Patient and Healthcare Provider Barriers to Hypertension Awareness, Treatment and Follow Up: A Systematic Review and Meta-Analysis of Qualitative and Quantitative Studies
Bibliographic record
Abstract
BACKGROUND: Although the importance of detecting, treating, and controlling hypertension has been recognized for decades, the majority of patients with hypertension remain uncontrolled. The path from evidence to practice contains many potential barriers, but their role has not been reviewed systematically. This review aimed to synthesize and identify important barriers to hypertension control as reported by patients and healthcare providers. METHODS: Electronic databases MEDLINE, EMBASE and Global Health were searched systematically up to February 2013. Two reviewers independently selected eligible studies. Two reviewers categorized barriers based on a theoretical framework of behavior change. The theoretical framework suggests that a change in behavior requires a strong commitment to change [intention], the necessary skills and abilities to adopt the behavior [capability], and an absence of health system and support constraints. FINDINGS: Twenty-five qualitative studies and 44 quantitative studies met the inclusion criteria. In qualitative studies, health system barriers were most commonly discussed in studies of patients and health care providers. Quantitative studies identified disagreement with clinical recommendations as the most common barrier among health care providers. Quantitative studies of patients yielded different results: lack of knowledge was the most common barrier to hypertension awareness. Stress, anxiety and depression were most commonly reported as barriers that hindered or delayed adoption of a healthier lifestyle. In terms of hypertension treatment adherence, patients mostly reported forgetting to take their medication. Finally, priority setting barriers were most commonly reported by patients in terms of following up with their health care providers. CONCLUSIONS: This review identified a wide range of barriers facing patients and health care providers pursuing hypertension control, indicating the need for targeted multi-faceted interventions. More methodologically rigorous studies that encompass the range of barriers and that include low- and middle-income countries are required in order to inform policies to improve hypertension control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.069 | 0.177 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.022 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".