Knowledge, perception and practice of health professionals regarding blood pressure measurement methods: a scoping review
Bibliographic record
Abstract
OBJECTIVE: Guideline-concordant performance of accurate blood pressure measurement (BPM), whether the modality is home (HBPM), ambulatory (ABPM), automated (AOBP) or office (OBPM), is dependent on proper technique. Knowledge, perception and practice of health professionals for BPM is crucial and has been partly studied, but a thorough review has never been reported. A scoping review of global studies was conducted to synthesize published data on this topic. METHODS: An Arksey and O'Malley methodological framework was used. Keywords were identified and extraction was completed to April 2019 using CINAHL and MEDLINE. Studies were classified as positive for knowledge, perception and practice if the majority (>50%) of reported responses were favourable, and negative otherwise. If specific results were not reported, the author's conclusions were used to classified. RESULTS: Seventy-two studies were identified: 25 HBPM, 14 ABPM, two AOBP, 40 OBPM. For knowledge, the percentage of negative studies were higher for HBPM (40%) and OBPM (68%) and lower for ABPM (14%) regarding BPM techniques. For perception, the number of negative studies were lower for HBPM (20%) and ABPM (7%) regarding usefulness of BPM methods in hypertension management. For practice, the number of negative studies were higher for HBPM (48%), ABPM (71%), OBPM (73%) and AOBP (50%) regarding implementation of hypertension guidelines. CONCLUSION: The results of this scoping review demonstrate adequate perception of BPM but suboptimal knowledge and practice. Education is still needed to improve knowledge and practice. Future efforts should focus on improving what we know and what we do when measuring BP.
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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 | 0.025 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".