Implementation of Modified Cardiovascular Health Awareness Program for Canadian Adults on a Waiting List for a Family Physician
Bibliographic record
Abstract
INTRODUCTION: The Cardiovascular Health Awareness Program (CHAP) was originally developed and evaluated as a community-based cardiovascular diseases (CVD) prevention program in communities where access to family physicians was not a significant issue. Many Canadians now face sub-optimal access to a regular source of primary care. Centralized waiting lists and prioritization based on urgency of medical need were created to address this problem. We aimed to assess the acceptability, CVD risk profile, and potential benefits of offering a modified version of CHAP to adults on the waiting list. METHODS: The implementation was conducted in Laval (Canada) between March and June 2016, targeting individuals 40 years of age or older who were registered on the waiting list (GACO) and had a priority code of 3. Participants were invited through a personalized letter to attend sessions in community health centers. During the sessions, participants completed CVD risk profiles, risk of type 2 diabetes questionnaire (CANRISK); had their blood pressure, height and weight as well as waist circumference measured. They also received targeted healthy lifestyle and patient education materials and were referred to local programs including a medical follow-up, when required. RESULTS: A total of 1976 invitation letters were sent resulting in 281 (14.2%) participants. The average age of attendees was 58.1 (SD = 8.2) and a majority were female (58%, n = 163). A third of participants (34.2%, n = 96) had BP ≥140/90 and 11.4% (n = 32) were classified as having a very high risk for developing diabetes. Almost half (41.6%, n = 117) of participants were referred either to health promotion programs offered by local health authorities, to family physicians (4.6%, n = 13) or emergency departments (1.8%, n = 5) for short-term medical assistance. CONCLUSION: Despite low participation rate, many adults on a waiting list had elevated risk for CVD and would greatly benefit from having a regular source of primary care.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".