Determination the cut-off point for the Bergen social media addiction (BSMAS): Diagnostic contribution of the six criteria of the components model of addiction for social media disorder
Open accessAbstract
Objective: Social media disorder (SMD) is an increasing problem, especially in adolescents. The lack of a consensual classification for SMD hinders the further development of the research field. The six components of Griffiths’ biopsychosocial model of addiction have been the most widely used criteria to assess and diagnosis SMD. The Bergen social media addiction scale (BSMAS) based on Griffiths’ six criteria is a widely used instrument to assess the symptoms and prevalence of SMD in populations. This study aims to: (1) determine the optimal cut-off point for the BSMAS to identify SMD among Chinese adolescents, and (2) evaluate the contribution of specific criteria to the diagnosis of SMD. Method: Structured diagnostic interviews in a clinical sample ( n = 252) were performed to determine the optimal clinical cut-off point for the BSMAS. The BSMAS was further used to investigate SMD in a community sample of 21,375 adolescents. Results: The BSMAS score of 24 was determined as the best cut-off score based on the gold standards of clinical diagnosis. The estimated 12-month prevalence of SMD among Chinese adolescents was 3.5%. According to conditional inference trees analysis, the criteria “mood modification”, “conflict”, “withdrawal”, and “relapse” showed the higher predictive power for SMD diagnosis. Conclusions: Results suggest that a BSMAS score of 24 is the optimal clinical cut-off score for future research that measure SMD and its impact on health among adolescents. Furthermore, criteria of “mood modification”, “conflict”, “withdrawal”, and “relapse” are the most relevant to the diagnosis of SMA in Chinese adolescents.
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Participants remained below the threshold for clinical diagnosis of social media disorder.
“While SMA tendencies were evident, participants remained below the threshold for clinical diagnosis of social media disorder.[20]”
From Does social media addiction disrupt mindful attention of students in health colleges at a university in Saudi Arabia? (2025) · cites this paper as [20]
The Results section, “Determination of the clinical cut-off point for the BSMAS,” identifies a score of 24 as the clinical cut-off for social media disorder. The source does not report scores for the citing paper’s participants, so it cannot establish that they remained below that threshold. (LLM, conf=0.84)
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- Authors
- Luo, T., Qin, L., Cheng, L., Wang, S., Zhu, Z., Xu, J., Chen, H., Liu, Q., Hu, M., Tong, J., Hao, W., Wei, B., & Liao, Y.
- Affiliations
- Central South University (CN)
- Tsinghua University (CN)
- 4Department of Psychology Yingtan People’s Hospital, Yingtan, 335000, P. R. China
- Jiangxi Mental Health Center (CN)
- First Affiliated Hospital of Nanchang University (CN)
- Sir Run Run Shaw Hospital (CN)
- Corresponding author
- Hu, Maorong
- Wei, Bo
- Liao, Yanhui
- Venue
- Journal of Behavioral Addictions
- Publisher
- Akademiai Kiado Zrt.
- Published
- 2021-07-19
- Volume
- 10
- Issue
- 2
- Pages
- 281-290
- ISSN
- 2062-5871 (ISSN-L)
- 2063-5303
- PMC
- PMC8996805
- OpenAlex
- W3162555763
- Cited by
- 170
- References
- 39
- Citations by year
- 2026: 44 · 2025: 47 · 2024: 18 · 2023: 33 · 2022: 24 · 2021: 4
- FWCI
- 27.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Behavioral Addictions (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
- Funders
- Natural Science Foundation of Jiangxi Province of China (20192BAB205037)
- Zhejiang University
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
- Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Keywords
- social media disorder, Bergen Social Media Addiction Scale, cut-off values, diagnostic criteria, Chinese adolescents, prevalence, mood modification, conflict, withdrawal, relapse, conditional inference trees
- MeSH terms
- Internet Addiction Disorder, Adolescent, Humans, Prevalence, Behavior, Addictive, Social Media
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