Bibliographic record
Abstract
The aim of this study was to analyze risk factors present in schizophrenic patients with depressive symptomatology. The sample comprised of 76 respondents diagnosed with schizophrenia. In the study, we used the Positive and Negative Syndrome Scale (PANSS) and Calgary Depression Scale for Schizophrenia. The prevalence of depression was estimated to be 30%. The mean scores on the negative subscale of the PANSS were significantly higher in patients with schizophrenia and depression compared to control group (U=3.64, p=0.00), and so were those on the General Psychopathology Scale (U=4.91, p=0.00). Socio-demographic factors were identified as important factors (p<0.05). Personal and environmental factors such as loneliness, immediate social environment, social support and isolation were statistically significantly different between the groups (p<0.05). There was a correlation of poor compliance with psycho-pharmacotherapy, increased number of hospitalizations and shorter remission period with the severity of clinical presentation (p<0.05). Since the presence of these factors is associated with depression in schizophrenia, their early detection in clinical practice is vital to ensure timely prevention of the development of depressive symptomatology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".