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The Clinical Representativeness of Couple Therapy Outcome Research

2007· review· en· W2167372714 on OpenAlexaff
John Wright, Stéphane Sabourin, Josianne Mondor, Pierre McDuff, Salima Mamodhoussen

Bibliographic record

VenueFamily Process · 2007
Typereview
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsNational Defence Medical CentreUniversité LavalDepartment of National DefenceUniversité de Montréal
Fundersnot available
KeywordsRepresentativeness heuristicGeneralizability theoryMarital TherapyOutcome (game theory)PsychologyClinical psychologyRating scaleClinical trialMedicineDevelopmental psychologySocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

The clinical representativeness of outcome studies is defined as the generalizability of recruitment processes, assessment/diagnostic procedures, treatment protocols, and therapeutic results from research settings to naturalistic treatment settings. The main goal of the present study was to examine the clinical representativeness of couple therapy in outcome studies. The data set was formed by 50 published clinical trials, including 34 couple therapy outcome studies for marital distress (CTMD) and 16 couple therapy outcome studies for comorbid relational and mental disorders (CTMD + C). The present findings showed that, overall, the clinical representativeness of couple therapy outcome studies is only fair (i.e., the mean global score is slightly lower than the midpoint of the rating scale used to assess representativeness). CTMD + C studies fared better than CTMD studies on many dimensions of clinical relevance. Studies in which pretherapy training was less intensive (for CTMD studies only), treatment was less structured, and therapists were more experienced showed larger effect sizes than those in which such was not the case.

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)0.490
metaresearch head score (Gemma)0.594
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.510
Threshold uncertainty score0.629

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4900.594
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0090.009
Science and technology studies0.0010.006
Scholarly communication0.0060.003
Open science0.0040.004
Research integrity0.0030.002
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 head0.725
GPT teacher head0.731
Teacher spread0.007 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreReview

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

Citations33
Published2007
Admission routes1
Has abstractyes

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