Quality of Life, Perceived Social Support and Death Anxiety Among People Having Cardiovascular Disorders: A Cross-Sectional Study
Bibliographic record
Abstract
Aim: To assess the quality of life, perceived social support, and death anxiety among people having cardiovascular disorders Study type: A Cross-sectional study Place and Duration: This study was conducted at Civil Hospital, BMCH Quetta Pakistan from June 2020 to June 2021 Methodology: This study was designed to evaluate the correlation between quality of life, hope, and death anxiety among people having cardiovascular disorders. We gathered data by using a convenience sampling technique for 4 months. We used the questionnaire method for our survey. Our questionnaire was based on five sections including basic demographic, the 17-item McGill QoL (MQoL) Questionnaire, Herth hope to score, Thorson-Powell Death Anxiety Scale (TPDAS), and Death depression scale (DDS). Results: Out of 500 participants half of them were female (52.4%), most of the participants were married with no formal education and belonged to poor or middle-class families. Participants with intermediate education levels who were financially dependent on the government had a better quality of life than others. We observed that patients with myocardial infarction (MI) had higher levels of anxiety. Furthermore, we observed that patients with a belief in life after death had higher death anxiety than those who don't believe. Conclusion: Our results concluded a positive association among quality of life and hope. We examined that social support plays a vital role in managing CVD disorders. However, patients with myocardial infarction had high levels of death anxiety than others. Keywords: Cardiovascular disorders, coronary artery disease, myocardial infarction, death anxiety, quality of life, social support.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".