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Depressão na esquizofrenia: prevalência e relação com a qualidade de vida

2007· article· pt· W2110367931 on OpenAlexaboutno aff
Clareci Silva Cardoso, Waleska Teixeira Caiaffa, Marina Bandeira, Arminda Lúcia Siqueira, Jussara Teixeira Silva, José Otávio Penido Fonseca

Bibliographic record

VenueCadernos de Saúde Pública · 2007
Typearticle
Languagept
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Quality of life (healthcare)Schizophrenia (object-oriented programming)MedicinePsychiatryScale (ratio)GerontologyPsychologyClinical psychology

Abstract

fetched live from OpenAlex

This study aimed to investigate the prevalence of depression in schizophrenia and associated factors, including quality of life. A cross-sectional study was conducted with 150 outpatients. The Calgary Depression Scale for Schizophrenia measured depression, and the Quality of Life Scale-Brazil measured quality of life. Major depression was found in 56% of patients with schizophrenia. Patients with major depression had low quality of life according to both the global scale and the occupational subscale. Global quality of life was important for separating the decision-tree statistical analyses. In patients with low quality of life, three factors were associated with depression: presence of schizophrenic symptoms, number of medications, and lack of household activities. In patients with better quality of life scores, only duration of the illness was significant. The study shows a high prevalence of depression in schizophrenia, besides highlighting its repercussions on quality of life. When evaluating quality of life, the presence of depression should be taken into consideration.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.036
GPT teacher head0.339
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2007
Admission routes1
Has abstractyes

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