Evidence map›Paper›PMID 35896018›Full record

ArticleJournal of medical Internet research2022

Item Response Theory Analyses of Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Criteria Adapted to Screen Use Disorder: Exploratory Survey.

Mathieu Boudard, Jean-Marc Alexandre, Charlotte Kervran, Louise Jakubiec, Dvora Shmulewitz, Deborah Hasin, Lucie Fournet, Christophe Rassis, Patrice Claverie, Fuschia Serre and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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 at 2 institutions in 2 countries.

Mathieu Boudard *Sanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0002-9338-9291
Jean-Marc Alexandre *Sanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0001-9260-903X
Charlotte Kervran *Sanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0003-0108-1079
Louise JakubiecSanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0001-5737-0588
Dvora ShmulewitzDepartment of Psychiatry, Columbia University, New York, NY, United States.ORCID 0000-0002-8297-6183
Deborah HasinDepartment of Psychiatry, Columbia University, New York, NY, United States.ORCID 0000-0002-6533-7021
Lucie FournetSanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0002-6161-3682
Christophe RassisSanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0001-7199-1014
Patrice ClaverieMairie de Martignas, Martignas, France.ORCID 0000-0001-6719-4426
Fuschia SerreSanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0002-0228-3572
Marc AuriacombeSanpsy (Sleep Addiction and Neuropsychiatry), CNRS (Centre National de la Recherche Scientifique), UMR (Unité Mixte de Recherche) 6033, University of Bordeaux, Bordeaux, France.ORCID 0000-0002-8938-8683
Centre National de la Recherche Scientifique · FRColumbia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScreen use is part of daily life worldwide and morbidity related to excess use of screens has been reported. Some use of screens in excess could indicate a screen use disorder (ScUD). An integrative approach to ScUD could better fit the polymodal reality of screens, and concurrent problems with screens, than a split approach, activity by activity. In that paradigm, a pragmatic and operationalized approach to study a potential ScUD requires the use of common criteria, for all screens and activities done on screens, in a single questionnaire.

objectiveOur goals were (1) to describe screen uses in a general population sample and (2) to test the unidimensionality, local independence, and psychometric properties of the 9 Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) internet gaming disorder (IGD) criteria adapted to screen use in a community sample. We hypothesized that the 9 DSM-5 IGD criteria adapted to ScUD would show unidimensionality, local independence, and good discrimination, with criteria distributed on the severity continuum.

methodsThis cross-sectional survey in a French suburban city targeted adults and adolescents. A self-administered questionnaire covered the main types of screens used and their use for various activities in the past month. Presence of ScUD diagnostic criteria in past 12 months was also self-evaluated in the questionnaire. Factor and 2-parameter Item Response Theory analysis were used to investigate the dimensionality, local independence, and psychometric properties of the ScUD criteria.

resultsAmong the 300 participants, 171 (57.0%) were female (mean age 27 years), 297 (99.0%) used screens, 134 (44.7%) reported at least one criterion (potential problem users), and 5 (1.7%) reported 5 or more criteria and endorsed an ScUD. The most endorsed criteria were loss of control (60/300, 20.0%) and preoccupation (52/300, 17.3%). Screen types used and screen activities differed between participants with no ScUD criteria and those with at least one ScUD criterion. The latter were more likely to have a computer as the most used screen type, and more video gaming, communication/social network, and watching news and research of information as activities. Unidimensionality was confirmed by all fit indices. Local independence was confirmed by the absence of residual correlation between the items. Criteria had relatively high factor loading, with loss of interest in other recreational activities having the highest. However, criteria with the lowest factor loading all remained above the cut-offs, sanctioning unidimensionality. Most discriminating criteria were loss of interests, preoccupation, deceive/cover up, and risk/lose relationship/opportunities, which also provided the most information on the measurement of the latent trait.

conclusionsWe described screen uses in a French community sample and have shown that the adaptation of the DSM-5 IGD to "ScUD" has good psychometric validity and is discriminating, confirming our hypothesis. We suggest to use those criteria to assess potential "ScUD." Further studies should determine if all criteria are needed and whether others should be added.

Indexed as

Behavior, AddictiveVideo GamesAdolescentAdultCross-Sectional StudiesDiagnostic and Statistical Manual of Mental DisordersFemaleHumansInternetMaleReproducibility of ResultsSurveys and Questionnairesinternet gaming disorderItem Response Theoryscreen addictionscreen media usescreen use disorder

Identifiers

PMID35896018
PMCPMC9377463
OpenAlexW4288058236

What OpenQuestion holds

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LicenceCC BY
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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.