Factors Predicting Social Media Addiction among University Students in Klang Valley, Malaysia

Abstract BackgroundSocial media addiction is an emerging concern, particularly among university students, who represent a highly connected demographic. Sleep disturbances may contribute to increased social media use.ObjectiveThis study aimed to assess the prevalence of social media addiction and examine its predictors, including sociodemographic factors and sleep quality, among university students in Klang Valley, Malaysia.MethodsA cross-sectional study was conducted among 1,373 students selected through stratified sampling from public and private universities in Klang Valley. Data were collected using a self-administered online questionnaire, including the Bergen Social Media Addiction Scale and the Pittsburgh Sleep Quality Index. Descriptive statistics, chi-square tests, and binary logistic regression were used for data analysis.ResultsAbout 35.0% participants were classified as addicted to social media. Social media addiction was significantly associated with age (p = 0.010), academic performance (p = 0.013), and sleep quality (p < 0.001). Logistic regression analysis identified poor sleep quality (AOR = 2.42, 95% CI = 1.844–3.191, p < 0.001), CGPA < 2.70 (AOR = 2.019, 95% CI = 1.313–3.42, p = 0.009), and aged 22–23 years (AOR = 1.824, 95% CI = 1.185–2.807, p = 0.006) as significant predictors of social media addiction.ConclusionThe findings indicate a high prevalence of social media addiction among university students in Klang Valley. Given that poor sleep quality predicted social media addiction, promoting good sleep hygiene may mitigate addiction risk, especially among those with older age and low academic performance.