Cardiovascular disease and stroke prevention educational-behavioural programmes for culturally and/or linguistically diverse communities: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: To identify the types of cardiovascular disease (CVD) and stroke prevention educational-behavioural programs for people from culturally and/or linguistically diverse (CALD) backgrounds and investigate their effect on CVD risk factors and disease knowledge. METHODS AND RESULTS: Four electronic databases were searched from inception to September 2023. Mean difference (MD) and standardised MD was calculated using random-effects model, and heterogeneity was assessed using the I2 statistic. Studies that were not included in the meta-analysis were narratively described. The Cochrane Risk of Bias tool and Joana Briggs Institute Critical Appraisal checklist were used to assess the quality of the included studies. Sixteen studies originating from USA and UK (4 RCTs and 12 quasi-experimental pre-post studies) with n=2331 participants (mean age 57.2 years, 50% women) were included. The programs were multi-component, 15 of which were culturally adapted and 1 was co-designed. Most were delivered face-to-face in groups. In contrast to the results among the pre-post studies, the pooled analysis showed that educational-behavioural programs may have little to no effect on SBP (MD 1.18 mmHg, 95% CI -2.42-4.79) and HbA1c (MD -0.29%, 95% CI -0.89-0.32). The results for LDL cholesterol, BMI, physical activity and dietary intake were also mixed except for CVD or stroke knowledge which demonstrated statistically significant improvements after the intervention. CONCLUSION: The effect of educational-behavioural programs on CVD risk factors is inconclusive but may improve CVD or stroke knowledge. Co-designing programs underpinned by behaviour change theories/techniques with stakeholders and target CALD communities may enhance their potential impact. Future studies should use more rigorous study design i.e., RCTs, valid and reliable outcome measures to reduce inherent bias and strengthen the evidence base for the effectiveness of these programs.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| 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 | 0.001 |
| 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".