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Record W4406882973 · doi:10.1080/10503307.2025.2454455

Effectiveness of emotion-focused therapy: Main results of a practice–research network study

2025· article· en· W4406882973 on OpenAlexaff
Uëli Kramer, Marielle Sutter, Julian Rubel, José Blanco Machinea, Catalina Woldarsky, Lars Auszra, Imke Herrmann, Martin Grosse Holtforth

Bibliographic record

VenuePsychotherapy Research · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversity of Windsor
FundersUniversité de Lausanne
KeywordsPsychotherapistPsychologyPsychoanalysis

Abstract

fetched live from OpenAlex

Background Emotion-Focused Therapy is one of the evidence-based psychotherapies for a range of psychological problems. While most evidence was gained from randomized controlled studies or process research at university settings, there is a need for more outcome research conducted within practitioner–researcher networks assessing the effectiveness of Emotion-Focused Therapy in private practice.Methods A total of N = 70 clients with a variety of psychiatric disorders have been included in the bi-national practitioner researcher network for Emotion-focused Therapy Switzerland–Germany. Symptom change was assessed using CORE-OM, BDI-II, IIP and WSAS. Therapist adherence was assessed by the self-reported version of the PCEPS. Pre–post-follow-up analyses were conducted using paired sample t-tests and hierarchical linear modeling.Results Pre–post-assessment shows small to medium effect sizes for all outcome measures (except for interpersonal problems which did not change). Symptom reduction is maintained for CORE, BDI and WSAS, and increased for IIP at 3 and 6 months follow-up. Therapist adherence is good to excellent in this sample.Conclusions Emotion-Focused Therapy is effective in the real-world practice, as suggested by the small to moderate effect sizes. The smaller effects found in the current study as compared to randomized controlled trials are consistent with the literature and suggest that EFT remains moderately effective when applied in a naturalistic context.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.121
GPT teacher head0.534
Teacher spread0.412 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations7
Published2025
Admission routes1
Has abstractyes

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