Evaluation of the Relationship between Disability and Disease Severity, Cognitive Functions, and Insight in Patients with Schizophrenia
Bibliographic record
Abstract
Objective: This study aims to examine the clinical characteristics, cognitive functions, and levels of insight, which are thought to be related to disability in schizophrenia patients, and to determine which variable will guide the clinician to predict the disability.Methods: Participants were 102 individuals with schizophrenia aged 18-60.All participants completed the social functioning scale and the Beck cognitive insight scale.To determine the severity of disability, World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) scale was conducted.Positive and negative syndrome scale, Calgary depression scale for schizophrenia, trail making tests and Stroop test were performed.Results: The regression analysis indicated that high income, increased education level, and fewer hospitalization variables had significant negative effects (p 0.05) on the WHODAS overall score, explaining 20.8% of the variance.The duration of trail-making test form A, PANSS total score, and Stroop 3 duration variables had significant positive effects (p 0.05) on the WHODAS score, explaining 49.3% of the total variance.Increased levels of education, higher income, and higher cognitive insight were found to be associated with less disability.Increased severity of disease and some deterioration in the mental field were found to be related to high disability.Conclusion: In this research, the predictors of disability in individuals with schizophrenia, level of education, and income are among the predictors of disability, and disease severity seems to be more related to the impairment of cognitive functions.Interventions and treatments that support the psychosocial functionality should be planned rather than symptom-oriented treatment approaches.
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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 | 0.001 | 0.002 |
| 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 | 0.002 |
| 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".