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Record W2143096755 · doi:10.1192/bjp.187.48.s72

Implementing cognitive-behavioural therapy for first-episode psychosis

2005· article· en· W2143096755 on OpenAlexaff
Jean Addington, John Gleeson

Bibliographic record

VenueThe British Journal of Psychiatry · 2005
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychosisEarly psychosisPsychologySchizophrenia (object-oriented programming)CognitionIntervention (counseling)Cognitive behavioral therapyPsychotherapistPsychiatryCognitive therapyOutcome (game theory)Clinical psychology

Abstract

fetched live from OpenAlex

Significant symptomatic improvement after a first episode of psychosis is not matched by a similar improvement in functional outcome. Thus, increased attention has been given to psychological intervention, in particular cognitive cognitive-behavioural therapy (CBT), with the hope of enhancing functional recovery. Outcome trials of CBT for schizophrenia are few, in particular for the first episode, and have been occasionally criticised for their lack of significance compared with supportive therapies. We describe a modular CBT approach for those with a first episode of psychosis that addresses adaptation as well as both functional and symptomatic outcome and one that parallels the theoretical shift in CBT that has occurred in the last decade. Guidelines for integrating CBT into an early psychosis service are presented.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.034
GPT teacher head0.339
Teacher spread0.304 · 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 designNon-randomized trial
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

Citations44
Published2005
Admission routes1
Has abstractyes

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