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Record W2153689494 · doi:10.3390/bs4040437

Merging Evidence-Based Psychosocial Interventions in Schizophrenia

2014· article· en· W2153689494 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavioral Sciences · 2014
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversité du Québec à Trois-RivièresCentre for Disability Prevention and RehabilitationUniversité de SherbrookeUniversité de Montréal
Fundersnot available
KeywordsPsychosocialSchizophrenia (object-oriented programming)Psychological interventionPsychologyClinical psychologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Psychosocial interventions are an essential part of the treatment for people with severe mental illness such as schizophrenia. The criteria regarding what makes an intervention "evidence-based" along with a current list of evidence-based interventions are presented. Although many evidence-based interventions exist, implementation studies reveal that few, if any, are ever implemented in a given setting. Various theories and approaches have been developed to better understand and overcome implementation obstacles. Among these, merging two evidence-based interventions, or offering an evidence-based intervention within an evidence-based service, are increasingly being reported and studied in the literature. Five such merges are presented, along with their empirical support: cognitive behavior therapy (CBT) with skills training; CBT and family psychoeducation; supported employment (SE) and skills training; SE and cognitive remediation; and SE and CBT.

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.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.186
GPT teacher head0.442
Teacher spread0.257 · 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