Modelling the future: Understanding the impact of technology on adolescent’s well-being (FUTURE)

Projekt nespadá pod Filozofickou fakultu, ale pod Fakultu sociálních studií. Oficiální stránka projektu je na webu muni.cz.

Kód projektu
GX19-27828X
Období řešení
1/2019 - 12/2023
Investor / Programový rámec / typ projektu
Grantová agentura ČR
Fakulta / Pracoviště MU
Fakulta sociálních studií
Další fakulta/pracoviště MU
Fakulta informatiky

This project aims to develop a complex evidence-based theory depicting impacts of technology usage on physical, psychological and social well-being of adolescents. We will integrate theories used by different fields, such as ecological systems theory (psychology), differential susceptibility to media effects theory (media studies), problem behavior theory (psychology) and behavioral change theory (health). Further, we plan to develop an innovative methodology integrating findings from short-term and long-term data collections. The first work package (WP) is based on the analyses of up-to-date data and aims to understand the associations of selected online risks and opportunities with well-being in the cross-culture perspective. We will use data from the project EU Kids Online, which collected representative data in 25 countries in the year 2010 and in 12 countries in the years 2017 to 2018. The second WP will assess the effects of the technology and various psycho-social factors on well-being of adolescents in longitudinal perspective. To capture the changes and to provide results in terms of causality, we will carry out the three-wave longitudinal research (with a one-year interval between each wave) on Czech adolescents aged 11-18 years. We aim for a sample of at least 1,000 adolescents and parents who attended the survey in all three waves. The third WP will comprise series of short-term studies focusing on examination of the cognitive processes related to impact of technology on well-being. We will present the stimuli on a computer/smartphone screen, and using eye-tracker, capture the pattern of eye movement. We will measure how different stimuli causes changes in well-being in relation to cognitive perceptions of the screens. The fourth WP will develop innovative research tools which will integrate short-term and long-term data collections. We will develop a software based on machine learning tools which will automatically access online behavior of adolescents. The data collection will combine intensive data collections based on real time behavior of adolescents (4x two weeks) with short surveys displayed on smart phones and two standard surveys.