ArticleFrontiers in psychology2024
Factors influencing older adults' acceptance of voice assistants.
Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- An innovative data mining-driven optimisation modelling approach based on TAM for the design of elderly-centric ICT products.Scientific reports · 2026Article
- Older adults' adoption of shared service platforms outside long-term care insurance in Japan based on technology acceptance model.Frontiers in public health · 2026Article
- Factors influencing older adults' intention to use social chatbots: examining technology acceptance, anthropomorphism, authenticity, and artificial intelligence social interaction.Innovation in aging · 2026Article
- Human-Centred Perspectives on Artificial Intelligence in the Care of Older Adults: A Q Methodology Study of Caregivers' Perceptions.Behavioral sciences (Basel, Switzerland) · 2025Article
- Association Between Intergenerational Support, Technology Perception and Trust, and Intention to Seek Medical Care on the Internet Among Chinese Older Adults: Cross-Sectional Questionnaire Study.Journal of medical Internet research · 2025Article
- Factors influencing older adults' adoption of AI voice assistants: extending the UTAUT model.Frontiers in psychology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Voice assistants (VAs) have the potential to uphold and enhance the quality of life for older adults. However, the extent to which older adults accept and benefit from VAs may be relatively modest. Methods: This study developed a comprehensive model combined with product and personal characteristics to explain the acceptance of VAs among older adults, using semi-structured interviews (Study 1) and questionnaires (Study 2). Results: Results revealed that in terms of product characteristics, perceived usefulness and perceived enjoyment significantly affect behavior intention. Regarding personal characteristics of older adults, technological self-efficacy and dispositional resistance to change significantly affect behavior intention. However, no direct impact of perceived ease of use and perceived trust on behavior intention. Additionally, perceived enjoyment influenced both perceived ease of use and perceived usefulness. Discussion: Results suggested the significant role of technology self-efficacy and dispositional resistance to change in predicting the acceptance of VAs among older adults. Our newly developed model offers valuable insights for tailoring VAs to this demographic during design and implementation.
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Registered trials
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