uses, constraints, and outcomes simultaneously and over a long period. Nineteen community-dwelling older adults aged 75-97 were given a SAR for physical training for 6 weeks. Their experiences were documented via in-depth interviews conducted before and after the study period, short weekly telephone surveys, and reports produced by the robots. Analysis revealed two distinct groups: (A) The 'Fans' - participants who enjoyed using the SAR, attributed added value to it, and experienced a successful assimilation process; and (B) The 'Skeptics' - participants who did not like it, negatively evaluated its use, and experienced a disappointing assimilation process. Despite the vast differences between the groups, both reported more positive evaluations of SARs at the end of the study than before it began. Overall, the results indicated that the process of SARs' assimilation is not homogeneous and provided a profound understanding of the factors shaping older adults' QE of SARs following actual use. Additionally, the findings demonstrated the theoretical and practical usefulness of a holistic approach in researching older SARs users.

Factors influencing older adults' acceptance of voice assistants

Introduction

Voice assistants (VAs) have the potential to uphold and enhance the quality of life for older adults. However, the extent to which older adults accept and benefit from VAs may be relatively modest.

Methods

This study developed a comprehensive model combined with product and personal characteristics to explain the acceptance of VAs among older adults, using semi-structured interviews (Study 1) and questionnaires (Study 2).

Results

Results revealed that in terms of product characteristics, perceived usefulness and perceived enjoyment significantly affect behavior intention. Regarding personal characteristics of older adults, technological self-efficacy and dispositional resistance to change significantly affect behavior intention. However, no direct impact of perceived ease of use and perceived trust on behavior intention. Additionally, perceived enjoyment influenced both perceived ease of use and perceived usefulness.

Discussion

Results suggested the significant role of technology self-efficacy and dispositional resistance to change in predicting the acceptance of VAs among older adults. Our newly developed model offers valuable insights for tailoring VAs to this demographic during design and implementation.

Reducing Loneliness and Improving Social Support among Older Adults through Different Modalities of Personal Voice Assistants

This study examines the potential of AI-powered personal voice assistants (PVAs) in reducing loneliness and increasing social support among older adults. With the aging population rapidly expanding, innovative solutions are essential. Prior research has indicated the effectiveness of various interactive communication technologies (ICTs) in mitigating loneliness, but studies focusing on PVAs, particularly considering their modality (audio vs. video), are limited. This research aims to fill this gap by evaluating how voice assistants, in both audio and video formats, influence perceived loneliness and social support. This study examined the impact of voice assistant technology (VAT) interventions, both audio-based (A-VAT) and video-based (V-VAT), on perceived loneliness and social support among 34 older adults living alone. Over three months, participants engaged with Amazon Alexa™ PVA through daily routines for at least 30 min. Using a hybrid natural language processing framework, interactions were analyzed. The results showed reductions in loneliness (Z = -2.99, p < 0.01; pre-study loneliness mean = 1.85, SD = 0.61; post-study loneliness mean = 1.65, SD = 0.57), increases in social support post intervention (Z = -2.23, p < 0.05; pre-study social support mean = 5.44, SD = 1.05; post-study loneliness mean = 5.65, SD = 1.20), and a correlation between increased social support and loneliness reduction when the two conditions are combined (ρ = -0.39, p < 0.05). In addition, V-VAT was more effective than A-VAT in reducing loneliness (U = 85.50, p < 0.05) and increasing social support (U = 95, p < 0.05). However, no significant correlation between changes in perceived social support and changes in perceived loneliness was observed in either intervention condition (V-VAT condition: ρ = -0.24, p = 0.37; A-VAT condition: ρ = -0.46, p = 0.06). This study's findings could significantly contribute to developing targeted interventions for improving the well-being of aging adults, addressing a critical global issue.

Investigating the Integration and the Long-Term Use of Smart Speakers in Older Adults' Daily Practices: Qualitative Study

BACKGROUND

As smart speakers become more popular, there have been an increasing number of studies on how they may benefit older adults or how older adults perceive them. Despite the increasing ownership rates of smart speakers among older adults, studies that examine their integration and the long-term use in older adults' daily practices are scarce.

OBJECTIVE

This study aims to uncover the integration of smart speakers into the daily practices of older adults over the long term, contributing to an in-depth understanding of maintained technology use among this demographic.

METHODS

To achieve these objectives, the study interviewed 20 older adults who had been using smart speakers for over 6 months. These semistructured interviews enabled participants to share their insights and experiences regarding the maintained use of smart speakers in the long term.

RESULTS

We identified 4 dimensions of the long-term use of smart speakers among older adults, including functional integration, spatial integration, cognitive integration, and semantic integration. For the functional integration of smart speakers, the study reported different types of use, including entertainment, information collection, medication reminders, companionship, environment modification, and emergency calls. For the spatial integration of smart speakers, the study showed older adults' agency in defining, changing, and reshaping daily practices through the spatial organization of smart speakers. For the cognitive integration of smart speakers, the findings showed the cognitive processes involved in adapting to and incorporating smart speakers into daily habits and routines. For the semantic integration of smart speakers, the findings revealed that older adults' enjoyable user experience and strong bonds with the device contributed to their acceptance of occasional functional errors. Finally, the study proposed several suggestions for designers and developers to better design smart speakers that promote maintainable use behaviors among older adults.

CONCLUSIONS

On the basis of the findings, this study highlighted the importance of understanding how older adults use smart speakers and the practices through which they integrate them into their daily routines. The findings suggest that smart speakers can provide significant benefits for older adults, including increased convenience and improved quality of life. However, to promote maintainable use behaviors, designers and developers should consider more about the technology use contexts and the specific needs and preferences of older adults when designing these devices.

Older adults' intention to use voice assistants: Usability and emotional needs

Population aging is a global problem, and improving the well-being of older adults is an urgent issue. Voice assistants (VAs) offer hands-free voice control and friendly human-computer interaction, making them a significant solution to address the aging problem. Most extant research on VAs is fragmented, and there are relatively few studies conducted from the perspective of emotional needs. This work proposes a comprehensive research model extending the technology acceptance model (TAM) by incorporating the influencing factors subordinate to two research directions: usability and emotional needs. Usability needs include three factors: perceived convenience, security/privacy, and Internet self-efficacy. Emotional needs include humanized interaction, perceived enjoyment, and perceived companionship. A structural equation model (SEM) was used to validate the model empirically with a sample of 425 older users of VAs. The analysis results are quite consistent with the research assumptions, and the findings illustrate that companionship is the most critical factor affecting older adults' intention to adopt VA use, which demonstrates the pivotal role of VAs in meeting the emotional needs of the elderly. The most unexpected observation was seen for the relationship between perceived ease of use and behavioral intention, which was non-significant. This result confirms that when a technology is perceived as very easy to use, perceived ease of use has little to no impact on individuals' intention to use that technology. The novelty of this study lies in the investigation of older adults' behavioral intentions toward using VAs, providing valuable insights for the design and development of VAs tailored for the elderly population. Beyond the academic realm, this research serves as direct inspiration for designers, developers, and policymakers in the fields of assistive technologies and geriatric care. It offers practical insights into creating VAs that effectively address the emotional needs of older adults and enhance their quality of life. Furthermore, elderly individuals are poised to experience significant benefits from the outcomes of this study，the insights garnered from this study empower the elderly to embrace technological advancements that align with their preferences and comfort levels. This study contributes to a more comprehensive understanding of VAs and their potential to enhance the well-being of older adults, while also paving the way for future investigations in this domain. As underscored by this study's emphasis on the significance of emotional needs in technology acceptance, it encourages the adoption of more user-centered design strategies in the development of future VAs.

Coadaptation Between Smart Technologies and Older Adults Over Time: Protocol for a Scoping Review

BACKGROUND

The Internet of Things (IoT) has gained significant attention due to advancements in technology and has potential applications in meeting the needs of an aging population. Smart technologies, a subset of IoT, can support older adults in aging in place, promoting independent living and improving their quality of life. However, there is a lack of research on how older adults and smart technologies coadapt over time to maximize their benefits and sustain adoption.

OBJECTIVE

We will aim to comprehensively review and analyze the existing scientific literature pertaining to the coadaptation between smart technologies and older adults. The primary focus will be to investigate the extent and nature of this coadaptation process and explore how older adults and technology coevolve over time to enhance older adults' experience with technology.

METHODS

This scoping review will follow the methodology outlined in the Joanna Briggs Institute Reviewer's Manual and adhere to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews) guidelines for reporting. Peer-reviewed articles will be searched in databases like Ovid MEDLINE, OVID Embase, PEDro, OVID PsycINFO, EBSCO CINAHL, the Cochrane Library, Scopus, IEEE Xplore, Web of Science, and Global Index Medicus. The research team will create a data extraction form covering study characteristics, participant characteristics, underlying models and frameworks, research findings, implications for technology coadaptation, and any identified study limitations. A directed content analysis approach will be used, incorporating the Selection, Optimization, and Compensation framework and Sex- and Gender-Based Analysis Plus theoretical framework.

RESULTS

The results of this study are expected in January 2024.

CONCLUSIONS

This scoping review endeavors to present a thorough overview of the available evidence concerning how smart technologies interact with older adults over an extended period. The insights gained from this review will lay the groundwork for a research program that explores how older adults adapt to and use smart technologies throughout their lives, ultimately leading to improved user satisfaction and experience and facilitating aging in place with tailored support and user-centered design principles.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/51129.

Screen or No Screen? Lessons Learnt from a Real-World Deployment Study of Using Voice Assistants With and Without Touchscreen for Older Adults

While voice user interfaces offer increased accessibility due to hands-free and eyes-free interactions, older adults often have challenges such as constructing structured requests and perceiving how such devices operate. Voice-first user interfaces have the potential to address these challenges by enabling multimodal interactions. Standalone voice + touchscreen Voice Assistants (VAs), such as Echo Show, are specific types of devices that adopt such interfaces and are gaining popularity. However, the affordances of the additional touchscreen for older adults are unknown. Through a 40-day real-world deployment with older adults living independently, we present a within-subjects study (N = 16; age M = 82.5, SD = 7.77, min. = 70, max. = 97) to understand how a built-in touchscreen might benefit older adults during device setup, conducting self-report diary survey, and general uses. We found that while participants appreciated the visual outputs, they still preferred to respond via speech instead of touch. We identified six design implications that can inform future innovations of senior-friendly VAs for managing healthcare and improving quality of life.

How do Older Adults Set Up Voice Assistants? Lessons Learned from a Deployment Experience for Older Adults to Set Up Standalone Voice Assistants

While standalone Voice Assistants (VAs) are promising to support older adults' daily routine and wellbeing management, onboarding and setting up these devices can be challenging. Although some older adults choose to seek assistance from technicians and adult children, easy set up processes that facilitate independent use are still critical, especially for those who do not have access to external resources. We aim to understand the older adults' experience while setting up commercially available voice-only and voice-first screen-based VAs. Rooted in participants observations and semi-structured interviews, we designed a within-subject study with 10 older adults using Amazon Echo Dot and Echo Show. We identified the values of the built-in touchscreen and the instruction documents, as well as the impact of form factors, and outline important directions to support older adult independence with VAs.

The association between perioperative frailty and ability to complete a web-based geriatric assessment among older adults with cancer

INTRODUCTION

The aim of this study was to assess the degree to which patient frailty is associated with both need for assistance and time required to complete the eRFA, a web-based GA tool.

MATERIALS AND METHODS

We retrospectively identified patients who underwent surgery for cancer from 2015 to 2020, had a hospital length of stay ≥1 day, and completed the eRFA before surgery. Frailty was assessed using two methods: the MSK-FI (score 0-11) and the AGD (score 0-13). Time to complete the eRFA was automatically recorded by a web-based tool; assistance with eRFA completion was self-reported by the patient.

RESULTS

In total, 3456 patients were included (median age, 78 years). Overall, 58% of surveys were completed without assistance, 30% were completed with assistance, and 12% were completed by someone other than the patient. Younger age (median age: without assistance, 77 years; with assistance, 80 years; completed by someone else, 80 years) and lower frailty score (median AGD: 4, 6, and 8, respectively; median MSK-FI: 2, 3, and 3, respectively) were associated with independency (all p < 0.001). Higher frailty score was associated with longer time to complete the eRFA (all nonlinear association p < 0.001).

CONCLUSION

Frail patients are more likely to benefit from completion of GA to determine appropriate treatment. Given that not all cancer patients have a caregiver who can assist completing a digital questionnaire, innovative solutions are needed to help frail patients complete the eRFA without assistance.

Toward Smart Communication Components: Recent Advances in Human and AI Speaker Interaction

This study aims to investigate how humans and artificial intelligence (AI) speakers interact and to examine the interactions based on three types of communication failures: system, semantic, and effectiveness. We divided service failures using AI speaker user data provided by the top telecommunication service providers in South Korea and investigated the means to increase the continuity of product use for each type. We proved the occurrence of failure due to system error (H1) and negative results on sustainable use of the AI speaker due to not understanding the meaning (H2). It was observed that the number of users increases as the effectiveness failure rate increases. For single-person households constituted by persons in their 30s and 70s or older, the continued use of AI speakers was significant. We found that it alleviated loneliness and that human-machine interaction using AI speaker could reach a high level through a high degree of meaning transfer. We also expect AI speakers to play a positive role in single-person households, especially in cases of the elderly, which has become a tough challenge in the recent times.

Using Smart Displays to Implement an eHealth System for Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial

Background

Voice-controlled smart speakers and displays have a unique but unproven potential for delivering eHealth interventions. Many laptop- and smartphone-based interventions have been shown to improve multiple outcomes, but voice-controlled platforms have not been tested in large-scale rigorous trials. Older adults with multiple chronic health conditions, who need tools to help with their daily management, may be especially good candidates for interventions on voice-controlled devices because these patients often have physical limitations, such as tremors or vision problems, that make the use of laptops and smartphones challenging.

Objective

The aim of this study is to assess whether participants using an evidence-based intervention (ElderTree) on a smart display will experience decreased pain interference and improved quality of life and related measures in comparison with participants using ElderTree on a laptop and control participants who are given no device or access to ElderTree.

Methods

A total of 291 adults aged ≥60 years with chronic pain and ≥3 additional chronic conditions will be recruited from primary care clinics and community organizations and randomized 1:1:1 to ElderTree access on a smart display along with their usual care, ElderTree access on a touch screen laptop along with usual care, or usual care alone. All patients will be followed for 8 months. The primary outcomes are differences between groups in measures of pain interference and psychosocial quality of life. The secondary outcomes are between-group differences in system use at 8 months, physical quality of life, pain intensity, hospital readmissions, communication with medical providers, health distress, well-being, loneliness, and irritability. We will also examine mediators and moderators of the effects of ElderTree on both platforms. At baseline, 4 months, and 8 months, patients will complete written surveys comprising validated scales selected for good psychometric properties with similar populations. ElderTree use data will be collected continuously in system logs. We will use linear mixed-effects models to evaluate outcomes over time, with treatment condition and time acting as between-participant factors. Separate analyses will be conducted for each outcome.

Results

Recruitment began in August 2021 and will run through April 2023. The intervention period will end in December 2023. The findings will be disseminated via peer-reviewed publications.

Conclusions

To our knowledge, this is the first study with a large sample and long time frame to examine whether a voice-controlled smart device can perform as well as or better than a laptop in implementing a health intervention for older patients with multiple chronic health conditions. As patients with multiple conditions are such a large cohort, the implications for cost as well as patient well-being are significant. Making the best use of current and developing technologies is a critical part of this effort.

Trial Registration

ClinicalTrials.gov NCT04798196; https://clinicaltrials.gov/ct2/show/NCT04798196

International Registered Report Identifier (IRRID)

PRR1-10.2196/37522

"It's Kind of Like Code-Switching": Black Older Adults' Experiences with a Voice Assistant for Health Information Seeking

Black older adults from lower socioeconomic environments are often neglected in health technology interventions. Voice assistants have a potential to make healthcare more accessible to older adults, yet, little is known about their experiences with this type of health information seeking, especially Black older adults. Through a three-phase exploratory study, we explored health information seeking with 30 Black older adults in lower-income environments to understand how they ask health-related questions, and their perceptions of the Google Home being used for that purpose. Through our analysis, we identified the health information needs and common search topics, and discussed the communication breakdowns and types of repair performed. We contribute an understanding of cultural code-switching that has to be done by these older adults when interacting with voice assistants, and the importance of such phenomenon when designing for historically excluded groups.

A Grand Challenge for Psychology: Reducing the Age-related Digital Divide

World-wide population aging and rapid diffusion of digital technology have converged to produce an age-related digital divide in technology adoption, as seen in use of the internet and ownership of smartphones. Given the centrality of these technologies for full participation in modern society, reducing that gap is an important challenge for psychologists. We outline more and less malleable factors associated with technology adoption. We argue that interventions that can change both the aging user and the design of products will be necessary. Adaptive technology systems that incorporate artificial intelligence and extended reality represent promising new approaches to reducing the age-related digital divide.

Reducing Loneliness Among Aging Adults: The Roles of Personal Voice Assistants and Anthropomorphic Interactions

The perception of feeling lonely is an influential factor in determining quality of life among aging adults. As the US Census Bureau projects that the number of Americans ages 65 and older will double by 2060, reducing loneliness is imperative. Personal voice assistants (PVAs) such as Amazon's Echo offer the ease-of-use of voice control with a friendly, helpful artificial intelligence. This study aimed to understand the influence of a PVA on loneliness reduction among adults of advanced ages, i.e., 75+, and explore anthropomorphism as a potential underlying mechanism. Participants (N = 16) ages 75 or older used an Amazon Echo PVA for 8 weeks in an independent living facility in the Midwest. Surveys were used to collect information about perceived loneliness, and PVA interaction data was recorded and analyzed. Participants consistently exceeded the required daily interactions. As hypothesized, after the first 4 weeks of the intervention, aging adults reported significantly lower loneliness (baseline mean = 2.22, SD = 0.42; week 4 mean = 1.99, SD = 0.45, Z = −2.45, and p = 0.01). Four dominant anthropomorphic themes emerged after thematic analysis of the entire 8 weeks' PVA interaction data (Cohen's Kappa = 0.92): (1) greetings (user-initiated, friendly phrases); (2) comments/questions (user-initiated, second-person pronoun), (3) polite interactions (user-initiated, direct-name friendly requests), (4) reaction (user response to Alexa). Relational greetings predicted loneliness reductions in the first 4 weeks and baseline loneliness predicted relational greetings with the PVA during the entire 8 weeks, suggesting that anthropomorphization of PVAs may play a role in mitigating loneliness in aging adults.

To Play and To Be Played: Exploring the Design of Urban Machines for Playful Placemaking

Within the paradigm of the smart and playable city, the urban landscape and street furniture have provided a fertile platform for pragmatic and hedonic goals of urban liveability through technology augmentation. Smart street furniture has grown from being a novelty to become a common sight in metropolitan cities, co-opted for improving the efficiency of services. However, as we consider technologies that are increasingly smarter, with human-like intelligence, we navigate towards uncharted waters when discussing the consequences of their integration with the urban landscape. The implications of a new genre of street furniture embedded with artificial intelligence, where the machine has autonomy and is an active player itself, are yet to be fully understood. In this article, we analyse the evolving design of public benches along the axes of smartness and disruption to understand their qualities as playful, urban machines in public spaces. We present a concept-driven speculative design case study, as an exploration of a smart, sensing, and disruptive urban machine for playful placemaking. With the emergence of artificial intelligence, we expand on the potential of urban machines to partake an increasingly active role as co-creators of play and playful placemaking in the cities of tomorrow.

Voice-Activated Virtual Home Assistant Use and Social Isolation and Loneliness Among Older Adults: Mini Review

A lack of social connectedness is common among older adults due to living alone, loss of loved ones, reduced mobility, and, more recently, social distancing created by the global Covid-19 pandemic. Older adults are vulnerable to social isolation and loneliness, which pose significant health risks comparable to those of smoking, obesity, physical inactivity, and high blood pressure. A lack of social connectedness is also correlated with higher mortality rates even when controlling for other factors such as age and comorbid conditions. The purpose of this mini review was to explore the emerging concepts of older adults' use of commercially available artificial intelligent virtual home assistants (VHAs; e.g., Amazon Echo, Google Nest), and its relationship to social isolation and loneliness. A secondary purpose was to identify potential areas for further research. Results suggest that VHAs are perceived by many older adult users as “companions” and improve social connectedness and reduce loneliness. Available studies are exploratory and descriptive and have limited generalizability due to small sample sizes, however, similar results were reported across several studies conducted in differing countries. Privacy concerns and other ethical issues and costs associated with VHA use were identified as potential risks to older adults' VHA adoption and use. Older adults who were using VHAs expressed the need and desire for more structured training on device use. Future research with stronger methods, including prospective, longitudinal, and randomized study designs are needed. Public education, industry standards, and regulatory oversight is required to mitigate potential risks associated with VHA use.