Evidence map›Paper›PMID 42732775›Full record

ArticlePsychiatry investigation2026

Latent Trajectories of Screen Time and Their Predictors in School-Aged Children: A Six-Year Longitudinal Analysis.

Sunmi Cho, Saebom Jeon, Sang-Ha Lee, Ji-Hye Song, Yunmi Shin

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Article in Psychiatry investigation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sunmi Cho *Department of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea.
Saebom Jeon *School of Mathematics, Statistics and Data Science, Sungshin Women's University, Seoul, Republic of Korea.
Sang-Ha LeeDepartment of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea.
Ji-Hye SongDepartment of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea.
Yunmi ShinDepartment of Psychiatry, Ajou University School of Medicine, Suwon, Republic of Korea. ymshin@ajou.ac.kr.

Funding

National Center for Mental Health MHER25B01Sungshin Women's University
6 · The paper itself

Abstract

objectiveChildren's screen time has increased rapidly with the rise of digital technology and was further accelerated by the COVID-19 pandemic, heightening concerns about developmental impacts. This study investigates six-year trajectories of children's screen time, identifies usage profiles, and examines key social and behavioral factors influencing these patterns during and after the pandemic.

methodsWe analyzed data from 313 children participating in a prospective South Korean cohort study (2018-2023). Caregivers reported weekday and weekend screen time on smartphones, tablets, and personal computers (PCs). Joint latent class profile analysis (JLCPA) identified trajectories, and multinomial logistic regression tested the influence of child sex, age, parental education, household income, and Child Behavior Checklist (CBCL) scores.

resultsScreen time increased across devices, particularly smartphones and PCs. JLCPA revealed four distinct trajectories: low-risk (27.2%), mid-risk (38.4%), risk-increasing (15.3%), and high-risk (19.1%). Membership in the high-risk trajectory increased during and after the COVID-19 pandemic. Significant differences were observed across trajectories, with lower maternal education and male sex emerging as the most robust predictors of higher-risk membership. Children whose mothers had lower educational attainment were up to six times more likely to belong to the high-risk trajectory. Older age and higher caregiver-reported CBCL scores were also associated with increased odds of membership in higher-risk trajectories.

conclusionChildren's screen time behaviors are diverse and shaped by developmental, familial, and socioeconomic factors, with notable pandemic-related changes. Tailored interventions and continued research are essential to promote healthy digital habits and mitigate potential risks.

Indexed as

Child behaviorJoint latent class analysisLongitudinal cohort studyScreen time

Identifiers

PMID42732775
PMCPMC13571864

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