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Record W2322290765 · doi:10.1037/a0034708

Transference interventions and the process between therapist and patient.

2014· article· en· W2322290765 on OpenAlexaff
Randi Ulberg, Svein Amlo, Kenneth L. Critchfield, Alice Marble, Per Høglend

Bibliographic record

VenuePsychotherapy · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsCentre for Addiction and Mental Health
FundersNorges ForskningsrådUniversitetet i Oslo
KeywordsPsychologyPsychological interventionPsychotherapistPsychodynamic psychotherapyInter-rater reliabilityPsychodynamicsCategorizationValence (chemistry)Context (archaeology)Rating scaleClinical psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Interpreting the transference has been considered a core ingredient in psychodynamic psychotherapy. The effects of analyzing the transference are probably dependent on certain characteristics of the interventions themselves and the context in which transference interventions are given. The present study describes the development and use of a therapy process rating scale (Transference Work Scale; TWS) constructed to identify, categorize, and explore work with the transference. TWS has subscales that rate timing, content, and valence of the transference interventions, as well as response from the patient. Transcribed segments (10 min) from 51 different patients were scored with TWS by 2 independent raters. The interrater agreement on the TWS items was good to excellent. Clinical examples of transference work were also rated using the Structural Analysis of Social Behavior (SASB). TWS and SASB supplement each other. TWS might be a potentially useful tool to explore the interaction of timing, category, and valence of transference work in predicting in-session patient response as well as treatment outcome.

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)0.019
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.080
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.371
Teacher spread0.342 · 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 designQualitative
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

Citations25
Published2014
Admission routes1
Has abstractyes

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