Evidence map›Paper›PMID 40063937›Full record

ArticleJMIR public health and surveillance2025

Nationwide Trends in Screen Time and Associated Risk Factors by Family Structures Among Adolescents, 2008-2022: Nationwide Cross-Sectional Study.

Seokjun Kim, Hyesu Jo, Yejun Son, Min Kyung Shin, Kyeongmin Lee, Jaeyu Park, Hayeon Lee, Lee Smith, Elena Dragioti, Guillaume Fond and 7 more

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

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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

17 authors.

Seokjun Kim *Department of Medicine, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0009-0006-8716-7904
Hyesu Jo *Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0009-0004-1895-300X
Yejun Son *Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0009-0001-3939-2983
Min Kyung Shin *Department of Medicine, Wonkwang University College of Medicine, Iksan, Republic of Korea.ORCID 0009-0007-7794-9459
Kyeongmin LeeCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0009-0004-0379-2151
Jaeyu ParkCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0009-0005-2009-386X
Hayeon LeeCenter for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0009-0000-2403-6241
Lee SmithCentre for Health, Performance and Wellbeing, Anglia Ruskin University, Cambridge, United Kingdom.ORCID 0000-0002-5340-9833
Elena DragiotiResearch Laboratory Psychology of Patients, Families, and Health Professionals, Department of Nursing, School of Health Sciences, University of Ioannina, Ioannina, Greece.ORCID 0000-0001-9019-4125
Guillaume FondCEReSS-Health Service Research and Quality of Life Center, Assistance Publique-Hôpitaux de Marseille, Aix-Marseille University, Marseille, France.ORCID 0000-0003-3249-2030
Laurent BoyerCEReSS-Health Service Research and Quality of Life Center, Assistance Publique-Hôpitaux de Marseille, Aix-Marseille University, Marseille, France.ORCID 0000-0003-1229-6622
Guillermo F López SánchezDivision of Preventive Medicine and Public Health, Department of Public Health Sciences, School of Medicine, University of Murcia, Murcia, Spain.ORCID 0000-0002-9897-5273
Mark A TullySchool of Medicine, Ulster University, Londonderry, United Kingdom.ORCID 0000-0001-9710-4014
Masoud RahmatiCEReSS-Health Service Research and Quality of Life Center, Assistance Publique-Hôpitaux de Marseille, Aix-Marseille University, Marseille, France.ORCID 0000-0003-4792-027X
Damiano PizzolHealth Unit, Eni, San Donato Milanese, Italy.ORCID 0000-0003-4122-0774
Selin WooDepartment of Medicine, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0001-7961-2074
Dong Keon YonDepartment of Medicine, Kyung Hee University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0003-1628-9948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough understanding long-term trends in adolescent screen time and the influence of family structure is essential, there is a lack of research addressing these issues comprehensively.

objectiveThis study aimed to conduct comprehensive investigations into adolescent screen time before and during the COVID-19 pandemic, with a particular focus on family structures.

methodsThis study used nationwide, large-scale data from the Korea Youth Risk Behavior Web-Based Survey from South Korea. We aimed to indicate the changes in adolescent screen time over 15 years from 2008 to 2022. Weighted linear regression was used to analyze annual trends in screen time before and during the pandemic, and stratified analyses were conducted to examine associated risk factors across different family structures.

resultsThis study used data from a total of 836,972 individuals (n=403,456, 48.2% women), with an age range of 12-18 years. The analysis revealed an overall increase in screen time prepandemic (β=8.06, 95% CI 7.74-8.39), with a notable increase observed at the onset of the pandemic (β=162.06, 95% CI 159.49-164.64). Among diverse family structures, the orphanage group showed the most substantial increase in screen time during the pandemic (β

conclusionsThere has been a notable increase in average screen time among adolescents since the onset of the pandemic, with the orphanage group exhibiting a pronounced trend. The risk factors associated with screen time during the pandemic varied for each family structure. Findings from this study suggest that the implementation of individualized measures tailored to each family structure should be adopted to effectively address the increased issue of adolescent screen time since the pandemic.

Indexed as

Adolescent BehaviorCOVID-19Family CharacteristicsScreen TimeAdolescentChildCross-Sectional StudiesFamily StructureFemaleHumansMalePandemicsRepublic of KoreaRisk FactorsSurveys and Questionnairesadolescentsfamily typemobile phonepandemicrisk factorscreen timesedentary activitySouth Korea

Identifiers

PMID40063937
PMCPMC11933748

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.