Alexithymia, Posttraumatic Growth, and Life Contentment among Cardiac Sufferers
Bibliographic record
Abstract
Background: Cardiovascular diseases are a common and increasing number of deaths in developing and developed countries. Heart diseases are considered chronic and affect blood flow that leads to a number of psychological issues. Cardiac issues cause a major disturbance in the quality of life of the patient. Objective: To find out the relationship among alexithymia, posttraumatic growth, and life satisfaction among cardiac sufferers at DHQ Teaching Hospital and Siddique Sadiq Memorial Trust Hospital Gujranwala (Punjab; Pakistan). Study type, settings & duration: A cross sectional study was conducted DHQ Teaching Hospital and Siddique Sadiq Memorial Trust Hospital, Gujranwala from February to August 2020. Methodology: One hundred patients of heart attack from both genders aged 21-60 years. Toronto alexithymia scale (TAS-20), Posttraumatic growth inventory (PGI), and Satisfaction with life scale was used to collect data from the heart attack patients. Results: The results of this study revealed that alexithymia including three sub-factors i.e. difficulty in identifying feelings, difficulty in describing feelings, and externally oriented thinking is significantly negatively correlated with life satisfaction while posttraumatic growth i.e. new possibilities and appreciations of life significant positive correlated with life satisfaction. Conclusion: It was concluded that alexithymia has negative association with the satisfaction of life while posttraumatic growth is positively correlated with life satisfaction.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".