Survey Data on Product-Related Stigma and Wheelchair Morphological Semantics among Elderly Users
Description
This dataset supports an empirical study examining how wheelchair appearance semantics relate to Product-Related Stigma (PRS), emotional responses, and behavioral avoidance in the Chinese sociocultural context. The data were collected in two phases. Phase 1: Semantic evaluation data. Forty valid participants (industrial design students, professional designers, and wheelchair users) evaluated ten representative wheelchair samples using a seven-point Semantic Differential scale across nine stigma-related semantic dimensions, yielding 3,600 valid semantic data points (Cronbach's α = 0.861). Scores were linearly standardized to the interval [−3, 3] and aggregated into a Stigma Strength Score (SSS) for each sample, which was used to classify wheelchairs into high-, medium-, and low-stigma conditions. Phase 2: Field behavioral experiment data. A naturalistic field experiment was conducted on a riverside greenway in Guangzhou, China, using a single-confederate design with three wheelchair stimuli of differing stigma levels (SSS = 0.900, 0.300, −0.356). The dataset includes 300 valid pedestrian observations of behavioral avoidance, operationalized as Minimum Lateral Distance (MLD, in meters) recorded by a millimeter-wave radar system (Wheeltec MR20), and 215 valid emotional response records derived from facial Action Unit analysis using FaceReader, coded as negative, neutral, or positive. Pedestrian gender (coded 0 = female, 1 = male) and estimated age are included as moderating and control variables. The data were used to estimate a Structural Equation Model (WLSMV estimation) testing the associations among PRS, emotional response, and behavioral avoidance. All data have been fully anonymized: no facial images, video recordings, or personally identifiable information are included; only derived numerical and categorical variables are provided. The study was conducted in accordance with institutional ethics review requirements for naturalistic observation research.
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Institutions
- Guangdong University of TechnologyGuangdong, Guangzhou