# Design and Implementation of Health and Risk Level Assessment for Socially Disadvantaged Patients
## 3 Platform Design and Implementation
### Development of Smartphone Application

Table 5: UI layouts and screenshots. This research aimed to verify whether the information measured using digital biomarkers is related to the depression and anxiety of the subjects. The general characteristics of data using this research are as shown in Table 6. Prior to the experiment, the research questions that were tested are as follows: (1) the relationship between digital biomarkers and depression, and (2) the relationship between digital biomarkers and anxiety. In this research, the depression and anxiety scores were measured using a depression screening tool and an anxiety scale test for 300 adults living in South Korea. Data from 278 people (85 males and 193 females) who responded faithfully were used for the analysis (Table 7). In addition, the research subjects installed a sensor measurement application on their smartphone, and collected oxygen saturation, accelerometer, gyroscope, touch screen, and sleep mode information at regular intervals through the application for a period of 2 weeks. This study was conducted after receiving approval from the Public Institutional Bioethics Committee. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline \multirow{2}{*}{**Factor**} & \multirow{2}{*}{**AUC**} & \multirow{2}{*}{**SE**} & \multicolumn{2}{c}{**95\% Confidence Interval**} & \multirow{2}{*}{\(p\)**} \\ \cline{3-3} \cline{5-6}  & & & **Lower** & & **Upper** \\ \hline co\_rev (GPS) & 0.981 & 0.024 & 0.935 & \(1\) & \textless{}0.001 \\ \hline af\_av (Touch) & 0.944 & 0.048 & 0.851 & \(1\) & 0.001 \\ \hline ex\_rev (Gyro) & 0.963 & 0.041 & 0.883 & \(1\) & \textless{}0.001 \\ \hline mo\_av (Data) & 0.537 & 0.132 & 0.278 & 0.796 & 0.776 \\ \hline sl\_av (Sleep) & 0.231 & 0.11 & 0.017 & 0.446 & 0.039 \\ \hline de\_av (PHQ-9) & 0.44 & 0.13 & 0.186 & 0.694 & 0.644 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: General characteristics of research subjects. \begin{table}
\begin{tabular}{l l l l l} \hline \hline \multirow{2}{*}{**Factor**} & \multirow{2}{*}{**AUC**} & \multirow{2}{*}{**SE**} & \multicolumn{2}{c}{**95\% Confidence Interval**} & \multirow{2}{*}{\(p\)**} \\ \cline{3-3} \cline{5-6}  & & & **Lower** & & **Upper** \\ \hline co\_rev (GPS) & 0.981 & 0.024 & 0.935 & \(1\) & \textless{}0.001 \\ \hline af\_av (Touch) & 0.944 & 0.048 & 0.851 & \(1\) & 0.001 \\ \hline ex\_rev (Gyro) & 0.963 & 0.041 & 0.883 & \(1\) & \textless{}0.001 \\ \hline mo\_av (Data) & 0.537 & 0.132 & 0.278 & 0.796 & 0.776 \\ \hline sl\_av (Sleep) & 0.231 & 0.11 & 0.017 & 0.446 & 0.039 \\ \hline de\_av (PHQ-9) & 0.44 & 0.13 & 0.186 & 0.694 & 0.644 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._As for the sex of the research subjects, there were 85 males (30.6%) and 193 females (69.4%), with about twice as many females as males. As for whether or not they had a job, 175 (62.9%) were unemployed and 103 (37.1%) had a job, indicating that there were more unemployed participants than those with a job. The age of the study subjects was evenly distributed from the 20s to 80s, and among them, 75 (27.0%) were in their 50s, which was the highest proportion. In terms of monthly income, 188 people (67.6%) were the lowest earners with less than KRW 1 million. Finally, 117 people (42.1%) were in the second category, and 161 people (57.9%) were recipients of slightly more income than average. When the subjects participated in this research, a survey was conducted using the anxiety scale and the depression scale. Based on the results of the survey and counseling, only those who were judged to be eligible to participate in the study were selected as study subjects after confirming once again through guidance and counseling. Subjects who agreed to participate in the study installed an application named \"Dr. Forest\", a digital biomarker collection application, on their smartphones to provide location, gyroscope, touch, data usage, and sleep mode information. Statistical analysis was performed by refining the normally collected data without any losses, collected by the smartphone sensors.