A Multisite Examination of Sex Differences in Cardiac Rehabilitation Barriers by Participation Status
Bibliographic record
Abstract
BACKGROUND: Despite its proven benefits and need, women are significantly less likely than men to participate in and complete cardiac rehabilitation (CR). The purpose of this study was to quantitatively investigate sex differences in CR barriers by participation status. METHODS: Cardiac outpatients (1496, 430 female, 28.7%) of 97 cardiologists completed a mailed survey to discern CR participation. Respondents were asked to rate 19 CR barriers on a 5-point Likert scale. RESULTS: Five hundred twenty-nine (43%) respondents self-reported participating in CR, with men being more likely to participate (p < 0.05). There was no significant sex difference in total number of CR barriers, but differences in individual barriers were found. For CR participants, t tests revealed significant sex differences in the perception of exercise as tiring or painful (p = 0.042) and work responsibilities (p = 0.013). For CR nonparticipants, women rated the following barriers as greater than men: transportation (p = 0.025), family responsibilities (p = 0.039), lack of CR awareness (p = 0.036), experiencing exercise as tiring or painful (p = 0.002), and comorbidities (p = 0.009). CONCLUSIONS: Overall, women do not perceive greater barriers to CR participation than men, but the nature of their barriers differs, particularly among nonparticipants. Beliefs about the value of CR, awareness, and exercise parameters are all modifiable barriers that should be addressed among women.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".