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<p>Against the dual backdrop of global population ageing and digital transformation, how to leverage smart eldercare technologies to bridge the “digital divide” and enhance older adults’ psychological well-being has become a pressing issue. Grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study innovatively develops a deep hybrid analytical framework that integrates Structural Equation Modeling (SEM) with Artificial Neural Networks (ANN). SEM is employed to validate the linear causal pathways among variables, while ANN is introduced to uncover nonlinear relationships and predictive weights in the data. The SEM results confirm a clear transmission pathway of “technology perception → demand satisfaction → enhancement of well-being,” in which “usage demand” plays a key mediating role. The nonlinear sensitivity analysis based on ANN further reveals that perceived usefulness and usage demand are the primary driving factors for predicting older adults’ well-being, indicating that their value orientation toward technology has shifted from “usable” to “truly useful.” The findings suggest that future product design should move away from mere functional stacking toward precise value alignment and zero–cognitive-load interaction, thereby providing scientific evidence for achieving high-quality, proactive healthy ageing.</p>

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How smart companions reshape psychological well-being in later life: the role of artificial intelligence technology in mental health during senior years

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月21日

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  • Bin Luan,
  • Yongchuan Li

摘要

Against the dual backdrop of global population ageing and digital transformation, how to leverage smart eldercare technologies to bridge the “digital divide” and enhance older adults’ psychological well-being has become a pressing issue. Grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study innovatively develops a deep hybrid analytical framework that integrates Structural Equation Modeling (SEM) with Artificial Neural Networks (ANN). SEM is employed to validate the linear causal pathways among variables, while ANN is introduced to uncover nonlinear relationships and predictive weights in the data. The SEM results confirm a clear transmission pathway of “technology perception → demand satisfaction → enhancement of well-being,” in which “usage demand” plays a key mediating role. The nonlinear sensitivity analysis based on ANN further reveals that perceived usefulness and usage demand are the primary driving factors for predicting older adults’ well-being, indicating that their value orientation toward technology has shifted from “usable” to “truly useful.” The findings suggest that future product design should move away from mere functional stacking toward precise value alignment and zero–cognitive-load interaction, thereby providing scientific evidence for achieving high-quality, proactive healthy ageing.