Predicting interpersonal dynamics during the COVID-19 pandemic using machine learning: A cross-national longitudinal study.
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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.
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