A Qualitative Examination of the Factors That Influence Women's Quality of Life as They Live With Coronary Artery Disease
Bibliographic record
Abstract
The purpose of this study is understanding women's experiences regarding health-related quality of life (HRQOL) in the context of living with coronary artery disease (CAD). Sampling was purposive and continued until data saturation. The women participated in semistructured interviews that were tape-recorded and completed in less than 1 hour. Conventional content analysis was used to analyze the data. Results indicate that CAD influenced the participants' HRQOL. This occurred through categories the investigators labeled "dealing with one more thing," "surrendering roles and pleasures," "managing the health system," "understanding CAD," and "resolving to be strong." The thoughtful responses of the women in this study suggest that understanding the HRQOL of women who have CAD lies in the context of considering their quality and quantity of social support. Thus, it behooves health care providers to assess patients' levels of social support and intervene as appropriate.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".