A Qualitative Study of Patient Perspectives about Hypertension
Bibliographic record
Abstract
To understand hypertensive patients' perspectives regarding blood pressure and hypertension treatment, this qualitative study applied semistructured interviews of hypertensive patients. Participants were recruited from two hypertension clinics at the University of Alberta in Edmonton, Canada. To be eligible for inclusion, patients had to be aged 18 years or older, diagnosed with hypertension by a healthcare provider, and currently taking an antihypertensive medication. Participants were stratified in the analysis according to blood pressure control. Twenty-six patients (mean age 57; 62% female) were interviewed, of which 42% were on target and 58% were not. Three underlying themes emerged from the interviews: (a) knowledge of blood pressure relating to diagnosis and management and control of hypertension, (b) integration of hypertension management into daily routine, and (c) feelings and beliefs of wellness. None of the above themes were associated with better control. Knowledge gaps were found, which emphasize the need for further patient education and physician training. Feelings and beliefs of wellness, and not knowledge, were important factors in home assessment of blood pressure. The absence of connections between control of hypertension and the identified domains indicates that current approaches could benefit from the development of a more personalized approach for education and communication.
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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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".