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Record W2517272063 · doi:10.1111/eip.12379

Cognitive‐behavioural social skills training for first‐episode psychosis: a feasibility study

2016· article· en· W2517272063 on OpenAlexaff
Yarissa Herman, Huma Shireen, Sarah Bromley, Natalie Yiu, Eric Granholm

Bibliographic record

VenueEarly Intervention in Psychiatry · 2016
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsAdlerProfessional Engineers OntarioCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychosisPsychologyCognitionPopulationClinical psychologyPsychiatrySocial skillsSocial cognitive theoryCognitive trainingMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

AIM: To conduct a preliminary feasibility examination of cognitive-behavioural social skills training (CBSST) in a first-episode psychosis population. METHODS: Twenty two first-episode psychosis clients participated in an 18-week CBSST group adapted for a younger population. RESULTS: Adaptive functioning significantly improved following group participation and was maintained at 3-month follow-up. CONCLUSION: The CBSST group was feasible and well accepted in the first episode programme. These preliminary findings warrant further testing in a larger trial to determine efficacy.

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)0.004
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: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.074
GPT teacher head0.399
Teacher spread0.325 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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