Evidence map›Paper›PMID 33031057›Full record

ArticleJournal of behavioral addictions2020

More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses.

Guang-Heng Dong, Ziliang Wang, Haohao Dong, Min Wang, Yanbin Zheng, Shuer Ye, Jialin Zhang, Marc N Potenza

Open access · goldAbstract read
In one paragraph

Article in Journal of behavioral addictions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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  14. Independent component analysis for internet gaming disorder.Dialogues in clinical neuroscience · 2023
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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 at 4 institutions in 2 countries.

Guang-Heng Dong1Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, PR China.ORCID 0000-0001-8813-8730
Ziliang Wang4School of Psychology, Beijing Normal University, Beijing, PR China.
Haohao Dong5Department of Psychology, Zhejiang Normal University, Jinhua, PR China.
Min Wang1Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, PR China.
Yanbin Zheng1Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, PR China.
Shuer Ye1Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, PR China.
Jialin Zhang5Department of Psychology, Zhejiang Normal University, Jinhua, PR China.
Marc N Potenza6Department of Psychiatry, Child Study Center, Yale University School of Medicine, New Haven, CT, USA.ORCID 0000-0002-6323-1354
Hangzhou Normal University · CNZhejiang Normal University · CNBeijing Normal University · CNYale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInternet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.

methodsIn the current study, machine learning was used, based on regional and interregional brain features. Resting-state data from 374 subjects (including 148 IGD subjects with DSM-5 scores ≥5 and 93 IGD subjects with DSM-5 scores ≥6) were collected, and multivariate pattern analysis (MVPA) was employed to classify IGD from recreational game use (RGU) subjects based on regional brain features (ReHo) and communication between brain regions (functional connectivity; FC). Permutation tests were used to assess classifier performance.

resultsThe results demonstrated that when using DSM-5 scores ≥5 as the inclusion criteria for IGD subjects, MVPA could not differentiate IGD subjects from RGU, whether based on ReHo or FC features or by using different templates. MVPA could differentiate IGD subjects from RGU better than expected by chance when using DSM-5 scores ≥6 with both ReHo and FC features. The brain regions involved in the default mode network and executive control network and the cerebellum exhibited high discriminative power during classification. DISCUSSION: The current findings challenge the current IGD diagnostic criteria thresholding proposed in the DSM-5, suggesting that more stringent criteria may be needed for diagnosing IGD. The findings suggest that brain regions involved in the default mode network and executive control network relate importantly to the core criteria for IGD.

Indexed as

ConnectomeMachine LearningRecreationVideo GamesAdolescentAdultBrainDefault Mode NetworkDiagnostic and Statistical Manual of Mental DisordersExecutive FunctionFemaleHumansImage Interpretation, Computer-AssistedInternet Addiction DisorderMagnetic Resonance ImagingMalediagnosing criteriafunctional connectivityinternet gaming disorderMVPAReHo

Identifiers

PMID33031057
PMCPMC8943664
OpenAlexW3092245544

What OpenQuestion holds

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LicenceCC BY-NC
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.