The Level of Optimism and Pessimism and its Relationship to the Quality of Life in Patients with Renal Failure in the Government and Private Hospitals in Irbid
Bibliographic record
Abstract
The aim of this study was to detect the level of optimism and pessimism and its relation to the quality of life in patients with renal failure in the government and private hospitals in Irbid in light of the variables: gender, age, duration of disease and educational level of patients, the sample of the study consisted of (93) patients with kidney failure, who were randomly selected from the study population. The researchers used optimism and pessimism scale and the quality of life scales, their validity and reliability were verified. Results of the study showed that the means for optimism scale ranged between (3.602-3.075) with a medium degree, and the means for pessimism scale ranged between (4.086-3.118) with a high and medium degree, while the means for quality of life scale ranged between (4.054-2.957) with a high and medium degree. Results also showed the existence of a correlation between the level of optimism and the level of quality of life and this relationship is a moderate relationship, and a lack of correlation between level of optimism and level of pessimism and level of pessimism and quality of life. There are no statistically significant differences at the level of significance (0.05) in the patients' responses on the optimism, pessimism scales according to (gender, family income, medical insurance and origin).
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 | 0.002 |
| 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 | 0.001 |
| 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".