Women living with coronary heart disease, barriers to care
Bibliographic record
Abstract
The myth that Coronary Heart Disease (CHD) is a male problem originated with studies conducted in the 1950s and 60s. Women are not aware of the extent of their risk, yet heart disease is the leading cause of death among North American women. In a 1996 Gallup poll, 67% of doctors did not know that cardiac disease symptoms, warning signs, and diagnosis were different for women. Feminist activities continue to advocate for woman-centered health care. In this study, a qualitative methodology was utilized. Women with CHD were invited to participate in Focus Groups and describe their experience of living with the disease. Four major themes emerged: Being Heard, Helps and Hindrances, Validation, and Living for the New Me. Findings revealed that there was still evidence of gender bias and that women experienced an array of barriers to care. Support was apparent, but the women voiced a lack of understanding by others of what they were experiencing, especially the depression and extreme fatigue. Staff were caring, helpful and provided necessary information. Fear of dying alone was revealed, which had not been addressed in the literature reviewed. Implications for caregivers included continuing to address gender bias, and focusing on prevention, especially targeting young women. Including families in education programs was suggested to enhance understanding.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".