Empowering citizens as frontline screeners: a framework with blended learning for cardiovascular risk assessment.

Roxane Brouwers, Evangelos Ntalianis, Ella Wils, Everton Santana, Tatiana Kuznetsova, Nicholas Cauwenberghs

Abstract read

In one paragraph

Article in Scientific reports, 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

6 authors.

Roxane BrouwersResearch Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, KU Leuven, University of Leuven, Kapucijnenvoer 7 - Block H, 3000, Leuven, Belgium.

Evangelos NtalianisResearch Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, KU Leuven, University of Leuven, Kapucijnenvoer 7 - Block H, 3000, Leuven, Belgium.

Ella WilsResearch Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, KU Leuven, University of Leuven, Kapucijnenvoer 7 - Block H, 3000, Leuven, Belgium.

Everton SantanaResearch Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, KU Leuven, University of Leuven, Kapucijnenvoer 7 - Block H, 3000, Leuven, Belgium.

Tatiana KuznetsovaResearch Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, KU Leuven, University of Leuven, Kapucijnenvoer 7 - Block H, 3000, Leuven, Belgium.

Nicholas CauwenberghsResearch Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, KU Leuven, University of Leuven, Kapucijnenvoer 7 - Block H, 3000, Leuven, Belgium. nicholas.cauwenberghs@kuleuven.be.

Funding

Fonds Wetenschappelijk Onderzoek G0C5319NHORIZON EUROPE European Research Council grant agreement 101058677Onderzoeksraad, KU Leuven C24M/21/025Onderzoeksraad, KU Leuven DB/22/010/BM

6 · The paper itself

Abstract

Population-wide screening for cardiovascular risk factors (CVRF) is challenging, given the shortage of healthcare professionals. Laypeople may aid in CVRF screening. We therefore investigated a blended training programme to conduct a basic CVRF assessment, including point-of-care testing (PoC). We conducted a pre-experimental study with one-group pretest–posttest design with repeated measures between September and December 2024. Fourteen laypeople completed a training on measuring body mass index (BMI), blood pressure and PoC testing of blood glucose and lipids. Each tester conducted screenings on five different individuals, using a mobile application for guidance. We evaluated their practical skills and benchmarked their performance to experts. Feasibility was 100% for BMI and blood pressure assessment. From the first to the fifth screening, feasibility for blood glucose rose from 92.9 to 100% and for lipids from 78.6 to 92.9%. Average test time dropped from 20.7 to 16.9 min (P = 0.011), approaching the 16.6 min of the experts (P = 0.49). Practical skills improved from 88.8% at the first to 97.2% at the fifth screening (P = 0.004). Agreement with experts was excellent for BMI (mean relative bias: − 0.5%) and blood pressure (e.g. systolic: +2.9%), reasonable for blood glucose (− 0.1%), total cholesterol (+ 1.3%) and HDL cholesterol (+ 9.7%), but poor for triglycerides (− 16.8%). Self-rated confidence and skilfulness increased by the final session. In conclusion, laypeople reliably assessed CVRF with blended training, intuitive equipment and a mobile screening assistant. Within five sessions, agreement with experts was acceptable for all measurements but PoC-derived triglycerides. Future studies should assess the real-world scalability of citizen-conducted screenings.

Indexed as

Cardiovascular DiseasesMass ScreeningAdultBlood GlucoseBlood PressureBody Mass IndexFemaleHeart Disease Risk FactorsHumansLipidsMaleMiddle AgedPoint-of-Care TestingRisk AssessmentBlood GlucoseLipidsCardiovascular risk factorsCitizen collected dataCitizen engagementScreening

Identifiers

PMID41361568

DOI10.1038/s41598-025-31452-w

PMCPMC12796428

What OpenQuestion 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 OpenQuestion graph.