Evidence map›Paper›PMID 34675706›Full record

ArticlePsychology research and behavior management2021

The Relationship Between Social Support and Internet Addiction Among Chinese Adolescents During the COVID-19 Pandemic: A Multiple Mediation Model of Resilience and Post-Traumatic Stress Disorder Symptoms.

Xiumin Cui, Xinli Chi

Open access · goldAbstract read
In one paragraph

Article in Psychology research and behavior management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

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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

26 citing papers in PubMed, 50 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Xiumin CuiCollege of Education for the Future, Beijing Normal University, Zhuhai, 519087, People's Republic of China.
Xinli ChiSchool of Psychology, Shenzhen University, Shenzhen, 518060, People's Republic of China.
Beijing Normal University · CNShenzhen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLockdowns and online homeschooling during the COVID-19 coronavirus pandemic have significantly increased Internet use and adolescents' risk of developing or reinforcing related addictive behaviors. While various theoretical propositions have suggested that social support, resilience, and post-traumatic stress disorder (PTSD) symptoms can predict Internet addiction, no study has yet examined the combined influence of these factors on Internet addiction. This study therefore aimed to investigate the mediating roles of resilience and PTSD symptoms in the relationship between perceived social support and the Internet addiction of Chinese adolescents in the context of COVID-19.

methodsThis study included 2544 adolescents living in the south China city of Qinzhou. The participants completed a self-report questionnaire one week before their return to classes after homeschooling. To examine whether resilience and PTSD symptoms mediated the relationship between social support and Internet addiction, we performed serial mediation analysis using the Model 6 PROCESS macro developed by Hayes (2013).

resultsSocial support was negatively and directly associated with Internet addiction and indirectly via resilience, PTSD symptoms, and by the multiple mediation of resilience to PTSD symptoms. DISCUSSION: The results of this study suggest that, to address Internet addiction, it may be more effective to focus not on addictive behaviors themselves but on individuals' existing mental health. It is important to provide adequate social support to improve the resilience of adolescents, thereby reducing PTSD symptoms and Internet addiction.

Indexed as

adolescentsCOVID-19 pandemicInternet addictionPTSD symptomsresiliencesocial support

Identifiers

PMID34675706
PMCPMC8517982
OpenAlexW3204791712

What OpenQuestion holds

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LicenceCC BY-NC
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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.