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Record W3191411862 · doi:10.32920/ryerson.14655240.v1

An examination of individual provider characteristics in the dissemination and uptake of cognitive-behavioral conjoint therapy for posttraumatic stress disorder

2021· preprint· en· W3191411862 on OpenAlexaffabout
Amy Brown‐Bowers

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCognitionPsychotherapistPsychologyClinical psychologyCognitive therapyPosttraumatic stressCognitive behavioral therapyOrientation (vector space)Conjoint analysisClinical PracticeCognitive processing therapyMedicinePsychiatryPreferenceNursing

Abstract

fetched live from OpenAlex

Support for the use of evidence-based psychological practice in Canada is growing, but there remains a large gap between psychotherapy research and real-world psychotherapy practice. There also exists a chasm between the number of clinicians who attend psychotherapy trainings and those who implement the training material into their clinical practice. The present study examined individual provider characteristics in the uptake of Cognitive-Behavioral Conjoint Therapy for Posttraumatic Stress Disorder. There was a trend for an interaction between attitudes toward manualized treatments and attitudes toward the use of couple therapy to treat individuals with PTDS. Specifically, as attitudes in each area were more positive, piecemeal uptake of the protocol decreased. Contrary to hypothesis, prior training in couple therapy or in cognitive-behavioural therapy for PTDS, years since the highest degree was completed, and therapeutic orientation were not associated with uptake.

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)0.010
metaresearch head score (Gemma)0.070
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 score0.025
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.070
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.067
GPT teacher head0.433
Teacher spread0.366 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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