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Record W2056855234 · doi:10.1080/00048670902873672

Reliability and Validity of the Chinese Version of the Calgary Depression Scale for Schizophrenia

2009· article· en· W2056855234 on OpenAlexaboutno aff
Weidong Xiao, Hao Liu, Hongyan Zhang, Qi Liu, Pei-Xin Fu, Xiaoping Wang, Gaohua Wang, Lingzhi Li, Liang Shu

Bibliographic record

VenueAustralian & New Zealand Journal of Psychiatry · 2009
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPositive and Negative Syndrome ScalePsychologyCronbach's alphaSchizophrenia (object-oriented programming)Rating scaleClinical psychologyPsychiatryConstruct validityReliability (semiconductor)PsychopathologyDepression (economics)Scale (ratio)Inter-rater reliabilityPsychometricsPsychosisDevelopmental psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the present study was to determine the reliability and validity of the Chinese version of the Calgary Depression Scale for Schizophrenia (CDSS-C) in schizophrenia patients. METHOD: One hundred and one inpatients from four mental health units who met DSM-IV criteria for schizophrenia were enrolled. The Positive and Negative Syndrome Scale (PANSS), Hamilton Depression Rating Scale (HDRS-24), Simpson-Augus Rating Scale (SAS), and Barnes Acathisia Rating Scale (BARS) were administered by the first rater, whereas the CDSS-C was assessed by a second independent rater. RESULTS: The internal consistency (Cronbach's alpha = 0.80) and the inter-rater reliability (kappa coefficient >0.79) were good. The test-retest reliability was high (r = 0.927). The scale had good construct validity, with statistically significant correlations with the HDRS-24, G6 item (depression) of PANSS, and significant weak correlations with the general psychopathology subscale of PANSS. The CDSS-C showed no correlation with the positive and negative subscale of PANSS, the SAS and the BARS. CONCLUSION: The Chinese version of CDSS is a valid and reliable instrument for the assessment of depression in schizophrenia.

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)0.000
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 score0.022
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.015
GPT teacher head0.298
Teacher spread0.283 · 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 teacher head, 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

Citations38
Published2009
Admission routes1
Has abstractyes

Explore more

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