Comparison of Quality of Life Between Jordanian and Saudi Patients With Heart Failure
Bibliographic record
Abstract
INTRODUCTION: Heart failure can influence all aspects of patients' health despite the improvement in its treatment. Different factors might affect the quality of life for patients with heart failure. These factors include but are not limited to: age, gender, ejection fraction, culture, and social support. Therefore, the purpose of this study was to examine differences in quality of life and perceived social support in patients with heart failure from Jordan and Saudi Arabia.MATERIALS & METHODS: A cross-sectional correlational design was used to test the objective of this study. A total of 202 patients were recruited from outpatient clinics of three hospitals in Jordan and Saudi Arabia. Data were collected through the SF-36 and the MOS-SSS questionnaires.RESULTS: The results of this study demonstrated that Jordanian patients with heart failure reported significantly greater social support in all MOS-SSS subscales than the Saudi patients except for the tangible support. The Saudi patients reported significantly more mental impairment (p ˂ .01) and lower level of fatigue (p ˂ .01) than the Jordanian patients.CONCLUSIONS: It is important to assess and identify physical and psychological resources available for patients at home and in the community to improve their quality of life.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".