Evidence map›Paper›PMID 41219005›Full record

ArticleBJGP open2025

Artificial intelligence in general practice in Germany: an online survey of current use, perceived benefits, barriers, and future needs.

Anne Werner, Stefanie Fischer, Markus Bleckwenn, Anne Schrimpf

Abstract read
In one paragraph

Article in BJGP open, 2025. 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

4 authors.

Anne WernerInstitute for General Practice, Faculty of Medicine, University of Leipzig, Leipzig, Germany anne.werner@medizin.uni-leipzig.de.ORCID https://orcid.org/0000-0003-0481-0919
Stefanie FischerInstitute for General Practice, Faculty of Medicine, University of Leipzig, Leipzig, Germany.
Markus BleckwennInstitute for General Practice, Faculty of Medicine, University of Leipzig, Leipzig, Germany.
Anne SchrimpfInstitute for General Practice, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly recognised as a transformative tool in health care. However, despite these prospects, the adoption of AI in primary care remains limited in Germany owing to various concerns.

aimTo investigate current AI use, perceived barriers, and training needs among GPs. It also aims to compare attitudes of current users and non-users of AI technologies. DESIGN &

settingThis was a cross-sectional study of practising GPs in the Free State of Saxony, Germany; participants received an invitation to participate in an online survey between November 2024 and January 2025.

methodIn total, 1620 GPs received an invitation and two additional reminders to complete the survey via REDCap.

resultsA total of 154 GPs completed the questionnaire, of whom

conclusionOur study underscores the need for targeted training programmes that address GPs' specific needs and concerns.

Indexed as

artificial intelligencedigital healthgeneral practitionersprimary health care

Identifiers

PMID41219005
PMCPMC12820482

What OpenQuestion holds

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LicenceCC BY
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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.