Effects of Disability and Symptom Severity on Quality of Life in Schizophrenia Patients
Bibliographic record
Abstract
Objective: Schizophrenia is a chronic disease marked by intellectual deterioration and cognitive impairment. Although much progress has been achieved in the treatment of schizophrenia, quality of life in schizophrenia patients is far from satisfactory. This study aims to investigate effects of disability and severity of symptoms on quality of life in schizophrenia. Method: The study included fifty (50) patients who met the DSM-IV diagnostic criteria for schizophrenia. Patients were evaluated by using Sociodemographic Data Form, World Health Organization Disability Assessment Schedule II (WHO-DASII), Brief Psychiatric Rating Scale (BPRS), Positive and Negative Symptoms Scale (PANSS), The Calgary Depression Scale for Schizophrenia (CDSS), Insight Assessment Scale and Liebowitz Social Anxiety Scale (LSAS). Results: Results suggested a positive correlation between economic status of patients and all areas of quality of life. A positive relationship was also determined between onset age of disease and instrumental role category, and common objects and activities. Results revealed a positive relationship between all areas of quality of life and BPRS and PANSS negative scores. A negative relationship was found between disability scores and all parts of quality of life. On the other hand, a positive relationship was found between interpersonal relations area of quality of life and insight scores, while a negative relationship was determined between interpersonal relations area of quality of life and LSAS anxiety and avoidance scores. Conclusion: This study investigated quality of life and factors that may affect quality of life in schizophrenia patients. Results suggested that, similan to chronic physical diseases, disability also affects quality of life negatively in chronic psychological disease such as schizophrenia. Therefore reducing disability would perhaps be the most effective way to increase quality of life.
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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 | 0.001 | 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 | 0.000 | 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".