A Systematic Review of Interventions With an Educational Component Aimed at Increasing Enrollment and Participation in Cardiac Rehabilitation
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to systematically review the impact and characteristics of interventions with an educational component designed to improve enrollment and participation in cardiac rehabilitation (CR) among patients with cardiovascular disease. REVIEW METHODS: Five electronic databases were searched from data inception to February 2023. Randomized controlled trials and controlled, cohort, and case-control studies were considered for inclusion. Title, abstract, and full text of records were screened by two independent reviewers. The quality of included studies was rated using the Mixed Methods Assessment Tool. Results were analyzed in accordance with the Synthesis Without Meta-analysis reporting guideline. RESULTS: From 7601 initial records, 13 studies were included, six of which were randomized controlled trials ("high" quality = 53%). Two studies evaluated interventions with an educational component for health care providers (multidisciplinary team) and 11 evaluated interventions for patient participants (n = 2678). These interventions were delivered in a hybrid (n = 6; 46%), in-person (n = 4; 30%), or virtual (n = 3; 23%) environment, mainly by nurses (n = 4; 30%) via discussion and orientation. Only three studies described the inclusion of printed or electronic materials (eg, pamphlets) to support the education. Eleven of 12 studies reported that patients who participated in interventions with an educational component or were cared for by health care providers who were educated about CR benefits (inhospital and/or after discharge) were more likely to enroll and participate in CR. CONCLUSION: Interventions with an educational component for patients or health care providers play an important role in increasing CR enrollment and participation and should be pursued. Studies investigating the effects of such interventions in people from ethnic minority groups and living in low-and-middle-income countries, as well as the development of standard educational materials are recommended.
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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 | 0.014 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".