TY - JOUR
T1 - How Older Adults with Chronic Conditions Perceive Artificial Intelligence (AI)-Based Virtual Humans
T2 - A Q Methodology Approach
AU - Jeong, Youn Gill
AU - Shin, Seo Jung
AU - Lee, Song Yi
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/7
Y1 - 2025/7
N2 - Background/Objectives: This study examines the subjective perceptions of older adults with mild chronic conditions regarding an artificial intelligence (AI)-based caregiving device, referred to as an “AI Human”, by identifying and categorising their viewpoints through Q methodology. Methods: We conducted the study in February 2025 at two adult welfare centres in Buyeo, South Korea. Thirteen older adults used the AI Human device with support for at least 15 days. We initially generated 152 opinion statements through a literature review, focus group interviews, and AI-assisted methods and refined them to a Q sample of 34 statements. Participants completed Q sorts, and we used Ken-Q Analysis software (version 2.0.1) to analyse the data, applying principal component analysis and Varimax rotation. Results: Four distinct perception types emerged: (1) emotionally engaged users prioritise reminiscence and emotional interaction; (2) present-oriented conversationalists prefer real-time, everyday dialogue; (3) usage-burdened users are interested in the device but experience usage difficulty; and (4) function-oriented users value health and caregiving functions. Conclusions: The acceptance of AI caregiving devices among older adults varies based on their emotional needs, conversation preferences, technical accessibility, and perceived usefulness. This study provides theoretical and practical insights for developing personalised, elder-friendly AI systems that support ageing and promote emotional well-being.
AB - Background/Objectives: This study examines the subjective perceptions of older adults with mild chronic conditions regarding an artificial intelligence (AI)-based caregiving device, referred to as an “AI Human”, by identifying and categorising their viewpoints through Q methodology. Methods: We conducted the study in February 2025 at two adult welfare centres in Buyeo, South Korea. Thirteen older adults used the AI Human device with support for at least 15 days. We initially generated 152 opinion statements through a literature review, focus group interviews, and AI-assisted methods and refined them to a Q sample of 34 statements. Participants completed Q sorts, and we used Ken-Q Analysis software (version 2.0.1) to analyse the data, applying principal component analysis and Varimax rotation. Results: Four distinct perception types emerged: (1) emotionally engaged users prioritise reminiscence and emotional interaction; (2) present-oriented conversationalists prefer real-time, everyday dialogue; (3) usage-burdened users are interested in the device but experience usage difficulty; and (4) function-oriented users value health and caregiving functions. Conclusions: The acceptance of AI caregiving devices among older adults varies based on their emotional needs, conversation preferences, technical accessibility, and perceived usefulness. This study provides theoretical and practical insights for developing personalised, elder-friendly AI systems that support ageing and promote emotional well-being.
KW - artificial intelligence
KW - caregiving technology
KW - continuity theory
KW - older adults
KW - Q methodology
KW - technology acceptance
KW - virtual human
UR - https://www.scopus.com/pages/publications/105010237241
U2 - 10.3390/healthcare13131525
DO - 10.3390/healthcare13131525
M3 - Article
AN - SCOPUS:105010237241
SN - 2227-9032
VL - 13
JO - Healthcare (Switzerland)
JF - Healthcare (Switzerland)
IS - 13
M1 - 1525
ER -