Bibliographic record
Abstract
Objectives：The aim of this study was to examine associations between quality of life in patients with schizophrenia and their family relationships. Methods：A total of 68 patients with schizophrenia participated in the study. Socio-demographic and clinical data were collected, as well as results from the Subjective Well-being under Neuroleptic Treatment Scale-Short Form(SWNK), Family Emotional Involvement and Criticism Scale(FEICS), a visual analogue scale for evaluating the degree of perceived criticism(VAS), the Family Adaptability and Cohesion Evaluation Scale(FACES), Beck Cognitive Insight Scale(BCIS), and Rosenberg Self Esteem Scale(R-SES). Psychiatrists administered the Positive and Negative Syndrome Scale and the Calgary Depression Scale for Schizophrenia(CDSS), and collected a history of previous suicide attempts. Results：The SWN-K total scores showed significant negative correlations with scores on the FEICS perceived criticism, CDSS, and VAS measures and significant positive correlations with scores on the R-SES, FACES, and BCIS. Multiple regression analysis revealed that FEICS perceived criticism, FACES, and BCIS scores were significantly associated with SWN-K scores. The FACES total score was significantly lower in patients with a history of previous suicide attempt. Conclusion：The quality of life of patients with schizophrenia was negatively associated with greater perceived familial criticism and positively associated with better family cohesion and higher patient insight. In patients with a history of suicide attempts, family adaptability and cohesion were significantly low.
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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 | 0.000 | 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) | 0.002 | 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".