Development, Testing, and Implementation of a Training Curriculum for Nonphysician Health Workers to Reduce Cardiovascular Disease
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide. The need to address CVD is greatest in low- and middle-income countries where there is a shortage of trained health workers in CVD detection, prevention, and control. OBJECTIVES: Based on the growing evidence that many elements of chronic disease management can be shifted to nonphysician health care workers (NPHW), the HOPE-4 (Heart Outcomes Prevention and Evaluation Program) aimed to develop, test, and implement a training curriculum on CVD prevention and control in Colombia, Malaysia, and low-resource settings in Canada. METHODS: Curriculum development followed an iterative and phased approach where evidence-based guidelines, revised blood pressure treatment algorithms, and culturally relevant risk factor counseling were incorporated. Through a pilot-training process with high school students in Canada, the curriculum was further refined. Implementation of the curriculum in Colombia, Malaysia, and Canada occurred through partner organizations as the HOPE-4 team coordinated the program from Hamilton, Ontario, Canada. In addition to content on the burden of disease, cardiovascular system pathophysiology, and CVD risk factors, the curriculum also included evaluations such as module tests, in-class exercises, and observed structured clinical examinations, which were administered by the local partner organizations. These evaluations served as indicators of adequate uptake of curriculum content as well as readiness to work as an NPHW in the field. RESULTS: Overall, 51 NPHW successfully completed the training curriculum with an average score of 93.19% on module tests and 84.76% on the observed structured clinical examinations. Since implementation, the curriculum has also been adapted to the World Health Organization's HEARTS Technical Package, which was launched in 2016 to improve management of CVD in primary health care. CONCLUSIONS: The robust curriculum development, testing, and implementation process described affirm that NPHW in diverse settings can be trained in implementing measures for CVD prevention and control.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".