Evidence map›Paper›PMID 40186180›Full record

SynthesisBMC public health2025

Text messages as a tool to improve cardiovascular disease risk factors control: a systematic review and meta-analysis of randomized clinical trials.

Ernesto Calderon Martinez, Stephin Zachariah Saji, Jonathan Victor Salazar Ore, Ajay Kumar, Angie Carolina Alonso Ramírez, Sutirtha Mohanty, Viridiana Yumiko Nakamura Ramírez, Ahmad Hammoud, Leen Nasser Shaban, Vaidarshi Abbagoni

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Observational
  4. Review
  5. Review
  6. Development of a Health Text Message System to Support Stroke Prevention: A Component of the Love Your Brain Digital Platform.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
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.

Ernesto Calderon MartinezDigital Health, Universidad Nacional Autónoma de México, Mexico City, Mexico. ernestocalderon.mtz@gmail.com.
Stephin Zachariah SajiOur Lady of Fatima University, College of Medicine, Valenzuela City, Philippines.
Jonathan Victor Salazar OreFacultad de Ciencias Médicas, Universidad de Buenos Aires, Buenos Aires, Argentina. jonathan.salazar@campus.fmed.uba.ar.
Ajay KumarIsra University Faculty of Medicine and Allied Medical Sciences, Hyderabad, Sindh, Pakistan.
Angie Carolina Alonso RamírezFacultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia.
Sutirtha MohantyGovernment Medical College Kozhikode, Kerala University of Health Sciences, Kozhikode, India.
Viridiana Yumiko Nakamura RamírezFacultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Ahmad HammoudIlia State University, Tbilisi, Georgia.
Leen Nasser ShabanIlia State University, Tbilisi, Georgia.
Vaidarshi AbbagoniSt. Vincent Medical Center, Frank H. Netter Quinnipiac University, Bridgeport, CT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiovascular diseases (CVDs) are the leading cause of global mortality, claiming 17.9 million lives annually. Major risk factors include unhealthy diets, physical inactivity, tobacco use, and excessive alcohol consumption. Text messaging interventions have the potential to improve individual risk factors and encourage healthy habits. These interventions have been shown to help manage risk factors and slow disease progression. This systematic review and meta-analysis aimed to evaluate the efficacy of text messaging interventions for the primary prevention of CVD risk factors.

methodsThis review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines. Searches were conducted on PubMed, MEDLINE, Cochrane, Scopus, Web of Science, Embase, and CINAHL using MeSH and free-text terms related to cardiovascular disease and text messaging interventions on February 12, 2024.

resultsOut of 5,748 identified articles, 22 studies met the inclusion criteria. The meta-analysis revealed that text messaging interventions significantly improved medication adherence, with a pooled effect size (Mean Difference [MD]) of 0.62 (95% CI: 0.37 to 0.86; p < 0.01; I² = 0.0%). They also significantly reduced diastolic blood pressure (MD: -2.66; 95% CI: -4.63 to -0.70; I² = 85%; p < 0.01) and systolic blood pressure (MD: -6.12; 95% CI: -10.26 to -1.97; I² = 96%; p < 0.01). However, no significant improvements were observed in BMI, LDL, HDL, total cholesterol, or HbA1c levels.

conclusionText messaging interventions effectively improve medication adherence and reduce blood pressure, making them a promising tool for CVD risk control. However, their impact on other cardiovascular risk factors is limited, highlighting the need for further research to explore long-term effects and personalized interventions for diverse populations. Integrating these digital tools into healthcare strategies could enhance CVD prevention efforts and improve cardiovascular risk factor control outcomes.

Indexed as

Cardiovascular DiseasesHeart Disease Risk FactorsText MessagingHumansRandomized Controlled Trials as TopicRisk FactorsCardiovascularRisk factorsMeta-analysisSystematic reviewText messages

Identifiers

PMID40186180
PMCPMC11971745

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.