Evidence map›Paper›PMID 41285603›Full record

ArticleAnnals of family medicine2025

Artificial Intelligence Readiness Among Young Family Doctors in Europe.

Seyma Handan Akyon, Ikbal Humay Arman, Gülşah Onur, Rita Abecasis, Pemra Cobek Unalan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of family medicine, 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

5 authors.

Seyma Handan AkyonSincan Education and Research Hospital, Ankara, Türkiye drseymahandan@gmail.com.
Ikbal Humay ArmanIstanbul Medipol University, School of Medicine, Department of Family Medicine, Istanbul, Türkiye.
Gülşah OnurHacettepe University, Faculty of Medicine, Department of Family Medicine, Ankara, Türkiye.
Rita AbecasisPrimary Health Care Area, Unidade de Saúde Familiar da Baixa, Unidade Local de Saúde São José, Lisbon, Portugal.
Pemra Cobek UnalanMarmara University, School of Medicine, Department of Family Medicine, Istanbul, Türkiye, The European General Practice Research Network (EGPRN).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to assess family doctors' readiness toward artificial intelligence (AI) in health care. We conducted a descriptive study using snowball sampling, targeting young family doctors. We administered a web-based questionnaire incorporating the validated medical AI readiness scale (MAIRS) via digital networks. A total of 134 participants from 20 European countries were included. MAIRS scores reflected variable readiness levels, with a median total of 69 of 110. Participants' readiness for AI increased significantly with their knowledge of its current applications and knowledge of AI usage in health care (

Indexed as

Artificial IntelligenceAttitude of Health PersonnelPhysicians, FamilyAdultEuropeFemaleHumansMalePrimary Health CareSurveys and Questionnairesartificial intelligencedigital technologyhealth servicesprimary care

Identifiers

PMID41285603
PMCPMC12751281

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.