ArticleBMC psychiatry2023
Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis.
Article in BMC psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Objective and perceived smartphone use volume, addiction risk, and deprivation feelings.Addictive behaviors reports · 2026Article
- Differences in Internalizing Problems Across Risk Groups of Smartphone Addiction: Simulation-Based Network Analysis of Intervention Targets.Behavioral sciences (Basel, Switzerland) · 2026Article
- Digital addiction comorbidity patterns and their differential links to internalizing symptoms, suicidal behaviors and non-suicidal self-injury in vocational high school students.BMC psychology · 2026Article
- Cumulative effects of excess weight, sleep quality, and depressive and anxiety symptoms in Chinese adolescents.BMC psychology · 2026Article
- Peer bullying victimisation and depressive symptoms as serial mediators between attention-deficit/hyperactivity disorder symptoms and internet gaming disorder among Chinese adolescents: A three-wave longitudinal study.General psychiatry · 2026Article
- Difficulties in Emotion Regulation Mediate the Association Between Peer Attachment and Problematic Use of Smartphone.Brain and behavior · 2026Article
- The relationship between abnormalities in amygdala functional connectivity and emotion regulation difficulties in problematic smartphone users.BMC psychology · 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
- Demographic, social, psychological, mental health, and academic correlates of problematic smartphone use among French psychology students.Frontiers in digital health · 2026Article
- Article
- The Impact of Smartphone Addiction on PTSD Symptoms Among South African University Students: Resilience as a Protective Factor.Healthcare (Basel, Switzerland) · 2025Article
- The effect of bullying victimization trajectory on internet gaming disorder and the mediating role of impaired resilience: a three-wave cohort study among Chinese adolescents.BMC psychiatry · 2025Article
- Indonesian Validation of the YouTube Addiction Scale Among Young Adults.Psychiatry investigation · 2025Article
- Trajectory of internet gaming disorder among Chinese adolescents: Course, predictors, and long-term mental health outcomes.Journal of behavioral addictions · 2025Article
- Burden of gaming disorder among adolescents: A systemic review and meta-analysis.Public health in practice (Oxford, England) · 2025Review
- Symptom network between problematic smartphone use and poor sleep quality in adolescents with depression.BMC psychiatry · 2025Article
- Impaired sleep quality mediates the relationship between internet gaming disorder and conduct problems among adolescents: a three-wave longitudinal study.Child and adolescent psychiatry and mental health · 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
- Internet gaming disorder and depression mediated by impaired resilience and sleep distress: a three-wave longitudinal study among Chinese adolescents.Epidemiology and psychiatric sciences · 2025Article
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10 authors.
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Abstract
backgroundsThe Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD).
methodWe recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems).
resultsLPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as "PSU cases" in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%).
conclusionA potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.
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