## 4 Empirical Analysis  
### Reliability and Validity Analysis  
In this study, we established the variables by adapting measurement items from previous research. We then employed confirmatory factor analysis to assess the fit of the predefined model. This type of analysis is intended to validate a specified factor model, rather than merely estimating correlations between items. Specifically, the confirmatory factor analysis in this study assessed how well the measurement items aligned with their designated factors [60,61]. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variable** & **Category** & **Frequency** & **Percentage** \\ \hline \multirow{3}{*}{Gender} & male & 168 & 54.0 \\ \cline{2-4}  & female & 143 & 46.0 \\ \hline \multirow{6}{*}{Age} & below 20 & 29 & 9.3 \\ \cline{2-4}  & 20–29 & 106 & 34.0 \\ \cline{2-4}  & 30–39 & 99 & 31.8 \\ \cline{2-4}  & 40–49 & 45 & 14.5 \\ \cline{2-4}  & over 50 & 32 & 10.3 \\ \hline \multirow{6}{*}{Occupation} & employed & 169 & 54.3 \\ \cline{2-4}  & self-employed & 72 & 23.2 \\ \cline{2-4}  & student & 48 & 15.4 \\ \cline{2-4}  & homemaker & 13 & 4.2 \\ \cline{2-4}  & other & 9 & 2.9 \\ \hline \multirow{6}{*}{Education level} & high school graduate & 31 & 10.0 \\ \cline{2-4}  & some university education & 48 & 15.4 \\ \cline{1-1} \cline{2-4}  & bachelor’s degree & 182 & 58.5 \\ \cline{1-1} \cline{2-4}  & postgraduate degree & 50 & 16.1 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Characteristics of respondents. During the confirmatory factor analysis, one item from the e-SQ scale was found to be unsuitable for measuring the intended construct. Consequently, this item was removed, and the fit of the revised model was re-evaluated to ensure its validity. Following this, we assessed the reliability and validity of the constructs in the model. First, we examined the reliability coefficient using [PERSON]'s \(\alpha\). As shown in Table 2, the [PERSON]'s \(\alpha\) values of all variables were 0.765 or higher, thereby exceeding the reference value (\(\geq\)0.7) [62] and indicating satisfactory internal consistency. Second, confirmatory factor analysis was conducted to evaluate the validity of the variables, and we found that \(\chi^{2}\) = 182.829, d.f. = 84, \(\chi^{2}\)/d.f. = 2.177, TLI = 0.962, CFI = 0.970, RMR = 0.022, and RMSEA = 0.062; these results adequately met the criteria for good model fit as proposed by [PERSON] et al. [48]. The factor loading values of the measurement items ranged from 0.636 to 0.953, thus satisfying the concept validity above the standard value (\(\geq\)0.5). Composite reliability (CR) was 0.907-0.960, which exceeded the standard value (\(\geq\)0.7), while the average variance extracted (AVE) was 0.761-0.859, which exceeded the threshold of 0.50 [63]. These indicators revealed the good convergent validity of the measures. Table 3 presents the correlation coefficients between the constructs and the discriminant validity results. All correlations were statistically significant (\(p\) < 0.001). The square root of the AVE of each construct was greater than the correlation coefficients between the constructs, thereby implying discriminant validity [64]. These results demonstrate that the reliability and validity criteria were satisfied.