METHOD OF FUNCTIONING THE INFORMATION TECHNOLOGY OF PYSCHOEMOTIONAL SCREENING AND DETERMINING THE CONDITION OF PATIENTS WITH DEPRESSION BASED ON THEIR PHYSICAL ACTIVITY

Abstract

The article proposes and describes in detail a method for using information technology to screen for and determine the mental state of patients with depression based on an analysis of their physical activity. The relevance of the study is due to the rapid increase in the prevalence of mental disorders worldwide and the critical situation in Ukraine, where approximately 15 million citizens require psychological assistance as a result of the war. The main scientific novelty of the method lies in the integration of subjective clinical tools, such as the standardized PHQ-9, GAD-7, and PSS-10 questionnaires, with objective monitoring of the patient's motor activity obtained from available wearable devices. The developed method involves continuous and non-invasive collection of data on total daily activity, inactivity indices, sleep duration and fragmentation, which allows detecting early signs of deterioration in the patient's condition even before they are noticed by the person themselves. The method of functioning of the information technology includes the stages of patient registration, data verification through the medics.ua system, primary signal processing with noise filtering, and comparison of current indicators with the user's individual baseline. If abnormal values of patient inactivity are detected, the information technology initiates a digital survey, based on the results of which it automatically classifies the patient's condition from mild to critical. The practical significance of the development is realized through the creation of a closed support ecosystem that provides operational feedback between the patient, their family, and the doctor. The implementation of this method guarantees medical intervention within 24 hours in critical cases, optimizes the use of human resources in medical institutions, and helps overcome social stigma by transitioning to a preventive model of mental health support for the population. The results obtained become the theoretical basis for the development of highly effective information technology for remote monitoring of psycho-emotional health.