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Record W7016211387

Women living with coronary heart disease, barriers to care

2000· other· en· W7016211387 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2000
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchFocus groupDiseaseCoronary heart diseaseDepression (economics)Perspective (graphical)Cause of death
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.003
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.001
GPT teacher head0.144
Teacher spread0.143 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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