Community-Based Culturally Tailored Education Programs for Black Communities with Cardiovascular Disease, Diabetes, Hypertension, and Stroke: Systematic Review Findings
Bibliographic record
Abstract
BACKGROUND: Community-based culturally tailored education (CBCTE) programs for chronic diseases may reduce health disparities; however, a synthesis across chronic diseases is lacking. We explored (1) the characteristics and outcomes of CBCTE programs and (2) which strategies for culturally appropriate interventions have been used in CBCTE programs, and how they have been implemented. METHODS: A systematic review was conducted by searching three databases to identify empirical full-text literature on CBCTE programs for Black communities with cardiovascular disease, hypertension, diabetes, or stroke. Studies were screened in duplicate, then data regarding study characteristics, participants, intervention, and outcomes were extracted and analyzed. Cultural tailoring strategies within programs were categorized using Kreuter and colleagues' framework. RESULTS: Of the 74 studies, most were conducted in the USA (97%) and delivered in one site (53%; e.g., church/home). CBCTE programs targeted diabetes (65%), hypertension (30%), diabetes and hypertension (1%), cardiovascular disease (3%), and stroke (1%). Reported program benefits included physiological, medication-related, physical activity, and literacy. Cultural tailoring strategies included peripheral (targeted Black communities), constituent-involving (e.g., community informed), evidential (e.g., integrated community resources), linguistic (e.g., delivered in community's dialect/accent), and sociocultural (e.g., integrated community members' religious practices). CONCLUSIONS: CBCTE programs may have beneficial outcomes, but a small sample size limited several. The strategies identified can be adopted by programs seeking to culturally tailor. Future interventions should clearly describe community members' roles/involvement and deliver programs in multiple locations to broaden reach. TRIAL REGISTRATION: PROSPERO CRD42021245772.
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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 | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".