Student-Led Blood Pressure Clinics: A Community-Level Intervention to Improve Blood Pressure Health Literacy among Adults Living in Northern Ontario
Bibliographic record
Abstract
Background: High blood pressure affects approximately 25% of the Canadian population and is implicated in a number of poor health outcomes. According to the 2020 Hypertension Canada Guidelines, for both the prevention and management of hypertension, health behaviour interventions can effectively lower blood pressure. Health literacy is recognized as a significant social determinant of health. Low health literacy is associated with adverse health behaviours and poor subjective health. This study aims to assess whether student-led blood pressure clinics can improve the blood pressure related health literacy of adults in Northern Ontario. Methods: Blood pressure clinics were held at four different publicly accessible sites in Thunder Bay, ON. 110 participants were presented with a survey before and after their participation in an educational intervention centred on hypertension. Pre- and post-test scores were compared and linear regression analyses were conducted to assess for relationships between scores and sociodemographics. Results: A significant increase in post-test scores across all domains was observed. Linear regression analyses revealed that income and previous diagnosis of hypertension were significant predictors of pre-test performance, income and education level were significant predictors of post-test performance, and education was a significant predictor of percent score improvement. Conclusions: This study highlights the effectiveness of a student-led educational intervention designed to improve hypertension health literacy among community members in Thunder Bay, ON. The findings suggest that structured, student-led education can enhance blood pressure related knowledge and may encourage hypertension prevention and/or more effective blood pressure management. This pop-up clinic model offers a scalable framework for other student-run free clinics to adopt, providing them with a practical approach to addressing hypertension-related health literacy disparities in their own communities.
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".