Older Adults’ Interaction With Intelligent Virtual Assistants: The Role of Information Modality and Feedback

Abstract

Intelligent virtual assistants (IVAs) can help older adults with information queries. Examining older adults’ preferences for IVAs’ information presentation can help improve user experience and older adults’ acceptance of IVAs. This study investigated the effects of information modality and feedback on older adults’ social presence, attitudinal outcomes (i.e., perceived enjoyment and satisfaction), and acceptance (i.e., perceived ease of use, perceived usefulness, and behavioral intention to use). A total of 102 subjects were recruited to participate in two experiments. Results show that the visual-auditory bimodality is superior to single visual modality and single auditory modality for older adults based on the perceptions of social presence, attitudinal outcomes, and acceptance. Older adults perceived greater social presence, perceived enjoyment, satisfaction, and acceptance with text feedback than without in IVAs. Social-oriented voice feedback can improve older adults’ perceptions of social presence, enjoyment, satisfaction, and acceptance than task-oriented voice feedback. This study provides practical implications in the design of IVAs’ information presentation targeted at older adults.

Disclosure statement

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

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant Number 71901033] and Beijing Natural Science Foundation [Grant Number 9204029].

Notes on contributors

Na Liu

Na Liu is an associate professor in the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. Her research interests include human factors and ergonomics, and human-computer interaction.

Quanlin Pu

Quanlin Pu is a master student in the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. Her research interests include human-computer interaction and user experience.

Yan Shi

Yan Shi is a master student in the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. His research interests include human-computer interaction and user experience.

Shengtai Zhang

Shengtai Zhang is a professor in the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. His research interests include human resource management and knowledge management.

Luyi Qiu

Luyi Qiu is a lecturer in the School of Economics and Management of Beijing University of Posts and Telecommunications, Beijing, China. His research interests include public policy, resource and environment management.