Overestimation of Covid-19 Vaccination Coverage in Population Surveys Due to Social Desirability Bias

Results of an Experimental Methods Study in Germany

Datos Bibliográficos

ID8020535
AutoresFelix Wolter (0000-0002-0686-8527, University of Konstanz), Jochen Mayerl (0000-0002-4599-9976, Chemnitz University of Technology, autor de correspondencia), Henrik Kenneth Andersen (0000-0001-6842-5337, Chemnitz University of Technology), Theresa Wieland (0009-0007-1336-4830, University of Konstanz), Justus Junkermann (Martin Luther University Halle-Wittenberg)
Año2022
Volumen8
Fecha de publicación2022-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSocius Sociological Research for a Dynamic World (JOURNAL)
Identificadores de la revistaISSN: 2378-0231 • E-ISSN: 2378-0231
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1177/23780231221094749
OpenAlexW4285114980
IdiomaEN
Citas recibidas14
Referencias citadas16

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

2019-20 coronavirus outbreak · Actuarial science · Coronavirus disease 2019 (COVID-19 · Disease · Econometrics · Economics · Environmental health · Infectious disease (medical specialty · Non-response bias · Outbreak · Pandemic · Population · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Social desirability · Social desirability bias · Social distance · Sociology · Statistics · Survey methodology · Vaccination · COVID-19 epidemiological studies · Demography · Mathematics · Medicine · Psychology · Social Psychology · Survey Sampling and Estimation Techniques · Vaccine Coverage and Hesitancy · Virology