Six addiction components of problematic social media use in relation to depression, anxiety, and stress symptoms: a latent profile analysis and network analysis
Peng P, Liao Y
BMC psychiatry · 49 citations
How it was studied
- Design
- Cross-sectional study (classified by our AI screen)
- Studied in
- People
- Main outcome
- Health markers and function
Who paid for it
- Funding
- Independent funding
- Government
- STI 2030—Major Projects - "Brain Science and Brain-like Research" Project
Based on 1 listed funder(s) and full-text disclosure statement.
Publication
- Published
- 2023-05-08 · BMC Psychiatry · vol. 23 · issue 1 · p. 321
- Publisher
- BioMed Central
- Cited
- 109 citations · more than 100% of similar papers · 50.2× the field average
- Impact
- Top 10% most cited in its field
- References
- 53 works
- Access
- Open access (journal) · CC-BY
- Research areas
- Impact of Technology on Adolescents · Mental Health via Writing · Mental Health Research Topics
- Keywords
- social media addiction, salience, tolerance, mood modification, relapse, withdrawal, conflict, depression, anxiety, stress, Bergen Social Media Addiction Scale, symptom networks
- MeSH
- humans, depression, anxiety, anxiety disorders, mood disorders, social media
2 authors
From CN
- Pu PengSir Run Run Shaw Hospital; Second Xiangya Hospital of Central South University; Zhejiang University
- Yanhui Liao · correspondingSir Run Run Shaw Hospital; Zhejiang University
Abstract
Backgrounds
Components of addiction (salience, tolerance, mood modification, relapse, withdrawal, and conflict) is the most cited theoretical framework for problematic social media use (PSMU). However, studies criticized its ability to distinguish problematic users from engaged users. We aimed to assess the association of the six criteria with depression, anxiety, and stress at a symptom level.
Methods
Ten thousand six hundred sixty-eight participants were recruited. Bergen Social Media Addiction Scale (BSMAS) was used to detect six addiction components in PSMU. We applied the depression-anxiety-stress scale to assess mental distress. Latent profile analysis (LPA) was conducted based on BSMAS items. Network analysis (NA) was performed to determine the symptom-symptom interaction of PSMU and mental distress.
Results
(1) Social media users were divided into five subgroups including occasional users (10.6%, n = 1127), regular users (31.0%, n = 3309), high engagement low risk users (10.4%, n = 1115), at-risk users (38.1%, n = 4070), and problematic users (9.8%, n = 1047); (2) PSMU and mental distress varied markedly across subgroups. Problematic users had the most severe PSMU, depression, anxiety, and stress symptoms. High engagement users scored high on tolerance and salience criteria of PSMU but displayed little mental distress; (3) NA showed conflict and mood modification was the bridge symptoms across the network, while salience and tolerance exhibited weak association with mental distress.
Conclusions
Salience and tolerance might not distinguish engaged users from problematic users. New frameworks and assessment tools focusing on the negative consequences of social media usage are needed.
Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY).
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