Evidence map›Paper›PMID 35996568›Full record

ArticleCities (London, England)2022

Gentle or rude? A study on China's publicity of epidemic prevention and governance of urban and rural areas based on anti-epidemic slogans.

Yu Hou, Tianxing Wei, Zixin Zhan, Fang Wang

Abstract read
In one paragraph

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Yu HouCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China.
Tianxing WeiCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China.
Zixin ZhanCollege of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China.
Fang WangNSFC-DFG Sino-German Cooperation Group on Urbanization and Locality (UAL); College of Architecture and Landscape Architecture, Peking University, Beijing 100871, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has swept through the world, challenging countries' ability to respond to crises and their public governance. One of the difficulties of public governance in China is the knowledge gap caused by the urban-rural dual structure. This study takes anti-epidemic slogans in China, a traditional means of information governance as its research object in the context of COVID-19. Independent sample tests and cluster analysis were conducted to measure the knowledge gap between urban and rural residents in acquiring epidemic information, and compare the different slogans posted in urban and rural areas, as well as the feedback they received. Based on this, the study explores the different logic of urban and rural governance in China. The results show that, although slogans cannot convey the latest information, they can make the public aware of the severity of the epidemic. Urban residents were found to give lower evaluations to slogans, although they acknowledged that slogans had the effect of rendering an anti-epidemic atmosphere, whereas rural residents were more accepting of rude and threatening slogans and control measures. Slogans with scientific guidance were more likely to trigger changes in their awareness and behavior. The study is significant as it can be a reference for other regions' and countries' publicity work and governance approaches in the prevention and control of infectious diseases.

Indexed as

Anti-epidemic slogansCOVID-19Crisis responseInformation governanceUrban and rural governance

Identifiers

PMID35996568
PMCPMC9385216

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.