Staff Hours
“Staff Hours” was designed to capture physicians’ work hours, work patterns, and circadian rhythms in real time. An algorithm was developed to automatically identify the number of hours a physician spends in medical workplaces (e.g., hospitals, clinics). This technology is based on Global Positioning System (GPS) signals, which is then combined with self-reported work hour data.
“Staff Hours” is our latest development of a fully automated time recording app. Its main principle is to use the Global Positioning System (GPS) in an extremely low power mode to automatically calculate work hours. There is no need to manually record clock-in and clock-out times every day as the app will automatically calculate work hours once installed. This app is the first research tool we have developed for our “fully automated real-time labor inspection system,” which will significantly improve the efficiency of traditional labor inspections. In the future, we will also establish real-time “sweatshop maps” for various types of work throughout Taiwan for immediate monitoring. This will provide employees who experience overtime and overwork with assurance through recorded work hours, without having to wait for labor inspections.
The “Staff Hours” will automatically draw a chart of your past work hours and calculate your actual work hours and overtime hours for the past seven days. If there is any discrepancy between the recorded hours and your actual work hours, you can adjust it by clicking on the bar chart on the screen within seven days.
Publications
1. Developing Methods for Assessing Mental Activity Using Human-Smartphone Interactions: A Comparative Analysis of Activity Levels and Phase Patterns in General Mental Activities, Working Mental Activities, and Physical Activities.
Chen HH, Lin C, Chang HC, Chang JH, Chuang HH, Lin YH.
Journal of Medical Internet Research. 2024 Jun 17:26:e56144. doi: 10.2196/56144.
2. Assessing Physicians’ Recall Bias of Work Hours With a Mobile App: Interview and App-Recorded Data Comparison.
Wang HH, Lin YH.
J Med Internet Res 2021;23(12):e26763
3. Assessing User Retention of a Mobile App: Survival Analysis.
Lin YH, Chen SY, Lin PH, Tai AS, Pan YC, Hsieh CE, Lin SH.
JMIR Mhealth Uhealth. 2020 Nov 26;8(11):e16309.
4. Automatic Work-Hours Recorder for Medical Staff (Staff Hours): Mobile App Development
Chiang TW, Chen SY, Pan YC, Lin YH.
JMIR Mhealth Uhealth. 2020 Feb 25;8(2):e16063.