Predicting Quality of Life Based on Early Maladaptive Schemas and Personality Traits in Women with Breast Cancer

Document Type : Original Article

Authors

1 M.A., Department of psychology, Karaj branch, Islamic Azad University, Alborz, Iran.

2 Assistant Professor, Department of Psychology, Karaj Branch, Islamic Azad University, Karaj, Iran.

3 Assistant Professor, Department of psychology, Karaj branch, Islamic Azad University, Alborz, Iran.

Abstract

Background and Aim: Cancer is one of the most common diseases in the world, and more than 30,000 Iranians die of cancer every year. This study aimed to predict the quality of life based on early maladaptive schemas and personality traits in women with breast cancer.

Methods: The research method was descriptive-correlational. The statistical population of the study included all women with breast cancer, 240 women who were referred to Jam Hospital in Tehran in 2019, 144 people were selected by the available method. Data were obtained using the quality of life questionnaire, Young Schema Questionnaire (YSQ-SF), Personality Traits Questionnaire, and Early Ineffective Schema Questionnaire. Data were analyzed by Pearson correlation coefficient and linear regression using SPSS22 software.

Results: The results showed that the quality of life has a predictive role based on early maladaptive schemas and personality traits in women with breast cancer (p <0.001). The results of the regression coefficient show that quality of life can predict agreeableness (Beta=0.38), social isolation/alienation (Beta=-0.26), distress (Beta=-0.22), pleasantness (Beta=0.26), and obedience (Beta=0.17).

Conclusion: It can be concluded that the quality of life has a predictive role based on early maladaptive schemas and personality traits in women with breast cancer.

Keywords


Open Access Policy: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/

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