Overestimation of COVID-19 Vaccination Coverage in Population Surveys Due to Social Desirability Bias : Results of an Experimental Methods Study in Germany

Lade...
Vorschaubild
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2022
Autor:innen
Mayerl, Jochen
Andersen, Henrik K.
Junkermann, Justus
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Gold
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Socius : Sociological Research for a Dynamic World. Sage Publishing. 2022, 8, pp. 1-8. ISSN 2378-0231. eISSN 2378-0231. Available under: doi: 10.1177/23780231221094749
Zusammenfassung

In Germany, studies have shown that official coronavirus disease 2019 (COVID-19) vaccination coverage estimated using data collected directly from vaccination centers, hospitals, and physicians is lower than that calculated using surveys of the general population. Public debate has since centered on whether the official statistics are failing to capture the actual vaccination coverage. The authors argue that the topic of one’s COVID-19 vaccination status is sensitive in times of a pandemic and that estimates based on surveys are biased by social desirability. The authors investigate this conjecture using an experimental method called the item count technique, which provides respondents with the opportunity to answer in an anonymous setting. Estimates obtained using the item count technique are compared with those obtained using the conventional method of asking directly. Results show that social desirability bias leads some unvaccinated individuals to claim they are vaccinated. Conventional survey studies thus likely overestimate vaccination coverage because of misreporting by survey respondents.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
300 Sozialwissenschaften, Soziologie
Schlagwörter
COVID-19, vaccine coverage, sensitive topics, social desirability, item count technique
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690WOLTER, Felix, Jochen MAYERL, Henrik K. ANDERSEN, Theresa WIELAND, Justus JUNKERMANN, 2022. Overestimation of COVID-19 Vaccination Coverage in Population Surveys Due to Social Desirability Bias : Results of an Experimental Methods Study in Germany. In: Socius : Sociological Research for a Dynamic World. Sage Publishing. 2022, 8, pp. 1-8. ISSN 2378-0231. eISSN 2378-0231. Available under: doi: 10.1177/23780231221094749
BibTex
@article{Wolter2022Overe-57431,
  year={2022},
  doi={10.1177/23780231221094749},
  title={Overestimation of COVID-19 Vaccination Coverage in Population Surveys Due to Social Desirability Bias : Results of an Experimental Methods Study in Germany},
  volume={8},
  issn={2378-0231},
  journal={Socius : Sociological Research for a Dynamic World},
  pages={1--8},
  author={Wolter, Felix and Mayerl, Jochen and Andersen, Henrik K. and Wieland, Theresa and Junkermann, Justus}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/57431">
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-05-05T10:42:48Z</dcterms:available>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/34"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57431/3/Wolter_2-3l8cwvsxnf9v4.pdf"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:contributor>Junkermann, Justus</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/34"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/57431"/>
    <dc:creator>Wieland, Theresa</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <dcterms:abstract xml:lang="eng">In Germany, studies have shown that official coronavirus disease 2019 (COVID-19) vaccination coverage estimated using data collected directly from vaccination centers, hospitals, and physicians is lower than that calculated using surveys of the general population. Public debate has since centered on whether the official statistics are failing to capture the actual vaccination coverage. The authors argue that the topic of one’s COVID-19 vaccination status is sensitive in times of a pandemic and that estimates based on surveys are biased by social desirability. The authors investigate this conjecture using an experimental method called the item count technique, which provides respondents with the opportunity to answer in an anonymous setting. Estimates obtained using the item count technique are compared with those obtained using the conventional method of asking directly. Results show that social desirability bias leads some unvaccinated individuals to claim they are vaccinated. Conventional survey studies thus likely overestimate vaccination coverage because of misreporting by survey respondents.</dcterms:abstract>
    <dc:contributor>Mayerl, Jochen</dc:contributor>
    <dc:language>eng</dc:language>
    <dc:creator>Junkermann, Justus</dc:creator>
    <dc:creator>Andersen, Henrik K.</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57431/3/Wolter_2-3l8cwvsxnf9v4.pdf"/>
    <dc:contributor>Andersen, Henrik K.</dc:contributor>
    <dcterms:issued>2022</dcterms:issued>
    <dc:creator>Wolter, Felix</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43613"/>
    <dc:contributor>Wieland, Theresa</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43613"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-05-05T10:42:48Z</dc:date>
    <dcterms:title>Overestimation of COVID-19 Vaccination Coverage in Population Surveys Due to Social Desirability Bias : Results of an Experimental Methods Study in Germany</dcterms:title>
    <dc:contributor>Wolter, Felix</dc:contributor>
    <dc:creator>Mayerl, Jochen</dc:creator>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Ja
Diese Publikation teilen