The correlation of suicide attempt and suicidal ideation with insight, depression and severity of illness in schizophrenic patients
Bibliographic record
Abstract
The correlation of suicide attempt and suicidal ideation with insight, depression and severity of illness in schizophrenic patientsObjective: At this study, it is aimed to determine criteria to predict the suicidal risks of schizophrenic patients and to explore the correlation of suicide attempt and suicidal ideation with insight, depression and severity of illness as well.Method: Randomly selected 104 inpatients between 20 and 65 years of age, treated with a diagnosis of schizophrenia according to DSM-IV-TR criteria at Bakirkoy Training and Research Hospital for Psychiatry, Neurology and Neurosurgery were included, and patients were examined at the period of first 72 hours of admission.The patients were evaluated with Schedule for Assessing the Three Components of Insight (SAI), Positive and Negative Syndrome Scale (PANSS), and Calgary Depression Scale for Schizophrenia (CDSS).Results: Depression scores were higher in the patients who had suicide attempt compared to those without suicide attempt.Depression and insight scores of the patients who had suicidal ideation were found to be higher compared to those without suicidal ideation.In the logistic regression analysis, CDSS was found to be the determinant of suicide attempt and suicidal ideation, PANSS negative total score was found to be the determinant of suicidal ideation, and self destructive behavior was found to be the determinant of suicide attempt.Conclusion: As depression was the common factor that determines the suicidal ideation and suicide attempts, suicidal ideation should be inquired more carefully and in more detail in the presence of depressive symptoms in patients with schizophrenia.We consider that CDSS can be easily applied and can determine the depression in patients with schizophrenia and the treatment of depression with eligible methods in turn, decreases risk of suicide.
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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".