Evidence map›Paper›PMID 35006084›Full record

ArticleJournal of medical Internet research2022

Heterogeneity of Prevalence of Social Media Addiction Across Multiple Classification Schemes: Latent Profile Analysis.

Cecilia Cheng, Omid V Ebrahimi, Jeremy W Luk

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 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
20.1field-weighted citation impact, top 1% 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

31 citing papers in PubMed, 54 citations in OpenAlex.

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  14. Heterogeneity of pain-fatigue-sleep disturbance symptom clusters in lung cancer patients after chemotherapy: a latent profile analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
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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

3 authors at 3 institutions in 3 countries.

Cecilia ChengDepartment of Psychology, The University of Hong Kong, Pokfulam, Hong Kong.ORCID 0000-0002-7250-2224
Omid V EbrahimiDepartment of Psychology, University of Oslo, Oslo, Norway.ORCID 0000-0002-8335-2217
Jeremy W LukNational Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, United States.ORCID 0000-0002-9061-1555
National Institute on Alcohol Abuse and Alcoholism · USUniversity of Hong Kong · HKUniversity of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs 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.

objectiveThe 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.

methodsA 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.

resultsThe 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.

conclusionsAmong the classification schemes, the polythetic scheme is more well-balanced across all 4 indices.

Indexed as

Internet Addiction DisorderSocial MediaAdultAnxiety DisordersCross-Sectional StudiesFemaleHumansMalePrevalencebehavioral addictioncompulsive social media useinformation technology addictionmental healthpsychological assessmentsensitivitysocial networkingsocial network sitewell-being

Identifiers

PMID35006084
PMCPMC8787656
OpenAlexW4205145200

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.