ArticleJournal of behavioral addictions2020
Classification of probable online social networking addiction: A latent profile analysis from a large-scale survey among Chinese adolescents.
Article in Journal of behavioral addictions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Exploring the Comorbidity Mechanism of Internet Addiction, Insomnia, Depression, and Suicidality Among Chinese College Students Through Network Analysis.Alpha psychiatry · 2026Article
- The association between fear of missing out and problematic smartphone use: A latent profile analysis of problematic social media use.Addictive behaviors reports · 2026Article
- Preliminary identification of psychometric cut-off points for the SQoL-CHD: a cross-sectional study based on LPA and ROC analyses in a Chinese clinical sample.Frontiers in public health · 2026Article
- Identifying foreign language learning burnout: latent profiles, cutoff points, and an explainable web-based calculator.Frontiers in psychology · 2026Article
- Exploring heterogeneous profiles of academic performance among college students: a latent profile and LASSO regression analysis.Frontiers in psychology · 2026Article
- Developmental trajectories of problematic social media use among adolescents: Associations with multiple interpersonal factors.Journal of behavioral addictions · 2025Article
- Scale of employees' initiative for proactive health: development and validity testing.BMC psychology · 2025Article
- Assessing Short-Video Dependence for e-Mental Health: Development and Validation Study of the Short-Video Dependence Scale.Journal of medical Internet research · 2025Article
- The relationship between physical exercise and academic burnout in adolescents: the chain-mediated role of internet addiction and self-control.Frontiers in psychology · 2025Article
- Heterogeneity of demoralization syndrome in Chinese cancer patients: an optimal cut-off threshold for the demoralization scale.Frontiers in psychiatry · 2025Article
- Development and validation of a machine learning-based predictive model for compassion fatigue in Chinese nursing interns: a cross-sectional study utilizing latent profile analysis.BMC medical education · 2024Article
- Classification of nomophobia among Chinese college students: Evidence from latent profile and ROC analysis.Journal of behavioral addictions · 2024Article
- Characteristics and influencing factors of anticipated HIV stigma among HIV-negative/unknown MSM in China: A regression mixture model.Brain and behavior · 2024Article
- The associations between optimism, personal growth initiative and the latent classes of social media addiction.Frontiers in psychology · 2024Article
- The interplay of psychological resilience and adolescent mobile phone addiction in Henan province, China: insights from latent class analysis.Frontiers in public health · 2024Article
- Evaluation of the nutrition literacy assessment questionnaire for college students and identification of the influencing factors of their nutrition literacy.BMC public health · 2023Article
- Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis.BMC psychiatry · 2023Article
- Perceived stigma among discharged patients of COVID-19 in Wuhan, China: A latent profile analysis.Frontiers in public health · 2023Article
- Depression and stress are associated with latent profiles of problematic social media use among college students.Frontiers in psychiatry · 2023Article
- Distinct patterns of problematic smartphone use and related factors in Chinese college students.BMC psychiatry · 2022Article
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Authors and funding
9 authors.
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Abstract
BACKGROUND AND
aimsProblematic online social networking use is prevalent among adolescents, but consensus about the instruments and their optimal cut-off points is lacking. This study derived an optimal cut-off point for the validated Online Social Networking Addiction (OSNA) scale to identify probable OSNA cases among Chinese adolescents.
methodsA survey recruited 4,951 adolescent online social networking users. Latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses were applied to the validated 8-item OSNA scale to determine its optimal cut-off point.
resultsThe 3-class model was selected by multiple criteria, and validated in a randomly split-half subsample. Accordingly, participants were categorized into the low risk (36.4%), average risk (50.4%), and high risk (13.2%) groups. The highest risk group was regarded as "cases" and the rest as "non-cases", serving as the reference standard in ROC analysis, which identified an optimal cut-off point of 23 (sensitivity: 97.2%, specificity: 95.2%). The cut-off point was used to classify participants into positive (probable case: 17:0%) and negative groups according to their OSNA scores. The positive group (probable cases) reported significantly longer duration and higher intensity of online social networking use, and higher prevalence of Internet addiction than the negative group.
conclusionsThe classification strategy and results are potentially useful for future research that measure problematic online social networking use and its impact on health among adolescents. The approach can facilitate research that requires cut-off points of screening tools but gold standards are unavailable.
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