Evidence mapPaperPMID 41969930Full record

ReviewInternational journal of public health2026

Moving From Representativeness Toward Transportability in an Era of Digital and Big Data.

Arnaud Chiolero

Abstract readReview
In one paragraph

Review in International journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Arnaud ChioleroPopulation Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evidence-based public health demands that study findings provide meaningful insights into improving the health of target populations, making representativeness a widely regarded hallmark of high-quality epidemiological research. However, big data and the digital health datademic are changing the way target and study populations are defined and how to ensure the external validity of study findings. What matters is assessing the degree of transportability of these findings-how well they inform about the target population. I review the gain of shifting the focus away from study representativeness and instead prioritizing the explicit assessment and reporting of transportability.

Indexed as

Big DataPublic HealthDigital HealthHumansdata scienceepidemiologyevidencepopulation healthrepresentativeness

Identifiers

PMID41969930
PMCPMC13065729

What Socratic holds

Textmetadata
LicenceCC BY
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.