Prevalence of depression in persons with schizophrenia – a cross-sectional study from a tertiary psychiatric hospital
Bibliographic record
Abstract
Background: It is important to be aware of depressive symptoms in schizophrenia because of the impact it has on its course and outcome. There are only a few studies that have evaluated depression in schizophrenia in Indian settings and no data is available from Kerala. The objective of this study was to find the prevalence and associated factors of depression in persons with schizophrenia. Methods: This was a cross-sectional study in which 225 patients with a diagnosis of schizophrenia according to DSM-5 who availed outpatient or inpatient services from a tertiary psychiatric hospital were included. Socio-demographic data were collected using a structured proforma. The symptom domains of schizophrenia were assessed using the Positive and Negative Syndrome Scale (PANSS). Depression was measured using the Calgary Depression Scale for Schizophrenia (CDSS). A cut-off score of ?6 on the CDSS was used to identify clinically significant depressive symptoms. Results: This study found the prevalence of depression in schizophrenia to be 30% (95 % CI - 29.94, 30.06). Higher education, being married, greater insight, a past history of suicide attempt, positive symptoms and general psychopathology symptoms were found to be associated with depression in schizophrenia. A positive correlation between PANSS positive subscale and CDSS scores was identified. Conclusions: Depression was seen in almost one-third of the patients with schizophrenia. Screening and management of depressive symptoms can help in improving the quality of care provided to patients with schizophrenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".