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Record W2936301778 · doi:10.4081/ripppo.2019.352

Ruptures and repairs of group therapy alliance. An untold story in psychotherapy research

2019· article· en· W2936301778 on OpenAlexaff
Gianluca Lo Coco, Giorgio A. Tasca, Paul L. Hewitt, Samuel F. Mikail, Dennis M. Kivlighan

Bibliographic record

VenueResearch in Psychotherapy Psychopathology Process and Outcome · 2019
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversity of British ColumbiaUniversity of Ottawa
Fundersnot available
KeywordsAllianceContext (archaeology)PsychotherapistGroup psychotherapyIntervention (counseling)Empirical researchMedicinePsychologyPsychiatryPolitical scienceEpistemologyLaw

Abstract

fetched live from OpenAlex

Although previous studies investigated the characteristics of therapeutic alliance in group treatments, there is still a dearth of research on group alliance ruptures and repairs. The model by Safran and Muran was originally developed to address therapeutic alliance in individual therapies, and the usefulness of this approach to group intervention needs to be demonstrated. Alliance ruptures are possible at member to therapist, member to member, member to group levels. Moreover, repairs of ruptures in group are quite complex, i.e., because other group members have to process the rupture even if not directly involved. The aim of the current study is to review the empirical research on group alliance, and to examine whether the rupture repair model can be a suitable framework for clinical understanding and research of the complexity of therapeutic alliance in group treatments. We provide clinical vignettes and commentary to illustrate theoretical and research aspects of therapeutic alliance rupture and repair in groups. Our colleague Jeremy Safran made a substantial contribution to research on therapeutic alliance, and the current paper illustrates the enduring legacy of this work and its potential application to the group therapy 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)0.011
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.152
GPT teacher head0.523
Teacher spread0.372 · 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 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

Citations24
Published2019
Admission routes1
Has abstractyes

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