Evidence map›Paper›PMID 32980199›Full record

ArticleVaccine2020

Intention of nurses to accept coronavirus disease 2019 vaccination and change of intention to accept seasonal influenza vaccination during the coronavirus disease 2019 pandemic: A cross-sectional survey.

Kailu Wang, Eliza Lai Yi Wong, Kin Fai Ho, Annie Wai Ling Cheung, Emily Ying Yang Chan, Eng Kiong Yeoh, Samuel Yeung Shan Wong

Open access · greenAbstract read
In one paragraph

Article in Vaccine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 269 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
269citing papers in PubMed, 10 pooled it
44.6field-weighted citation impact, top 1% 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

269 citing papers in PubMed, 10 syntheses or guidelines pooled it, 416 citations in OpenAlex.

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209 more citing papers are in PubMed but not listed here.

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

7 authors at 1 institution in 1 country.

Kailu WangCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Eliza Lai Yi WongCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. Electronic address: lywong@cuhk.edu.hk.
Kin Fai HoJC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Annie Wai Ling CheungCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Emily Ying Yang ChanJC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Eng Kiong YeohCentre for Health Systems and Policy Research, JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Samuel Yeung Shan WongJC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Chinese University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaintaining health of healthcare workers with vaccination is a major component of pandemic preparedness and acceptance of vaccinations is essential to its success. This study aimed to examine impact of the coronavirus disease 2019 (COVID-19) pandemic on change of influenza vaccination acceptance and identify factors associated with acceptance of potential COVID-19 vaccination.

methodA cross-sectional self-administered anonymous questionnaire survey was conducted among nurses in Hong Kong, China during 26 February and 31 March 2020. Their previous acceptance of influenza vaccination and intentions to accept influenza and COVID-19 vaccination were collected. Their relationship with work-related and other factors were examined using multiple multinomial logistic regressions.

resultsResponses from 806 participants were retrieved. More nurses changed from vaccination refusal to hesitancy or acceptance than those changed from acceptance to vaccination hesitancy or refusal (15.5% vs 6.8% among all participants, P < 0.001). 40.0% participants intended to accept COVID-19 vaccination, and those in private sector (OR: 1.67, 95%CI: 1.11-2.51), with chronic conditions (OR: 1.83, 95%CI: 1.22-2.77), encountering with suspected or confirmed COVID-19 patients (OR: 1.63, 95%CI: 1.14-2.33), accepted influenza vaccination in 2019 (OR: 2.03, 95%CI: 1.47-2.81) had higher intentions to accept it. Reasons for refusal and hesitation for COVID-19 vaccination included "suspicion on efficacy, effectiveness and safety", "believing it unnecessary", and "no time to take it".

conclusionWith a low level of COVID-19 acceptance intentions and high proportion of hesitation in both influenza and COVID-19 vaccination, evidence-based planning are needed to improve the uptake of both vaccinations in advance of their implementation. Future studies are needed to explore reasons of change of influenza vaccination acceptance, look for actual behaviour patterns of COVID-19 vaccination acceptance and examine effectiveness of promotion strategies.

Indexed as

AdolescentAdultAge FactorsBetacoronavirusCoronavirus InfectionsCOVID-19COVID-19 VaccinesCross-Sectional StudiesFemaleHealth PersonnelHong KongHumansInfluenza, HumanInfluenza VaccinesIntentionMaleCOVID-19 VaccinesInfluenza VaccinesViral VaccinesCoronavirus disease 2019Influenza vaccinesNursesVaccinationVaccine acceptance

Identifiers

PMID32980199
PMCPMC7834255
OpenAlexW3086668930

What OpenQuestion holds

Textmetadata
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.