Proceedings of the 2025 6th International Conference on Big Data and Social Sciences (ICBDSS 2025)

Older Adults’ Acceptance of Emotionally Supportive Artificial Intelligence: An Empirical Study of Current Status and Influencing Factors

Authors
Yushan Mei1, *
1The experimental high school attached to Beijing Normal University, Beijing, China
*Corresponding author. Email: combellamei2008@163.com
Corresponding Author
Yushan Mei
Available Online 26 February 2026.
DOI
10.2991/978-94-6239-598-5_25How to use a DOI?
Keywords
emotionally supportive AI; technology acceptance; older adults; perceived usefulness; social support
Abstract

As China’s population rapidly ages, emotionally supportive artificial intelligence (AI) technologies have emerged as a potential means to alleviate loneliness and enhance the well-being of older adults. However, factors influencing their acceptance remain underexplored. This study investigates the current status and multidimensional determinants of elderly individuals’ willingness to adopt emotionally supportive AI, using the Technology Acceptance Model (TAM) as the theoretical foundation. A structured questionnaire comprising 34 items was administered via “Questionnaire Star” to respondents aged 50–80 across several Chinese provinces, yielding 221 valid responses. Descriptive statistics and multiple linear regression analyses were conducted to examine individual, family, social, and technological influences. Results revealed that perceived usefulness—particularly improvements in well-being, reductions in loneliness, and enhancements in life quality—was the strongest positive predictor of willingness to use AI. Conversely, perceived risks related to privacy, data misuse, and system reliability significantly inhibited acceptance. Unexpectedly, perceived ease of use demonstrated a negative relationship with willingness, suggesting that over-simplified interfaces may undermine older adults’ sense of competence and autonomy. Social and environmental factors such as media support, community infrastructure, and organizational backing positively influenced willingness, while excessive family or community encouragement had adverse effects. Overall, the findings highlight a “benefit-driven, risk-inhibited, and autonomy-sensitive” acceptance mechanism among older adults. The study extends the TAM framework by revealing the complex role of social support and psychological autonomy in AI adoption. Practical implications include the need for emotionally supportive AI systems that balance usability with dignity, strengthen risk management, and foster environments that respect elderly users’ autonomy while promoting voluntary engagement.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 6th International Conference on Big Data and Social Sciences (ICBDSS 2025)
Series
Advances in Computer Science Research
Publication Date
26 February 2026
ISBN
978-94-6239-598-5
ISSN
2352-538X
DOI
10.2991/978-94-6239-598-5_25How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Yushan Mei
PY  - 2026
DA  - 2026/02/26
TI  - Older Adults’ Acceptance of Emotionally Supportive Artificial Intelligence: An Empirical Study of Current Status and Influencing Factors
BT  - Proceedings of the 2025 6th  International Conference on Big Data and Social Sciences (ICBDSS 2025)
PB  - Atlantis Press
SP  - 248
EP  - 262
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-598-5_25
DO  - 10.2991/978-94-6239-598-5_25
ID  - Mei2026
ER  -