## 4 Results
### Study 1
#### 4.1.2 Quantitative Results  
A Pearson correlation analysis was conducted to assess the relationship between SCM (means of warm and competence data) and WEAR ratings. A statistically significant moderate positive correlation was found between the Euclidean length of the warmth-competence vector and the WEAR scores, \(r(958)=0.453\), \(p<0.001\), with a 95% confidence interval of (0.402, 0.502). This result confirms the findings from [PERSON] and [PERSON] [71] that social acceptance ratings correlate with combined competence and warmth data. Stereotype Content Model (SCM)  
The Shapiro-Wilk normality test indicated no normal distribution (only selected SCM competence data showed \(p\succeq 0.05\), while all other stimuli for SCM competence and warmth had \(p<0.05\)). Therefore, a non-parametric two-factorial ART RM-ANOVA was conducted to determine the effects of Design Type and Orthotic Category on SCM competence and warmth. For the SCM competence data, statistically significant main effects were found for the Orthotic Category, \(F(3,869)=56.752\), \(p<0.001\), \(\eta_{p}^{2}=0.464\) (large effect size), and Design Type, \(F(2,869)=9.931\), \(p<0.001\), \(\eta_{p}^{2}=0.092\) (medium effect size). However, no interaction effect was found between Orthotic Category \(\times\) Design Type, \(F(6,869)=1.038\), \(p=0.399\), \(\eta_{p}^{2}=0.031\) (small effect size). For the SCM warmth data, statistically significant main effects were identified for the Orthotic Category, \(F(3,869)=3.201\), \(p=0.023\), \(\eta_{p}^{2}=0.278\), and Design Type, \(F(2,869)=4.493\), \(p=0.012\), \(\eta_{p}^{2}=0.265\), both with large effect sizes. However, the interaction effect of the Orthotic Category \(\times\) Design Type was not significant, with \(F(6,869)=1.055\), \(p=0.388\), and \(\eta_{p}^{2}=0.202\) (large effect size). Post hoc comparisons using Wilcoxon signed-rank tests with Bonferroni correction revealed significant effects in SCM competence and warmth data, as documented in Table 1. Figure 4 displays the mean values of perceived warmth and competence for each of the three Design Types within each of the four Orthotic Categories. Additionally, the  
Wearable Acceptability Range (WEAR)  
The Shapiro-Wilk test for normality indicated that the data are not normally distributed (\(p=0.003\)). An ART RM-ANOVA showed statistically significant main effects for the Orthotic Category, \(F(3,869)=39.949\), \(p<0.001\), \(\eta_{p}^{2}=0.423\) (large effect size), and Design Type, \(F(2,869)=17.677\), \(p<0.001\), \(\eta_{p}^{2}=0.178\) (large effect size), but no interaction effect for Orthotic Category\(\times\) Design Type, \(F(6,869)=1.372\), \(p=0.223\), \(\eta_{p}^{2}=0.048\) (small effect size). Bonferroni corrected pairwise comparisons were conducted using Wilcoxon signed-rank tests and revealed significant effects between _Generative AI \(\times\) Development concepts_ (\(p_{\text{adj. }}<0.001\)), _Generative AI \(\times\) Orthopedic products_ (\(p_{\text{adj. }}<0.001\)), and _Development concepts \(\times\) Orthopedic products_ (\(p_{\text{adj.}}=0.021\)). Furthermore, pairwise comparisons between Orthotic Categories revealed five significant effects, which are summarized in Figure 5.  
Seven-Point Likert Scale  
The evaluations of the two statements regarding device acceptance and aesthetic design expectations were not normally distributed (\(p<0.05\)). A non-parametric two-factorial ART-ANOVA on rated device acceptance statements revealed a significant main effect for the Orthotic Category, \(F(3,869)=24.717\), \(p<0.001\), \(\eta_{p}^{2}=0.336\), and Design Type, \(F(2,869)=24.077\), \(p<0.001\), \(\eta_{p}^{2}=0.247\), as well as a significant interaction effect for Orthotic Category\(\times\) Design Type, \(F(6,869)=4.068\), \(p<0.001\), \(\eta_{p}^{2}=0.142\) (each with a large effect size).