Evidence map›Paper›PMID 36619083›Full record

ArticleFrontiers in psychology2022

The relationship between internet use preference and loneliness among college students during COVID-19: The chain mediating effect of online social support and self-esteem.

Qing Luo, Lu Huang, Na Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

5 citing papers in PubMed, 10 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

3 authors at 3 institutions in 1 country.

Qing LuoDepartment of Psychology, School of Public Policy and Administration, Nanchang University, Nanchang, China.
Lu HuangSchool of Marxism, Wuhan Business University, Wuhan, China.
Na WuDepartment of Psychology, College of Education and Science, Hubei Normal University, Huangshi, China.
Hubei Normal University · CNNanchang University · CNWuhan Business University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of COVID-19, especially the demands of social interaction and spatial distancing behavior, has led to a surge in Internet use, which has also led to an increase in loneliness. Therefore, we investigated the role of online social support and self-esteem in the relationship between Internet use preference and loneliness. In this study, 1053 college students were surveyed with a questionnaire based on the framework of Ecological System Theory, and a chain mediation model was established to clarify the mechanism between Internet use preference and loneliness. The results show that Internet use preference not only positively predicts loneliness, but also indirectly influences loneliness through the mediators of online social support and self-esteem, thereby impacting loneliness through the "online social support → self-esteem" chain. The results also indicate the need to pay attention to college students' mental health status during COVID-19. The advent of COVID-19 has impacted people's lifestyles and has changed the impact of the Internet on individual mental health. This study provides a new way to further understand college students' Internet use preferences, online social support, self-esteem, and loneliness status during COVID-19. It provides targeted interventions for college students' loneliness during COVID-19.

Indexed as

chain mediating effectinternet use preferencelonelinessonline social supportself-esteem

Identifiers

PMID36619083
PMCPMC9813670
OpenAlexW4312187521

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.