Using Micro-analyzing Tools to Investigate Therapist Skills in Emotionally Focused Couples Therapy With Couples in a High-Conflict Relationship.
Published In: Journal of Systemic Therapies, 2023, v. 42, n. 1. P. 74 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Karakurt, Gunnur; Katta, Pranaya; Apte, Sarah; Choi, Jason; Doan, Chi; Gole, Sarin; Jordan, Sara 3 of 3
Abstract
The study focuses on the initial phase of emotionally focused therapy (EFT) and explores techniques and skills therapists employ to break and de-escalate conflictual cycles in relationships. Using micro-analysis, the researchers examined a 50-minute therapy session with a couple in a high-conflict relationship that was conducted by Dr. Susan Johnson. The research team identified and classified the therapist's skills with moment-by-moment interactional processes. A tiering system was developed to examine skills. A total of 404 therapist skills were analyzed. We observed reflecting 90 times, reframing 84 times, cycle work 56 times, validating 50 times, asking evocative questions 48 times, accessing underlying emotions 32 times, heightening emotions 28 times, and enactmentlike skills 16 times. Results showed that the therapist combined active listening methods with EFT-specific strategies such as accessing underlying emotions, highlighting emotions, tracking interactional cycles, and facilitating communication via enactments. Findings are discussed along with implications for clinical training. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Systemic Therapies. 2023/03, Vol. 42, Issue 1, p74
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2023
- ISSN:1195-4396
- DOI:10.1521/jsyt.2023.42.1.74
- Accession Number:169712226
- Copyright Statement:Copyright of Journal of Systemic Therapies is the property of Guilford Publications Inc. 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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