Patient education interventions for health behaviour change in adults diagnosed with coronary heart disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background Patient education is recommended to increase disease-related knowledge and modify coronary heart disease (CHD) risk factors. Although the importance has been established, there is a lack of knowledge of its efficacy and relative impact of duration on disease-related knowledge and health behaviour outcomes. Purpose It aimed to assess the efficacy of structured patient education on those outcomes in adults with CHD for short-term (less than six months) and long-term (six to 12 months) effect. Methods Eligible randomised controlled trials published in English, Simplified Chinese, Spanish, and Portuguese were searched in seven electronic databases from database inception through 2020. Reference lists, relevant conference lists, and keywords from the Internet were also searched. Outcomes included disease-related knowledge, smoking cessation, medication adherence, physical activity, and healthy dietary behaviour. Results Overall, 73 studies reporting 71 unique trials were included. Participants (n = 24,985) were aged mean 60.5 ± 5.7 years, mostly male (72.5%). About 74% of studies used more than one mode for education delivery, with phone calls and booklets being used the most frequent. Patient education was associated with significant improvement in all outcomes measured in meta-analyses (P < 0.05). In addition, regression analyses showed that a prolonged intervention duration does not significantly improve the outcomes, except for the disease knowledge (p = 0.009) and physical activity (p = 0.026). Conclusions Structured patient education, in a variety of modes and intensities, improves disease-related knowledge and health behaviours in adults with CHD. The findings can be used to guide design of cardiac programs, particularly related to intervention duration in clinical practice. Abstract Figure 1. PRISMA flow diagram
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".