Evidence map›Paper›PMID 37273413›Full record

ArticleHumanities & social sciences communications2023

Factors driving the implementation of the 'Local New Year' policy to prevent COVID-19 in China.

Bifeng Zhu, Manqi Ding, Xingwei Xiang, Chaoyang Sun, Xiaoqian Tian, Junfeng Yin

Abstract read
In one paragraph

Article in Humanities & social sciences communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Bifeng ZhuCollege of Urban Construction, Zhejiang Shuren University, Hangzhou, China.ORCID 0000-0001-6214-3021
Manqi DingCollege of Architecture, Zhejiang University of Technology Zhijiang College, Shaoxing, China.ORCID 0000-0002-7239-0920
Xingwei XiangSchool of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan, China.
Chaoyang SunZhejiang Yongze Architectural Design Co., Ltd, Hangzhou, China.
Xiaoqian TianCollege of Architecture, Zhejiang University of Technology Zhijiang College, Shaoxing, China.
Junfeng YinSchool of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines the contradiction caused by the 'local new year' policy, that is, the conflict between the pandemic prevention policies and people's emotional demands during the Spring Festival, based on the normalisation of pandemic prevention and control. It focuses on the scientific logical relationship with the contradiction that people voluntarily support 'local new year', to explore the primary driving factors of their willingness. By evaluating the migrant workers in large cities, the primary influencing factors were screened, and the primary dynamic factors and their relationship were obtained using the Logit logical selection model and maximum-likelihood estimation. The study identified, 'whether social and entertainment activities are planned in migrant cities', as the primary driving factor, followed by 'whether there are relatives (elderly /children) at home', and 'contracting the infection during travel'. In view of this conclusion, this study further proposes corresponding policy suggestions: Relevant measures should be adopted according to different regions and the current situation of the pandemic in combination with the characteristics of the episodic and local nature of the pandemic. 'Local new year' is encouraged from the perspective of enriching people's emotional needs for spiritual entertainment and care. This study provides a new perspective and theoretical basis for the research and formulation of policies related to the normalisation of pandemic prevention and control in China and worldwide, and has a certain practical reference value.

Indexed as

PsychologySocial policyTheatre and performance studies

Identifiers

PMID37273413
PMCPMC10212730

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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.