Bakımevinde kalan şizofreni hastalarında yaşam kalitesi ve depresyon
Bibliographic record
Abstract
Quality of life and depression in schizophrenia patients living in a nursing home Objective: Nursing homes are seen as alternative housing for patients with schizophrenia. However, it has not yet been established how suitable this accommodation is for schizophrenia patients. First aim of this study is to assess the quality of life and depression level in schizophrenic patients and compare this data with that of patients living with their families. Second aim is to assess factors related to the quality of living and depression state in all participants of this study. Method: This is a cross-sectional study conducted with patients presenting to the Psychotic Disorders Policlinic of the Beyhekim Psychiatric Clinic of Konya Training and Research Hospital consecutively between December 2012 and May 2013 who had received a diagnosis of schizophrenia according to DSM IV-TR. All participants were administered a sociodemographic data form, Brief Psychiatric Rating Scale (BPRS), Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale for Schizophrenia (CDSS), and Quality of Life Scale for Schizophrenia Patients (QLSSP). Results: CDSS scores were found to be significantly increased in schizophrenic patients living in nursing homes. Their QLSSP scores, including interpersonal relations, occupational role, mental symptoms, personal belongings/activity scores, and total scores were statistically significantly low. A significant negative correlation was observed between negative symptom levels and occupational area, mental findings, and the personal belongings/activity areas of quality of life. Between positive symptom levels and quality of life, only scores in the occupational area showed a significant negative correlation. A significant negative correlation between CSDS and QLS was observed in all areas. Conclusion: Quality of life and depression need to be evaluated in all schizophrenia patients, as they are conditions that significantly affect treatment and prognosis.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".