A Dominant Overall Evaluation Structure in Older Users’ Ratings of Social Application Interfaces: A Kansei Engineering Study

Abstract

Understanding how older users evaluate user interfaces is essential for inclusive digital design. This study examined the structure of older users’ emotional evaluations using Kansei Engineering. A total of 269 older adults evaluated eight social application interfaces using ten semantic differential scales, producing 2,152 participant–interface evaluations. The data showed high internal consistency (Cronbach’s α = 0.935) and sampling adequacy (KMO = 0.969; Bartlett’s χ2(45) = 13,418.428, p < 0.001). PCA identified a dominant component explaining 63.258% of the variance. A one-factor CFA of participant-level mean ratings provided additional within-sample support (CFI = 0.996, TLI = 0.995, RMSEA = 0.036, SRMR = 0.010). These findings suggest that multiple Kansei attributes may converge into a dominant overall evaluative structure when older users assess social application interfaces, providing a cautious empirical foundation for age-friendly interface design.