Using Reinforcement Sensitivity Theory to Predict COVID-19 Vulnerability: Data from Students in México and the US

The study assessed the capacity of revised Reinforcement Sensitivity Theory to predict COVID-19 vulnerability and outcome. A convenience sample of 1033 undergraduate students from Mexico and the US answered the RST-PQ and a COVID-19 symptom checklist. Data showed that FFFS and BIS are direct and significant predictors of the severity of COVID-19 symptoms; GDP is a significant and inverse predictor. Additionally, both RR and RI significantly differentiate between individuals that present COVID-19 infections, and those that do not. In general, the results only partially coincide with those produced on the issue by r-RST; however, they align well with scientific literature produced outside the framework. Apparently, individuals who score high in trait anxiety related scales of the RST-PQ will present worse COVID-19 infection symptoms. Additionally, individuals who score high in extroversion related scales of the RST-PQ, will have a higher probability of presenting a COVID-19 infection.