## 4 Results
### Questionnaire Survey and Data Analysis
#### 4.3.2 Analysis of Reliability and Validity of Collected Questionnaire Data
To accomplish this, the _confirmatory factor analysis_ (CFA) process, utilizing the AMOS package, was applied to the gathered questionnaire data. The outcome of this analysis resulted in two three-dimensional structure-model graphs, as depicted in Figure 7. Additionally, the CFA generated a comprehensive list of _structure-model fit indices_ for each of the two scales, \"magic viewing experience\" and \"multimedia technology understanding\", as presented in Table 17. It can be seen that the four index values of \(\chi^{2}/\mathrm{df}\), agfi, cfi, and RMSEA obtained for each scale are, respectively, \"between 1 to 5\", \"approximately 0.8\", \"larger than 0.9\", and \"approximately between 0.05 and 0.08\", indicating that the structural model, established according to the latent dimensions of the scale, _fits fairly_ to the collected questionnaire data, according to [PERSON] and [PERSON] [26]. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Scale**} & \multirow{2}{*}{**df**} & \multirow{2}{*}{\(\chi^{2}\)} & \multirow{2}{*}{\(\chi^{2}/\mathrm{df}\)} & \multirow{2}{*}{**agfi**} & \multirow{2}{*}{**cfi**} & \multirow{2}{*}{**RMSEA**} & \multicolumn{2}{c}{**RMSEA (90\% CI)**} \\ \cline{5-8}  & & & & & & **LO** & **HI** \\ \hline Magic viewing experience & 62 & 96.292 & 1.553 & 0.828 & 0.957 & 0.073 & 0.042 & 0.100 \\ \hline \multicolumn{8}{c}{Multimedia technology understanding} & \multirow{2}{*}{62} & \multirow{2}{*}{112.702} & \multirow{2}{*}{1.818} & \multirow{2}{*}{0.797} & \multirow{2}{*}{0.920} & \multirow{2}{*}{0.088} & \multirow{2}{*}{0.062} & \multirow{2}{*}{0.114} \\ \hline \hline \end{tabular} Note: Meanings of symbols—df: degree of freedom; gfi: goodness-of-fit index; agfi: average gfi; cfi: comparative fit index; RMSEA: root mean square error of approximation; CI: confidence interval; LO: low; HI: high.  
\end{table} 
Table 17: Fitness indexes of the structural models of the two indicators of GPIC and the elderly’s attitude generated through CFA. Figure 7: Results of the confirmatory factor analysis (CFA) using the AMOS package. (**a**) Diagram of the structural model of the scale of “magic viewing experience” generated through the CFA. (**b**) Diagram of the structural model of the scale of “multimedia technology understanding” generated through the CFA. (5) _Step 5: Verification of the validity of the collected questionnaire data_  
Having established the fact that the model structures of both scales fit the questionnaire data fairly, the next step involves a more in-depth analysis of the data's validity. In Figure 7, showing the structure model of the questionnaire data, all the _factor-loading values_ (standardized regression weights) related to the scales (along the paths from FS1 through FS3 and FT1 through FT3 to the questions S1 through S13 and T1 through T13, respectively) exceed the threshold 0.5 except one (on the path from FT3 to T11). This observation indicates that the construct validity of the model is fairly good. Furthermore, this validation is reinforced by the construct validity values of all the latent dimensions computed by the EFA process mentioned earlier, as detailed in Table 18, where each value surpasses the threshold of 0.6 for passing the construct validity verification. Through the above five steps of statistical processes, the verification of the reliability and validity of the questionnaire data is completed. Then, we can proceed to analyze the questionnaire data of each latent dimension, as conducted in the subsequent discussions.