Predicting the Recovery of Psychophysiological State after Chronic Stress: A Neural Network Model

The psychophysiological state of combatants is determined by stress resistance, volitional self-regulation, the level of per- sonal anxiety and individual characteristics of higher nervous activity. Scientists have so far paid insufficient attention to predicting the recovery of the psycho-emotional state, although it is extremely important in modern conditions. The purpose of the research is to study the features of the psychophysiological state of individuals with different stress resistance who have experienced chronic stress and to develop neural network models for predicting the effectiveness and duration of their re - habilitation. An examination of 637 people who returned from the combat zone in the first week, one month and three months later was conducted. Stress resistance, level of depression, volitional self-regulation, personal and situational anxiety were determined, and individual characteristics of higher nervous activity were assessed. During the study, it was established that the most significant psychophysiological parameters for predicting an effective rehabilitation period are stress resis- tance, personal and situational anxiety, and emotional stability. These parameters had a pronounced impact on forecasting with high accuracy (92%), sensitivity (90%). The high sensitivity and specificity of the constructed neural model allows for an individual approach to the duration of the rehabilitation period for persons who have experienced acute stress.