Community Mobilization, Participation, and Blood Pressure Status in a Cardiovascular Health Awareness Program in Ontario
Bibliographic record
Abstract
PURPOSE: To determine the feasibility of a community-wide approach integrated with primary care (Cardiovascular Health Awareness Program [CHAP]) to promote monitoring of blood pressure (BP) and awareness of cardiovascular disease risk. DESIGN: Demonstration project. SETTING: Two midsized Ontario communities. PARTICIPANTS: Community-dwelling seniors. INTERVENTION: CHAP sessions were offered in pharmacies and promoted to seniors using advertising and personalized letters from physicians. Trained volunteers measured BP, completed risk profiles, and provided risk-specific education materials. METHOD: We examined the distribution of risk factors among participants and predictors of multiple visits and elevated BP. RESULTS: Opinion leaders aided recruitment of family physicians (n = 56/63) and pharmacists (n = 18/19). Over 90 volunteers were recruited. Invitations were mailed to 4394 seniors. Over 10 weeks, there were 4165 assessments of 2350 unique participants (approximately 30% of senior residents). 37.5% of attendees had untreated (16%; 360/2247) or uncontrolled (21.5%; 482/2247) high BP. Participants who received a letter (odds ratio [OR] 2.5, 95% confidence interval [CI] 2.1-3.0), had an initial elevated BP (OR 1.2, 95% CI 1.0-1.5), or reported current antihypertensive medication (OR 1.4, 95% CI 1.1-1.6) were more likely to attend multiple sessions (p ≤ .05 for all). Older age (≥ 70 years; OR 1.5, 95% CI 1.3-1.8), BMI ≥ 30 (OR 1.7, 95% CI 1.4-2.2), current antihypertensive medication (OR 1.6, 95% CI 1.3-1.9), and diabetes (OR 2.4, 95% CI 1.9-3.2) predicted elevated BP (p < .001 for all). CONCLUSION: The program yielded learning about community mobilization and identified a substantial number of seniors with undiagnosed/uncontrolled high BP.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".