Controlled pilot test of a translated cardiac rehabilitation education curriculum in percutaneous coronary intervention patients in a middle-income country delivered using WeChat: acceptability, engagement, satisfaction and preliminary outcomes
Bibliographic record
Abstract
In China, despite the rapid increase in percutaneous coronary interventions (PCIs), cardiac rehabilitation (CR) is just burgeoning, leaving a need for comprehensive evidence-based education curricula. This pilot study assessed the acceptability of Simplified Chinese CR education delivered via booklets and videos on WeChat asynchronously and the impact on improving knowledge, risk factors, health behaviors and quality of life. In this pre-post, controlled, observational study, interested PCI patients received the 12-week intervention or usual care and WeChat without education. Participants completed validated surveys, including the Coronary Artery Disease Education-Questionnaire and Self-Management Scale. Acceptability (14 Likert-type items), engagement (minutes per week) and satisfaction were assessed in intervention participants. Ninety-six patients consented to participate (n = 49 intervention), of which 66 (68.8%) completed the follow-up assessments. Twenty-seven (77.1%) retained intervention participants engaged with the materials, rating content as highly acceptable (all means ≥4/5) and satisfactory (2.19 ± 0.48/3); those engaging more with the intervention were significantly more satisfied (P = 0.03). While participants in both groups achieved some improvements, only intervention participants had significant increases in disease-related knowledge, reductions in body mass index and triglycerides, as well as improvements in diet (all P < 0.05). In this first study validating the recently translated CR patient education intervention, acceptability and benefits have been supported.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".