What Predicts Adherence to Governmental COVID-19 Measures among Danish Students?

Research output: Contribution to journalJournal articleResearchpeer-review

Documents

  • Gabriele Berg-Beckhoff
  • Julie Dalgaard Guldager
  • Pernille Tanggaard Andersen
  • Christiane Stock
  • Jervelund, Signe Smith

Knowledge on compliance with governmental recommendations in combating the spread of COVID-19 in different groups is important to target efforts. This study investigated the adherence to the governmental implemented COVID-19 measures and its predictors in Danish university students, a not-at-risk group for COVID-19 mortality and normally characterized by many social contacts. As part of the COVID-19 International Student Wellbeing Study, a survey on socio-demographic situation, study information, living arrangements, lifestyle behaviors, stress, questions about COVID-19 infection and knowledge and concern about COVID-19 infection was sent via email to relevant university students in Denmark in May, 2020 (n = 2.945). Stepwise multiple linear regression analysis was employed. Our results showed that around 60% of the students were not concerned about COVID-19, while 68% reported that they followed governmental measures. The main facilitators for following the recommendations were older age, concern about COVID-19 and depression, while barriers were living in a student hall, being physical active or reporting mental stress. Only 9% of the variation in adhering to governmental recommendations could be explained by the analyzed predictors. Results may inform health communication. Emotionally appealing information rather than knowledge-based information may be more effective in motivating students to follow COVID-19 measures.

Original languageEnglish
Article number1822
JournalInternational Journal of Environmental Research and Public Health
Volume18
Issue number4
Number of pages13
ISSN1661-7827
DOIs
Publication statusPublished - 2021

    Research areas

  • COVID-19, risk behavior, students, governmental recommendation predictors

Number of downloads are based on statistics from Google Scholar and www.ku.dk


No data available

ID: 258135903