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Record W2789567393 · doi:10.1002/capr.12167

Bridging the gap between cognitive and interpersonal variables in depression

2018· article· en· W2789567393 on OpenAlexaff
Debora A. D'Iuso, Keith S. Dobson, Kia Watkins‐Martin, Leah Beaulieu, Martin Drapeau

Bibliographic record

VenueCounselling and Psychotherapy Research · 2018
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsUniversity of CalgaryMcGill University
Fundersnot available
KeywordsPsychologyCognitionInterpersonal communicationClinical psychologyContext (archaeology)Rating scaleMajor depressive disorderAssociation (psychology)Depression (economics)PsychotherapistDevelopmental psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Abstract Background Cognitive and interpersonal variables are often understood to be related to the etiology and maintenance of major depression. However, few studies have examined the relationship between these two constructs. Aim This study examined the association between cognitive errors (CEs) most commonly endorsed among individuals with major depressive disorder ( MDD ) and their interpersonal functioning. Method These processes were examined early in psychotherapy and at the end of 20 sessions of cognitive behavioral therapy for depression. Therapy transcripts of 42 clients with MDD were rated for CEs using the Cognitive Error Rating Scale ( CERS : Drapeau, Perry & Dunkley, 2008) and for interpersonal behaviors using the Structural Analysis of Social Behavior ( SASB : Benjamin & Cushing, 2000). Findings Results of this study revealed significant associations between CEs and interpersonal behaviors early in treatment and at the end of treatment. Implications of these findings are discussed in the context of improving psychotherapy process and 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.212
GPT teacher head0.505
Teacher spread0.293 · 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 teacher head, 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

Citations2
Published2018
Admission routes1
Has abstractyes

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