A Systematic Review of Patient Self‐Reported Barriers of Adherence to Antihypertensive Medications Using the World Health Organization Multidimensional Adherence Model
Bibliographic record
Abstract
Multiple barriers can influence adherence to antihypertensive medications. The aim of this systematic review was to determine what adherence barriers were included in each instrument and to describe the psychometric properties of the identified surveys. Barriers were characterized using the World Health Organization (WHO) Multidimensional Adherence Model with patient, condition, therapy, socioeconomic, and health care system/team-related barriers. Five databases (Medline, Embase, Health and Psychological Instruments, CINHAL, and International Pharmaceutical Abstracts [IPA]) were searched from 1980 to September 2011. Our search identified 1712 citations; 74 articles met inclusion criteria and 51 unique surveys were identified. The Morisky Medication Adherence Scale was the most commonly used survey. Only 20 surveys (39%) have established reliability and validity evidence. According to the WHO Adherence Model domains, patient-related barriers were most commonly addressed, while condition, therapy, and socioeconomic barriers were underrepresented. The complexity of adherence behavior requires robust self-report measurements and the inclusion of barriers relevant to each unique patient population and intervention.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".