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dc.contributor.authorRopovik, Ivan
dc.contributor.authorMartončik, Marcel
dc.contributor.authorBabinčák, Peter
dc.contributor.authorBaník, Gabriel
dc.contributor.authorVargová, Lenka
dc.contributor.authorAdamkovič, Matúš
dc.date.accessioned2023-01-03T07:49:27Z
dc.date.available2023-01-03T07:49:27Z
dc.date.issued2023
dc.identifier.citationRopovik, I., Martončik, M., Babinčák, P., Baník, G., Vargová, L., & Adamkovič, M. (2023). Risk and protective factors for (internet) gaming disorder : A meta-analysis of pre-COVID studies. <i>Addictive Behaviors</i>, <i>139</i>, Article 107590. <a href="https://doi.org/10.1016/j.addbeh.2022.107590" target="_blank">https://doi.org/10.1016/j.addbeh.2022.107590</a>
dc.identifier.otherCONVID_164500524
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/84686
dc.description.abstractThis large-scale meta-analysis aimed to provide the most comprehensive synthesis to date of the available evidence from the pre-COVID period on risk and protective factors for (internet) gaming disorder (as defined in the DSM-5 or ICD-11) across all studied populations. The risk/protective factors included demographic characteristics, psychological, psychopathological, social, and gaming-related factors. In total, we have included 1586 effects from 253 different studies, summarizing data from 210557 participants. Apart from estimating these predictive associations and relevant moderating effects, we implemented state-of-the-art adjustments for publication bias, psychometric artifacts, and other forms of bias arising from the publication process. Additionally, we carried out an in-depth assessment of the quality of underlying evidence by examining indications of selective reporting, statistical inconsistencies, the typical power of utilized study designs to detect theoretically relevant effects, and performed various sensitivity analyses. The available evidence suggests the existence of numerous moderately strong and highly heterogeneous risk factors (e.g., male gender, depression, impulsivity, anxiety, stress, gaming time, escape motivation, or excessive use of social networks) but only a few empirically robust protective factors (self-esteem, intelligence, life satisfaction, and education; all having markedly smaller effect sizes). We discuss the theoretical implications of our results for prominent theoretical models of gaming disorder and for the existing and future prevention strategies. The impact of various examined biasing factors on the available evidence seemed to be modest, yet we identified shortcomings in the measurement and reporting practices.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesAddictive Behaviors
dc.rightsCC BY 4.0
dc.subject.othergaming disorder
dc.subject.otherinternet gaming disorder
dc.subject.othervideo game
dc.subject.othergaming addiction
dc.subject.otherrisk factor
dc.subject.otherprotective factor
dc.titleRisk and protective factors for (internet) gaming disorder : A meta-analysis of pre-COVID studies
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202301031044
dc.contributor.laitosMusiikin, taiteen ja kulttuurin tutkimuksen laitosfi
dc.contributor.laitosDepartment of Music, Art and Culture Studiesen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn0306-4603
dc.relation.volume139
dc.type.versionpublishedVersion
dc.rights.copyright© 2022 The Author(s). Published by Elsevier Ltd.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber101042052
dc.relation.grantnumber101042052
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/101042052/EU//ORE
dc.subject.ysopelaaminen
dc.subject.ysoInternet
dc.subject.ysonettiriippuvuus
dc.subject.ysovideopelit
dc.subject.ysoriskitekijät
dc.subject.ysoriippuvuus
dc.subject.ysoongelmapelaaminen
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p14483
jyx.subject.urihttp://www.yso.fi/onto/yso/p20405
jyx.subject.urihttp://www.yso.fi/onto/yso/p25639
jyx.subject.urihttp://www.yso.fi/onto/yso/p17281
jyx.subject.urihttp://www.yso.fi/onto/yso/p13277
jyx.subject.urihttp://www.yso.fi/onto/yso/p9414
jyx.subject.urihttp://www.yso.fi/onto/yso/p25449
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1016/j.addbeh.2022.107590
dc.relation.funderEuropean Commissionen
dc.relation.funderEuroopan komissiofi
jyx.fundingprogramERC Starting Grant, HEen
jyx.fundingprogramERC Starting Grant, HEfi
jyx.fundinginformationThis work was supported by the Slovak Research and Development Agency under contracts no. APVV-18-0140, APVV-17-0418, and APVV-20-0319, the Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic and Slovak Academy of Sciences (VEGA) under the contract no. 1/0217/20, project PRIMUS/20/HUM/009, and NPO Systemic Risk Institute (LX22NPO5101). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon Europe research and innovation programme (grant agreement No 101042052)
dc.type.okmA1


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