This study aimed to demonstrate the key factors of emotional well-being in university students’ social networks. The research was carried out at a public university in Peru. The study used a sample of 436 students of both sexes. It was possible to explore the multivariate relationships of the proposed theoretical model using a quantitative, cross-sectional approach. The most important result of the study is that the model estimated using CB-SEM SmartPLS shows a better overall fit than IBM SPSS AMOS in analyzing the predictors of emotional well-being in social networks of university students. This better fit is manifested in the Chi-square, RMSEA, GFI, NFI, TLI and CFI. In conclusion, this research highlights the complex dynamics between the use of social networks and emotional well-being in the academic context. The conclusions indicate the need to develop strategies and policies in educational environments that address the dependence on social networks and enhance academic satisfaction and privacy management as protective factors of student well-being.

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Predictors of Emotional Well-Being on Social Networks in University Students

  • O. Gutierrez-Aguilar,
  • A. Duche-Pérez,
  • A. Gutierrez-Aguilar,
  • S. Chicana-Huanca

摘要

This study aimed to demonstrate the key factors of emotional well-being in university students’ social networks. The research was carried out at a public university in Peru. The study used a sample of 436 students of both sexes. It was possible to explore the multivariate relationships of the proposed theoretical model using a quantitative, cross-sectional approach. The most important result of the study is that the model estimated using CB-SEM SmartPLS shows a better overall fit than IBM SPSS AMOS in analyzing the predictors of emotional well-being in social networks of university students. This better fit is manifested in the Chi-square, RMSEA, GFI, NFI, TLI and CFI. In conclusion, this research highlights the complex dynamics between the use of social networks and emotional well-being in the academic context. The conclusions indicate the need to develop strategies and policies in educational environments that address the dependence on social networks and enhance academic satisfaction and privacy management as protective factors of student well-being.