The Buddy System: African American Women with Self-Reported Hypertension and Their Experiences in a Peer (Dyadic) Support Intervention
Bibliographic record
Abstract
INTRODUCTION: Hypertension is the leading modifiable risk factor for cardiovascular disease, and it disproportionately affects African American women, who face increased risks of heart disease, kidney disease, and stroke. The Dietary Approaches to Stop Hypertension (DASH) diet effectively reduces blood pressure, but African American women often face challenges with adhering to it. Peer support, a proven mechanism for improving health behaviors through social connections and community resources, may help these women better manage their diet and hypertension. This qualitative study explored the experiences of African American women participating in an eight-week peer (dyadic) support intervention to improve DASH diet adherence and lowering systolic blood pressure, with an emphasis on understanding the dyadic relationship. METHODS: A purposive sample of 40 African American women (20 dyads) was recruited for five focus groups that were conducted both online and in person. Content analysis was used to identify themes related to the nature and quality of peer interactions and relationships from the perspectives of the 34 women who completed the intervention (Mean age = 71.38 years; SD = 8.38). RESULTS: Four subthemes emerged: emotional support, shared experiences, informational/inspirational support, and accountability. The participants reported forming strong, supportive relationships that were crucial in improving diet and blood pressure management. CONCLUSION: This study underscores the benefits of peer support in managing hypertension among older African American women, suggesting the need for future randomized controlled trials to examine the effectiveness of the DASH diet with and without peer support.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".