ArticleFrontiers in psychiatry2026
A network analysis of depressive and internet addiction symptoms among bullying-victimized adolescents: a comparison between left-behind and non-left-behind children.
Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Bullying victimization and depressive symptoms among left-behind children: a moderated mediation model involving Internet Addiction.Frontiers in psychiatry · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: School bullying is an important risk factor for mental health problems in adolescents. Depressive symptoms and internet addiction often co-occur among adolescents who have experienced bullying; however, the associations among specific symptoms remain unclear. This study aimed to investigate the comorbidity network characteristics of depressive symptoms and internet addiction among bullying-victimized adolescents, and to compare differences in network characteristics between left-behind and non-left-behind adolescents. Methods: This study employed a cross-sectional design and included 15,984 bullying-victimized adolescents selected through stratified random sampling. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), and internet addiction was measured using the 9-item Internet Addiction Scale. A mixed graphical model (MGM) was used to construct the symptom network of depressive symptoms and internet addiction. Node centrality and bridge centrality indices were calculated, and network stability was assessed using bootstrap methods. The Network Comparison Test was conducted to compare differences in network structure and global strength between left-behind and non-left-behind adolescents. Results: Among bullying-victimized adolescents, the overall predictability of network nodes was 0.27. Risky persistence and Tolerance showed the highest strength centrality in the symptom network. The principal bridge symptoms were Risky persistence, Escape coping, and Depressive affect. The network model demonstrated good stability. No significant differences were observed between left-behind and non-left-behind adolescents in terms of either the overall network structure or global strength (all P > 0.05). Conclusion: Compared with interventions targeting only inter-symptom relationships, exposure to school bullying itself may be a more critical and primary intervention target. Left-behind and non-left-behind children exhibited highly similar symptom network patterns; therefore, intervention strategies should not rely solely on identity-based distinctions, but rather focus on bullying exposure and symptom severity to implement more precise interventions. These findings provide symptom-level empirical evidence for developing integrated intervention strategies for adolescents exposed to school bullying.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.