During medical pandemics, protective behaviors need to be motivated by effective communication, where finding predictors of fear and perceived health is of critical importance. The varying trajectories of the COVID-19 pandemic in different countries afford the opportunity to assess the unique influence of ‘macro-level’ environmental factors and ‘micro-level’ psychological variables on both fear and perceived health. Here, we investigate predictors of fear and perceived health using machine learning as lockdown restrictions in response to the COVID-19 pandemic were introduced in Austria, Spain, Poland and Czech Republic. Over a seven-week period, 533 participants completed weekly self-report surveys which measured the target variables subjective fear of the virus and perceived health, in addition to potential predictive variables related to psychological factors, social factors, perceived vulnerability to disease (PVD), and economic circumstances. Viral spread, mortality and governmental responses were further included in the analysis as potential environmental predictors. Results revealed that our models could accurately predict fear of the virus (accounting for approximately 23% of the variance) using predictive factors such as worrying about shortages in food supplies and perceived vulnerability to disease (PVD), where interestingly, environmental factors such as spread of the virus and governmental restrictions did not contribute to this prediction. Furthermore, our results revealed that perceived health could be predicted using PVD, physical exercise, attachment anxiety and age as input features, albeit with smaller effect sizes. Taken together, our results emphasize the importance of ‘micro-level’ psychological factors, as opposed to ‘macro-level’ environmental factors, when predicting fear and perceived health, and offer a starting point for more extensive research on the influences of pathogen threat and governmental restrictions on the psychology of fear and health.

The COVID-19 pandemic along with the restrictions that were introduced within Europe starting in spring 2020 allows for the identification of predictors for relationship quality during unstable and stressful times. The present study began as strict measures were enforced in response to the rising spread of the COVID-19 virus within Austria, Poland, Spain and Czech Republic. Here, we investigated quality of romantic relationships among 313 participants as movement restrictions were implemented and subsequently phased out cross-nationally. Participants completed self-report questionnaires over a period of 7 weeks, where we predicted relationship quality and change in relationship quality using machine learning models that included a variety of potential predictors related to psychological, demographic and environmental variables. On average, our machine learning models predicted 29% (linear models) and 22% (non-linear models) of the variance with regard to relationship quality. Here, the most important predictors consisted of attachment style (anxious attachment being more influential than avoidant), age, and number of conflicts within the relationship. Interestingly, environmental factors such as the local severity of the pandemic did not exert a measurable influence with respect to predicting relationship quality. As opposed to overall relationship quality, the change in relationship quality during lockdown restrictions could not be predicted accurately by our machine learning models when utilizing our selected features. In conclusion, we demonstrate cross-culturally that attachment security is a major predictor of relationship quality during COVID-19 lockdown restrictions, whereas fear, pathogenic threat, sexual behavior, and the severity of governmental regulations did not significantly influence the accuracy of prediction.

In times of medical pandemics, protective behaviors need to be motivated by effective communication, and finding predictors of perceived threat and subjective health is of importance. The varying trajectories of the COVID-19 pandemic in different countries present the opportunity to include the influence of environmental factors in such analyses. Here, we investigate viral spread, governmental responses and interpersonal differences as potential predictors of fear of the virus and perceived health. We identify interpersonal factors that are important predictors, whereas environmental conditions (case/death counts, governmental response, country of residence) do not add predictive value.Critically, our machine-learning analysis and the predictive nature of our models together with the finding that nationality does not contribute to predicting our target variables promises a good generalizability for Western cultures.

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The COVID-19 pandemic presents a global medical stressor and brought about unprecedented governmental regulations. The present study investigates the romantic relationships of 350 participants from Austria, Poland, Spain and Czech Republic as movement restrictions were implemented and phased out in those countries. Participants filled in questionnaires over a period of seven weeks, and we predicted relationship using machine learning models that include a variety of potential predictors related to psychological, demographic and environmental factors.On average, our models predict 32 percent of the variance of relationship quality, the most important predictors being attachment security and amount of fights. We demonstrate that attachment security is a major predictor of relationship quality in these unstable times, whereas sexual behavior, fear, pathogenic threat and the severity of governmental regulations do not influence these variables. Statement of relevanceThe COVID-19 pandemic along with the curfews that were introduced in Europe in spring 2020 presents a unique opportunity to study the effects of environmental factors on intimate relationships and identify factors that contribute to relationship quality under stressful conditions. The present study took place precisely as strict measures in response to the rising spread of the virus were adopted in Austria, Poland, Spain and Czech Republic and ends as the main restrictions were dropped. We examine predictors of relationship quality and sexual behavior in these unstable times, and found that attachment security is one of the main predictors, whereas fear of the virus or environmental factors such as the stringency of curfews do not hold any predictive value.The cross-cultural composition of our sample and the fact that our models are evaluated by their performance on unknown subjects makes these findings relatively generalizable for western cultures.