Speaker
Description
The exponential increase of communication devices by younger generations in the past years has made it difficult to identify the patterns and scope of their use. The heightened use combined with concerns about potential health impacts of these devices, highlights the importance of unraveling and identifying how individuals use these devices. The aim of our study is to use latent class analysis to identify potential patterns in communication device use of young people. We used an online panel survey data collected in the GOLIAT EU funded project regarding use and functions of devices of 4,000 individuals ages 16-25 from Spain, Italy, Poland, and Switzerland. We performed a latent class analysis to identify classes of device use. Subsequently, we used multinomial logistic regression to identify differences of class membership based on various characteristics individually: age group, gender, parental education, and country. We identified four device use classes: high usage, low usage, smartphone and laptop preference, and non-smartphone preference. Older age groups were more likely to be high usage users. Males were more likely to be non-smartphone preference and low usage users. Participants with parents from higher education were more likely to be high usage users. Participants from Switzerland were more likely to be non-smartphone preference users, and from Poland smartphone and laptop preference users. Future work includes identifying changes of communication device classes and identifying differences of individual RF-EMF dose estimates based on class assignment.
