Ageing in the digital age: What drives virtual reality technology adoption among older adults?
Abstract
In a rapidly ageing population, virtual reality (VR) technology is emerging as a useful tool to meet the increasing demands for medical health, social interaction and entertainment for older adults. This study explores the factors influencing the acceptance of VR technology among older adults to boost their VR use. The acceptance model of VR technology among older adults was founded on the technology acceptance model and incorporated personal factors such as self-efficacy (SE), technology anxiety (TA), perceived enjoyment (PE) and self-satisfaction (SS). Results revealed that SE, PE and SS positively influence their intention to use VR technology, while TA has a negative impact.
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AR technology's use in a blended-reality approach is considered effective for administering CBT, particularly for SAD.
“While AR technology has been developed for various applications in healthcare and education, its use in a blended-reality approach is considered effective for administering CBT, particularly for SAD [28,29,30,31,32].”
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- Authors
- Man, S. S., Wang, J., Chan, A. H. S., & Liu, L.
- Affiliations
- South China University of Technology (CN)
- City University of Hong Kong (HK)
- Dalian Maritime University (CN)
- Corresponding author
- Liu, Li
- Venue
- Ergonomics
- Publisher
- Informa UK Limited
- Published
- 2025-03-06
- Volume
- 69
- Issue
- 4
- Pages
- 642-656
- ISSN
- 0014-0139 (ISSN-L)
- 1366-5847
- OpenAlex
- W4408192063
- Cited by
- 11
- References
- 96
- Citations by year
- 2026: 8 · 2025: 3
- FWCI
- 24.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ergonomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (72301110, 72071170)
- Guangzhou Municipal Science and Technology Bureau (2024A04J2279)
- China Postdoctoral Science Fund (2024M760318)
- 1st Batch of
- MOE of PRC Industry-University Collaborative Education Program (230805329290236)
- Fundamental Research Funds for the Central Universities (QNMS202418)
- Topics
- Social Sciences › Demography › Technology Use by Older Adults
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Keywords
- virtual reality, older adults, technology adoption, technology acceptance model, self-efficacy, technology anxiety, perceived enjoyment, self-satisfaction, intention to use, population aging, digital inclusion
- MeSH terms
- Virtual Reality, Aged, Aged, 80 and over, Aging, Anxiety, Attitude to Computers, Female, Humans, Male, Middle Aged, Personal Satisfaction, Self Efficacy, Intention, Pleasure
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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