Identifying accurate methods of assessing blood pressure and health information by lay volunteers in the Philippines: Adapting a Canadian cardiometabolic health program to LMICs
Bibliographic record
Abstract
Background Hypertension is a leading cause of mortality worldwide, especially in low- and middle-income countries (LMICs). In Canada, the Cardiovascular Health Awareness Program (CHAP) was proven effective in reducing cardiovascular hospitalizations. The next research will evaluate an adapted version of CHAP in the southern Philippines (Community Health Assessment Program in the Philippines (CHAP-P)). Methods Prior to full program adaptation, this two-phase study was conducted to evaluate the most appropriate methods locally for 1) assessing blood pressure (BP) readings and 2) collecting CHAP-P participant information. Phase 1 compared the correlation (Pearson's r ) of BP readings of three automated BP monitoring devices (WatchBP Office Target, Omron HEM-7130, Microlife 3QA1); manual measurement by a health care professional; and the gold standard (trained observers using a mercury sphygmomanometer). Phase 2 compared three data collection methods (tablet, cell phone, and paper) used by Barangay Health Workers (BHWs), the local volunteers who will implement the intervention. Errors, missed data, and BHW experiences were explored during each phase. Results Phase 1: the device most highly correlated with the gold standard for systolic BP was the WatchBP Office Target ( r = 0.84). For diastolic BP, the WatchBP Office Target produced the same result as the Omron HEM-7130 ( r = 0.67). Manual BP measurement showed a very poor correlation ( r < 0.60) with the gold standard. Phase 2: BHWs found cell phones and tablets more accurate and easier than paper. They preferred tablets due to the larger screen. Conclusion The WatchBP Office target and tablet will be used in the next phase of the project.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.092 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".