Anticipated acceptance of domestic humanoid robots among digitally familiar older adults in South Korea: Exploratory mixed-methods evidence

초록

Domestic humanoid robots may be evaluated through cognitive, social-contextual, and affective-relational expectations before use, but mixed-methods evidence among digitally familiar older adults remains limited. This exploratory cross-sectional mixed-methods study analyzed survey data from a selective, predominantly community-based sample of 170 relatively active, digitally familiar older adults in South Korea, with male participants and those aged 60–64 predominating, and conducted interviews with 10 participants. Acceptance Intention was treated as prospective willingness to try or use a domestic humanoid robot in anticipated contexts rather than as actual adoption. Exploratory quantitative analyses were integrated with thematic analysis to contextualize, extend, or complicate patterns. Across the domain-specific specifications, Social Influence and Intimacy showed more consistent conditional alignments with Acceptance Intention than Effort Expectancy and Empathy, respectively. In the full four-predictor specification, Social Influence, Intimacy, and Effort Expectancy were statistically distinguishable from zero, whereas Empathy was not. Empirical proximity between Social Influence and Acceptance Intention and between Intimacy and Empathy limits claims of construct separability. Emotional Reassurance contextualized the Intimacy-related pattern through predictable, low-burden support, while Substitutive Intimacy extended relational comfort through companionship-like availability and routine interaction. Cognitive Identification contextualized Social Influence through social visibility and role appropriateness and complicated the Empathy-related pattern through ambivalent interpretations of human-like responsiveness. The study offers bounded mixed-methods evidence and conceptual clarification rather than model validation, causal inference, or evidence of actual or sustained use. Functional clarity, user control, ethical safeguards, and transparent disclosure of machine limitations remain provisional priorities for prototype, field-based, and longitudinal evaluation. © 2026 The Authors.

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