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Record W2350250922

Study of depressive symptoms of patients with chronic schizophrenia

2009· article· en· W2350250922 on OpenAlexaboutno aff
Ping Zhou

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2009
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Schizophrenia (object-oriented programming)Incidence (geometry)PsychiatryPositive and Negative Syndrome ScaleDepressive symptomsMedicineLogistic regressionPsychologyClinical psychologyInternal medicinePsychosisCognition
DOInot available

Abstract

fetched live from OpenAlex

Objective:To examine the depressive symptoms and the relevant factors in chronic schizophrenic patients.Method:The Chinese version of Calgary depression scale for schizophrenia(CDSS),the positive syndrome scale(SAPS),negative syndrome scale(SANS),treatment emergent symptom scale(TESS)and the questionaire for relevant factors of depression were administered to 180 inpatients with chronic schizophrenia.Results:The incidence of depression in chronic schizophrenic inpatients was 40.6%.The patients with and without depressive symptoms showed significant differences in total disease course,times of hospitalization,degree of education,family economic level,social supports,the recovery of insight,times of having drugs,drug types and doses,drug side-effects,the positive and negative symptoms,complications.The binary Logistic analysis indicated that the factors influencing the depression were the negative symptoms,complication,types of anti-psychotropic drugs,social supports,the insight and the drug side-effects.Conclusion:The incidence of depression in chronic schizophrenic inpatients is high and influencing factors are great,and depression should be treated and prevented in different ways.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.037
GPT teacher head0.423
Teacher spread0.386 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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