Social Connectedness Buffering the Interaction Between Problematic Internet Use and Psychopathological Symptoms Among Adolescents: Undirected and Bayesian Network Analyses.

Jiaqi Xu, Wenxin Bao, Kexin Zhou, Qiyuan Cao, Min Hu, Jing Li, Xiacan Chen, Jiajun Xu

Abstract readMulticenter Study

In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jiaqi Xu *Mental Health Center, West China Hospital, Sichuan University, No. 28, Telecom South Street, Chengdu, Sichuan, 610000, China, 86 17381883373.ORCID http://orcid.org/0009-0007-1926-9834

Wenxin Bao *Mental Health Center, West China Hospital, Sichuan University, No. 28, Telecom South Street, Chengdu, Sichuan, 610000, China, 86 17381883373.ORCID http://orcid.org/0009-0007-3246-5143

Kexin ZhouMental Health Center, West China Hospital, Sichuan University, No. 28, Telecom South Street, Chengdu, Sichuan, 610000, China, 86 17381883373.ORCID http://orcid.org/0009-0001-2769-049X

Qiyuan CaoMental Health Center, West China Hospital, Sichuan University, No. 28, Telecom South Street, Chengdu, Sichuan, 610000, China, 86 17381883373.ORCID http://orcid.org/0009-0008-1361-1800

Min HuPsychiatry department, Chengdu Southwest Rehabilitation Hospital, Chengdu, China.

Jing LiMental Health Center, West China Hospital, Sichuan University, No. 28, Telecom South Street, Chengdu, Sichuan, 610000, China, 86 17381883373.ORCID http://orcid.org/0000-0002-5697-8353

Xiacan ChenInstitute of Forensic Medicine, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, China.ORCID http://orcid.org/0000-0002-5604-987X

Jiajun XuMental Health Center, West China Hospital, Sichuan University, No. 28, Telecom South Street, Chengdu, Sichuan, 610000, China, 86 17381883373.ORCID http://orcid.org/0000-0002-3260-383X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Problematic internet use (PIU) in adolescents often co-occurs with psychopathological symptoms. Social connectedness (SC) is a potential protective factor for both PIU and psychopathological symptoms, but how SC interacts with the PIU-psychopathology system remains unclear. Objective: This study aimed to characterize the factor-level comorbidity network linking PIU with psychopathological symptoms among adolescents at high risk of PIU and to clarify how offline and online SC function in this system. We also applied Bayesian network structure learning to explore algorithm-preferred edge orientations. Methods: This multicenter study included 9407 adolescents aged 12 to 18 years from 4 provinces in China. PIU, depression, anxiety, irritability, repetitive thoughts and behaviors, anger, aggression, and SC were assessed. We estimated an undirected factor-level symptom network and a directed acyclic graph derived from a Bayesian network structure to characterize associations and conditional dependency structures among SC, PIU, and 8 psychopathological symptoms. Results: The integrative symptom network encompassing PIU, internalizing and externalizing symptoms, and SC showed great stability and accuracy. Anxiety, anger, and depression were identified as central bridging symptoms that reinforce the interplay between PIU and other psychopathological symptoms. Offline SC exhibited the highest number of negative edges and the highest bridge expected influence value, followed by online SC. In the exploratory directed acyclic graph, offline SC showed algorithm-selected outgoing arrows to PIU salience and to several internalizing and externalizing symptoms, including depression, anxiety, verbal aggression, and hostility. Conclusions: PIU and psychopathological symptoms formed a closely interconnected factor-level network among adolescents in the high-risk PIU group. Offline SC occupied a prominent negative bridge position, whereas online SC showed a secondary negative network position and was positively connected with offline SC. These findings support further evaluation of offline SC as a candidate prevention and intervention target.

Indexed as

InternetInternet Addiction DisorderInternet UseAdolescentBayes TheoremChildChinaFemaleHumansMaledirected acyclic graphnetwork analysisproblematic internet usepsychopathological symptomssocial connectedness

Identifiers

PMID42684264

DOI10.2196/92473

PMCPMC13528827

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

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.