Predicting Corona anxiety based on the quality of life and parenting practices in women
Keywords:
Parenting methods, quality of life, Corona anxiety, working womenAbstract
Women are always a source of encouragement and a symbol of patience in the home and families. However, in modern society, due to the changing roles, they are also engaged in work and activities in society in addition to the family. Sometimes, due to mental pressure and much communication with clients in the work environment, they suffer a lot of worry and anxiety due to the conflict with the coronavirus. Therefore, the current research aimed to predict the anxiety of Corona based on the quality of life and parenting methods in the working women of Arak city. The research is descriptive-correlation type. The statistical population of this research consists of all the women of Arak city. The available method was used to select the sample, and the sample number of 150 working women was selected. The Alipoor Corona Virus Anxiety Scale, World Health Organization (WHO) Quality of Life Questionnaire, and Bamrind Parenting Practices Questionnaire were used to collect data. Data analysis has been done using descriptive and inferential statistics such as Pearson's correlation coefficient and multiple regression. The research findings showed that the quality of life has a significant negative (inverse) relationship with Corona anxiety. Among parenting styles, the authoritarian parenting style has a significant direct relationship with Corona anxiety, the logical, decisive parenting style has a significant negative relationship with Corona anxiety, and finally, no significant relationship was observed with the permissive parenting style with Corona anxiety. According to the obtained results, quality of life and authoritarian parenting style had the highest predicting power of Corona anxiety. As a result, it is suggested that women and their families be informed about this issue with proper planning and training to minimize the anxiety of Corona.
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Copyright (c) 2022 Alireza Rezaei, Mohammadreza Ghanati, Davood Taghvaei (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.