A Model for Predicting Emotional Divorce Based on Emotional Literacy, Coping Styles, Quality of Life, and Emotion Seeking with Emotion Regulation Mediation

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction

The purpose of this study was to present a model for predicting emotional divorce based on emotional literacy, coping styles, quality of life, and emotion-seeking through mediating emotion regulation.

Methods

The purpose of this study was descriptive-correlational in terms of purpose and structural model approach. A total of 350 women were selected from the community of married women employed in public primary schools in Tehran. Data were collected using Gutman's Emotional Divorce Questionnaire, Varouchrion's Quality of Life, Lazarus-Folkman Coping Styles, Zuckerman's Emotionalism Questionnaire, Iranian-Iranian Chemical Family Functioning Questionnaire, and Graz's Emotion Regulation Difficulty Questionnaire.

Results

Regression tests showed that emotional literacy and quality of life had a negative effect on emotional divorce. Emotional seeking, emotion regulation, and avoidance style have a positive impact on emotional divorce. Emotional literacy with -0.37 has the greatest impact on emotional divorce. Indirect effect coefficients mediated by emotion regulation show that avoidance and avoidance-avoidance have a positive effect on emotional divorce. Confrontation, social support, quality of life, and responsibility have indirect negative impact coefficients, which means that they have a negative impact on emotional divorce mediated by emotion regulation. The two variables of avoidance-avoidance and quality of life have both direct and indirect effects on emotional divorce.

Conclusion

There is a relationship between emotional literacy, coping styles, quality of life, and emotion-seeking with emotional divorce that can mediate this relationship.

Language:
English
Published:
Medical Journal of Mashhad University of Medical Sciences, Volume:62 Issue: 6, 2019
Pages:
388 to 402
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