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Record W3186310175 · doi:10.1111/jmft.12543

Somatic experience of emotion in emotionally focused couple therapy: Experienced trainer therapists' views and experiences

2021· article· en· W3186310175 on OpenAlexaff
Sari Kailanko, Stephanie A. Wiebe, Giorgio A. Tasca, Aarno Laitila, Robert Allan

Bibliographic record

VenueJournal of Marital and Family Therapy · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversity of OttawaSaint Paul University
FundersJyväskylän Yliopisto
KeywordsTrainerPsychologyPsychotherapistRelevance (law)Somatic cellClinical psychology

Abstract

fetched live from OpenAlex

In general, arousal of emotions is often felt and expressed as a somatic experience in the body. In Emotionally Focused Couple Therapy (EFT), the deepening of emotional experiencing enables therapeutic change. This research explores the experiences of eight experienced EFT trainer therapists regarding their somatic experiences in their work with couples. Using interpretative phenomenological analysis of transcribed in-depth interviews, this research data yielded three core themes that captured therapists' experiences of using their own and couples' somatic experiences in therapy: (1) the importance and relevance of somatic experiences, (2) therapists' use of their own somatic experiences, and (3) working with clients' somatic experiences. The findings suggest that therapists do focus on their own and couples' somatic experiences in their work with couples, and that EFT therapists could benefit from a map to guide therapists how to focus on felt, somatic experiences as a way of maintaining an emphasis on emotional experience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.338
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

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