An International Perspective on Priority Areas for Women’s Cardiovascular Health Research: Qualitative Findings From a Cross-Sectional Survey
Bibliographic record
Abstract
Background: The Global Cardiovascular Research Funders Forum (GCRFF) unites international research funders interested in supporting cardiovascular disease (CVD) research. One focus area is women's cardiovascular health; the present study aimed to identify priority themes for future joint research funding opportunities. Methods: After ethics approval, a survey was developed based on literature review, GCRFF feedback, and input from methodologists/content experts. The survey comprised 3 open-ended and 5 multiple-choice questions. With the use of widespread dissemination strategies, an electronic survey portal was opened for 8 weeks, from November 15, 2023, to January 15, 2024, with various language options. Results were downloaded into a secure REDCap database for analysis. Independent theming of responses was completed by 3 reviewers until coding consensus was achieved, following which 1 coder completed the remaining theming. Descriptive statistics are reported. Results: Among the 191 responses, all 9 GCRFF countries were represented. Most respondents identified as women (74%) and clinicians/academics (77%); fewer people with lived or living experience participated (23%). Common themes included women-specific risk factors and prevention strategies (56%), life-course issues (43%), and sex- and gender-specific treatments and outcomes (36%). Common topics were CVD (66%), coronary artery disease (CAD) (18%), and heart disease (13%). Designated research pillars included clinical (52%), population health (36%), and basic science (30%). Solutions proposed included knowledge generation (71%), increased funding (55%), networking researchers (52%), and knowledge mobilisation (41%). Congruence of priority ordering was demonstrated between sex and respondent residence subgroups. Conclusion: Diverse international input prioritised research in risk factors and prevention strategies specific to women and in sex- and gender-specific treatment and outcomes of heart disease, with considerations of life-course issues across all research pillars.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".