# Design and Implementation of Health and Risk Level Assessment for Socially Disadvantaged Patients
## 4 Performance Analysis
### Sensor Data Measurement, Analysis, and Consideration
For income, the relationship between depression and negative (\(-\)) was statistically significant (r = \(-\)0.201, \(p\) < 0.01), and the relationship between anxiety and negative (\(-\)) was statistically significant (r = \(-\)0.180, \(p\) < 0.01). This can be interpreted to mean that a lower income is associated with a poorer mental health. \begin{table}
\begin{tabular}{l l l l l} \hline \hline  & **Occupation** & **Size** & **Mean** & **Standard Deviation** \\ \hline \multirow{3}{*}{depression} & Yes & 175 & 9.69 & 7.553 \\ \cline{2-5}  & No & 103 & 3.56 & 4.988 \\ \hline \multirow{3}{*}{anxiety} & Yes & 175 & 7.96 & 6.466 \\ \cline{2-5}  & No & 103 & 3.42 & 3.792 \\ \hline \multirow{3}{*}{location} & Yes & 175 & 8.61 & 2.89 \\ \cline{2-5}  & No & 103 & 9.707 & 2.343 \\ \hline \multirow{3}{*}{gyroscope} & Yes & 175 & 5642 & 1292.4 \\ \cline{2-5}  & No & 103 & 6134 & 1085.9 \\ \hline \multirow{3}{*}{data usage} & Yes & 175 & 105.67 & 93.081 \\ \cline{2-5}  & No & 103 & 71.99 & 70.52 \\ \hline \multirow{3}{*}{touch} & Yes & 175 & 302 & 227.66 \\ \cline{2-5}  & No & 103 & 172 & 133.82 \\ \hline \multirow{3}{*}{sleep mode} & Yes & 175 & 9.114 & 2.282 \\ \cline{2-5}  & No & 103 & 10.429 & 1.359 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Depression/anxiety level according to occupational status: average digital sensor data value trend. The result of the multiple regression analysis following correlation analysis found that only income information had a statistically significant negative (\(-\)) effect on mental health. For income, depression and negative (\(-\)) effects were statistically significant (\(t=-2.622\), \(p<0.01\)), and anxiety and negative (\(-\)) effects were statistically significant (\(t=-3.65\), \(p<0.001\)). This indicates that there is a negative effect on depression and anxiety as income decreases. To confirm research question 1 of this study, correlation analysis and multiple regression analysis between our application and depression were conducted (Tables 13 and 14). The location (11.88 \(\pm\) 9.01) showed a negative (\(-\)) correlation (r = \(-0.682\), \(p<0.01\)) with depression (7.42 \(\pm\) 7.33), and gyroscope (5824.53 \(\pm\) 1241.05) and depression showed a negative (\(-\)) correlation (r = \(-0.681\), \(p<0.01\)). The data usage (93.19 \(\pm\) 86.82) showed a positive (\(+\)) correlation with depression (r = 0.505, \(p<0.01\)), and touch (254.15 \(\pm\) 207.52) showed a positive (\(+\)) correlation with depression (r = 0.654, \(p<0.01\)). Also, sleep mode (9.01 \(\pm\) 2.74) showed a negative (\(-\)) correlation (r= \(-0.645\), \(p<0.01\)) with depression. It was confirmed that all five items of sensor information in our application correlated with depression, and showed significant correlations in the order of location, gyroscope, touch, data usage, and sleep mode. Based on this, we conducted an additional multiple regression analysis to closely observe the relationship between the variables, as shown in Table 13. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline  & **Location** & **Gyroscope** & **Data Usage** & **Touch** & **Sleep Mode** \\ \hline PHQ-9 & \(-\)0.682 ** & \(-\)0.681 ** & 0.505 ** & 0.654 ** & \(-\)0.645 ** \\ \hline GAD-7 & \(-\)0.549 ** & \(-\)0.550 ** & 0.669 ** & 0.839 ** & \(-\)0.786 ** \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Correlation between depression and anxiety and digital sensor data.