# Design and Implementation of Health and Risk Level Assessment for Socially Disadvantaged Patients
## 4 Performance Analysis
### Sensor Data Measurement, Analysis, and Consideration
\begin{table}
\begin{tabular}{l l l l l} \hline \hline  & **Socially Disadvantaged** & **Size** & **Mean** & **Standard Deviation** \\ \hline \multirow{2}{*}{depression} & No & 117 & 4.37 & 5.851 \\ \cline{2-5}  & Yes & 161 & 9.64 & 7.519 \\ \hline \multirow{2}{*}{anxiety} & No & 117 & 4.01 & 4.421 \\ \cline{2-5}  & Yes & 161 & 7.93 & 6.506 \\ \hline \multirow{2}{*}{location} & No & 117 & 9.454 & 2.571 \\ \cline{2-5}  & Yes & 161 & 8.698 & 2.835 \\ \hline \multirow{2}{*}{gyroscope} & No & 117 & 6056 & 1153.4 \\ \cline{2-5}  & Yes & 161 & 5655 & 1278.2 \\ \hline \multirow{2}{*}{data usage} & No & 117 & 72.415 & 72.13 \\ \cline{2-5}  & Yes & 161 & 108.291 & 93.45 \\ \hline \multirow{2}{*}{touch} & No & 117 & 193 & 169.47 \\ \cline{2-5}  & Yes & 161 & 298 & 221.63 \\ \hline \multirow{2}{*}{sleep mode} & No & 117 & 10.179 & 1.574 \\ \cline{2-5}  & Yes & 161 & 9.181 & 2.307 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Depression and anxiety and average digital biomarkers according to recipients of the lowest income. The result of the multiple regression analysis between the digital biomarkers and depression, as shown in Table 14, showed that the explanatory power of the regression model was 78.8%, and the regression equation was found to be statistically significant for location, gyroscope, touch, and sleep mode, but not for data usage (F = 82.138, \(p<0.001\)). In terms of the independent variables, location was found to have a statistically significant negative (\(-\)) effect on depression (\(t=-8.518\), \(p<0.001\)), and gyroscope also appeared to have a negative (\(-\)) effect (\(t=-6.807\), \(p<0.001\)). Data usage showed a statistically significant negative (\(-\)) correlation in the correlation analysis with depression but was found to have no statistically significant effect in the multiple regression analysis. Touch appeared to have a statistically significant positive (\(+\)) effect on depression (\(t=4.712\), \(p<0.001\)). Finally, sleep mode was found to have a statistically significant negative (\(-\)) effect on depression (\(t=-3.714\), \(p<0.001\)). To test the second hypothesis of this research, correlation analysis and multiple regression analysis were conducted using the sensor data. Location showed a negative (\(-\)) correlation (r = \(-0.549\), \(p<0.01\)) with anxiety (6.28 \(\pm\) 6.03), and a negative (\(-\)) correlation (r = \(-0.550\), \(p<0.01\)) was found between gyroscope and anxiety. Data usage showed a positive (\(+\)) correlation with anxiety (r = 0.669, \(p<0.01\)), and touch showed a positive (\(+\)) correlation with anxiety (r = 0.839, \(p<0.01\)). Also, sleep mode showed a negative (\(-\)) correlation with anxiety (r = \(-0.786\), \(p<0.01\)). It was confirmed that all five items of sensor information from the digital biomarkers correlated with anxiety, and showed significant correlations in the order of location, gyroscope, touch, data usage, and sleep mode. Based on this, an additional multiple regression analysis was conducted to closely observe the relationship between the variables. The result of the multiple regression analysis between the digital biomarkers and depression showed that the explanatory power of the regression model was 86.0%, and our application's measurement of location, gyroscope, touch, data usage, and sleep mode were found to be statistically significant in the anxiety and regression equations (F = 135.969, \(p<0.001\)). In terms of the independent variables, location was found to have a statistically significant negative (\(-\)) effect on anxiety (\(t=-3.164\), \(p<0.01\)), and gyroscope also had a statistically significant negative (\(-\)) effect on anxiety (\(t=-3.227\), \(p<0.001\)). Data usage was found to have a statistically significant positive (\(+\)) effect on anxiety (\(t=4.833\), \(p<0.001\)), and the touch was also found to have a statistically significant positive (\(+\)) effect on anxiety (\(t=12.728\), \(p<0.001\)).