The association between social media addiction and eating disturbances is mediated by muscle dysmorphia-related symptoms: a cross-sectional study in a sample of young adults
Abstract
Although the association between problematic use of the internet and eating disorders (EDs) in young adults has been previously established, its underlying mechanisms have not been completely clarified. It has been suggested that exposure to idealized very thin and toned body images (e.g., “thinspiration” and “fitspiration” trends) on social media might lead to increased feelings of body dissatisfaction which, in turn, can represent a trigger for EDs. We have tested this hypothesis in a sample (N = 721) of young adults (504 females, mean age: 24.13 ± 3.70 years; range 18–34). Self-report measures investigating symptoms related to social media addiction (SMA), muscle dysmorphia (MD), and EDs were used. A mediational model analyzing the direct and indirect effects of SMA-related symptoms on ED-related symptoms through the mediating role of MD-related symptoms was performed controlling for confounding factors (e.g., socio-demographic variables, substances use, body mass index, psychopathological distress). The model showed that the total effect of SMA-related symptoms on ED-related symptoms was significant (B = 0.213; p = 0.022) and that this association was mediated by MD-related symptoms (B = 0.083; p = 0.021). Our findings support the possibility that MD-related symptoms play a relevant role in mediating the association between SMA severity and ED pathology. Level III, evidence obtained from well-designed cohort or case–control analytic studies.
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 721 participants or records.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.