Archive Issue
International Interdisciplinary Scientific Journal "Expert"
Volume 3 (2026)
Language of the original article: English
ABSTRACT. The The integration of artificial intelligence (AI) in the field of social services for adults and older people has established itself as one of the dynamic and interdisciplinary areas of technological development over the last decade. This article presents a systematic and in-depth theoretical analysis of the complex psychosocial mechanisms that determine the readiness and perception of intelligent technologies—including social assistance robots, virtual agents, and adaptive interfaces—by the aging population. The study focuses on a critical review of three key psychological constructs that mediate consumer behavior: trust, perceived control, and perceived usefulness. The theoretical framework of the analysis is constructed through a synthesis of established models of technology acceptance, such as the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM), expanded through the gerontology-specific Almere Model. Special attention is paid to psychological theories of trust, viewed as a multidimensional construct involving cognitive and affective components such as competence, reliability, and predictability of the system. The article explores the role of perceived control and autonomy as protective factors against technological anxiety and feelings of depersonalization in the human-robot interaction process. The analytical focus covers the dynamic interaction between cognitive processes and emotional experiences that modulate the long-term engagement of adult users with AI platforms. By systematizing the latest research published between 2020 and 2025, existing theoretical deficits and conceptual gaps in understanding the specific needs of older adults are identified. In conclusion, promising directions for future research are outlined and practical recommendations are made for the design of ethical, anthropocentric, and psychologically validated technological solutions aimed at improving the quality of life and social inclusion of older adults in today's digital society.
Keywords: artificial intelligence, social robots, older adults, trust, perceived control, perceived usefulness, technological acceptance, psychosocial mechanisms.
1. Martínez-Roig, R. (2024). Robots sociales, música y movimiento: Percepciones de las personas mayores sobre el robot Pepper para su formación [Social robots, music, and movement: Older adults’ perceptions of the Pepper robot for training]. Pixel-Bit. Revista de Medios y Educación, 70, 25–41. https://doi.org/10.12795/pixelbit.104621 [in Spanish]
2. Giorgi, I., Minutolo, A., Tirotto, F., et al. (2025). I am robot, your health adviser for older adults: Do you trust my advice? International Journal of Social Robotics, 17, 883–902. https://doi.org/10.1007/s12369-023-01019-8
3. Kadylak, T., Bayles, M. A., & Rogers, W. A. (2023). Are Friendly Robots Trusted More? An Analysis of Robot Sociability and Trust. Robotics, 12(6), 162. https://doi.org/10.3390/robotics12060162
4. Cortellessa, G., De Benedictis, R., Fracasso, F., Orlandini, A., Umbrico, A. & Cesta, A. (2021). AI and robotics to help older adults: Revisiting projects in search of lessons learned. Paladyn, Journal of Behavioral Robotics, 12(1), 356-378. https://doi.org/10.1515/pjbr-2021-0025
5. Pinto-Bernal, M., Boels, K., Belpame, T., et al. (2025). Fostering social connection and emotional engagement to mitigate social isolation in care homes using empathetic human-robot conversation. Research Square (Preprint, Version 1, June 12). https://doi.org/10.21203/rs.3.rs-6811088/v1
6. Naseer, F., Khan, M. N., Tahir, M., Addas, A., & Kashif, H. (2025). Enhancing elderly care with socially assistive robots: A holistic framework for mobility, interaction, and well-being. IEEE Access, 13, 82698–82717. https://doi.org/10.1109/ACCESS.2025.3567331
7. Felber, N. A., Lipworth, W., Tian, Y. J., et al. (2024). Informing existing technology acceptance models: A qualitative study with older persons and caregivers. European Journal of Ageing, 21, Article 12. https://doi.org/10.1007/s10433-024-00801-5
8. Giorgi, I., Rajapakse, S., Palomino, M., & Masala, G. L. (2025). Older adults’ perceptions of robots with differing intelligence in social multi-robot interactions. ACM Transactions on Human-Robot Interaction, 15(1), Article 25, 1–28. https://doi.org/10.1145/3769854
9. Dosso, J. A., Bandari, E., Malhotra, A., et al. (2022). User perspectives on emotionally aligned social robots for older adults and persons living with dementia. Journal of Rehabilitation and Assistive Technologies Engineering, 9. https://doi.org/10.1177/20556683221108364
10. Sadler, J. R., Khan, A., Lwin, M., & Mubin, O. (2024). Social Robots for Meaningful Seated Activities: Acceptance & Use by Older Adults. Healthcare, 12(13), 1334. https://doi.org/10.3390/healthcare12131334
11. He, Q., He, Y., Liu, Q., & Ma, C. (2023). Acceptance of social assistant robots for the older adults living in the community in China. Geriatric Nursing, 52, 191–198. https://doi.org/10.1016/j.gerinurse.2023.06.006
12. Zhang, L. (2025). Breaking Barriers: A Dual-Factor Model Unraveling Ageism in Socially Assistive Robot Adoption among Older Chinese Adults. International Journal of Human–Computer Interaction, 41(2), 1397–1413. https://doi.org/10.1080/10447318.2024.2314352
13. Kadylak, T., Bayles, M., & Rogers, W. (2021). Exploring social and assistive domestic robots for older adults: Robot sociability, trust, and acceptance. Innovation in Aging, 5(Supplement_1), 300. https://doi.org/10.1093/geroni/igab046.1170
14. Chen, K. (2025). Does ascribing robots with mental capacities increase or decrease trust in middle-aged and older adults? International Journal of Social Robotics, 17, 1617–1631. https://doi.org/10.1007/s12369-025-01307-5
15. Luo, C., Yuan, R., Mao, B., Liu, Q., Wang, W., & He, Y. (2024). Technology Acceptance of Socially Assistive Robots Among Older Adults and the Factors Influencing It: A Meta-Analysis. Journal of Applied Gerontology, 43(2), 115-128. https://doi.org/10.1177/07334648231202669
16. He, Y., Li, P., Luo, C., Yuan, R., Yang, C., & Liu, Q. (2025). Exploring the acceptance of socially assistive robots by older adults in care institutions and its influencing factors: Based on the Almere model. Journal of Applied Gerontology. https://doi.org/10.1177/07334648251399946
17. Fracasso, F., Buchweitz, L., Theil, A., et al. (2022). Social robots acceptance and marketability in Italy and Germany: A cross-national study focusing on assisted living for older adults. International Journal of Social Robotics, 14, 1463–1480. https://doi.org/10.1007/s12369-022-00884-z
18. Amin, M. A. S., Johnson, V. L., Prybutok, V., & Koh, C. E. (2024). An investigation into factors affecting the willingness to disclose personal health information when using AI-enabled caregiver robots. Industrial Management & Data Systems, 124(4), 1677–1699. https://doi.org/10.1108/IMDS-09-2023-0608
19. Seaborn, K., Sekiguchi, T., Tokunaga, S., et al. (2023). Voice over body? Older adults’ reactions to robot and voice assistant facilitators of group conversation. International Journal of Social Robotics, 15, 143–163. https://doi.org/10.1007/s12369-022-00925-7
20. Hebesberger, D., Koertner, T., Gisinger, C., et al. (2017). A long-term autonomous robot at a care hospital: A mixed methods study on social acceptance and experiences of staff and older adults. International Journal of Social Robotics, 9, 417–429. https://doi.org/10.1007/s12369-016-0391-6
21. Giorgi, I., et al. (2022). Friendly but faulty: A pilot study on the perceived trust of older adults in a social robot. IEEE Access, 10, 92084–92096. https://doi.org/10.1109/ACCESS.2022.3202942
22. Whelan, S., & Casey, D. (2021). Examining social robot acceptability for older adults and people with dementia. In Collaborative robots. IntechOpen. https://doi.org/10.5772/intechopen.98365
23. Vekova, L., Uzhikanova-Kovacheva, E., Georgiev, P., & Vazova, T. (2026). Information systems and technologies with the implementation of artificial intelligence as an interdisciplinary approach for the development of digital competencies and training of social workers. ARPHA Proceedings, 10, 545–557. https://doi.org/10.3897/ap.10.e0545
ABSTRACT. The The integration of artificial intelligence (AI) in the field of social services for adults and older people has established itself as one of the dynamic and interdisciplinary areas of technological development over the last decade. This article presents a systematic and in-depth theoretical analysis of the complex psychosocial mechanisms that determine the readiness and perception of intelligent technologies—including social assistance robots, virtual agents, and adaptive interfaces—by the aging population. The study focuses on a critical review of three key psychological constructs that mediate consumer behavior: trust, perceived control, and perceived usefulness. The theoretical framework of the analysis is constructed through a synthesis of established models of technology acceptance, such as the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM), expanded through the gerontology-specific Almere Model. Special attention is paid to psychological theories of trust, viewed as a multidimensional construct involving cognitive and affective components such as competence, reliability, and predictability of the system. The article explores the role of perceived control and autonomy as protective factors against technological anxiety and feelings of depersonalization in the human-robot interaction process. The analytical focus covers the dynamic interaction between cognitive processes and emotional experiences that modulate the long-term engagement of adult users with AI platforms. By systematizing the latest research published between 2020 and 2025, existing theoretical deficits and conceptual gaps in understanding the specific needs of older adults are identified. In conclusion, promising directions for future research are outlined and practical recommendations are made for the design of ethical, anthropocentric, and psychologically validated technological solutions aimed at improving the quality of life and social inclusion of older adults in today's digital society.
Keywords: artificial intelligence, social robots, older adults, trust, perceived control, perceived usefulness, technological acceptance, psychosocial mechanisms.
References
1. Martínez-Roig, R. (2024). Robots sociales, música y movimiento: Percepciones de las personas mayores sobre el robot Pepper para su formación [Social robots, music, and movement: Older adults’ perceptions of the Pepper robot for training]. Pixel-Bit. Revista de Medios y Educación, 70, 25–41. https://doi.org/10.12795/pixelbit.104621 [in Spanish]
2. Giorgi, I., Minutolo, A., Tirotto, F., et al. (2025). I am robot, your health adviser for older adults: Do you trust my advice? International Journal of Social Robotics, 17, 883–902. https://doi.org/10.1007/s12369-023-01019-8
3. Kadylak, T., Bayles, M. A., & Rogers, W. A. (2023). Are Friendly Robots Trusted More? An Analysis of Robot Sociability and Trust. Robotics, 12(6), 162. https://doi.org/10.3390/robotics12060162
4. Cortellessa, G., De Benedictis, R., Fracasso, F., Orlandini, A., Umbrico, A. & Cesta, A. (2021). AI and robotics to help older adults: Revisiting projects in search of lessons learned. Paladyn, Journal of Behavioral Robotics, 12(1), 356-378. https://doi.org/10.1515/pjbr-2021-0025
5. Pinto-Bernal, M., Boels, K., Belpame, T., et al. (2025). Fostering social connection and emotional engagement to mitigate social isolation in care homes using empathetic human-robot conversation. Research Square (Preprint, Version 1, June 12). https://doi.org/10.21203/rs.3.rs-6811088/v1
6. Naseer, F., Khan, M. N., Tahir, M., Addas, A., & Kashif, H. (2025). Enhancing elderly care with socially assistive robots: A holistic framework for mobility, interaction, and well-being. IEEE Access, 13, 82698–82717. https://doi.org/10.1109/ACCESS.2025.3567331
7. Felber, N. A., Lipworth, W., Tian, Y. J., et al. (2024). Informing existing technology acceptance models: A qualitative study with older persons and caregivers. European Journal of Ageing, 21, Article 12. https://doi.org/10.1007/s10433-024-00801-5
8. Giorgi, I., Rajapakse, S., Palomino, M., & Masala, G. L. (2025). Older adults’ perceptions of robots with differing intelligence in social multi-robot interactions. ACM Transactions on Human-Robot Interaction, 15(1), Article 25, 1–28. https://doi.org/10.1145/3769854
9. Dosso, J. A., Bandari, E., Malhotra, A., et al. (2022). User perspectives on emotionally aligned social robots for older adults and persons living with dementia. Journal of Rehabilitation and Assistive Technologies Engineering, 9. https://doi.org/10.1177/20556683221108364
10. Sadler, J. R., Khan, A., Lwin, M., & Mubin, O. (2024). Social Robots for Meaningful Seated Activities: Acceptance & Use by Older Adults. Healthcare, 12(13), 1334. https://doi.org/10.3390/healthcare12131334
11. He, Q., He, Y., Liu, Q., & Ma, C. (2023). Acceptance of social assistant robots for the older adults living in the community in China. Geriatric Nursing, 52, 191–198. https://doi.org/10.1016/j.gerinurse.2023.06.006
12. Zhang, L. (2025). Breaking Barriers: A Dual-Factor Model Unraveling Ageism in Socially Assistive Robot Adoption among Older Chinese Adults. International Journal of Human–Computer Interaction, 41(2), 1397–1413. https://doi.org/10.1080/10447318.2024.2314352
13. Kadylak, T., Bayles, M., & Rogers, W. (2021). Exploring social and assistive domestic robots for older adults: Robot sociability, trust, and acceptance. Innovation in Aging, 5(Supplement_1), 300. https://doi.org/10.1093/geroni/igab046.1170
14. Chen, K. (2025). Does ascribing robots with mental capacities increase or decrease trust in middle-aged and older adults? International Journal of Social Robotics, 17, 1617–1631. https://doi.org/10.1007/s12369-025-01307-5
15. Luo, C., Yuan, R., Mao, B., Liu, Q., Wang, W., & He, Y. (2024). Technology Acceptance of Socially Assistive Robots Among Older Adults and the Factors Influencing It: A Meta-Analysis. Journal of Applied Gerontology, 43(2), 115-128. https://doi.org/10.1177/07334648231202669
16. He, Y., Li, P., Luo, C., Yuan, R., Yang, C., & Liu, Q. (2025). Exploring the acceptance of socially assistive robots by older adults in care institutions and its influencing factors: Based on the Almere model. Journal of Applied Gerontology. https://doi.org/10.1177/07334648251399946
17. Fracasso, F., Buchweitz, L., Theil, A., et al. (2022). Social robots acceptance and marketability in Italy and Germany: A cross-national study focusing on assisted living for older adults. International Journal of Social Robotics, 14, 1463–1480. https://doi.org/10.1007/s12369-022-00884-z
18. Amin, M. A. S., Johnson, V. L., Prybutok, V., & Koh, C. E. (2024). An investigation into factors affecting the willingness to disclose personal health information when using AI-enabled caregiver robots. Industrial Management & Data Systems, 124(4), 1677–1699. https://doi.org/10.1108/IMDS-09-2023-0608
19. Seaborn, K., Sekiguchi, T., Tokunaga, S., et al. (2023). Voice over body? Older adults’ reactions to robot and voice assistant facilitators of group conversation. International Journal of Social Robotics, 15, 143–163. https://doi.org/10.1007/s12369-022-00925-7
20. Hebesberger, D., Koertner, T., Gisinger, C., et al. (2017). A long-term autonomous robot at a care hospital: A mixed methods study on social acceptance and experiences of staff and older adults. International Journal of Social Robotics, 9, 417–429. https://doi.org/10.1007/s12369-016-0391-6
21. Giorgi, I., et al. (2022). Friendly but faulty: A pilot study on the perceived trust of older adults in a social robot. IEEE Access, 10, 92084–92096. https://doi.org/10.1109/ACCESS.2022.3202942
22. Whelan, S., & Casey, D. (2021). Examining social robot acceptability for older adults and people with dementia. In Collaborative robots. IntechOpen. https://doi.org/10.5772/intechopen.98365
23. Vekova, L., Uzhikanova-Kovacheva, E., Georgiev, P., & Vazova, T. (2026). Information systems and technologies with the implementation of artificial intelligence as an interdisciplinary approach for the development of digital competencies and training of social workers. ARPHA Proceedings, 10, 545–557. https://doi.org/10.3897/ap.10.e0545
© 2026 The Author(s)
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0).
Vazova, T. (2026). PSYCHOSOCIAL MECHANISMS OF AI ACCEPTANCE IN SOCIAL SERVICES FOR ADULTS AND OLDER PEOPLE: TRUST, CONTROL, AND PERCEIVED USEFULNESS. International Interdisciplinary Scientific Journal “Expert”, 3, Article 1, 1–10. https://doi.org/10.62034/2815-5300/2026-v3-001
Citation Format APA
Vazova, T. (2026). PSYCHOSOCIAL MECHANISMS OF AI ACCEPTANCE IN SOCIAL SERVICES FOR ADULTS AND OLDER PEOPLE: TRUST, CONTROL, AND PERCEIVED USEFULNESS. International Interdisciplinary Scientific Journal “Expert”, 3, Article 1, 1–10. https://doi.org/10.62034/2815-5300/2026-v3-001.
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