Frequency and characterization of depression in schizophrenia
Bibliographic record
Abstract
Context and Aims: The prevalence of depression in schizophrenia has been reported to be varying according to the stage of illness (early vs. chronic) and state (acute or postpsychotic). The presence of positive symptoms, extrapyramidal side effects, and insight have been said to predispose depression in a stable patient with schizophrenia. However, not many Indian studies have examined depression in patients with stable schizophrenic symptoms. Thus, we aimed to study the prevalence of depression and its correlates in a sample of stable patients with schizophrenia. Subjects and Methods: Eighty subjects of both genders, attending a tertiary care center, were consecutively taken up for the assessment. A semistructured pro forma was administered for all the subjects after getting informed consent. Positive and Negative Symptom Scale, Calgary Depression Scale for Schizophrenia (CDSS), Hamilton Depression (HAMD) Rating Scale, Extrapyramidal Symptom Rating Scale, Schedule for Assessment of Insight (SAI), and Global Assessment of Functioning Scale (GAF) were used to assess the patients. Results: In this study population, 34.5% had depressive symptoms. The study group had mild depression associated with schizophrenic psychopathology. The study populations did not have significant extrapyramidal symptoms during the assessment. The CDSS score and HAMD score had a significant positive correlation with SAI score. HAMD score had a negative correlation with GAF. Conclusions: This study demonstrates that patients with schizophrenia have significant depressive symptoms. These depressive symptoms appear to be independent of extrapyramidal symptoms and correlate positively to schizophrenic psychopathology. Poor insight may have led to low severity of reported depressive symptoms.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".