The relationship between depression and insight into the possibility of suicide in patients with schizophrenia
Bibliographic record
Abstract
Objective: This study aims at investigating the relationship between suicide probability and insight and depression in schizophrenic patients. Methods: A total of 104 patients, in the 18-65 age group, who were observed with schizophrenia diagnosis for minimum two years at psychiatry outpatient of a university and the Community Mental Health Center, were included into our study between the dates of March 17th and April 15th 2015. Interview form was used in collection of data along with the Suicide Probability Scale, the Calgary Depression Scale for Schizophrenia and Birchwood Insight Scale. Data were analyzed with the multiple comparison, independent t test, Kruskal-Wallis, Mann Whitney U, ANOVA, covariant analysis and Pearson correlation tests. Results: 56.7% of the cases have stated that they have previously attempted suicide, and 45.2% have used pills and 7.7% used sharp objects in their suicide attempt. A negative relationship was found between Suicide Probability total score, subscales of Suicide Ideation and Negative Self-Evaluation and the Awareness of Symptoms subscale of Birchwood Insight Scale. A positive relationship was found between Calgary Depression Scale for Schizophrenia and the Hopelessness and Hostility subscales of the Suicide Probability Scale and a negative relationship was found between the subscales of Suicide Ideation and Negative Self-Evaluation. Conclusion: Suicide is a significant problem in schizophrenia. Our study has shown that the probability of suicide decreased in patients who are aware of the symptoms however that the most important factors in suicide were negative affect and hopelessness.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".