Evidence map›Paper›PMID 35822654›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2023

Three dimensions of COVID-19 risk perceptions and their socioeconomic correlates in the United States: A social media analysis.

Shan Qiao, Zhenlong Li, Chen Liang, Xiaoming Li, Caroline Rudisill

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
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  13. Preventive Behaviors and Information Sources during COVID-19 Pandemic: A Cross-Sectional Study in Japan.International journal of environmental research and public health · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Shan QiaoDepartment of Health Promotion Education and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.ORCID 0000-0003-1834-1834
Zhenlong LiGeoinformation and Big Data Research Lab, Department of Geography, University of South Carolina, Columbia, South Carolina, USA.
Chen LiangDepartment of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Xiaoming LiDepartment of Health Promotion Education and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Caroline RudisillDepartment of Health Promotion Education and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.

Funding

Multilevel Determinants of Racial and Ethnic Disparities in Maternal Morbidity and Mortality in the Context of COVID-19 PandemicR01AI127203 · NIAID · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI LI, XIAOMING, LIU, JIHONG · 2017 to 2021
$5.2M
NIAID NIH HHS R01 AI127203
6 · The paper itself

Abstract

Social media analysis provides an alternate approach to monitoring and understanding risk perceptions regarding COVID-19 over time. Our current understandings of risk perceptions regarding COVID-19 do not disentangle the three dimensions of risk perceptions (perceived susceptibility, perceived severity, and negative emotion) as the pandemic has evolved. Data are also limited regarding the impact of social determinants of health (SDOH) on COVID-19-related risk perceptions over time. To address these knowledge gaps, we extracted tweets regarding COVID-19-related risk perceptions and developed indicators for the three dimensions of risk perceptions based on over 502 million geotagged tweets posted by over 4.9 million Twitter users from January 2020 to December 2021 in the United States. We examined correlations between risk perception indicator scores and county-level SDOH. The three dimensions of risk perceptions demonstrate different trajectories. Perceived severity maintained a high level throughout the study period. Perceived susceptibility and negative emotion peaked on March 11, 2020 (COVID-19 declared global pandemic by WHO) and then declined and remained stable at lower levels until increasing once again with the Omicron period. Relative frequency of tweet posts on risk perceptions did not closely follow epidemic trends of COVID-19 (cases, deaths). Users from socioeconomically vulnerable counties showed lower attention to perceived severity and susceptibility of COVID-19 than those from wealthier counties. Examining trends in tweets regarding the multiple dimensions of risk perceptions throughout the COVID-19 pandemic can help policymakers frame in-time, tailored, and appropriate responses to prevent viral spread and encourage preventive behavior uptake in the United States.

Indexed as

COVID-19Social MediaHumansPandemicsSocioeconomic FactorsSurveys and QuestionnairesUnited StatesCOVID-19risk perceptionssocial determinants of healthsocial media analysisTwitter data

Identifiers

PMID35822654
PMCPMC9350290

What OpenQuestion holds

Textmetadata
LicenceTDM
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.