Factors Associated With Hope and Quality of \nLife in Patients With Coronary Artery Disease
Bibliographic record
Abstract
Background: Psychological resources such as hope have been \nsuggested to affect quality of life (QoL) positively in patients \nwith heart disease. However, little information regarding the relationship \nbetween these two constructs is available. \nPurpose: Thiswork was aimed at examining the factors associated \nwith hope and QoL in patients with coronary artery disease. \nMethods: In this descriptive work, perceived QoL and hope \nwere assessed in 500 patients with heart disease. The information \nwas collected using the McGill QoL Questionnaire, demographic \nvariables, and the Herth Hope Index. The Pearson correlation \ntest and general linear model were used to examine correlations \nthrough SPSS Version 22. \nResults: A considerable correlation was discovered between \nQoL and hope (r = .337, p < .001).Multivariate analyseswith regression \nrevealed that religious beliefs and social support both \nhad significant and positive effects on the total perceived hope \nof patients and that patient age had a considerable negative impact \non QoL ( p < .05). None of these factors had a significant \nimpact on hope ( p < .05). In addition, the total QoL had a significant \nand positive effect on patient feelings and thoughts, \nwhereas the physical problems component of QoL had a significant \nand negative effect on hope ( p < .05). Participants with \nhigher levels of education reported more hope. \nConclusions: QoL relates significantly to self-perceived hope in \npatients. Understanding QoL and hopefulness in patients with \ncoronary artery disease has implications for nurses and other \nhealthcare professionals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".