Main content
Predicting interpersonal dynamics during the COVID-19 pandemic using machine learning: A cross-national longitudinal study.
- Stephanie J. Eder
- Michał Stefańczyk
- Michał Pieniak
- Judit Martínez Molina
- Ondra Pešout
- Jakub Binter
- Frank Scharnowski
- David Steyrl
- Andrew Nicholson
Date created: | Last Updated:
: DOI | ARK
Creating DOI. Please wait...
Category: Project
Description: This project surveyed 533 adult participants over a seven-week period in spring 2020, as lockdown measures were implemented in Austria, Poland, Spain and Czech Republic. Four aspects and subsets of the dataset are discussed in four peer-reviewed publications: 1) 'Predicting fear and perceived health during the COVID-19 pandemic using machine learning: A cross-national longitudinal study'. PLOS ONE. https://doi.org/10.1371/journal.pone.0247997 2) ‘Securing your relationship – Quality of intimate relationships and sexual behavior during the COVID-19 pandemic can be predicted by attachment security’. Frontiers in Psychology https://doi.org/10.3389/fpsyg.2021.647956 3) 'Food insecurity, hoarding behavior, and environmental harshness do not predict weight changes during the COVID-19 pandemic.' Human Ethology. https://doi.org/10.22330/he/35/122-136 4)'Danger and Strangers – Pathogenic threat, perceived vulnerability and fear do not predict ethnocentric orientations during the COVID-19 pandemic'. Human Ethology. https://doi.org/10.22330/he/36/125-137 Authors: Eder, S.J.,Stefańczyk,M.M., Pieniak, M., Martínez,J., Pešout, O., Binter, J., Smela, P., Scharnowski,F., Steyrl, D., Nicholson, A Here, we publish preprints, the collected data and more detailed information on the questions in our surveys.
Add important information, links, or images here to describe your project.
Files
Files can now be accessed and managed under the Files tab.