Evidence map›Paper›PMID 41832289›Full record

ArticleNPJ digital medicine2026

AI literacy mediates AI assisted diagnosis participation and critical thinking among medical students under supervision.

Yang Xin, Deng Yan, Luo Shuren, Luo Minyang, Lu Liuheng

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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Yang XinGuangxi Orthopedic Hospital, Nanning, China.
Deng YanGuangxi Medical University, Nanning, China.
Luo ShurenHealth Commission of Guangxi Zhuang Autonomous Region, Nanning, China.
Luo MinyangThe Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Lu LiuhengGuangxi Orthopedic Hospital, Nanning, China. luliuheng809@163.com.

Funding

2021 Guangxi Philosophy and Social Science Planning Research Project No. 21FKS0282022 Guangxi Higher Education Undergraduate Teaching Reform Project No. 2022JGZ155Health and Emergency Skills Training Center of Guangxi No. HESTCG202304
6 · The paper itself

Abstract

Concerns that AI tools may erode diagnostic reasoning contrast with claims that AI can foster higher-order thinking. This longitudinal study followed 372 medical students across 12 months of supervised rotations using an AI-assisted diagnosis system. AI-assisted diagnosis participation, AI literacy and medical critical thinking were assessed at baseline, 6 months and 12 months. Cross-lagged panel models examined prospective associations, statistical mediation by AI literacy and moderation by prior technological experience and learning goal orientation. Higher participation was associated with increases in AI literacy and critical thinking, and AI literacy statistically mediated the participation-to-critical thinking association. Indirect effects were stronger among students with greater technological experience and mastery-oriented goals and weaker among performance-oriented peers. Findings indicate that, within supervised clinical training, engagement with AI systems is associated with critical thinking development partly through enhanced AI literacy, supporting AI tools as educational resources under faculty guidance.

Identifiers

PMID41832289
PMCPMC13133384

What OpenQuestion holds

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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 OpenQuestion graph.