Evidence map›Paper›PMID 38336858›Full record

ArticleScientific reports2024

Assortative mixing of opinions about COVID-19 vaccination in personal networks.

Marian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, José Luis Molina, Marius Geantă

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
22.6field-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

10 citing papers in PubMed, 20 citations in OpenAlex.

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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 4 institutions in 7 countries.

Marian-Gabriel HânceanDepartment of Sociology, University of Bucharest, Panduri, 90-92, 050663, Bucharest, Romania. gabriel.hancean@sas.unibuc.ro.
Jürgen LernerDepartment of Computer and Information Science, University of Konstanz, 78457, Konstanz, Germany.
Matjaž PercFaculty of Natural Sciences and Mathematics, University of Maribor, Koroška Cesta 160, 2000, Maribor, Slovenia.
José Luis MolinaGRAFO - Department of Social and Cultural Anthtropology, Universitat Autònoma de Barcelona, 08193, Bellaterra (Cerdanyola del Vallès), Barcelona, Spain.
Marius GeantăCenter for Innovation in Medicine, Th. Pallady 42J, 032266, Bucharest, Romania.
China Medical University Hospital · TWRWTH Aachen University · DEUniversitat Autònoma de Barcelona · ESUniversity of Bucharest · RO

Funding

Deutsche Forschungsgemeinschaft 321869138Javna Agencija za Raziskovalno Dejavnost RS P1-0403Research Institute, University of Bucharest 8405 / 22.07.2023Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii PN-III-P4-ID-PCE-2020-2828
6 · The paper itself

Abstract

Many countries worldwide had difficulties reaching a sufficiently high vaccination uptake during the COVID-19 pandemic. Given this context, we collected data from a panel of 30,000 individuals, which were representative of the population of Romania (a country in Eastern Europe with a low 42.6% vaccination rate) to determine whether people are more likely to be connected to peers displaying similar opinions about COVID-19 vaccination. We extracted 443 personal networks, amounting to 4430 alters. We estimated multilevel logistic regression models with random-ego-level intercepts to predict individual opinions about COVID-19 vaccination. Our evidence indicates positive opinions about the COVID-19 vaccination cluster. Namely, the likelihood of having a positive opinion about COVID-19 vaccination increases when peers have, on average, a more positive attitude than the rest of the nodes in the network (OR 1.31, p < 0.001). We also found that individuals with higher education and age are more likely to hold a positive opinion about COVID-19 vaccination. With the given empirical data, our study cannot reveal whether this assortative mixing of opinions is due to social influence or social selection. However, it may nevertheless have implications for public health interventions, especially in countries that strive to reach higher uptake rates. Understanding opinions about vaccination can act as an early warning system for potential outbreaks, inform predictions about vaccination uptake, or help supply chain management for vaccine distribution.

Indexed as

COVID-19COVID-19 VaccinesBiological TransportHumansPandemicsVaccinationCOVID-19 Vaccines

Identifiers

PMID38336858
PMCPMC10858210
OpenAlexW4391678359

What OpenQuestion holds

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LicenceCC BY
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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.