JMIR Publications

ABSTRACT

Background:

Background:

Hypertension remains a predominant global risk factor for cardiovascular disease. Conventional follow-up models frequently fail to address the requirements for real-time monitoring and sustained intervention, whereas mobile health (mHealth) offers a transformative trajectory for chronic disease management. Despite a surge in relevant literature, the diversity of intervention modalities and the fragmented nature of existing evidence necessitate a systematic synthesis.

Objective:

Objective:

This study aimed to comprehensively evaluate the efficacy of mHealth in hypertension management through a systematic review combined with evidence mapping, identifying research gaps to provide evidence-based insights for precision nursing and future research directions.

Methods:

Methods:

A systematic search was conducted across PubMed, Web of Science, Cochrane Library, and Embase for randomized controlled trials (RCTs) involving mHealth interventions for hypertension, with the search period extending through February 2026. Literature was screened according to PICOS criteria, and methodological quality was appraised using the Cochrane Risk of Bias tool (RoB 1.0). Visual analytics, including Sankey diagrams and bubble plots, were employed to characterize the associations between intervention modalities and clinical outcomes. The study protocol was prospectively registered on the Open Science Framework (URL: https://osf.io/2vkwu).

Results:

Results:

A total of 106 publications (comprising 108 RCTs) were included. Publication volume has increased significantly since 2018, with the United States (31 papers) and China (19 papers) being the primary contributors. The intervention paradigm has evolved from rudimentary SMS reminders to a "closed-loop" management model centered on "App + Remote Monitoring," which demonstrates the most robust and consistent positive evidence for blood pressure (SBP/DBP) control and goal attainment rates. Blood pressure parameters occupied the "core evidence layer," while therapeutic adherence and disease knowledge formed the "behavioral evidence layer". Conversely, BMI, mental health, and quality of life remained in the "peripheral evidence layer," characterized by a notably higher proportion of non-significant results. Methodological quality was generally moderate-to-high with robust randomization; however, the implementation of blinding faced prevalent high risks due to the inherent nature of the interventions.

Conclusions:

Conclusion: mHealth significantly enhances hypertension management efficacy through a digital "monitoring-feedback-adjustment" loop, yet it encounters bottlenecks in achieving profound lifestyle modifications (e.g., weight management) and psychological interventions. Clinical decision-making should prioritize multicomponent interventions featuring real-time interaction. Future research should focus on long-term (>1 year) follow-up and cost-effectiveness transformation in resource-limited settings.