A systematic literature review of diabetes self-management education features to improve diabetes education in women of Black African/Caribbean and Hispanic/Latin American ethnicity
Bibliographic record
Abstract
OBJECTIVE: This systematic literature review aims to identify diabetes self-management education (DSME) features to improve diabetes education for Black African/Caribbean and Hispanic/Latin American women with Type 2 diabetes mellitus. METHODS: We conducted a literature search in six health databases for randomized controlled trials and comparative studies. Success rates of intervention features were calculated based on effectiveness in improving glycosolated hemoglobin (HbA1c), anthropometrics, physical activity, or diet outcomes. Calculations of rate differences assessed whether an intervention feature positively or negatively affected an outcome. RESULTS: From 13 studies included in our analysis, we identified 38 intervention features in relation to their success with an outcome. Five intervention features had positive rate differences across at least three outcomes: hospital-based interventions, group interventions, the use of situational problem-solving, frequent sessions, and incorporating dietitians as interventionists. Six intervention features had high positive rate differences (i.e. ≥50%) on specific outcomes. CONCLUSION: Different DSME intervention features may influence broad and specific self-management outcomes for women of African/Caribbean and Hispanic/Latin ethnicity. PRACTICAL IMPLICATIONS: With the emphasis on patient-centered care, patients and care providers can consider options based on DSME intervention features for its broad and specific impact on outcomes to potentially make programming more effective.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".