Women-focused cardiac rehabilitation delivery around the world and program enablers to support broader implementation
Bibliographic record
Abstract
Abstract Background Cardiovascular disease prevalence in women is high globally, which leads to a great burden of disability, and it is their leading cause of death. Cardiovascular rehabilitation (CR) is an outpatient model of secondary preventive care proven to mitigate this burden; however, significantly fewer women access CR than men, and those that do are less likely to complete the program. Accordingly, women-focused (W-F) models of CR have been developed, to better engage women and optimize their outcomes. Purpose The objectives of this study were to investigate: (1) the implementation of W-F CR by programs around the globe, (2) barriers to delivery of W-F CR, as well as (3) what they would want and need in order to apply the recommendations in their CR programs, particularly with regard to patient education and counselling. Methods In this cross-sectional study, a survey was administered to CR programs via REDCap from May-July/2023. Potential respondents were identified via the International Council of Cardiovascular Prevention and Rehabilitation’s (ICCPR) network. Results 223 responses were received from 52/111 (46.8% country response rate) countries in the world with any CR, across all 6 World Health Organization regions. Thirty-three (14.8%) programs from 30 countries reported offering any W-F programming. Programs did commonly offer elements preferred by women and recommended, namely: patient choice of session time (n=151, 70.6%), informal care providers/partners invited to sessions (n=121, 57.1%), having CR staff with expertise in women and heart diseases (n=112, 53.3%), separate changerooms for women (n=38, 52.8%), and discussing CR referral with patients (n=112, 52.1%). Main barriers to delivery of W-F exercise were physical resources (n=33; 14.8%), space (n=30, 13.5%), as well as staff time (n=26, 11.7%) and expertise (n=33, 10.3%). Main barriers to delivery of W-F education were human resources (n=114, 51.1%), educational resources (n=26, 11.7%) and expertise in the content (n=74, 33.2%). Enablers of W-F education delivery were availability of materials, in multiple modalities, as well as educated staff, and financial resources. Conclusions Despite the benefits, W-F CR is not commonly offered globally. Considering the barriers and enablers identified, ICCPR is developing resources to expand delivery. Results from this survey will be used to support implementation of the W-F CR Guideline recommendations such as increasing exercise modality options and psychosocial counselling, and development of W-F educational resources. Map.
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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 | 0.004 | 0.000 |
| 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 | 0.000 |
| 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".