Evidence map›Paper›PMID 41339493›Full record

ArticleNPJ digital medicine2025

The effectiveness of eHealth-based cardiovascular disease risk communication: a systematic review and meta-analysis.

Yujia Jin, Yunjing Qiu, Qiushi Zhang, Liam P Allan, Kiran Bam, Zhiting Guo, Muideen T Olaiya, Mi Yao, Dominique A Cadilhac, Beilei Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yujia JinNursing and Health School, Zhengzhou University, Zhengzhou, Henan, China.
Yunjing QiuSchool of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, Sydney, NSW, Australia.
Qiushi ZhangNursing and Health School, Zhengzhou University, Zhengzhou, Henan, China.
Liam P AllanStroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
Kiran BamStroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
Zhiting GuoNursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Muideen T OlaiyaStroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
Mi YaoDepartment of General Practice, Peking University First Hospital, Beijing, China.
Dominique A CadilhacStroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
Beilei LinNursing and Health School, Zhengzhou University, Zhengzhou, Henan, China. linbeilei@zzu.edu.cn.

Funding

Henan Province Higher Education Institutions Young Key Teacher Program 2024GGJS013National Natural Science Foundation of China 72104221National Natural Science Foundation of China 72304005Research Projects of Colleges and Universities in Henan Province 25A320027
6 · The paper itself

Abstract

This study aimed to systematically review and meta-analyze the effectiveness of eHealth-based cardiovascular disease (CVD) risk communication and its impact on health-related outcomes. Twenty-three RCTs were included. The eHealth-based CVD risk communication showed significant improvements in controlling systolic blood pressure (P = 0.03), low-density lipoprotein (P = 0.02), physical activity (P = 0.003), smoking cessation (P = 0.004), disease awareness (P = 0.002), and quality of life (P = 0.03). No significant effects were found for other outcomes, including diastolic blood pressure, total cholesterol, and overall risk scores. These findings provide valuable insights into the potential role of eHealth-based risk communication in CVD prevention. In addition, existing risk communication interventions are multicomponent, and future research could standardize intervention components and optimize intervention elements using the Behavior Change Techniques Taxonomy and factorial designs, while developing targeted risk communication strategies for different populations to improve health outcomes.

Identifiers

PMID41339493
PMCPMC12796483

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.