Predictive Models of Nomophobia in University Students: A Neural Network and Logistic Regression-Based Approach

This article examines nomophobia, defined as the fear of being without a mobile phone, and its growing prevalence among university students. The literature shows a strong association between nomophobia and psychological factors, particularly anxiety, stress, overthinking, fear of missing out (FoMO), and compulsive non-clinical behaviors, with anxiety emerging as the most influential factor in smartphone overdependence. While several studies indicate higher prevalence among women and younger individuals, evidence regarding gender differences remains inconclusive. Nomophobia also presents significant psychosocial consequences, including reduced face-to-face interaction, increased social anxiety, and the potential exacerbation of mental health conditions such as depression and anxiety disorders. The study employed a cross-sectional design using a survey administered to 500 university students to assess anxiety levels, emotional attachment to smartphones, and daily usage time. Advanced analytical methods, including logistic regression and neural networks, were applied, both achieving a high predictive accuracy of 98% in identifying nomophobia among students.