Evidence map›Paper›PMID 39917526›Full record

ArticleFrontiers in public health2024

Risk perception of COVID-19, depressive symptoms and Internet addiction among undergraduates: a longitudinal study.

Hongpo Zhang, Dandan Zhang, Wanghua Ji, Shun Peng

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

4 authors.

Hongpo ZhangSchool of Management, Henan University of Chinese Medicine, Zhengzhou, China.
Dandan ZhangSchool of Management, Henan University of Chinese Medicine, Zhengzhou, China.
Wanghua JiSchool of Management, Henan University of Chinese Medicine, Zhengzhou, China.
Shun PengSchool of Education, Huanggang Normal University, Huanggang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The COVID-19 pandemic has caused serious negative psychological effects worldwide, relatively little research has been performed on the potential enduring effects of COVID-19 on people's emotional health and Internet addiction. This study was to examine the longitudinal associations between risk perception of COVID-19, depressive symptoms, and Internet addiction among Chinese undergraduates. Methods: We conducted a two-wave longitudinal survey by convenience sampling, a total of 1,153 Chinese undergraduate students completed questionnaires measuring their COVID-19 risk perception and post-traumatic growth (PTG) in December 2022 (T1) via an online survey. Subsequently, 1,008 of the T1 participants (87.42%) completed the depressive symptoms scale and Internet addiction scale 6 months later, in June 2023 (T2). Results: (1) Risk perception of COVID-19 was significantly and positively predicted depressive symptoms and Internet addiction 6 months later; (2) Depressive symptoms played a mediating role between risk perceptions and Internet addiction; (3) PTG moderated the first-stage link between risk perception and Internet addiction, and this relationship was more robust for low PTG than for high PTG. Conclusion: These findings advance our understanding of the relationship and mechanisms between risk perception of COVID-19 and Internet addiction, and further support developing interventions to strengthen PTG for mitigating negative outcomes during major crises.

Indexed as

Behavior, AddictiveCOVID-19DepressionInternet Addiction DisorderStudentsAdolescentAdultChinaFemaleHumansInternetLongitudinal StudiesMaleSARS-CoV-2Surveys and QuestionnairesUniversitiesCOVID-19depressive symptomsInternet addictionpost-traumatic growthrisk perception

Identifiers

PMID39917526
PMCPMC11798794

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.