Knowledge and practice outcomes after home blood pressure measurement education programs
Bibliographic record
Abstract
OBJECTIVES: We investigated the outcomes of three home blood pressure measurement (HBPM) education programs on adult knowledge and practice. METHODS: We chose a pretest/post-test design and randomly divided 95 adults into three groups: individual training (group A), group training (group B), and self-learning (group C), for education regarding HBPM in accordance with the Canadian Hypertension Education Program. Participants involved in groups A and B received interactive education led by a nurse. Participants in group C learned by themselves using an instruction booklet and a HBPM device lent to them for 7 days. Knowledge was assessed pretest and post-test by questionnaire. Skills were evaluated postintervention by direct observation. RESULTS: Analysis of the 60 participants indicated significant knowledge improvement. Pretest scores of 38 (group A), 54 (group B), and 45% (group C) rose significantly to 97, 99, and 90%, respectively (pretest vs. post-test; P<0.0001). Individual and group training sessions were significantly more effective compared with the self-learning program, which was confirmed by differences between groups in post-test practice. Assessment scores: 74 (group A), 79 (group B), and 53% (group C; group A vs. group C; P=0.001, group B vs. group C; P=0.001). CONCLUSION: Our findings indicate that adults attending an individual or group training program for HBPM retained its theoretical and practical principles better than those engaged in self-learning. Their success may be attributed to interaction with the nurse.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".