Evidence map›Paper›PMID 35062753›Full record

ArticleVaccines2022

Factors That Impact Acceptance of COVID-19 Vaccination in Different Community-Dwelling Populations in China.

Jinhua Pan, Kezhong A, Zhixi Liu, Peng Zhang, Zhiyin Xu, Xiaoqin Guo, Guangtao Liu, Ao Xu, Jing Wang, Xinyu Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 18% of its field
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. COVID-19 drive-through mass vaccination in Northwest Louisiana.jLPHA : the official journal of the Louisiana Public Health Association · 2022
    Article
  8. 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

11 authors at 5 institutions in 1 country.

Jinhua PanKey Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
Kezhong ADepartment of Immunization Programme Institute, Qing Hai Center for Disease Prevention and Control, Qinghai 810007, China.
Zhixi LiuKey Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.ORCID 0000-0002-8552-4027
Peng ZhangHuzhou Center for Disease Prevention and Control, Huzhou 313000, China.
Zhiyin XuDepartment of Infections Disease Prevention and Control, Minhang Center for Disease Prevention and Control, Shanghai 201100, China.
Xiaoqin GuoSongjiang Center for Disease Prevention and Control, Shanghai 201600, China.
Guangtao LiuHuzhou Center for Disease Prevention and Control, Huzhou 313000, China.
Ao XuKey Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
Jing WangDepartment of Health and Environmental Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215000, China.ORCID 0000-0002-6263-4039
Xinyu WangKey Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
Weibing WangKey Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.ORCID 0000-0002-4497-5251
Fudan University · CNHuzhou University · CNChinese Center For Disease Control and Prevention · CNSongjiang District Central Hospital · CNXi’an Jiaotong-Liverpool University · CN

Funding

Bill & Melinda Gates Foundation INV-006277
6 · The paper itself

Abstract

(1) Background: It is important to improve vaccination strategies and immunization programs to achieve herd immunity to infectious diseases. (2) Methods: To assess the acceptance of COVID-19 vaccination, we conducted face-to-face surveys and online surveys in Shanghai, Zhejiang, and Qinghai provinces. A fixed-effect model and a random effects model were used to analyze factors associated with the acceptance of COVID-19 vaccination. (3) Findings: We initially recruited 3173 participants, 3172 participants completed the full questionnaire (the response rate was nearly 100%), of which 2169 were valid questionnaires, with an effective rate of 87.3%. The results indicated that 82.6% of participants were willing to receive vaccination when it was available in the community, and 57.2% of deliverymen, 43.3% of medical workers, 78.2% of parents of primary and secondary school children, and 72.2% of parents of preschool children were willing to receive vaccination. The models showed that participants who were male (female vs. male: OR = 1.49, 95% CI (1.12, 1.98)), 60 to 69 years-old (60-69 vs. <30: OR = 0.52, 95% CI (0.29, 0.92)), had less education (medium vs. low: OR = 1.50, 95% CI (1.05, 2.23)), had good health status (good vs. low: OR = 0.36, 95% CI (0.15, 0.88)), and had positive attitudes and trust (OR = 0.14, 95% CI (0.10, 0.20)) in vaccines approved by the National Health Commission were more likely to accept vaccination. Participants also had an increased vaccination acceptance if it was recommended by government sources, doctors, relatives, or friends. Most participants learned about COVID-19 vaccination from television, radio, and newspapers, followed by community or hospital campaigns and the internet. (4) Conclusions: Government sources and doctors could increase the acceptance of vaccination by promoting the efficacy and safety of COVID-19 vaccination by the use of mass media and emphasizing the necessity of vaccination for everyone.

Indexed as

COVID-19influencing factorsmulti-level logistic regressionvaccine acceptance rate

Identifiers

PMID35062753
PMCPMC8779453
OpenAlexW4225472015

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.