ArticlePloS one2024
Factors affecting the elderly's behavioral intention toward smart home systems: A cross-sectional study from China's eastern coast.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Acceptance and impact of Technology-Enabled Care (TEC) among community-dwelling older adults: A rapid review.PLOS digital health · 2026Review
- Perspectives of older adults with pre-frailty and frailty when engaging with an online nutrition educational resource: a qualitative study.BMC geriatrics · 2026Article
- Illusory competence vs. real needs a cross-sectional study on the mismatch in Smart Senior Care (SSC) perceptions between nursing students and older adults.Frontiers in public health · 2026Article
- Exploring care adoption intention among older adults using XGBoost: a rural case in Anhui, China.Frontiers in public health · 2026Article
- Digital inclusion, legal governance, and the adoption of smart care services by older adults in China: an evolutionary game analysis.Frontiers in public health · 2026Article
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Authors and funding
5 authors.
Funding
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Abstract
As China's population continues to age rapidly, smart elderly care has become a crucial strategy for addressing this societal challenge. Smart home systems have the potential to significantly enhance the quality of life, safety, and autonomy of the elderly. However, the adoption rate of these systems in this demographic remains relatively low, requiring an exploration of the key factors influencing the behavioral intention to use such systems. This study developed a comprehensive model based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Through empirical analysis using partial least squares structural equation modeling, this study systematically examined the pathways through which various factors affected the behavioral intentions of the elderly. The findings revealed that perceived usefulness, facilitating conditions, compatibility, and perceived cost had significant direct effects on behavioral intention. Additionally, social influence, perceived trust, facilitating conditions, and compatibility indirectly influenced behavioral intention through perceived usefulness and perceived ease of use. Although perceived trust did not directly affect behavioral intention, it exerted an indirect influence through perceived usefulness. This comprehensive model provides theoretical insights into the behavioral intentions of the elderly toward smart home systems and offers practical guidance for developers, designers, and policymakers in the development, design, and promotion of these systems.
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