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Record W2060419761 · doi:10.1097/nmd.0000000000000266

Clinical and Functional Outcomes in People With Schizophrenia With a High Sense of Well-Being

2015· article· en· W2060419761 on OpenAlexaff
Gagan Fervaha, Ofer Agid, Hiroyoshi Takeuchi, George Foussias, Jimmy Lee, Gary Remington

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2015
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsCentre for Addiction and Mental Health
FundersNational Institute of Mental HealthH. Lundbeck A/SSunovionInternational Business Machines Corporation
KeywordsSchizophrenia (object-oriented programming)Intervention (counseling)Life satisfactionPsychologyPsychiatryQuality of life (healthcare)AntipsychoticClinical psychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Optimal outcome in schizophrenia is thought to include remission of symptoms, functional recovery, and improved subjective well-being. The present study examined the characteristics of individuals with schizophrenia who report being satisfied with their life in general. Individuals with schizophrenia who participated in the Clinical Antipsychotic Trial of Intervention Effectiveness study were included in the present analysis. Approximately half of the individuals evaluated reported a high level of life satisfaction, even while many concurrently described themselves as at least moderately ill and experiencing moderate-severe symptoms and manifested severe functional deficits. Of all individuals evaluated, only about 1% experienced what was considered to be optimal outcome. Individuals with schizophrenia are able to experience a high level of life satisfaction, despite experiencing severe illness and functional deficits. Those involved in care should be aware that life satisfaction as an outcome is not necessarily associated with symptom remission and superior functioning.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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 designObservational
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

Citations15
Published2015
Admission routes1
Has abstractyes

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