Problematic smartphone use in early adolescence: Developmental heterogeneity and bidirectional links with risk factors

= 9.57 years; 48.5% female), followed annually for three years. Growth mixture modelling identified distinct PSU trajectories, and bidirectional associations with internal (e.g., shyness, depression, anxiety) and external factors (e.g., parental neglect, peer exclusion) were examined. Cross-lagged network analysis further assessed interval-specific variation in predictive associations. Two trajectories emerged: a low-decreasing group (intercept = 1.845, slope = -0.120) and a high-increasing group (intercept = 2.110, slope = 0.348). Early adolescents in the high-increasing group experienced more adverse environments and reported higher levels of risk factors. PSU was primarily predicted by external factors in early intervals, whereas both personal and environmental factors became influential in later intervals. These findings highlight the heterogeneous and dynamic nature of PSU and support early, targeted family-focused interventions.

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Publication Details

Journal
British Journal of Psychology
Published
2026-05-11
DOI
https://doi.org/10.1111/bjop.70081
Primary Topic
Impact of Technology on Adolescents
Type
article
Field-Weighted Citation Impact
0.00

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article

Problematic smartphone use in early adolescence: Developmental heterogeneity and bidirectional links with risk factors

Zhifang Hu, Yue Lin, Jingjing Shi, Zongyuan Wang et al.
British Journal of Psychology
Impact of Technology on Adolescents
article

Problematic smartphone use in early adolescence: Developmental heterogeneity and bidirectional links with risk factors

Zhifang Hu, Yue Lin, Jingjing Shi, Zongyuan Wang, Qinxue Liu
article en

Abstract

= 9.57 years; 48.5% female), followed annually for three years. Growth mixture modelling identified distinct PSU trajectories, and bidirectional associations with internal (e.g., shyness, depression, anxiety) and external factors (e.g., parental neglect, peer exclusion) were examined. Cross-lagged network analysis further assessed interval-specific variation in predictive associations. Two trajectories emerged: a low-decreasing group (intercept = 1.845, slope = -0.120) and a high-increasing group (intercept = 2.110, slope = 0.348). Early adolescents in the high-increasing group experienced more adverse environments and reported higher levels of risk factors. PSU was primarily predicted by external factors in early intervals, whereas both personal and environmental factors became influential in later intervals. These findings highlight the heterogeneous and dynamic nature of PSU and support early, targeted family-focused interventions.

British Journal of Psychology
Westlake University (CN), Central China Normal University (CN), Shaanxi Normal University (CN)
National Social Science Fund of China
Reduced inequalities
Openalex Percentile: Top 4%
Impact of Technology on Adolescents
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