Using machine learning to unveil relevant predictors of adherence to recommended health-protective behaviors during the COVID-19 pandemic in Denmark
- Author(s)
- Lau Lilleholt, Gretchen B Chapman, Robert Böhm, Ingo Zettler
- Abstract
What were relevant predictors of individuals' proclivity to adhere to recommended health-protective behaviors during the COVID-19 pandemic in Denmark? Applying machine learning (namely, lasso regression) to a repeated cross-sectional survey spanning 10 months comprising 25 variables (Study 1; N = 15,062), we found empathy toward those most vulnerable to COVID-19, knowledge about how to protect oneself from getting infected, and perceived moral costs of nonadherence to be strong predictors of individuals' self-reported adherence to recommended health-protective behaviors. We further explored the relations between these three factors and individuals' self-reported proclivity for adherence to recommended health-protective behaviors as they unfold between and within individuals over time in a second study, a Danish panel study comprising eight measurement occasions spanning eight months (N = 441). Results of this study suggest that the relations largely occurred at the trait-like interindividual level, as opposed to at the state-like intraindividual level. Together, the findings provide insights into what were relevant predictors for individuals' overall level of adherence to recommended health-protective behaviors (in Denmark) as well as how these predictors might (not) be leveraged to promote public adherence in future epidemics or pandemics.
- Organisation(s)
- Department of Occupational, Economic and Social Psychology
- External organisation(s)
- University of Copenhagen, Carnegie Mellon University
- Journal
- Applied Psychology: Health and Well-Being
- Volume
- 16
- Pages
- 1819-1839
- No. of pages
- 21
- ISSN
- 1758-0846
- DOI
- https://doi.org/10.1111/aphw.12563
- Publication date
- 2024
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 501021 Social psychology
- Keywords
- ASJC Scopus subject areas
- Applied Psychology
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/d7691075-00b9-48cd-b3e2-49dfffe233dd