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

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.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2026-09-21
DOI
https://doi.org/10.1080/10447318.2026.2730086
Primary Topic
Technology Use by Older Adults
Type
article
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article

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

Irwan Syah Md Yusoff, Wenyu Wang, Ting Gao, Yang Bo et al.
International Journal of Human-Computer Interaction
Technology Use by Older Adults
article

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

Irwan Syah Md Yusoff, Wenyu Wang, Ting Gao, Yang Bo, Azrina Binti Kamaruddin
article en

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.

International Journal of Human-Computer Interaction
Universiti Putra Malaysia (MY), Faculty of Design (SI)
Reduced inequalities
Openalex Percentile: Top 5%
Technology Use by Older Adults
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A Dominant Overall Evaluation Structure in Older Users’ Ratings of Social Application Interfaces: A Kansei Engineering Study — Irwan Syah Md Yusoff, Wenyu Wang, et al. · International Journal of Human-Computer Interaction (2026) | TGRS Research Map | TGRS