# Design and Implementation of Health and Risk Level Assessment for Socially Disadvantaged Patients
## 4 Performance Analysis
### Sensor Data Measurement, Analysis, and Consideration
Finally, sleep mode was shown to have a statistically significant negative (\(-\)) effect on anxiety (\(t=-8.465\), \(p<0.001\)). This research was conducted to determine whether it is possible to measure users' mental health problems using smartphones, as mental illness and mental health problems \begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline  & **Var.** & \(\beta\) & \(t\) & \(p\) & \(R\) & \(R^{2}\) & F &
\begin{tabular}{l} **Durbin–** \\ **Watson** \\ \end{tabular} \\ \hline \multirow{4}{*}{depression} & Location & \(-0.3\) & \(-8.518\) *** & \(0\) & & & & \\ \cline{2-9}  & Gyroscope & \(-0.254\) & \(-6.807\) *** & \(0\) & & & \\ \cline{2-9}  & Data usage & \(0.004\) & \(0.116\) & \(0.908\) & \(0.888\) & \(0.788\) & \(82.138\)** & \(1.957\) \\ \cline{2-9}  & Touch & \(0.207\) & \(4.712\) *** & \(0\) & & & & \\ \cline{2-9}  & Sleep mode & \(-0.153\) & \(-3.714\) *** & \(0\) & & & & \\ \hline \multirow{4}{*}{anxiety} & Location & \(-0.09\) & \(-3.164\) ** & \(0.002\) & & & & \\ \cline{2-9}  & Gyroscope & \(-0.098\) & \(-3.227\) ** & \(0.001\) & & & & \\ \cline{2-9}  & Data usage & \(0.146\) & \(4.833\) *** & \(0\) & \(0.928\) & \(0.86\) & \(135.969\)** & \(1.837\) \\ \cline{2-9}  & Touch & \(0.455\) & \(12.728\) *** & \(0\) & & & & \\ \cline{2-9}  & Sleep mode & \(-0.283\) & \(-8.465\) *** & \(0\) & & & & \\ \hline \multirow{4}{*}{\(\text{anxiety}\)} & \multicolumn{6}{l}{**\(p<0.01\), *** \(p<0.001\).} \\ \cline{2-9}  & \multicolumn{6}{l}{**\(p<0.01\), *** \(p<0.001\).} \\ \cline{2-9}  & \multicolumn{6}{l}{**Table 14. Results of multiple regression analysis between digital biomarkers and depression and anxiety.} \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Results of multiple regression analysis between digital biomarkers and depression and anxiety. are increasing. First of all, the mental health relevance according to the general characteristics of the research subjects was analyzed. It was found that depression was more likely to occur in women than in men, but in this research, it was found that men had poorer mental health than women. This is thought to be influenced by the fact that most of the study subjects were unemployed or recipients of low income. Marital status and family relationships had a significant negative effect on mental health. In addition, there was a difference in mental health depending on whether the participant was employed and whether or not there was a pension recipient; the result of multiple regression analysis between income and mental health showed that income had a negative (\(-\)) effect on mental health. As is widely known, economic activity and income level have an effect on mental health, which is consistent with the results of this research. Therefore, it is necessary to address any issues with economic activity and income level in order to manage mental health, and as the aging population increases, job creation and economic activity participation policies for the aging population are necessary. In this research, the correlation and influence of digital biomarkers and users' depression and anxiety, measurable using a smartphone, were analyzed using correlation analysis and multiple regression analysis. The application used in this research used data relating to location, which measures the distance traveled; gyroscope, which measures the number of steps and other physical activity information; data usage; touch, which measures the number of smartphone touches; and sleep mode, which measures sleep time. In this research, the location and gyroscope information were measured and used as variables to explain the physical activity of the participants. The results showed that location was found to have a statistically significant positive (\(-\)) effect on depression (\(p<0.001\)), and gyroscope was shown to have a statistically significant negative (\(-\)) effect on depression (\(p<0.001\)).