Evidence map›Paper›PMID 42907110›Full record

ArticleBMJ open2026

Glow Up: a single-centre observational study protocol to develop digital biomarkers for prediabetes screening and digital phenotyping.

Victoria Brügger, Magdalena Fuchs, Qiuhan Jin, Benjamin Wirth, Stefan Bilz, Michael Brändle, Tobias Kowatsch, Mia Jovanova

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2026. 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

8 authors.

Victoria BrüggerDigital Health Interventions, School of Medicine, University of St Gallen, St. Gallen, Switzerland victoria.bruegger@unisg.ch.ORCID http://orcid.org/0000-0002-8294-2370
Magdalena FuchsCentre for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zürich, Zürich, Switzerland.ORCID http://orcid.org/0009-0003-5621-1560
Qiuhan JinDigital Health Interventions, School of Medicine, University of St Gallen, St. Gallen, Switzerland.
Benjamin WirthDivision of Endocrinology and Diabetes, Kantonsspital St.Gallen, HOCH Health Ostschweiz, St. Gallen, Switzerland.
Stefan BilzDivision of Endocrinology and Diabetes, Kantonsspital St.Gallen, HOCH Health Ostschweiz, St. Gallen, Switzerland.
Michael BrändleDivision of Endocrinology and Diabetes, Kantonsspital St.Gallen, HOCH Health Ostschweiz, St. Gallen, Switzerland.
Tobias KowatschDigital Health Interventions, School of Medicine, University of St Gallen, St. Gallen, Switzerland.ORCID http://orcid.org/0000-0001-5939-4145
Mia JovanovaDigital Health Interventions, School of Medicine, University of St Gallen, St. Gallen, Switzerland.ORCID http://orcid.org/0000-0003-3634-4449

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

BehaviorDiabetes Mellitus, Type 2Digital TechnologyMachine LearningPREVENTIVE MEDICINEWearable Devices

Identifiers

PMID42907110
PMCPMC13711582

What OpenQuestion holds

Textmetadata
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.