Human-Centred Perspectives on Artificial Intelligence in the Care of Older Adults: A Q Methodology Study of Caregivers’ Perceptions

This study used Q methodology to explore and categorise caregivers' subjective perceptions of artificial intelligence (AI)-powered 'virtual human' (AVH) devices in caring for older adults. We derived 123 initial statements from literature and focus groups and narrowed them to 34 statements as the final Q sample. Seventeen caregivers, nurses, and social workers completed the Q-sorting procedure. Using principal component analysis and Varimax rotation in Ken-Q, we identified three perception types: Active Acceptors, who emphasise the devices' practical utility in patient communication; Improvement Seekers, who conditionally accept the technology while seeking greater accuracy and effectiveness; and Emotional Support Seekers, who view the device as a tool for emotional relief and psychological support. These findings suggest that technology acceptance in caregiving extends beyond functional utility. It also involves trust, affective experience, and interpersonal interaction. This study integrates multiple frameworks, including the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), Science and Technology Studies (STS), and Human-Machine Communication (HMC) theory, to provide a multifaceted understanding of caregivers' acceptance of AI technology. The results offer valuable implications for designing user-centred AI care devices and enhanced emotional and communicative functions.

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Publication Details

Journal
Behavioral Sciences
Published
2025-11-12
DOI
https://doi.org/10.3390/bs15111541
Primary Topic
Technology Use by Older Adults
Type
article
Field-Weighted Citation Impact
0.00
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article

Human-Centred Perspectives on Artificial Intelligence in the Care of Older Adults: A Q Methodology Study of Caregivers’ Perceptions

Song Yi Lee, Seung-Uoo Shin, Yejee Jeong, Ji Yeong Kim et al.
Behavioral Sciences
Technology Use by Older Adults
article

Human-Centred Perspectives on Artificial Intelligence in the Care of Older Adults: A Q Methodology Study of Caregivers’ Perceptions

Song Yi Lee, Seung-Uoo Shin, Yejee Jeong, Ji Yeong Kim, Kyoung Yeon Moon
article en

Abstract

This study used Q methodology to explore and categorise caregivers' subjective perceptions of artificial intelligence (AI)-powered 'virtual human' (AVH) devices in caring for older adults. We derived 123 initial statements from literature and focus groups and narrowed them to 34 statements as the final Q sample. Seventeen caregivers, nurses, and social workers completed the Q-sorting procedure. Using principal component analysis and Varimax rotation in Ken-Q, we identified three perception types: Active Acceptors, who emphasise the devices' practical utility in patient communication; Improvement Seekers, who conditionally accept the technology while seeking greater accuracy and effectiveness; and Emotional Support Seekers, who view the device as a tool for emotional relief and psychological support. These findings suggest that technology acceptance in caregiving extends beyond functional utility. It also involves trust, affective experience, and interpersonal interaction. This study integrates multiple frameworks, including the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), Science and Technology Studies (STS), and Human-Machine Communication (HMC) theory, to provide a multifaceted understanding of caregivers' acceptance of AI technology. The results offer valuable implications for designing user-centred AI care devices and enhanced emotional and communicative functions.

Behavioral SciencesVol. 15(11)
Dongguk University (KR)
Openalex Percentile: Top 43%
Technology Use by Older Adults
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