Women’s preferences for cardiac rehabilitation program model: A randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Although cardiac rehabilitation (CR) is effective, women often report programs do not meet their needs. Innovative models have been developed that may better suit women. The objectives of the study were to describe: (1) adherence to CR model allocation; (2) satisfaction by model attended; and (3) CR preferences. DESIGN AND METHODS: Tertiary objectives from a randomized controlled trial of female patients randomized to mixed-sex, women-only, or home-based CR were tested. Patients were recruited from six hospitals. Consenting participants were asked to complete a survey and undertook a CR intake assessment. Eligible patients were randomized. Participants were mailed a follow-up survey six months later. Adherence to model allocation was ascertained from CR charts. RESULTS: Overall 169 (18.6%) patients were randomized, of which 116 (68.6%) completed the post-test survey. Forty-five (26.6%) participants did not receive the allocated model, with those referred to home-based CR least likely to attend the allocated model (n = 25; 45.4%). Semi-structured interviews revealed participants also often switched from women-only to mixed-sex CR due to time conflicts. Satisfaction was high across all models (mean = 4.23 ± 1.16/5; p = 0.85) but participants in the women-only program felt significantly more comfortable in their workout attire (p = 0.003) and perceived the environment as less competitive (p = 0.02). Patients equally preferred mixed-sex (n = 44, 41.9%) and women-only (n = 44, 41.9%) CR, over home-based (n = 17, 16.2%), with patients preferring the model they attended. CONCLUSION: Females were highly satisfied regardless of CR model attended but preferred supervised programs most. Patient preference and session timing should be considered in program model allocation decisions.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".