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Record W2049483728 · doi:10.1111/jmft.12077

Predicting Change in Marital Satisfaction Throughout Emotionally Focused Couple Therapy

2014· article· en· W2049483728 on OpenAlexaff
Susan M. Johnson, Melissa Burgess Moser, Marie‐France Lafontaine, Stephanie A. Wiebe, Giorgio A. Tasca

Bibliographic record

VenueJournal of Marital and Family Therapy · 2014
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsOttawa HospitalMount Allison UniversityUniversity of Ottawa
Fundersnot available
KeywordsPsychologyMarital TherapyPsychotherapistAnxietyClinical psychologyMultilevel modelSession (web analytics)Attachment theoryPsychiatry

Abstract

fetched live from OpenAlex

Emotionally focused couple therapy (EFT) is an empirically validated approach to couple therapy that uses attachment theory to understand the needs and emotions of romantic partners. EFT is recognized as one of the most effective approaches to couple therapy, but to guide therapists in their use of EFT, a theoretically based model to predict change is needed. This study tested such a model by recruiting 32 couples, and 14 therapists who provided approximately 21 sessions of EFT. Couples completed self-report measures of marital satisfaction, attachment security, relationship trust, and emotional control at pre- and posttherapy and after each therapy session. Results of hierarchical linear modeling suggested that individuals higher on self-report attachment anxiety and higher levels of emotional control had greater change in marital satisfaction across EFT sessions. Assessing attachment security at the start of therapy will inform therapists of the emotion regulating strategies used by couples and may help couples achieve positive outcomes from EFT.

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)0.011
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.045
GPT teacher head0.359
Teacher spread0.314 · 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

Citations110
Published2014
Admission routes1
Has abstractyes

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