Evidence map›Paper›PMID 37370074›Full record

ArticleBMC public health2023

Information interaction and social support: exploring help-seeking in online communities during public health emergencies.

Yanni Yang, Yue Zhang, Anling Xiang

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 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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.

Yanni YangSchool of Literature and Media, China Three Gorges University, Yichang, 443000, China.
Yue ZhangDavid Nazarian College of Business and Economics, California State University Northridge, Los Angeles, 91330-8378, USA. jeff.zhang@csun.edu.
Anling XiangSchool of Journalism and Communication, Minzu University of China, Beijing, 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring public health emergencies, online community users can obtain social support and assistance through information interaction in the online community. This study takes the COVID-19 pandemic as the context and aims to analyze the influence of user information interaction in online communities on the acquisition of social support during this public health emergency.

methodsData collected from help-seeking posts in the "COVID-19 Patients Help-Seeking Dialog" subforum on China's Sina Weibo were used as the research sample. The influence of the frequency of interaction and responsiveness on help seekers' receipt of online social support was analyzed, and the moderating effect of help seekers' identity type and intensity of online community use was explored.

resultsThe results reveal that the frequency of interaction positively impacts informational support (β = 0.367, p < 0.001) and negatively impacts emotional support (β=-0.240, p < 0.001), and the responsiveness of other users toward help-seeking posts positively impacts emotional support (β = 0.145, p < 0.01). Moreover, help seeker's identity type and intensity of online community use significantly moderate the relationship between the frequency of interaction and the emotional support obtained by the help seeker.

conclusionsThe study highlights the impact of user information interaction on obtaining help-seeking information from online communities for social support. The initiative would facilitate the resolution of issues related to users' information help-seeking during public health emergencies.

Indexed as

COVID-19Social MediaEmergenciesHumansPandemicsPublic HealthSocial SupportCOVID-19 pandemicInformation interactionOnline communityOnline help-seekingOnline social supportPublic health emergency

Identifiers

PMID37370074
PMCPMC10304684

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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.