## 4 Result
### Structural Model  
Prior to empirical testing, a structural equation model was constructed and then AMOS 24.0 was used to perform calculations using the maximum likelihood method to obtain Figure 2 and Table 7. Table 7 shows that all data results meet the criteria, indicating that the model satisfies both the recommended level of independence of fit and the rule of combination, so it has a good fit and a good degree of fit. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{8}{c}{**Correlations and Discrimination**} \\ \hline RA & RA & CO & TR & GA & OB & PEU & PU & BIU & BU \\ RA & **0.832** & & & & & & & & \\ CO & 0.462 ** & **0.740** & & & & & & & \\ TR & 0.465 ** & 0.354 ** & **0.833** & & & & & & \\ GA & 0.518 ** & 0.467 ** & 0.403 ** & **0.827** & & & & & \\ OB & 0.186 ** & 0.208 ** & 0.160 ** & 0.180 ** & **0.777** & & & & \\ PEU & 0.409 ** & 0.348 ** & 0.476 ** & 0.328 ** & 0.132 ** & **0.803** & & & \\ PU & 0.435 ** & 0.408 ** & 0.414 ** & 0.427 ** & 0.243 ** & 0.457 ** & **0.859** & & \\ BIU & 0.425 ** & 0.401 ** & 0.334 ** & 0.414 ** & 0.339 ** & 0.361 ** & 0.379 ** & **0.781** & \\ BU & 0.348 ** & 0.359 ** & 0.340 ** & 0.314 ** & 0.329 ** & 0.325 ** & 0.295 ** & 0.496 ** & **0.829** \\ \hline \hline \end{tabular}  
* Correlation is significant at the 0.01 level (2-tailed).  
\end{table} 
Table 6: Correlation and differential validity analysis. Figure 2: Results of a proposed model to assess seniors’ use of fitness software. The results of the data analysis indicated that RA, CO, and TR had a notable positive impact on PEU, with TR exhibiting the most pronounced effect (STD Estimate = 0.356). This suggests that TR played a pivotal role in explaining PEU. Conversely, GA and OB demonstrated a non-significant effect on PEU (\(p\) > 0.05), indicating that these variables possess limited explanatory power with regard to perceived ease of use. All DOI variables (RA, CO, TR, GA, OB) had a significant positive effect on PU, with GA having the strongest effect (STD Estimate = 0.161). Additionally, PEU had a significant positive effect on PU (STD Estimate = 0.245), indicating that an increase in perceived ease of use is associated with an increase in perceived usefulness. Both PEU and PU had a significant positive effect on BIU, with PU having a slightly stronger effect (STD Estimate = 0). The results indicated that perceived usefulness exerted a slightly stronger influence on the intention to use BIU (296 vs. 0.285), suggesting that it is a slightly more powerful predictor of actual use behavior. Moreover, the effect of behavioral intention on actual use behavior was found to be the strongest single effect in the model (STD Estimate = 0.57), which is consistent with the notion that behavioral intention is a crucial predictor of actual use behavior. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Measurement** & **CMIN** & **DF** & **CMIN/DF** & **SRMR** & **GFI** & **IFI** & **TLI** & **CFI** & **RMSEA** \\ \hline Measured value & 984.75 & 716 & 1.375 & 0.078 & 0.925 & 0.983 & 0.981 & 0.983 & 0.025 \\ Reference standard & - & - & \textless{}3 & \textless{}0.08 & \textgreater{}0.9 & \textgreater{}0.9 & \textgreater{}0.9 & \textgreater{}0.9 & \textgreater{}0.9 & \textless{}0.08 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Measurement model fit indices.