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dc.date.accessioned2022-02-11T19:10:39Z
dc.date.available2022-02-11T19:10:39Z
dc.date.created2022-01-18T09:57:24Z
dc.date.issued2022
dc.identifier.citationCheng, Cecilia Ebrahimi, Omid Vakili Luk, Jeremy W. . Heterogeneity of Prevalence of Social Media Addiction Across Multiple Classification Schemes: Latent Profile Analysis. Journal of Medical Internet Research. 2022
dc.identifier.urihttp://hdl.handle.net/10852/90829
dc.description.abstractBackground As social media is a major channel of interpersonal communication in the digital age, social media addiction has emerged as a novel mental health issue that has raised considerable concerns among researchers, health professionals, policy makers, mass media, and the general public. Objective The aim of this study is to examine the prevalence of social media addiction derived from 4 major classification schemes (strict monothetic, strict polythetic, monothetic, and polythetic), with latent profiles embedded in the empirical data adopted as the benchmark for comparison. The extent of matching between the classification of each scheme and the actual data pattern was evaluated using sensitivity and specificity analyses. The associations between social media addiction and 2 comorbid mental health conditions—depression and anxiety—were investigated. Methods A cross-sectional web-based survey was conducted, and the replicability of findings was assessed in 2 independent samples comprising 573 adults from the United Kingdom (261/573, 45.6% men; mean age 43.62 years, SD 12.24 years) and 474 adults from the United States (224/474, 47.4% men; mean age 44.67 years, SD 12.99 years). The demographic characteristics of both samples were similar to those of their respective populations. Results The prevalence estimates of social media addiction varied across the classification schemes, ranging from 1% to 15% for the UK sample and 0% to 11% for the US sample. The latent profile analysis identified 3 latent groups for both samples: low-risk, at-risk, and high-risk. The sensitivity, specificity, and negative predictive values were high (83%-100%) for all classification schemes, except for the relatively lower sensitivity (73%-74%) for the polythetic scheme. However, the polythetic scheme had high positive predictive values (88%-94%), whereas such values were low (2%-43%) for the other 3 classification schemes. The group membership yielded by the polythetic scheme was largely consistent (95%-96%) with that of the benchmark. Conclusions Among the classification schemes, the polythetic scheme is more well-balanced across all 4 indices.
dc.languageEN
dc.publisherJMIR Publications
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleHeterogeneity of Prevalence of Social Media Addiction Across Multiple Classification Schemes: Latent Profile Analysis
dc.typeJournal article
dc.creator.authorCheng, Cecilia
dc.creator.authorEbrahimi, Omid Vakili
dc.creator.authorLuk, Jeremy W.
cristin.unitcode185,88,0,1
cristin.unitnameKlinisk psykologi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1983224
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal of Medical Internet Research&rft.volume=&rft.spage=&rft.date=2022
dc.identifier.jtitleJournal of Medical Internet Research
dc.identifier.volume24
dc.identifier.issue1
dc.identifier.doihttps://doi.org/10.2196/27000
dc.identifier.urnURN:NBN:no-93434
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1438-8871
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/90829/1/ChengEbrahimiLuk2022-HeterogeneityofPrevalenceofSocialMediaAddictionAcrossMultipleClassificationSchemes-LatentProfileAnalysis.pdf
dc.type.versionPublishedVersion
cristin.articleide27000


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