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Record W2991932916 · doi:10.1111/jmft.12416

Short‐Term and Long‐Term Effects of Training in EFT: A Multinational Study in Spanish‐speaking Countries

2019· article· en· W2991932916 on OpenAlexaff
Martiño Rodríguez‐González, Maria Schweer‐Collins, Paul S. Greenman, Marie‐France Lafontaine, Maria-Dolores Fatás, Jonathan G. Sandberg

Bibliographic record

VenueJournal of Marital and Family Therapy · 2019
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of OttawaUniversité du Québec en Outaouais
Fundersnot available
KeywordsEmpathyMultinational corporationCompetence (human resources)PsychologyCompassionTraining (meteorology)Multilevel modelCultural competenceSample (material)Clinical psychologySocial psychologyPedagogyPolitical scienceGeography

Abstract

fetched live from OpenAlex

This study seeks to validate the cross-cultural effectiveness of emotionally focused couple therapy (EFT) training in a sample of Spanish-speaking clinicians. The 28-hr formalized training for EFT was offered in six different Spanish-speaking countries, covering Europe, North America, Central America, and South America. Two hundred and seven therapists of 14 different Spanish-speaking nationalities completed pre-training assessments, 153 of them completed post-training assessments, and 92 therapists also completed the follow-up assessment. Using multilevel growth modeling (MLM), results indicated that therapists experienced significant and positive changes in terms of EFT competence (knowledge and skill acquisition), mature empathy, self-compassion, and attachment over time. Implications for transnational EFT training, specifically in Spanish-speaking countries, are discussed.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.355
Teacher spread0.330 · 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 designObservational
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

Citations11
Published2019
Admission routes1
Has abstractyes

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