Evidence map›Paper›PMID 34676821›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2021

The four weeks before lockdown during the COVID-19 pandemic in Germany: a weekly serial cross-sectional survey on risk perceptions, knowledge, public trust and behaviour, 3 to 25 March 2020.

Cornelia Betsch, Lars Korn, Tanja Burgard, Wolfgang Gaissmaier, Lisa Felgendreff, Sarah Eitze, Philipp Sprengholz, Robert Böhm, Volker Stollorz, Michael Ramharter and 6 more

Abstract read
In one paragraph

Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Individual and collective protective responses during the early phase of the COVID-19 pandemic in 10 different countries: Results from the EUCLID online survey.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
  5. Article
  6. Personal Protective Measures during the COVID-19 Pandemic in Germany.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
  7. Review
  8. Article
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

16 authors.

Cornelia BetschUniversity of Erfurt, Erfurt, Germany.
Lars KornUniversity of Erfurt, Erfurt, Germany.
Tanja BurgardLeibniz Institute for Psychology Information and Documentation, Trier, Germany.
Wolfgang GaissmaierUniversity of Konstanz, Konstanz, Germany.
Lisa FelgendreffUniversity of Erfurt, Erfurt, Germany.
Sarah EitzeUniversity of Erfurt, Erfurt, Germany.
Philipp SprengholzUniversity of Erfurt, Erfurt, Germany.
Robert BöhmUniversity of Copenhagen, Copenhagen, Denmark.
Volker StollorzScience Media Center Germany gGmbH, Köln, Germany.
Michael RamharterDepartment of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine and I. Dep. of Medicine University Medical Center, Hamburg-Eppendorf, Germany.
Nikolai PromiesKarlsruhe Institute of Technology, Karlsruhe, Germany.
Freia De BockFederal Centre for Health Education, Köln, Germany.
Philipp SchmidUniversity of Erfurt, Erfurt, Germany.
Britta RennerUniversity of Konstanz, Konstanz, Germany.
Lothar H WielerRobert Koch Institute, Berlin, Germany.
Michael BosnjakRobert Koch Institute, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BackgroundDuring the COVID-19 pandemic, public perceptions and behaviours have had to adapt rapidly to new risk scenarios and radical behavioural restrictions.AimTo identify major drivers of acceptance of protective behaviours during the 4-week transition from virtually no COVID-19 cases to the nationwide lockdown in Germany (3-25 March 2020).MethodsA serial cross-sectional online survey was administered weekly to ca 1,000 unique individuals for four data collection rounds in March 2020 using non-probability quota samples, representative of the German adult population between 18 and 74 years in terms of age × sex and federal state (n = 3,910). Acceptance of restrictions was regressed on sociodemographic variables, time and psychological variables, e.g. trust, risk perceptions, self-efficacy. Extraction of homogenous clusters was based on knowledge and behaviour.ResultsAcceptance of restrictive policies increased with participants' age and employment in the healthcare sector; cognitive and particularly affective risk perceptions were further significant predictors. Acceptance increased over time, as trust in institutions became more relevant and trust in media became less relevant. The cluster analysis further indicated that having a higher education increased the gap between knowledge and behaviour. Trust in institutions was related to conversion of knowledge into action.ConclusionIdentifying relevant principles that increase acceptance will remain crucial to the development of strategies that help adjust behaviour to control the pandemic, possibly for years to come. Based on our findings, we provide operational recommendations for health authorities regarding data collection, health communication and outreach.

Indexed as

COVID-19PandemicsAdultCommunicable Disease ControlCross-Sectional StudiesGermanyHumansPerceptionSARS-CoV-2Surveys and QuestionnairesTrustbehavioural insightscluster analysiscoronavirusCOVID-19knowledge-behaviour gaplockdownpolicy acceptance

Identifiers

PMID34676821
PMCPMC8532505

What OpenQuestion 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 OpenQuestion graph.