Effects of a WhatsApp-Assisted Health Educational Intervention for Cardiac Rehabilitation: A Randomized Controlled Clinical Trial Protocol
Bibliographic record
Abstract
Although the effectiveness of cardiac rehabilitation (CR) programs in secondary prevention is well-recognized, there is a lack of studies exploring the potential of mobile health to enhance educational interventions within CR. The objective is to assess the impact of a structured WhatsApp-assisted health educational intervention, in conjunction with the usual care, compared to the usual care alone among participants enrolled in a CR program. The trial will recruit 32 participants enrolled in a CR program, who will be randomly assigned to a structured WhatsApp-assisted health educational intervention plus usual care or usual care alone group. The intervention will span 4 weeks, with assessments at baseline, 4 weeks, and 3, 6, and 12 months. The primary outcome measure is the cardiovascular risk factors knowledge score. Secondary outcomes include physical activity levels, anxiety and depression, and quality of life. Expected results include improved knowledge of cardiovascular risk factors, increased physical activity levels, and better mental health outcomes in the intervention group. Additionally, an enhancement in the overall quality of life is anticipated. These findings are expected to underscore the value of integrating mHealth with traditional CR methods, potentially shaping future approaches in chronic disease management and prevention.
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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 | 0.028 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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".