Predicting coronavirus anxiety based on problem-solving styles and distress tolerance in working women

Abstract

This research was conducted to determine the anxiety of the coronavirus based on distress tolerance and problem-solving styles in working women of Yasouj city. The current research design was descriptive and correlational. The research's statistical population was comprised of all working women of Yasouj city in 2020. Based on Morgan's table, 364 people were selected and studied from the statistical population as a one-stage cluster random sampling. Distress tolerance questionnaires of Simmons and Gaher (2005), the problem-solving strategies of Cassidy and Long (1996), and the anxiety of coronavirus Alipour et al. (2018) were used to collect data. After collecting and extracting the data, the participants' scores were analyzed using Pearson's correlation coefficient, multiple regression analysis, and SPSS statistical software. The correlation coefficient results showed that Corona's anxiety correlates negatively with constructive problem-solving style and distress tolerance and significantly positively correlated with non-constructive problem-solving style. Also, the multivariable regression results showed that the constructive problem-solving style with a beta coefficient of 0.11, the non-constructive problem-solving style with a beta coefficient of -0.76, and distress tolerance with a beta coefficient of 0.20 could predict corona anxiety in working women because problem-solving styles and distress tolerance can be a good predictor for anxiety of corona disease. Corona disease anxiety can be reduced by examining practical problem-solving strategies and increasing distress tolerance.