Systematic review, meta‐analysis and meta‐regression to determine the effects of patient education on health behaviour change in adults diagnosed with coronary heart disease
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To assess the effectiveness of educational interventions and the relative effect of intervention duration on secondary prevention health behaviours in adults with coronary heart disease. BACKGROUND: Patient education can reduce disease progression and improve outcomes. However, there is a lack of knowledge of its efficacy and the relative impact of education duration on health behaviour change in this population. DESIGN: A systematic review and meta-analysis. METHODS: Seven electronic databases and grey literature were searched from Inception to July 2021. The review followed the PRISMA guidelines. This meta-analysis was analysed in Comprehensive Meta-Analysis version 3 software. Outcomes considered were disease knowledge and health behavioural outcomes. Data were pooled together with random-effects models using the inverse-variance method. The effect of education duration (<3 vs. ≥3 months) was examined by meta-regressions. RESULTS: In summary, 73 studies were included with a total of participants (n = 24,985) aged mean of 60.5 ± 5.7 years and mostly male (72.5%). Patient education improved all behaviours including disease knowledge at <6 and 6-12 months follow-up, the likelihood of quitting smoking at <6, and 6-12 months, medication adherence at <6 and 6-12 months; physical activity and exercise participation at <6 and 6-12 months and healthy dietary behaviours, at <6 and 6-12 months. Furthermore, education programmes with a longer duration (≥3 months) improved disease knowledge and physical activity more than shorter programmes. CONCLUSION: Patient education for secondary prevention, in various delivery modes and intensities, improves multiple self-reported health behaviours in patients with coronary heart disease. RELEVANCE TO CLINICAL PRACTICE: This study assessed the effectiveness of secondary prevention education and demonstrated improvements in all outcomes in this population. Longer duration programmes were more effective in improving disease knowledge and physical activity in the long term. These findings can assist the cardiac programmes' design, particularly in ensuring sufficient intervention duration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.065 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.058 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".