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A Structural Model for Predicting Post-Traumatic Growth Inventory (PTGI) Based on Personality Traits: Mediating Role of Resilience in Women with Breast Cancer
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Sima Babazadeh Namini    , Mohammad Reza Seirafi , Seyed Ahmad Elahi , Mehrdad Sabet |
| Assistant Professor, Dept. of Psychology, Islamic Azad University, Karaj , Msf_3@yahoo.com |
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Abstract: (1459 Views) |
Background: Human life is always accompanied by many crises and injuries. Impact or injury is an incident that can create a serious challenge to the individual. This study aims to present a structural model for predicting post-traumatic growth Inventory based on personality traits mediated by resilience in women with breast cancer.
Methods: This is a descriptive correlational study in which 200 women diagnosed with breast cancer admitted to Imam Hosein Hospital in Tehran and Imam Ali Hospital Complex of Alborz University of Medical Sciences were selected by convenience sampling method and tested in terms of personality traits, resilience and post-traumatic growth Inventory.
Results: Data were analyzed using structural equation modeling. This model contains three Predictor variable (extraversion, openness to experience, and conscientiousness), one mediating variable (resilience), and one criterion variable (post-traumatic growth Inventory). The results showed different direct and indirect effects of the variables. Some coefficients were significant at 99% confidence level while some others were not significant at 95% confidence level (the level of significance was greater than 0.05). Extroversion and openness to experience had the greatest and least effects on resilience, respectively. Moreover, resilience had the greatest effect on posttraumatic growth.
Conclusion: Resilience mediates extraversion and conscientiousness. Extraversion and conscientiousness affect post-traumatic growth Inventory. |
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| Keywords: Breast Cancer, Personality Traits, Post-Traumatic Growth Inventory, Resilience |
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Full-Text [PDF 2290 kb]
(518 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2021/07/11 | Accepted: 2021/05/31 | Published: 2021/05/31
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