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Social media use and abuse: Different profiles of users and their associations with addictive behaviours

INTRODUCTION: Social media use has become increasingly prevalent worldwide. Simultaneously, concerns surrounding social media abuse/problematic use, which resembles behavioural and substance addictions, have proliferated. This has prompted the introduction of ‘Social Media Addiction’ [SMA], as a con...

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Detalles Bibliográficos
Autores principales: Tullett-Prado, Deon, Stavropoulos, Vasileios, Gomez, Rapson, Doley, Jo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9898019/
https://www.ncbi.nlm.nih.gov/pubmed/36748081
http://dx.doi.org/10.1016/j.abrep.2023.100479
Descripción
Sumario:INTRODUCTION: Social media use has become increasingly prevalent worldwide. Simultaneously, concerns surrounding social media abuse/problematic use, which resembles behavioural and substance addictions, have proliferated. This has prompted the introduction of ‘Social Media Addiction’ [SMA], as a condition requiring clarifications regarding its definition, assessment and associations with other addictions. Thus, this study aimed to: (a) advance knowledge on the typology/structure of SMA symptoms experienced and: (b) explore the association of these typologies with addictive behaviours related to gaming, gambling, alcohol, smoking, drug abuse, sex (including porn), shopping, internet use, and exercise. METHODS: A sample of 968 [Mage = 29.5, SDage = 9.36, nmales = 622 (64.3 %), nfemales = 315, (32.5 %)] adults was surveyed regarding their SMA experiences, using the Bergen Social Media Addiction Scale (BSMAS). Their experiences of Gaming, Internet, Gambling, Alcohol, Cigarette, Drug, Sex, Shopping and Exercise addictions were additionally assessed, and latent profile analysis (LPA) was implemented. RESULTS: Three distinct profiles were revealed, based on the severity of one’s SMA symptoms: ‘low’, ‘moderate’ and ‘high’ risk. Subsequent ANOVA analyses suggested that participants classified as ‘high’ risk indicated significantly higher behaviours related to internet, gambling, gaming, sex and in particular shopping addictions. CONCLUSIONS: Results support SMA as a unitary construct, while they potentially challenge the distinction between technological and behavioural addictions. Findings also imply that the assessment of those presenting with SMA behaviours, as well as prevention and intervention targeting SMA at risk groups, should consider other comorbid addictions.