MétaCan
Menu
Back to cohort
Record W2921691392 · doi:10.1097/nmd.0b013e31826dd9af

Cognitive Behavioral Therapy for Schizophrenia

2012· review· en· W2921691392 on OpenAlexaff
Neil A. Rector, Aaron T. Beck

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2012
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Randomized controlled trialQuality of life (healthcare)Psychological interventionCognitive behavioral therapyCognitive therapyPsychiatryAdjunctive treatmentClinical psychologyPsychologyIntervention (counseling)Cognitive remediation therapyMEDLINECognitionClinical trialMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Early case studies and noncontrolled trial studies focusing on the treatment of delusions and hallucinations have laid the foundation for more recent developments in comprehensive cognitive behavioral therapy (CBT) interventions for schizophrenia. Seven randomized, controlled trial studies testing the efficacy of CBT for schizophrenia were identified by electronic search (MEDLINE and PsychInfo) and by personal correspondence. After a review of these studies, effect size (ES) estimates were computed to determine the statistical magnitude of clinical change in CBT and control treatment conditions. CBT has been shown to produce large clinical effects on measures of positive and negative symptoms of schizophrenia. Patients receiving routine care and adjunctive CBT have experienced additional benefits above and beyond the gains achieved with routine care and adjunctive supportive therapy. These results reveal promise for the role of CBT in the treatment of schizophrenia although additional research is required to test its efficacy, long-term durability, and impact on relapse rates and quality of life. Clinical refinements are needed also to help those who show only minimal benefit with the intervention.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.113
GPT teacher head0.415
Teacher spread0.302 · 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 designOther design
Domainnot available
GenreReview

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

Citations61
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Nervous and Mental DiseaseSame topicSchizophrenia research and treatmentFrench-language works237,207