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Record W4414994254 · doi:10.1037/pst0000606

Parsing the within- and between-therapist positive regard–outcome association in cognitive–behavioral therapy for generalized anxiety disorder.

2025· article· en· W4414994254 on OpenAlexafffund
Anuj H. P. Mehta, Michael J. Constantino, Alice E. Coyne, Averi N. Gaines, Henny A. Westra, Martin M. Antony

Bibliographic record

VenuePsychotherapy · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsToronto Metropolitan UniversityYork University
FundersCanadian Institutes of Health Research
KeywordsWorryAssociation (psychology)DistressAnxietyGeneralized anxiety disorderMultilevel model

Abstract

fetched live from OpenAlex

= 52) to responsively address patient resistance (Westra et al., 2016). Ten therapists treated patients in CBT only, and nine distinct therapists treated patients in MI-CBT only. Patients rated therapist-offered positive regard repeatedly across 15 sessions and their worry and general distress outcomes at baseline and posttreatment. Multilevel structural equation modeling revealed a significant association between patients' experience of higher early treatment positive regard and lower posttreatment worry and general distress at the within-therapist level. There was no between-therapist association for either outcome. Additionally, neither between-therapist positive regard nor treatment condition moderated the within-therapist effect of positive regard on either outcome. Results underscore the value of therapists working to foster their patients' felt regard irrespective of the treatment they use or the general ability they have in cultivating this relational experience. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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)0.008
metaresearch head score (Gemma)0.024
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.052
GPT teacher head0.428
Teacher spread0.376 · 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
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

Citations1
Published2025
Admission routes2
Has abstractyes

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