Cross-Cultural Examination of Problematic Internet Use and Associated Psychological Variables: A Comparative Study in Italy, Spain, Ecuador, and Peru.

Background: Several studies focused on the escalating prevalence of Problematic Use of Internet (PUI) and its consequential impact on mental health globally. This study investigates the relationship between PUI and associated psychological variables across different cultural contexts in Italy, Spain, Ecuador, and Peru. Method: A total of 675 participants, aged 18 to 54 (M = 22.73; SD = 4.05), completed measures assessing Internet addiction, social media addiction, Fear of Missing Out, Internet Gaming Disorder, and Phubbing. Results: Significant cultural variations were found, with Italian participants showing higher levels of Internet addiction but lower levels of social media addiction compared to other countries. Fear of Missing Out was higher in Italy, while the Italian sample exhibited lower Internet Gaming Disorder levels compared to Peru. As regards the communication disturbance caused by Phubbing, the Italian sample demonstrated significantly higher scores than the Peruvian sample. Linear regression analyses revealed distinct predictors for problematic Internet use in each country, emphasizing the importance of considering the cultural context in understanding this phenomenon. Conclusions: These findings contribute valuable insights into the interplay of cultural factors, psychological variables, and problematic Internet use, guiding future research and interventions.

Psychosocial risk factors of technological addictions in a sample of Spanish University students: The influence of Emotional (Dys)Regulation, personality traits and Fear of Missing Out on internet addiction.

Perception of the need to be online can lead to the compulsive use of the Internet. The aim of this study is to investigate the relationships between Internet Addiction and Social Media Addiction and some psychological variables that could influence the onset of these disorders (FoMO, Emotional Dysregulation, Personality traits). The sample was composed by 598 Spanish university students aged from 18 to 35 (471 women and 118 men; average age = 21.56; standard deviation = 2.73). Participants responded to an online questionnaire regarding the use of Internet (IAT), the use of social media (BSMAS), Fear of Missing Out (FoMO), Emotional (Dys)regulation (DERS) and personality traits (BFI-15). Correlation analysis showed a positive relationship between FoMO, Social Media Addiction, Internet Addiction, Emotional (Dys)regulation and Neuroticism dimension of Big five. Also, we observed a negative relationship between Internet Addiction and Social Media Addiction, Conscientiousness dimension of Big Five, and gender. The tested mediation model highlighted that the total effect of the DERS on the IAT score was significant as well as its indirect effect via the BSMAS and FoMO scores was positive and significant. In conclusion, we proposed a new integrated model for understanding the characteristics, predictors, and risk factors of IA.

From Emotional (Dys)Regulation to Internet Addiction: A Mediation Model of Problematic Social Media Use among Italian Young Adults.

Internet addiction (IA) has mostly been investigated with the fear of missing out and difficulties in emotional regulation. The present study examined the link between IA and variables related to problematic social media use (i.e., fear of missing out, social media addiction), together with emotional (dys)regulation and personality traits, providing new insights and an integrated assessment of IA. In total, 397 participants, aged 18-35 years (M = 22.00; SD = 3.83), were administered a set of questionnaires pertaining to IA, problematic social media use, emotional (dys)regulation, and personality traits. Pearson's correlations showed significant associations between IA and the investigated variables, and the tested mediation model highlighted the crucial role played by emotional (dys)regulation in the fear of missing out and problematic use of social networks. Overall, the findings provide support for a new integrated model for understanding the features, predictors, and risk factors of IA.