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August 16, 2025Open Access

Conceptually Informed AI/ML for South Korean Adolescent Smartphone Overdependency: Low-Risk Screening, Construct Exploration, Place-Based Policy Implication Profiles

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Authors

AKA. KimULUibin LeeYCY.J. Cho

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Overview

Analysis reveals a low-risk screening tool and regional differences in smartphone overdependence among adolescents, suggesting targeted policy interventions.

Key Points

  • AUC of 81.5% indicates strong predictive performance of the developed screening tool for smartphone overdependence.
  • The study utilizes data from 1,873 South Korean adolescents, revealing features driving overdependency variations by region.
  • This analysis employs a nested modeling approach, merging AI/ML with conceptual frameworks for effective screening.
  • Call for further research on cognitive patterns linked to smartphone usage, emphasizing the need for place-based public health strategies.

Cite This Study

Kim et al. (2025) studied this question.

synapsesocial.com/papers/68c235fdb210217d647729bahttps://doi.org/10.20944/preprints202508.0028.v1
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Adolescent Smartphone Overdependence in South Korea: A Place-Stratified Evaluation of Conceptually Informed AI/ML Modeling2025
  2. 2Adolescent Smartphone Overdependence in South Korea: A Place-Stratified Evaluation of Conceptually Informed AI/ML Modeling2025
  3. 3Psychosocial Pathways to Smartphone Overdependence in Adolescence: A Multi-Group Path Analysis of Early vs. Late Adolescents2025
  4. 4Machine learning model for prediction of smartphone addiction2025
  5. 5Context-Aware Digital Phenotyping of Youth Mental Health Using Mobile Ecological Prospective Assessments of Smartphone Use2025