Influence of physician and consumer demographics on AI-use penalties in primary care: a vignette-based study.

Moritz Reis, Jungmin Choi, Yeun Joon Kim, Yingyue Luna Luan, Pengzhao Lyu, Florian Reis

Abstract read

In one paragraph

Article in NPJ digital medicine, 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

6 authors.

Moritz ReisInstitute of Psychology, University of Wuerzburg, Wuerzburg, Germany. moritz.reis@uni-wuerzburg.de.ORCID https://orcid.org/0000-0002-1547-8109

Jungmin ChoiInstitute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-3272-1609

Yeun Joon KimInstitute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0001-9400-1386

Yingyue Luna LuanUQ Business School, The University of Queensland, Brisbane, QLD, Australia.ORCID https://orcid.org/0000-0001-5579-0597

Pengzhao LyuCambridge Judge Business School, University of Cambridge, Cambridge, Cambridge, UK.

Florian ReisInstitute of Medical Informatics, Charité - Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0009-0009-1064-9173

Funding

Faculty of humanities of the University of Wuerzburg OH_4_2025_3-4

6 · The paper itself

Abstract

We investigated how the "AI-use penalty"- physicians disclosing AI use being perceived more negatively-is affected by physician and consumer demographics in primary care settings. Participants (N = 1030) assessed fictitious family doctor advertisements varying in AI-use and demographics. Physicians stating that they use (vs. never use) AI were rated as less warm and competent, with reduced appointment willingness. Effects were stronger among younger participants but largely independent of physician demographics.

Identifiers

PMID42823464

DOI10.1038/s41746-026-03361-3

PMCPMC13631233

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.