Reliability and Validity of the Chinese Version of the Calgary Depression Scale for Schizophrenia
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".