ArticleCities (London, England)2022
Managing urban citizens' panic levels and preventive behaviours during COVID-19 with pandemic information released by social media.
Article in Cities (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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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.
The trial behind it
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- The role of social media on COVID-19 preventive behaviors worldwide, systematic review.PloS one · 2024Pooled it
- COVID-19 information seeking and individuals' protective behaviors: examining the role of information sources and information content.BMC public health · 2024Article
- Social Media Fact-Checking: The Effects of News Literacy and News Trust on the Intent to Verify Health-Related Information.Healthcare (Basel, Switzerland) · 2023Article
- The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities.Cities (London, England) · 2023Article
- Revealing the spatiotemporal characteristics of the general public's panic levels during the pandemic crisis in China.Transactions in GIS : TG · 2022Article
- Deep learning modeling of public's sentiments towards temporal evolution of COVID-19 transmission.Applied soft computing · 2022Article
- The fluctuation analysis of public opinion energy: Modeling social group opinion base on the event of social networks.Intelligent systems with applications · 2022Article
- Spatial evolution patterns of public panic on Chinese social networks amidst the COVID-19 pandemic.International journal of disaster risk reduction : IJDRR · 2022Article
- Analyzing Risk Communication, Trust, Risk Perception, Negative Emotions, and Behavioral Coping Strategies During the COVID-19 Pandemic in China Using a Structural Equation Model.Frontiers in public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reducing citizens' panic and promoting their preventive behaviours are critical parts of pandemic management for the government. However, the effects of pandemic information types (daily statistical vs. detailed case information) and sources (official vs. unofficial social media accounts) on the psychological states and behaviours of urban citizens need to be explored further. Furthermore, the heterogeneity of these effects for citizens from areas with different epidemic levels also needs further investigation. Therefore, we conducted a survey during the COVID-19 outbreak in mainland China in March 2020, and 1298 urban citizens (592 from Wuhan) offered reliable data. Results of linear regression analysis indicated that non-Wuhan urban citizens who were more concerned about detailed case information (e.g., patients' movement paths) exhibited more preventive behaviours than those concerned about daily statistical information (e.g., case numbers) and did not show higher panic levels. Additionally, regarding social media information sources, unofficial social media caused both Wuhan and non-Wuhan urban citizens to have higher levels of panic than official media but had no significant impacts on their preventive behaviours. These findings contribute to urban management through the discovery of the effects of different information types and social media information sources on urban citizens during pandemics.
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Registered trials
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.