The investigation of patients with epilepsy in terms of alexithymia, sleep quality and mental symptoms
Bibliographic record
Abstract
Objective: The aim of this study was to investigate the relationships among alexithymia, sleep quality and mental symptoms in patients with epilepsy. Methods: This study was conducted with 96 patients admitted to the Epilepsy Unit of Celal Bayar University Medical Faculty Hospital as a descriptive cross-sectional study. Data were collected from Socio-demographic Data Form, The Pittsburgh Sleep Quality Index (PSQI), Toronto Alexithymia Scale (TAS) and Symptom Check List (SCL-90-R). In the analysis of data, Student's t-test, ANOVA and Pearson Correlation analysis were used. Results: The level of sleep quality of 49% of patients was poor. 41.8% of the patients was alexithymic. It was found that alexithymic patients had poor sleep quality by taking higher scores from PSQI (t=1.99, p=0.040). Alexithymic patients SCL-90-R (general symptom level) was higher than non-alexithymic patients. A positive correlation (p=0.000, r=0.560) was determined between PSQI and SCL-90-R (general symptom level) scores of patients with epilepsy. Conclusion: As a result, the level of alexithymia in patients' sleep quality was worse. Moreover deterioration in mental status of patients was found to lead to deterioration of sleep quality. (Anatolian Journal of Psychiatry 2011; 12:114-120)
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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) | 0.001 | 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".