Smart Technology-Supported Independent Living for Older Adults: An Editorial

Smart technology may provide endless opportunities for older adults. While population is aging rapidly, smart technology is also evolving fast. Older adults need to keep up with new technologies, particularly those empowered by dig data and artificial intelligence. Using smart technologies or new functions, older adults usually faced usability problems and acceptance problems. Therefore, this special issue aims to investigate older adults’ needs of smart technology for independent living, to learn from practices of implementing smart technology, and to identify directions toward the humanized interaction for older adults. This special issue included 15 articles after peer review. They covered smartphones, smart watches, smart bracelets, virtual reality (VR), smart speakers, smart homes and integrated services.

1. Usage and acceptance of smart devices

Usability problems and acceptance barriers of smart devices differ across interaction paradigms such as touch-based interaction, voice-based interaction, text-based interaction, and full-body interaction. First, a common usability problem of touch-based interaction is that older adults usually get lost in limited screens. Among common navigational interface elements (e.g., menu list, grid, gallery, and cards), Li and Luximon (2022) investigated the influence of interface metaphors (i.e., 3 D cards or 2 D lists), task complexity, content similarity, and three user characteristics on older adults’ navigation performance and subjective evaluations. The results of the experiment indicated the advantages of 2 D lists in terms of cognitive load for older adults with lower perceptual speed. Second, voice-based interaction and text-based interaction are seen in smart speakers and virtual voice assistants in smart handheld devices and wearables. Voice-based interaction requires users to remember instructions and conversations, so text-based interaction was proposed to solve this problem but also requires additional visual attention. Thus, it is not surprising that there is on-going debate about whether smart speakers should have displays. Displays could provide additional text-based feedback in addition to voice-based feedback, but the role of the bi-modal feedback on task performance and attitude of older adults is not conclusive. Therefore, Liu et al. (2022) conducted two experiments among 102 older adults to investigate the influence of information modality and feedback of voice assistants. The results of the experiments indicated the advantages of visual-auditory bimodality for older adults in terms of social presence, perceived enjoyment, satisfaction, and acceptance. Werner et al. (2022) conducted four focus groups among 18 older adults. They distinguished between users and non-users contributes to insights into their perceptions and usage intentions of smart speech systems. Third, interaction with VR through full-body gestures is a possible way to help older adults keep physically active. To examine older adults’ acceptance of VR exergames, Xu et al. (2022) recruited 51 older adults to wear Oculus Quest 1 and to use a remote controller to play three VR exergames about 12 min. After that, older adults filled in questionnaires. The results of the survey indicated an exergame acceptance model for older adults.

2. Smart services for mental well-being

Services such as social media and emotional care services integrated on smart devices might contribute to participation of older adults in society. Previous studies mainly examined smart services from perspectives of three stakeholders including users, service providers, and platform providers. First, older adults’ relatively low self-efficacy is an obstacle of their use of social media on mobile devices. Therefore, Chen and Gao (2022) conducted a survey among 276 older users of mobile social media to investigate the relationships among self-efficacy, informational use, loneliness, self-esteem, and emotional happiness. The results stressed the importance of social media self-efficacy on older adults’ mental health. Second, service providers usually consider how to manage systems to meet older adults’ needs. For example, emotional care might help older adults who suffer from social isolation and depression, so Wen and Chen (2022) examined how the emotional care services should be delivered to older adults more efficiently and more effectively, managing service requests from multiple older adults in communities. Another study investigated how in-flight service attributes influenced customers’ perceptions and usage intention among various age groups through Kansei engineering (Cai et al., 2022). Third, platform providers may examine advanced algorithms for more natural interaction of older adults. An et al. (2022) proposed the ALBERT Based Text Extraction Network to automatically organize life stories in order to solve problems of redundancy and disorder. The results would caregivers better understand older adults’ life stories and better meet their psychological needs.

3. Smart services for physical health

Older adults’ acceptance of smart health care services was examined in different duration of use. First, cross-section studies revealed technology acceptance models of older adults without or with disabilities. Older adults’ adoption of mobile health services was investigated through interviews and questionnaire survey, and the results identified a pine tree model (Pan & Dong, 2022). Similarly, Peng et al. (2022) examined technology acceptance model of telecare based on results of the questionnaire survey. They stressed the importance of governmental regulations in promoting telecare acceptance. Among various acceptance factors, Schomakers and Ziefle (2022) examined how older adults weighed between privacy barriers and security benefits for emergency detection technologies for aging in place. Apart from normal aging, for older adults with functional disabilities who faced insufficient hospital resources, they need rehabilitation training at home and in community. In this situation, Sun et al. (2022) reviewed technologies for home-based and community-based stroke rehabilitation and those for therapists’ remote participation. However, advantages of assistive technologies were not necessarily enjoyed by older adults particularly when they resisted certain technology even before usage. Thus, Offermann (2022) examined how older adults perceived the benefits, barriers of assistive technologies and what are the influential factors. A survey was conducted among 1123 respondents from five countries. The results indicated that the perception of care is related with technology acceptance, even more with perception of barriers, and most strongly with perception of benefits. Second, longitudinal studies examined how the role of acceptance factors change with time. Kavčič et al. (2022) tested caregivers’ and carereceivers’ acceptance and usage of three commercial e-care services during eight weeks. They used features through equipment installed in their homes and/or on their mobile phones, and the results revealed a complex mix of interrelated factors that influenced older adults’ technology acceptance and future use of home-based e-care systems. Ma et al. (2022) recruited 20 older adults to use smart watches or smart bracelets at home for a period of over four weeks. Older adults’ ratings on experiential qualities, affordances, values and adoption were collected through weekly meetings and compared to their original ratings before actual usage. For example, as usage time increased, the importance of call notifications and message notifications increased. Influencing factors of older adults’ adoption intention and use frequency differ as time increases. The regression models at different phases indicated that different from the persisting role of perceived utilitarian value, older adults’ perceived hedonic value only influenced their adoption intention before actual use.

In sum, the 15 articles addressed usability problems and acceptance barriers of smart devices and integrated services for older adults. Usability and acceptance are often intertwined in these studies, and influencing factors of older adults’ acceptance of smart technologies are not conclusive. One possible reason is that older adults’ technology acceptance may depend on needs and characteristics of older adults, the design and implement of smart devices and services, and the facilitating systems managed by various stakeholders such as service providers and governments. Given that more studies in this special issue mainly considered the older users, it would be interesting to examine the interplay between stakeholders in more longitudinal studies. Collaboration from stakeholders is needed to further improve older adults’ quality of life through smart technologies.

Acknowledgement

We really appreciate Professors Gavriel Salvendy and Constantine Stephanidis for their valuable suggestions and prompt help to prepare and organize the special issue. Besides, we are grateful for authors and reviewers for their contribution to this special issue. Furthermore, the author would like to acknowledge the support from National Natural Science Foundation of China (72171030).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Social Science Fund of China.

Notes on contributors

Jia Zhou

Jia Zhou is a Professor at the School of Management Science and Real Estate at Chongqing University. She is also the co-chair of the International Conference on Human Aspects of IT for the Aged Population (ITAP) since 2015. Her research focuses on IT products and services for older adults.