FREQUENCY OF SUICIDAL IDEATION IN DIAGNOSED CASES OF SCHIZOPHRENIA
Bibliographic record
Abstract
Background: Schizophrenia is a chronic psychiatric disorder associated with high morbidity and premature mortality, with suicide being a major contributor. Globally, 20% to 40% of individuals with schizophrenia attempt suicide at least once in their lifetime. Despite the severity of this concern, limited research has been conducted locally to assess the burden of suicidal ideation among individuals diagnosed with schizophrenia. This study aims to address this gap and support future preventive strategies and interventions. Objective: To determine the frequency of suicidal ideation in patients diagnosed with schizophrenia presenting to a tertiary care hospital. Methods: This cross-sectional study was conducted at the Department of Psychiatry, Pakistan Institute of Medical Sciences (PIMS), Islamabad, from July 5, 2024, to January 4, 2025. A total of 142 patients (68 males, 74 females), aged 18–60 years and diagnosed with schizophrenia per DSM-5 criteria, were enrolled through non-probability consecutive sampling. Patients with substance abuse, intellectual disability, or neurological disorders were excluded. Suicidal ideation was assessed using the Beck Scale for Suicidal Ideation, with a score of ≥7 taken as the cutoff. Demographic and clinical data were analyzed using SPSS version 26, with significance set at p<0.05. Results: The mean age of participants was 38.00 ± 10.63 years, with 64.8% under 40 years of age. Females constituted 52.1% of the sample. A BMI above 25.0 kg/m² was observed in 44.4% of cases. Suicidal ideation was present in 33 patients (23.2%). Significant associations were found between suicidal ideation and BMI (p = 0.032) as well as profession (p = 0.001), while other variables showed no statistically significant correlation. Conclusion: A substantial proportion of patients with schizophrenia reported suicidal ideation, particularly among those with higher BMI and salaried occupations. These findings highlight the need for targeted screening and intervention strategies to mitigate suicide risk in this vulnerable population.
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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 | 0.001 |
| 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) | 0.002 | 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".