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Record W2147120209 · doi:10.7202/014531ar

Le traitement du trouble délirant et ses aspects cognitifs

2007· article· fr· W2147120209 on OpenAlexvenueno aff
Kieron O’Connor, Émmanuel Stip, Sophie Robillard

Bibliographic record

VenueSanté mentale au Québec · 2007
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

This article reviews the cognitive phenomenology of delusional disorders (DD) and examines the current cognitive models. Some case studies have shown considerable promise concerning the utilisation of cognitive behavioral therapy (CBT) for the treatment of DD, even if this approach is in its infancy. Although the stages of CBT to treat DD are very similar to that of other psychotic disorders, there are also considerable differences. However, it is essential to combine several strategies in order to modify inferences specific to DD. The clinical evaluation of delusions as well as the application of CBT as a treatment is illustrated in two cases with a diagnosis of DD with persecutory subtype. The cases required different time periods for different stages of CBT and highlight the importance of tailoring CBT according to need.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.032
GPT teacher head0.363
Teacher spread0.332 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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