Evidence map›Paper›PMID 37002340›Full record

ArticleScientific reports2023

The COVID-19 vaccination decision-making preferences of elderly people: a discrete choice experiment.

Yuhan Chen, Jimeng Wang, Meixi Yi, Hongteng Xu, Hailun Liang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
3.3field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Pooled it
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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

5 authors at 1 institution in 1 country.

Yuhan ChenSchool of Public Administration and Policy, Renmin University of China, Beijing, 100872, China.
Jimeng WangSchool of Philosophy, Renmin University of China, Beijing, China.
Meixi YiSchool of Public Administration and Policy, Renmin University of China, Beijing, 100872, China.
Hongteng XuGaoling School of Artificial Intelligence, Renmin University of China, Beijing, China.
Hailun LiangSchool of Public Administration and Policy, Renmin University of China, Beijing, 100872, China. hliang@ruc.edu.cn.
Renmin University of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is a continuing threat to global public health security. For elderly people, timely and effective vaccination reduces infection rates in this group and safeguards their health. This paper adopted an offline Discrete Choice Experiment (DCE) to research the preference for COVID-19 vaccination amongst Chinese adults aged 50 years and above. Through multinomial logistic regression analysis, our DCE leverages five attributes-the risk of adverse reactions, protective duration, injection doses, injection period, and effectiveness-each of which is split into three to four levels. The risk of adverse reaction and the protective duration were demonstrated to be determinants of vaccination preference. Moreover, it was found that socio demographic factors like region, self-health assessment and the number of vaccinated household members can strengthen or weaken the effects of vaccine attributes. In conclusion, the preferences of the elderly population should be considered when developing COVID-19 vaccination programs for this population in China. Accordingly, the results may provide useful information for policymakers to develop tailored, effectively vaccination strategies.

Indexed as

COVID-19VaccinesAdultAgedChoice BehaviorCOVID-19 VaccinesHumansVaccinationCOVID-19 VaccinesVaccines

Identifiers

PMID37002340
PMCPMC10063931
OpenAlexW4362471446

What Socratic 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 Socratic graph.