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Record W2112028238 · doi:10.1521/jsyt.23.2.18.36644

Between-Session Change in Solution-Focused Therapy: A Replication

2004· article· en· W2112028238 on OpenAlexvenueno aff
Margarita Herrero de Vega, Mark Beyebach

Bibliographic record

VenueJournal of Systemic Therapies · 2004
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)Deconstruction (building)Replication (statistics)MillerPsychotherapistPsychologySolution focused brief therapyComputer scienceMedicineWorld Wide WebEngineeringBiology

Abstract

fetched live from OpenAlex

This paper presents a replication of the Reuterlov, Lofgren, Nordstrom, Ternstrom, and Miller study (2000) on the stability of clients' descriptions of improvement during solution-focused therapy. Our replication confirmed that the great majority of clients who report improvements at the outset of a session tend to increase their answer to the scaling question at the end of the interview. We also confirmed Reuterlov et al.'s fnding that when clients begin the session without reporting improvements, they tend to not see improvements at the end of it, in spite of their therapists' best efforts to “deconstruct” their initial description. However, our findings are less clear-cut than those of the Swedish team, and suggest that in some occasions (37.5% in our study, as opposed to 13% in the original paper) deconstruction may pay off as a therapeutic strategy, helping clients who initially do not describe any improvements to see some at the end of the session. Therefore, we consider it premature to dismiss deconstruction as a useless therapeutic strategy, and suggest that more studies be done on the conditions under which it is most helpful.

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)0.089
metaresearch head score (Gemma)0.251
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0890.251
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0020.003
Science and technology studies0.0040.004
Scholarly communication0.0030.004
Open science0.0040.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.061
GPT teacher head0.335
Teacher spread0.274 · 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.

Study designObservational
DomainReproducibility
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
Published2004
Admission routes1
Has abstractyes

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