## 3 Results  
In this study, we analyzed PVT data from 356 participants to examine the differences in sustained attention based on age, gender, and time of day. The general linear model revealed that the reaction time (RT) was significantly affected by both age and time of day (\(p<0.001\)), with longer RTs observed among older participants and those tested in the morning (Table 2). Missed responses--minor lapses (MNLs) and major lapses (MJLs)--also occurred more frequently during the morning hours (\(p<0.001\)), indicating decreased attentional performance. Gender differences were evident as well, with significant effects found in the RTs, MNLs, and MJLs (\(p=0.018,0.05\), and \(0.045\), respectively). Across both genders, the RTs, MNLs, and MJLs were significantly lower in the 13:00-18:00 time window compared to 8:00-12:00. Furthermore, the RTs and MNLs were particularly lower in males during the early morning hours (8:00-12:59), suggesting higher concentration and better performance in males during that period (Figure 1). Nevertheless, attention performance improved in the afternoon for both genders. \begin{table}
\begin{tabular}{l c c c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Time Class**} & \multicolumn{6}{c}{**Fixed Factor**} \\ \cline{2-13} \multirow{2}{*}{**Sex**} & **8:00–12:00** & **13:00–16:00** & **16:00–18:00** & **Sex** & \multicolumn{6}{c}{**Time Class**} & **Age** & \multicolumn{6}{c}{**Sex \(\times\) Time Class**} \\ \cline{2-13}  & **M (\(n=93\)), F (\(n=88\))** & **M (\(n=75\)), F (\(n=38\))** & **M (\(n=46\))** & **F** & \(p\) & \(\eta^{2}\) & **F** & \(p\) & \(\eta^{2}\) & **F** & \(p\) & \(\eta^{2}\) \\ \hline Male & 428 \(\pm\) & 8 & 297 \(\pm\) & 4 & 293 \(\pm\) & 4 & & & & & & & & & & & & \\ Female & 465 \(\pm\) & 9 & 312 \(\pm\) & 7 & 291 \(\pm\) & 7 & & & & & & & & & & & \\ \hline Male & 77 \(\pm\) & 7 & 82 \(\pm\) & 14 & 63 \(\pm\) & 3 & & & & & & & & & & & \\ Female & 68 \(\pm\) & 3 & 62 \(\pm\) & 3 & 59 \(\pm\) & 4 & & & & & & & & & & & \\ \hline Male & 5.70 \(\pm\) & 0.41 & 2.20 \(\pm\) & 0.14 & 1.99 \(\pm\) & 0.16 & & & & & & & & & & & & \\ Female & 8.18 \(\pm\) & 0.53 & 2.14 \(\pm\) & 0.21 & 1.93 \(\pm\) & 0.25 & & & & & & & & & & & & \\ Male & 1.54 \(\pm\) & 0.10 & 1.41 \(\pm\) & 0.09 & 1.26 \(\pm\) & 0.09 & & & & & & & & & & & & & \\ Female & 1.45 \(\pm\) & 0.09 & 1.13 \(\pm\) & 0.08 & 1.09 \(\pm\) & 0.09 & & & & & & & & & & & & & \\ Male & 2.50 \(\pm\) & 0.72 & 2.36 \(\pm\) & 0.66 & 0.80 \(\pm\) & 0.28 & & & & & & & & & & & & & \\ Female & 1.68 \(\pm\) & 0.33 & 1.13 \(\pm\) & 0.28 & 0.80 \(\pm\) & 0.27 & & & & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results of the statistical analysis of the PVT and partial eta squared (\(\eta^{2}\)). In the regression model for the RT, the age, gender, and time of day were significant explanatory variables. The standardized coefficients (\(\beta\)) indicated that younger women who performed the PVT in the early morning had longer RTs, with the time of day showing a particularly strong effect. In the model for MNLs, the gender and time of day significantly predicted performance, with higher MNL frequencies observed among women tested in the morning. The RT model had a correlation coefficient of 0.7188 and explained 51.26% of the variance (Table 3). The MNL model showed a correlation coefficient of 0.4784 and explained 22.45% of the variance, indicating lower model accuracy (Tables 4 and 5). For the SDRT, a valid predictive model could not be established. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{2}{*}{**RT**} & \multicolumn{4}{c}{**Standardized Coefficients**} & \multirow{2}{*}{**T**} & \multirow{2}{*}{**_p_} \\ \cline{2-2} \cline{5-6}  & **B** & **SD** & & & \\ \hline Constant & 511.8912 & & & & \\ Age & \(-1.0232\) & 0.2001 & \(-0.263\) & \(-5.114\) & \(<\)0.0001 \\ Gender & 27.0655 & 7.604 & 0.1864 & 3.559 & 0.0004 \\ Time period & \(-76.5889\) & 5.245 & \(-0.6142\) & \(-14.602\) & \(<\)0.0001 \\ \hline \hline \end{tabular}
\end{table}