From delta to omicron: The role of individual factors and social context in self-reported compliance with pandemic regulations and recommendations


As SARS-CoV-2 spreads especially when larger groups gather (e.g., at the workplace), it is crucial to understand compliance with regulations and recommendations in such settings. Using data from adults in Germany (N = 29,355) assessed between October 2021 and February 2022, we investigated factors associated with self-reported compliance in both private and working life and how these relate to each other. The results indicate that private compliance was stronger among older individuals and females; among those who worried more about the pandemic situation and assumed that infection was more severe; among those who trusted the government more; and among those who did not perceive public health measures as exaggerated. Private compliance was also associated with personality traits; in particular, individuals who followed regulations and recommendations were likely to be more introverted, conscientious, open, and agreeable. Compliance at work related to both private compliance and colleagues’ behaviors. Individuals whose private compliance was high also complied at work. However, when private compliance was low, compliance at work aligned with colleagues’ behaviors; that is, compliance at work was high when colleagues complied and low when they did not. The observed effects were stable over time. In summary, they suggest that compliance with regulations and recommendations depends on individual risk perception, trust in government, perception of required or recommended measures, and social norms. To promote protective behaviors in contexts where larger groups gather (including workplaces), making positive social norms more salient (e.g., by supporting role models) may prove especially useful.

Social Science and Medicine
Philipp Sprengholz
University of Bamberg
Robert W. Bruckmann
Robert W. Bruckmann
Master Student

Intrigued by human (health) behavior.

Marc Wiedermann
Marc Wiedermann
PostDoc / Data Scientist

Researcher and Data Scientist with strong interests in time series and network analysis, predictive models and low-dimensional dynamical systems for the spread of human behavior.

Dirk Brockmann
Dirk Brockmann

Head of Research on Complex Systems Group

Cornelia Betsch
University of Erfurt