Evidence map›Paper›PMID 37481541›Full record

ArticleBMC public health2023

COVID-19 victimization experience and university students' smartphone addiction: the mediating role of emotional intelligence.

Hongxia Chen, Hong-Xin Zhang

Abstract read
In one paragraph

Article in BMC public health, 2023. 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.

  1. Article
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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.

Hongxia ChenSchool of Marxism, Zhoukou Normal University, 466001 Wenchang Road, Zhoukou City, Henan Province, China.
Hong-Xin ZhangSchool of Marxism, Zhoukou Normal University, 466001 Wenchang Road, Zhoukou City, Henan Province, China. 544346440@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesDuring the post-COVID-19 era, everyone has the risk of contracting the virus and becoming the victims of COVID-19. Examining the relationship between the COVID-19 victimization experience and its effects is more urgent. The aim of present study is to propose a mediation model to investigate the association between COVID-19 victimization experience and smartphone addiction, and the mediating role of emotional intelligence.

methodsA online questionnaire including the COVID-19 Victimization Experience Scale, the Smartphone Addiction Scale, and the Emotional Intelligence Scale among Chinese university students, were employed in this study. Finally, 1154 valid questionnaires were collected. The reliability and confirmatory factor analysis results showed that all three scales had good reliability and validity.

resultsStructural Equation Model (SEM) demonstrated that COVID-19 victimization experience significantly predicted smartphone addiction in university students, and emotional intelligence partially mediated the association between COVID-19 victimization experience and smartphone addiction. Bootstrap results furthermore tested the rigor of the mediating effect.

conclusionCOVID-19 victimization experience was a important variables in predicting university students's martphone addiction, and emotional intelligence was a protective factor in decreasing the negative effect of COVID-19 victimization experience on addictive behaviors. It is suggested that instructors should integrate emotional intelligence training programs into mental health courses so as to improve students' emotional intelligence ability.

Indexed as

COVID-19Emotional IntelligenceHumansInternet Addiction DisorderReproducibility of ResultsStudentsUniversitiesCOVID-19 victimization experienceEmotional intelligencePost-COVID-19 eraSmartphone addictionUniversity students

Identifiers

PMID37481541
PMCPMC10362569

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.