The predictive rol of self-esteem and emotional intelligence on addiction to social networks in Peruvian university students

Vargas-Guerrero E.; Goya-Diaz E.; Morón-Sifuentes J.; Turpo Chaparro J.E.; Conde I.; Huanca-Lopez S. · F1000Research (2026) · DOI: 10.12688/f1000research.163145.2

Resumen

Background: The digital age has brought numerous technological advances that have transformed our way of living and relating. Among them, Social media have revolutionized how we communicate and share information. However, there is a silent danger behind this seemingly harmless tool: Social media addiction. For this reason, the objective of this re-search was to determine if emotional intelligence and self-esteem predict addiction to Social media in Peruvian university students. Methods: Therefore, a cross-sectional predictive design study was developed, in which 289 Peruvian university students participated voluntarily, whose ages fluctuated between 23.71 years (SD = 5.85 years); 53.63% were female, and 46.37% were male. In addition, to measure the variables, the Wong-Law Emotional Intelligence Scale (WLEIS), the Rosenberg Self-Esteem Scale – EAR, and the Social media addiction questionnaire (ARS) were used. Results: Linear regression results show that self-esteem (SELF) is the strongest predictor across all models, with beta coefficients of -0.293 for Social Media Obsession (SMO), -0.225 for Lack of Control, and -0.153 (LAU) for Excessive Social Media Use (USO). Regarding the emotional intelligence dimensions, Self-Emotion Appraisal (SEA) and Use of Emotion (UEO) showed small negative associations with social media obsession, with standardized coefficients ranging from β = -.072 to β = -.136. Conclusions: It is concluded that the models explain 17.2% of the variance in SMO, 14.8% in LAU, and 9.2% in USO. These values suggest that, while self-esteem and emotional intelligence predict SMO addiction, other additional factors may also play an important role. Copyright:

Instituciones: Universidad Peruana Unión