Relationship of depression with cognitive insight and socio-occupational outcome in patients with schizophrenia
Bibliographic record
Abstract
AIM: To evaluate the prevalence of depression using different measures in patients with schizophrenia and to study the relationship of depression in schizophrenia with cognitive insight and clinical insight, disability and socio-occupational functioning. METHODS: A total of 136 patients with schizophrenia were evaluated for depression, cognitive insight and socio-occupational functioning. RESULTS: Of the 136 patients included in the study, one-fourth ( N = 34; 25%) were found to have depression as per the Mini International Neuropsychiatric Interview (MINI). The prevalence of depression as assessed by Calgary Depression Scale for Schizophrenia (CDSS), Hamilton depression rating scale (HDRS) and Depressive Subscale of Positive and Negative Syndrome Scale (PANSS-D) was 23.5%, 19.9% and 91.9%, respectively. Among the different scales, CDSS has highest concordance with clinician's diagnosis. Sensitivity, specificity, positive predictive value and negative predictive value for CDSS was also higher than that noted for HDRS and PANSS-D. When those with and without depression as per clinician's diagnosis were compared, those with depression were found to have significantly higher scores on Positive and Negative Syndrome Scale (PANSS) positive and general psychopathology subscales, PANSS total score, participation restriction as assessed by P-scale and had lower level of functioning as assessed by Global Assessment of Functioning (GAF). No significant difference was noted on negative symptom subscale of PANSS, clinical insight as assessed on G-12 item of PANSS, disability as assessed by Indian Disability Evaluation and Assessment Scale (IDEAS) and socio-occupational functioning as assessed by Social and Occupational Functioning Assessment Scale (SOFS). In terms of cognitive insight, those with depression had significantly higher score for both the subscales, that is, self-reflective and self-certainty subscales as well as the mean composite index score. CONCLUSION: Our results suggest that one-fourth of patients with schizophrenia have depression, compared to HDRS and PANSS-D, CDSS has highest concordance with clinician's diagnosis of depression and presence of depression is related to cognitive insight.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".