Predictors of psychological behavior of users of social networks and information technologies

Project leader: Olessia Koltsova
Project participants: Polina Panicheva, Yadviga Sinyawskaia, Larisa Mararitsa
Joint project with Humanteq company

The project aims to identify "digital traces" that enable the automatic assessment of an individual's life satisfaction and their evaluation of their psycho-emotional state. In psychology, subjective well-being assessment traditionally divides into so-called "positive well-being" and the absence of mental health disorders. In the project, psychological assessment involves the Satisfaction With Life Scale (SWLS), developed by Ed Diener, and the WHO (Five) Well-Being Index (WHO-5), proposed by WHO specialists.

Within the study, based on data from the Vkontakte social network and smartphone usage patterns, parameters (digital predictors) will be identified to automatically predict the level of users' subjective well-being. It analyzes how smartphone usage patterns impact an individual's state, including identifying factors that negatively influence psychological well-being, such as internet addiction and prolonged negative emotional experiences. The obtained results will allow for the formulation of criteria for predictive automated detection of psychological distress risks in social networks and smartphone use. This, in turn, can enhance the accessibility and timeliness of social and psychological intervention methods aimed at improving the psychological well-being of the population.

Publications:

• Panicheva P., Mararitsa L., Sorokin S., Koltsova O., Rosso P. (2022) Predicting subjective well-being in a high-risk sample of Russian mental health app users // EPJ Data Science.  Volume 11. P. 1-42.  Download (PDF, 200 Кб)