Design and Preliminary Realization of a Screening and Early Warning Health Management System for Populations at High Risk for Depression

• Published in: International journal of environmental research and public health Vol. 19; no. 6; p. 3599
• Main Authors: Chen, Xin, Xu, Liangwen, Pan, Zhigeng
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18.03.2022; MDPI
• Subjects: Artificial intelligence; Data collection; Depression - diagnosis; Depression - epidemiology; Design; Disease prevention; Exercise; Humans; Machine learning; Mass Screening; Medical screening; Mental depression; Mental disorders; Mental health; Mobile Applications; Physical fitness; Questionnaires; Reproducibility of Results; Sleep; Smartphones; Software; Telemedicine; Text Messaging; Traditional Chinese medicine; app; screening and early warning; SMS platform; high-risk population; depression; health management system; preventive treatment of disease
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph19063599

Depression has a high incidence in the world. Based on the concept of preventive treatment of disease of traditional Chinese medicine, timely screening and early warning of depression in populations at high risk for this condition can avoid, to a certain extent, the dysfunctions caused by depression. This work studied a method to collect information on depression, generate a database of depression features, design algorithms for screening populations at high risk for depression and creating an early warning model, develop an early warning short-message service (SMS) platform, and implement a scheme of depression screening and an early warning health management system. The implementation scheme included mobile application (app), cloud form, screening and early warning model, cloud platform, and computer software. Multiple modules jointly realized the screening, early warning, and management of the health functions of individuals at high risk for depression. At the same time, function modules such as mobile app and cloud form for collecting depression health information, early warning SMS platform, and health management software were designed, and the functions of the modules were preliminarily developed. Finally, the black-box test and white-box test were used to assess the system’s functions and ensure the reliability of the system. Through the integration of mobile app and computer software, this study preliminarily realized the screening and early warning health management of a population at high risk for depression.