Evidence map›Paper›PMID 42560759›Full record

ArticleJournal of behavioral addictions2026

A trans-therapeutic signature of recovery in internet gaming disorder: From shared network reorganization to molecular underpinnings.

Ningning Zeng, Jiejie Fu, Shuang Li, Haoseng Ni, Qinxuan Li, Xin Luo, Meiting Wei, Zhoukang Wu, Liangjiecheng Huang, Min Wang and 1 more

Abstract read
In one paragraph

Article in Journal of behavioral addictions, 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

11 authors.

Ningning Zeng1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.ORCID https://orcid.org/0000-0002-8916-5690
Jiejie Fu1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.
Shuang Li1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.
Haoseng Ni1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.
Qinxuan Li1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.ORCID https://orcid.org/0009-0007-9643-3247
Xin Luo1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.
Meiting Wei1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.
Zhoukang Wu3Department of Psychology, Ningbo University, Ningbo, 315211, China.ORCID https://orcid.org/0009-0005-5449-8793
Liangjiecheng Huang3Department of Psychology, Ningbo University, Ningbo, 315211, China.ORCID https://orcid.org/0000-0001-6693-9537
Min Wang3Department of Psychology, Ningbo University, Ningbo, 315211, China.ORCID https://orcid.org/0000-0003-0560-1983
Guangheng Dong1Center for Educational Cognitive Neuroscience, Faculty of Education, Yunnan Normal University, Kunming, 650000, China.ORCID https://orcid.org/0009-0000-9991-7676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: A variety of self-regulation interventions have shown efficacy in treating Internet Gaming Disorder (IGD), but their shared and unique neurobiological mechanisms remain unclear. This study aims to identify a common, trans-therapeutic neural signature of recovery and to delineate the specific connectivity fingerprints of five different self-regulation interventions for IGD. Methods: This secondary analysis pooled resting-state fMRI data from 269 individuals with IGD who participated in one of five randomized controlled trials of self-regulation-based interventions: Approach Bias Modification (ApBM), Retrieval-Aversive Conditioning (R-AC), Progressive Aerobic Training (PAT), face-to-face Mindfulness Meditation (MM), and a Digital (online) mindfulness intervention. Participants were diagnosed with IGD according to DSM-5. Partial Least Squares (PLS) regression was used to identify a shared connectivity pattern associated with clinical improvement and similarity network fusion to define intervention-specific connectivity fingerprints. Imaging-transcriptomic analysis was further used to explore the molecular correlates. Results: All interventions were associated with significant reductions in IGD severity. PLS analysis identified a shared connectivity pattern predictive of treatment response, characterized by a rebalancing of Subcortical Network (SCN) connectivity along the sensorimotor-association axis. This shared pattern was linked to gene expression profiles related to cellular stress and neuroplasticity. Each intervention also induced a unique connectivity fingerprint, targeting distinct neural circuits. Discussion and Conclusions: Diverse self-regulation interventions for IGD converge on a shared therapeutic pathway involving the large-scale reorganization of cortico-subcortical circuits. These findings identify a robust neurobiological phenotype of recovery, offering a potential biomarker for treatment response and a target for future circuit-based therapies.

Indexed as

BrainInternet Addiction DisorderMindfulnessNerve NetSelf-ControlVideo GamesAdolescentAdultFemaleHumansMagnetic Resonance ImagingMaleNeuronal PlasticityTreatment OutcomeYoung Adultbrain networkinternet gaming disordermindfulness interventionneuroplasticityrandomized clinical trials

Identifiers

PMID42560759
PMCPMC13678394

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.