Frontiers in Public Health
Behavioural intentions to limit social media use among nursing students in Saudi Arabia: a cross-sectional theory of planned behaviour and structural equation modelling study
By Asrar S. Almutairi, Rayhanah R. Almutairi, Abdulaziz M. Alodhailah and 3 others.
Abstract
BackgroundSocial media addiction (SMA) carries professional risks for nursing students, yet determinants of their intention to limit social media use are poorly characterised. Using the Theory of Planned Behaviour (TPB), this study examined how attitudes, subjective norms, and perceived behavioural control relate to this intention in Saudi nursing students.MethodsA cross-sectional survey of 258 nursing students (response rate 91.5%), recruited by stratified random sampling from nursing colleges in Riyadh, Saudi Arabia, was conducted in April–May 2026. Participants completed the Bergen Social Media Addiction Scale (BSMAS) and a 17-item TPB questionnaire. Analyses comprised confirmatory factor analysis (CFA), hierarchical regression, and structural equation modelling (SEM).ResultsIn total, 48.4% scored at or above the BSMAS threshold for probable SMA, and perceived behavioural control scored lowest (2.62/5). The four-factor CFA fitted well (CFI = 0.984; RMSEA = 0.029). The final regression model explained 41.2% of variance in intention, with perceived behavioural control the largest standardised predictor (β = 0.43), followed by attitudes (β = 0.22) and subjective norms (β = 0.13). In SEM, perceived behavioural control (β = 0.57) and attitudes (β = 0.28) were associated with intention; subjective norms were associated with attitudes (β = 0.57) but not directly with intention.ConclusionPerceived behavioural control was the least strongly held TPB antecedent but the most strongly associated with intention. As the design was cross-sectional and measured only intention, these associations identify candidate targets for nursing education interventions, not causes of behaviour change. Longitudinal studies measuring actual use are needed.



