Personalized Informational Support for Patients With Hypertension: Single-Arm Pretest-Posttest Study
Bibliographic record
Abstract
Background: Informational support has been demonstrated to enhance patients' treatment adherence. However, which specific mode of informational support is more effective for patients with hypertension remains undetermined. Objective: The primary objective of this study was to conduct a feasibility exploration of personalized informational support in patients with hypertension using a single-arm pretest-posttest design. Methods: A prospective, single-center, pretest-posttest study was used to investigate the feasibility of providing an informational support intervention to patients with hypertension attending a community health facility in Chengdu, China. The intervention combined in-person follow-ups and telephone counseling. Adherence and clinical outcomes (blood pressure, ambulatory blood pressure, and laboratory tests) were measured at baseline and the postintervention time point. Patients' health behaviors were assessed at baseline and the postintervention time point using validated structured questionnaires. Descriptive statistics and effect sizes were calculated to determine clinically important changes relative to baseline. Results: Significant improvements were observed: medication adherence scores increased by 0.65 points (95% CI 0.38-0.91; P<.001). Nutrition scores increased by 1.31 points (95% CI 0.53-2.09; P<.001), interpersonal relationship scores increased by 1.17 points (95% CI 1.03-2.02; P=.007), health responsibility scores increased by 2.42 points (95% CI 0.33-3.80; P=.001), and the total Health-Promoting Lifestyle Profile II-Revised score significantly increased by 6.81 points (95% CI 3.01-10.61; P=.001). Nighttime systolic blood pressure decreased significantly by 5.07 mm Hg (95% CI -8.12 to -2.01; P=.001), and nighttime diastolic blood pressure decreased significantly by 3.39 mm Hg (95% CI -5.12 to -1.67; P<.001). Conclusions: This feasibility study found that a structured informational support intervention was well accepted (93/100, 93% retention) and was associated with preliminary improvements in medication adherence and nocturnal blood pressure. These findings suggest potential benefits and support the need for a definitive randomized controlled trial to establish efficacy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".