JOURNAL ARTICLE

Solution‐Focused Brief Therapy for Improving Couple Dyadic Relationships in Iran: A Systematic Review.

  • Published In: Journal of Marital & Family Therapy, 2025, v. 51, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Naseh, Mitra; Badiezadeh, Sahar; Rafieifar, Maryam; Taridashti, Sarvenaz; Reddy, Swathi M.; Panisch, Lisa S. 3 of 3

Abstract

Despite the popularity of Solution‐Focused Brief Therapy (SFBT) in Iran, the existing literature synthesis has limitations due to the reliance on studies published primarily in Farsi. This systematic review addresses these gaps by synthesizing and evaluating the effectiveness of SFBT on the marital outcomes of couples in Iran, incorporating both Farsi and English sources. The search for this review yielded 1523 records, from which 26 randomized controlled trials were included. The participants across the included studies (n = 1110) were predominantly married women and couples experiencing marital discord, from varied educational backgrounds across multiple Iranian cities. SFBT, primarily delivered in a group format, demonstrated medium to large effect sizes in improving marital outcomes such as dyadic adjustment, satisfaction, and intimacy. However, the presence of bias in study design and reporting necessitates caution in interpreting findings. This review highlights the potential of SFBT to improve marital relationships within the Iranian context. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Marital & Family Therapy. 2025/01, Vol. 51, Issue 1, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:0194-472X
  • DOI:10.1111/jmft.12758
  • Accession Number:184014871
  • Copyright Statement:Copyright of Journal of Marital & Family Therapy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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