Introduction: The Current Covid-19 pandemic is affecting the mental health of pregnant women and increases anxiety during pregnancy. To date, antenatal care in health facilities only focused on the health and physical well-being of mother and foetus. As the result, mental health of pregnant women is often neglected so as increases the risk of maternal and neonatal complications. Today, the use of internet-based technology in early detection of health problems can improve the ability of health workers to prevent and diagnose early. This study aims to develop a prototype of an antenatal depression screening application to prevent maternal mental problems by performing short assessments related to the mental health conditions of pregnant women. Methods: This study use the prototype method with a Software Development Life Cycle (SDLC) model. Results: The prototype of an Android-based antenatal depression screening tool is not only to detect the risk of depression during pregnancy but also finds the risk factors of depression. This tool allows midwives to assess the risk factors based on women's profile and history, screen for depression, identify the risk factor of anxiety/depression, and make decision related to the screening score of pregnant women. This prototype use Edinburgh Postnatal Depression Scale (EPDS) questionnaire to screen depression. The results of the black-box testing indicate that the application is functioning properly. Conclusion: The prototype antenatal depression detection system that has been developed can help to overcome maternal mental health problems through early detection system.
|Number of pages||7|
|Journal||Malaysian Journal of Medicine and Health Sciences|
|Publication status||Published - Oct 2022|