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Record W2349685355

The Reliability and Validity of the Calgary Depression Scale for Schizophrenia

2013· article· en· W2349685355 on OpenAlexaboutno aff
Wen Qiqin

Bibliographic record

VenueClinical Medicine & Engineering · 2013
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsPositive and Negative Syndrome ScaleSchizophrenia (object-oriented programming)MedicineDiscriminant validityClinical psychologyReliability (semiconductor)HamdPsychiatryDepression (economics)Convergent validityScale (ratio)Internal consistencyPsychometricsPsychosis
DOInot available

Abstract

fetched live from OpenAlex

Objective To explore the reliability and validity of the Mandarin version of the Calgary Depression Scale for Schizophrenia (CDSS). Methods 100 healthy controls redid the CDSS in 2 weeks for investigating the re-test reliability; CDSS, Hamilton Depression Scale (HAMD), Positive and Negative Syndrome Scale (PANSS) were evaluated in 150 schizophrenic patients, who were separated into schizophrenia with or without depression group by Structured Clinical Interview for DSM-IV-TR (Research Version, SCID), to explore the internal consistency, split-half reliability, criteria-related validity, convergent and discriminant validity. Results The re-test reliability of CDSS was good (r=0.650, P0.01); the CDSS was found to have high internal consistency (α=0.838, P0.01) and split-half reliability (r=0.857, P0.01). The criteria-related validity was excellent (Z=-5.109, P0.01); the correlation between CDSS and HAMD was significantly positive (r=0.751, P0.01), a weak correlation between CDSS and the PANSS negative and positive subscales was also discovered (r=0.23, P0.05). Conclusions Our findings suggest positive support to Mandarin version of the CDSS; it may be helpful to identify the depressive symptoms in Chinese schizophrenic patients.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.223
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.041
GPT teacher head0.361
Teacher spread0.320 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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