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Record W2134066496 · doi:10.1080/10503307.2010.495957

Therapist and client perceptions of therapeutic presence: The development of a measure

2010· article· en· W2134066496 on OpenAlexaff
Shari M. Geller, Leslie S. Greenberg, Jeanne C. Watson

Bibliographic record

VenuePsychotherapy Research · 2010
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsInstitute for Christian StudiesUniversity of TorontoYork University
Fundersnot available
KeywordsPsychologyAlliancePsychotherapistSession (web analytics)Therapeutic relationshipConstruct validityReliability (semiconductor)Predictive validityClinical psychologyContent validityMeasure (data warehouse)Psychometrics

Abstract

fetched live from OpenAlex

The authors developed two versions of a therapeutic presence measure, based on an earlier model of presence (Geller & Greenberg, 2002)-Therapeutic Presence Inventory-therapist (TPI-T) and client (TPI-C) versions-to measure in-session therapeutic presence. They explored their reliability and validity in two studies. In the first, items generated from the previously established model were subjected to analyses and expert ratings. In the second study, therapists and clients rated therapists' presence postsession. Therapists also completed the Relationship Inventory, and clients assessed two additional factors: session outcome, using the Client Task Specific Measure-Revised, and therapeutic alliance, using the Working Alliance Inventory. Findings revealed that both versions of the TPI had good reliability and construct validity. However, TPI-T had low predictive validity and the TPI-C showed good predictive validity. In particular, clients reported positive therapeutic alliance and change following sessions when they felt their therapist was present with them.

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)0.013
metaresearch head score (Gemma)0.039
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: Methods · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
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 head0.106
GPT teacher head0.475
Teacher spread0.369 · 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
GenreMethods

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

Citations136
Published2010
Admission routes1
Has abstractyes

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