Design of Black Impact: A Randomized Controlled Trial Evaluating the Mechanisms Underlying Psychosocial Stress Reduction in a Cardiovascular Health Intervention
Bibliographic record
Abstract
BACKGROUND: Lower attainment of cardiovascular health (CVH), indicated by lower scores on the American Heart Association's Life's Essential 8 metrics, is a major contributor to Black men having the shortest life expectancy of any nonindigenous race/sex group. Evidence-based community interventions to improve CVH in Black men are sparse; thus, an academic-community-government-industry partnership was developed to cocreate and test a 24-week CVH intervention for Black men, Black Impact, in line with best practices for community-based participatory research. METHODS AND RESULTS: The Black Impact intervention is delivered by health coaches, fitness trainers, and community health workers and emphasizes weekly physical activity, health education, and addressing social needs. Together, academic-community-government-industry partners will conduct a randomized, waitlist-controlled trial among 340 Black men with suboptimal CVH to determine intervention: (1) efficacy on CVH and psychosocial stress; (2) effect on individual and interpersonal outcomes; (3) effect on biological mechanisms responsive to psychosocial stress; and (4) organizational contexts and resources necessary for sustainability of the academic-community-government-industry partnership. An intervention working group of academic-community-government-industry partner representatives will guide implementation and evaluation. Upon trial completion, findings (eg, change in CVH at 24 weeks [primary], change in perceived stress at 24 weeks [coprimary], biological mechanisms, psychosocial process mediators [stress, social and interpersonal processes]) will be disseminated in scientific and lay settings. CONCLUSIONS: Robust clinical trials are needed to test novel interventions focused on CVH equity. Black Impact will determine intervention efficacy, evaluate biological and psychosocial mediators of impact, and lay a framework for sustainability and scalability. REGISTRATION: URL: https://clinicaltrials.gov/; Unique Identifier: NCT06055036.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".