Study of Relationship Between Depression and Quality of Life in Patients With Chronic Schizophrenia
Bibliographic record
Abstract
Depression is among the personality traits of schizophrenic patients, which results from psychotic features or is a consequence of a period of psychosis. Depression in schizophrenic patients is one of the important factors affecting their quality of life. The study population of this descriptive and analytic study consists of patients with chronic schizophrenia in Zahedan in 2014. The sample included 60 patients who simultaneously suffered from depression and were selected using random sampling (30 males and 30 females). The research instruments included the Schizophrenia Quality of Life Scale (SQLS) and the Beck Depression Inventory (the inventory was filled out by the tester). In order to form a statistics analysis, we used Pearson correlation and regression multivariate. Investigating the study hypotheses showed that there was a negative correlation between the high level of depression and low quality of life. the relationship between depression and the quality of life subscales showed that in women, the variable of symptoms and complications was a significant predictor; however, the other two variables (energy and motivation and psychosocial) were not significant predictors. In case of men, psychosocial variable was a significant predictor; however, the other two variables (energy and motivation and symptoms and complications) were not significant predictors. In general, depression on these patients makes discontent of life on them; therefore, elimination of their depression on their treatment is necessary.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".