Predicting Emotional Divorce Based on Differentiation with the Mediation of Communication Patterns




Objective:  The current study aimed to predict emotional divorce based on differentiation with the mediation of communication patterns among women attending counseling and psychology centers.

Methods and Materials: The present study quantitative research. The research design is descriptive-correlational, conducted using path analysis method. The study population consisted of women experiencing emotional divorce visiting counseling and psychology centers (both private and public) in District 2 of Tehran in the year 2020. A total of 368 individuals were selected using convenience sampling method and responded to the Gottman Emotional Divorce questionnaire (2008), the Skowron and Friedlander Differentiation Scale (1998), and the Christensen and Sullaway Communication Patterns Questionnaire (1984). The data were analyzed using structural equation modeling.

Findings: According to the results, the direct path coefficients of differentiation and communication patterns to the emotional divorce of married women are significant (p < 0.05). The direct path coefficients from differentiation to constructive reciprocal communication and avoidant reciprocal communication are significant (p < 0.05). The results of the bootstrap test indicate the significance of the indirect pathways between these variables. This result indicates the significance of the mediating role of communication patterns in the relationship between differentiation and emotional divorce (p < 0.05).

Conclusion: The results showed that constructive reciprocal communication, avoidant reciprocal communication, and expectation/withdrawal communication mediate the relationship between differentiation and emotional divorce.


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How to Cite

Ahmadi, E. ., Jahangir, P., & Niknam, M. . (2024). Predicting Emotional Divorce Based on Differentiation with the Mediation of Communication Patterns. Journal of Adolescent and Youth Psychological Studies (JAYPS), 5(2), 105-113.

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