Psychological, Not Environmental Factors Are Important

During pandemics, protective behavior must be motivated by effective communication. A critical factor in understanding a population’s response to such a threat is the fear it evokes, as fear both contributes to motivational protective responses, but can also lead to panic-driven behavior. In addition, lockdown measures affect well-being, making it important to identify protective factors that help maintain high perceived health levels during restrictions. An international team of researchers led by scientists from the University of Vienna has now identified psychological predictors of anxiety and health during the lockdowns. The result of the study, published in PLOS ONE: Individual psychological variables have a much better predictive power than environmental variables.

The current publication aims to identify predictors of anxiety and perceived health during home ordering in response to the COVID-19 pandemic. “In this way we can predict how different people and population groups will react to external threats and restrictions”, explains Stephanie Eder of the Faculty of Psychology.

Researchers from the University of Vienna, in collaboration with scientists from the University of Wroclaw (PL), University of Barcelona (ESP), Charles University and Jan Evangelista Purkyne University (CZ), examined 533 participants during the ‘first wave’ of the COVID-19 pandemic. 19 pandemic in Europe.

Using machine learning models, they identified psychological predictors of anxiety and health during the lockdowns. Anxiety can be predicted very well if concerns about supply shortages, perceived contagiousness for disease in general, germ aversion and infections in the immediate social sphere are taken into account. Predictors of perceived health include higher perceived infectivity for disease in general, attachment security, physical activity, and younger age; suggesting that older populations with high perceived infectivity and insecure attachment are most vulnerable in these uncertain times.

Interestingly, environmental variables such as the local severity of lockdown restrictions and mortality were not predictive of any of the target variables. “We could demonstrate the value of micro-level psychological factors relative to macro-scale environmental conditions in predicting a population’s response to a crisis and in designing behavioral interventions for specific target groups,” says Eder.

Reference: “Predicting anxiety and perceived health during the COVID-19 pandemic using machine learning: a transnational longitudinal study” by Stephanie Josephine Eder, David Steyrl, Michal Mikolaj Stefanczyk, Michał Pieniak, Judit Martínez Molina, Ondra Pešout, Jakub Binter, Patrick Smela, Frank Scharnowski, and Andrew A. Nicholson, March 11, 2021, PLOS ONE.
DOI: 10.1371/journaal.pone.0247997