Culturally Tailored Diabetes Self-Management Education and Support Programs in Black African and Caribbean Adults With Type 2 Diabetes (HEAL-D): Protocol for a Multicenter, Pragmatic Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: People of Black African and Black Caribbean ethnicity experience higher rates and poorer outcomes of type 2 diabetes (T2D) than people of White European ethnicity; these inequalities are compounded by poor healthcare access. Cultural tailoring of diabetes self-management education and support (DSMES) programs has the potential to improve healthcare engagement and clinical outcomes for ethnic minority groups. Healthy Eating & Active Lifestyles for Diabetes (HEAL-D) is a co-designed, culturally tailored group-based DSMES program for adults of Black African and Black Caribbean ethnicity. OBJECTIVE: This trial aims to evaluate the clinical and cost effectiveness of the HEAL-D intervention, compared to standard DSMES programs, in Black African and Black Caribbean adults living with T2D. METHODS: , blood lipids, anthropometric outcomes, blood pressure, physical activity, and patient-reported outcome measures relating to psychological well-being and self-management support, lifestyle behaviors, and health economics will be collected at baseline and follow-up visits (6, 12, and 24 months). Cost-effectiveness will be assessed through a cost-utility analysis conducted from a health and social care perspective. A mixed methods process evaluation will provide a formative evaluation of delivery, intervention fidelity, and implementation of HEAL-D, and an embedded study within a project will assess the impact of multiple long-term conditions on uptake of, and engagement with HEAL-D, and the impact of HEAL-D on multiple long-term conditions. The trial received Research Authority and Research Ethics Council approval on April 22, 2024. RESULTS: Funding began in August 2023. Site "green light" was received on August 15, 2024, for London; November 29, 2024, for Manchester; and January 31, 2025, for the West Midlands. Recruitment commenced in August 2024 and is due to run for 11 months. As of March 26, 2025, a total of 76 participants have consented. Last patient, last visit is expected in June 2027; primary data analysis is expected to begin in July 2027. Final results are anticipated to be available in September 2027, and publication is expected by the end of 2027. CONCLUSIONS: The HEAL-D trial will address whether a culturally tailored DSMES program, provided in-person or via videoconferencing, is clinically and cost-effective compared to standard DSMES at improving diabetes management in Black African and Black Caribbean adults. If effective, this would provide an evidence-based model of equitable DSMES services and improve the implementation of healthcare programs for ethnic minority groups. TRIAL REGISTRATION: ISRCTN 1434448; https://www.isrctn.com/ISRCTN14344948. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71861.
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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 | 0.039 | 0.028 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.076 | 0.011 |
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".