Effect of a Mobile Health Intervention in the Management of Hypertension: Open-Label Cluster-Randomized Trial
Bibliographic record
Abstract
Background: Digital therapeutics represents a promising approach to support the management of hypertension. Rural regions in China face substantial challenges in hypertension prevention and management. Given the rapid growth in use of the internet and mobile technologies, particularly smartphones, we developed a user-friendly WeChat mini-program "E-controlled pressure (eKongya)" to assist village physicians in managing patients with hypertension. Objective: This trial aimed to investigate the efficacy of digital interventions for blood pressure (BP) control in patients with hypertension. Methods: This open-label cluster-randomized controlled study was conducted in 8 villages in China. Individuals with systolic BP (SBP) ≥140 mm Hg or diastolic BP (DBP) ≥90 mm Hg were recruited. Eight villages were randomly assigned in a 1:1 ratio to the digital intervention group or control group. The primary end point was the hypertension control rate at 24 weeks among the study participants. The secondary end points were the changes in mean SBP and DBP from baseline to 24 weeks. All analyses were performed using the full analysis set. Results: Between June and July 2024, a total of 95 participants were enrolled and allocated to the digital intervention group (n=48, 51%) or the control group (n=47, 49%). After 24 weeks, data were available from 87 (92%) participants, and the mean age was 63.8 (SD 9.7) years, with 48% (n=42) being female participants. The digital intervention group (25/44, 57%) had a higher percentage of participants with controlled BP compared to the control group (21/43, 49%), although this difference was not statistically significant (P=.60). Logistic regression analysis showed that the digital interventions did not significantly increase the hypertension control rate (odds ratio 0.73, 95% CI 0.31-1.69; P=.46). In the intervention group, SBP decreased from 158.0 (SD 18.4) mm Hg at baseline to 137.5 (SD 13.0) mm Hg at 24 weeks and DBP decreased from 93.8 (SD 10.3) mm Hg to 85.3 (SD 11.6) mm Hg. In the control group during that same period, SBP decreased from 161.1 (SD 18.2) mm Hg to 139.6 (SD 13.2) mm Hg, and DBP decreased from 99.2 (SD 9.2) mm Hg to 83.4 (SD 12.1) mm Hg. After adjusting for baseline SBP or DBP, the mean change from baseline to 24 weeks was comparable between the digital intervention and control groups for both SBP (between-group difference -1.6, 95% CI -7.2 to 3.9; P=.56) and DBP (between-group difference 3.3, 95% CI -1.8 to 8.5; P=.21). No major program-related safety events occurred up to 24 weeks. Conclusions: Our study demonstrated that the digital interventions increased the hypertension control rate in rural areas, although this improvement was not statistically significant. Nevertheless, providing convenient BP measurements and health education to these patients notably enhanced hypertension control rates.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".