The relationship between smartphone addiction and aggression among Lebanese adolescents: the indirect effect of cognitive function

Abstract

Background Despite a large body of research has shown that smartphone addiction (SA) is associated with aggressive behaviors, only a few mediators have been previously examined in this relationship among early adolescent students. No previous studies have explored, to our knowledge, the indirect role of cognitive function despite its great importance during this life period. This study is intended to verify whether cognitive function have indirect effects on the relationship between SA and aggression among high-school students in the context of Lebanese culture. Methods This was a cross-sectional designed study, conducted between January and May 2022, and enrolling 379 Lebanese adolescent students (aged 13–17 years). The Cognitive Functioning Self-Assessment Scale, the Buss–Perry Aggression Questionnaire-Short Form, and the Smartphone Addiction Scale-Short form were used. Results The bivariate analysis results revealed that higher SA and worse cognitive function were significantly associated with more physical aggression, verbal aggression, anger and hostility. The mediation analyses found that cognitive function mediated the association between SA and physical aggression, verbal aggression, anger and hostility. Higher SA was significantly associated with worse cognitive function and more physical aggression, verbal aggression, anger and hostility. Finally, worse cognitive function was significantly associated with more physical aggression, verbal aggression, anger and hostility. Conclusion Our findings cautiously suggest that, to reduce adolescent students’ aggression, interventions that promote cognitive performance may be effective. Particularly, students who are addicted to smartphones and show aggressive tendencies require interventions designed to improve cognition function.

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“…Buss-Perry Aggression Questionnaire-Short Form (BPAQ-SF). This questionnaire, validated in Lebanon [34], was used to assess the level of aggression of an individual [4,26]. It is a self-report tool consisting of 29 items such as "If I have to resort to violence to protest my rights, I will", "I have threatened people I know" and "When people annoy me, I may tell them what I think of them".…”

Literature Review of Deep-Learning-Based Detection of Violence in Video

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